climate change denial research paper

Climate Change Denial and Corporate Environmental Responsibility

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• Published: 15 March 2024

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• Mansoor Afzali   ORCID: orcid.org/0000-0001-6877-3139 1 ,
• Gonul Colak   ORCID: orcid.org/0000-0003-4407-176X 2 , 4 , 5 &
• Sami Vähämaa   ORCID: orcid.org/0000-0003-2957-4780 3  

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This paper examines whether corporate environmental responsibility is influenced by regional differences in climate change denial. While there is an overwhelming consensus among scientists that climate change is happening, recent surveys still indicate widespread climate change denial across societies. Given that corporate activity causing climate change is fundamentally rooted in individual beliefs and societal institutions, we examine whether local perceptions about climate change matter for firms’ engagement in environmental responsibility. We use climate change perception surveys conducted in the U.S. to compute a novel measure of climate change denial for each U.S. county. We find that firms located in counties with higher levels of climate change denial have weaker environmental performance ratings, are more likely to commit environmental violations, and impose greater environmental costs on society. Regional differences in religiosity, social capital, political leaning, or county-level demographic characteristics cannot explain these results. Furthermore, we document that strong corporate governance mechanisms and corporate culture moderate the negative relationship between climate change denial and corporate environmental responsibility. Overall, our findings offer new insights into how local beliefs and perceptions about climate change may influence firm-level sustainability practices.

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Introduction

Climate scientists unanimously agree that human-caused climate change is an existing threat to our planet (for reviews, see Cook et al., 2013 , 2016 ). Nevertheless, recent survey evidence suggests that climate change denial is still widespread in societies, and nearly 30 percent of American adults, for instance, do not believe that climate change is happening as suggested by scientific research (Tyson et al., 2021 ). Given that corporate decisions and activities that inflict climate change and global warming are likely to be influenced by societal views and values, widespread climate change denial in the local society can create severe negative externalities for sustainable development and initiatives related to environmental responsibility. In this paper, we aim to empirically examine the impact of climate change denial on corporate environmental responsibility.

Building on the institutional theory, previous studies have acknowledged the role of local communities and local socio-political norms in influencing corporate decisions and outcomes (see, e.g., Powell & DiMaggio, 1991 ; Campbell, 2007 ; Marquis & Battilana, 2009 ; Caprar & Neville, 2012 ; Burdon & Sorour, 2020 ). A vast body of research has documented that attributes related to firms’ operating environment and geographical location, such as civic engagement, local culture, social capital and trust, religiosity, and political leanings, are reflected in firms’ strategic decisions, financial policies, governance mechanisms, and various other corporate outcomes (e.g., Hilary & Hui, 2009 ; El Ghoul et al., 2012 ; McGuire et al., 2012 ; Callen & Fang, 2015 ; Hasan et al., 2017 ; Hoi et al., 2019 ; Hasan et al., 2020 ; Colak et al., 2021 ; Afzali et al., 2022 ; Gupta & Minnick, 2022 ). Most closely related to our study, Di Giuli and Kostovetsky ( 2014 ), Du et al. ( 2014 ), Jha and Cox ( 2015 ), Cui et al. ( 2015 ), Attig and Brockman ( 2017 ), Cahan et al. ( 2017 ), Hoi et al. ( 2018 ), Zolotoy et al. ( 2019 ), and Ucar and Staer ( 2020 ) have documented that local norms and beliefs permeate engagement in corporate social responsibility (CSR) and environmental responsibility. We intend to extend the existing literature by investigating whether local beliefs and perceptions about climate change influence corporate environmental performance.

Given that corporate policies and decisions related to environmental threats and opportunities boil down to individual beliefs and societal institutions (Hoffman, 2010 ), it is likely that local perceptions regarding climate change influence such decisions and permeate the concomitant firm-level environmental outcomes. The institutional theory predicts that organizations seek the need to “fit” their social environment through their activities, and local social norms and values may discipline firms to enact certain policies and decisions (Kitzmueller & Shimshack, 2012 ; Scott, 2001 ). Following Hoepner et al. ( 2021 ), we rely on the institutional theory as an analytical framework in our study.

The formal rules, laws, and regulations—often linked to the regulative pillar of the institutional theory—form the foundational framework for guiding organizational behavior. Prior research documents country-specific regulation as a key determinant of the emergence of socially responsible investing (e.g., Sandberg et al., 2009 ; Scholtens & Sievänen, 2013 ). In the context of climate change and environmental responsibility, in regions where climate change denial is more prevalent, there may be weaker support for stringent environmental regulations or resistance to implementing new environmental policies. As a result, firms operating in these regions may face fewer external pressures to adopt sustainable practices, which can lead to weaker corporate environmental performance.

Similarly, social norms and values constitute another important pillar of the institutional theory and influence the expectations and behavior of individuals as well as organizations. In regions where climate change denial is widespread, there might be a cultural acceptance or even endorsement of environmentally harmful practices. Experimental evidence, for instance, shows that climate change denialism at the individual level is associated with self-interested choices at the expense of environmental harm (Berger & Wyss, 2021 ). This phenomenon could create a social norm that downplays the significance of climate change and devalues corporate environmental responsibility. Furthermore, in regions with higher levels of climate change denialism, corporate executives, employees, investors, and decision-makers may also hold more skeptical views regarding the importance of climate change and its impact on their business operations. These cognitive biases can influence strategic decisions, investment choices, and resource allocation, leading to a reduced focus on corporate environmental responsibility. Collectively, the different elements of institutional theory suggest that firms may be less likely to take measures that reduce their environmental impact in communities where local perceptions about climate change are more incredulous and skeptical. Therefore, we hypothesize that corporate environmental performance is negatively associated with the level of climate change denial in the firms’ social environment.

Our empirical analysis uses data on publicly traded U.S. firms to test the hypothesis that climate change denial influences corporate environmental responsibility. Specifically, we utilize a novel measure of climate change denial for each county in the U.S. estimated from survey data collected as part of the Climate Change in the American Mind project (see, Leiserowitz et al., 2013 ). The climate change perception survey comprises several questions that measure public opinion on climate change beliefs, risk perceptions, and policy support. Regarding “beliefs,” survey respondents are asked, for instance, whether climate change is happening and whether humans are causing climate change. Concerning “risk perceptions,” the respondents are asked whether they are worried about climate change and whether climate change will harm people in the U.S. Finally, the survey questions related to “policy support” aim to measure support for regulating carbon dioxide emissions and imposing a carbon tax on fossil fuel companies. Based on the survey responses, we construct a single county-level measure of climate change denial using principal component analysis. We employ the Environmental (E) pillar score of the MSCI’s environmental, social, and governance (ESG) ratings to measure firm-level environmental responsibility. The E score encompasses firm-level policies, outcomes, and risks related to climate change, natural resource use, waste management, and carbon emissions. In addition to the MSCI E score, we use five different E score subcomponents, Refinitiv’s Environmental pillar score, federal environmental compliance violations, and environmental costs as alternative measures to gauge environmental responsibility.

Consistent with our research hypothesis, we document that corporate environmental responsibility is negatively influenced by climate change denial. Specifically, our empirical findings demonstrate that firms located in counties with higher levels of climate change denial have weaker environmental performance ratings after controlling for firm characteristics and various county-level attributes such as social capital, religiosity, and political leaning. In terms of economic magnitude, our estimates suggest that a one standard deviation increase in local climate change denial is associated with an almost 5 percent decrease in the firms’ environmental scores. Our results also indicate that firms headquartered in high climate change denial counties are more likely to commit federal environmental compliance violations and impose more environmental costs on society.

We perform several additional tests to mitigate endogeneity concerns and rule out alternative explanations. First, we use instrumental variable regressions and entropy balancing to address endogeneity biases and facilitate causal inferences. Regardless of the approach, our tests provide support for the hypothesis that corporate environmental responsibility is negatively influenced by local climate change denial. We further utilize corporate headquarters relocations as a quasi-natural experiment to assess the causal linkage between local climate change perceptions and environmental performance. The results suggest that environmental performance decreases after a firm relocates its corporate headquarters to a county with a higher level of climate change denial.

We then proceed by investigating whether corporate governance practices and corporate culture influence the negative linkage between climate change denial and corporate environmental responsibility. As documented in the prior literature, effective governance mechanisms and corporate culture may promote ethical behavior and engagement in CSR (e.g., Chen et al., 1997 ; Jo & Harjoto, 2011 , 2012 ; Biggerstaff et al., 2015 ; Davidson et al., 2015 ; Baselga-Pascual et al., 2018 ; Chen et al., 2020 ; Döring et al., 2023 ; Drobetz et al., 2023 ). Our empirical findings suggest that the negative relationship between corporate environmental responsibility and local climate change denial is moderated by strong governance and culture.

To the best of our knowledge, this paper is the first to examine the effects of climate change denialism on corporate environmental responsibility as measured by various environmental performance indicators, environmental compliance violations, and the environmental costs firms impose on society. A growing body of research suggests that local socio-political norms and beliefs may influence firm-level CSR practices and environmental performance (e.g., Attig & Brockman, 2017 ; Cahan et al., 2017 ; Cui et al., 2015 ; Di Giuli & Kostovetsky, 2014 ; Hoi et al., 2018 ; Jha & Cox, 2015 ; Ucar & Staer, 2020 ). Closely related to but distinct from our study, Zhang et al. ( 2023 ) document that county-level social norms regarding climate change may influence corporate cash holdings, while the findings of Huang and Lin ( 2022 ) suggest that local climate risk perceptions are associated with firms’ CSR policies. Similarly, Baldauf et al. ( 2020 ) find that properties expected to be underwater in areas where residents believe in climate change sell at lower prices than houses in areas in which climate change denialism is more prevalent, suggesting that real estate prices are influenced by differing beliefs about long-term climate risks.

By utilizing a novel measure of climate change denial and employing rigorous methodologies to reduce endogeneity concerns, we contribute to the existing literature by documenting that corporate environmental responsibility is negatively influenced by climate change denialism in the surrounding society. In doing so, our study fills a gap in the understanding of the interplay between local climate change perceptions and corporate behavior, and moreover, of how this linkage is affected by the strength and efficacy of corporate governance mechanisms and corporate culture. Our results also underline the importance of societal beliefs in shaping corporate actions and emphasize the need for a multi-faceted approach to address environmental challenges. Given these findings, we hope to spur further research in this area and advocate policymakers and corporate leaders to consider the broader societal context in their efforts towards sustainability.

The remainder of this paper proceeds as follows. The next section introduces the theoretical framework and presents our research hypothesis. The third section describes the data and the variables and presents our empirical setup. Our empirical findings on the influence of local climate change denial on corporate environmental performance are presented and discussed in the fourth section. In the fifth section, we discuss the implications of our results from corporate, public policy, and ethical perspectives. Finally, the last section provides concluding remarks.

Theoretical Framework and Hypothesis Development

Recent studies demonstrate that the community is a salient stakeholder with powerful influence over corporate decisions and outcomes (for a review, see Habib et al., 2023 ). Community-level civic norms and social capital, for instance, mitigate agency problems related to managerial opportunism and compensation (Gupta & Minnick, 2022 ; Hoi et al., 2019 ) and positively influence managers’ use of resources (Gao et al., 2021 ). More importantly, such social norms may also pressure firms to behave more responsibly by engaging in positive CSR practices that benefit stakeholders and by curbing negative CSR activities that harm stakeholders (e.g., Attig & Brockman, 2017 ; Cahan et al., 2017 ; Hoi et al., 2018 ; Jha & Cox, 2015 ; Ucar & Staer, 2020 ).

In our setting, the institutional theory (see e.g., Meyer and Rowan, 1977 ; North, 1990 ; Scott, 2001 ) provides a coherent theoretical framework to understand how local perception regarding climate change may influence firms’ engagement in environmental responsibility. Prior research draws on institutional theory to emphasize the role of local communities in influencing corporate decisions and outcomes. According to Scott ( 2001 ) and Marquis and Battilana ( 2009 ), local communities can influence organizational processes through regulative, social-normative, and cultural-cognitive influences. Communities can enact rules, review others’ compliance with those rules, and establish mechanisms that punish deviance from such rules (Scott, 2001 ). In his seminal study, Carroll ( 1991 ) argues that CSR should be framed in a way that encompasses the entire range of business responsibilities, including economic, legal, ethical, and philanthropic considerations. Carroll ( 1991 ) further contends that ethical responsibilities stem from standards, norms, and expectations of what society deems fair and just. Such norms can also be a driving force behind regulatory reforms that guide ethical responsibility. We use the institutional theory as an analytical framework to illustrate how local climate change perceptions may potentially influence local firms’ environmental responsibility. Several prior studies rely on institutional theory to derive conceptual frameworks for a comparative understanding of corporate social responsibility (e.g., Campbell, 2007 ; Matten & Moon, 2008 ).

While our theorization heavily relies on the different pillars of the institutional theory, we are also cognizant of the overlap between the institutional theory, legitimacy theory, and stakeholder theory in explaining social and environmental responsibility (Chen & Roberts, 2010 ). The legitimacy theory, developed by Dowling and Pfeffer ( 1975 ), suggests that firms seek to ensure that they are perceived as operating within the bounds and norms of their respective societies or environment. This theory has been widely used to analyze corporate behavior, especially in the context of corporate social and environmental sustainability. According to the theory, organizations are more likely to engage in socially responsible behavior, such as investing in green technologies or fair labor practices, if they believe that such behavior will enhance their legitimacy in the eyes of key stakeholders (Bebbington et al., 2008 ; Magness, 2006 ). In the context of our study, firms located in areas with higher levels of climate change denial may feel less pressure to engage in environmentally responsible behaviors due to the lower perceived need for legitimacy obtained through climate actions.

Similarly, our analysis can also be motivated by the stakeholder theory which posits that instead of focusing solely on maximizing shareholder value, companies also need to consider how they can create value for their broader set of stakeholders, where stakeholders are defined as anyone who can affect or is affected by the actions, decisions, policies, practices, or goals of the organization (Freeman, 1984 ). A vast body of literature has adopted the stakeholder theory to study the antecedents of CSR practices (Herremans et al., 2016 ; Yang & Rivers, 2009 ). In the context of environmental responsibility, Kassinis and Vafeas ( 2006 ) use stakeholder theory to find that several stakeholder pressures correspond to expected (dis)engagement in environmental responsibility. The stakeholder theory predicts that firms located in areas with high climate change denial may be responding to the attitudes and beliefs of important local stakeholders. Because these firms perceive less demand or value from these stakeholders for environmental responsibility, they may be less likely to invest in environmentally sustainable practices.

The institutional theory is particularly expedient for our study as it allows for a more granular understanding of the complex influences shaping corporate environmental responsibility in the face of prevalent climate change denial in the vicinity of the firm’s headquarters. Whereas the legitimacy theory could explain firms’ behavior as a response to the perceived need to conform to societal expectations, and the stakeholder theory may help to understand the diverse pressures from different groups, the institutional theory provides a more comprehensive view of the institutional landscape. As we illustrate in the following, different elements within institutional theory can influence firms’ (dis)engagement in environmentally responsible behavior, allowing for a more nuanced exploration of their multifaceted impacts on firms’ environmental responsibilities. In contrast, the legitimacy theory does not specify how alignment with societal values can be achieved (Chen & Roberts, 2010 ) and the stakeholder theory, in turn, is more pertained to the relationships and interactions between organizations and their stakeholders, which is not the primary focus of our study.

An important aspect of the institutional theory is how regulative institutions, which encompass laws, rules, and sanctions, play a significant role in shaping corporate behavior. The degree of legal mandates in the U.S. largely varies across states based on the interpretation and implementation of the legislation. Such regional variation in implementation is shown, for instance, in the advancement of female executives and the diffusion of maternity-leave policies (Guthrie & Roth, 1999a , 1999b ). As documented by Hamilton and Keim ( 2009 ) and Howe et al. ( 2015 ), the perceptions and beliefs regarding climate change vary considerably across the different geographical areas of the U.S. Given that the public perception of climate change largely shapes support or opposition to climate policies (Leiserowitz, 2005 ), it can be argued that different communities are likely to respond differently to climate change risks. Footnote 1 Local communities where perceptions about climate change are more skeptical are unlikely to advocate for regulations that curb local firms’ detrimental environmental impact. Regulatory and political institutions may favor climate change denying narratives, reducing the pressure on firms to adopt environmentally responsible practices.

From a social-normative perspective of the institutional theory, local norms and values serve as a platform for firms’ social engagement (Marquis et al., 2007 ). Campbell ( 2007 ) proposes that firms will be more likely to behave in socially responsible ways if local institutions such as nongovernmental and social movement organizations monitor their behavior effectively. In the absence of such norms and strong institutions to monitor deviance from norms, local firms are more likely to behave socially irresponsibly. Furthermore, firm-level decisions related to environmental threats and opportunities may boil down to individual beliefs and societal institutions (Hoffman, 2010 ). At the individual-level, recent experimental research finds that individuals denying the existence of climate change are more likely to make self-interested decisions that can harm the environment (Berger & Wyss, 2021 ). When local perceptions regarding climate change are more incredulous and skeptical, local socio-political norms are unlikely to play an effective role in monitoring and influencing environmentally responsible corporate behavior. Moreover, managers and employees in high climate change denial regions are likely to share local norms and may therefore be more likely to make myopic decisions causing environmental harm. Put differently, firms are less likely to take measures that reduce their environmental impact when the local demand for better environmental performance is low or nonexistent.

Furthermore, when climate change denial is deeply ingrained in the local culture, firms may not only perceive environmental responsibility as less necessary or beneficial, but they may also actively resist adopting environmentally responsible practices due to a perceived misalignment with the prevailing cultural norms. This assertion aligns with the recent findings of Hoepner et al. ( 2021 ) who document that asset owners from social backgrounds that are more culturally aligned with the values represented by the responsible investing movement are more likely to sign the United Nations Principles of Responsible Investing (PRI). However, these implications are not limited to investment choices alone. Hoepner et al. ( 2021 ) also document that corporate cultures that are harmonious with the principles of responsible investing might foster increased receptivity and commitment to sustainable practices. This implies that cultural influences play a substantial role in shaping corporate environmental responsibility by reinforcing or undermining local values associated with environmental sustainability. Collectively, these arguments lead to the following hypothesis:

Corporate environmental responsibility is negatively influenced by the pervasiveness of climate change denial in the local society.

We proceed by considering the potential roles of corporate governance mechanisms and corporate culture in influencing the linkage between local climate change denial and corporate environmental responsibility. Considerable empirical evidence suggests that both internal and external corporate governance mechanisms affect the firm’s engagement in CSR activities. For instance, Jo and Harjoto ( 2011 , 2012 ) study several internal and external governance mechanisms and conclude that effective monitoring and oversight by the board of directors and external monitors such as institutional investors and financial analysts is positively associated with CSR engagement. The role of institutional ownership in influencing CSR has also been studied extensively. Chen et al. ( 2020 ), for instance, document that exogenous increases in institutional ownership are positively associated with CSR performance. In a similar vein, Dyck et al. ( 2019 ) use an international setting to show that institutional investors coming from countries with stronger environmental and social norms are the primary drivers of the positive association between institutional ownership and CSR engagement. Recent studies by Döring et al. ( 2023 ) and Drobetz et al. ( 2023 ) suggest that institutional investors and their legal origin and investment horizon matter for corporate greenhouse gas emissions disclosure and environmental costs.

In a context where climate change denialism is prevalent, strong corporate governance mechanisms can mitigate the potential negative influence of local climate change denial on environmental performance through strategic commitment to CSR initiatives. Institutional shareholders, particularly those inclined towards responsible investing and sustainability, and local climate deniers may not only hold divergent beliefs about climate change but also different underlying motivations and perceptions regarding the role of corporate environmental responsibility. Institutional shareholders may be more influenced by global environmental norms and the potential financial implications of climate risks whereas local climate deniers are likely to be influenced by local cultural norms and beliefs. Therefore, the engagement of institutional shareholders may also counterbalance the adverse effects of local climate change denial on corporate environmental initiatives. Building on these arguments, we posit the following hypothesis:

The negative association between climate change denial and corporate environmental responsibility is moderated by strong internal and external corporate governance mechanisms.

We further presume that corporate culture may also influence the linkage between climate change denialism and corporate environmental responsibility. Corporate culture can be considered as an informal institution that comprises firmly held values and norms within an organization (O’Reilly & Chatman, 1996 ). It is represented by values and norms that are widely-held and endorsed by the members of an organization, facilitating social control (Sørensen, 2002 ). The strength of corporate culture has been empirically linked to firm performance, efficiency, and earnings comparability (Afzali, 2023 ; Guiso et al., 2015 ; Li et al., 2021b ). The culture-performance link is particularly salient during economic downturns (Li et al., 2021a ). A strong corporate culture, especially one that values integrity and transparency, may discourage climate change denial and promote environmental responsibility. Such a culture is likely to foster a sense of accountability and ethical behavior among its members, leading to more responsible environmental practices. Furthermore, climate change and the firm’s engagement in environmentally responsible activities are ethical issues (Bridge, 2022 ; DesJardins, 1998 ; Markowitz, 2012 ) and a strong corporate culture that values integrity, transparency, accountability, and cooperation is a fundamental antecedent to ethical decision-making (Chen et al., 1997 ). Consequently, we posit the following hypothesis:

The negative association between climate change denial and corporate environmental responsibility is less prevalent in firms with stronger corporate cultures.

Data and Methodology

We test the hypothesis that climate change denial influences corporate environmental responsibility ( H1 ) using data on publicly traded U.S. firms over the period 2012–2020. The data are collected from the following sources: (i) climate change denial data are obtained from Yale Program on Climate Change Communication, (ii) the data on firms’ environmental performance are from MSCI and Refinitiv, (iii) the data on firms’ environmental compliance violations are taken from the Violation Tracker database compiled by the Good Jobs First organization, (iv) the data on firm-level environmental costs are obtained from Freiberg et al. ( 2022 ), (v) firm headquarters locations are identified through Securities and Exchange Commission (SEC) filings, (vi) the financial statement and balance sheet data are obtained from Compustat, (vii) the county-level data on regional demographic characteristics are collected from U.S. Census Bureau, and (viii) other county-level characteristics are obtained from the Association of Religion Data Archives, the Northeast Regional Center for Rural Development, the MIT Election Data, and the National Centers for Environmental Information. To test the moderating role of internal and external corporate governance mechanisms ( H2 ), we collect data on board characteristics from BoardEx and on institutional ownership from Thomson Reuters 13-F Institutional Holdings. Finally, to examine the role of corporate culture ( H3 ), we use data on corporate culture obtained from Kai Li’s data library. Footnote 2

The initial sample consists of all U.S. firms included in Compustat. After excluding American Depository Receipts (ADRs), Footnote 3 limited partnerships, holding companies, and firms with missing data for environmental performance, climate change denial, firm characteristics, and county-level characteristics, we are left with a sample of 2746 individual firms and an unbalanced panel of 15,570 firm-year observations over the period 2012–2020.

Climate Change Denial

National-level climate change perception surveys in the U.S. have existed for over a decade. Footnote 4 However, such broad, national-level surveys do not capture the large variations in the beliefs and opinions across the different geographical areas of the U.S. To overcome this limitation, Howe et al. ( 2015 ) construct local estimates of climate change perception at the state, county, and congressional district level using national survey data collected as part of the Climate Change in the American Mind project (see, Leiserowitz et al., 2013 ). These estimates are compiled as part of the research project led by the Yale Program on Climate Change Communication and the George Mason University Center for Climate Change Communication in order to understand how climate-related opinions differ at the local levels and to provide means for policymakers and other stakeholders to better address climate change (see e.g., Leiserowitz et al., 2022 ).

To derive the local estimates across the U.S., Howe et al. ( 2015 ) utilize a multilevel regression and poststratification (MRP) approach in which they first model individual beliefs, opinions, and policy support as a function of demographic, geographic, and temporal effects, and then use the first-stage coefficients to derive weighted estimates for each geographic area. Unlike disaggregation which relies on pooling the responses of all respondents in each geographic region, the MRP approach produces more reliable estimates and reduces uncertainties for areas with a smaller population (Lax & Phillips, 2009 ). Thus, this approach expands the national-level estimates of climate change opinions to state, county, and congressional district levels with great accuracy. However, to further validate the estimates, internal cross-validations and external validations have been conducted through multiple independent surveys across different geographic areas with identical questions to the original national-level survey. The estimates obtained from these surveys are markedly similar to those produced by the MRP approach, which further reduces concerns related to measurement error (Howe et al., 2015 ).

The surveys comprise several questions measuring public opinion on climate change beliefs, risk perceptions, and policy support. Regarding “climate change beliefs”, survey respondents are being asked whether climate change is happening, whether humans are causing climate change, and whether scientists have a consensus on its existence. With respect to “climate change risk perceptions”, the respondents are asked whether they are worried about climate change and whether climate change will harm people in the U.S. Finally, the survey questions related to “policy support” aim to measure the respondents’ tendency to support climate-related policies such as regulating carbon dioxide emissions and imposing a carbon tax on fossil fuel companies. The local estimates are available for the years 2014, 2016, 2018, and 2021 based on the national surveys conducted in each of these years.

We rely on the estimates of Howe et al. ( 2015 ) from the Yale Program on Climate Change Communication to calculate a unique measure of climate change denial for each U.S. County. Specifically, we collect survey responses to nine questions related to climate change beliefs, risk perceptions, and policy support. We then use principal component analysis (PCA) to identify the common component with the highest eigenvalue. More details on the PCA and our climate change denial measure are provided in Table  1 .

In Panel A of Table  1 , we present the nine individual survey questions that comprise our measure of climate change denial as well as the national average values for each survey year. As can be seen from Panel A, the percentage of respondents who do not believe that global warming is happening ( Happening Oppose ) is about 20 percent in 2014, it drops to around 16–17 percent in 2016 and 2018, and then increases to 19.4 percent in 2021 while still remaining below the 2014 value. Nevertheless, both the percentages of respondents who think that global warming is caused mostly by natural changes in the environment instead of humans ( Human Oppose ) and who believe there is a lot of disagreement among scientists about whether or not global warming is happening ( Consensus Oppose ) decline over time. The survey estimates also indicate that the respondents’ risk perceptions related to climate change have changed over time as more people believe that climate change will negatively affect people in the U.S. as well as them personally. Interestingly, at the same time, the percentages of respondents who are more likely to oppose regulating carbon dioxide emissions and setting strict limits on existing coal-fired power plants have slightly increased from 2014 to 2021. Footnote 5

The results of the principal component analysis of the nine individual climate change perception variables are reported in Panel B of Table  1 . Additionally, in Fig.  1 , we provide a scree plot of how much variance is explained by each principal component and the eigenvalues associated with the components. The first principal component explains 75.5 percent of the variation in the nine variables and has an eigenvalue of 6.791. We use the scoring coefficients to obtain the first principal component score for each county and year. Because the estimates are available only for 2014, 2016, 2018, and 2021, we follow the prior literature (e.g., Hilary & Hui, 2009 ) and use the estimates from the most recent year to extend the sample period. For instance, for the years 2012 and 2013, we use the 2014 survey estimates. As an alternative approach, we create also an extrapolated version of climate change denial that accounts for the time-series variation in respondents’ perceptions. Finally, we obtain our county-level measure of climate change denial, Climate Change Denial , by normalizing the climate change denial score based on the PCA to range from 0 to 1 with higher values representing higher degrees of climate change denialism in the county.

Scree plot of eigenvalues after principal component analysis

Descriptive statistics for Climate Change Denial are presented in Panel C of Table  1 . The degree of climate change denial exhibits considerable variation across the U.S. counties around the mean value of 0.571. The county with the highest climate change denial score is Loving County in Texas, followed by Cameron Parish in Louisiana and Emery County in Utah. At the other end of the spectrum, counties with the lowest climate change denial scores are Wade Hampton Census Area, Alaska, Oglala Lakota County in South Dakota, Bronx County in New York, and Suffolk County in Massachusetts. To put these scores into perspective, in Loving County, Texas, an estimated 34.5 percent of residents do not believe that global warming is happening, compared to a mere 5.5 percent of the residents of Bronx County, New York. To illustrate the regional variation in the level of climate change denial across the U.S., Fig.  2 plots the county-level climate change denial scores for the years 2014 and 2021.

