research papers in environmental policy

• Methodology
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• Published: 13 June 2019

Systematic reviews of qualitative evidence for environmental policy and management: an overview of different methodological options

• Biljana Macura   ORCID: orcid.org/0000-0002-4253-1390 1 ,
• Monika Suškevičs 2 ,
• Ruth Garside 3 ,
• Karin Hannes 4 ,
• Rebecca Rees 5 &
• Romina Rodela 6 , 7  

Environmental Evidence volume  8 , Article number:  24 ( 2019 ) Cite this article

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Qualitative research related to the human dimensions of conservation and environment is growing in quantity. Rigorous syntheses of such studies can help develop understanding and inform decision-making. They can combine findings from studies in varied or similar contexts to address questions relating to, for example, the lived experience of those affected by environmental phenomena or interventions, or to intervention implementation. Researchers in environmental management have adapted methodology for systematic reviews of quantitative research so as to address questions about the magnitude of intervention effects or the impacts of human activities or exposure. However, guidance for the synthesis of qualitative evidence in this field does not yet exist. The objective of this paper is to present a brief overview of different methods for the synthesis of qualitative research and to explore why and how reviewers might select between these. The paper discusses synthesis methods developed in other fields but applicable to environmental management and policy. These methods include thematic synthesis, framework synthesis, realist synthesis, critical interpretive synthesis and meta-ethnography. We briefly describe each of these approaches, give recommendations for the selection between them, and provide a selection of sources for further reading.

Qualitative research related to the human dimensions of conservation and environment is growing in quantity [ 1 , 2 ] and robust syntheses of such research are necessary. Systematic reviews, where researchers use explicit methods for identifying, appraising, analysing and synthesising the findings of studies relevant to a research question, have long been considered a valuable means for informing research, policy and practice across various sectors, from health to international development and conservation [ 3 , 4 , 5 , 6 , 7 ].

The methodological development of systematic reviews took off in the 1980s, initially with a strong focus on the synthesis of quantitative data. The exploration of specific methods for qualitative synthesis started to grow a decade or so later [ 8 , 9 ]. Examples addressed questions related to the lived experience of those affected by, and the contextual nuances of, given interventions. The methodology for the synthesis of quantitative research appears to have been adapted for environmental management for the first time in 2006 and has been developing since [ 10 , 11 ]. However, guidance in the field for those producing or interested in working with qualitative evidence synthesis still does not exist.

To date, the vast majority of systematic reviews in environmental management are syntheses of quantitative research evidence that evaluate the effectiveness of an intervention or the impact of an activity or exposure [ 12 ]—here called systematic reviews of quantitative evidence. These typically aggregate relatively homogenous outcome measures from similar interventions or exposures to create a more precise and accurate summary estimate of an overall effect [ 13 , 14 ].

Current debates about systematic reviews of quantitative evidence in other fields point out that such reviews, while they address essential questions about the magnitude of effects or impacts, cannot help us answer other policy- and practice-relevant issues [ 15 , 16 ]. In addition, the complexity within studies on impacts of environmental actions or exposures, and in studies of environmental management initiatives, will mean that a simple aggregation of study findings will only mask important differences and enable us to predict very little about what might happen to whom (human or otherwise) in any set of given circumstances. Here we argue that qualitative evidence syntheses can add value to environmental research and decision-making. Systematic reviews that make use of qualitative research can provide a rigorous evidence base for a deeper understanding of the context of environmental management. They can give useful input to policy and practice on (1) intervention feasibility and appropriateness (e.g., how a management strategy might best be implemented? What are people’s beliefs and attitudes towards a conservation intervention? ); (2) intervention adoption or acceptability (e.g., what is the extent of adoption of a conservation intervention?; What are facilitators and barriers to its acceptability? ); (3) subjective experience (e.g., what are the priorities and challenges for local communities? ); and (4) heterogeneity in outcomes (e.g., what values do people attach to different outcomes? For whom and why did an intervention not work? ) [ 8 , 15 , 17 , 18 ].

In common with individual studies of quantitative research, individual qualitative studies may be subject to limitations, in terms of their breadth of inquiry, conceptual reach and/or methodology or conduct. Projects that systematically find, describe, appraise and synthesise qualitative evidence can provide findings that are more broadly applicable to new contexts [ 19 ] or explanations that are more complete [ 20 ]. Such qualitative evidence syntheses (QES) may stand alone, be directly related to a systematic review of quantitative evidence on a related question(s) or may be part of mixed methods multi-component reviews that aim to bring two distinct syntheses of evidence together.

In spite of its value, there is a limited discussion on the synthesis of qualitative research evidence in the environmental field and tailored methodological guidance could usefully address how to:

conduct syntheses of evidence so as to go beyond questions of effectiveness or impact;

use synthesis to identify explanations for and produce higher levels of interpretation of the phenomena under study;

include rich descriptive and often heterogeneous evidence from different research domains; and

combine and link qualitative and quantitative evidence.

The objective of this paper is to present a brief overview of different methodological options for the synthesis of qualitative research developed in other fields (such as health, education and social sciences) and applicable to environmental management practice and policy. A selection of sources for further reading, including those that expand on how to identify, describe and appraise evidence for QES is also included. Before describing the different synthesis options, we briefly explore the nature of environmental problems and management to explain the context for QES in this field.

The context of environmental policy, management, and research

Environmental and conservation problems are wicked, highly complex, and embedded in ecological as well as social systems [ 21 , 22 , 23 , 24 ]. The complexity stems from several sources: (1) a high level of uncertainty; (2) large temporal and spatial scale; (3) cross-sectoral and multi-level spanning; and (4) the irreversibility of potential damages [ 25 , 26 ]. The loss of global biodiversity or changes in the global climate system [ 27 , 28 ] can illustrate this complexity: our knowledge about these systems is imperfect, a multiplicity of actors is associated with them (see, e.g., [ 22 , 25 ]); their impacts span from local to global levels and the damages potentially cannot be repaired [ 29 , 30 , 31 ]. On top of this, interventions to address these challenges are themselves often complex, in that they are made up of many interacting components and are introduced into and rely upon social systems for their implementation [ 32 ].

Instead, the dynamic nature and complexity of environmental problems, and their possible solutions call for the use and integration of scientific knowledge from several and different disciplinary domains. This need is reflected already in the interdisciplinary nature of environmental research that occurs at the level of theory, methods and/or data [ 33 , 34 , 35 , 36 ]. Environmental research is frequently based on observational studies [ 37 ]. Studies are commonly developed around a well-defined theoretical and a geographical boundary, with the aim to develop a comprehensive understanding of the chosen phenomena. However, this means that such research produces highly heterogeneous evidence scattered across different contexts [ 38 ].

These issues related to the type and nature of environmental evidence imply that systematic review methods need to include a plurality of different approaches [ 39 ]. Adding qualitative and mixed methods evidence synthesis to the systematic review toolbox may be vital in cases where context is very important, complexity and heterogeneity is the norm, and where a more in-depth understanding of the views and experiences of various actors can help to explain how, why and for whom an intervention does or does not work [ 18 ]. These methods can further aid in the understanding of success and failure of environmental interventions through the analysis of implementation factors. Furthermore, they can also help in describing the range and nature of impacts, and in understanding unintended or unanticipated impacts [ 40 ].

What is qualitative evidence synthesis (QES)?

Qualitative evidence synthesis refers to a set of methodological approaches for systematically identifying, screening, quality appraisal and synthesis of primary qualitative research evidence. Various labelling terms have been used (see Box 1 ).

It should be noted here that QES is distinct from two other categories of reviews that have been labelled as ‘qualitative’. The first category contains narrative summaries of findings from studies with quantitative data. Here, the original intention was to use quantitative synthesis methods (e.g., meta-analysis) but that was not possible due to, for example, the heterogeneity between studies. Review authors in the second category have the intention to use a narrative approach to synthesis of quantitative data right from the start. Neither of these two review categories is discussed further here.

Box 1 Definitions and labels

Qualitative research refers to a wide range of different kinds of research studies that tend to collect and analyse qualitative data, to organise and interpret the results and produce findings that are largely narrative in form (see also [ 41 ]).

Qualitative data typically refers to textual data (although other types of data, such as visual data, can be produced during the research process). Data are obtained through recording of, for example, e.g., individual or group interviews, or observations of behaviours.

Qualitative evidence synthesis (QES) is an umbrella term that encompasses a set of various methodological approaches for systematically identifying, screening, quality appraising and synthesising primary qualitative research evidence.

Other generic terms used for qualitative evidence synthesis:

Systematic review of qualitative research

Qualitative systematic reviews

Meta-synthesis

Qualitative research synthesis

An overview of QES approaches

In common with methods for systematic reviews of quantitative evidence, there are a number of stages of the systematic review process which are followed in most QES approaches, including (1) question formulation, (2) searching for literature, (3) eligibility screening, (4) quality appraisal, (5) synthesis and (6) reporting of findings. However, the methods used within each of these stages varies, depending on the specific review approach adopted with its epistemology and relation to theory.

QES approaches lie on an epistemological continuum between idealist and realist positions and can be positioned anywhere between the two extremes ([ 16 , 42 , 43 ], see Fig.  1 ). Idealist approaches to synthesis operate under the assumption that there is no single ‘correct’ answer, but the focus is in understanding variation in different conceptualisations [ 43 ]. They are less bound by pre-defined procedures and have open review questions allowing for constantly emerging concepts and theories [ 44 ]. In these iterative approaches, any stage of the review process may be revisited as the ideas develop through interaction with the evidence base. The iterations are recorded, described and justified in the write-up. These approaches may aim to create a model or theory that increases our understanding of what might hinder or facilitate the uptake of a policy or a program, or how a phenomenon operates and is experienced. Approaches on the realist side of the continuum assume that there is a single independent and knowable reality, and review findings are understood as an objective interpretation of this reality [ 43 , 45 ]. The review questions are closed and fixed, and the reviews follow strict formal linear methodological procedures. These approaches usually aim to test existing theories ([ 43 ], see Fig.  1 ).

(Source: Gough et al. [ 43 ])

Dimensions of difference in review approaches

QES approaches may also vary in the way they address and understand the importance of the context and so, they can be multi-context or context-specific. Multi-context reviews aim at an exhaustive sampling of literature to include diverse contexts, e.g., different geographical, socio‐cultural, political, historical, economic, ecological settings. Such reviews are currently common in systematic reviews of quantitative evidence. Context-specific QES use selective sampling and focuses on only one context to provide specific understanding to a targeted audience and develop theories that are specific to the local setting (see [ 46 ]).

In the following sub-sections, we give an overview of five commonly used qualitative synthesis methods: thematic synthesis, framework synthesis, realist synthesis, critical interpretative synthesis and meta-ethnography [ 47 , 48 ]. Table  1 shows the main purpose of the method, a type of the review question and a type of evidence commonly used in the synthesis stage (qualitative or mixed) and key readings. Anyone wanting to undertake a review should keep in mind that each method might imply a specific approach to review stages (from literature search to critical appraisal) and the key readings listed in Table  1 should be checked for specific advice.

• Framework synthesis

Framework synthesis uses a deductive approach and it has been used for the syntheses of qualitative data alone (e.g., [ 49 ]), as well as by those undertaking mixed methods syntheses [ 50 , 51 ]. Framework synthesis has been grouped along with other approaches that are less suitable for developing explanatory theory through interpretation or making use of rich reports in study findings. The approach can be seen as one means of exploring existing theories [ 42 ]. Framework synthesis begins with an explicit conceptual framework. Reviewers start their synthesis by using the theoretical and empirical background literature to shape their understanding of the issue under study. The initial framework that results might take the form of a table of themes and sub-themes and/or a diagram showing relationships between themes. Coding is initially based on this framework. This framework is then developed further during the synthesis as new data from study findings are incorporated and themes are modified, or further themes are derived. The findings of a framework synthesis usually consist of a final, revised framework, illustrated by a narrative description that refers to the included studies. The initial conceptual framework in framework synthesis is seen as providing a “scaffold against which findings from the different components of an assessment may be brought together and organise” ([ 52 ]:29). The approach builds upon framework analysis, which is a method of analysing primary research data that has often been applied to address policy concerns [ 53 ].

Six stages of framework synthesis are generally identified: familiarisation, framework selection, indexing, charting, mapping and interpretation. In the familiarisation stage reviewers aim to become acquainted with current issues and ideas about the topic under study. The involvement of subject experts in the team can be particularly helpful at this stage. The next stage, framework selection, sees reviewers finalising their initial conceptual framework. Here some argue for the value of quickly selecting a ‘good enough’ existing framework [ 52 ], rather than developing one from a variety of sources. An indexing stage then sees reviewers characterising each included study according to the a priori framework. In the charting stage reviewers analyse the main characteristics of each research paper, by grouping characteristics into categories related to the framework and deriving themes directly from those data. During the mapping stage of a framework synthesis, derived themes are considered in the light of the original research questions and the reviewer draws up a presentation of the review’s findings. The interpretation stage, as with much research, is the point at which the findings are considered in relation to the wider research literature and the context in which the review was originally undertaken.