Climate change denial at the county level in 2014 and 2021

Corporate Environmental Responsibility

The dependent variable in our analysis is corporate environmental responsibility. As our main measure of firm-level environmental responsibility, we use the Environmental (E) pillar score of the MSCI’s environmental, social, and governance (ESG) ratings ( Environmental Score ). According to MSCI (2022), their ESG ratings “aim to measure a company’s resilience to long-term, financially relevant ESG risks” and combine thousands of data points across several ESG issues that present significant risks and opportunities. The MSCI ESG ratings and their individual subcomponents have been commonly used in the prior literature to measure corporate social responsibility (see e.g., Attig et al., 2013 , 2016 ; Harjoto et al., 2015 ; Arouri & Pijourlet, 2017 ; Attig & Brockman, 2017 ; Harjoto & Laksmana, 2018 ; Maas, 2018 ; Tsai & Wu, 2022 ; Bae et al., 2023 ). The MSCI ratings are also highly correlated with the holdings of ESG mutual funds in the U.S. (Berg et al., 2023 ).

MSCI’s environmental pillar score focuses on a range of factors related to a firm’s environmental impact, including carbon emissions, energy efficiency, water usage, waste management, and biodiversity. MSCI uses a data-driven approach to analyze firms’ environmental practices, relying on a combination of company-reported data, third-party data, and proprietary research. MSCI’s methodology for measuring environmental performance includes a series of quantitative and qualitative assessments that evaluate a firm’s environmental management systems, operational performance, and disclosure practices. The quantitative assessments use environmental data points, such as greenhouse gas emissions, energy consumption, and water usage, to calculate a company’s environmental performance. The qualitative assessments rely on MSCI’s research and analysis of company disclosures and management practices to evaluate a company’s environmental policies, programs, and performance. Overall, MSCI’s environmental pillar score provides a comprehensive assessment of a firm’s environmental impact. Footnote 6

MSCI’s environmental pillar score comprises five underlying subscores: Climate Change Score , Natural Resource Use Score , Waste Management Score , Carbon Emissions Score , and Toxic Emissions Score . MSCI’s Climate Change Score assesses a firm’s exposure to and management of climate-related risks and opportunities. The score is based on a range of factors, including the firm’s greenhouse gas emissions, energy efficiency, renewable energy use, and climate-related disclosure practices. The Natural Resource Use Score assesses a firm’s management of natural resource-related risks and opportunities, including water use, land use, and biodiversity. The score evaluates the firm’s resource management practices, such as water efficiency, sustainable sourcing, and land conservation efforts. The Waste Management Score assesses the management of waste-related risks and opportunities, including hazardous and non-hazardous waste generation, recycling and disposal practices, and pollution prevention efforts. The Carbon Emissions Score assesses a firm’s greenhouse gas emissions intensity, emissions reduction targets, and renewable energy use. Finally, the Toxic Emissions Score assesses the management of toxic emissions and hazardous substances, including air and water pollution, chemical spills, and other environmental releases.

Corporate Governance and Corporate Culture

For testing H2 and H3 , we need empirical measures of corporate governance and corporate culture. Corporate governance is inherently a multifaceted construct, characterized by a complex interplay of various organizational mechanisms, structures, and practices. In the prior literature (see e.g., Jo & Harjoto, 2011 , 2012 ), the conceptualization of corporate governance efficacy has often revolved around observable variables related to board characteristics and ownership structure. In our empirical analysis, we follow the approach of Colak and Liljeblom ( 2022 ) and measure the strength of corporate governance mechanisms with a composite index ( Corporate Governance ) constructed as the sum of the following five binary variables: (i) the firm’s Chief Executive Officer and the chairperson of the board of directors are different individuals, (ii) the average number of directorships held by board members is less than three, (iii) the number of board members is less than 12, (iv) the percentage of independent directors is above the sample median, and (v) the percentage of institutional ownership is above the sample median. By construction, this governance index can take a value between 0 and 5 with higher values indicating stronger corporate governance.

In contrast to the observable board and ownership characteristics that are commonly used to gauge corporate governance, corporate culture is a more difficult concept to define and especially to measure. To test H3 , we rely on the framework of O’Reilly and Chatman ( 1996 ) which defines corporate culture as the deep-rooted values and standards informally established within an organization. Within this framework, Li et al., ( 2021a , 2021b ) propose a machine learning technique based on word embedding to measure corporate culture from firms’ earnings call transcripts. The corporate culture measure of Li et al., ( 2021b ) reflects five key dimensions of corporate value—innovation, integrity, quality, respect, and teamwork—based on the frequency of specific culture-reflecting words and phrases used in earnings calls. Recent studies have used this novel measure to examine how corporate culture is reflected in firm value and financial reporting practices (Graham et al., 2022 ; Li et al., 2021a ; Afzali, 2023 ). Following Li et al., ( 2021b ), we measure the strength of corporate culture ( Corporate Culture ) for each firm by first calculating the sum of the culture scores across the five individual corporate culture dimensions and then creating annual quartile ranks of the aggregated corporate culture scores. Firms with corporate culture scores in the top quartile are considered to have the strongest culture.

The Empirical Models

We estimate alternative versions of the following fixed-effects panel regression specification to test the hypothesis that corporate environmental responsibility is negatively influenced by local climate change denial:

where Environmental Score i,t is the MSCI environmental pillar score for firm i in year t and Climate Change Denial is the climate change denial score for firm i ’s headquarters location county j in year t . H1 predicts that the coefficient for Climate Change Denial will be negative. To test H2 and H3 , we estimate modified versions of Eq. ( 1 ) in which we include interaction terms between local climate change denial and the strength of corporate governance and corporate culture, i.e., Climate Change Denial  ×  Corporate Governance and Climate Change Denial  ×  Corporate Culture .

Following prior literature on corporate social responsibility (e.g., Attig et al., 2016 ; Cai et al., 2016 ; Di Giuli & Kostovetsky, 2014 ; Jha & Cox, 2015 ), we control for firm size, return on assets, book-to-market ratio, the ratio of cash holdings and dividend payouts, leverage, the level of financial constraint based on the Kaplan and Zingales ( 1997 ) index, research and development expenditures, and advertisement intensity. The county-level controls included in Eq. ( 1 ) are county population, population growth, median household income, median age, and an indicator variable for whether the county is part of a metropolitan area. As documented by Kassinis and Vafeas ( 2006 ), geographic areas with greater income and population density can exert more pressure on local firms to act environmentally responsibly. Following prior research on the influence of local socio-political norms on firm-level CSR engagement, we also control for county-level differences in social capital (Hoi et al., 2018 ; Jha & Cox, 2015 ), religiosity (Du et al., 2014 ; Cui et al., 2015 ; Zolotoy et al., 2019 ), and political orientation (Di Giuli & Kostovetsky, 2014 ; Rubin, 2008 ). The definitions of all the variables included in Eq. ( 1 ) are provided in Appendix 1. To reduce the impact of outliers, we winsorize all control variables at the 1st and 99th percentiles.

In addition to the firm-specific and county-level controls, we include state, industry, and year fixed-effects to reduce potential biases related to omitted variables and to account for systematic variation in environmental responsibility across states and industries and over time. Finally, we cluster standard errors at the county level. Footnote 7

Descriptive Statistics

Table 2 reports descriptive statistics for the variables used in the regressions. The mean (median) values of Climate Change Denial and Happening Oppose are 0.419 (0.414) and 12.113 (11.505), respectively. It is important to note that these means and medians are different from those reported in Table  1 because the sample only includes counties in which publicly traded firms are headquartered. We identify only 375 unique such counties out of a total of over 3000 counties in the U.S. The mean, median, and standard deviation of Environmental Score t + 1 are 4.709, 4.600, and 2.197, respectively. The descriptive statistics indicate that the environmental performance of our sample firms exhibits substantial cross-sectional variation with the Environmental Score ranging from 0 to 10.

Pairwise correlation coefficients (not tabulated) indicate that Climate Change Denial and Happening Oppose are negatively correlated with Environmental Score while being positively correlated with Environmental Violations . Thus, the correlations provide support for the hypothesis that corporate environmental responsibility is negatively associated with the degree of local climate change denial. Not surprisingly, Climate Change Denial is significantly correlated with all of the county-level control variables, the strongest correlations being with median household income ( r  = –0.41) and county population ( r  = –0.35). In general, the correlation coefficients between the different independent variables used in the regressions are relatively low in magnitude, all being below 0.60 in absolute value.

Univariate Analysis

To initially illustrate the correlation between climate change denial and environmental performance, we create a binned scatterplot by first segmenting climate change denial scores into percentiles and then mapping the average one-year-ahead environmental performance along these percentiles. The scatterplot is depicted in Fig.  3 . The downward-sloping line indicates a trend of increasing climate change denial being associated with decreasing environmental responsibility. Thus, Fig.  3 provides preliminary support for H1 .

Binned scatterplot of climate change denial and environmental responsibility

We next perform univariate t -tests to examine the differences between firms headquartered in high versus low climate change denial counties. For this purpose, we divide firm-year observations into two subsamples based on the top and bottom terciles of Climate Change Denial . The results of the univariate are reported in Table  3 .

Consistent with our hypothesis, the t -tests indicate that firms headquartered in the high climate change denial counties have lower environmental performance than firms headquartered in the low climate change denial counties. As can be noted from Table  3 , the mean difference between Environmental Score between the two subsamples is negative and statistically significant at the 1 percent level. Moreover, all the other environmental performance indicators, such as climate change, natural resource use, waste management, carbon emission, and toxic emission scores, are also statistically significantly lower for firms headquartered in high climate change denial counties. The univariate tests also demonstrate that firms located in high climate change denial counties commit significantly more federal environmental violations than firms in low climate change denial counties.

With respect to the firm-specific and county-specific control variables, the univariate tests in Table  3 suggest that firms located in the regions of high climate change denial are more profitable and have higher book-to-market and leverage ratios, while also having significantly lower cash holdings, R&D expenditures, and advertisement intensity. Furthermore, the results of the t -tests indicate that counties with high degrees of climate change denial are very different from the ones with low degrees of denial in terms of socio-political characteristics. Specifically, climate change denialism is more prevalent in smaller counties and non-metropolitan areas, more religious and decisively Republican counties, and regions with an older population and lower median household income. Footnote 8

Main Results: Test of H1

Table 4 presents the estimation results of five alternative versions of Eq. ( 1 ). We begin by estimating a parsimonious industry and year fixed-effects specification with Climate Change Denial as the only explanatory variable (Model 1). The adjusted R 2 indicates that this constrained model explains about 26 percent of the cross-sectional variation in Environmental Score . As can be noted from Table  4 , the coefficient estimate for Climate Change Denial in Model 1 is negative and statistically significant at the 1 percent level, indicating that corporate environmental performance decreases with increasing local climate change denial. For reference purposes, we estimate Model 2 which excludes Climate Change Denial and includes all the control variables as well as industry and year fixed-effects. In this specification, the coefficients for most of the control variables appear statistically significant, and the adjusted R 2 increases to 30.9 percent after the inclusion of these controls.

Model 3 is our baseline model which includes all the control variables along with industry and year fixed-effects. Consistent with H1 , the estimated coefficient for Climate Change Denial is negative and statistically significant at the 1 percent level. Given that local socio-political values and preferences are likely to influence both climate change denial and corporate environmental responsibility, we then augment the set of county-level characteristics by including region fixed-effects in Model 4 and state fixed-effects in Model 5 to control for potential biases related to systematic heterogeneity in firm-level environmental responsibility across different regions and states. Similar to the other models, the estimated coefficients for Climate Change Denial in both of these specifications are negative and statistically highly significant.

Overall, the regression results in Table  4 provide strong support for the hypothesis that corporate environmental responsibility is negatively influenced by local climate change denial ( H1 ). In addition to being statistically significant, the results can also be considered economically meaningful. For instance, the coefficient estimate of –1.050 for Climate Change Denial in Model 3 suggests that, ceteris paribus, an increase of one standard deviation in the degree of local climate change denial is associated with a 4.92 percent [(–1.050 × 0.221) ÷ 4.709] decrease in Environmental Score .

As can be seen from Table  4 , the coefficient estimates for most of the firm-level control variables in Models 2–5 are statistically significant and consistent with our expectations. Footnote 9 Specifically, the regression results demonstrate that corporate environmental performance is positively related to firm size, R&D intensity, cash holdings, dividend payout, and the level of financial constraint while being negatively associated with book-to-market ratio. Interestingly, the coefficients for county-level control variables appear statistically insignificant throughout the regressions, with the only exceptions being the negative coefficients for Republican in Models 2, 3, and 5. Broadly consistent with the findings of Di Giuli and Kostovetsky ( 2014 ), the negative coefficients for Republican suggest that firms headquartered in Republican states tend to be less environmentally responsible. Footnote 10

Endogeneity Bias

Our regression results indicate that local climate change denial has a negative influence on the firm’s environmental responsibility. However, we acknowledge that endogeneity caused by omitted variables, reverse causality, and selection biases may influence the estimates and impede causal interpretations. In our main regressions, we have included a range of firm-specific and county-specific control variables as well as industry, year, and state fixed-effects to alleviate concerns related to omitted variables. Nevertheless, it is possible that some omitted or unobservable attribute is simultaneously influencing firm-level environmental responsibility and county-level beliefs and perceptions about climate change.

It is also conceivable that the environmental responsibility of local firms influences the public perception regarding climate change in the surrounding community, which would lead to reverse causality from firm-level environmental performance to county-level climate change denial. The endogenous nature of selecting headquarters location may also bias our results if environmentally responsible firms self-select their location into the geographic areas with lower degrees of climate change denial. To address these endogeneity concerns, we next utilize entropy balancing and instrumental variable regressions in order to establish a causal linkage from local climate change denial to corporate environmental responsibility.

Entropy Balancing

Our first approach for mitigating endogeneity concerns, specifically relating to selection bias, is entropy balancing (Hainmueller, 2012 ). Prior research has used this technique to deal with endogeneity concerns (e.g., Chapman et al., 2019; Chahine et al., 2020 ). We use entropy balancing to construct a balanced sample based on firm and county-level characteristics (covariates). Entropy balancing aids us in reducing observable differences between the control and treatment groups without requiring assumptions about any relationships between the covariates and the dependent variable. We begin by dividing our sample into firms headquartered in high climate change denial (treatment) and low denial (control) counties. Entropy balancing then assigns weights for each observation in the treatment and control groups such that the weighted samples have identical means for all the pre-specified covariates, thereby addressing potential selection bias. Similar to our univariate tests, we use values above and below the median of Climate Change Denial to define the high and low climate change denial counties. Footnote 11 Untabulated univariate tests indicate that the observable differences in firm-specific and county-specific attributes observed in Table  3 become statistically insignificant in the entropy-balanced sample, suggesting that the process effectively eliminates the observable differences between the matched and the treatment firms.

The regression results based on the matched-firm sample are reported in the first numerical column of Table  5 . Consistent with our main regressions, the coefficient estimate for Climate Change Denial is negative and statistically significant at the 5 percent level. Thus, the estimates suggest that local climate change denial has a negative influence on corporate environmental responsibility even after curtailing the observable differences in firm characteristics and socio-political attributes between high and low climate change denial counties. These findings provide further support for our first hypothesis.

Instrumental Variable Regressions

We proceed to address potential endogeneity concerns with two-stage instrumental variable (IV) regressions. For this purpose, we use two different instruments for Climate Change Denial , the endogenous variable of interest: (i) Average CC Denial and (ii) Temperature Anomaly . Following Zhang et al. ( 2023 ), we define Average CC Denial as the average climate change denial score in the state excluding the county in which the firm is headquartered. As our second instrument, we use “temperature anomaly” in July for each county. To calculate this measure, we obtain county-level monthly average temperatures over the period 1901–2021 from the National Centers for Environmental Information. We define Temperature Anomaly as the difference between the temperature in a given July of a county-year minus the average July temperature over the period 1901–2000. We use July because it is the hottest month of the year in most U.S. states.

The relevance criterion requires that the instrumental variables should be meaningfully correlated with Climate Change Denial . Given that norms and perceptions are likely to be relatively similar within a given geographic region, we expect counties within the same state to have similar climate change perceptions as the county of the firm’s headquarters. This presumption is based on the premise that people within a state are more likely to be influenced by common state-level factors when forming their climate change perceptions. Thus, it is reasonable to assume that Average CC Denial reflects regional climate change perceptions relevant to the county of the firm’s headquarters. With respect to our second instrument, we contend that unusually warm and rising temperatures are likely to affect local perceptions of climate change. When temperatures deviate significantly from historical averages, individuals living in these areas are more likely to notice and potentially link such anomalies to climate change through experiential processing, i.e., they learn through personal experience. This relationship between experiential processing and climate change perceptions has empirical support in the climate science literature (see e.g., Myers et al., 2013 ; Spence et al., 2011 ).

For the instrumental variables to be valid, they must also satisfy the exclusion criteria, i.e., the instrument should not affect firm-level environmental performance independently but only through the endogenous variable. It is reasonable to presume that the perceptions of individuals working in a given county are likely to be influenced by the broader climate change perceptions prevailing in their state. The impact of state-level climate change denial on firm-level environmental performance is therefore likely to be mediated through county-level climate change denial, satisfying the exclusion restriction. Similarly, anomalous local temperatures in July are expected to affect local perceptions of climate change within a county. It is unlikely that unusually warm temperatures in individual U.S. counties would have a direct, independent effect on firm-level environmental performance. The logical channel is that such temperature anomalies would influence individuals within the county to form certain climate change perceptions that, in turn, influence their engagement with environmental issues, potentially impacting firm-level environmental responsibility. Footnote 12

The second numerical column of Table  5 presents the estimates of the first-stage regression. As can be seen from the table, the average degree of climate change denial score of the counties in the state is strongly positively correlated with the endogenous variable, Climate Change Denial . Similarly, as predicted, the anomalous temperature in July is significantly negatively associated with the climate change denial score. The Craig-Donald F-statistic has a value above the thresholds suggested in Stock and Yogo ( 2005 ), indicating that our instrumental variable estimates do not suffer from a weak instrument problem. The results of the second-stage IV regressions with the instrumented Climate Change Denial are reported in the third numerical column of Table  5 . Overall, the second-stage estimates are consistent with our main regressions reported in Table  4 . The coefficient estimate for the instrumented Climate Change Denial is negative and statistically significant at the 5 percent level, and it is very similar in magnitude to the coefficients in Table  4 . The Hansen j -statistic and the accompanying p -value indicate that the instruments do not overidentify the equation. Thus, the IV regressions facilitate the causal interpretation of our results and suggest that corporate environmental responsibility is negatively influenced by local climate change denial even after controlling for potential endogeneity.

Corporate Headquarters Relocation as a Quasi-Natural Experiment

Following the recent literature studying the effects of local socio-political norms on corporate decisions and outcomes (e.g., Hasan et al., 2017 ; Hoi et al., 2019 ), we next utilize headquarters relocation as a quasi-natural experiment to assess the causal linkage between local climate change perceptions and corporate environmental performance. In our sample, we are able to identify 185 individual firms that relocated their headquarters to another county during the sample period. We require at least 3 years of non-missing data for all the variables in our baseline model before and after the headquarters relocation. This filtering process leaves us with a sample of 62 headquarters relocations. We next identify whether the corporate headquarters relocation is from a county with lower climate change denial to a county with higher climate change denial, and vice versa. In 49 relocations, climate change denial is lower in the new headquarters location county than in the old location, and in the remaining 13 relocations corporate headquarters moves to a county with a higher degree of climate change denial. The final headquarters relocation sample for the quasi-natural experiment comprises 532 firm-year observations.

The main variable of interest in the quasi-natural experiment is the interaction term between a dummy variable CCD Increasing Relocation that equals 1 if the firm relocates from a low climate change denial county to a high climate change denial county and a dummy variable Post that equals 1 for the years after the corporate headquarters relocation and 0 before the relocation year. The regression results based on the corporate headquarters relocation sample are presented in the fourth numerical column of Table  5 . As can be noted from the table, the coefficient estimate for the interaction variable CCD Increasing Relocation  ×  Post is negative and statistically significant at the 5 percent level. This negative coefficient suggests that the environmental performance of firms that relocate their corporate headquarters to a county with a higher level of climate change denial decreases after the relocation in comparison to firms that relocate to counties with lower climate change denial. Thus, the quasi-natural experiment based on headquarters relocations provides evidence of a causal linkage from local climate change denial to corporate environmental responsibility.

An Additional Test Related to Reverse Causality

In our main regressions, Climate Change Denial and all the other independent variables are lagged by 1 year relative to Environmental Score to address potential reverse causality. Although the instrumental variable regressions and the quasi-natural experiment based on headquarters relocations should alleviate endogeneity arising from reverse causality, we perform an additional test to reduce any remaining concerns related to reverse causality. Specifically, following the approach of Hillman and Keim ( 2001 ), we use the change in local climate change denial from year t to year t  +  1 as the dependent variable and corporate environmental performance in year t as the main independent variable along with the set of control variables used in Eq. ( 1 ). We estimate these cross-sectional regressions with the change in climate change denial as the dependent variable for each year in our sample. Our untabulated regression results indicate that corporate environmental performance is not associated with changes in climate change perceptions. This result further mitigates concerns related to reverse causality.

The Roles of Corporate Governance and Corporate Culture: Tests of H2 and H3

We next investigate whether the linkage between local climate change denial and corporate environmental responsibility is influenced by the strength of corporate governance mechanisms ( H2 ) and corporate culture ( H3 ). In order to test H2 and H3 and to assess the potential mediating effect of corporate governance and culture on the negative relation between climate change denial and corporate environmental responsibility, we estimate modified versions of Eq. ( 1 ) which include either an interaction term between climate change denial and the strength of corporate governance ( Climate Change Denial  ×  Corporate Governance ) or an interaction term between climate change denial and corporate culture ( Climate Change Denial  ×  Corporate Culture ). Following Colak and Liljeblom ( 2022 ), we measure the strength of corporate governance with a governance index that reflects the effectiveness of internal and external governance. To gauge the strength of corporate culture, we employ the corporate culture measure of Li et al., ( 2021b ) which is constructed from earnings call transcripts by utilizing machine learning techniques.

The results of the interaction regressions are reported in Table  6 . Models 1 and 3 are estimated without the county-level control variables, while Models 2 and 4 include the full set of controls in addition to industry and year fixed-effects. Regardless of the model specification, the coefficient estimates for the interaction variables Climate Change Denial  ×  Governance and Climate Change Denial  ×  Corporate Culture are positive and statistically highly significant. Thus, the estimates indicate that the negative relationship between local climate change denial and corporate environmental performance is mitigated by strong corporate governance mechanisms and corporate culture. Collectively, these results provide support for H2 and H3 and thereby highlight the importance of corporate governance mechanisms and corporate culture for socially responsible behavior. Our findings imply that strong internal and external governance mechanisms and firm-level cultural values can act as buffers against the detrimental influence of local climate change denialism on corporate environmental responsibility and strategic commitment to CSR initiatives.

Additional Tests

Subscores of environmental responsibility.

Thus far, we have measured corporate environmental performance with the MSCI environmental score. Next, we decompose Environmental Score into the following five subscores of environmental responsibility: (i) Climate Change Score , (ii) Natural Resource Use Score , (iii) Waste Management Score , (iv) Carbon Emissions Score , and (v) Toxic Emissions Score .

The estimates of Eq. ( 1 ) with the alternative environmental performance subscores as the dependent variables are presented in the first five numerical columns of Table  7 . Because the different subscores are not available for all firms, the number of firm-year observations used in these regressions is lower than in our main regressions, ranging from 5803 to 14,723. The adjusted R 2 s of the regressions vary between 38 and 46 percent. Overall, the results of these additional regressions are broadly consistent with our main analysis. Specifically, the coefficient estimates for Climate Change Denial are negative and statistically highly significant in the regressions with Climate Change Score , Natural Resource Use Score , and Carbon Emissions Score as the dependent variables, while being insignificant in the Waste Management Score and Toxic Emissions Score regressions. The magnitudes and the significance levels of the coefficient estimates indicate that local climate change denial has a particularly strong negative influence on the responsible use of natural resources. The estimates suggest that a one standard deviation increase in local climate change denial is associated with a 3.5 percent lower Natural Resource Use Score .

Alternative Measures of Environmental Responsibility

Recent studies have documented that there is substantial disagreement across different ESG rating providers regarding the environmental, social, and governance performance of individual firms (Berg et al., 2022 ; Chatterji et al., 2016 ; Christensen et al., 2022 ). Therefore, to ascertain that our empirical findings are robust to different assessments of corporate environmental performance, we next use Refinitiv’s Environmental Pillar Score as an alternative dependent variable. Refinitiv’s Environmental Pillar Score aims to rank firms’ environmental performance relative to their peers on a scale of 0–100 based on data related to emissions reduction, resource use, and environmental innovations. Again, the sample size is lower than in Table  4 because Refinitiv covers a smaller number of individual firms than MSCI. Footnote 13 The estimates of Eq. ( 1 ) with the Environmental Pillar Score from Refinitiv as the dependent variable are reported in the sixth numerical column of Table  6 . Consistent with our main regressions, the coefficient for Climate Change Denial is negative and statistically significant at the 5 percent level.

As the next approach to measure corporate environmental responsibility, we follow the recent literature (e.g., Heese et al., 2022 ; Raghunandan & Rajgopal, 2021 ) and use the number of federal environmental compliance violations from the Violation Tracker database compiled by the nonprofit organization Good Jobs First. Unlike the environmental performance assessments constructed by different ESG rating providers, the federal environmental compliance violations reflect actual firm-level environmental outcomes rather than being subjective assessments based on the firm’s CSR disclosure, sustainability reports, and environmental policies. We estimate a Poisson regression with the number of committed environmental violations as the dependent variable. As shown in Table  7 , the coefficient estimate for Climate Change Denial is positive and statistically significant at the 5 percent level. This suggests that higher levels of climate change denial in the firm’s social environment increase the number of environmental violations committed by the firm.

Our third alternative measure of corporate environmental responsibility is motivated by recent studies on environmental costs (Drobetz et al., 2023 ; Freiberg et al., 2022 ). Specifically, we use data obtained from Freiberg et al. ( 2022 ) to measure environmental intensity as the total environmental costs divided by the total revenue of the firm. The approach of Freiberg et al. ( 2022 ) allows the conversion of environmental impact estimates into scalable monetary values. These estimates are derived by applying specific characterization pathways and monetization factors to the environmental outputs of an organization, which can include carbon emissions, water usage, and various other types of emissions. The regression results with Environmental Costs as the dependent variable are reported in the eighth numerical column of Table  7 . The positive and statistically significant coefficient for Climate Change Denial suggests that firms headquartered in high climate change denial counties impose more environmental costs on society than firms located in counties with lower levels of climate change denialism. Nevertheless, it should be acknowledged that the sample size in this regression is considerably lower than in our other specifications, and thus, these estimates should be approached more cautiously.

Alternative Measures of Climate Change Denial

We also conduct two additional tests related to the measurement of climate change denial. First, we acknowledge that the use of a single climate change denial score which is based on the principal component analysis of nine survey questions may also lead to a measurement bias. To address this concern, we use Happening Oppose instead of Climate Change Denial to measure local beliefs about climate change. This variable is the estimated percentage of county residents who do not believe that global warming is happening. The ninth numerical column of Table  7 presents the estimates of Eq. ( 1 ) with Happening Oppose as the test variable of interest. Consistent with the hypothesis that corporate environmental responsibility is negatively influenced by local climate change denial, the coefficient estimate for Happening Oppose is negative and statistically significant at the 1 percent level.

Second, while in our main analysis, we extrapolate the sample period to cover the years 2012–2020, the county-level climate change denial scores can only be estimated for the years 2014, 2016, 2018, and 2020. To ensure that our results are not affected by this extrapolation, we estimate Eq. ( 1 ) based on a sample constrained to the 4 years during which the climate change perception surveys were conducted. The estimation results of this specification are reported in the tenth numerical column of Table  7 . As shown in the table, the coefficient for Climate Change Denial remains negative and statistically significant at the 1 percent level even after constraining the sample to the survey years.

Discussion and Ethical Implications

Our empirical findings have broad implications for firms, policy makers, and society at large regarding sustainability practices, socially responsible investing, and sustainable development. From the firm’s perspective, it is essential to acknowledge that climate change denial in the surrounding community may inflict environmental initiatives and create conflicts with the long-term interests of shareholders, other stakeholders, and the broader society. Thus, local climate change denialism can create significant reputational and financial risks for firms. In regions with a tendency towards high climate change denialism, firms may face less stringent demands from investors, financial institutions, and other external stakeholders to disclose their environmental impact and demonstrate their commitment to environmental responsibility. To mitigate these risks, firms that prioritize corporate environmental responsibility may have to consider relocating their headquarters to regions with lower levels of climate change denial.

From a public policy perspective, our findings highlight the need for governments and non-governmental organizations to shape solutions and regulations that address climate change and curb global warming. If incredulous local beliefs about climate change influence firms’ engagement in environmental responsibility, in addition to regulation, policy makers should direct efforts towards initiatives and public awareness campaigns that reduce climate change skepticism and enhance public trust in institutions and science. By enhancing public trust in environmental science, policy makers can encourage firms to prioritize corporate environmental responsibility and foster sustainable development. One approach proposed by Bain et al. ( 2012 ) would be to direct efforts toward policies that have positive societal outcomes and create societies where people are more considerate and caring. Furthermore, society as a whole should recognize the importance of sustainable development and climate change mitigation. Public opinion and beliefs about climate change may play a crucial role in shaping firms’ engagement in environmental responsibility and policy responses to climate change.

Our study also has important ethical implications. Our empirical findings emphasize the moral responsibility of firms to transcend local biases and misconceptions about climate change and to uphold rigorous environmental standards. In regions with higher levels of climate change denialism, firms face a greater ethical obligation to ensure that their operational decisions are not influenced by the prevailing local misconceptions about climate change but are instead based on scientific evidence and global ethical standards. Our results also highlight the important role of internal and external corporate governance mechanisms and corporate culture in mitigating the detrimental influence of local climate change denial on environmental responsibility. On a more general level, our findings point to the ethical imperative for organizational leadership to cultivate a culture of environmental stewardship that instills values that take into account the well-being of the planet and all its inhabitants while ensuring that corporate policies and practices align with global initiatives aimed at mitigating environmental degradation and climate change. In this broader context, corporate ethics goes beyond mere legal compliance; it entails a moral obligation to contribute positively to global efforts to combat climate change, especially in regions where climate change denialism is more prevalent.

Conclusions

We examine whether corporate environmental responsibility is influenced by regional differences in climate change denial. Using unique, survey-based estimates of climate change denial in U.S. counties, we find that corporate environmental responsibility is negatively influenced by the prevalence of climate change denialism in the local community. Specifically, our empirical findings demonstrate that firms located in counties with higher levels of climate change denial have weaker environmental performance ratings after controlling for firm characteristics and various county-level attributes such as social capital, religiosity, and political leaning. When the environmental score is decomposed into the five subscores of environmental responsibility, we find that local climate change denial has a particularly strong negative influence on the subscores that reflect carbon emissions, climate change, and responsible use of natural resources. Furthermore, our results indicate that firms headquartered in high climate change denial counties are more likely to commit federal environmental compliance violations and impose greater environmental costs on society. We also document that strong corporate governance mechanisms and corporate culture moderate the negative relationship between climate change denial and corporate environmental performance. Thus, our findings suggest that internal and external governance structures and firm-level cultural values can act as effective buffers against the detrimental influence of local climate change denialism on environmentally responsible corporate behavior.

The results documented in this study open several avenues for future research. First, given that our empirical analysis is based on climate change denialism within U.S. counties, future studies could employ a broader international sample to investigate the influence of climate change denial on corporate outcomes across different socio-political and institutional settings. It would be intriguing to examine whether country-level differences in climate change denial are reflected in corporate environmental performance. Future studies could further investigate how different socio-political norms and cultural contexts potentially influence the linkage between climate change denialism and corporate sustainability practices. It would be also important to address the impact of different types of public awareness campaigns or anti-pro-environmental initiatives in changing attitudes toward climate change and to examine if these efforts prompt shifts in corporate behavior. Finally, future research could examine the influence of climate change denialism on other corporate decisions ranging from environmental disclosure practices to investment and payout policies.

Data availability

The data used in this paper are either derived from public sources or obtained from commercial databases.

As an anecdotal example, the State of California, where the level of climate change denial is relatively low, has enacted several legislations aimed at carbon capture and sequestration in forests and reducing motor vehicle emissions.

The data on corporate culture are obtained from Kai Li’s data library at https://sites.google.com/view/kaili .

We exclude ADRs because our empirical analysis is based on climate change denial in U.S. counties and we cannot use foreign firms in our tests.

Pew Research Center conducted their first survey on climate change perceptions in 2009.

For details on trends at the state level, see Marlon et al. ( 2022 ).

For additional details, see https://www.msci.com/esg-and-climate-methodologies .

Clustering of standard errors at the firm or industry levels does alter our main inferences.

While it remains unclear how county-level characteristics such as population, median age, and median household income may affect firm-level environmental performance, we include these variables as additional control variables in our regressions to alleviate potential concerns related to omitted correlated variables.

The expected signs for the control variables are derived from prior research. Specifically, we use Di Giuli and Kostovetsky ( 2014 ) as a reference point for firm characteristics and political affiliation. For county-level income and population, we rely on the findings of Kassinis and Vafeas ( 2006 ). With respect to social capital and religiosity, the expected signs are consistent with Jha and Cox ( 2015 ), Hoi et al. ( 2018 ), and Dimic et al. ( 2024 ).

Given that regional differences in political leanings may influence corporate environmental responsibility as well as the perceptions about climate change (e.g., Hornsey et al., 2016 ), we also estimate Eq. ( 1 ) using subsamples of firms located in Democratic and Republican states as an additional test. In these untabulated regressions, the coefficient estimates for Climate Change Denial are negative and statistically significant at the 5 percent level in both subsamples. Thus, we conclude that the negative association between local climate change denial and corporate environmental performance is not induced by state-level political leanings.

As a robustness check, we have also used the bottom and top deciles to classify high and low climate change denial counties. The estimates based on this alternative classification are consistent with our main regressions.

While there is no formal empirical test for the exclusion criteria, to mitigate concerns that our instrumental variables are directly related to the dependent variable in the second stage, we estimate a regression in which we use the instruments as additional control variables. The coefficient estimates for both instrumental variables are insignificant, suggesting that our instruments are not directly associated with environmental responsibility.

Until recently, Refinitiv’s ESG scores have been primarily available for large U.S. firms while MSCI has also covered smaller firms and a significantly larger portion of the U.S. equity market.

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Acknowledgements

We wish to thank three anonymous referees, Omrane Guedhami (Section Editor), Helen Bollaert, Marco Ceccarelli, Denis Davydov, Samuel Fosu, Qiping Huang, Nikolaos Kavadis, Panagiotis Koutroumpis, Sarada Krishnan, Maureen Mascha, David Marqués-Ibáñez, Radu Tunaru, and conference and seminar participants at the 63rd Annual Meeting of the Southern Finance Association, the 7th Liechtenstein Workshop of Sustainable Finance, the 22nd Workshop on Corporate Governance and Investment, the 2023 Wolpertinger Conference, the 2023 International Workshop on ESG Values, European Central Bank, Hanken School of Economics, the University of Sussex, and the University of Vaasa for valuable comments and suggestions. We gratefully acknowledge the financial support of the OP Group Research Foundation, the Hanken Support Foundation, and the Czech Science Foundation (grant number: 22-19617S). Part of this paper was written while Mansoor Afzali was visiting the Weatherhead Center at Harvard University. This paper received the Best Paper Award at the 2023 International Workshop on ESG Values and the Climate Finance Award at the 7th Liechtenstein Workshop of Sustainable Finance.

Open Access funding provided by University of Vaasa. This study was partially funded by the OP Group Research Foundation, the Hanken Support Foundation, and the Czech Science Foundation (grant number: 22-19617S).

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Afzali, M., Colak, G. & Vähämaa, S. Climate Change Denial and Corporate Environmental Responsibility. J Bus Ethics (2024). https://doi.org/10.1007/s10551-024-05625-y

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10 Organized Climate Change Denial

Riley E. Dunlap is Regents Professor of Sociology, Oklahoma State University.

Aaron M. McCright is Associate Professor of Sociology, Lyman Briggs College, Department of Sociology, and Environmental Science and Policy Program, Michigan State University.

• Published: 06 January 2012
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Even as the consensus over the reality and significance of anthropogenic climate change (ACC) becomes stronger within the scientific community, this global environmental problem is increasingly contested in the political arena and wider society. The spread of debate and contention over ACC from the scientific to socio-political realms has been detrimental to climate science. This article provides an overview of organized climate change denial. Focusing primarily on the US, where denial first took root and remains most active, this article begins by describing the growth of conservative-based opposition to environmentalism and environmental science in general. It then explains why climate change became the central focus of this opposition, which quickly evolved into a coordinated and well-funded machine or ‘industry’. It also examines denialists' rationale for attacking the scientific underpinnings of climate change policy and the crucial strategy of ‘manufacturing uncertainty’ they employ.

Even as the consensus over the reality and significance of anthropogenic climate change (ACC) becomes stronger within the scientific community, this global environmental problem is increasingly contested in the political arena and wider society. The spread of debate and contention over ACC from the scientific to socio‐political realms has been detrimental to climate science, as reflected in significant declines in public belief in global warming in 2009 and 2010 (Leiserowitz et al. 2010 ). Contrarian scientists, fossil fuels corporations, conservative think tanks, and various front groups have assaulted mainstream climate science and scientists for over two decades. Their recently intensified denial campaign building on the manufactured ‘Climategate’ scandal (Fang 2009 ) and revelations of various relatively minor errors in the 2007 IPCC Fourth Assessment Report appears to have seriously damaged the credibility of climate science (Tollefson 2010 ). The blows have been struck by a well‐funded, highly complex, and relatively coordinated ‘denial machine’ (Begley 2007 ). 1 It consists of the above actors as well as a bevy of amateur climate bloggers and self‐designated experts, public relations firms, astroturf groups, conservative media and pundits, and conservative politicians.

The motivations of the various cogs of the denial machine vary considerably, from economic (obvious in the case of the fossil fuels industry) to personal (reflected in the celebrity status enjoyed by a few individuals), but the glue that holds most of them together is shared opposition to governmental regulatory efforts to ameliorate climate change, such as restrictions on carbon emissions. While the claims of these actors sometimes differ and evolve over time (there's no warming, it's not caused by humans, it won't be harmful, etc.), the theme of ‘no need for regulations’ remains constant (McCright and Dunlap 2000 ; Oreskes and Conway 2010 ). A staunch commitment to free markets and disdain of governmental regulations reflect the conservative political ideology that is almost universally shared by the climate change denial community. 2 This suggests how the diverse elements of the denial machine are able to work in a compatible and mutually reinforcing manner even when their efforts are not necessarily coordinated. By attacking climate science and individual scientists in various venues and fashions, the denial machine seeks to undermine the case for climate policy making by removing (in the eyes of the public and policy makers) the scientific basis for such policies—i.e. by challenging the reality and seriousness of climate change.

Viewed through a broader theoretical lens, climate change denial can be seen as part of a more sweeping effort to defend the modern Western social order (Jacques 2006 ), which has been built by an industrial capitalism powered by fossil fuels (Clark and York 2005 ). Since anthropogenic climate change is a major unintended consequence of fossil fuel use, simply acknowledging its reality poses a fundamental critique of the industrial capitalist economic system. European scholars such as Ulrich Beck and Anthony Giddens describe the current era as one of ‘reflexive modernization,’ in which advanced nations are undergoing critical self‐confrontation with the unintended and unanticipated consequences of industrial capitalism—especially low‐probability, high‐consequence risks that are no longer circumscribed spatially or temporally such as genetic engineering, nuclear energy, and particularly climate change (Beck 1992 ; Beck et al. 1994 ; Giddens 1990 ). Reflexive modernization theorists like Beck and Giddens argue that a heightened level of reflexivity is a necessary precondition for dealing effectively with this new set of human‐induced ecological and technological threats.

Crucial drivers of this reflexivity, or societal self‐confrontation and examination, are citizen action/social movements (Beck's ‘sub‐politics’) and science, most notably environmental activism and those scientific fields that examine ecological and human health impacts of technologies and economic activities. By directing societal attention to environmental disasters like massive oil spills and crescive problems like climate change that result from economic production, the forces of reflexivity draw the ire of defenders of the capitalist system who often mobilize against them (Beck 1997 ; Mol 2000 ). This has been particularly true in the United States, where a combination of corporate and conservative interests have long battled environmentalism (Helvarg 2004 ) and environmental science (Jacques et al. 2008 ). We have argued elsewhere that these interests are now mobilizing more broadly in opposition to reflexive modernization writ large and are becoming a source of ‘anti‐reflexivity’ (McCright and Dunlap 2010 ). Nowhere is this anti‐reflexive orientation—particularly the dismissal of scientific evidence and methodology—more apparent than in climate change denial.

This chapter provides an overview of organized climate change denial. 3 We begin by describing the growth of conservative‐based opposition to environmentalism and environmental science in general, and then explain why climate change became the central focus of this opposition, which quickly evolved into a coordinated and well‐funded machine or ‘industry’ (Monbiot 2007 ). We also examine denialists' rationale for attacking the scientific underpinnings of climate change policy and the crucial strategy of ‘manufacturing uncertainty’ they employ (Michaels 2008; Oreskes and Conway 2010 ). The remainder of the chapter describes the complex and evolving set of actors espousing climate change denial, touching on their tactics when appropriate and tracing their interconnections when possible. Describing the climate change denial machine is difficult, because it is both a complex and ever‐evolving labyrinth and because many of its components intentionally mask their efforts and sources of support. We focus primarily on the US, where denial first took root and remains most active, but also include a brief look at its international diffusion. We conclude with observations about the dangers of growing anti‐reflexivity in an era of profound ecological threats such as climate change.

1 History and Strategy of Climate Change Denial

Riding the wave of a conservative resurgence launched in reaction to the progressive gains of the 1960s and early 1970s (Lapham 2004 ), including an impressive set of environmental agencies and regulations, the Reagan Administration came into office promising to get government off the back of the private sector. However, the administration's efforts to curtail environmental protection created a backlash that forced it to moderate its anti‐environmental rhetoric and actions, albeit not its objectives (Dunlap 1987 ). This experience taught conservatives (and industry) that it was more efficacious to question the need for environmental regulations by challenging evidence of environmental degradation, rather than the goal of environmental protection. Promoting ‘environmental skepticism’ which disputes the seriousness of environmental problems (Jacques 2006 ) has subsequently been heavily employed by conservative think tanks and their corporate allies, especially since the 1990s when the downfall of the Soviet Union and the rise of global environmentalism represented by the 1992 Rio ‘Earth Summit’ led conservatives to substitute a ‘green threat’ for the disappearing ‘red threat’ (Jacques et al. 2008 ). Perception of the Clinton‐Gore Administration as receptive to environmental protection heightened conservatives' fears of increasing national and international environmental regulations.

These fears crystallized around climate change, as creation of the Intergovernmental Panel on Climate Change (IPCC) by the United Nations Environmental Program and the World Meteorological Organization represented an unprecedented international effort to develop a scientific basis for policy making. 4 This, combined with the encompassing nature and wide‐ranging implications of climate change, turned ACC into a cause célèbre for conservatives. The mainstream conservative movement, embodied in leading foundations and think tanks, quickly joined forces with the fossil fuels industry (which recognized very early the threat posed by recognition of global warming and the role of carbon emissions) and wider sectors of corporate America to combat the threat posed by climate change—not as an ecological problem but as a problem for the pursuit of unbridled economic growth (Gelbspan 1997 ). In the process this coalition took the promotion of environmental skepticism to a new level, attacking the entire field of climate science as ‘junk science’ and launching attacks on such pillars of science as the importance of peer‐reviewed publications (Jacques et al. 2008 ). The result has been an evolution of environmental skepticism into a full‐blown anti‐reflexivity in which the ability and utility of science for documenting the unintended consequences of economic growth are being undermined (McCright and Dunlap 2010 ).

The conservative movement/fossil fuels complex quickly adopted the strategy of ‘manufacturing’ uncertainty and doubt (perfected by the tobacco industry) as its preferred strategy for promoting skepticism regarding ACC (Union of Concerned Scientists 2007 ). Early on contrarian scientists—with considerable support from industry and conservative think tanks—stressed the ‘uncertainty’ concerning global warming and human contributions to it (Oreskes and Conway 2010 ). As the threat of international policy making increased, from the 1997 Kyoto Protocol to the 2009 COP in Copenhagen, the growing army of opponents to carbon emissions reduction policies has stepped up their attacks (Greenpeace 2010a ; McCright and Dunlap 2003 ; Pooley 2010 ). They have also broadened their tactics well beyond manufacturing uncertainty, increasingly criticizing peer‐review, refereed journals, governmental grant making, scientific institutions (American Association for the Advancement of Science, US National Academy of Sciences, etc.) and the expertise and ethics of scientists (Nature 2010a , 2010b ; Sills 2010 ). Again, this assault on scientific practices, evidence, and institutions weakens a major mechanism of reflexive modernization. We now turn to an examination of the major actors in the denial machine, which are portrayed in Figure 10.1 to help readers readily identify them and visualize their interconnections.

Key components of the climate change denial machine.

2 Major Actors

2.1 fossil fuels industry and corporate america.

Coal and oil corporations recognized the implications of global warming and efforts to combat it for their industries early on, as burning fossil fuels was quickly identified as a major source of greenhouse gas emissions. Not surprisingly, therefore, the fossil fuels industry pioneered the charge against climate science and policy making (Begley 2007 ; Gelbspan 1997 ; Goodell 2007 ). Both individual corporations such as ExxonMobil and Peabody Coal as well as industry associations such as the American Petroleum Institute, Western Fuels Association, and Edison Electric Institute provided funding for individual contrarian scientists, conservative think tanks active in climate change denial, and a host of front groups we discuss below. ExxonMobil 5 has long been the leading contributor to think tanks and front groups involved in climate change denial, although it cut back somewhat in recent years in response to negative publicity and severe criticism (Mooney 2005 ; Union of Concerned Scientists 2007 ).

The efforts of fossil fuels corporations and industry associations to combat climate science and policy making were quickly supplemented by those of numerous energy companies (e.g. Southern Company), other resource‐based corporations in the steel, forestry, and mining industries as well as their associations (e.g. National Mining Association), numerous manufacturing companies such as automobile corporations (e.g. Chrysler, Ford, and General Motors), and large national associations such as the National Association of Manufacturers and the US Chamber of Commerce (Gelbspan 1997 , 2004 ; Hoggan with Littlemore 2009 ; Layzer 2007 ). Thus, in the early 1990s it appeared that much of corporate America was lining up against climate science and policy making, with the IPCC being the crucial target.

The growing evidence of anthropogenic climate change reported in the IPCC's Second Assessment Report in 1995 and the adoption of the Kyoto Protocol at the 1997 Kyoto Conference led to some fracturing within the business community, and several corporations including BP announced that they no longer questioned the reality of ACC and were halting efforts to undermine climate science. Several oil companies and other major corporations joined with leading environmental organizations to form the US Climate Action Partnership, and it appeared that a major segment of corporate America was ready to accept the reality of climate change and the inevitability of carbon reduction policies (Kolk and Levy 2001 ; Layzer 2007 ). However, with the inauguration of the George W. Bush Administration, which institutionalized climate change denial in the federal government (McCright and Dunlap 2010 ), the fossil fuels industry in particular had little to fear.

The election of Barack Obama and a Democratic majority in both houses of Congress has made the reality of legislation to limit carbon emissions salient, and the result has been enormous corporate lobbying to oppose or weaken the various measures introduced in the House and Senate as well as international efforts such as COP‐15 in Copenhagen (Goodell 2010 ; Pooley 2010 ). This lobbying has been accompanied by escalating attacks on climate science and scientists as well as the IPCC, with considerable support from corporations such as ExxonMobil and associations such as the US Chamber of Commerce (Greenpeace 2010a ; Mashey 2010 ). Thus, while there are divisions within corporate America over policy proposals such as ‘cap‐and‐trade,’ it appears that significant portions of it remain active in climate change denial.

2.2 Conservative Philanthropists, Foundations, and Think Tanks

The earlier‐mentioned conservative resurgence began when wealthy conservative philanthropists such as Joseph Coors began to fund, typically through their family foundations, the establishment of conservative think tanks (CTTs) such as the Heritage Foundation to wage a ‘war of ideas’ against the progressive gains of the 1960s (Himmelstein 1990 ; Lapham 2004 ). By the 1990s conservative foundations were funding a ‘conservative labyrinth’ designed to implant conservative values and goals in academic, media, governmental, legal, and religious institutions (Covington 1997 : 3). Particularly important is the network of well‐heeled and influential think tanks that churn out an endless flow of policy proposals credited with moving the US policy agenda significantly to the right (Krehely et al. 2004 ) and—since the 1990s—influencing climate policy (McCright and Dunlap 2003 , 2010 ).

Major funders include foundations controlled by Richard Mellon Scaife and David and Charles Koch (both drawing upon family fortunes stemming in part from oil interests). Besides giving generously to a vast range of CTTs and conservative causes, they are responsible for establishing the Cato Institute (C. Koch), Citizens for a Sound Economy, now Americans for Prosperity (D. Koch) and Committee for a Constructive Tomorrow or CFACT (R. M. Scaife)—three particularly crucial elements of the denial machine. In fact, in recent years the Scaife and Koch families of funds may have exceeded ExxonMobil in terms of funding climate change denial actors and activities (Grandia 2009 ; Greenpeace 2010b ; Mashey 2010 ).

CTTs represent ‘social movement organizations’ that typically serve as spokespersons and facilitators for conservative causes, and share a universal commitment to free enterprise, limited government, and the promotion of unfettered economic growth (Jacques et al. 2008 ; McCright and Dunlap 2000 ). While corporations like ExxonMobil have joined conservative foundations in providing generous funding for CTTs, many of the latter appear to oppose climate science and policy making for purely ideological reasons (McCright and Dunlap 2010 : 109–11), and some of their leaders have criticized corporations for disengaging from climate change denial (Layzer 2007 : 112). CTTs involved in climate change denial range from large, multi‐issue ones (e.g. the Heritage Foundation and American Enterprise Institute), to medium ones with a strong interest in environmental/climate issues (e.g. George Marshall Institute and the Heartland Institute), to small shops currently dedicated to climate change denial (e.g. Fred Singer's Science and Environmental Policy Project and Republican operative Robert Ferguson's Science and Public Policy Institute) (Mashey 2010 ; McCright and Dunlap 2003 ).

CTTs are a fundamental and highly effective component of the denial machine, providing institutional bases for leading contrarians such as Patrick Michaels (a Cato Fellow), hosting anti‐IPCC conferences (Heartland Institute), sponsoring ‘educational events’ for politicians (National Center for Policy Analysis), assisting the George W. Bush Administration's efforts to impede climate policy (Competitive Enterprise Institute), and producing and circulating a vast range of anti‐climate change material via various forms of media (reports, press releases, press conferences, videos, radio and television interviews), among other activities (see e.g. Hoggan with Littlemore 2009 ; Lahsen 2008 ; McCright and Dunlap 2000 , 2003 ; Oreskes and Conway 2010 ).

More generally, CTTs help shield the efforts of corporations and philanthropists to combat climate change policy, as for example ExxonMobil, the Koch brothers, and R. M. Scaife support contrarian scientists and denial campaigns effectively but ‘discreetly’ by funneling millions into think tanks that sponsor the contrarians and organize the campaigns (Greenpeace 2010b ; Mashey 2010 ; Union of Concerned Scientists 2007 ). 6 Furthermore, CTTs have been successful in marketing themselves as objective sources of information, basically an alternate academia, and thus they have more credibility with much of the public, many media outlets, and some policy makers than do corporations (Jacques et al. 2008 ). They enhance their credibility by sponsoring contrarian scientists who are treated as ‘experts’ (regardless of the relevance or quality of their research records) by the media and public, and whose ideas are amplified considerably by CTTs' media access (Hoggan with Littlemore 2009 ; McCright and Dunlap 2000 , 2003 ; Mooney 2005 ; Oreskes and Conway 2010 ). Finally, CTTs work carefully with corporate America to set up a maze of front groups and astroturf campaigns to combat climate science and policy making.

2.3 Front Groups

Most corporations prefer to shield their anti‐environmental activities from public scrutiny, and creating front groups that act on their behalf is one way to do this. The Global Climate Coalition (GCC), formed in 1989 in reaction to establishment of the IPCC, was an early front group designed to combat evidence of climate change and climate policy making. Sponsored by oil companies (ExxonMobil, Texaco, and BP), automobile manufacturers (Chrysler, Ford, and GM) and industrial associations such as the American Petroleum Institute (API), US Chamber of Commerce, and the National Association of Manufacturers, it was originally led by William O'Keefe of API. The GCC was very active in opposing US ratification of the Kyoto Protocol, running television ads against it, and played a critical role in launching a vicious (and unfounded) attack on climate scientist Benjamin Santer for allegedly altering a chapter in the 1995 IPCC report in an effort to discredit the entire report and the IPCC (Gelbspan 2004 : 78–80; Oreskes and Conway 2010 : 207–13). The accumulating scientific evidence in support of climate change led BP, Shell, and other companies to leave the GCC in the late 1990s, presumably because they no longer wanted to be associated with its aggressive and highly visible opposition to climate science and policy. The GCC disbanded in 2002, confident that its goals were shared by the George W. Bush Administration (Gelbspan 2004 ; Greenpeace 2010a ; Pooley 2010 ).

The Information Council on the Environment (ICE) was created in 1991 by coal and utility interests, including the National Coal Association, Western Fuels Association, and Edison Electric Institute, and launched a campaign to ‘reposition global warming as a theory (not fact)’ (Pooley 2010 : 41). Assisted by contrarian scientists such as Patrick Michaels, Robert Balling, and Sherwood Idso, ICE ran a media campaign designed to denigrate the notion of global warming and campaigned against US agreement to mandatory greenhouse gas emissions at the 1992 Earth Summit in Rio. ICE folded up when its strategic plans were leaked to the press, but the Western Fuels Association subsequently established the Greening Earth Society in 1998 to promote the idea that CO 2 was good for the environment and thus global warming was to be welcomed. Besides an advertising campaign, it sponsored a quarterly World Climate Review edited by contrarian Patrick Michaels, which has been replaced by the World Climate Report blog also edited by Michaels but with unknown sources of support (Gelbspan 2004 ; Hoggan with Littlemore 2009 ; Pooley 2010 ). 7

The Cooler Heads Coalition (CHC) is the final major US front group for climate change denial, and unlike its predecessors its membership consists primarily of CTTs including CFACT, the Marshall Institute, the Heartland Institute, and the Competitive Enterprise Institute (CEI)—who, of course, receive significant corporate and conservative foundation funding. It emerged in 1997 as a subgroup of the National Consumer Coalition, a project of Consumer Alert—an industry‐funded entity founded in 1977 to oppose consumer protection regulations such as mandatory seatbelts. It is tied closely to CEI, which hosts its website 〈 www.globalwarming.org 〉, where CHC is described as ‘an informal and ad‐hoc group focused on dispelling the myths of global warming.’ CHC/CEI leaders Myron Ebell and Christopher Horner are central figures in the denial machine, and use both CHC and CEI to distribute a flood of denial material, host press conferences and Congressional briefings, and amplify the voices of contrarian scientists (Hoggan with Littlemore 2009 ; Mooney 2005 ; Pooley 2010 ). They have played a crucial role in promoting ‘Climategate’ and waging war on the IPCC, and often launch malicious attacks on individual climate scientists.