Framework synthesis is relatively structured and therefore able to accommodate quite large amounts of data. Like thematic synthesis (see below), researchers using this method often seek to provide review output that is directly applicable to policy and practice. This method can be suitable for understanding feasibility and acceptance of conservation interventions. A variation of the method, the ‘best-fit synthesis’ approach, might help if funder timescales are extremely tight [ 54 ]. A review by Belluco and colleagues [ 55 ] of the potential benefits and challenges from nanotechnology in the meat food chain is a recent example of framework synthesis. Here reviewers coded studies to describe the area of the meat supply chain, using a pre-specified framework. Belluco’s team interrogated their set of 79 studies to derive common themes as well as gaps—areas of the framework where studies appeared not to have been conducted.

• Thematic synthesis

Thematic synthesis draws on methods of thematic analysis for primary qualitative research and is a common approach to qualitative evidence synthesis in health and other disciplines [ 56 ]. Examples in the literature range from more descriptive to more interpretative approaches. Findings from the included studies are either extracted and then coded or, increasingly, full-texts of the eligible studies are uploaded into appropriate software (e.g., NVIVO or EPPI-reviewer) and coded there. These codes are used to identify patterns and themes in the data. Often these codes are descriptive but can then be built up into more conceptual or theory-driven codes. Initial line-by-line descriptive coding groups together ideas from pieces of text within and across the included papers. Similarities and differences are then grouped together into hierarchical codes. These are then revisited, and new codes developed to capture the meaning of groups of the initial codes. A narrative summary of the findings, describing these themes is then written. Finally, these findings can be interpreted to explore the implications of these findings for the context of a specific policy or practice question that has framed the review. The method is therefore suitable for addressing questions related to effectiveness, need, appropriateness and acceptability of an intervention [ 16 ] and usually from the point of view of the targeted groups (e.g., local communities, conservation managers, etc.). Similar to systematic reviews of quantitative research, this method attempts to retain the explicit and transparent link between review conclusions and the included primary studies [ 56 ]. There are only a few examples of reviews in the environmental management field that have explicitly applied thematic synthesis. For instance, Schirmer and colleagues [ 57 ] use “thematic coding” [ 56 ] (within the approach they call qualitative meta-synthesis) to analyse the role of Australia’s natural resource management programs in farmers’ wellbeing. Haddaway and colleagues [ 58 ] use thematic synthesis to define the term “ecotechnology”.

• Meta-ethnography

This method was developed by Noblit and Hare [ 59 ] and originally applied to the field of education. The method was further improved in the early 2000s by Britten and colleagues [ 60 ] who applied it to health services research and has since been used for increasing numbers of evidence synthesis, particularly in health research and other topic areas.

Meta-ethnography is an explicitly interpretative approach to synthesis and aims to create new understandings and theories from a body of work. It uses authors’ interpretations (sometimes called second-order constructs, where the quotes from study participants are first-order constructs) and looks for similarities and differences at this conceptual level. It uses the idea of “translation” between constructs in the included studies. This involves juxtaposing ideas from studies and examining them in relation to each other, in order to identify where they are describing similar or different ideas.

This method includes seven stages: (1) identification of the intellectual interest that the review might inform; (2) deciding what is relevant to the initial interest; (3) reading the studies and noting the concepts and themes; (4) determining how the studies are related; (5) translating studies into one another; (6) synthesising translations; and (7) communicating review findings [ 59 ]. There are three main types of synthesis (stages 5 and 6): reciprocal translation, refutational translation, and line of argument. Different findings within a single meta-ethnography may contain examples of one or all of these approaches depending on the nature of the findings within the included studies. Reciprocal translation is used where concepts from different studies are judged to be about similar ideas, and so can be “translated into each other”. Refutational translation refers to discordant findings, where differences cannot be explained by differences in participants or within a theoretical construct. A line of argument can be constructed to identify how translated concepts are related to each other and can be joined together to create a more descriptive understanding of the findings as a whole. This method is therefore very well suited to produce new interpretations, theories or conceptual models [ 61 , 62 ]. In the conservation, this method could be used to understand how, for example, local communities experience conservation interventions and how this influences their acceptance of conservation interventions. Head and colleagues [ 63 ] used meta-ethnography to understand dimensions of household-level everyday life that have implications for climate change mitigation and adaptation strategies.

Critical interpretive synthesis

The critical interpretive synthesis approach was originally developed by Dixon-Woods and colleagues [ 64 ]. Review authors using this approach [ 64 ] are interested in theory generation while being able to integrate findings from a range of study types, and empirical and theoretical papers. Further, this method can integrate a variety of different types of evidence from quantitative, qualitative and mixed methods studies. We included critical interpretative synthesis in our paper because this method is often used for synthesis of qualitative evidence.

In the overall synthesis a coherent framework is usually presented, showcasing a complex network of interrelating theoretical constructs and the relationships between them. The framework partly builds on existing constructs as reported in the different studies and introduces newly derived, synthetic constructs generated through the synthesis procedure itself. Reported themes are then gradually mapped against each other to create an overall understanding of the phenomenon of interest. This is similar to developing a line of argument in a meta-ethnography (see above). Critical interpretive synthesis distinguishes itself from other approaches such as formal grounded theory [ 65 , 66 ] and meta-ethnography by adopting a critical stance towards findings reported in the primary studies, the assumptions involved, and the recommendations proposed. Rather than taking the findings for granted, review authors involved in critical interpretive synthesis “critically question the entire construction of the story the primary-level authors told in their research reports” [ 17 ]. They would potentially critique recommendations based on, e.g., ethical or moral arguments, such as the desirability of a particular rollout of an intervention. This method is therefore very well suited for understanding of what may have influenced proposed solutions to a problem [ 64 ] and to examine the constructions of concepts [ 67 ]. In the environmental field, this method could, for example, be applied to understand how different narratives influence environmental practice and policy or to critically assess new forms of conservation governance and management. Explicit examples of critical interpretive synthesis review projects applied to the broad area of environmental sciences are currently non-existent to our knowledge. However, there are a few related examples from health studies, such as review on environmentally responsible nursing [ 68 ]. In that review, authors justify the use of critical interpretative synthesis mainly by the ability of this method to synthesise diverse types of primary studies in terms of their topic and methodology.

• Realist synthesis

Realist synthesis is a theory-driven approach to combining evidence from various study types. Originally developed in 2005 by Ray Pawson and colleagues [ 69 ], it is aimed at unpacking the mechanisms for how particular interventions work, for whom and in which particular context and setting. It is included here because it is increasingly used for synthesising qualitative data, although data can be both qualitative and quantitative.

Realist synthesis has been developed to evaluate the integrity of theories (does a program work as predicted) and theory adjudication (which intervention fits best). In addition, it allows for a comparison of interventions across settings or target groups or explains how the policy intent of a particular intervention translates into practice [ 69 ].

The realist synthesis approach is highly iterative, so it is difficult to identify a distinct synthesis stage as such. The synthesis process usually starts by identifying theories that underpin specific interventions of interest. The theoretical assumptions about how an intervention is supposed to work and what impact it is supposed to generate are made explicit from the start. Depending on the exact purpose of the review, various types of evidence related to the interventions under evaluation (potentially both quantitative and qualitative) are then consulted and appraised for quality. In evaluating what works for whom in which circumstances, contradictory evidence is used to generate insights about the influence of context and so to link various configurations of context, mechanism and outcome. Conclusions are usually presented as a series of contextualised decision points. An example of a realist synthesis in the environmental context is the one from McLain, Lawry and Ojanen [ 70 ] in which the evidence of 31 articles examine the environmental outcomes of marine protected areas governed under different types of property regimes. The use of a realist synthesis approach allowed the review authors to gain a deeper understanding of the ways in which mechanisms such as perceptions of legitimacy, perceptions of the likelihood of benefits, and perceptions of enforcement capacity interact under different socio-ecological contexts to trigger behavioural changes that affect environmental conditions. Another example from the environmental domain is the review by Nilsson and colleagues [ 71 ] who applied a realist synthesis to 17 community-based conservation programs in developing countries that measured behavioural changes linked to conservation outcomes. The RAMESES I project ( http://www.ramesesproject.org ) offers methodological guidance, publication standards and training resources for realist synthesis.

Choosing the appropriate QES method

Here we explain the criteria for the selection of different QES methods presented in this paper.

There are several aspects to be considered when choosing the right evidence synthesis approach [ 42 , 67 , 72 ]. These include the type of a review question, epistemology, purpose of the review, type of data, and available expertise including the background of the research team and resource requirements. Here, we briefly discuss the more pragmatic aspects to be considered. For a detailed discussion of other criteria we refer the reader to the work of Hannes and Lockwood [ 67 ], and Booth and colleagues [ 42 , 72 ].

Particularities of the evidence

As noted above, environmental problems are complex and involve a high degree of uncertainty. Environmental research is often inter- and transdisciplinary and involves, for example, the use of contested and/or diverse concepts and terms, as well as heterogeneous datasets. Thus, it is very important to understand if the QES method is fit-for-purpose and if it will result in the expected and desired synthesis outcomes. More complex and contextual outcomes are expected from the idealist methods (such as critical interpretative synthesis or meta-ethnography) (Fig.  1 and Table  1 ), which offer insights to policy or practice only after further interpretation. In contrast, more concrete and definitive outcomes can be expected from more realist methods (such as thematic synthesis) [ 67 ]. The type of evidence to be synthesised (e.g., qualitative or mixed, see Table  1 ) is yet another aspect needing consideration when choosing the synthesis method.

Background of the researchers and the review team

Researchers should consider their methodological backgrounds and epistemological viewpoints, to make sure they have appropriate expertise as well as experience in the review team when choosing the method. Some more complex methods (such as realist synthesis) may require specific skills (e.g., a familiarity with the realist perspective), and larger teams of researchers with different disciplinary backgrounds. Such methods may also require that the researchers are more familiar with the content of the research they review. Other methods (such as thematic or framework synthesis) can be done in a smaller team of researchers who do not necessarily have deeper subject expertise.

Resource requirements

Requirements for review funding will obviously depend on the resource requirements, i.e. a number of researchers to be involved, the time needed to conduct a review, costs associated with access to a specific data analysis or review management software, and access to literature. Some methods may be more resource demanding. Multi-component mixed method reviews, for example, requires expertise in both qualitative and quantitative synthesis methods, as well as the allocation of time for producing more than one parallel and/or consecutive syntheses. Other methods, such as framework synthesis, are maybe less resource-consuming (needing comparatively fewer people over less time) as long as initial frameworks have already been developed and are uncontentious. The issue of time spent on a review also depends on the breadth of the research question and the extent of the literature.

Challenges and points of contestation

Whilst QES can be valuable for environmental practice and policy, readers should be aware of several well-known challenges that might also appear problematic when QES approaches are used for the synthesis of environmental qualitative research. Here we summarise some of the most important ones including conceptual and methodological heterogeneity in primary research studies, issues with quality appraisal and transparency in reporting.

Qualitative evidence is likely to be situated in different disciplines, theoretical assumptions, and general philosophical orientations [ 73 ]. For aggregative less interpretative methods (such as framework synthesis), this poses a challenge in terms of comparability during the synthesis stage of the review process. In case of more interpretive approaches (e.g., meta-ethnography), such diversity is often seen as an asset rather than a problem as the translation of one study to another [ 74 ] allows for a comparison of studies with different theoretical backgrounds.

As with systematic reviews of quantitative evidence, critical appraisal of study validity is perhaps one of the most contested stages of the QES review process [ 75 ]. Quality appraisal (and the extent to which it matters) likely depends on the methodological approach. For example, framework and thematic syntheses assess the reliability and methodological rigour of individual study findings and may exclude methodologically flawed studies from the synthesis. Meta-ethnography or critical interpretative synthesis assess included studies in terms of content and utility of their findings, level to which they inform theory and include all studies in the synthesis [ 16 ].

Finally, reviews can be often criticised for lack of transparency and unclear or incomplete reporting. However, to ensure that all the important decisions related to the review conduct are reported at the sufficient level of detail, there are reporting standards applicable for QES such as ENTREQ [ 76 ] and ROSES [ 77 ]. Additionally, RAMESES are reporting standards developed specifically for realist syntheses [ 78 ] and the EMERGE project developed reporting standards for meta-ethnographies ([ 79 ], http://emergeproject.org ). These standards aim to increase transparency and hopefully drive up the quality of the review conduct [ 80 ].

Additional methodological options: Linking quantitative and qualitative evidence together

In the following paragraphs, we briefly present an additional methodological option that could be, for example, useful for the synthesis of complex conservation interventions and is suited to address some of the above challenges (such as methodological heterogeneity).

Namely, in some cases, synthesis of only one type of study findings (either qualitative or quantitative) might not be sufficient to understand multi-layered or complex interventions or programs typical for the environmental sector. The mixed methods review approach has been developed to link qualitative, mixed and quantitative study findings in a way to enhance the breadth and depth of understanding phenomena, problems and/or study topics [ 81 , 82 ]. Mixed methods reviews is a systematic review in which quantitative, qualitative and primary studies are synthesized using both quantitative and qualitative methods [ 81 ]. The data included in such a review are the findings or results extracted from either quantitative, qualitative or mixed methods primary studies. These findings are then integrated using a mixed method analytical approach [ 17 ].