2.4 Contrarian Scientists

From the earliest stages of climate change denial the fossil fuels industry and conservative think tanks, and their fronts groups like GCC, recognized the importance of employing credentialed scientists to manufacture uncertainty concerning climate change (building on the tobacco industry's success with this strategy—Oreskes and Conway 2010 ), and they readily found scientists who were eager to assist (Gelbspan 1997 ; McCright 2007 ). Some had expertise relevant to climate science (e.g. Patrick Michaels and Fred Singer), but many did not. For instance, the George C. Marshall Institute was established by a trio of prominent physicists who, despite having no expertise in climate science per se, quickly made climate change denial a central mission of the Institute and created a magnet that eventually attracted several contrarians, such as Roy Spencer, who do have climate science expertise (Lahsen 2008 ; Oreskes and Conway 2010 ).

It is impossible to discern whether contrarian scientists sought affiliations with CTTs (and front groups) or were solicited by them, but at this point most of the highly visible contrarians have some form of affiliation with CTTs, such as: having formal appointments like Patrick Michaels at the Cato Institute; serving on boards, as scientific advisors, or as affiliated experts; giving talks at the CTTs and participating in CTT press conferences, political briefings, and public lectures; and especially publishing material for CTTs (McCright and Dunlap 2000 , 2003 ). 8 Being affiliated with CTTs enables contrarians to avoid the ‘stigma’ of being directly linked to fossil fuels corporations (see e.g. Gelbspan 1997 : 41), while still benefiting from the industry's largesse to many CTTs (Mashey 2010 ; Union of Concerned Scients 2007 ).

The strong bond between contrarian scientists and CTTs reflects the staunch conservative aversion to governmental regulations and commitment to free markets shared by nearly all leading contrarian scientists (Oreskes and Conway 2010 ). It may also reflect contrarians' realization that their marginal standing within mainstream climate science (Anderegg et al. 2010 ) can be offset by moving into the public and policy spheres where their messages are greatly amplified by their very influential CTT sponsors and often welcomed by journalists eager to provide ‘balanced’ reporting (Boykoff and Boykoff 2004 ; McCright 2007 ; McCright and Dunlap 2003 ).

As climate change denial has matured, the number of ‘scientists’ who promote it has grown both in size and diversity (as well as spread internationally). CTTs and fossil‐fuels front groups, in particular, now sponsor a multitude of ‘experts’ who often have no discernible credibility as climate scientists. An increasing number of their spokespersons appear to lack any scientific training or expertise, such as the ubiquitous Christopher Walter Monckton (aka Lord Monckton) who is affiliated with the Science and Public Policy Institute in the US. However, manufacturing uncertainty is most successful when it is done by individuals that the media and public will accept as experts, and CTTs continue to find and support a number of credentialled scientists critical of climate science, giving them unprecedented visibility regardless of how poorly their typically non‐peer‐reviewed work fares among the scientific community (see e.g. Enting 2010 on one example). Indeed, Monbiot's ( 2007 ) characterization of the ‘denial industry’ reflects the fact that climate change denial now offers the possibility of a rewarding ‘career’ for contrarian scientists and others eager to work with CTTs, front groups, and conservative media.

2.5 Conservative Media

The influence of the conservative media or ‘echo chamber’ has been well documented and has been credited with helping move the US rightward in recent decades (e.g. Jamieson and Cappella 2008 ). For right‐wing talk radio commentators, most notably Rush Limbaugh, attacks on ‘environmental wackos’ is standard fare, and climate change (and Al Gore) a favorite target (Nature 2010b ; Wolcott 2007 ). Perhaps exceeding the impact of the right‐wing dominance of talk radio is Rupert Murdoch's Fox News, as both its reporters and most popular commentators (Glenn Beck, Bill O'Reilly, and Sean Hannity) consistently denigrate climate change by, for example, highlighting ‘Climategate’ and critiques of the IPCC and providing frequent opportunities for contrarian scientists and CTT representatives to disparage climate change, the IPCC, and climate scientists.

The conservative media assault on climate science also occurs in print media, especially conservative newspapers such as the Murdoch‐owned Wall Street Journal (whose editorial pages have become a regular forum for climate change denial, including columns by contrarian scientists) and the New York Post and the Reverend Moon's Washington Times . Climate change denial is also a regular feature in leading conservative magazines such as The Weekly Standard , National Review , and The American Spectator as well as online publications such as The American Thinker . Add in prominent conservative columnists like George Will and Charles Krauthammer (infamous for their erroneous statements about climate change—Dickinson 2010 ), who reach vast newspaper audiences via national syndication, and the result is a barrage of assaults on climate science (and, increasingly, climate scientists) that not only inundates committed conservative audiences but also reaches a large segment of the general public. Conservative media consistently present contrarian scientists and CTT representatives as ‘objective’ experts, in stark contrast to their portrayal of scientists working with the IPCC as self‐interested and biased, further magnifying the influence of the former relative to the latter.

In recent years these conservative media outlets have been supplemented (and to some degree supplanted) by the conservative blogosphere, and numerous blogs now constitute a vital element of the denial machine. While a few are hosted by contrarian scientists (most notably Roy Spencer), the most popular North American blogs are run by a retired TV meteorologist (wattsupwiththat.com), a retired mining executive and dedicated critic of the ‘hockey stick’ model of historical climate trends (climateaudit.org), and a self‐styled ‘warrior’ in the climate wars (climatedepot.com). The latter individual, Marc Morano, exemplifies the deep roots of climate change denial in conservative circles. Before setting up Climate Depot, which is modeled on the popular right‐wing ‘Drudge Report’ and supported by R. M. Scaife's CFACT, Morano—who has a BA degree in political science—worked for Rush Limbaugh, right‐wing Cybercast News Service (where he played a key role in the ‘swift‐boat’ campaign against 2004 Democratic Presidential candidate John Kerry), and then for Republican Senator James Inhofe (Dickinson 2010 ; Harkinson 2009b ).

Having this powerful, pervasive, and multifaceted media apparatus at its service provides the denial machine with a highly effective means of spreading its message, as reflected quite recently by its success in turning a tiny and highly unrepresentative sample of thirteen years worth of personal e‐mails hacked from the Climate Research Unit at the University of East Anglia into a major scandal that has generated a decline in public belief in climate change and trust in climate scientists (see Leiserowitz et al. 2010 on public opinion and Greenpeace 2010b on the role of Koch‐funded actors in publicizing Climategate)—despite the fact that several investigations have concluded that the e‐mails neither demonstrate unethical behavior nor undermine climate science (Young 2010 ).

2.6 Conservative Politicians

Most conservative politicians have been highly skeptical of climate change from the outset, as accepting its reality challenges their faith in inevitable progress created by the free market and raises the specter of increased governmental regulations. Republicans in Congress have been eager hosts of contrarian scientists, CTT spokespersons, and a raft of other non‐credentialed deniers from novelist Michael Crichton (whose State of Fear portrayed climate change as a contrived plot) to, most recently, Lord Monckton. They have also called hearings to rebut and in some instances harass mainstream climate scientists. The most notable include the 1994–5 House of Representatives hearings called by California Republican Dana Rohrbacher devised to portray evidence for dioxin, ozone depletion, and global warming as ‘junk science’ (McCright and Dunlap 2003 : 361), and a 2005 House hearing held by Texas Republican Joe Barton designed to disprove the hockey stick model of Mann, Bradley, and Hughes and thereby discredit the IPCC (Mashey 2010 ). 9

The single most prominent Republican when it comes to climate change denial is Oklahoma Senator James Inhofe, famous for claiming in a Senate speech that global warming is ‘the greatest hoax ever perpetrated on the American people.’ When Inhofe was Chair of the Committee on Environment and Public Works he turned it into a bastion of climate change denial via its website run by Marc Morano and his frequent invitations to contrarian scientists to testify at Committee hearings (McCright and Dunlap 2010 ). More recently he has called for a criminal investigation of leading climate scientists (Nature 2010a ). The ease with which Inhofe and his Republican colleagues gain access to conservative media like Fox News provides yet another means for amplifying the messages of contrarian scientists in the conservative echo chamber.

The inauguration of George W. Bush institutionalized climate change denial throughout the most powerful branch of the US government, allowing representatives of the fossil fuels industry and CTTs to undermine climate science and policy from within the administration. For eight years the Bush administration used a variety of techniques, ranging from emphasizing the ‘uncertainty’ of climate science and calling for ‘sound science’ to suppressing the work of governmental scientists, to justify inaction on climate policy (McCright and Dunlap 2010 ). By the time it was replaced by the Obama Administration, most Republican politicians had followed its lead in questioning the seriousness of climate change. The predictable upsurge in denial activism and lobbying against climate policy that has occurred following the change in administrations, especially the embrace of denialism among the more extreme elements of the Right (e.g. Tea Party supporters), has turned climate change denial into a litmus test for Republicans (Johnson 2010 ). As a consequence, even one‐time sponsors of bipartisan climate legislation like Republican Senators John McCain and Lindsey Graham have had to back‐pedal to appease Republican interest groups and supporters.

2.7 Astroturf Groups and Campaigns

The defining feature of astroturf groups is that they are generated by an industry, think tank, or front group, but disguised to appear as a spontaneous, popular ‘grassroots’ effort. They are created to lobby or campaign on behalf of their sponsors, who hope to remain hidden from view (Beder 1998 ). Front groups and PR firms typically play key roles, and are often inseparable from the astroturf group/campaign itself, the key distinction being that the former tend to last longer while astroturf efforts come and go in response to specific events and policies. The use of astroturf groups has flourished in the Obama era, being used to oppose healthcare reform and other progressive goals of the President and Democratic Congress. Especially important are the roles played by the Koch‐funded Americans for Prosperity and FreedomWorks front groups in generating a significant portion of the ‘Tea Party’ and encouraging it to focus on climate change (Dickinson 2010 ; Goodell 2010 ; Pooley 2010 ).

For example, Americans for Prosperity sponsored a multi‐state ‘Hot Air Tour’ in 2008 with the slogan, ‘Global Warming Alarmism: Lost Jobs, Higher Taxes, Less Freedom,’ while FreedomWorks played a major role in promoting the 2009 rallies against climate legislation in about twenty states that were ‘officially’ sponsored by ‘Energy Citizens’—an astroturf group created by the American Petroleum Institute (API). While its website proclaims that Energy Citizens ‘is a movement made up of tens of thousands of Americans,’ API President Jack Gerard's memo to API member corporations urged them to provide ‘strong support for employee participation at the rallies’ and asked that his (inevitably leaked) memo be treated as ‘sensitive information’ because ‘we don't want critics to know our game plan’ (Dickinson 2010 ; Goodell 2010 ). 10

More generally, the success of Americans for Prosperity and Freedom Works along with CFACT and other conservative organizations and spokespersons (e.g. Glenn Beck) in melding climate change denial into the faux populist rage of the Tea Partiers has put climate science squarely in the sights of right‐wing extremists, which has no doubt contributed to the escalating attacks against climate scientists (Hickman 2010 ). As Levy ( 2010 : 4) states, ‘Tea Party activism has elevated climate change to the status of a litmus test of cultural politics in the U.S., up there with abortion, guns, god, gays, immigration and taxes.’ This raises the politicization of climate change/science (Dunlap and McCright 2008 ) to a new level and into a treacherous domain. 11 While the entire denial machine (but particularly the Kochs and their operatives) has contributed to this ‘accomplishment,’ it epitomizes successful astroturfing.

2.8 International Diffusion of Climate Change Denial

We have concentrated on the US because it is where climate change denial was born and continues to be most active, but denialism has spread to other nations—often with some degree of assistance from American actors. It tends to be strongest in nations that currently have or have recently had conservative governments and in which CTTs are firmly planted, notably the UK, Canada, and Australia, reinforcing our claim that free‐market conservatism (with the strong support of the fossil fuels industry in the latter two countries) is the unifying force behind climate change denial. The UK's International Policy Network and its affiliate the Institute of Economic Affairs, Canada's Fraser Institute, and Australia's Institute of Public Affairs, for example, have provided early and continuing support for contrarian scientists and others active in climate change denial in their respective nations (Hamilton 2010 ; Hoggan with Littlemore 2009 ; Monbiot 2007 ).

In addition, one finds a similar emphasis on the creation of a web of front groups to act on behalf of industry and think tanks, perhaps best exemplified by Australia. There the Institute of Public Affairs (a free‐market think tank) created in 2005 the Australian Environment Foundation (to mimic the pro‐environmental Australian Conservation Foundation), which in turn set up the Australian Climate Science Coalition to promote climate change denial. These organizations are complemented by the Lavoisier Group, funded heavily by mining interests, which focuses specifically on climate change. Most leading Australian contrarian scientists such as Robert Carter, William Kininmonth, Garth Paltridge, and Ian Plimer are connected in some fashion to these organizations, which are also active in bringing American contrarians to Australia. In fact, the US denial machine was very active in helping establish its counterpart in Australia. Contrarians such as Fred Singer and Patrick Michaels visited there early on, and in the mid‐1990s the Competitive Enterprise Institute recognized that Australia's Howard Government could become a valuable ally in opposing the Kyoto Protocol and began to coordinate efforts with the Institute for Public Affairs and mining interests (Hamilton 2007 ; Climate Action Network Australia 2010 ).

Climate change denial is now spreading far beyond the US, UK, Canada, and Australia, and once again this is directly due to the efforts of crucial CTTs to diffuse their goals and influence internationally. In particular, the Atlas Economic Research Foundation (established by Sir Anthony Fisher of the UK, but based in the US) serves as an ‘incubator’ for free‐market think tanks around the world, and is credited with helping plant them in several dozen nations where they are frequently active in climate change denial. Canada's Fraser Institute (which receives funding from Koch and Scaife foundations) has a similar international reach with its Economic Freedom Network having affiliates in scores of nations, many helping spread climate change denial. And finally, in 2007 Fisher's UK‐based International Policy Network created the ‘Civil Society Coalition on Climate Change’ which consists of ‘independent civil society organizations’ in forty nations committed to denying the reality of climate change (Harkinson 2009a ).

As Harkinson ( 2009a : 1) puts it, ‘With US‐backed overseas think tanks parroting denier talking points in dozens of languages, the echo chamber is already up and running.’ In sum, we are witnessing the globalization of organized climate change denial, and this does not bode well for the future of climate science and especially for effective international action and policy making to deal with the reality of climate change.

3 Conclusion

Many factors influence both national and international policy‐making on environmental (and other) issues (Dryzek et al. 2002 ). We are definitely not suggesting that organized climate change denial has been the sole factor in undermining efforts to develop domestic climate policies in nations such as the US, Australia, and Canada where it has been especially prominent, nor at the international level where diverging national interests are obviously a major obstacle (Parks and Roberts 2010 ). Nonetheless, it is reasonable to conclude that climate change denial campaigns in the US have played a crucial role in blocking domestic legislation and contributing to the US becoming an impediment to international policy making (McCright and Dunlap 2003 ; Pooley 2010 ). The financial and organizational resources and political and public relations expertise available to and embodied in the major components of this machine, and the various actors' ability to coordinate efforts and reinforce one another's impacts, have certainly had a profound effect on the way in which climate change is perceived, discussed, and increasingly debated—particularly within the US.

We have argued that because of the perceived threat posed by climate change to their interests, actors in the denial machine have strived to undermine scientific evidence documenting its reality and seriousness. Over the past two decades they have engaged in an escalating assault on climate science and scientists, and in recent years on core scientific practices, institutions, and knowledge. Their success in these efforts not only threatens our capacity to understand and monitor human‐induced ecological disruptions from the local to global levels (Hanson 2010 ), but it also weakens an essential component of societal reflexivity when the need for the latter is greater than ever.

The actions of those who consistently seek to deny the seriousness of climate change make the terms ‘denial’ and ‘denier’ more accurate than ‘skepticism’ and ‘skeptic’ (Diethelm and McKee 2009 ), particularly since all scientists tend to be skeptics (Schneider 2010 : 205). We will, however, refer to scientists involved in the denial machine as ‘contrarians.’ For an alternative but complementary use of ‘denial’ see Kari Norgaard's chapter in this volume.

This may be somewhat less true of contrarian scientists, but the few examples of self‐professed liberals active in climate change denial such as Freeman Dyson are clearly exceptions to the rule (Larson and Keating 2010 ).

For overviews that provide clear time‐lines for the historical evolution of climate change denial see Greenpeace ( 2010a ) and Mashey ( 2010 ).

The explicit merger of science and policy making within the IPCC has contributed to climate science and climate scientists, along with the IPCC, becoming targets for those fearful that strong evidence of climate change will lead to national and international regulations on carbon emissions that create restrictions on corporate behavior, free markets, and economic growth (Corfee‐Morlott et al. 2007 ).

Exxon merged with Mobil to become ExxonMobil in 1999, and other oil companies have merged and/or changed their names (e.g. British Petroleum became BP) in the past two decades. To avoid confusion, we will employ the current names even when describing activities undertaken by earlier versions of the contemporary corporations.

Only recently have the links between the Koch brothers and right‐wing activities, including the Tea Party and climate change denial, been publicized (Greenpeace 2010b ; Mayer 2010 ).

Another important coal‐based front group, the Center for Energy and Economic Development, and its offshoots Americans for Balanced Energy Choices and American Coalition for Clean Coal Energy, have also supported climate change denial; however, their primary focus has been on lobbying against climate legislation by generating phony citizens' or astroturf (see below) campaigns (see Hoggan with Littlemore 2009 and especially Pooley 2010 ).

While the activities of a number of contrarian scientists are discussed in Begley ( 2007 ), Gelbspan ( 1997 , 2004 ), Mooney ( 2005 ), and Oreskes and Conway ( 2010 ), individuals seeking detailed information on the CTT affiliations of leading contrarians should consult Greenpeace's website detailing connections between ExxonMobil and CTTs and contrarians (〈 http://www.exxonsecrets.org 〉), the data base created by James Hoggan and colleagues at their Desmogblog website (〈 http://www.desmogblog.com/global‐warming‐denier‐database 〉), or John Mashey's highly detailed report (Mashey 2010 ).

Mashey ( 2010 ) provides evidence suggesting that the Competitive Enterprise Institute and the Marshall Institute played a role in stimulating Barton's hearing by promoting the efforts of Canadians Stephen McIntyre and Ross McKitrick to critique the work of Michael Mann and his colleagues.

The leaked memo is trivial compared to an earlier API embarrassment: a 1998 ‘Global Climate Science Communication Action Plan’ developed at a meeting of leading figures in the denial machine hosted by API was made public by Greenpeace. The document laid out a detailed astroturfing strategy (involving contrarian scientists) and suggested that ‘Victory will be achieved when average citizens understand (recognize) uncertainties in climate science…, media [does the same], and those promoting the Kyoto treaty on the basis of extant science appear to be out of touch with reality’ (Greenpeace 2010a : 9; Hoggan with Littlemore 2009 : 42–5).

Readers are encouraged to read the ‘comments’ on various denial websites particularly in response to posts about climate scientists to get a sense of the vitriol aimed at the latter.

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February 2, 2024

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Why are people climate change deniers? Study reveals unexpected results

by University of Bonn

Do climate change deniers bend the facts to avoid having to modify their environmentally harmful behavior? Researchers from the University of Bonn and the Institute of Labor Economics (IZA) ran an online experiment involving 4,000 US adults, and found no evidence to support this idea. The authors of the study were themselves surprised by the results. Whether they are good or bad news for the fight against global heating remains to be seen. The study is published in the journal Nature Climate Change .

A surprisingly large number of people still downplay the impact of climate change or deny that it is primarily a product of human activity. But why? One hypothesis is that these misconceptions are rooted in a specific form of self-deception, namely that people simply find it easier to live with their own climate failings if they do not believe that things will actually get all that bad.

"We call this thought process 'motivated reasoning,'" says Professor Florian Zimmermann, an economist at the University of Bonn and Research Director at IZA.

Motivated reasoning helps us to justify our behavior. For instance, someone who flies off on holiday several times a year can give themselves the excuse that the plane would still be taking off without them, or that just one flight will not make any difference, or—more to the point—that nobody has proven the existence of human-made climate change anyway. All these patterns of argument are examples of motivated reasoning. Bending the facts until it allows us to maintain a positive image of ourselves while maintaining our harmful behavior.

Self-deception to preserve a positive self-image

But what role does this form of self-deception play in how people think about climate change? Previously, there had been little scientific evidence produced to answer the question. The latest study has now closed this knowledge gap—and has thrown up some unexpected results. Zimmermann and his colleague Lasse Stötzer ran a series of online experiments, using a representative sample of 4,000 US adults.

At the center of the experiments was a donation worth $20. Participants were allocated at random to one of two groups. The members of the first group were able to split the $20 between two organizations, both of which were committed to combating climate change. By contrast, those in the second group could decide to keep the $20 for themselves instead of giving it away and would then actually receive the money at the end.

"Anyone keeping hold of the donation needs to justify it to themselves," says Zimmermann, who is also a member of the ECONtribute Cluster of Excellence, the Collaborative Research Center Transregio 224 and the Transdisciplinary Research Area Individuals & Societies at the University of Bonn. "One way to do that is to deny the existence of climate change."

As it happened, nearly half of those in the second group decided to hold on to the money. The researchers now wanted to know whether these individuals would justify their decision retrospectively by repudiating climate change. The two groups had been put together at random. Without "motivated reasoning," therefore, they should essentially share a similar attitude to human-made global heating. If those who kept the money for themselves justified their actions through self-deception, however, then their group should exhibit greater doubt over climate change.

"Yet we didn't see any sign of that effect," Zimmermann reveals.

Climate change denial: A hallmark of one's identity?

This finding was also borne out in two further experiments.

"In other words, our study didn't give us any indications that the widespread misconceptions regarding climate change are due to this kind of self-deception," says Zimmermann, summing up his work. On the face of it, this is good news for policymakers, because the results could mean that it is indeed possible to correct climate change misconceptions, simply by providing comprehensive information. If people are bending reality, by contrast, then this approach is very much a non-starter.

Zimmermann advises caution, however, stating, "Our data does reveal some indications of a variant of motivated reasoning, specifically that denying the existence of human-made global heating forms part of the political identity of certain groups of people."

Put another way, some people may to an extent define themselves by the very fact that they do not believe in climate change. As far as they are concerned, this way of thinking is an important trait that sets them apart from other political groups , and thus they are likely to simply not care what researchers have to say on the topic.

Journal information: Nature Climate Change

Provided by University of Bonn

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Geoffrey Supran, who co-authored a research paper on ExxonMobil’s climate disinformation campaign in 2017, discusses current House investigation into the company’s disinformation.

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Tracing Big Oil’s PR war to delay action on climate change

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Harvard researchers chart evolution from denial to misdirection as House inquiry widens

The U.S. House of Representatives’ Oversight Committee earlier this month widened its inquiry into the oil industry’s role in fostering doubt about the role of fossil fuels in causing climate change. A letter from the panel to Darren Woods, ExxonMobil chief executive, said lawmakers were “concerned that to protect … profits, the industry has reportedly led a coordinated effort to spread disinformation to mislead the public and prevent crucial action to address climate change.” The Gazette spoke with Geoffrey Supran , a research fellow in the History of Science, who, together with Naomi Oreskes , the Henry Charles Lea Professor of the History of Science, published a series of studies in recent years, the most recent one in May, on the climate communications of ExxonMobil, one of the world’s biggest oil and gas companies.

Geoffrey Supran

GAZETTE: Tell me about your research on the oil and gas industry’s role in spreading climate disinformation.

SUPRAN: In 2017, I and Naomi Oreskes published a series of three papers focused on what you might call traditional climate-science denial by ExxonMobil. Then, in May of this year, we shifted gears slightly, releasing a new study looking at the company’s more subtle forms of climate propaganda.

GAZETTE: What kinds of issues do you suspect the House committee will find?

SUPRAN: In 2017, our research was the first peer-reviewed analysis of ExxonMobil’s 40-year history of climate-change communications. And what we discovered was that there were systematic discrepancies between, on the one hand, what Exxon and ExxonMobil scientists said about climate-science privately and in academic circles, versus what Exxon, Mobil, and ExxonMobil said to the general public in The New York Times and elsewhere. That analysis showed that ExxonMobil misled the public about basic climate science and its implications. They did so by contributing quietly to climate science, and loudly to promoting doubt about that science.

Our work and others’ in that area provides evidence for the committee, demonstrating ExxonMobil’s long history of attacking science and scientists in order to undermine and delay climate action. Our more recent work, this May, is an evolution of that study in that it focuses on how, beyond outright disinformation, ExxonMobil has used language to subtly but systematically shape the way the public thinks about climate change, often in misleading ways. That study demonstrates how the company has selectively emphasized some terms and topics in public while consistently avoiding others.

The takeaway message across all of our work is that over and over, ExxonMobil has misled the public about climate change by telling the public one thing and then saying and doing the opposite behind closed doors. Our latest work shows that while their tactics have evolved from outright, blatant climate denial to more subtle forms of lobbying and propaganda, their end goal remains the same. And that’s to stop action on climate change.

GAZETTE:  So according to your findings, within the walls of ExxonMobil there was never any doubt about climate science. Is that right?

SUPRAN: Right, there was never the undue doubt that they promoted in public. In fact, behind closed doors and in academic circles, Exxon has known that its products would likely cause dangerous global warming since at least the 1970s. By way of its trade association, the American Petroleum Institute, the oil industry as a whole has been on notice even longer — since the 1950s.

Naomi Oreskes (pictured) and Geoffrey Supran’s new study looks at ExxonMobil’s subtle forms of climate propaganda.

Rose Lincoln/Harvard file photo

GAZETTE:  What was the most disturbing finding from this hard look at ExxonMobil’s communications?

SUPRAN: A key contribution of our work has been demonstrating the systematic and statistically significant bias of ExxonMobil’s public communications toward denial and delay. But the most uncomfortable realization is how subtle and systematic and increasingly sophisticated their propaganda has become.

In our most recent work, we’ve had to rely on statistical techniques from computational linguistics to uncover patterns of speech hiding in plain sight. These include a systematic fixation on consumer energy demand rather than on the fossil fuels that the company supplies and the systematic representation of climate change as a “risk” rather than a reality. These are subtle patterns that, we’ve now realized, have been systematically embedded into climate discourse by ExxonMobil and other fossil fuel interests.

That’s particularly discomforting, because when you start to pull back the curtain you see just how sophisticated the oil industry’s propaganda machine has been, how easily their rhetoric has snuck into people’s consciousness and biased the way the public thinks about this. Mobil’s vice president and pioneer of PR in the ’70s and ’80s literally talked about what he called “semantic infiltration.” He called it “the process whereby language does the dirty work of politics.” And he said that the first “general principle” of PR was to, quote, “grab the good words … while sticking your opponents with the bad ones.” Our research now shows that’s exactly what they’ve been up to for decades.

GAZETTE: Have the oil companies stopped outright denying climate change? The subtle approach you talk about, is that all they’re doing now?

SUPRAN: From the mid-2000s through to the 2010s, ExxonMobil and other fossil-fuel companies gradually “evolved” their language, in the words of one ExxonMobil manager, from blatant climate denial to these more subtle and insidious forms of delayism. Another ExxonMobil manager described the effort by former company chairman and chief executiveRex Tillerson in the mid-2000s as an effort to “carefully reset” the company’s profile on climate change so that it would be “more sustainable and less exposed.” They did so by drawing straight from the tobacco industry’s playbook of threading a very fine rhetorical needle, using language about climate change just strong enough to be able to deny that they haven’t warned the public, but weak enough to exculpate them from charges of having marketed a deadly product.

So while their outright denial has tapered off, their propaganda hasn’t stopped. It’s in fact shifted into high gear and is now operating with a sophistication that we’ve never seen before. In our recent study, I mentioned the rhetoric of risk and individualized responsibility, but we also identified systematic use of language indicative of other what we call “discourses of delay,” such as greenwashing, fossil-fuel solutionism, technological optimism, and so on. These are now pervasive in industry marketing and, in turn, in the ways that the public and policymakers think and talk about the climate crisis.

To give just one example, did you know that the very notion of a personal carbon footprint — a concept that’s completely ubiquitous in discussions about personal responsibility — was first popularized by BP as part of a $100 million per year marketing campaign between 2004 and 2006?

They’ve also upgraded their tactics, moving from print advertorials to digital advertorials and microtargeted social media. Digital advertorials are ads presented to appear in the style of newspapers online and made for the oil companies by the newspapers themselves. They are the direct digital descendant of the print advertorials that Mobil pioneered in the ’70s through the 2000s, in part with their climate messaging.

“The takeaway message across all of our work is that over and over, ExxonMobil has misled the public about climate change by telling the public one thing and then saying and doing the opposite behind closed doors.”

GAZETTE:  Did we get a sense as to how this happens? Are there company memos about phrasing and language, that kind of thing? Or is it still opaque?

SUPRAN: Proving intent is generally nontrivial, but all signs point to “Yes.” In terms of outright climate denial, we have smoking-gun documents that lay out in black and white Exxon’s intentions from the ’80s and ’90s to, in their words, “emphasize the uncertainty,” “extend the science,” and so on. In terms of delayism, we know, for example, that in 1981, Mobil internally reviewed its PR campaigns from the previous decade and celebrated how their advertorials in The New York Times had allowed them to become part of what they called “the collective unconscious” of the nation, as not only the general population but the Times editorial board had begun to shift their opinions in line with the company’s views. As I mentioned, the pioneer of Mobil’s advertorials, Herb Schmertz, also talked a lot about their public-affairs principles.

Beyond that, we don’t yet have the smoking-gun strategy documents for delay equivalent to the ones for denial. This is speculation, but part of the reason that we see propaganda mirrored so closely between different companies and different industries is because much of the time they work with the same PR firms and ad agencies. And so it could be that those memos lie in the file cabinets of PR firms rather than the oil companies themselves. That’s why there are now campaigns to hold those PR agents to account as well.

GAZETTE:  This is kind of a horrible question to ask, but were you ever, despite yourself, impressed with the strategy and its effectiveness?

SUPRAN: Through our research, it has gradually dawned on me and my colleagues how central to the invention and advancement of modern propaganda the oil and gas industry has been over the last century. For me, coming from a physics and engineering background and retraining to work in this discipline, it’s been eye-opening and humbling to realize how much of the way we think and talk about this crisis has been encouraged and embodied by fossil-fuel-industry propaganda.

So I do recognize just how effective this industry’s public-affairs tactics have been. They’ve certainly undermined public concern and action on this crisis for decades. For my entire lifetime, in fact, the climate denial and delay machine has been in full swing. I’m not sure if “marvel” is the right word, but I’m very cognizant of the fact that I am part of the climate-change generation, born into a society locked into fossil fuels not for want of scientific understanding or technology or policy know-how, but because of the greed and disinformation and lobbying of a small group of fossil-fuel interests and conservative billionaires.

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CLEARING UP THE CLIMATE DEBATE: Professor Stephan Lewandowsky holds “sceptics” accountable for their subversion of the peer review process.

On 20 April 2010, a BP oil rig exploded in the Gulf of Mexico, killing 11 workers and creating the largest oil spill in history.

When President Obama sought to hold the corporation accountable by creating a $20B damage fund, this provoked Republican Congressman from Texas Joe Barton to issue a public apology.

An apology not to the people affected by the oil spill … but to BP.

In a peculiar inversion of ethics, Barton called the President’s measures a “ shakedown ”, finding it a “tragedy in the first proportion” that a corporation should be held accountable for the consequences of its actions.

What does a Congressman’s inverted morality have to do with climate denial?

Quite a bit.

In a similar inversion of normal practice, most climate deniers avoid scrutiny by sidestepping the peer-review process that is fundamental to science, instead posting their material in the internet or writing books.

Books may be impressively weighty, but remember that they are printed because a publisher thinks they can make money, not necessarily because the content has scientific value.

Fiction sells, even if dressed up as science .

During peer review, by contrast, commercial interests are removed from the publication decision because journals are often published by not-for-profit professional organizations. Even if private publishers are involved, they make their profit primarily via university subscriptions, and universities subscribe to journals based on their reputation, rather than based on individual publication decisions.

Very occasionally a contrarian paper does appear in a peer-reviewed journal, which segments of the internet and the media immediately hail as evidence against global warming or its human causes, as if a single paper somehow nullifies thousands of previous scientific findings.

What are we to make of that handful of contrarian papers? Do they make a legitimate if dissenting contribution to scientific knowledge?

In some cases, perhaps.

But in many other cases, troubling ethical questions arise from examination of the public record surrounding contrarian papers.

For example, in 2003 the reputable journal Climate Research published a paleoclimatological analysis that concluded, in flat contradiction to virtually all existing research, that the 20th century was probably not the warmest of the last millennium. This paper, partially funded by the American Petroleum Institute, attracted considerable public and political attention because it seemingly offered relief from the need to address climate change.

The paper also engendered some highly unusual fall-out.

First, three editors of Climate Research resigned in protest over its publication, including the incoming editor-in-chief who charged that “…some editors were not as rigorous in the review process as is otherwise common.”

This highly unusual mass resignation was followed by an even more unusual public statement from the publisher that acknowledged flaws in the journal’s editorial process.

Three editorial resignations and a publisher’s acknowledgement of editorial flaws are not standard scientific practice and call for further examination of the authors and the accepting editor.

The first author of this paper, Dr Willie Soon, is an astrophysicist by training. In U.S. congressional testimony, he identified his “training” in paleoclimatology as attendance at workshops, conferences, and summer schools. (The people who teach such summer schools, actual climate scientists, published a scathing rebuttal of Soon’s paper.)

Undaunted, Dr Soon has since become an expert on polar bears, publishing a paper that accused the U.S. Geological Survey of being “unscientific” in its reports about the risks faced by polar bears from climate change.

Most recently, Dr Soon has become an expert on mercury poisoning, using the Wall Street Journal as a platform to assuage fears about mercury-contaminated fish because, after all, “mercury has always existed naturally in Earth’s environment.”

Lest one wonder what links paleoclimatology, Arctic ecology, and environmental epidemiology, the answer is not any conventional area of academic expertise but ideology .

As Professor Naomi Oreskes and historian Erik Conway have shown in their insightful book, Merchants of Doubt , the hallmark of organized denial is that the same pseudo-experts emerge from the same shadowy “think” tanks over and over to rail against what they call “junk science”.

Whether it is the link between smoking and lung cancer, between mercury and water poisoning, or between carbon emissions and climate change, ideology inverts facts and ethics whenever overwhelming scientific evidence suggests the need to regulate economic activity.

So what of the editor who accepted the flawed Climate Research paper, Dr Chris de Freitas of Auckland?

Later, De Freitas co-authored a paper in 2009 that some media outlets heralded as showing that climate change was down to nature .

One of the authors, Adjunct academic Bob Carter from James Cook University, claimed that “our paper confirms what many scientists already know: which is that no scientific justification exists for emissions regulation.” Welcome news indeed, at least for the coal industry, but does the paper support this conclusion?

For starters, the 2009 paper by McLean, de Freitas, and Carter did not address long-term global warming at all.

It discussed the association between ocean currents and air temperature — in particular the time lag between the warm El Niño current and the ensuing increase in temperature.

Indeed, the article does not even contain the words “climate change” except in a citation of the IPCC, and its only conceivable connection with climate change arises from the speculative phrase “ … and perhaps recent trends in global temperature …” in the final sentence.

It appears ethically troubling to derive strong statements about emissions regulations from such a tentative clause in one’s final sentence in a paper on quite a different issue.

Such statements appear even more troubling if one considers paragraph 14 of the paper, which reads, “to remove the noise, the absolute values were replaced with derivative values based on variations. Here the derivative is the 12-month running average subtracted from the same average for data 12 months later.”

What happens to data if successive annual values are subtracted from each other? This mathematically removes any linear time trend.

In other words, temperatures could have doubled every other year and it would have escaped detection by the authors.

This removal of the trend did not escape detection by the scientific community, however, and the published rebuttal of this “it’s-all-natural” paper was as swift and devastating as it was for Dr Soon’s.

To remove the linear trend from temperature data in a paper that does not address climate change, and to then claim that nature is responsible for global warming and there is no scientific basis for emissions regulations smacks of an inversion of scientific ethics and practice.

Let us return to Congressman Barton.

Before apologizing to BP, not for the nearly $3,000,000 he has received in contributions from the oil, gas, and energy industries, but for President Obama seeking accountability from the corporation, Mr Barton also sponsored a contrived investigation of the famed “hockeystick” paper by Professor Michael Mann and colleagues.

The hockeystick is the iconic graph that shows the sky-rocketing temperatures of the last few decades in comparison to the relatively constant temperatures during the preceding centuries. The U.S. National Academy of Sciences affirmed the basic conclusions of Professor Mann, as have numerous other papers published during the last decade.

Mr. Barton, however, relied on a report by a certain Professor Wegman, who claimed to have identified statistical flaws in the analysis underlying the original hockeystick. (Even if correct, that criticism has no bearing on the overall conclusion of Professor Mann’s paper or on the numerous independent hockeysticks produced by other researchers.)

Professor Wegman subsequently published part of his report in the journal Computational Statistics and Data Analysis . Although normally a peer-reviewed journal, in this instance the paper was accepted a few days after submission, in July 2007, in an especially ironic twist as the paper tried to cast doubt on the quality of peer review in climate research.

Alas, the paper’s lifetime was cut tragically short when it was officially withdrawn by the publisher a few weeks ago.

The paper by Wegman and colleagues was officially withdrawn because of substantial plagiarism . Conforming to the typical pattern of inversions, Wegman also appears to have plagiarized large parts of his initial hockeystick critique for Congressman Barton, while additionally distorting and misrepresenting many of the conclusions of the cited authors.

We have examined just the tip of an iceberg of inversion of normal standards of ethics and scientific practice.

These multiple departures from common scientific practice are not isolated incidents — on the contrary, they represent a common thread that permeates all of climate denial.

Because climate denial is just that: denial, not scepticism.

Science is inherently sceptical, and peer-review is the instrument by which scientific scepticism is pursued.

Circumventing or subverting that process does not do justice to the public’s need for scientific accountability.

At a time when Greenland is losing around 9,000 tonnes of ice every second — all of which contributes to sea level rises – it is time to hold accountable those who invert common standards of science, decency, and ethics in pursuit of their agenda to delay action on climate change.

This is the sixth part of our series Clearing up the Climate Debate . To read the other instalments, follow the links below:

Part One: Climate change is real: an open letter from the scientific community .

Part Two: The greenhouse effect is real: here’s why .

Part Three: Speaking science to climate policy .

Part Four: Our effect on the earth is real: how we’re geo-engineering the planet

Part Five: Who’s your expert? The difference between peer review and rhetoric

Part Seven: When scientists take to the streets it’s time to listen up

Part Eight: Australia’s contribution matters: why we can’t ignore our climate responsibilities

Part Nine: A journey into the weird and wacky world of climate change denial

Part Ten: The chief troupier: the follies of Mr Monckton

Part Eleven: Rogues or respectable? How climate change sceptics spread doubt and denial

Part Twelve: Bob Carter’s climate counter-consensus is an alternate reality

Part Thirteen: The false, the confused and the mendacious: how the media gets it wrong on climate change

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A review of the global climate change impacts, adaptation, and sustainable mitigation measures

Kashif abbass.

1 School of Economics and Management, Nanjing University of Science and Technology, Nanjing, 210094 People’s Republic of China

Muhammad Zeeshan Qasim

2 Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Xiaolingwei 200, Nanjing, 210094 People’s Republic of China

Huaming Song

Muntasir murshed.

3 School of Business and Economics, North South University, Dhaka, 1229 Bangladesh

4 Department of Journalism, Media and Communications, Daffodil International University, Dhaka, Bangladesh

Haider Mahmood

5 Department of Finance, College of Business Administration, Prince Sattam Bin Abdulaziz University, 173, Alkharj, 11942 Saudi Arabia

Ijaz Younis

Associated data.

Data sources and relevant links are provided in the paper to access data.

Climate change is a long-lasting change in the weather arrays across tropics to polls. It is a global threat that has embarked on to put stress on various sectors. This study is aimed to conceptually engineer how climate variability is deteriorating the sustainability of diverse sectors worldwide. Specifically, the agricultural sector’s vulnerability is a globally concerning scenario, as sufficient production and food supplies are threatened due to irreversible weather fluctuations. In turn, it is challenging the global feeding patterns, particularly in countries with agriculture as an integral part of their economy and total productivity. Climate change has also put the integrity and survival of many species at stake due to shifts in optimum temperature ranges, thereby accelerating biodiversity loss by progressively changing the ecosystem structures. Climate variations increase the likelihood of particular food and waterborne and vector-borne diseases, and a recent example is a coronavirus pandemic. Climate change also accelerates the enigma of antimicrobial resistance, another threat to human health due to the increasing incidence of resistant pathogenic infections. Besides, the global tourism industry is devastated as climate change impacts unfavorable tourism spots. The methodology investigates hypothetical scenarios of climate variability and attempts to describe the quality of evidence to facilitate readers’ careful, critical engagement. Secondary data is used to identify sustainability issues such as environmental, social, and economic viability. To better understand the problem, gathered the information in this report from various media outlets, research agencies, policy papers, newspapers, and other sources. This review is a sectorial assessment of climate change mitigation and adaptation approaches worldwide in the aforementioned sectors and the associated economic costs. According to the findings, government involvement is necessary for the country’s long-term development through strict accountability of resources and regulations implemented in the past to generate cutting-edge climate policy. Therefore, mitigating the impacts of climate change must be of the utmost importance, and hence, this global threat requires global commitment to address its dreadful implications to ensure global sustenance.

Introduction

Worldwide observed and anticipated climatic changes for the twenty-first century and global warming are significant global changes that have been encountered during the past 65 years. Climate change (CC) is an inter-governmental complex challenge globally with its influence over various components of the ecological, environmental, socio-political, and socio-economic disciplines (Adger et al.  2005 ; Leal Filho et al.  2021 ; Feliciano et al.  2022 ). Climate change involves heightened temperatures across numerous worlds (Battisti and Naylor  2009 ; Schuurmans  2021 ; Weisheimer and Palmer  2005 ; Yadav et al.  2015 ). With the onset of the industrial revolution, the problem of earth climate was amplified manifold (Leppänen et al.  2014 ). It is reported that the immediate attention and due steps might increase the probability of overcoming its devastating impacts. It is not plausible to interpret the exact consequences of climate change (CC) on a sectoral basis (Izaguirre et al.  2021 ; Jurgilevich et al.  2017 ), which is evident by the emerging level of recognition plus the inclusion of climatic uncertainties at both local and national level of policymaking (Ayers et al.  2014 ).

Climate change is characterized based on the comprehensive long-haul temperature and precipitation trends and other components such as pressure and humidity level in the surrounding environment. Besides, the irregular weather patterns, retreating of global ice sheets, and the corresponding elevated sea level rise are among the most renowned international and domestic effects of climate change (Lipczynska-Kochany  2018 ; Michel et al.  2021 ; Murshed and Dao 2020 ). Before the industrial revolution, natural sources, including volcanoes, forest fires, and seismic activities, were regarded as the distinct sources of greenhouse gases (GHGs) such as CO 2 , CH 4 , N 2 O, and H 2 O into the atmosphere (Murshed et al. 2020 ; Hussain et al.  2020 ; Sovacool et al.  2021 ; Usman and Balsalobre-Lorente 2022 ; Murshed 2022 ). United Nations Framework Convention on Climate Change (UNFCCC) struck a major agreement to tackle climate change and accelerate and intensify the actions and investments required for a sustainable low-carbon future at Conference of the Parties (COP-21) in Paris on December 12, 2015. The Paris Agreement expands on the Convention by bringing all nations together for the first time in a single cause to undertake ambitious measures to prevent climate change and adapt to its impacts, with increased funding to assist developing countries in doing so. As so, it marks a turning point in the global climate fight. The core goal of the Paris Agreement is to improve the global response to the threat of climate change by keeping the global temperature rise this century well below 2 °C over pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5° C (Sharma et al. 2020 ; Sharif et al. 2020 ; Chien et al. 2021 .

Furthermore, the agreement aspires to strengthen nations’ ability to deal with the effects of climate change and align financing flows with low GHG emissions and climate-resilient paths (Shahbaz et al. 2019 ; Anwar et al. 2021 ; Usman et al. 2022a ). To achieve these lofty goals, adequate financial resources must be mobilized and provided, as well as a new technology framework and expanded capacity building, allowing developing countries and the most vulnerable countries to act under their respective national objectives. The agreement also establishes a more transparent action and support mechanism. All Parties are required by the Paris Agreement to do their best through “nationally determined contributions” (NDCs) and to strengthen these efforts in the coming years (Balsalobre-Lorente et al. 2020 ). It includes obligations that all Parties regularly report on their emissions and implementation activities. A global stock-take will be conducted every five years to review collective progress toward the agreement’s goal and inform the Parties’ future individual actions. The Paris Agreement became available for signature on April 22, 2016, Earth Day, at the United Nations Headquarters in New York. On November 4, 2016, it went into effect 30 days after the so-called double threshold was met (ratification by 55 nations accounting for at least 55% of world emissions). More countries have ratified and continue to ratify the agreement since then, bringing 125 Parties in early 2017. To fully operationalize the Paris Agreement, a work program was initiated in Paris to define mechanisms, processes, and recommendations on a wide range of concerns (Murshed et al. 2021 ). Since 2016, Parties have collaborated in subsidiary bodies (APA, SBSTA, and SBI) and numerous formed entities. The Conference of the Parties functioning as the meeting of the Parties to the Paris Agreement (CMA) convened for the first time in November 2016 in Marrakesh in conjunction with COP22 and made its first two resolutions. The work plan is scheduled to be finished by 2018. Some mitigation and adaptation strategies to reduce the emission in the prospective of Paris agreement are following firstly, a long-term goal of keeping the increase in global average temperature to well below 2 °C above pre-industrial levels, secondly, to aim to limit the rise to 1.5 °C, since this would significantly reduce risks and the impacts of climate change, thirdly, on the need for global emissions to peak as soon as possible, recognizing that this will take longer for developing countries, lastly, to undertake rapid reductions after that under the best available science, to achieve a balance between emissions and removals in the second half of the century. On the other side, some adaptation strategies are; strengthening societies’ ability to deal with the effects of climate change and to continue & expand international assistance for developing nations’ adaptation.

However, anthropogenic activities are currently regarded as most accountable for CC (Murshed et al. 2022 ). Apart from the industrial revolution, other anthropogenic activities include excessive agricultural operations, which further involve the high use of fuel-based mechanization, burning of agricultural residues, burning fossil fuels, deforestation, national and domestic transportation sectors, etc. (Huang et al.  2016 ). Consequently, these anthropogenic activities lead to climatic catastrophes, damaging local and global infrastructure, human health, and total productivity. Energy consumption has mounted GHGs levels concerning warming temperatures as most of the energy production in developing countries comes from fossil fuels (Balsalobre-Lorente et al. 2022 ; Usman et al. 2022b ; Abbass et al. 2021a ; Ishikawa-Ishiwata and Furuya  2022 ).

This review aims to highlight the effects of climate change in a socio-scientific aspect by analyzing the existing literature on various sectorial pieces of evidence globally that influence the environment. Although this review provides a thorough examination of climate change and its severe affected sectors that pose a grave danger for global agriculture, biodiversity, health, economy, forestry, and tourism, and to purpose some practical prophylactic measures and mitigation strategies to be adapted as sound substitutes to survive from climate change (CC) impacts. The societal implications of irregular weather patterns and other effects of climate changes are discussed in detail. Some numerous sustainable mitigation measures and adaptation practices and techniques at the global level are discussed in this review with an in-depth focus on its economic, social, and environmental aspects. Methods of data collection section are included in the supplementary information.

Review methodology

Related study and its objectives.

Today, we live an ordinary life in the beautiful digital, globalized world where climate change has a decisive role. What happens in one country has a massive influence on geographically far apart countries, which points to the current crisis known as COVID-19 (Sarkar et al.  2021 ). The most dangerous disease like COVID-19 has affected the world’s climate changes and economic conditions (Abbass et al. 2022 ; Pirasteh-Anosheh et al.  2021 ). The purpose of the present study is to review the status of research on the subject, which is based on “Global Climate Change Impacts, adaptation, and sustainable mitigation measures” by systematically reviewing past published and unpublished research work. Furthermore, the current study seeks to comment on research on the same topic and suggest future research on the same topic. Specifically, the present study aims: The first one is, organize publications to make them easy and quick to find. Secondly, to explore issues in this area, propose an outline of research for future work. The third aim of the study is to synthesize the previous literature on climate change, various sectors, and their mitigation measurement. Lastly , classify the articles according to the different methods and procedures that have been adopted.

Review methodology for reviewers

This review-based article followed systematic literature review techniques that have proved the literature review as a rigorous framework (Benita  2021 ; Tranfield et al.  2003 ). Moreover, we illustrate in Fig.  1 the search method that we have started for this research. First, finalized the research theme to search literature (Cooper et al.  2018 ). Second, used numerous research databases to search related articles and download from the database (Web of Science, Google Scholar, Scopus Index Journals, Emerald, Elsevier Science Direct, Springer, and Sciverse). We focused on various articles, with research articles, feedback pieces, short notes, debates, and review articles published in scholarly journals. Reports used to search for multiple keywords such as “Climate Change,” “Mitigation and Adaptation,” “Department of Agriculture and Human Health,” “Department of Biodiversity and Forestry,” etc.; in summary, keyword list and full text have been made. Initially, the search for keywords yielded a large amount of literature.

Methodology search for finalized articles for investigations.

Source : constructed by authors

Since 2020, it has been impossible to review all the articles found; some restrictions have been set for the literature exhibition. The study searched 95 articles on a different database mentioned above based on the nature of the study. It excluded 40 irrelevant papers due to copied from a previous search after readings tiles, abstract and full pieces. The criteria for inclusion were: (i) articles focused on “Global Climate Change Impacts, adaptation, and sustainable mitigation measures,” and (ii) the search key terms related to study requirements. The complete procedure yielded 55 articles for our study. We repeat our search on the “Web of Science and Google Scholars” database to enhance the search results and check the referenced articles.

In this study, 55 articles are reviewed systematically and analyzed for research topics and other aspects, such as the methods, contexts, and theories used in these studies. Furthermore, this study analyzes closely related areas to provide unique research opportunities in the future. The study also discussed future direction opportunities and research questions by understanding the research findings climate changes and other affected sectors. The reviewed paper framework analysis process is outlined in Fig.  2 .

Framework of the analysis Process.

Natural disasters and climate change’s socio-economic consequences

Natural and environmental disasters can be highly variable from year to year; some years pass with very few deaths before a significant disaster event claims many lives (Symanski et al.  2021 ). Approximately 60,000 people globally died from natural disasters each year on average over the past decade (Ritchie and Roser  2014 ; Wiranata and Simbolon  2021 ). So, according to the report, around 0.1% of global deaths. Annual variability in the number and share of deaths from natural disasters in recent decades are shown in Fig.  3 . The number of fatalities can be meager—sometimes less than 10,000, and as few as 0.01% of all deaths. But shock events have a devastating impact: the 1983–1985 famine and drought in Ethiopia; the 2004 Indian Ocean earthquake and tsunami; Cyclone Nargis, which struck Myanmar in 2008; and the 2010 Port-au-Prince earthquake in Haiti and now recent example is COVID-19 pandemic (Erman et al.  2021 ). These events pushed global disaster deaths to over 200,000—more than 0.4% of deaths in these years. Low-frequency, high-impact events such as earthquakes and tsunamis are not preventable, but such high losses of human life are. Historical evidence shows that earlier disaster detection, more robust infrastructure, emergency preparedness, and response programmers have substantially reduced disaster deaths worldwide. Low-income is also the most vulnerable to disasters; improving living conditions, facilities, and response services in these areas would be critical in reducing natural disaster deaths in the coming decades.

Global deaths from natural disasters, 1978 to 2020.

Source EMDAT ( 2020 )

The interior regions of the continent are likely to be impacted by rising temperatures (Dimri et al.  2018 ; Goes et al.  2020 ; Mannig et al.  2018 ; Schuurmans  2021 ). Weather patterns change due to the shortage of natural resources (water), increase in glacier melting, and rising mercury are likely to cause extinction to many planted species (Gampe et al.  2016 ; Mihiretu et al.  2021 ; Shaffril et al.  2018 ).On the other hand, the coastal ecosystem is on the verge of devastation (Perera et al.  2018 ; Phillips  2018 ). The temperature rises, insect disease outbreaks, health-related problems, and seasonal and lifestyle changes are persistent, with a strong probability of these patterns continuing in the future (Abbass et al. 2021c ; Hussain et al.  2018 ). At the global level, a shortage of good infrastructure and insufficient adaptive capacity are hammering the most (IPCC  2013 ). In addition to the above concerns, a lack of environmental education and knowledge, outdated consumer behavior, a scarcity of incentives, a lack of legislation, and the government’s lack of commitment to climate change contribute to the general public’s concerns. By 2050, a 2 to 3% rise in mercury and a drastic shift in rainfall patterns may have serious consequences (Huang et al. 2022 ; Gorst et al.  2018 ). Natural and environmental calamities caused huge losses globally, such as decreased agriculture outputs, rehabilitation of the system, and rebuilding necessary technologies (Ali and Erenstein  2017 ; Ramankutty et al.  2018 ; Yu et al.  2021 ) (Table ​ (Table1). 1 ). Furthermore, in the last 3 or 4 years, the world has been plagued by smog-related eye and skin diseases, as well as a rise in road accidents due to poor visibility.

Main natural danger statistics for 1985–2020 at the global level

Source: EM-DAT ( 2020 )

Climate change and agriculture

Global agriculture is the ultimate sector responsible for 30–40% of all greenhouse emissions, which makes it a leading industry predominantly contributing to climate warming and significantly impacted by it (Grieg; Mishra et al.  2021 ; Ortiz et al.  2021 ; Thornton and Lipper  2014 ). Numerous agro-environmental and climatic factors that have a dominant influence on agriculture productivity (Pautasso et al.  2012 ) are significantly impacted in response to precipitation extremes including floods, forest fires, and droughts (Huang  2004 ). Besides, the immense dependency on exhaustible resources also fuels the fire and leads global agriculture to become prone to devastation. Godfray et al. ( 2010 ) mentioned that decline in agriculture challenges the farmer’s quality of life and thus a significant factor to poverty as the food and water supplies are critically impacted by CC (Ortiz et al.  2021 ; Rosenzweig et al.  2014 ). As an essential part of the economic systems, especially in developing countries, agricultural systems affect the overall economy and potentially the well-being of households (Schlenker and Roberts  2009 ). According to the report published by the Intergovernmental Panel on Climate Change (IPCC), atmospheric concentrations of greenhouse gases, i.e., CH 4, CO 2 , and N 2 O, are increased in the air to extraordinary levels over the last few centuries (Usman and Makhdum 2021 ; Stocker et al.  2013 ). Climate change is the composite outcome of two different factors. The first is the natural causes, and the second is the anthropogenic actions (Karami 2012 ). It is also forecasted that the world may experience a typical rise in temperature stretching from 1 to 3.7 °C at the end of this century (Pachauri et al. 2014 ). The world’s crop production is also highly vulnerable to these global temperature-changing trends as raised temperatures will pose severe negative impacts on crop growth (Reidsma et al. 2009 ). Some of the recent modeling about the fate of global agriculture is briefly described below.