This approach allows us to study how different (intervention) components are related and how they interact with each other [ 83 ]. Apart from studying the effectiveness of interventions, these reviews include qualitative evidence on the contextual influence, applicability and barriers to implementation for these interventions. For example, topics covered by reviews that link qualitative and quantitative data are the impact of urban design, land use and transport policies and practices to increase physical activity [ 84 ]; the socio-economic effects of agricultural certification schemes [ 85 ]; the impact of outdoor spaces on wellbeing for people with dementia [ 86 ]. Qualitative and quantitative bodies of evidence can point to different facets of the same phenomena and enrich understanding of it. In a review on protected area impacts on human wellbeing [ 87 ], it is revealed that qualitative findings were not studied quantitatively and only once combined in a synthesis these two evidence bases could provide a complete picture of the protected area impact.

Conclusions

Synthesis of qualitative research is crucial for addressing wicked environmental problems and for producing reliable support for decisions in both policy and practice. We have provided an overview of methodological approaches for the synthesis of qualitative research, each characterised by different ways of problematising the literature and level of interpretation. We have also explained what needs to be considered when choosing among these methods.

Environmental and conservation social science has witnessed an accumulation of primary research during the past decades. However, social scientists argue that there is a little integration of qualitative evidence into conservation policy and practice [ 33 ], and this suggests that there is a ‘synthesis gap’ (sensu [ 88 ]). This paper, with an overview of different methodological tools, provides the first guidance for environmental researchers to conduct synthesis of qualitative evidence so that they can start bridging the synthesis gap between environmental social science, policy and practice. Furthermore, introduced examples may inspire reviewers to adapt existing methods to their specific subject and, where necessary, help develop new methods that are a better fit for the field of environmental evidence. This is especially important as currently used methods in synthesis of environmental evidence fall short on utilising the potential of qualitative research that translates into lack of a deeper contextual understanding around implementation and effectiveness of environmental management interventions, and disregard the diversity of perspectives and voices (e.g., indigenous peoples, farmers, park managers) fundamental for tackling wicked environmental issues.

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Acknowledgements

We thank the BONUS Secretariat for covering article processing fees. BM thanks to Mistra Council for Evidence-based Environmental Management (EviEM) and BONUS RETURN for allocated time to draft this manuscript. RG is partially supported by the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care South West Peninsula.

Article processing fees were covered by BONUS RETURN. BONUS RETURN project is supported by BONUS (Art 185), funded jointly by the EU and Swedish Foundation for Strategic Environmental Research FORMAS, Sweden’s innovation agency VINNOVA, Academy of Finland and National Centre for Research and Development in Poland.

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Biljana Macura

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Monika Suškevičs

European Centre for Environment and Human Health, University of Exeter Medical School, Truro, UK

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BM and MS developed the framework for and edited the end version of this paper. All authors (BM, MS, RG, KH, R. Rees and R. Rodela) wrote substantial pieces of the manuscript. RG, KH, R. Rees and R. Rodela commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Macura, B., Suškevičs, M., Garside, R. et al. Systematic reviews of qualitative evidence for environmental policy and management: an overview of different methodological options. Environ Evid 8 , 24 (2019). https://doi.org/10.1186/s13750-019-0168-0

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In this paper, Johansson et al. examine sea spray aerosol as a potential transport vehicle for perfluoroalkyl carboxylic and sulfonic acids. The surfactant properties of these compounds are well known and, in fact, key to many of the technical applications for which they are used. The fact that these compounds are enriched at the air–water interface makes enrichment in sea spray aerosols seem reasonable. Johansson et al. systematically tested various perfluoroalkyl acids enrichment in aerosols under conditions relevant to sea spray formation, finding that longer chain lengths lead to higher aerosol enrichment factors. They augmented their experimental work with a global model, which further bolstered the conclusion that global transport of perfluoroalkyl acids by sea spray aerosol is and will continue to be an important process in determining the global distribution of these compounds.

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First Runner-up Best Paper: Yamakawa, Takami, Takeda, Kato, Kajii, Emerging investigator series: investigation of mercury emission sources using Hg isotopic compositions of atmospheric mercury at the Cape Hedo Atmosphere and Aerosol Monitoring Station (CHAAMS), Japan , Environ. Sci.: Processes Impacts , 2019, 21 , 809–818, DOI: 10.1039/C8EM00590G .

Second Runner-up Best Paper: Avery, Waring, DeCarlo, Seasonal variation in aerosol composition and concentration upon transport from the outdoor to indoor environment , Environ. Sci.: Processes Impacts , 2019, 21 , 528–547, DOI: 10.1039/C8EM00471D .

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Second Runner-up Best Paper: Genter, Marks, Clair-Caliot, Mugume, Johnston, Bain, Julian, Evaluation of the novel substrate RUG™ for the detection of Escherichia coli in water from temperate (Zurich, Switzerland) and tropical (Bushenyi, Uganda) field sites , Environ. Sci.: Water Res. Technol. , 2019, 5 , 1082–1091, DOI: 10.1039/C9EW00138G .

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First Runner-up Best Paper: Janković, Plata, Engineered nanomaterials in the context of global element cycles , Environ. Sci.: Nano , 2019, 6 , 2697–2711, DOI: 10.1039/C9EN00322C .

Second Runner-up Best Paper: González-Pleiter, Tamayo-Belda, Pulido-Reyes, Amariei, Leganés, Rosal, Fernández-Piñas, Secondary nanoplastics released from a biodegradable microplastic severely impact freshwater environments , Environ. Sci.: Nano , 2019, 6 , 1382–1392, DOI: 10.1039/C8EN01427B .

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• J. Miao, H.-J. Jiang, Z.-W. Yang, D.-y. Shi, D. Yang, Z.-Q. Shen, J. Yin, Z.-G. Qiu, H.-R. Wang, J.-W. Li and M. Jin, Assessment of an electropositive granule media filter for concentrating viruses from large volumes of coastal water, Environ. Sci.: Water Res. Technol. , 2019, 5 , 325–333,   10.1039/C8EW00699G .
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• The role of the Environmental Protection Agency in enforcing environmental laws.
• The influence of the Kyoto Protocol on global greenhouse gas emissions.
• The effectiveness of the Paris Agreement in mitigating climate change.
• The role of policy in promoting renewable energy adoption.
• The impact of environmental policy on industrial pollution.
• The role of policy in managing water resources.
• The effectiveness of policy in controlling deforestation.
• The impact of environmental policy on sustainable agriculture.

 International Environmental Policy

• The role of the United Nations in shaping global environmental policy.
• The impact of international treaties on national environmental policies.
• The role of international law in protecting the global commons.
• The effectiveness of international cooperation in addressing climate change.
• The role of trade agreements in promoting environmental sustainability.
• The impact of international policy on biodiversity conservation.
• The role of the World Bank in promoting sustainable development.
• The influence of international policy on national renewable energy adoption.
• The effectiveness of international policy in controlling marine pollution.
• The impact of international policy on global deforestation.

Environmental Policy and Economics

• The role of environmental policy in shaping economic development.
• The impact of environmental regulations on business operations.
• The influence of economic incentives on environmental protection.
• The effectiveness of market-based environmental policies.
• The role of environmental policy in promoting green jobs.
• The impact of environmental taxes on pollution levels.
• The role of economic analysis in environmental policy-making.
• The influence of environmental policy on consumer behavior.
• The effectiveness of economic instruments in promoting renewable energy.
• The impact of environmental policy on economic inequality.

Environmental Policy and Politics

• The role of political institutions in shaping environmental policy.
• The impact of political ideology on environmental policy-making.
• The influence of public opinion on environmental policy.
• The effectiveness of political activism in promoting environmental protection.
• The role of political parties in shaping environmental policy.
• The impact of lobbying on environmental policy-making.
• The role of political leadership in promoting environmental sustainability.
• The influence of electoral politics on environmental policy.
• The effectiveness of political campaigns in promoting environmental awareness.
• The impact of political conflict on environmental policy implementation.

Environmental Policy and Law

• The role of legal institutions in shaping environmental policy.
• The impact of environmental laws on pollution levels.
• The influence of legal precedents on environmental policy-making.
• The effectiveness of environmental litigation in promoting environmental protection.
• The role of legal sanctions in enforcing environmental laws.
• The impact of legal rights on environmental policy-making.
• The role of the judiciary in interpreting environmental laws.
• The influence of constitutional law on environmental policy.
• The effectiveness of legal instruments in promoting environmental justice.
• The impact of legal reforms on environmental policy implementation.

Environmental Policy and Society

• The role of social movements in shaping environmental policy.
• The impact of societal values on environmental policy-making.
• The influence of social norms on environmental behavior.
• The effectiveness of social marketing in promoting environmental protection.
• The role of societal institutions in enforcing environmental norms.
• The impact of social inequality on environmental policy outcomes.
• The role of social science research in informing environmental policy.
• The influence of societal change on environmental policy evolution.
• The effectiveness of social policies in promoting environmental justice.
• The impact of social media on environmental policy debates.

Environmental Policy and Technology

• The role of technological innovation in shaping environmental policy.
• The impact of environmental policy on technological development.
• The influence of technology diffusion on environmental outcomes.
• The effectiveness of technology policy in promoting environmental sustainability.
• The role of technology assessment in environmental policy-making.
• The impact of information technology on environmental awareness.
• The role of technology transfer in international environmental policy.
• The influence of emerging technologies on environmental policy challenges.
• The effectiveness of technology standards in reducing environmental impacts.
• The impact of technology-driven changes on environmental policy needs.

Environmental Policy and Education

• The role of environmental education in shaping environmental policy.
• The impact of environmental policy on education systems.
• The influence of educational attainment on environmental attitudes.
• The effectiveness of education policy in promoting environmental literacy.
• The role of schools in fostering environmental citizenship.
• The impact of environmental curriculum on student outcomes.
• The role of higher education in advancing environmental research.
• The influence of educational resources on environmental awareness.
• The effectiveness of environmental education programs in changing behavior.
• The impact of education reform on environmental learning opportunities.

Environmental Policy and Health

• The role of health considerations in shaping environmental policy.
• The impact of environmental policy on public health outcomes.
• The influence of health research on environmental risk assessment.
• The effectiveness of health policy in addressing environmental health risks.
• The role of health impact assessments in environmental policy-making.
• The impact of environmental exposures on health disparities.
• The role of health agencies in enforcing environmental regulations.
• The influence of health advocacy on environmental policy debates.
• The effectiveness of health-based standards in controlling environmental hazards.
• The impact of health care practices on environmental sustainability.

Environmental Policy and the Future

• The role of future scenarios in shaping environmental policy.
• The impact of environmental policy on future generations.
• The influence of future-oriented thinking on environmental decision-making.
• The effectiveness of policy measures in addressing future environmental risks.
• The role of foresight methods in environmental policy planning.
• The impact of future technological changes on environmental policy needs.
• The role of future studies in informing environmental policy debates.
• The influence of future uncertainties on environmental policy strategies.
• The effectiveness of future-proofing measures in environmental policy design.
• The impact of future climate changes on environmental policy responses.

In conclusion, the field of environmental policy offers a wealth of research topics that can cater to various interests and academic requirements. Whether you’re interested in policy analysis, international environmental policy, environmental economics, or any other aspect of environmental policy, there’s a topic for you. Remember, the key to a successful research paper is choosing a topic that not only interests you but also aligns with your academic and career goals.

Environmental Policy Research Guide

In today’s world, environmental issues have become a pressing concern, requiring urgent attention and action. As our planet faces complex challenges such as climate change, pollution, deforestation, and resource depletion, it has become crucial to understand the role of environmental policy in addressing these issues. Environmental policy plays a pivotal role in shaping regulations, laws, and initiatives aimed at preserving and protecting our natural environment.

This page serves as a valuable resource for students studying environmental science and engaging in research paper writing. Here, we delve into the realm of environmental policy research and provide a comprehensive guide to help students explore this fascinating field. By delving into the various aspects of environmental policy research, students can gain a deeper understanding of the intricate relationship between policy decisions and environmental outcomes.

The primary objective of this page is to equip students with the necessary knowledge and tools to embark on their own environmental policy research journey. By delving into diverse environmental policy research paper topics and providing expert advice on topic selection, we aim to inspire students to explore the multifaceted world of environmental policy and contribute meaningfully to the field.

As students, you have the power to influence the future of environmental policy through your research and insights. By examining the intersection of environmental science and policy, you can contribute to the development of effective strategies and solutions that promote sustainability, conservation, and equitable environmental outcomes.

Throughout this page, we will explore a comprehensive list of environmental policy research paper topics, spanning various categories and addressing critical issues in environmental governance. Additionally, we will provide expert advice on how to choose suitable research topics within the realm of environmental policy. Furthermore, we will guide you through the process of writing an impactful environmental policy research paper, offering essential tips to enhance your writing and research skills.

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Choosing an Environmental Policy Topic

Choosing the right research topic is a critical step in the process of writing an impactful environmental policy research paper. With a plethora of issues and areas to explore within the realm of environmental policy, it can be challenging to narrow down your focus and select a topic that is both relevant and engaging. To assist you in this endeavor, we have compiled expert advice and 10 essential tips to guide you in choosing environmental policy research paper topics that are meaningful, well-defined, and aligned with your interests and academic goals.

• Identify your passion and interests : Start by reflecting on your personal interests within the field of environmental policy. What aspects of environmental governance intrigue you the most? By choosing a topic that resonates with your passion, you will be more motivated and engaged throughout the research and writing process.
• Stay updated with current issues : Environmental policy is a rapidly evolving field, with new challenges and developments emerging constantly. Stay informed about current environmental issues, policy debates, and emerging trends to identify timely and relevant environmental policy research paper topics that contribute to ongoing discussions and address pressing concerns.
• Consider the scope and depth of the topic : Assess the scope and depth of the topic you wish to explore. Is it broad enough to provide a comprehensive analysis, or does it require further refinement to ensure a focused and manageable research paper? Strike a balance between a topic that is sufficiently narrow to allow in-depth analysis and one that is broad enough to provide substantial content.
• Conduct a preliminary literature review : Before finalizing your research topic, conduct a preliminary literature review to familiarize yourself with existing scholarship and research gaps in the field of environmental policy. This will help you identify areas that have been extensively studied and areas that require further exploration, providing valuable insights for topic selection.
• Consider the policy context : Environmental policy is shaped by various social, political, economic, and cultural factors. When selecting a research topic, consider the policy context within which it operates. Analyze the stakeholders, policy frameworks, and implementation challenges associated with your chosen topic to ensure its relevance and significance.
• Engage in interdisciplinary perspectives : Environmental policy research often requires an interdisciplinary approach. Consider incorporating perspectives from other disciplines such as economics, sociology, law, or public health to enrich your analysis and provide a holistic understanding of the environmental policy issue you are investigating.
• Seek inspiration from real-world case studies : Real-world case studies provide valuable insights and practical implications for environmental policy research. Look for successful or failed policy interventions, case studies of environmental conflicts, or instances where policy measures have made a substantial impact. These examples can serve as a source of inspiration and provide a solid foundation for your research.
• Evaluate the feasibility of data collection : Before finalizing your research topic, consider the availability of data and the feasibility of data collection. Determine if the necessary data sources, such as government reports, surveys, or existing datasets, are accessible for your chosen topic. Adequate data availability is essential for conducting rigorous and evidence-based research.
• Consider the social and environmental justice dimensions : Environmental policy intersects with social and environmental justice issues. Explore environmental policy research paper topics that address issues of equity, inclusivity, and the distribution of environmental benefits and burdens. Consider how your research can contribute to advancing social and environmental justice within the realm of environmental policy.
• Seek guidance from mentors and experts : Engage in discussions with your mentors, professors, and experts in the field of environmental policy. Seek their guidance and input during the topic selection process. They can provide valuable insights, suggest relevant literature, and help you refine your research topic to ensure its academic rigor and contribution to the field.

By following these expert tips, you will be able to choose an environmental policy research paper topic that aligns with your interests, contributes to the existing body of knowledge, and addresses critical environmental challenges. Remember, the topic you choose is the foundation of your research, and investing time and effort in selecting the right one will set the stage for a successful and impactful research paper.

How to Write an Environmental Policy Research Paper

Writing an environmental policy research paper requires careful planning, critical analysis, and effective communication of ideas. To assist you in navigating the process and producing a high-quality research paper, we have compiled ten essential tips that will guide you from the initial stages of research to the final writing and presentation of your findings. Follow these steps to ensure that your environmental policy research paper is well-structured, thoroughly researched, and effectively communicated.

• Define your research question : Start by clearly defining your research question or objective. This will serve as the guiding principle throughout your research and help maintain focus and clarity in your paper. Ensure that your research question is specific, relevant, and aligned with the broader objectives of environmental policy research.
• Conduct a comprehensive literature review : Before diving into your own research, conduct a thorough literature review to familiarize yourself with existing scholarship on the topic. Identify key theories, concepts, and empirical studies that have shaped the understanding of environmental policy in your chosen area. This will help you situate your research within the existing body of knowledge and identify research gaps.
• Develop a coherent research methodology : Based on your research question, identify and employ appropriate research methods and data collection techniques. Consider whether your research requires qualitative or quantitative approaches, primary or secondary data, surveys, interviews, or case studies. Justify your chosen methodology and ensure that it aligns with the research question and objectives.
• Collect and analyze data : Collect data in accordance with your research methodology and analyze it using appropriate analytical tools and techniques. Ensure that you maintain a systematic approach to data collection, organization, and analysis to ensure the reliability and validity of your findings. Use data visualization techniques to present your results effectively.
• Use theoretical frameworks and conceptual models : Incorporate relevant theoretical frameworks and conceptual models into your research paper to provide a theoretical foundation for your analysis. These frameworks will help you analyze and interpret your findings in the context of existing theories and concepts in environmental policy.
• Consider policy implications : Environmental policy research aims to inform policy-making and contribute to the development of effective environmental policies. Analyze the policy implications of your findings and provide recommendations for policymakers, practitioners, and stakeholders. Consider the feasibility and practicality of your recommendations within the political and institutional context.
• Structure your paper effectively : Follow a clear and logical structure for your research paper. Include sections such as an introduction, literature review, research methodology, findings and analysis, discussion, conclusion, and references. Use headings and subheadings to organize your content and facilitate readability.
• Write in a clear and concise manner : Communicate your ideas in a clear and concise manner, using language that is accessible to your target audience. Avoid jargon and technical terms unless necessary, and provide clear explanations for complex concepts. Use proper grammar, punctuation, and citation style to maintain academic integrity.
• Support your arguments with evidence : Ensure that your arguments are supported by robust evidence and relevant examples. Cite credible sources such as academic journals, government reports, and reputable organizations to strengthen the validity of your claims. Include both primary and secondary sources to provide a well-rounded perspective.
• Revise, edit, and proofread : Take the time to revise, edit, and proofread your research paper to ensure clarity, coherence, and accuracy. Check for consistency in formatting, citations, and references. Read your paper multiple times, and consider seeking feedback from peers or mentors to identify areas for improvement.

By following these tips, you will be able to produce an environmental policy research paper that is well-researched, well-structured, and contributes to the existing body of knowledge in the field. Remember to allocate sufficient time for each stage of the research process, seek guidance from your professors or mentors, and maintain a disciplined approach to your work.

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Numbers, Facts and Trends Shaping Your World

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• Gen Z, Millennials Stand Out for Climate Change Activism, Social Media Engagement With Issue
• 2. Climate, energy and environmental policy

Table of Contents

• 1. Climate engagement and activism
• 3. Local impact of climate change, environmental problems
• Acknowledgments
• Methodology
• Appendix: Detailed charts and tables

A majority of Americans consider climate change a priority today so that future generations can have a sustainable planet, and this view is held across generations.

Looking to the future, the public is closely divided on what it will take to address climate change: While about half say it’s likely major lifestyle changes in the U.S. will be needed to deal with climate change impacts, almost as many say it’s more likely new developments in technology will address most of the problems cause by climate change.

On policy, majorities prioritize the use of renewable energy and back the expanded use of specific sources like wind and solar. Americans offer more support than opposition to a range of policies aimed at reducing the effects of climate change, including key climate-related aspects of President Joe Biden’s recent infrastructure proposal. Still, Americans do not back a complete break with carbon: A majority says oil and gas should still be part of the energy mix in the U.S., and about half oppose phasing out gas-powered vehicles by 2035.

Overall, 64% of U.S. adults say reducing the effects of climate change needs to be “a top priority to ensure a sustainable planet for future generations, even if that means fewer resources for addressing other important problems today.” By contrast, 34% say that reducing the effects of climate change needs to be “a lower priority, with so many other important problems facing Americans today, even if that means more climate problems for future generations.”

There are stark partisan differences over this sentiment. Nearly nine-in-ten Democrats (87%) say efforts to reduce the effects of climate change need to be prioritized today to ensure a sustainable planet. By contrast, 61% of Republicans say that efforts to reduce the effects of climate change need to be a lower priority, with so many other important problems facing Americans today. (Democrats and Republicans include those who lean to each party.)

Asked to look to the future 50 years from now, 51% of Americans say it’s more likely that major changes to everyday life in the U.S. will be needed to address the problems caused by global climate change. By contrast, 46% say it’s more likely that new technology will be able to address most of the problems caused by global climate change.

Most Democrats (69%) expect that in 50 years major lifestyle changes in the U.S. will be needed to address the problems caused by climate change. By contrast, among Republicans, two-thirds (66%) say it’s likelier that new technology will be able to address most climate change problems in the U.S. Among Republicans, this view is widely held (81%) among the majority who do not see climate change as an important personal concern; Republicans who express greater personal concern about climate change are more likely to say major changes to everyday life in the future will be needed to address problems caused by climate change.

Overall, majorities across generations believe that climate change should be a top priority today to ensure a sustainable planet for future generations. Generational divisions are more prominent among Republicans than Democrats, however.

Among Republicans, about half of Gen Zers (49%) and Millennials (48%) give top priority to reducing the effect of climate change today, even if that means fewer resources to deal with other important problems. By contrast, majorities of Gen X (61%) and Baby Boomer and older Republicans (71%) say reducing the effects of climate change needs to a lower priority today, given the other problems Americans are facing.

Generational differences among Democrats on this question are modest, with clear majorities giving priority to dealing with climate change today.

Majority of Americans prioritize developing alternative energy sources, but only a third would phase out all fossil fuels

Burning fossil fuels for electricity and in cars and trucks are among the primary sources of U.S. greenhouse gas emissions that contribute to climate change. Americans broadly favor increasing the use of renewable energy sources, but a majority reject the idea of phasing out fossil fuel energy sources completely. And Americans are about evenly divided on the idea of phasing out the production of new gasoline cars and trucks by 2035.

There are familiar partisan divisions over nearly every aspect of energy policy, particularly when it comes to fossil fuels. Political divides have widened over the past year as Republican support for alternative energy sources – including wind and solar power – has fallen while support for expanding offshore oil drilling, hydraulic fracturing and coal mining has ticked up.

Within both parties, Gen Zers and Millennials are more supportive of proposals to move away from fossil fuels than their older counterparts.

A majority of Americans (71%) continue to say that the U.S. should prioritize developing alternative energy, while a much smaller share (27%) prioritizes expanding the production of oil, coal and natural gas.

The share of Republicans who prioritize developing alternative energy sources over expanding the production of fossil fuels has fallen 18 percentage points in the past year. As a result, Republicans are now closely divided between these two energy priorities. Democrats remain near consensus levels in their support for prioritizing development of alternative energy levels.

Among Republicans, there are significant generational differences in support for increasing the development of renewable energy sources. Majorities of Gen Z (63%) and Millennial (62%) Republicans prioritize increased development of renewable sources, such as wind and solar. Smaller shares of Gen X Republicans (50%) and just 33% of Baby Boomer and older Republicans prioritize this approach over the expanding of fossil fuel development. For more details, including longer-term trends over time, see the Appendix .

Republicans and Democrats also differ over the best way to encourage reliance on renewable energy sources. Most Democrats (81%) continue to see a need for government regulations to increase reliance on renewable energy. On the other hand, two-thirds of Republicans (67%) say the private marketplace alone will be enough. See the Appendix for details.

In keeping with support for prioritizing the development of renewable energy, most Americans favor expanding solar panel farms (84%) and wind turbine farms (77%). By contrast, majorities oppose more coal mining (61%), more hydraulic fracturing (56%) and more offshore oil and gas drilling (55%).

Americans are divided over expanding nuclear power: 50% favor more nuclear power plants, while 47% are opposed.

Republican support for expanding solar power is down 11 points in the last year (from 84% to 73%), and support for wind power has fallen 13 points (from 75% to 62%). Democrats’ widely held support for increasing both energy sources remains largely unchanged.

In addition, there has been an increase since 2020 in the shares of Republicans who support expanding hydraulic fracturing of natural gas (up 10 points), offshore oil and gas drilling (up 6 points) and coal mining (up 6 points). See the Appendix for details.

Even so, younger Republicans remain less likely than their older counterparts to support expanding fossil fuel sources, consistent with past Center surveys.

For instance, 79% of Baby Boomer and older Republicans support more offshore oil and gas drilling, while roughly half (48%) of Gen Z Republicans say the same (a difference of 31 points). There are similar divides over hydraulic fracturing, the primary extraction technique for natural gas (74% of Baby Boomer and older Republicans favor vs. 44% of Gen Z Republicans).

Nearly two-thirds of Americans support using a mix of fossil fuel and renewable energy sources, younger adults more inclined to phase out fossil fuels completely

While a large share of U.S. adults would prioritize alternative energy development over expanding the use of fossil fuels, most adults are not inclined to give up reliance on fossil fuels altogether.

The survey finds 64% of Americans say they support ongoing use of oil, coal and natural gas as well as renewable energy sources, while a third (33%) say the country should phase out the use of fossil fuels completely.

There are sharp differences of opinion about this issue by party. Most Republicans (86%) say that the U.S. should rely on a mix of fossil fuel and renewable energy sources. Democrats are about evenly divided, with 47% in favor of using a mix of sources and 50% calling for a phase out of fossil fuels. About two-thirds of liberal Democrats (65%) support phasing out fossil fuels but fewer moderate and conservative Democrats say the same (39%).