Decline in cereal productivity

Crop productivity will also be affected dramatically in the next few decades due to variations in integral abiotic factors such as temperature, solar radiation, precipitation, and CO 2 . These all factors are included in various regulatory instruments like progress and growth, weather-tempted changes, pest invasions (Cammell and Knight 1992 ), accompanying disease snags (Fand et al. 2012 ), water supplies (Panda et al. 2003 ), high prices of agro-products in world’s agriculture industry, and preeminent quantity of fertilizer consumption. Lobell and field ( 2007 ) claimed that from 1962 to 2002, wheat crop output had condensed significantly due to rising temperatures. Therefore, during 1980–2011, the common wheat productivity trends endorsed extreme temperature events confirmed by Gourdji et al. ( 2013 ) around South Asia, South America, and Central Asia. Various other studies (Asseng, Cao, Zhang, and Ludwig 2009 ; Asseng et al. 2013 ; García et al. 2015 ; Ortiz et al. 2021 ) also proved that wheat output is negatively affected by the rising temperatures and also caused adverse effects on biomass productivity (Calderini et al. 1999 ; Sadras and Slafer 2012 ). Hereafter, the rice crop is also influenced by the high temperatures at night. These difficulties will worsen because the temperature will be rising further in the future owing to CC (Tebaldi et al. 2006 ). Another research conducted in China revealed that a 4.6% of rice production per 1 °C has happened connected with the advancement in night temperatures (Tao et al. 2006 ). Moreover, the average night temperature growth also affected rice indicia cultivar’s output pragmatically during 25 years in the Philippines (Peng et al. 2004 ). It is anticipated that the increase in world average temperature will also cause a substantial reduction in yield (Hatfield et al. 2011 ; Lobell and Gourdji 2012 ). In the southern hemisphere, Parry et al. ( 2007 ) noted a rise of 1–4 °C in average daily temperatures at the end of spring season unti the middle of summers, and this raised temperature reduced crop output by cutting down the time length for phenophases eventually reduce the yield (Hatfield and Prueger 2015 ; R. Ortiz 2008 ). Also, world climate models have recommended that humid and subtropical regions expect to be plentiful prey to the upcoming heat strokes (Battisti and Naylor 2009 ). Grain production is the amalgamation of two constituents: the average weight and the grain output/m 2 , however, in crop production. Crop output is mainly accredited to the grain quantity (Araus et al. 2008 ; Gambín and Borrás 2010 ). In the times of grain set, yield resources are mainly strewn between hitherto defined components, i.e., grain usual weight and grain output, which presents a trade-off between them (Gambín and Borrás 2010 ) beside disparities in per grain integration (B. L. Gambín et al. 2006 ). In addition to this, the maize crop is also susceptible to raised temperatures, principally in the flowering stage (Edreira and Otegui 2013 ). In reality, the lower grain number is associated with insufficient acclimatization due to intense photosynthesis and higher respiration and the high-temperature effect on the reproduction phenomena (Edreira and Otegui 2013 ). During the flowering phase, maize visible to heat (30–36 °C) seemed less anthesis-silking intermissions (Edreira et al. 2011 ). Another research by Dupuis and Dumas ( 1990 ) proved that a drop in spikelet when directly visible to high temperatures above 35 °C in vitro pollination. Abnormalities in kernel number claimed by Vega et al. ( 2001 ) is related to conceded plant development during a flowering phase that is linked with the active ear growth phase and categorized as a critical phase for approximation of kernel number during silking (Otegui and Bonhomme 1998 ).

The retort of rice output to high temperature presents disparities in flowering patterns, and seed set lessens and lessens grain weight (Qasim et al. 2020 ; Qasim, Hammad, Maqsood, Tariq, & Chawla). During the daytime, heat directly impacts flowers which lessens the thesis period and quickens the earlier peak flowering (Tao et al. 2006 ). Antagonistic effect of higher daytime temperature d on pollen sprouting proposed seed set decay, whereas, seed set was lengthily reduced than could be explicated by pollen growing at high temperatures 40◦C (Matsui et al. 2001 ).

The decline in wheat output is linked with higher temperatures, confirmed in numerous studies (Semenov 2009 ; Stone and Nicolas 1994 ). High temperatures fast-track the arrangements of plant expansion (Blum et al. 2001 ), diminution photosynthetic process (Salvucci and Crafts‐Brandner 2004 ), and also considerably affect the reproductive operations (Farooq et al. 2011 ).

The destructive impacts of CC induced weather extremes to deteriorate the integrity of crops (Chaudhary et al. 2011 ), e.g., Spartan cold and extreme fog cause falling and discoloration of betel leaves (Rosenzweig et al. 2001 ), giving them a somehow reddish appearance, squeezing of lemon leaves (Pautasso et al. 2012 ), as well as root rot of pineapple, have reported (Vedwan and Rhoades 2001 ). Henceforth, in tackling the disruptive effects of CC, several short-term and long-term management approaches are the crucial need of time (Fig.  4 ). Moreover, various studies (Chaudhary et al. 2011 ; Patz et al. 2005 ; Pautasso et al. 2012 ) have demonstrated adapting trends such as ameliorating crop diversity can yield better adaptability towards CC.

Schematic description of potential impacts of climate change on the agriculture sector and the appropriate mitigation and adaptation measures to overcome its impact.

Climate change impacts on biodiversity

Global biodiversity is among the severe victims of CC because it is the fastest emerging cause of species loss. Studies demonstrated that the massive scale species dynamics are considerably associated with diverse climatic events (Abraham and Chain 1988 ; Manes et al. 2021 ; A. M. D. Ortiz et al. 2021 ). Both the pace and magnitude of CC are altering the compatible habitat ranges for living entities of marine, freshwater, and terrestrial regions. Alterations in general climate regimes influence the integrity of ecosystems in numerous ways, such as variation in the relative abundance of species, range shifts, changes in activity timing, and microhabitat use (Bates et al. 2014 ). The geographic distribution of any species often depends upon its ability to tolerate environmental stresses, biological interactions, and dispersal constraints. Hence, instead of the CC, the local species must only accept, adapt, move, or face extinction (Berg et al. 2010 ). So, the best performer species have a better survival capacity for adjusting to new ecosystems or a decreased perseverance to survive where they are already situated (Bates et al. 2014 ). An important aspect here is the inadequate habitat connectivity and access to microclimates, also crucial in raising the exposure to climate warming and extreme heatwave episodes. For example, the carbon sequestration rates are undergoing fluctuations due to climate-driven expansion in the range of global mangroves (Cavanaugh et al. 2014 ).

Similarly, the loss of kelp-forest ecosystems in various regions and its occupancy by the seaweed turfs has set the track for elevated herbivory by the high influx of tropical fish populations. Not only this, the increased water temperatures have exacerbated the conditions far away from the physiological tolerance level of the kelp communities (Vergés et al. 2016 ; Wernberg et al. 2016 ). Another pertinent danger is the devastation of keystone species, which even has more pervasive effects on the entire communities in that habitat (Zarnetske et al. 2012 ). It is particularly important as CC does not specify specific populations or communities. Eventually, this CC-induced redistribution of species may deteriorate carbon storage and the net ecosystem productivity (Weed et al. 2013 ). Among the typical disruptions, the prominent ones include impacts on marine and terrestrial productivity, marine community assembly, and the extended invasion of toxic cyanobacteria bloom (Fossheim et al. 2015 ).

The CC-impacted species extinction is widely reported in the literature (Beesley et al. 2019 ; Urban 2015 ), and the predictions of demise until the twenty-first century are dreadful (Abbass et al. 2019 ; Pereira et al. 2013 ). In a few cases, northward shifting of species may not be formidable as it allows mountain-dwelling species to find optimum climates. However, the migrant species may be trapped in isolated and incompatible habitats due to losing topography and range (Dullinger et al. 2012 ). For example, a study indicated that the American pika has been extirpated or intensely diminished in some regions, primarily attributed to the CC-impacted extinction or at least local extirpation (Stewart et al. 2015 ). Besides, the anticipation of persistent responses to the impacts of CC often requires data records of several decades to rigorously analyze the critical pre and post CC patterns at species and ecosystem levels (Manes et al. 2021 ; Testa et al. 2018 ).

Nonetheless, the availability of such long-term data records is rare; hence, attempts are needed to focus on these profound aspects. Biodiversity is also vulnerable to the other associated impacts of CC, such as rising temperatures, droughts, and certain invasive pest species. For instance, a study revealed the changes in the composition of plankton communities attributed to rising temperatures. Henceforth, alterations in such aquatic producer communities, i.e., diatoms and calcareous plants, can ultimately lead to variation in the recycling of biological carbon. Moreover, such changes are characterized as a potential contributor to CO 2 differences between the Pleistocene glacial and interglacial periods (Kohfeld et al. 2005 ).

Climate change implications on human health

It is an understood corporality that human health is a significant victim of CC (Costello et al. 2009 ). According to the WHO, CC might be responsible for 250,000 additional deaths per year during 2030–2050 (Watts et al. 2015 ). These deaths are attributed to extreme weather-induced mortality and morbidity and the global expansion of vector-borne diseases (Lemery et al. 2021; Yang and Usman 2021 ; Meierrieks 2021 ; UNEP 2017 ). Here, some of the emerging health issues pertinent to this global problem are briefly described.

Climate change and antimicrobial resistance with corresponding economic costs

Antimicrobial resistance (AMR) is an up-surging complex global health challenge (Garner et al. 2019 ; Lemery et al. 2021 ). Health professionals across the globe are extremely worried due to this phenomenon that has critical potential to reverse almost all the progress that has been achieved so far in the health discipline (Gosling and Arnell 2016 ). A massive amount of antibiotics is produced by many pharmaceutical industries worldwide, and the pathogenic microorganisms are gradually developing resistance to them, which can be comprehended how strongly this aspect can shake the foundations of national and global economies (UNEP 2017 ). This statement is supported by the fact that AMR is not developing in a particular region or country. Instead, it is flourishing in every continent of the world (WHO 2018 ). This plague is heavily pushing humanity to the post-antibiotic era, in which currently antibiotic-susceptible pathogens will once again lead to certain endemics and pandemics after being resistant(WHO 2018 ). Undesirably, if this statement would become a factuality, there might emerge certain risks in undertaking sophisticated interventions such as chemotherapy, joint replacement cases, and organ transplantation (Su et al. 2018 ). Presently, the amplification of drug resistance cases has made common illnesses like pneumonia, post-surgical infections, HIV/AIDS, tuberculosis, malaria, etc., too difficult and costly to be treated or cure well (WHO 2018 ). From a simple example, it can be assumed how easily antibiotic-resistant strains can be transmitted from one person to another and ultimately travel across the boundaries (Berendonk et al. 2015 ). Talking about the second- and third-generation classes of antibiotics, e.g., most renowned generations of cephalosporin antibiotics that are more expensive, broad-spectrum, more toxic, and usually require more extended periods whenever prescribed to patients (Lemery et al. 2021 ; Pärnänen et al. 2019 ). This scenario has also revealed that the abundance of resistant strains of pathogens was also higher in the Southern part (WHO 2018 ). As southern parts are generally warmer than their counterparts, it is evident from this example how CC-induced global warming can augment the spread of antibiotic-resistant strains within the biosphere, eventually putting additional economic burden in the face of developing new and costlier antibiotics. The ARG exchange to susceptible bacteria through one of the potential mechanisms, transformation, transduction, and conjugation; Selection pressure can be caused by certain antibiotics, metals or pesticides, etc., as shown in Fig.  5 .

A typical interaction between the susceptible and resistant strains.

Source: Elsayed et al. ( 2021 ); Karkman et al. ( 2018 )

Certain studies highlighted that conventional urban wastewater treatment plants are typical hotspots where most bacterial strains exchange genetic material through horizontal gene transfer (Fig.  5 ). Although at present, the extent of risks associated with the antibiotic resistance found in wastewater is complicated; environmental scientists and engineers have particular concerns about the potential impacts of these antibiotic resistance genes on human health (Ashbolt 2015 ). At most undesirable and worst case, these antibiotic-resistant genes containing bacteria can make their way to enter into the environment (Pruden et al. 2013 ), irrigation water used for crops and public water supplies and ultimately become a part of food chains and food webs (Ma et al. 2019 ; D. Wu et al. 2019 ). This problem has been reported manifold in several countries (Hendriksen et al. 2019 ), where wastewater as a means of irrigated water is quite common.

Climate change and vector borne-diseases

Temperature is a fundamental factor for the sustenance of living entities regardless of an ecosystem. So, a specific living being, especially a pathogen, requires a sophisticated temperature range to exist on earth. The second essential component of CC is precipitation, which also impacts numerous infectious agents’ transport and dissemination patterns. Global rising temperature is a significant cause of many species extinction. On the one hand, this changing environmental temperature may be causing species extinction, and on the other, this warming temperature might favor the thriving of some new organisms. Here, it was evident that some pathogens may also upraise once non-evident or reported (Patz et al. 2000 ). This concept can be exemplified through certain pathogenic strains of microorganisms that how the likelihood of various diseases increases in response to climate warming-induced environmental changes (Table ​ (Table2 2 ).

Examples of how various environmental changes affect various infectious diseases in humans

Source: Aron and Patz ( 2001 )

A recent example is an outburst of coronavirus (COVID-19) in the Republic of China, causing pneumonia and severe acute respiratory complications (Cui et al. 2021 ; Song et al. 2021 ). The large family of viruses is harbored in numerous animals, bats, and snakes in particular (livescience.com) with the subsequent transfer into human beings. Hence, it is worth noting that the thriving of numerous vectors involved in spreading various diseases is influenced by Climate change (Ogden 2018 ; Santos et al. 2021 ).

Psychological impacts of climate change

Climate change (CC) is responsible for the rapid dissemination and exaggeration of certain epidemics and pandemics. In addition to the vast apparent impacts of climate change on health, forestry, agriculture, etc., it may also have psychological implications on vulnerable societies. It can be exemplified through the recent outburst of (COVID-19) in various countries around the world (Pal 2021 ). Besides, the victims of this viral infection have made healthy beings scarier and terrified. In the wake of such epidemics, people with common colds or fever are also frightened and must pass specific regulatory protocols. Living in such situations continuously terrifies the public and makes the stress familiar, which eventually makes them psychologically weak (npr.org).

CC boosts the extent of anxiety, distress, and other issues in public, pushing them to develop various mental-related problems. Besides, frequent exposure to extreme climatic catastrophes such as geological disasters also imprints post-traumatic disorder, and their ubiquitous occurrence paves the way to developing chronic psychological dysfunction. Moreover, repetitive listening from media also causes an increase in the person’s stress level (Association 2020 ). Similarly, communities living in flood-prone areas constantly live in extreme fear of drowning and die by floods. In addition to human lives, the flood-induced destruction of physical infrastructure is a specific reason for putting pressure on these communities (Ogden 2018 ). For instance, Ogden ( 2018 ) comprehensively denoted that Katrina’s Hurricane augmented the mental health issues in the victim communities.

Climate change impacts on the forestry sector

Forests are the global regulators of the world’s climate (FAO 2018 ) and have an indispensable role in regulating global carbon and nitrogen cycles (Rehman et al. 2021 ; Reichstein and Carvalhais 2019 ). Hence, disturbances in forest ecology affect the micro and macro-climates (Ellison et al. 2017 ). Climate warming, in return, has profound impacts on the growth and productivity of transboundary forests by influencing the temperature and precipitation patterns, etc. As CC induces specific changes in the typical structure and functions of ecosystems (Zhang et al. 2017 ) as well impacts forest health, climate change also has several devastating consequences such as forest fires, droughts, pest outbreaks (EPA 2018 ), and last but not the least is the livelihoods of forest-dependent communities. The rising frequency and intensity of another CC product, i.e., droughts, pose plenty of challenges to the well-being of global forests (Diffenbaugh et al. 2017 ), which is further projected to increase soon (Hartmann et al. 2018 ; Lehner et al. 2017 ; Rehman et al. 2021 ). Hence, CC induces storms, with more significant impacts also put extra pressure on the survival of the global forests (Martínez-Alvarado et al. 2018 ), significantly since their influences are augmented during higher winter precipitations with corresponding wetter soils causing weak root anchorage of trees (Brázdil et al. 2018 ). Surging temperature regimes causes alterations in usual precipitation patterns, which is a significant hurdle for the survival of temperate forests (Allen et al. 2010 ; Flannigan et al. 2013 ), letting them encounter severe stress and disturbances which adversely affects the local tree species (Hubbart et al. 2016 ; Millar and Stephenson 2015 ; Rehman et al. 2021 ).

Climate change impacts on forest-dependent communities

Forests are the fundamental livelihood resource for about 1.6 billion people worldwide; out of them, 350 million are distinguished with relatively higher reliance (Bank 2008 ). Agro-forestry-dependent communities comprise 1.2 billion, and 60 million indigenous people solely rely on forests and their products to sustain their lives (Sunderlin et al. 2005 ). For example, in the entire African continent, more than 2/3rd of inhabitants depend on forest resources and woodlands for their alimonies, e.g., food, fuelwood and grazing (Wasiq and Ahmad 2004 ). The livings of these people are more intensely affected by the climatic disruptions making their lives harder (Brown et al. 2014 ). On the one hand, forest communities are incredibly vulnerable to CC due to their livelihoods, cultural and spiritual ties as well as socio-ecological connections, and on the other, they are not familiar with the term “climate change.” (Rahman and Alam 2016 ). Among the destructive impacts of temperature and rainfall, disruption of the agroforestry crops with resultant downscale growth and yield (Macchi et al. 2008 ). Cruz ( 2015 ) ascribed that forest-dependent smallholder farmers in the Philippines face the enigma of delayed fruiting, more severe damages by insect and pest incidences due to unfavorable temperature regimes, and changed rainfall patterns.

Among these series of challenges to forest communities, their well-being is also distinctly vulnerable to CC. Though the detailed climate change impacts on human health have been comprehensively mentioned in the previous section, some studies have listed a few more devastating effects on the prosperity of forest-dependent communities. For instance, the Himalayan people have been experiencing frequent skin-borne diseases such as malaria and other skin diseases due to increasing mosquitoes, wild boar as well, and new wasps species, particularly in higher altitudes that were almost non-existent before last 5–10 years (Xu et al. 2008 ). Similarly, people living at high altitudes in Bangladesh have experienced frequent mosquito-borne calamities (Fardous; Sharma 2012 ). In addition, the pace of other waterborne diseases such as infectious diarrhea, cholera, pathogenic induced abdominal complications and dengue has also been boosted in other distinguished regions of Bangladesh (Cell 2009 ; Gunter et al. 2008 ).

Pest outbreak

Upscaling hotter climate may positively affect the mobile organisms with shorter generation times because they can scurry from harsh conditions than the immobile species (Fettig et al. 2013 ; Schoene and Bernier 2012 ) and are also relatively more capable of adapting to new environments (Jactel et al. 2019 ). It reveals that insects adapt quickly to global warming due to their mobility advantages. Due to past outbreaks, the trees (forests) are relatively more susceptible victims (Kurz et al. 2008 ). Before CC, the influence of factors mentioned earlier, i.e., droughts and storms, was existent and made the forests susceptible to insect pest interventions; however, the global forests remain steadfast, assiduous, and green (Jactel et al. 2019 ). The typical reasons could be the insect herbivores were regulated by several tree defenses and pressures of predation (Wilkinson and Sherratt 2016 ). As climate greatly influences these phenomena, the global forests cannot be so sedulous against such challenges (Jactel et al. 2019 ). Table ​ Table3 3 demonstrates some of the particular considerations with practical examples that are essential while mitigating the impacts of CC in the forestry sector.

Essential considerations while mitigating the climate change impacts on the forestry sector

Source : Fischer ( 2019 )

Climate change impacts on tourism

Tourism is a commercial activity that has roots in multi-dimensions and an efficient tool with adequate job generation potential, revenue creation, earning of spectacular foreign exchange, enhancement in cross-cultural promulgation and cooperation, a business tool for entrepreneurs and eventually for the country’s national development (Arshad et al. 2018 ; Scott 2021 ). Among a plethora of other disciplines, the tourism industry is also a distinct victim of climate warming (Gössling et al. 2012 ; Hall et al. 2015 ) as the climate is among the essential resources that enable tourism in particular regions as most preferred locations. Different places at different times of the year attract tourists both within and across the countries depending upon the feasibility and compatibility of particular weather patterns. Hence, the massive variations in these weather patterns resulting from CC will eventually lead to monumental challenges to the local economy in that specific area’s particular and national economy (Bujosa et al. 2015 ). For instance, the Intergovernmental Panel on Climate Change (IPCC) report demonstrated that the global tourism industry had faced a considerable decline in the duration of ski season, including the loss of some ski areas and the dramatic shifts in tourist destinations’ climate warming.

Furthermore, different studies (Neuvonen et al. 2015 ; Scott et al. 2004 ) indicated that various currently perfect tourist spots, e.g., coastal areas, splendid islands, and ski resorts, will suffer consequences of CC. It is also worth noting that the quality and potential of administrative management potential to cope with the influence of CC on the tourism industry is of crucial significance, which renders specific strengths of resiliency to numerous destinations to withstand against it (Füssel and Hildén 2014 ). Similarly, in the partial or complete absence of adequate socio-economic and socio-political capital, the high-demanding tourist sites scurry towards the verge of vulnerability. The susceptibility of tourism is based on different components such as the extent of exposure, sensitivity, life-supporting sectors, and capacity assessment factors (Füssel and Hildén 2014 ). It is obvious corporality that sectors such as health, food, ecosystems, human habitat, infrastructure, water availability, and the accessibility of a particular region are prone to CC. Henceforth, the sensitivity of these critical sectors to CC and, in return, the adaptive measures are a hallmark in determining the composite vulnerability of climate warming (Ionescu et al. 2009 ).

Moreover, the dependence on imported food items, poor hygienic conditions, and inadequate health professionals are dominant aspects affecting the local terrestrial and aquatic biodiversity. Meanwhile, the greater dependency on ecosystem services and its products also makes a destination more fragile to become a prey of CC (Rizvi et al. 2015 ). Some significant non-climatic factors are important indicators of a particular ecosystem’s typical health and functioning, e.g., resource richness and abundance portray the picture of ecosystem stability. Similarly, the species abundance is also a productive tool that ensures that the ecosystem has a higher buffering capacity, which is terrific in terms of resiliency (Roscher et al. 2013 ).

Climate change impacts on the economic sector

Climate plays a significant role in overall productivity and economic growth. Due to its increasingly global existence and its effect on economic growth, CC has become one of the major concerns of both local and international environmental policymakers (Ferreira et al. 2020 ; Gleditsch 2021 ; Abbass et al. 2021b ; Lamperti et al. 2021 ). The adverse effects of CC on the overall productivity factor of the agricultural sector are therefore significant for understanding the creation of local adaptation policies and the composition of productive climate policy contracts. Previous studies on CC in the world have already forecasted its effects on the agricultural sector. Researchers have found that global CC will impact the agricultural sector in different world regions. The study of the impacts of CC on various agrarian activities in other demographic areas and the development of relative strategies to respond to effects has become a focal point for researchers (Chandioet al. 2020 ; Gleditsch 2021 ; Mosavi et al. 2020 ).

With the rapid growth of global warming since the 1980s, the temperature has started increasing globally, which resulted in the incredible transformation of rain and evaporation in the countries. The agricultural development of many countries has been reliant, delicate, and susceptible to CC for a long time, and it is on the development of agriculture total factor productivity (ATFP) influence different crops and yields of farmers (Alhassan 2021 ; Wu  2020 ).

Food security and natural disasters are increasing rapidly in the world. Several major climatic/natural disasters have impacted local crop production in the countries concerned. The effects of these natural disasters have been poorly controlled by the development of the economies and populations and may affect human life as well. One example is China, which is among the world’s most affected countries, vulnerable to natural disasters due to its large population, harsh environmental conditions, rapid CC, low environmental stability, and disaster power. According to the January 2016 statistical survey, China experienced an economic loss of 298.3 billion Yuan, and about 137 million Chinese people were severely affected by various natural disasters (Xie et al. 2018 ).

Mitigation and adaptation strategies of climate changes

Adaptation and mitigation are the crucial factors to address the response to CC (Jahanzad et al. 2020 ). Researchers define mitigation on climate changes, and on the other hand, adaptation directly impacts climate changes like floods. To some extent, mitigation reduces or moderates greenhouse gas emission, and it becomes a critical issue both economically and environmentally (Botzen et al. 2021 ; Jahanzad et al. 2020 ; Kongsager 2018 ; Smit et al. 2000 ; Vale et al. 2021 ; Usman et al. 2021 ; Verheyen 2005 ).

Researchers have deep concern about the adaptation and mitigation methodologies in sectoral and geographical contexts. Agriculture, industry, forestry, transport, and land use are the main sectors to adapt and mitigate policies(Kärkkäinen et al. 2020 ; Waheed et al. 2021 ). Adaptation and mitigation require particular concern both at the national and international levels. The world has faced a significant problem of climate change in the last decades, and adaptation to these effects is compulsory for economic and social development. To adapt and mitigate against CC, one should develop policies and strategies at the international level (Hussain et al. 2020 ). Figure  6 depicts the list of current studies on sectoral impacts of CC with adaptation and mitigation measures globally.

Sectoral impacts of climate change with adaptation and mitigation measures.

Conclusion and future perspectives

Specific socio-agricultural, socio-economic, and physical systems are the cornerstone of psychological well-being, and the alteration in these systems by CC will have disastrous impacts. Climate variability, alongside other anthropogenic and natural stressors, influences human and environmental health sustainability. Food security is another concerning scenario that may lead to compromised food quality, higher food prices, and inadequate food distribution systems. Global forests are challenged by different climatic factors such as storms, droughts, flash floods, and intense precipitation. On the other hand, their anthropogenic wiping is aggrandizing their existence. Undoubtedly, the vulnerability scale of the world’s regions differs; however, appropriate mitigation and adaptation measures can aid the decision-making bodies in developing effective policies to tackle its impacts. Presently, modern life on earth has tailored to consistent climatic patterns, and accordingly, adapting to such considerable variations is of paramount importance. Because the faster changes in climate will make it harder to survive and adjust, this globally-raising enigma calls for immediate attention at every scale ranging from elementary community level to international level. Still, much effort, research, and dedication are required, which is the most critical time. Some policy implications can help us to mitigate the consequences of climate change, especially the most affected sectors like the agriculture sector;

Warming might lengthen the season in frost-prone growing regions (temperate and arctic zones), allowing for longer-maturing seasonal cultivars with better yields (Pfadenhauer 2020 ; Bonacci 2019 ). Extending the planting season may allow additional crops each year; when warming leads to frequent warmer months highs over critical thresholds, a split season with a brief summer fallow may be conceivable for short-period crops such as wheat barley, cereals, and many other vegetable crops. The capacity to prolong the planting season in tropical and subtropical places where the harvest season is constrained by precipitation or agriculture farming occurs after the year may be more limited and dependent on how precipitation patterns vary (Wu et al. 2017 ).

The genetic component is comprehensive for many yields, but it is restricted like kiwi fruit for a few. Ali et al. ( 2017 ) investigated how new crops will react to climatic changes (also stated in Mall et al. 2017 ). Hot temperature, drought, insect resistance; salt tolerance; and overall crop production and product quality increases would all be advantageous (Akkari 2016 ). Genetic mapping and engineering can introduce a greater spectrum of features. The adoption of genetically altered cultivars has been slowed, particularly in the early forecasts owing to the complexity in ensuring features are expediently expressed throughout the entire plant, customer concerns, economic profitability, and regulatory impediments (Wirehn 2018 ; Davidson et al. 2016 ).