There are also generational divisions on this issue, with younger generations more likely to support giving up fossil fuel use over time. In fact, majorities of Democratic Gen Zers (60%) and Millennials (57%) support phasing out fossil fuel use completely.

Americans are closely divided over phasing out gas-powered vehicles; Democrats, younger adults are more receptive to the idea

Climate advocates point to electric vehicles as a way to cut down on carbon emissions and reduce climate change. Americans are about equally divided on the idea of phasing out production of gasoline cars and trucks by 2035. A little under half (47%) say they would favor such a proposal, while 51% are opposed.

As with other proposals on climate and energy issues, partisans express opposing viewpoints. About two-thirds of Democrats (68%) support phasing out gasoline cars by 2035, while 76% of Republicans oppose this.

Most U.S. adults oppose oil drilling in ANWR but are more divided over Keystone XL decision

The issue of whether or not to allow oil and gas drilling in the Arctic National Wildlife Refuge has long been a controversy in energy policy. Overall, most Americans (70%) oppose the idea, while 27% are in favor.

Nearly all Democrats (89%) say they oppose allowing oil and gas drilling in the ANWR. Republicans are about evenly divided, with half in favor of allowing this and 48% opposed.

One of Biden’s  first actions as president  was revoking the permit for the Keystone XL pipeline. The pipeline would have carried oil from Canada into the U.S.

About half of Americans (49%) say canceling the pipeline was the right decision, while 45% say it was the wrong decision.

Most Democrats (78%) say it was the right decision, while most Republicans (80%) say otherwise. See details in the  Appendix .

But there are also generational dynamics in views about gasoline-powered vehicles, with younger adults more supportive than older adults of phasing out gas cars and trucks. Narrow majorities of Gen Zers (56%) and Millennials (57%) support such a proposal, compared with 38% of Baby Boomer and older Americans. This pattern holds within both parties, though sizable partisan divides remain across all generations. See the Appendix for a look at how these generational and partisan divides compare across measures.

The public is broadly familiar with electric vehicles: About nine-in-ten have heard either a lot (30%) or a little (62%) about them. When it comes to first-hand experience, 7% of adults say they currently have an electric or hybrid vehicle; 93% say they do not.

People who say they have heard a lot about electric vehicles are closely divided over the idea of phasing out gas-powered cars and trucks by a margin of 52% in favor to 48% opposed. Not surprisingly, those who currently own an electric or hybrid vehicle are largely in favor of this idea (68% vs. 31% opposed).

Broad public support for a number of policies to address climate change, including some proposed in Biden infrastructure plan

In late March, the Biden administration announced a $2 trillion infrastructure plan with several elements they argue would help reduce the effects of climate change. The new Center survey finds majorities of Americans support a number of proposals to address global climate change, including three specific elements in Biden’s infrastructure plan.

There are sharp partisan divisions over many of these proposals, as expected. In addition, there are concerns, particularly among Democrats, that Biden’s policy proposals will not go far enough in efforts to reduce the effects of climate change.

Majorities of U.S. adults support a range of approaches to address climate change

The new Center survey finds majorities back three specific elements of Biden’s infrastructure plan. More than seven-in-ten Americans (74%) favor a proposed requirement for power companies to use more energy from renewable sources, such as solar and wind, to reduce carbon emissions. A smaller majority – 62% – favors federal spending to build a network of electric vehicle charging stations across the country in order to increase the use of electric cars and trucks.

And 63% of Americans support the idea of raising corporate taxes to pay for more energy efficient buildings and improved roads and bridges, a key funding mechanism in Biden’s infrastructure proposal.

Biden has closely tied his climate-focused infrastructure proposals with economic and job growth. Half of U.S. adults think that the Biden administration’s plan to rebuild the nation’s infrastructure in ways that are aimed at reducing the effects of climate change will help the economy. Three-in-ten think this will hurt the economy, and 18% say it will make no difference.

Americans continue to broadly support a number of longer-standing proposals to reduce the effects of climate change. Nine-in-ten Americans favor planting additional trees to absorb carbon dioxide emissions. About eight-in-ten (81%) favor providing a tax credit for businesses that develop technology that can capture and store carbon emissions before they enter the atmosphere. Both of these ideas were part of a set of policies supported by congressional Republicans last year .

Large majorities of Americans also favor tougher restrictions on power plant carbon emissions (76%), taxing corporations based on the amount of carbon emissions they produce (70%) and tougher fuel-efficiency standards for automobiles and trucks (70%).

54% of Democrats think Biden administration’s climate policies will not go far enough

Three months into the Biden administration, there is no clear consensus over the administration’s approach on climate change. About four-in-ten Americans (41%) think the Biden administration’s policies to reduce the effects of climate change will not go far enough. Roughly three-in-ten (29%) think the Biden administration will go too far, and a similar share (28%) say the administration’s approach will be about right.

Republicans and Democrats have far different expectations for the Biden’s administration policies on climate change. A narrow majority of Democrats and those who lean to the Democratic Party (54%) –including 63% of liberal Democrats – think the administration’s policies will not go far enough to reduce the effects of climate change.

In contrast, six-in-ten Republicans and Republican-leaning independents say the Biden administration’s policies will go too far, including 74% of conservative Republicans.

There are some generational differences in views on this this issue among Republicans, in line with differences over the importance of addressing climate change. About as many Gen Z Republicans say Biden’s climate policies will not go far enough (35%) as say the policies will go too far (38%). By comparison, a 72% majority of Republicans in the Baby Boomer or older generations think the Biden administration will go too far on climate change.

When it comes to views about proposals aimed at reducing climate change, however, there are few differences of opinion across generations among either party. Yet large differences remain between Republicans and Democrats overall.

Democrats’ views about five proposals aimed at reducing the effects of climate change are uniformly positive. Roughly 85% to 95% of Democrats support each.

Republicans and Republican leaners are most supportive of proposals to absorb carbon emissions by planting large numbers of trees (88%), followed by a proposal to provide a corporate tax credit for carbon-capture technology (73%). A majority of the GOP (58%) favor tougher restrictions on carbon emissions from power plants. About half of Republicans favor taxing corporate carbon emissions (50%) or tougher fuel-efficiency standards for cars and trucks (49%).

There are no divisions within the GOP by generation across these issues, though ideological divides are often sharp. For example, 65% of moderate and liberal Republicans favor tougher fuel-efficiency standards for cars and trucks, compared with 40% of conservative Republicans.

Republicans and Democrats are also deeply divided over climate-focused proposals in the Biden administration’s infrastructure plan.

Large majorities of Democrats favor requiring power companies to use more energy from renewable sources (92%), raising corporate taxes to pay for energy efficient buildings and improved roads (84%) and building a network of electric vehicle charging stations across the country (82%).

About half of Republicans (52%) support requiring power companies to use more energy from renewable sources. There is less support for federal spending to build a nationwide network of electric vehicle charging stations (38%). An equal share of Republicans (38%) support the idea of raising taxes on corporations to pay for more energy efficient buildings and better roads, although more moderates and liberals in the GOP (59%) than conservatives (27%) support this idea.

There is comparatively more support for these proposals among younger Republicans, particularly for federal spending to build electric vehicle charging stations and requirements for power plants to use more renewable sources.

Republicans and Democrats at odds over economic impact of Biden’s infrastructure plan

Democrats are largely optimistic that the Biden administration’s plan to rebuild the nation’s infrastructure in ways aimed at reducing the effects of climate change will help the economy. About eight-in-ten Democrats (78%) say this.

Among Republicans, a majority (59%) thinks this proposed plan will hurt the economy, while only about two-in-ten (18%) say it will help. Conservative Republicans (71%) are especially inclined to say the climate-focused infrastructure proposal will hurt the economy.

Generational differences are largely modest but occur in both parties. Baby Boomer Republicans are the most pessimistic about the plan’s economic impact, while Boomer Democrats are the most optimistic that the plan will help the economy.

What are important considerations to Americans in climate proposals?

When it comes to proposals to reduce the effects of global climate change, protecting the environment for future generations and increasing jobs and economic growth are the top considerations Americans would like to see in policy proposals.

Asked to think about what is important to them in proposals to reduce the effects of climate change, 64% of the public says protecting the quality of the environment for future generations is a very important consideration to them personally; 28% say it’s somewhat important to them and just 6% say it’s not too or not at all important to them.

A majority (60%) also says that increasing job and economic growth is a very important consideration to them personally when it comes to proposals to reduce the effects of climate change.

About half (52%) say keeping consumer costs low is a very important consideration to them personally in climate proposals. Making sure proposals help lower-income communities is seen as a very important consideration by 45% of the public.

About a third (34%) say getting to net-zero carbon emissions as quickly as possible is a very important consideration to them personally. Joe Biden has set a goal for the U.S. to reach net-zero emissions by 2050.

Limiting the burden of regulations on businesses is seen as a very important climate policy consideration by 24% of the public – the lowest share who say this across the six items asked in the survey. However, majorities view all six factors, including limiting the regulatory burden on businesses, as at least somewhat important considerations in climate proposals.

Partisans have differing priorities when it comes to climate change proposals. Among Republicans, increasing job and economic growth (65% very important) and keeping consumer costs low (61%) are their top considerations. Among Democrats, protecting the quality of the environment for future generations is their clear top consideration (79% very important), followed by making sure proposals help lower-income communities (59%) and increasing job and economic growth (58%). About half of Democrats (51%) say getting to net-zero carbon emissions as quickly as possible is very important to them.

Public sees actions from businesses, ordinary Americans as insufficient on climate change

Americans see a range of actors as falling short in efforts to help reduce the effects of global climate change. The public is broadly critical of the lack of action from large businesses and the energy industry – but also views elected officials, as well as ordinary Americans, as failing to do their part.

Nearly seven-in-ten adults (69%) say large businesses and corporations are doing too little to help reduce the effects of global climate change, while just 21% say they are doing about the right amount and very few (8%) say they are doing too much to address climate change. Similarly, a majority of the public (62%) says the energy industry is doing too little to help reduce the effects of global climate change.

The public also extends criticism on climate inaction to Americans themselves and the officials they vote into elected office. Overall, 66% say ordinary Americans are doing too little to help reduce the effects of climate change, and 60% say this about their state’s elected officials. A separate question that asks about the actions of the federal government across a range of environmental areas finds that 59% say the federal government is doing too little on climate change.

Americans are less critical of their own individual actions in helping to address climate change: Roughly half (48%) believe they, themselves, are doing about the right amount to help reduce the effects of climate change. Still, almost as many (47%) say they are doing too little to help.

When it comes to the role of environmental advocacy organizations, 48% say they are doing about the right amount to help reduce the effects of climate change, compared with 29% who say they are doing too little and 22% who say they are doing too much.

There are stark partisan differences in views of the role groups and individuals are playing to help reduce the effects of climate change. Large majorities of Democrats and Democratic-leaning independents say large businesses (85%), ordinary Americans (82%), the energy industry (80%) and their state elected officials (79%) are doing too little to help reduce climate change impacts. By contrast, about half of Republicans and Republican leaners or fewer say these actors are doing too little to address climate change. Republicans are much more likely to say most of these groups are doing about the right amount than to say they are doing too much to address climate change.

Generational differences in views are most pronounced on this question within the GOP. In general, Gen Z and Millennial Republicans are more likely than older Republicans to say groups and individuals are doing too little to help reduce the effects of climate change. For instance, 57% of Gen Z and 59% of Millennial Republicans say large businesses are doing too little to help address climate change, compared with 50% of Gen X Republicans and 43% of Baby Boomer and older Republicans.

A 54% majority of U.S. adults see climate scientists’ role on policy as too limited, though some have doubts about scientists’ understanding

As the Biden administration, Congress and state and local governments debate how best to address climate change, 54% of Americans think climate scientists have too little influence on policy debates about climate change. Smaller shares say climate scientists have about the right amount (22%) or too much (22%) influence on climate policy.

At the same time, Americans appear to have reservations about climate scientists’ expertise and understanding. Only about two-in-ten Americans (18%) say climate scientists understand “very well” the best ways to address climate change. Another 42% say climate scientists understand ways to address climate change “fairly well”; 38% say they understand this not too or not at all well.

Public views of climate scientists’ understanding are more positive, if still generally skeptical, on the fundamentals of whether climate change is occurring (37% say scientists understand this very well) and what causes climate change (28%).

Americans’ overall views about climate scientists’ expertise and understanding of what is happening to the Earth’s climate are similar to 2016, the last time Pew Research Center asked these questions.

In keeping with the wide political divisions over climate policy issues, Democrats are far more likely than Republicans to rate climate scientists’ understanding highly. And these partisan divides have widened since 2016. For example, Democrats are 43 percentage points more likely than Republicans to say climate scientists understand very well whether or not climate change is occurring. This gap was 25 points in 2016. See the Appendix for details.

Similarly, far larger shares of Democrats than Republicans believe climate scientists have too little say in climate debates (77% vs. 27%).

Younger generations are especially likely to think climate scientists have too little say on climate policy debates. However, these generational dynamics occur only within the GOP.

Millennial (38%) and Gen Z (41%) Republicans are more likely than Baby Boomers and older generations of Republicans (18%) to think climate scientists have too little influence on related policy debates. About half of older Republicans (53%) say climate scientists have too much influence in these debates.