To get the full benefit of the CO 2 would certainly require additional nitrogen and other fertilizers. Nitrogen not consumed by the plants may be excreted into groundwater, discharged into water surface, or emitted from the land, soil nitrous oxide when large doses of fertilizer are sprayed. Increased nitrogen levels in groundwater sources have been related to human chronic illnesses and impact marine ecosystems. Cultivation, grain drying, and other field activities have all been examined in depth in the studies (Barua et al. 2018 ).

• The technological and socio-economic adaptation

The policy consequence of the causative conclusion is that as a source of alternative energy, biofuel production is one of the routes that explain oil price volatility separate from international macroeconomic factors. Even though biofuel production has just begun in a few sample nations, there is still a tremendous worldwide need for feedstock to satisfy industrial expansion in China and the USA, which explains the food price relationship to the global oil price. Essentially, oil-exporting countries may create incentives in their economies to increase food production. It may accomplish by giving farmers financing, seedlings, fertilizers, and farming equipment. Because of the declining global oil price and, as a result, their earnings from oil export, oil-producing nations may be unable to subsidize food imports even in the near term. As a result, these countries can boost the agricultural value chain for export. It may be accomplished through R&D and adding value to their food products to increase income by correcting exchange rate misalignment and adverse trade terms. These nations may also diversify their economies away from oil, as dependence on oil exports alone is no longer economically viable given the extreme volatility of global oil prices. Finally, resource-rich and oil-exporting countries can convert to non-food renewable energy sources such as solar, hydro, coal, wind, wave, and tidal energy. By doing so, both world food and oil supplies would be maintained rather than harmed.

IRENA’s modeling work shows that, if a comprehensive policy framework is in place, efforts toward decarbonizing the energy future will benefit economic activity, jobs (outweighing losses in the fossil fuel industry), and welfare. Countries with weak domestic supply chains and a large reliance on fossil fuel income, in particular, must undertake structural reforms to capitalize on the opportunities inherent in the energy transition. Governments continue to give major policy assistance to extract fossil fuels, including tax incentives, financing, direct infrastructure expenditures, exemptions from environmental regulations, and other measures. The majority of major oil and gas producing countries intend to increase output. Some countries intend to cut coal output, while others plan to maintain or expand it. While some nations are beginning to explore and execute policies aimed at a just and equitable transition away from fossil fuel production, these efforts have yet to impact major producing countries’ plans and goals. Verifiable and comparable data on fossil fuel output and assistance from governments and industries are critical to closing the production gap. Governments could increase openness by declaring their production intentions in their climate obligations under the Paris Agreement.

It is firmly believed that achieving the Paris Agreement commitments is doubtlful without undergoing renewable energy transition across the globe (Murshed 2020 ; Zhao et al. 2022 ). Policy instruments play the most important role in determining the degree of investment in renewable energy technology. This study examines the efficacy of various policy strategies in the renewable energy industry of multiple nations. Although its impact is more visible in established renewable energy markets, a renewable portfolio standard is also a useful policy instrument. The cost of producing renewable energy is still greater than other traditional energy sources. Furthermore, government incentives in the R&D sector can foster innovation in this field, resulting in cost reductions in the renewable energy industry. These nations may export their technologies and share their policy experiences by forming networks among their renewable energy-focused organizations. All policy measures aim to reduce production costs while increasing the proportion of renewables to a country’s energy system. Meanwhile, long-term contracts with renewable energy providers, government commitment and control, and the establishment of long-term goals can assist developing nations in deploying renewable energy technology in their energy sector.

Author contribution

KA: Writing the original manuscript, data collection, data analysis, Study design, Formal analysis, Visualization, Revised draft, Writing-review, and editing. MZQ: Writing the original manuscript, data collection, data analysis, Writing-review, and editing. HS: Contribution to the contextualization of the theme, Conceptualization, Validation, Supervision, literature review, Revised drapt, and writing review and editing. MM: Writing review and editing, compiling the literature review, language editing. HM: Writing review and editing, compiling the literature review, language editing. IY: Contribution to the contextualization of the theme, literature review, and writing review and editing.

Availability of data and material

Declarations.

Not applicable.

The authors declare no competing interests.

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Contributor Information

Kashif Abbass, Email: nc.ude.tsujn@ssabbafihsak .

Muhammad Zeeshan Qasim, Email: moc.kooltuo@888misaqnahseez .

Huaming Song, Email: nc.ude.tsujn@gnimauh .

Muntasir Murshed, Email: [email protected] .

Haider Mahmood, Email: moc.liamtoh@doomhamrediah .

Ijaz Younis, Email: nc.ude.tsujn@sinuoyzaji .

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The New Climate Denial

How social media platforms and content producers profit by spreading new forms of climate denial.

2023 was the hottest year on record, ever. Billions of people across the world experienced extreme heat, droughts, wildfires and major floods. Climate deniers can no longer pretend climate change isn’t happening - so they’ve changed their strategy. CCDH’s groundbreaking AI-powered research shows that New Climate Denial narratives that aim to undermine the climate movement, science and solutions, now constitute 70% of climate denial content on YouTube in 2023.

Download report Find out more

Report length: 56 pages Published: January 16, 2024 CCDH

2023 was the hottest year on record. Once unprecedented wildfires, floods, unbearable heat, and droughts are becoming normal to billions of people worldwide. It is difficult to deny the simple fact that our climate is changing in predictable and yet, still, even now, shocking ways. 

And yet, the sensible majority of us who seek to avert climate catastrophe find ourselves continually having to deal with a tidal wave of disinformation designed to delay action. These lies, welcomed, enabled, and often funded by oil and gas tycoons who benefit financially, are cynically used by political leaders to explain why they remain stubbornly incapable of taking urgent corrective action.

In this report, for the first time, researchers at the Center for Countering Digital Hate have quantified the startling and important rise over the past five years in what we call “New Denial” — the departure from rejection of anthropogenic climate change, to attacks on climate science and scientists, and rhetoric seeking to undermine confidence in solutions to climate change. “New Denial” claims now constitute 70% of all climate denial claims made on YouTube, up from 35% six years ago.

This study centers on data analysis performed by an AI tool, CARDS, developed by academics Travis G. Coan, Constantine Boussalis, John Cook and Mirjam O. Nanko. The AI allowed us to quantify the frequency of different types of climate denialist claims in text. CCDH researchers identified the changing tactics of climate deniers on YouTube by analyzing thousands of hours of transcripts of videos on the platform from 96 channels dating back to 2018.

In 2018, outright denialist claims like “the weather is cold” and “we’re heading into an ice age” were popular among climate denialists – but as temperatures and evidence of global warming have increased, those narratives are no longer as effective. Analysis of 4,458 hours or nearly 186 days of YouTube content since 2018 shows that “Old Denial” claims that anthropogenic climate change isn’t happening have dropped from 65% of all claims in 2018 to just 30% of claims in 2023.

It is vital that those advocating for action to avert climate disaster take note of this substantial shift from denial of anthropogenic climate change to undermining trust in both solutions and science itself, and shift our focus, our resources and our counternarratives accordingly. 

The narrative shift from “Old Denial” to “New Denial” seeks to undermine the solutions to mitigating the climate crisis and delay political action. A failure to shift our strategies would be enormously damaging. 

This report is a call-to-action to the climate change advocates, the funders, the politicians doing the hard work to green our economic models and incentives, to ensure their work effectively counters what our opponents are doing now, not six years ago.

Could the global cost of climate change really be six times worse than thought?

A new paper written for the National Bureau of Economic Research (NBER) suggests that the global economic cost of climate change could be around six times higher than previous estimations.

The paper, written by Northwestern economics professor Diego Känzig and Harvard economics professor Adrien Bilal, suggests that every one degree of atmospheric warming reduces global GDP by 12%.

It uses global heating data cross-referenced against aggregated national GDPs to come to a higher figure. The authors believe that this model provides a more complete picture, as many of the shocks, including extreme wind and precipitation, are affected by global conditions rather than localised heating.

It also places the social cost of carbon (SCC) at over $1,000/tCO2. This global measure estimates the economic damage caused by every tonne of carbon emitted and has historically been set far lower. According to the authors, their own calculations would only place the SCC at $151/tCO2 if evaluating local rather than global temperature shocks.

What does this mean for global economies?

The findings of this paper are clearly worrying as they suggest the threat to markets posed by climate change is significantly higher than previously quantifiable. The authors of the paper describe the impacts of a 1°C as “of the same magnitude as the growth impacts that typically occur after severe banking or financial crises,” and the long-term impacts of climate change as “comparable to the economic damage caused by fighting a war domestically and permanently [italics theirs].”

However, they also lead the authors to a conclusion that will likely be championed among environmental campaigners. By placing the SCC so high, the paper also ends up with a Domestic Cost of Carbon (DCC) high enough to justify unilateral decarbonisation in states like the US.

DCC is the cost per tonne of CO2 to an individual country and is commonly used when calculating the cost/benefit of decarbonisation measures. A typical analysis, the paper states, places the US DCC at around $30/tCO2, higher than the average cost of decarbonisation programmes that range from $27 to $95 per tonne. With a massively higher SCC, though, the domestic cost sits at $211/tCO2, meaning decarbonisation efforts are worthwhile even if other countries do not do the same.

The Breakthrough Institute controversy

The study has generated some controversy on X, where members of the market-focused environmental research centre The Breakthrough Institute (BTI) and associated ‘ecomodernists’ have questioned its methodology.

Co-director of climate and energy at the BTI Dr. Patrick Brown responded to the paper in a long post detailing his own findings using a different methodology, which he says “indicates to me that the signal supposedly identified is very difficult to see and, at best, is ‘not large’.”

This in turn prompted responses from academics including professor Marshall Burke, Stanford, who described Brown’s analysis as “akin to testing whether an analytical result is robust to a much worse way of running the analysis.”

The Breakthrough Institute is not without its own controversies. Its founder’s ecomodernist philosophy has been critiqued by journalists and academics, with climate scientist Michael E. Mann describing the organisation in his 2016 book The Madhouse Effect as appearing to be “opposed to anything – be it a price on carbon or incentives for renewable energy – that would have a meaningful impact,” while remaining “curiously preoccupied with opposing advocates for meaningful climate action and [being] coincidentally linked to natural gas interests.”

Industry response

The report may not have an immediate impact on the green finance sector, according to Philippe Pernstich, Founding Footprinting Lead at carbon accounting firm Minimum . He tells Energy Monitor : “The private sector does not directly apply the social cost of carbon or even the domestic cost of carbon.

“However, if countries incorporate the findings from this research, they will likely adjust their carbon pricing accordingly. Before this happens, financial institutions and the private sector more broadly should take note of these figures in their risk assessments. While this may not affect the physical risk estimates from climate change, it will impact the adaptation risks related to future carbon pricing.

“As a further knock-on effect, this could improve the business case for more expensive abatement options and increase the number of opportunities for meeting net-zero targets."

Of the paper’s methodology and findings, Pernstich comments: “The significant discrepancy of the results from the report compared to a relatively extensive body of previous research certainly warrants some pause for thought. The reason for this difference is well argued, but I would like to see a wider response to these findings. This is one of the strengths of the Intergovernmental Panel on Climate Change, as it periodically reviews all the literature published over a period of time to establish a consensus view.

“One of the really interesting implications of these findings, however, is that at this cost level, countries can justify their typical abatement costs purely on their own domestic costs of avoided climate change, rather than having to consider and internalise global costs. In effect, this could counteract the ‘tragedy of the commons’ where no individual actor is motivated to change their behaviour, leading to everyone suffering collectively from the lack of action.

“The methodology is well defined, building on previous research and directly addressing the differences to previous studies that explain the significant difference in results. As is common with scientific research, I would expect the real worth of this study to be demonstrated by further work in this area that responds to this research."

"Could the global cost of climate change really be six times worse than thought?" was originally created and published by Energy Monitor , a GlobalData owned brand.

The information on this site has been included in good faith for general informational purposes only. It is not intended to amount to advice on which you should rely, and we give no representation, warranty or guarantee, whether express or implied as to its accuracy or completeness. You must obtain professional or specialist advice before taking, or refraining from, any action on the basis of the content on our site.

The Macroeconomic Impact of Climate Change: Global vs. Local Temperature

This paper estimates that the macroeconomic damages from climate change are six times larger than previously thought. We exploit natural variability in global temperature and rely on time-series variation. A 1°C increase in global temperature leads to a 12% decline in world GDP. Global temperature shocks correlate much more strongly with extreme climatic events than the country-level temperature shocks commonly used in the panel literature, explaining why our estimate is substantially larger. We use our reduced-form evidence to estimate structural damage functions in a standard neoclassical growth model. Our results imply a Social Cost of Carbon of $1,056 per ton of carbon dioxide. A business-as-usual warming scenario leads to a present value welfare loss of 31%. Both are multiple orders of magnitude above previous estimates and imply that unilateral decarbonization policy is cost-effective for large countries such as the United States.

Adrien Bilal gratefully acknowledges support from the Chae Family Economics Research Fund at Harvard University. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

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• Open access
• Published: 14 May 2024

Rain, rain, go away, come again another day: do climate variations enhance the spread of COVID-19?

• Masha Menhat 1 ,
• Effi Helmy Ariffin   ORCID: orcid.org/0000-0002-8534-0113 2 ,
• Wan Shiao Dong 3 ,
• Junainah Zakaria 2 ,
• Aminah Ismailluddin 3 ,
• Hayrol Azril Mohamed Shafril 4 ,
• Mahazan Muhammad 5 ,
• Ahmad Rosli Othman 6 ,
• Thavamaran Kanesan 7 ,
• Suzana Pil Ramli 8 ,
• Mohd Fadzil Akhir 2 &
• Amila Sandaruwan Ratnayake 9  

Globalization and Health volume  20 , Article number:  43 ( 2024 ) Cite this article

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The spread of infectious diseases was further promoted due to busy cities, increased travel, and climate change, which led to outbreaks, epidemics, and even pandemics. The world experienced the severity of the 125 nm virus called the coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization (WHO) in 2019. Many investigations revealed a strong correlation between humidity and temperature relative to the kinetics of the virus’s spread into the hosts. This study aimed to solve the riddle of the correlation between environmental factors and COVID-19 by applying RepOrting standards for Systematic Evidence Syntheses (ROSES) with the designed research question. Five temperature and humidity-related themes were deduced via the review processes, namely 1) The link between solar activity and pandemic outbreaks, 2) Regional area, 3) Climate and weather, 4) Relationship between temperature and humidity, and 5) the Governmental disinfection actions and guidelines. A significant relationship between solar activities and pandemic outbreaks was reported throughout the review of past studies. The grand solar minima (1450-1830) and solar minima (1975-2020) coincided with the global pandemic. Meanwhile, the cooler, lower humidity, and low wind movement environment reported higher severity of cases. Moreover, COVID-19 confirmed cases and death cases were higher in countries located within the Northern Hemisphere. The Blackbox of COVID-19 was revealed through the work conducted in this paper that the virus thrives in cooler and low-humidity environments, with emphasis on potential treatments and government measures relative to temperature and humidity.

• The coronavirus disease 2019 (COIVD-19) is spreading faster in low temperatures and humid area.

• Weather and climate serve as environmental drivers in propagating COVID-19.

• Solar radiation influences the spreading of COVID-19.

• The correlation between weather and population as the factor in spreading of COVID-19.

Graphical abstract

Introduction

The revolution and rotation of the Earth and the Sun supply heat and create differential heating on earth. The movements and the 23.5° inclination of the Earth [ 1 ] separate the oblate-ellipsoid-shaped earth into northern and southern hemispheres. Consequently, the division results in various climatic zones at different latitudes and dissimilar local temperatures (see Fig.  1 ) and affects the seasons and length of a day and night in a particular region [ 2 ]. Global differential heating and climate variability occur due to varying solar radiation received by each region [ 3 ]. According to Trenberth and Fasullo [ 4 ] and Hauschild et al. [ 5 ] the new perspective on the issue of climate change can be affected relative to the changes in solar radiation patterns. Since the study by Trenberth and Fasullo [ 4 ] focused on climate model changes from 1950 to 2100, it was found that the role of changing clouds and trapped sunlight can lead to an opening of the aperture for solar radiation.

The annual average temperature data for 2021 in the northern and southern hemispheres ( Source: meteoblue.com ). Note: The black circles mark countries with high Coronavirus disease 2019 (COVID-19) infections

Furthermore, the heat from sunlight is essential to humans; several organisms could not survive without it. Conversely, the spread of any disease-carrying virus tends to increase with less sunlight exposure [ 6 ]. Historically, disease outbreaks that led to epidemic and pandemic eruptions were correlated to atmospheric changes. Pandemic diseases, such as the flu (1918), Asian flu (1956–1958), Hong Kong flu (1968), and recently, the coronavirus disease 2019 (COVID-19) (2019), recorded over a million death toll each during the winter season or minimum temperature conditions [ 7 ]. The total number of COVID-19 cases is illustrated in Fig.  2 .

A graphical representation of the total number of COVID-19 cases across various periods between 2020 and 2021. ( Source : www.worldometers.info ). Note: The black circles indicate countries with high numbers COVID-19-infections

In several previous outbreaks, investigations revealed a significant association between temperature and humidity with a particular focus on the transmission dynamics of the infection from the virus into the hosts [ 8 , 9 , 10 ]. Moreover, disease outbreaks tended to heighten in cold temperatures and low humidity [ 11 ]. Optimal temperature and sufficient relative humidity during evaporation are necessary for cloud formation, resulting in the precipitated liquid falling to the ground as rain, snow, or hail due to the activity of solar radiation balancing [ 4 ].

Consequently, the radiation balancing processes in the atmosphere are directly linked to the living beings on the earth, including plants and animals, and as well as viruses and bacterias. According to Carvalho et al. [ 12 ]‘s study, the survival rate of the Coronaviridae Family can decrease during summer seasons. Nevertheless, numerous diseases were also developed from specific viruses, such as influenza, malaria, and rubella, and in November 2019, a severe health threat originated from a 125 nm size of coronavirus, had resulted in numerous deaths worldwide.

Transmission and symptoms of COVID-19

The COVID-19, or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an infectious disease caused by a newly discovered pathogenic virus from the coronavirus family, the novel coronavirus (2019-nCoV) [ 13 ]. The first case was recorded in Wuhan, China, in December 2019 [ 14 ]. The pathogenic virus is transmitted among humans when they breathe in air contaminated with droplets and tiny airborne particles containing the virus [ 14 , 15 , 16 , 17 , 18 ].

According to the World Health Organization (WHO), the most common symptoms of COVID-19 infection include fever, dry cough, and tiredness. Nevertheless, older people and individuals with underlying health problems (lung and heart problems, high blood pressure, diabetes, or cancer) are at higher risk of becoming seriously ill and developing difficulty breathing [ 19 ]. The COVID-19 was initially only predominant in China but rapidly spread to other countries globally. The remarkably swift acceleration of the number of infections and mortality forced WHO to declare COVID-19 a global public health emergency on the 30th of January 2020, which was later declared as a pandemic on the 11th of March 2020 [ 20 ].

Since no vaccine was available then, WHO introduced the COVID-19 preventative measures to reduce the chances of virus transmission. The guideline for individual preventative included practising hand and respiratory hygiene by regularly cleaning hands with soap and water or alcohol-based sanitisers, wear a facemask and always maintaining at least a one-meter physical distance [ 21 ]. Nevertheless, the worldwide transmission of COVID-19 has resulted in fear and forced numerous countries to impose restrictions rules, such as lockdown, travel bans, closed country borders, restrictions on shipping activities, and movement limitations, to diminish the spread of COVID-19 [ 22 ].

According to WHO, by the 2nd of December 2020, 63,379,338 confirmed cases and 1,476,676 mortalities were recorded globally. On the 3rd of December 2021, 263,655,612 confirmed cases and deaths were recorded, reflecting increased COVID-19 infections compared to the previous year. The American and European regions documented the highest COVID-19 patients with 97,341,769 and 88,248,591 cases, respectively (see Fig. 2 ), followed by Southeast Asia with 44,607,287, Eastern Mediterranean accounted 16,822,791, Western Pacific recorded 6,322,034, and Africa reported the lowest number of cases at 6,322,034 [ 19 ].

Recently, an increasing number of studies are investigating the association between environmental factors (temperature and humidity) and the viability, transmission, and survival of the coronavirus [ 23 , 24 , 25 , 26 ]. The results primarily demonstrated that temperature was more significantly associated with the transmission of COVID-19 [ 27 , 28 , 29 ] and its survival period on the surfaces of objects [ 30 ]. Consequently, the disease was predominant in countries with low temperature and humidity [ 31 ], which was also proven by Diao et al. [ 32 ]‘s study demonstrating higher rates of COVID-19 transmission in China, England, Germany, and Japan.

A comprehensive systematic literature review (SLR) is still lacking despite numerous research on environmental factors linked to coronavirus. Accordingly, this article aimed to fill the gap in understanding and identifying the correlation between environmental factors and COVID-19 by analysing existing reports. Systematically reviewing existing literature is essential to contribute to the body of knowledge and provide beneficial information for public health policymakers.

Methodology

The present study reviewed the protocols, formulation of research questions, selection of studies, appraisal of quality, and data abstraction and analysis.

The protocol review

The present SLR was performed according to the reporting standards for systematic evidence syntheses (ROSES) and followed or adapted the guidelines as closely as possible. Thus, in this study, a systematic literature review was guided by the ROSES review protocol (Fig.  3 ). Compared to preferred reporting items for systematic review and meta-analysis (PRISMA), ROSES is a review protocol specifically designed for a systematic review in the conservation or environment management fields [ 33 ]. Compared to PRISMA, ROSES offers several advantages, as it is tailored to environmental systematic review, which reduces emphasis on quantitative synthesis (e.g. meta-analysis etc.) that is only reliable when used with appropriate data [ 34 ].

The flow diagram guide by ROSES protocol and Thematical Analysis

The current SLR started by determining the appropriate research questions, followed by the selection criteria, including the review, specifically on the keywords employed and the selection of journals database. Subsequently, the appraisal quality process and data abstraction and analysis were conducted.

Formulation of research questions

The entire process of this SLR was guided by the specific research questions, while sources to be reviewed and data abstraction and analysis were in line with the determined research question [ 35 , 36 ]. In the present article, a total of five research questions were formed, namely:

What the link between solar activity and COVID-19 pandemic outbreaks?

Which regions were more prone to COVID-19?

What were the temporal and spatial variabilities of high temperature and humidity during the spread of COVID-19?

What is the relationship between temperature and humidity in propagating COVID-19?

How did the government’s disinfection actions and guidelines can be reducing the spread of COVID-19?

Systematic searching strategies

Selection of studies.

In this stage of the study, the appropriate keywords to be employed in the searching process were determined. After referring to existing literature, six main keywords were chosen for the searching process, namely COVID-19, coronavirus, temperature, humidity, solar radiation and population density. The current study also utilised the boolean operators (OR, AND, AND NOT) and phrase searching.

Scopus was employed as the main database during the searching process, in line with the suggestion by Gusenbauer and Haddaway [ 37 ], who noted the strength of the database in terms of quality control and search and filtering functions. Furthermore, Google Scholar was selected as the supporting database. Although Halevi et al. [ 38 ] expressed concerns about its quality, Haddaway et al. [ 39 ] reported that due to its quantity, Google Scholar was suitable as a supporting database in SLR studies.

In the first stage of the search, 2550 articles were retrieved, which were then screened. The suitable criteria were also determined to control the quality of the articles reviewed [ 40 ]. The criteria are: any documents published between 2000 to 2022, documents that consist previously determined keywords, published in English, and any environment-related studies that focused on COVID-19. Based on these criteria, 2372 articles were excluded and 178 articles were proceeded to the next step namely eligibility. In the eligibility process, the title and the abstract of the articles were examined to ensure its relevancy to the SLR and in this process a total of 120 articles were excluded and only 58 articles were processed in the next stage.

Appraisal of the quality

The study ensured the rigor of the chosen articles based on best evidence synthesis. In the process, predefined inclusion criteria for the review were appraised by the systematic review team based on previously established guidelines and the studies were then judged as being scientifically admissible or not [ 40 ]. Hence, by controlling the quality based on the best evidence synthesis, the present SLR controls its quality by including articles that are in line with the inclusion criteria. It means that any article published within the timeline (in the year 2000 and above), composed of predetermined keywords, in English medium, and environment-related investigations focusing on COVID-19 are included in the review. Based on this process, all 58 articles fulfilled all the inclusion criteria and are considered of good quality and included in the review.

Data abstraction and analysis

The data abstraction process in this study was performed based on five research questions (please refer to 2.2, formulation of research questions). The data that was able to answer the questions were abstracted and placed in a table to ease the data analysis process. The primary data analysis technique employed in the current study was qualitative and relied on thematic analysis.

The thematic technique is a descriptive method that combines data flexibly with other information evaluation methods [ 41 ], aiming to identify the patterns in studies. Any similarities and relationships within the abstracted data emerge as patterns. Subsequently, suitable themes and sub-themes would be developed based on obtained patterns [ 42 ]. Following the thematic process, five themes were selected in this study.

Background of the selected articles

The current study selected 58 articles for the SLR. Five themes were developed based on the thematic analysis from the predetermined research questions: the link between solar activity and pandemic outbreaks, regional area, climate and weather, the relationship between temperature and humidity, and government disinfection action guidelines. Among the articles retrieved between 2000 and 2022; two were published in 2010, one in 2011, four in 2013, three in 2014, two in 2015, six in 2016 and 2017, respectively, one in 2018, six in 2019, twelve in 2020, eight in 2021, and seven in 2022.

Temperature- and humidity-related themes

The link between solar activity and pandemic outbreaks.

Numerous scientists have investigated the relationship between solar activities and pandemic outbreaks over the years ([ 43 ]; A [ 27 , 44 , 45 ].). Nuclear fusions from solar activities have resulted in minimum and maximum solar sunspots. Maximum solar activities are characterised by a high number of sunspots and elevated solar flare frequency and coronal mass injections. Minimum solar sunspot occurrences are identified by low interplanetary magnetic field values entering the earth [ 1 ].

A diminished magnetic field was suggested to be conducive for viruses and bacteria to mutate, hence the onset of pandemics. Nonetheless, Hoyle and Wickramasinghe [ 46 ] reported that the link between solar activity and pandemic outbreaks is only speculative. The literature noted that the data recorded between 1930 and 1970 demonstrated that virus transmissions and pandemic occurrences were coincidental. Moreover, no pandemic cases were reported in 1979, when minimum solar activity was recorded [ 47 ].

Chandra Wickramasinghe et al. [ 48 ] suggested a significant relationship between pandemic outbreaks and solar activities as several grand solar minima, including Sporer (1450–1550 AD), Mounder (1650–1700 AD), and Dalton (1800–1830) minimums, were recorded coinciding with global pandemics of diseases, such as smallpox, the English sweat, plague, and cholera pandemics. Furthermore, since the Dalton minimum, which recorded minimum sunspots, studies from 2002 to 2015 have documented the reappearance of previous pandemics. For example, influenza subtype H1N1 1918/1919 episodically returned in 2009, especially in India, China, and other Asian countries. Zika virus, which first appeared in 1950, flared and became endemic in 2015, transmitted sporadically, specifically in African countries. Similarly, SARS-CoV was first recorded in China in 2002 and emerged as an outbreak, MERS-CoV, in middle east countries a decade later, in 2012.

In 2020, the World Data Centre Sunspot Index and Long-term Solar Observations ( http://sidc.be ) confirmed that a new solar activity was initiated in December 2019, during which a novel coronavirus pandemic also occurred, and present a same as the previous hypothesis. Nevertheless, a higher number of pandemic outbreaks were documented during low minimum solar activities, including Ebola (1976), H5N1 (Nipah) (1967–1968), H1N1 (2009), and COVID-19 (2019–current). Furthermore, Wickramasinghe and Qu [ 49 ] reported that since 1918 or 1919, more devastating and recurrent pandemics tend to occur, particularly after a century. Consequently, within 100 years, a sudden surge of influenza was recorded, and novel influenza was hypothesised to emerge.