Roughly three-quarters to eight-in-ten Democrats across younger and older generations think climate scientists have too little say in climate policy debates.

Majority of Americans continue to say federal government is doing too little to protect key aspects of the environment

When it comes to environmental protection, a majority of Americans continue to see a role for stricter environmental regulations and majorities view the federal government as doing too little across most areas of environmental concern asked about in the survey, such as protecting air quality.

Gen Z and Millennials offer the broadest support for environmental regulations and for more government action to protect specific aspects of the environment.

Partisan gaps over government action to protect the environment remain very large and differences over the value of stricter environmental regulations have widened since last asked in September 2019 during the administration of Donald Trump.

There are generational and partisan differences over value of environmental regulations

Overall, 56% of Americans say that stricter environmental laws are worth the cost, compared with a smaller share (41%) who say they cost too many jobs and hurt the economy.

On balance Gen Z and Millennials are both much more likely to  stricter environmental laws as worth the cost than to say they cost too many jobs and hurt the economy (by 59% to 33% and 63% to 35%, respectively). Gen X and Boomer and older adults also see stricter environmental laws as worth the cost, though by narrower margins.

A large majority of Democrats (81%) believe that stricter environmental laws are worth the cost. By contrast, 71% of Republicans say they cost too many jobs and hurt the economy. Republicans have become much more likely to take a critical view of stricter environmental regulations since September 2019, when 55% said they hurt the economy and cost too many jobs. (For more details on this change over time, see the Appendix ).

Generational differences in views occur primarily within the GOP and not among Democrats. Among Republicans, Gen Z (35%) and Millennials (34%) are more likely than Baby Boomer and older adults (20%) to say stricter environmental laws are worth the cost, though larger shares across cohorts say these regulations cost too many jobs and hurt the economy. Roughly eight-in-ten Democrats across generations say that stricter environmental laws are worth the cost.

Far more Americans say government is doing too little, rather than too much, on key areas of environmental protection

Consistent with Center surveys over the past few years, majorities of U.S. adults support more government action to address a range of environmental concerns, including air and water quality as well as climate change.

Overall, 63% say the federal government is doing too little to protect the water quality of lakes, rivers and streams. Majorities also say the government is doing too little to reduce the effects of climate change (59%), protect air quality (59%) and protect animals and their habitats (57%). About half (51%) say the federal government is doing too little to protect open lands in national parks and nature preserves. Across all five items, small shares of the public believe the government is doing too much to address any one of these environmental issues.

There are wide differences in views on these issues by political party, with Democrats much more likely than Republicans to think that government efforts in these areas are insufficient.

While still the predominant viewpoint, the shares of Democrats who say the government is doing too little across these five areas are 6 to 10 percentage points lower than they were in May of 2020, before Joe Biden took office. Republicans’ views on these questions have been largely steady, although the share of Republicans who believe the federal government is doing too little to address climate change is down 5 percentage points, from 35% in May 2020 to 30% today.

Partisan groups remain far apart when it comes to assessment of government action on climate change: 83% of Democrats and Democratic leaners think the government’s efforts are insufficient, vs. 30% of Republicans and GOP leaners, a difference of 53 percentage points. Conservative Republicans stand out on this from their fellow partisans with a moderate or liberal ideology: 19% say the federal government is doing too little to address climate change compared with 49% of moderate or liberal Republicans.

Gen Zers and Millennials are more likely than older Americans to say the government is doing too little to address specific areas of environmental concern, though these divides are driven primarily by differences by generation within the GOP.

About two-thirds of Gen Zers (66%) and Millennials (65%) say the federal government is doing too little to protect air quality, compared with 58% of Gen X and 52% of Baby Boomer and older adults.

Similarly, 68% of Gen Zers and 66% of Millennials say the federal government is doing too little to reduce the effects of climate change versus 57% of Gen X and 52% of Baby Boomer and older adults.

Among Republicans, Gen Zers and Millennials are more likely than Baby Boomer and older adults to say the federal government is doing too little to address all five of these areas of environmental concern. Majorities of Democrats across generations say the government is doing too little to address these environmental issues.

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• Open access
• Published: 26 November 2023

Impact of industrial robots on environmental pollution: evidence from China

• Yanfang Liu 1  

Scientific Reports volume  13 , Article number:  20769 ( 2023 ) Cite this article

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The application of industrial robots is considered a significant factor affecting environmental pollution. Selecting industrial wastewater discharge, industrial SO 2 emissions and industrial soot emissions as the evaluation indicators of environmental pollution, this paper uses the panel data model and mediation effect model to empirically examine the impact of industrial robots on environmental pollution and its mechanisms. The conclusions are as follows: (1) Industrial robots can significantly reduce environmental pollution. (2) Industrial robots can reduce environmental pollution by improving the level of green technology innovation and optimizing the structure of employment skills. (3) With the increase in emissions of industrial wastewater, industrial SO 2 , and industrial dust, the impacts generated by industrial robots are exhibiting trends of a “W” shape, gradual intensification, and progressive weakening. (4) Regarding regional heterogeneity, industrial robots in the eastern region have the greatest negative impact on environmental pollution, followed by the central region, and the western region has the least negative impact on environmental pollution. Regarding time heterogeneity, the emission reduction effect of industrial robots after 2013 is greater than that before 2013. Based on the above conclusions, this paper suggests that the Chinese government and enterprises should increase investment in the robot industry. Using industrial robots to drive innovation in green technology and optimize employment skill structures, reducing environmental pollution.

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Introduction

Since the reform and opening up, China’s rapid economic growth has created a world-renowned “economic growth miracle” 1 . With the rapid economic growth, China’s environmental pollution problem is becoming more and more serious 2 . According to the “ Global Environmental Performance Index Report ” released by Yale University in the United States in 2022, China’s environmental performance index scores 28.4 points, ranking 160th out of 180 participating countries. The aggravation of environmental pollution not only affects residents’ health 3 , but also affects the efficiency of economic operation 4 . According to calculation of the General Administration of Environmental Protection, the World Bank and the Chinese Academy of Sciences, China’s annual losses caused by environmental pollution account for about 10% of GDP. Exploring the factors that affect environmental pollution and seeking ways to reduce environmental pollution are conducive to the development of economy within the scope of environment.

Industrial robots are machines that can be automatically controlled, repeatedly programmed, and multi-purpose 5 . They replace the low-skilled labor force engaged in procedural work 6 , reducing the raw materials required for manual operation. Industrial robots improve the clean technology level and energy efficiency of coal combustion, reducing pollutant emissions in front-end production. Industrial robots also monitor the energy consumption and sewage discharge in the production process in real time. The excessive discharge behavior of enterprises in the production process is regulated, reducing the emission of pollutants in the end treatment. Based on the selection and coding of literature (Appendix A ), this paper uses the meta-analysis method to compare the impacts of multiple factors such as economics, population, technology, and policy on environmental pollution. As shown in Table 1 , compared to other factors, industrial robots demonstrate greater advantages in reducing environmental pollution. There is a lack of research on the relationship between industrial robots and environmental pollution in China. With the advent of artificial intelligence era, China’s industrial robot industry has developed rapidly. According to data released by the International Federation of Robotics (IFR), from 1999 to 2019, China’s industrial robot ownership and installation shows an increasing trend year by year (Fig.  1 ). In 2013 and 2016, China’s industrial robot installation (36,560) and ownership (349,470) exceeds Japan for the first time, becoming the world’s largest country in terms of installation and ownership of industrial robots. Whether the application of industrial robots in China contributes to the reduction of environmental pollution? What is the mechanism of the impact of China’s industrial robots on environmental pollution? Researching this issue is crucial for filling the gaps in existing research and providing a reference for other countries to achieve emission reduction driven by robots.

Industrial robot installations in the world’s top five industrial robot markets from 1999 to 2019.

Based on the above analysis, this paper innovatively incorporates industrial robots and environmental pollution into a unified framework. Based on the panel data of 30 provinces in China from 2006 to 2019, this paper uses the ordinary panel model and mediating effect model to empirically test the impact of industrial robots on China’s environmental pollution and its transmission channels. The panel quantile model is used to empirically analyze the heterogeneous impact of industrial robots on environmental pollution under different environmental pollution levels.

Literature review

A large number of scholars have begun to study the problem of environmental pollution. Its research content mainly includes two aspects: The measurement of environmental pollution and its influencing factors. Regarding the measurement, some scholars have used SO 2 emissions 7 , industrial soot emissions 8 and PM2.5 concentration 9 and other single indicators to measure the degree of environmental pollution. The single indicator cannot fully and scientifically reflect the degree of environmental pollution. To make up for this defect, some scholars have included industrial SO 2 emissions, industrial wastewater discharge and industrial soot emissions into the environmental pollution evaluation system, and used the entropy method to measure environmental pollution level 10 . This method ignores the different characteristics and temporal and spatial trends of different pollutants, which makes the analysis one-sided. Regarding the influencing factors, economic factors such as economic development level 11 , foreign direct investment 12 and income 13 , population factors such as population size 14 and urbanization level 15 , energy consumption 16 all have an impact on environmental pollution. Specifically, economic development and technological innovation can effectively reduce environmental pollution 17 . The expansion of population size can aggravate environmental pollution. Income inequality can reduce environmental pollution, but higher income inequality may aggravate environmental pollution 18 . There are “pollution heaven hypothesis” and “pollution halo hypothesis” between foreign direct investment and environmental pollution 19 . Technological factors also have a non-negligible impact on environmental pollution 20 .

With continuous deepening of research, scholars have begun to focus on the impact of automation technology, especially industrial robot technology, on the environment. Ghobakhloo et al. 21 theoretically analyzed the impact of industrial robots on energy sustainability, contending that the application of industrial robots could foster sustainable development of energy. Using data from multiple countries, a few scholars have empirically analyzed the effect of industrial robots on environmental pollution (Table 2 ). Luan et al. 22 used panel data from 73 countries between 1993 and 2019 to empirically analyze the impact of industrial robots on air pollution, finding that the use of industrial robots intensifies environmental pollution. Using panel data from 66 countries from 1993 to 2018, Wang et al. 23 analyzed the impact of industrial robots on carbon intensity and found that industrial robots can reduce carbon intensity. On the basis of analyzing the overall impact of industrial robots on environmental pollution, some scholars conducted in-depth exploration of its mechanism. Based on data from 72 countries between 1993 and 2019, Chen et al. 5 explored the impact of industrial robots on the ecological footprint, discovering that industrial robots can reduce the ecological footprint through time saving effect, green employment effect and energy upgrading effect. Using panel data from 35 countries between 1993 and 2017, Li et al. 24 empirically examined the carbon emission reduction effect of industrial robots, finding that industrial robots can effectively reduce carbon emissions by increasing green total factor productivity and reducing energy intensity. Although the above studies have successfully estimated the overall impact of industrial robots on environmental pollution and its mechanisms, they have not fully considered the role of technological progress, labor structure and other factors in the relationship between the two. These studies all chose data from multiple countries as research samples and lack research on the relationship between industrial robots and environmental pollution in China, an emerging country.

The above literature provides inspiration for this study, but there are still shortcomings in the following aspects: Firstly, there is a lack of research on the relationship between industrial robots and environmental pollution in emerging countries. There are significant differences between emerging and developed countries in terms of institutional background and the degree of environmental pollution. As a representative emerging country, research on the relationship between industrial robots and environmental pollution in China can provide reliable references for other emerging countries. Secondly, theoretically, the study of the impact of industrial robots on environmental pollution is still in its initial stage. There are few studies that deeply explore its impact mechanism, and there is a lack of analysis of the role of technological progress and labor structure in the relationship between the two.

The innovations of this paper are as follows: (1) In terms of sample selection, this paper selects panel data from 30 provinces in China from 2006 to 2019 as research samples to explore the relationship between industrial robots and environmental pollution in China, providing references for other emerging countries to improve environmental quality using industrial robots. (2) In terms of theory, this paper is not limited to revealing the superficial relationship between industrial robots and environmental pollution. it starts from a new perspective and provides an in-depth analysis of how industrial robots affect environmental pollution through employment skill structure and green technology innovation. This not only enriches research in the fields of industrial robots and the environment, but is also of great significance in guiding the direction of industrial policy and technology research and development.

Theoretical analysis and hypothesis

Industrial robots and environmental pollution.

As shown in Fig.  2 , the impact of industrial robots on environmental pollution is mainly reflected in two aspects: Front-end production and end treatment. In front-end production, industrial robots enable artificial substitution effects 25 . Manual operation is replaced by machine operation, reducing the raw materials needed for manual operation. Through the specific program setting of industrial robots, clean energy is applied to industrial production 26 . The use of traditional fuels such as coal and oil is reduced. In terms of end treatment, the traditional pollutant concentration tester only measures a single type of pollutant. Its data cannot be obtained in time. It is easy to cause pollution incidents. Industrial robots can measure a variety of pollutants, and have the function of remote unmanned operation and warning. It reflects the pollution situation in time, reducing the probability of pollution incidents. The use of robots can upgrade sewage treatment equipment and improve the accuracy of pollution treatment, reducing pollutant emissions. Based on the above analysis, this paper proposes hypothesis 1.

The impact of industrial robots on environmental pollution.

Hypothesis 1

The use of industrial robots can reduce environmental pollution.