Figure  4 demonstrates that low minimum solar activity significantly reduced before 2020, hence substantiating the claim that pandemic events are closely related to solar activities. Moreover, numerous studies (i.e. [ 43 ], Chandra [ 46 , 47 , 48 ]) reported that during solar minimums, new viruses could penetrate the surfaces of the earth and high solar radiation would result in lower infection rates, supporting the hypothesis mentioned above.

The number of sunspots in the last 13 years. Note : The yellow curve indicates the daily sunspot number and the 2010–2021 delineated curve illustrates the minimum solar activity recorded (source: http://sidc.be/silso )

Regional area

In early December 2019, Wuhan, China, was reported as the centre of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak [ 50 ]. Chinese health authorities immediately investigated and controlled the spread of the disease. Nevertheless, by late January 2020, the WHO announced that COVID-19 was a global public health emergency. The upgrade was due to the rapid rise in confirmed cases, which were no longer limited to Wuhan [ 28 ]. The disease had spread to 24 other countries, which were mainly in the northern hemisphere, particularly the European and Western Pacific regions, such as France, United Kingdom, Spain, South Korea, Japan, Malaysia, and Indonesia [ 51 , 52 ]. The migration or movement of humans was the leading agent in the spread of COVID-19, resulting in an almost worldwide COVID-19 pandemic [ 53 ].

The first hotspots of the epidemic outspread introduced by the Asian and Western Pacific regions possessed similar winter climates with an average temperature and humidity rate of 5–11 °C and 47–79%. Consequently, several publications reviewed in the current study associated the COVID-19 outbreak with regional climates (i.e. [ 1 , 29 , 54 , 55 ]) instead of its close connection to China. This review also discussed the effects of a range of specific climatological variables on the transmission and epidemiology of COVID-19 in regional climatic conditions.

America and Europe documented the highest COVID-19 cases, outnumbering the number reported in Asia [ 19 ] and on the 2nd of December 2020, the United States of America (USA) reported the highest number of confirmed COVID-19 infections, with over 13,234,551 cases and 264,808 mortalities (Da S [ 56 ].). The cases in the USA began emerging in March 2020 and peaked in late November 2020, during the wintertime in the northern hemisphere (December to March) [ 53 ]. Figure  5 demonstrates the evolution of the COVID-19 pandemic in several country which represent comparison two phase of summer and one phase of winter. Most of these countries tend to increase of COVID cases close to winter season. Then, it can be worsening on phase two of summer due to do not under control of human movement although the normal trend it is presenting during winter phase.

The evolution of the COVID-19 pandemic from the 15th of February 2020 to the 2nd of December 2020 ( Source: https://www.worldometers.info/coronavirus )

The coronavirus spread aggressively across the European region, which recorded the second highest COVID-19 confirmed cases after America. At the end of 2020, WHO reported 19,071,275 Covid-19 cases in the area, where France documented 2,183,275 cases, the European country with the highest number of confirmed cases, followed by the United Kingdom (1,629,661 cases) and Spain (1,652,801 cases) [ 19 ]. Europe is also located in the northern hemisphere and possesses a temperate climate.

The spatial and temporal transmission patterns of coronavirus infection in the European region were similar to America and the Eastern Mediterranean, where the winter season increased COVID-19 cases. Typically, winter in Europe occurs at the beginning of October and ends in March. Hardy et al. [ 57 ] also stated that temperature commonly drops below freezing (approximately − 1 °C) when snow accumulates between December to mid-March, resulting in an extreme environment. Figure 5 indicates that COVID-19 cases peaked in October when the temperature became colder [ 21 ]. Similarly, the cases were the highest in the middle of the year in Australia and South Asian countries, such as India, that experience winter and monsoon, respectively, during the period.

In African regions, the outbreak of COVID-19 escalated rapidly from June to October before falling from October to March, as summer in South Africa generally occurs from November to March, while winter from June to August. Nevertheless, heavy rainfall generally transpires during summer, hence the warm and humid conditions in South Africa and Namibia during summer, while the opposite happens during winter (cold and dry). Consequently, the outbreak in the region recorded an increasing trend during winter and subsided during the summer, supporting the report by Gunthe et al. [ 58 ]. Novel coronavirus disease presents unique and grave challenges in Africa, as it has for the rest of the world. However, the infrastructure and resources have limitations for Africa countries facing COVID-19 pandemic and the threat of other diseases [ 59 ].

Conclusively, seasonal and regional climate patterns were associated with COVID-19 outbreaks globally. According to Kraemer et al. [ 60 ], they used real-time mobility data in Wuhan and early measurement presented a positive correlation between human mobility and spread of COVID-19 cases. However, after the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan.

Climate and weather

The term “weather” represents the changes in the environment that occur daily and in a short period, while “climate” is defined as atmospheric changes happening over a long time (over 3 months) in specific regions. Consequently, different locations would experience varying climates. Numerous reports suggested climate and weather variabilities as the main drivers that sped or slowed the transmission of SARS-CoV-2 worldwide [ 44 , 61 , 62 , 63 ].

From a meteorological perspective, a favourable environment has led to the continued existence of the COVID-19 virus in the atmosphere [ 64 ]. Studies demonstrated that various meteorological conditions, such as the rate of relative humidity (i.e. [ 28 ]), precipitation (i.e. [ 65 ]), temperature (i.e. [ 66 ]), and wind speed factors (i.e. [ 54 ]), were the crucial components that contributed to the dynamic response of the pandemic, influencing either the mitigation or exacerbation of novel coronavirus transmission. In other words, the environment was considered the medium for spreading the disease when other health considerations were put aside. Consequently, new opinions, knowledge, and findings are published and shared to increase awareness, thus encouraging preventive measures within the public.

The coronavirus could survive in temperatures under 30 °C with a relative humidity of less than 80% [ 67 ], suggesting that high temperatures and lower relative humidity contributed to the elicitation of COVID-19 cases [ 18 , 51 , 58 , 68 ]. Lagtayi et al. [ 7 ] highlighted temperature as a critical factor, evidently from the increased transmission rate of MERS-Cov in African states with a warm and dry climate. Similarly, the highest COVID-19 cases were recorded in dry temperate regions, especially in western Europe (France and Spain), China, and the USA, while the countries nearer to the equator were less affected. Nevertheless, the temperature factor relative to viral infections depends on the protein available in the viruses. According to Chen and Shakhnovich [ 69 ], there is a good correlation between decreasing temperature and the growth of proteins in virus. Consequently, preventive measures that take advantage of conducive environments for specific viruses are challenging.

Precipitation also correlates with influenza [ 43 ]. A report demonstrated that regions with at least 150 mm of monthly precipitation threshold level experienced fewer cases than regions with lower precipitation rates. According to Martins et al. [ 70 ], influenza and COVID-19 can be affected by climate, where virus can be spread through the respiratory especially during rainfall season. The daily spread of Covid-19 cases in tropical countries, which receive high precipitation levels, are far less than in temperate countries [ 27 ]. Likewise, high cases of COVID-19 were reported during the monsoon season (mid-year) in India during which high rainfall is recorded [ 71 ]. Moreover, the majority of the population in these regions has lower vitamin D levels, which may contribute to weakened immune responses during certain seasons [ 27 ].

Rainfall increases the relative atmospheric humidity, which is unfavourable to the coronaviruses as its transmission requires dry and cold weather. Moreover, several reports hypothesised that rain could wash away viruses on object surfaces, which is still questioned. Most people prefer staying home on rainy days, allowing less transmission or close contact. Conversely, [ 72 ] exhibited that precipitation did not significantly impact COVID-19 infectiousness in Oslo, Norway due the location in northern hemisphere which are during winter season presenting so cold.

Coşkun et al. [ 54 ] and Wu et al. [ 29 ] claimed that wind could strongly correlate with the rate of COVID-19 transmission. Atmospheric instability (turbulent occurrences) leads to increased wind speed and reduces the dispersion of particulate matter (PM 2.5 and PM 10 ) in the environment and among humans. An investigation performed in 55 cities in Italy during the COVID-19 outbreak proved that the areas with low wind movement (stable atmospheric conditions) possessed a higher correlation coefficient and exceeded the threshold value of the safe level of PM 2.5 and PM 10 . Resultantly, more individuals were recorded infected with the disease in the regions. As mentioned in Martins et al. [ 70 ] the COVID-19 can be affected by climate and the virus can be spread through respiratory which is the virus moving in the wind movement.

The relationship between temperature and humidity

Climatic parameters, such as temperature and humidity, were investigated as the crucial factors in the epidemiology of the respiratory virus survival and transmission of COVID-19 ([ 61 ]; S [ 73 , 74 ].). The rising number of confirmed cases indicated the strong transmission ability of COVID-19 and was related to meteorological parameters. Furthermore, several studies found that the disease transmission was associated with the temperature and humidity of the environment [ 55 , 64 , 68 , 75 ], while other investigations have examined and reviewed environmental factors that could influence the epidemiological aspects of Covid-19.

Generally, increased COVID-19 cases and deaths corresponded with temperature, humidity, and viral transmission and mortality. Various studies reported that colder and dryer environments favoured COVID-19 epidemiologically [ 45 , 76 , 77 ]. As example tropical region, the observations indicated that the summer (middle of year) and rainy seasons (end of the year) could effectively diminish the transmission and mortality from COVID-19. High precipitation statistically increases relative air humidity, which is unfavourable for the survival of coronavirus, which prefers dry and cold conditions [ 32 , 34 , 78 , 79 ]. Consequently, warmer conditions could reduce COVID-19 transmission. A 1 °C increase in the temperature recorded a decrease in confirmed cases by 8% increase [ 45 ].

Several reports established that the minimum, maximum, and average temperature and humidity correlated with COVID-19 occurrence and mortality [ 55 , 80 , 81 ]. The lowest and highest temperatures of 24 and 27.3 °C and a humidity between 76 and 91% were conducive to spreading the virulence agents. The propagation of the disease peaked at the average temperature of 26 °C and humidity of 55% before gradually decreasing with elevated temperature and humidity [ 78 ].

Researchers are still divided on the effects of temperature and humidity on coronavirus transmission. Xu et al. [ 26 ] confirmed that COVID-19 cases gradually increased with higher temperature and lower humidity, indicating that the virus was actively transmitted in warm and dry conditions. Nevertheless, several reports stated that the spread of COVID-19 was negatively correlated with temperature and humidity [ 10 , 29 , 63 ]. The conflicting findings require further investigation. Moreover, other factors, such as population density, elderly population, cultural aspects, and health interventions, might potentially influence the epidemiology of the disease and necessitate research.

Governmental disinfection actions and guidelines

The COVID-19 is a severe health threat that is still spreading worldwide. The epidemiology of the SAR-CoV-2 virus might be affected by several factors, including meteorological conditions (temperature and humidity), population density, and healthcare quality, that permit it to spread rapidly [ 16 , 17 ]. Nevertheless, in 2020, no effective pharmaceutical interventions or vaccines were available for the diagnosis, treatment, and epidemic prevention against COVID-19 [ 73 , 82 ]. Consequently, after 2020 the governments globally have designed and executed non-pharmacological public health measures, such as lockdown, travel bans, social distancing, quarantine, public place closure, and public health actions, to curb the spread of COVID-19 infections and several studies have reported on the effects of these plans [ 13 , 83 ].

The COVID-19 is mainly spread via respiratory droplets from an infected person’s mouth or nose to another in close contact [ 84 ]. Accordingly, WHO and most governments worldwide have recommended wearing facemasks in public areas to curb the transmission of COVID-19. The facemasks would prevent individuals from breathing COVID-19-contaminated air [ 85 ]. Furthermore, the masks could hinder the transmission of the virus from an infected person as the exhaled air is trapped in droplets collected on the masks, suspending it in the atmosphere for longer. The WHO also recommended adopting a proper hand hygiene routine to prevent transmission and employing protective equipment, such as gloves and body covers, especially for health workers [ 86 ].

Besides wearing protective equipment, social distancing was also employed to control the Covid-19 outbreak [ 74 , 87 ]. Social distancing hinders the human-to-human transmission of the coronavirus in the form of droplets from the mouth and nose, as evidenced by the report from Sun and Zhai [ 88 ]. Conversely, Nair & Selvaraj [ 89 ] demonstrated that social distancing was less effective in communities and cultures where gatherings are the norm. Nonetheless, the issue could be addressed by educating the public and implementing social distancing policies, such as working from home and any form of plague treatment.

Infected persons, individuals who had contact with confirmed or suspected COVID-19 patients, and persons living in areas with high transmission rates were recommended to undergo quarantine by WHO. The quarantine could be implemented voluntarily or legally enforced by authorities and applicable to individuals, groups, or communities (community containment) [ 90 ]. A person under mandatory quarantine must stay in a place for a recommended 14-day period, based on the estimated incubation period of the SARS-CoV-2 [ 19 , 91 ]. According to Stasi et al. [ 92 ], 14-days period for mandatory quarantine it is presenting a clinical improvement after they found 5-day group and 10-day group can be decrease number of patient whose getting effect of COVID-19 from 64 to 54% respectively. This also proven by Ahmadi et al. [ 43 ] and Foad et al. [ 93 ], quarantining could reduce the transmission of COVID-19.

Lockdown and travel bans, especially in China, the centre of the coronavirus outbreak, reduced the infection rate and the correlation of domestic air traffic with COVID-19 cases [ 17 ]. The observations were supported by Sun & Zhai [ 88 ] and Sun et al. [ 94 ], who noted that travel restrictions diminished the number of COVID-19 reports by 75.70% compared to baseline scenarios without restrictions. Furthermore, example in Malaysia, lockdowns improved the air quality of polluted areas especially in primarily at main cities [ 95 ]. As additional, Martins et al. [ 70 ] measure the Human Development Index (HDI) with the specific of socio-economic variables as income, education and health. In their study, the income and education levels are the main relevant factors that affect the socio-economic.

A mandatory lockdown is an area under movement control as a preventive measure to stop the coronavirus from spreading to other areas. Numerous governments worldwide enforced the policy to restrict public movements outside their homes during the pandemic. Resultantly, human-to-human transmission of the virus was effectively reduced. The lockdown and movement control order were also suggested for individuals aged 80 and above or with low or compromised immunities, as these groups possess a higher risk of contracting the disease [ 44 ].

Governments still enforced movement orders even after the introduction of vaccines by Pfizer, Moderna, and Sinovac, as the vaccines only protect high-risk individuals from the worst effects of COVID-19. Consequently, in most countries, after receiving the first vaccine dose, individuals were allowed to resume life as normal but were still required to follow the standard operating procedures (SOP) outlined by the government.

The government attempted to balance preventing COVID-19 spread and recovering economic activities, for example, local businesses, maritime traders, shipping activities, oil and gas production and economic trades [ 22 , 96 ]. Nonetheless, the COVID-19 cases demonstrated an increasing trend during the summer due to the higher number of people travelling and on vacation, primarily to alleviate stress from lockdowns. Several new variants were discovered, including the Delta and Omicron strains, which spread in countries such as the USA and the United Kingdom. The high number of COVID-19 cases prompted the WHO to suggest booster doses to ensure full protection.

As mentioned in this manuscript, the COVID-19 still uncertain for any kind factors that can be affected on spreading of this virus. However, regarding many sources of COVID-19 study, the further assessment on this factor need to be continue to be sure, that we ready to facing probably in 10 years projection of solar minimum phase can be held in same situation for another pandemic.

The sun has an eleven-year cycle known as the solar cycle, related to its magnetic field, which controls the activities on its surface through sunspots. When the magnetic fields are active, numerous sunspots are formed on its surface, hence the sun produces more radiation energy emitted to the earth. The condition is termed solar maximum (see Fig.  6 , denoted by the yellow boxes). Alternatively, as the magnetic field of the sun weakens, the number of sunspots decreases, resulting in less radiation energy being emitted to the earth. The phenomenon is known as the solar minimum (see Fig. 6 , represented by the blue boxes).

The emergence and recurrence of pandemics every 5 years in relation to solar activities ( Source: www.swpc.noaa.gov/ ). Note: The yellow boxes indicate the solar maximum, while the blue boxes represent the solar minimum

The magnetic field of the sun protects the earth from cosmic or galactic cosmic rays emitted by supernova explosions, stars, and gamma-ray bursts [ 97 ]. Nevertheless, galactic cosmic rays could still reach the earth during the solar minimum, the least solar radiation energy period. In the 20th and early 21st centuries, several outbreaks of viral diseases that affected the respiratory system (pneumonia or influenza), namely the Spanish (1918–1919), Asian (1957–1958) and Hong Kong (1968) flu, were documented. Interestingly, the diseases that claimed numerous lives worldwide occurred at the peak of the solar maximum.

Figure  6 illustrates the correlation between the number of sunspots and disease outbreaks from 1975 to 2021, including COVID-19, that began to escalate in December 2019. Under the solar minimum conditions, the spread of Ebola (1976), H5N1 (1997–1998), H1N1 (2009), and COVID-19 (2019-2020) were documented, while the solar maximum phenomenon recorded SARS (2002) and H7N9 (2012–2013) or MERS outbreaks. Nonetheless, solar activity through the production of solar sunspots began to decline since the 22nd solar cycle. Accordingly, further studies are necessary to investigate the influence such solar variations could impart or not on pandemic development.

Despite the findings mentioned above, the sun and cosmic radiations could influence the distribution or outspread of disease-spreading viruses. The rays could kill the viruses via DNA destruction or influence their genetic mutations, which encourage growth and viral evolution. Nevertheless, the connection between radiation and the evolutionary process requires further study by specialists in the field it is become true or not.

The spread of viral diseases transpires naturally in our surroundings and occurs unnoticed by humans. According to records, the spread of pandemic diseases, including the Black Death (fourteenth century) and the Spanish flu (1919), was significantly influenced by the decline and peak of solar activities. Furthermore, in the past 20 years, various diseases related to the influenza virus have been recorded. According to the pattern observed, if all diseases were related to the solar cycle (solar maximum and minimum), the viral diseases would reoccur every 5 to 6 years since they first appeared between 1995 and 2020. Accordingly, the next pandemic might occur around 2024 or 2025 and need to have a proper study for prove these statements. Nonetheless, the activities on the surface of the sun have been weakening since the 23rd solar cycle and it can be proven later after the proper study can be make it.

The beginning of the COVID-19 spread, only several countries with the same winter climate with an average temperature of 5–11 °C and an average humidity rate of 47–79% located at latitudes 30–50 N reported cases. The areas included Wuhan distribution centres in China, the United Kingdom, France, Spain, South Korea, Japan, and the USA (see Fig.  5 ). Other than biological aspects, the higher number of confirmed cases recorded in colder environments was due to the human body secreting less lymphoproliferative hormone, leading to decreased immunogenicity effects and increased risk of infection [ 24 ]. Consequently, the virus could attack and rapidly infect humans during the period [ 1 , 54 ].

The lymphoproliferative response is a protective immune response that plays a vital role in protecting and eradicating infections and diseases. On the other hand, staying in warm conditions or being exposed to more sunlight would lower the risks of infection. According to Asyary and Veruswati [ 98 ], sunlight triggers vitamin D, which increases immunity and increases the recovery rates of infected individuals.

Researchers believe that viruses could survive in the environment for up to 3 to 4 years or even longer. The survival rate of the microorganisms is relatively high, which is related to their biological structures, adaptability on any surfaces, and transmission medium to spread diseases. Viruses possess simple protein structures, namely the spike, membrane, and envelope protein; therefore, when they enter living organisms (such as through the respiratory system), the viruses are easily transmitted.

Once they have entered a host, the viruses duplicate exponentially and swarm the lungs. Subsequently, after the targeted organs, such as the lungs, are invaded, the viruses attack the immune system and create confusion in protective cells to destroy healthy cells. The situation is still considered safe in younger and healthy individuals as their immune systems could differentiate and counter-attack the viruses, curing them. Nonetheless, in elders and individuals with several chronic diseases, most of their protective cells are dead, hence their immune system is forced to work hard to overcome the infection. Pneumonia and death tend to occur when the situation is overwhelming [ 85 ]. Consequently, the viruses are harmful to humans as they could multiply in a short period, enter the blood, and overrun the body.

The coronavirus could attach to surfaces without a host, including door knobs and steel and plastic materials. The microorganisms could survive alone, but virologists have yet to determine how long. If someone touches any surface with the virus, the individual would then be infected. The situation would worsen if the infected person contacted numerous people and became a super spreader. A super spreader does not exhibit any symptoms and continuously transmits the virus without realising it. An infected individual transmits the coronavirus via droplets from coughs or sneezes. Nevertheless, scientists have yet to determine if coronavirus is spread via airborne or droplets, hence requiring thorough evaluation [ 99 ].

The COVID-19 virus mutates over time, and it can be changing any times. Mutations alter the behaviour and genetic structure of the virus, resulting in a new strain. Numerous research have been conducted to procure vaccines and anti-viral medications, but mutations have led to evolutionary disadvantages. The novel strains are more infectious than the original ones. As of November 2020, approximately six new coronavirus strains have been detected, each displaying different transmission behaviours [ 100 ].

Recent studies demonstrated that the mutated viruses exhibit little variability, allowing scientists to produce viable vaccines [ 71 ]. Furthermore, different types of vaccines are manufactured by different countries, which could be advantageous. Currently, most countries also recommend booster doses to attain extra protection after receiving the mandatory two vaccine doses. In same time, the social and physical interactions between humans also necessitate to be aware.

The COVID-19 virus is primarily transmitted through droplets produced by an infected person. Accordingly, physical distancing, a one-metre minimum distance between individuals [ 19 ], and following the SOP might prevent or avoid spreading the disease. Moreover, self-quarantine, school closures, working from home, cancelling large events, limiting gatherings, and avoiding spending long periods in crowded places are essential strategies in enforcing physical distancing at a community level. The policies are essential precautions that could reduce the further spreading of coronavirus and break the chain of transmission.

Government support also need to control the spread of COVID-19 with the strict SOP. The SOP enforcement in public places would enhance adherence to the new practice among the public and the community, aiding in curbing disease transmission. Practising limited meetings and social gatherings, avoiding crowded places, workplace distancing, preventing non-necessary travels of high-risk family members, especially those with chronic disease, and adhering to the recommended SOP could reduce coronavirus outbreaks. Nonetheless, individual awareness is also necessary to achieve COVID-19 spread prevention.

Many researchers are focused on identifying the primary drivers of pandemic outbreaks. Seasonal, temperature, and humidity differences significantly impacted COVID-19 growth rate variations. It is crucial to highlight the potential link between the recurrence of pandemics every 5 years and solar activities, which can influence temperature and humidity variations. Notable variations in COVID-19 mortality rates were observed between northern and southern hemisphere countries, with the former having higher rates. One hypothesis suggests that populations in the northern hemisphere may receive insufficient sunlight to maintain optimal vitamin D levels during winter, possibly leading to higher mortality rates.

The first COVID-19 case was detected in Wuhan, China, which is in the northern hemisphere. The number of cases rapidly propagated in December during the winter season. At the time, the temperature in Wuhan was recorded at 13–18 °C. Accordingly, one theory proposes that the survival and transmission of the coronavirus were due to meteorological conditions, namely temperatures between 13 and 18 °C and 50–80% humidity.

Daily rainfall directly impacts humidity levels. The coronavirus exhibited superior survival rates in cold and dry conditions. Furthermore, transmissible gastroenteritis (TGEV) suspensions and possibly other coronaviruses remain viable longer in their airborne states, which are more reliably collected in low relative humidity than in high humidity. Consequently, summer rains would effectively reduce COVID-19 transmission in southern hemisphere regions.

In southern hemisphere regions, the summer seasons are accompanied by a high average temperature at the end and beginning of the year. Countries with temperatures exceeding 24 °C reported fewer infections. As temperatures rise from winter to summer, virus transmission is expected to decline. Nonetheless, the activities and transmission of the virus were expected to decrease during winter to summer transitions, when the countries would be warmer. The peak intensity of infections strongly depends on the level of seasonal transmissions.

Social distancing plays a critical role in preventing the overload of healthcare systems. Many respiratory pathogens, including those causing mild common cold-like syndromes, show seasonal fluctuations, often peaking in winter. This trend can be attributed to increased indoor crowding, school reopening, and climatic changes during autumn.

The spread of COVID-19 to neighbouring regions can be attributed to population interactions. Migration patterns, such as the movement from northern to southern regions during the warmer months, have significant epidemiological impacts. This trend mirrors the behavior of influenza pandemics where minor outbreaks in spring or summer are often followed by major waves in autumn or winter.

Availability of data and materials

Not applicable.

Abbreviations

Novel coronavirus

Coronavirus disease 2019

Deoxyribonucleic acid

Swine influenza

Influenza A virus subtype H5N1

Asian Lineage Avian Influenza A(H7N9) Virus

Middle East respiratory syndrome

Middle East respiratory syndrome Coronavirus

Particulate matter

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

RepOrting standards for Systematic Evidence Syntheses

Severe Acute Respiratory Syndrome

Severe Acute Respiratory Syndrome Coronavirus

Syndrome coronavirus 2

Systematic literature review

Standard operating procedure

Transmissible gastroenteritis Virus

United States of America

World Health Organization

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Effective strategies for rebutting science denialism in public discussions

• Philipp Schmid   ORCID: orcid.org/0000-0003-2966-0806 1 , 2 &
• Cornelia Betsch   ORCID: orcid.org/0000-0002-2856-7303 1 , 2  

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Science deniers question scientific milestones and spread misinformation, contradicting decades of scientific endeavour. Advocates for science need effective rebuttal strategies and are concerned about backfire effects in public debates. We conducted six experiments to assess how to mitigate the influence of a denier on the audience. An internal meta-analysis across all the experiments revealed that not responding to science deniers has a negative effect on attitudes towards behaviours favoured by science (for example, vaccination) and intentions to perform these behaviours. Providing the facts about the topic or uncovering the rhetorical techniques typical for denialism had positive effects. We found no evidence that complex combinations of topic and technique rebuttals are more effective than single strategies, nor that rebutting science denialism in public discussions backfires, not even in vulnerable groups (for example, US conservatives). As science deniers use the same rhetoric across domains, uncovering their rhetorical techniques is an effective and economic addition to the advocates’ toolbox.

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Hostility has a trivial effect on persuasiveness of rebutting science denialism on social media

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The data supporting the findings of this study are available from the Open Science Framework ( https://doi.org/10.17605/OSF.IO/XX2KT ) 57 .

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Acknowledgements

The authors thank B. Wippert, T. Steinke, J. Gerlach and M. Schwarzer for their help collecting the data and developing the stimulus material and L. Korn for support visualizing Fig. 2 and Supplementary Fig. 2 . The authors are also grateful for the valuable input from K. Habersaat. Parts of the study were funded by grants to C.B. from the German Federal Ministry for Education and Research (BMBF) via the interdisciplinary and trans-sectoral consortium InfectControl2020 to the University of Erfurt (no. 03ZZ0819A) and the German Research Foundation to C.B. (no. BE3970/11-1). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. No other funding bodies were involved.

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Both authors substantially contributed to this article. P.S. and C.B. developed and designed the study, conducted the analyses and wrote the Article and Supplementary Information . P.S. visualized and curated the data. C.B. secured the funding.

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Schmid, P., Betsch, C. Effective strategies for rebutting science denialism in public discussions. Nat Hum Behav 3 , 931–939 (2019). https://doi.org/10.1038/s41562-019-0632-4

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Received : 20 August 2018

Accepted : 14 May 2019

Published : 24 June 2019

Issue Date : September 2019

DOI : https://doi.org/10.1038/s41562-019-0632-4

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