Mediating effect of green technology innovation

Industrial robots can affect environmental pollution by promoting green technology innovation. The transmission path of “industrial robots-green technology innovation-environmental pollution” is formed. Industrial robots are the materialization of technological progress in the field of enterprise R&D. Its impact on green technology innovation is mainly manifested in the following two aspects: Firstly, industrial robots classify known knowledge, which helps enterprises to integrate internal and external knowledge 27 . The development of green technology innovation activities of enterprises is promoted. Secondly, enterprises can simulate existing green technologies through industrial robots. The shortcomings of green technology in each link are found. Based on this, enterprises can improve and perfect green technology in a targeted manner. Industrial robots can collect and organize data, which enables enterprises to predict production costs and raw material consumption. Excessive procurement by enterprises can occupy working capital. Inventory backlog leads to warehousing, logistics and other expenses, increasing storage costs 28 . Forecasting the consumption of raw materials allows enterprises to purchase precisely, preventing over-procurement and inventory backlog, thereby reducing the use of working capital and storage costs 29 . The production cost of enterprises is reduced. Enterprises have more funds for green technology research and development.

The continuous innovation of green technology is helpful to solve the problem of environmental pollution. Firstly, green technology innovation helps use resources better 30 , lowers dependence on old energy, and reduces environmental damage. Secondly, green technology innovation promotes the greening of enterprises in manufacturing, sales and after-sales 31 . The emission of pollutants in production process is reduced. Finally, green technology innovation improves the advantages of enterprises in market competition 32 . The production possibility curve expands outward, which encourages enterprises to carry out intensive production. Based on the above analysis, this paper proposes hypothesis 2.

Hypothesis 2

Industrial robots can reduce environmental pollution through green technology innovation.

Mediating effect of employment skill structure

Industrial robots can affect environmental pollution through employment skill structure. The transmission path of “industrial robots-employment skill structure-environmental pollution” is formed. Industrial robots have substitution effect and creation effect on the labor force, improving the employment skill structure. Regarding the substitution effect, enterprises use industrial robots to complete simple and repetitive tasks to improve production efficiency, which crowds out low-skilled labor 6 . Regarding the creation effect, industrial robots create a demand for new job roles that matches automation, such as robot engineers, data analysts, machine repairers, which increases the number of highly skilled labor 33 . The reduction of low-skilled labor and increase of high-skilled labor improve employment skill structure.

High-skilled labor is reflected in the level of education 34 . Its essence is to have a higher level of skills and environmental awareness, which is the key to reducing environmental pollution. Compared with low-skilled labor, high-skilled labor has stronger ability to acquire knowledge and understand skills, which improves the efficiency of cleaning equipment and promotes emission reduction. The interaction and communication between highly skilled labor is also crucial for emission reduction. The excessive wage gap between employees brings high communication costs, which hinders the exchange of knowledge and technology between different employees. The increase in the proportion of high-skilled labor can solve this problem and improve the production efficiency of enterprises 35 . The improvement of production efficiency enables more investment in emission reduction research, decreasing pollutant emissions. Based on the above analysis, this paper proposes hypothesis 3.

Hypothesis 3

Industrial robots can reduce environmental pollution by optimizing employment skills structure.

Model construction and variable selection

Model construction, panel data model.

The panel data model is a significant statistical method, first introduced by Mundlak 36 . Subsequently, numerous scholars have used this model to examine the baseline relationships between core explanatory variables and explained variables 37 . To test the impact of industrial robots on environmental pollution, this paper sets the following panel data model:

In formula ( 1 ), Y it is the explained variable, indicating the degree of environmental pollution in region i in year t . IR it is the core explanatory variable, indicating the installation density of industrial robots in region i in year t . X it is a series of control variables, including economic development level (GDP), urbanization level (URB), industrial structure (EC), government intervention (GOV) and environmental regulation (ER). \(\lambda i\) is the regional factor. \(\varphi t\) is the time factor. \(\varepsilon it\) is the disturbance term.

Mediating effect model

To test the transmission mechanism of industrial robots affecting environmental pollution, this paper sets the following mediating effect model:

In formula ( 2 ), M is the mediating variable, which mainly includes green technology innovation and employment skill structure. Formula ( 2 ) measures the impact of industrial robots on mediating variables. Formula ( 3 ) measures the impact of intermediary variables on environmental pollution. According to the principle of mediating effect 38 , the direct effect \(\theta 1\) , mediating effect \(\beta 1 \times \theta 2\) and total effect \(\alpha 1\) satisfy \(\alpha 1 = \theta 1 + \beta 1 \times \theta 2\) .

Panel quantile model

The panel quantile model was first proposed by Koenke and Bassett 39 . It is mainly used to analyze the impact of core explanatory variables on the explained variables under different quantiles 40 . To empirically test the heterogeneous impact of industrial robots on environmental pollution under different levels of environmental pollution, this paper sets the following panel quantile model:

In formula ( 4 ), \(\tau\) represents the quantile value. \(\gamma 1\) reflects the difference in the impact of industrial robots on environmental pollution at different quantiles. \(\gamma 2\) indicates the different effects of control variables at different quantiles.

Variable selection

Explained variable.

The explained variable is environmental pollution. Considering the timeliness and availability of data, this paper selects industrial wastewater discharge, industrial SO 2 emissions and industrial soot emissions as indicators of environmental pollution.

Explanatory variable

According to production theory, industrial robots can enhance production efficiency 41 . Efficient production implies reduced energy wastage, which in turn decreases the emission of pollutants. Industrial robots can upgrade pollution control equipment, heightening the precision in pollution treatment and reducing pollutant discharge. Referring to Acemoglu and Restrepo 25 , this paper selects the installation density of industrial robots as a measure. The specific formula is as follows:

In formula ( 5 ), Labor ji is the number of labor force in industry j in region i . IR jt is the stock of industrial robot use in industry j in the year t .

Mediating variable

Green technology innovation. Industrial robots can increase the demand for highly-skilled labor 42 , subsequently influencing green technology innovation. Compared to ordinary labor, highly-skilled labor possesses a richer knowledge base and technological learning capability, improving the level of green technology innovation. Green technology innovation can improve energy efficiency 43 , reducing pollution generated by energy consumption. The measurement methods of green technology innovation mainly include three kinds: The first method is to use simple technology invention patents as measurement indicators. Some of technical invention patents are not applied to the production process of enterprise, they cannot fully reflect the level of technological innovation. The second method is to use green product innovation and green process innovation as measurement indicators. The third method is to use the number of green patent applications or authorizations as a measure 44 . This paper selects the number of green patent applications as a measure of green technology innovation.

Employment skill structure. The use of industrial robots reduces the demand for labor performing simple repetitive tasks and increases the need for engineers, technicians, and other specialized skilled personnel, improving the employment skill structure 45 . Compared to ordinary workers, highly-skilled laborers typically have a stronger environmental awareness 46 . Such environmental consciousness may influence corporate decisions, prompting companies to adopt eco-friendly production methods, thus reducing environmental pollution. There are two main methods to measure the structure of employment skills: One is to use the proportion of employees with college degree or above in the total number of employees as a measure. The other is to use the proportion of researchers as a measure. The educational level can better reflect the skill differences of workers. This paper uses the first method to measure the employment skill structure.

Control variable

Economic development level. According to the EKC hypothesis 47 , in the initial stage of economic development, economic development mainly depends on input of production factors, which aggravates environmental pollution. With the continuous development of economy, people begin to put forward higher requirements for environmental quality. The government also begins to adopt more stringent policies to control environmental pollution, which can reduce the level of environmental pollution. According to Liu and Lin 48 , This paper uses per capita GDP to measure economic development level.

Urbanization level. The improvement of urbanization level has both positive and negative effects on pollution. Urbanization can improve the agglomeration effect of cities. The improvement of agglomeration effect can not only promote the sharing of public resources such as infrastructure, health care, but also facilitate the centralized treatment of pollution. The efficiency of environmental governance is improved 49 . The acceleration of urbanization can increase the demand for housing, home appliances and private cars, which increases pollutant emissions 50 . This paper uses the proportion of urban population to total population to measure the level of urbanization.

Industrial structure. Industrial structure is one of the key factors that determine the quality of a country’s environmental conditions 51 . The increase in the proportion of capital and technology-intensive industries can effectively improve resource utilization efficiency and improve resource waste 52 . This paper selects the ratio of the added value of the tertiary industry to the secondary industry to measure industrial structure.

Government intervention. Government intervention mainly affects environmental pollution from the following two aspects: Firstly, the government can give high-tech, energy-saving and consumption-reducing enterprises relevant preferential policies, which promotes the development of emission reduction technologies for these enterprises 53 . Secondly, the government strengthens environmental regulation by increasing investment in environmental law enforcement funds, thus forcing enterprises to save energy and reduce emissions 54 . This paper selects the proportion of government expenditure in GDP to measure government intervention.

Environmental regulation. The investment in environmental pollution control is conducive to the development of clean and environmental protection technology, optimizing the process flow and improving the green production efficiency of enterprises 55 . Pollutant emissions are reduced. This paper selects the proportion of investment in pollution control to GDP to measure environmental regulation.

Data sources and descriptive statistics

This paper selects the panel data of 30 provinces in China from 2006 to 2019 as the research sample. Among them, the installation data of industrial robots are derived from International Federation of Robotics (IFR). The data of labor force and employees with college degree or above are from China Labor Statistics Yearbook . Other data are from the China Statistical Yearbook . The descriptive statistics of variables are shown in Table 3 . Considering the breadth of application and the reliability of analysis capabilities, this paper uses Stata 16 for regression analysis.

Results analysis

Spatial and temporal characteristics of environmental pollution and industrial robots in china, environmental pollution.

Figure  3 a shows the overall trend of average industrial wastewater discharge in China from 2006 to 2019. From 2006 to 2019, the discharge of industrial wastewater shows a fluctuating downward trend, mainly due to the improvement of wastewater treatment facilities and the improvement of treatment capacity. Figure  3 b shows the changing trend of average industrial wastewater discharge in 30 provinces of China from 2006 to 2019. Industrial wastewater discharge in most provinces has declined. There are also some provinces such as Fujian, Guizhou and Qinghai, which have increased industrial wastewater discharge. Their emission reduction task is very arduous.

Industrial wastewater discharge from 2006 to 2019.

Figure  4 a shows the overall trend of average industrial SO 2 emissions in China from 2006 to 2019. From 2006 to 2019, industrial SO 2 emissions shows a fluctuating downward trend, indicating that air pollution control and supervision are effective. Figure  4 b shows the trend of average industrial SO 2 emissions in 30 provinces of China from 2006 to 2019. Similar to industrial wastewater, industrial SO 2 emissions decrease in most provinces.

Industrial SO 2 emissions from 2006 to 2019.

Figure  5 a shows the overall trend of average industrial soot emissions in China from 2006 to 2019. Different from industrial wastewater and industrial SO 2 , the emission of industrial soot is increasing year by year. From the perspective of governance investment structure, compared with industrial wastewater and industrial SO 2 , the investment proportion of industrial soot is low. From the perspective of source, industrial soot mainly comes from urban operation, industrial manufacturing and so on. The acceleration of urbanization and the expansion of manufacturing scale have led to an increase in industrial soot emissions. Figure  5 b shows the trend of industrial soot emissions in 30 provinces in China from 2006 to 2019. The industrial soot emissions in most provinces have increased.

Industrial soot emissions from 2006 to 2019.

Figure  6 shows the spatial distribution characteristics of industrial wastewater, industrial SO 2 and industrial soot emissions. The three types of pollutant emissions in the central region are the largest, followed by the eastern region, and the three types of pollutant emissions in the western region are the smallest. Due to resource conditions and geographical location, the central region is mainly dominated by heavy industry. The extensive development model of high input and consumption makes its pollutant emissions higher than the eastern and western regions. The eastern region is mainly capital-intensive and technology-intensive industries, which makes its pollutant emissions lower than the central region. Although the leading industry in the western region is heavy industry, its factory production and transportation scale are not large, which produces less pollutants.

Spatial distribution characteristics of industrial wastewater, industrial SO 2 and industrial soot.

Industrial robots

Figure  7 a shows the overall trend of installation density of industrial robots in China from 2006 to 2019. From 2006 to 2019, the installation density of industrial robots in China shows an increasing trend year by year. The increase of labor cost and the decrease of industrial robot cost make enterprises use more industrial robots, which has a substitution effect on labor force. The installation density of industrial robots is increased. Figure  7 b shows the trend of installation density of industrial robots in 30 provinces of China from 2006 to 2019. The installation density of industrial robots in most provinces has increased. Among them, the installation density of industrial robots in Guangdong Province has the largest growth rate. The installation density of industrial robots in Heilongjiang Province has the smallest growth rate.

Installation density of industrial robots from 2006 to 2019.

Figure  8 shows the spatial distribution characteristics of installation density of industrial robots. The installation density of industrial robots in the eastern region is the largest, followed by the central region, and the installation density of industrial robots in the western region is the smallest. The eastern region is economically developed and attracts lots of talents to gather here, which provides talent support for the development of industrial robots. Advanced technology also leads to the rapid development of industrial robots in the eastern region. The economy of western region is backward, which inhibits the development of industrial robots.

Spatial distribution characteristics of industrial robots.

Benchmark regression results

Table 4 reports the estimation results of the ordinary panel model. Among them, the F test and LM test show that the mixed OLS model should not be used. The Hausman test shows that the fixed effect model should be selected in the fixed effect model and random effect model. This paper selects the estimation results of the fixed effect model to explain.

Regarding the core explanatory variable, industrial robots have a significant negative impact on the emissions of industrial wastewater, industrial SO 2 and industrial soot. Specifically, industrial robots have the greatest negative impact on industrial soot emissions, with a coefficient of -0.277 and passing the 1% significance level. The negative impact of industrial robots on industrial wastewater discharge is second, with an estimated coefficient of -0.242, which also passes the 1% significance level. The negative impact of industrial robots on industrial SO 2 emissions is the smallest, with an estimated coefficient of -0.0875 and passing the 10% significant level. Compared with industrial wastewater and SO 2 , industrial robots have some unique advantages in reducing industrial soot emissions. Firstly, in terms of emission sources, industrial soot emissions mainly come from physical processes such as cutting. These processes can be significantly improved through precise control of industrial robots. Industrial SO 2 comes from the combustion process. Industrial wastewater originates from various industrial processes. It is difficult for industrial robots to directly control these processes. Secondly, in terms of source control and terminal treatment, industrial robots can reduce excessive processing and waste of raw materials, thereby controlling industrial soot emissions at the source. For industrial SO 2 and industrial wastewater, industrial robots mainly play a role in terminal treatment. Since the terminal treatment of industrial SO 2 and industrial wastewater often involves complex chemical treatment processes, it is difficult for industrial robot technology to fully participate in these processes. This makes the impact of industrial robots in the field of industrial SO 2 and industrial wastewater more limited than that in the field of industrial soot.

Regarding the control variables, the level of economic development has a significant inhibitory effect on industrial SO 2 emissions. The higher the level of economic development, the stronger the residents’ awareness of environmental protection, which constrains the pollution behavior of enterprises. The government also adopts strict policies to control pollutant emissions. The impact of urbanization level on the discharge of industrial wastewater, industrial SO 2 and industrial soot is significantly negative. The improvement of urbanization level can improve the efficiency of resource sharing and the centralized treatment of pollutants, reducing environmental pollution. The industrial structure significantly reduces industrial SO 2 and industrial soot emissions. The upgrading of industrial structure not only reduces the demand for energy, but also improves the efficiency of resource utilization. The degree of government intervention only significantly reduces the discharge of industrial wastewater. The possible reason is that to promote economic development, the government invests more money in high-yield areas, which crowds out investment in the environmental field. Similar to the degree of government intervention, environmental regulation has a negative impact on industrial wastewater discharge. The government’s environmental governance investment has not given some support to the enterprise’s clean technology research, which makes the pollution control investment not produce good emission reduction effect.

Mediation effect regression results

Green technology innovation.

Table 5 reports the results of intermediary effect model when green technology innovation is used as an intermediary variable. Industrial robots can have a positive impact on green technology innovation. For every 1% increase in the installation density of industrial robots, the level of green technology innovation increases by 0.722%. After adding the green technology innovation, the estimated coefficient of industrial robots has decreased, which shows that the intermediary variable is effective.

In the impact of industrial robots on industrial wastewater discharge, the mediating effect of green technology innovation accounts for 8.17% of the total effect. In the impact of industrial robots on industrial SO 2 emissions, the mediating effect of green technology innovation accounts for 11.8% of the total effect. In the impact of industrial robots on industrial soot emissions, the mediating effect of green technology innovation accounts for 3.72% of the total effect.

Employment skill structure

Table 6 reports the results of intermediary effect model when the employment skill structure is used as an intermediary variable. Industrial robots have a positive impact on the employment skill structure. For every 1% increase in the installation density of industrial robots, the employment skill structure is improved by 0.0837%. Similar to green technology innovation, the intermediary variable of employment skill structure is also effective.

In the impact of industrial robots on industrial wastewater discharge, the mediating effect of employment skill structure accounts for 6.67% of the total effect. In the impact of industrial robots on industrial SO 2 emissions, the mediating effect of employment skill structure accounts for 20.66% of the total effect. In the impact of industrial robots on industrial soot emissions, the mediating effect of employment skill structure accounts for 15.53% of the total effect.

Robustness test and endogeneity problem

Robustness test.

To ensure the robustness of the regression results, this paper tests the robustness by replacing core explanatory variables, shrinking tail and replacing sample. Regarding the replacement of core explanatory variables, in the benchmark regression, the installation density of industrial robots is measured by the stock of industrial robots. Replacing the industrial robot stock with the industrial robot installation quantity, this paper re-measures the industrial robot installation density. Regarding the tail reduction processing, this paper reduces the extreme outliers of all variables in the upper and lower 1% to eliminate the influence of extreme outliers. Regarding the replacement of samples, this paper removes the four municipalities from the sample. The estimation results are shown in Table 7 . Industrial robots still have a significant negative impact on environmental pollution, which confirms the robustness of benchmark regression results.

Endogeneity problem

Logically speaking, although the use of industrial robots can reduce environmental pollution, there may be reverse causality. Enterprises may increase the use of industrial robots to meet emission reduction standards, which increases the use of industrial robots in a region. Due to the existence of reverse causality, there is an endogenous problem that cannot be ignored between industrial robots and environmental pollution.

To solve the impact of endogenous problems on the estimation results, this paper uses the instrumental variable method to estimate. According to the selection criteria of instrumental variables, this paper selects the installation density of industrial robots in the United States as the instrumental variable. The trend of the installation density of industrial robots in the United States during the sample period is similar to that of China, which is consistent with the correlation characteristics of instrumental variables. The application of industrial robots in the United States is rarely affected by China’s economic and social factors, and cannot affect China’s environmental pollution, which is in line with the exogenous characteristics of instrumental variables.

Table 8 reports the estimation results of instrumental variable method. Among them, the column (1) is listed as the first stage regression result. The estimated coefficient of instrumental variable is significantly positive, which is consistent with the correlation. Column (2), column (3) and column (4) of Table 8 are the second stage regression results of industrial wastewater, industrial SO 2 and industrial soot emissions as explanatory variables. The estimated coefficients of industrial robots are significantly negative, which again verifies the hypothesis that industrial robots can reduce environmental pollution. Compared with Table 4 , the absolute value of estimated coefficient of industrial robots is reduced, which indicates that the endogenous problems caused by industrial robots overestimate the emission reduction effect of industrial robots. The test results prove the validity of the instrumental variables.

Panel quantile regression results

Traditional panel data models might obscure the differential impacts of industrial robots at specific pollution levels. To address this issue, this paper uses a panel quantile regression model to empirically analyze the effects of industrial robots across different environmental pollution levels.

Table 9 shows that industrial robots have a negative impact on industrial wastewater discharge. With the increase of the quantile of industrial wastewater discharge, the regression coefficient of industrial robots shows a W-shaped change. Specifically, when the industrial wastewater discharge is in the 0.1 quantile, the regression coefficient of industrial robot is − 0.229, and it passes the 1% significant level. When the industrial wastewater discharge is in the 0.25 quantile, the impact of industrial robots on industrial wastewater discharge is gradually enhanced. Its regression coefficient decreases from − 0.229 to − 0.256. When the industrial wastewater discharge is in the 0.5 quantile, the regression coefficient of industrial robot increases from − 0.256 to − 0.152. When the industrial wastewater discharge is at the 0.75 quantile, the regression coefficient of industrial robot decreases from − 0.152 to − 0.211. When the industrial wastewater discharge is in the 0.9 quantile, the regression coefficient of industrial robot increases from − 0.211 to − 0.188. For every 1% increase in the installation density of industrial robots, the discharge of industrial wastewater is reduced by 0.188%.

When industrial wastewater discharge is at a low percentile, the use of industrial robots can replace traditional production methods, reducing energy waste and wastewater discharge. As industrial wastewater discharge increases, the production process becomes more complex. Industrial robots may be involved in high-pollution, high-emission productions, diminishing the robots’ emission-reducing effects. When industrial wastewater discharge reaches high levels, pressured enterprises seek environmentally friendly production methods and use eco-friendly industrial robots to reduce wastewater discharge. As wastewater discharge continues to rise, enterprises tend to prioritize production efficiency over emission control, weakening the negative impact of industrial robots on wastewater discharge. When wastewater discharge is at a high percentile, enterprises should balance production efficiency and environmental protection needs, by introducing eco-friendly industrial robots to reduce wastewater discharge.

Table 10 shows that with the increase of industrial SO 2 emission quantile level, the negative impact of industrial robots on industrial SO 2 emissions gradually increases. Specifically, when industrial SO 2 emissions are below 0.5 quantile, the impact of industrial robots on industrial SO 2 emissions is not significant. When the industrial SO 2 emissions are above 0.5 quantile, the negative impact of industrial robots on industrial SO 2 emissions gradually appears.

When industrial SO 2 emissions are at a low percentile, the application of industrial robots primarily aims to enhance production efficiency, not to reduce SO 2 emissions. Enterprises should invest in the development of eco-friendly industrial robots, ensuring they are readily available for deployment when a reduction in industrial SO 2 emissions is necessary. As industrial SO 2 emissions continue to rise, both the government and the public pay increasing attention to the issue of SO 2 emissions. To meet stringent environmental standards, enterprises begin to use industrial robots to optimize the production process, reduce reliance on sulfur fuels, and consequently decrease SO 2 emissions. Enterprises should regularly evaluate the emission reduction effectiveness of industrial robots, using the assessment data to upgrade and modify the robots’ emission reduction technologies.

Table 11 shows that with the increase of industrial soot emissions quantile level, the negative impact of industrial robots on industrial soot emissions gradually weakens. Specifically, when industrial soot emissions are below 0.75 quantile, industrial robots have a significant negative impact on industrial soot emissions. This negative effect decreases with the increase of industrial soot emissions. When the industrial soot emissions are above 0.75 quantile, the negative impact of industrial robots on industrial soot emissions gradually disappears.

When industrial soot emissions are at a low percentile, they come from a few sources easily managed by industrial robots. As industrial soot emissions increase, the sources become more diverse and complex, making it harder for industrial robots to control. Even with growing environmental awareness, it may take time to effectively use robots in high-emission production processes and control industrial soot emissions. Enterprises should focus on researching how to better integrate industrial robot technology with production processes that have high soot emission levels. The government should provide financial and technical support to enterprises, assisting them in using industrial robots more effectively for emission reduction.

Figure  9 intuitively reflects the trend of the regression coefficient of industrial robots with the changes of industrial wastewater, industrial SO 2 and industrial soot emissions. Figure  9 a shows that with the increase of industrial wastewater discharge, the regression coefficient of industrial robots shows a W-shaped trend. Figure  9 b shows that with the increase of industrial SO 2 emissions, the regression coefficient of industrial robots gradually decreases. The negative impact of industrial robots on industrial SO 2 emissions is gradually increasing. Figure  9 c shows that with the increase of industrial soot emissions, the regression coefficient of industrial robots shows a gradual increasing trend. The negative impact of industrial robots on industrial soot emissions has gradually weakened. Figure  9 a, b and c confirm the estimation results of Tables 9 , 10 and 11 .

Change of quantile regression coefficient.

Heterogeneity analysis

Regional heterogeneity.

This paper divides China into three regions: Eastern, central and western regions according to geographical location. The estimated results are shown in Table 12 . The industrial robots in eastern region have the greatest negative impact on three pollutants, followed by central region, and the industrial robots in western region have the least negative impact on three pollutants. The use of industrial robots in eastern region far exceeds that in central and western regions. The eastern region is far more than central and western regions in terms of human capital, technological innovation and financial support. Compared with central and western regions, the artificial substitution effect, upgrading of sewage treatment equipment and improvement of energy utilization efficiency brought by industrial robots in eastern region are more obvious.

Time heterogeneity

The development of industrial robots is closely related to policy support 56 . In 2013, the Ministry of Industry and Information Technology issued the “ Guiding Opinions on Promoting the Development of Industrial Robot Industry ”. This document proposes: By 2020, 3 to 5 internationally competitive leading enterprises and 8 to 10 supporting industrial clusters are cultivated. In terms of high-end robots, domestic robots account for about 45% of the market share, which provides policy support for the development of industrial robots. Based on this, this paper divides the total sample into two periods: 2006–2012 and 2013–2019, and analyzes the heterogeneous impact of industrial robots on environmental pollution in different periods. The estimation results are shown in Table 13 . Compared with 2006–2012, the emission reduction effect of industrial robots during 2013–2019 is greater.

The use of industrial robots can effectively reduce environmental pollution, which is consistent with hypothesis 1. This is contrary to the findings of Luan et al. 22 , who believed that the use of industrial robots would exacerbate air pollution. The inconsistency in research conclusions may be due to differences in research focus, sample size, and maturity of industrial robot technology. In terms of research focus, this paper mainly focuses on the role of industrial robots in reducing pollutant emissions during industrial production processes. Their research focuses more on the energy consumption caused by the production and use of industrial robots, which could aggravate environmental pollution. In terms of sample size, the sample size of this paper is 30 provinces in China from 2006 to 2019. These regions share consistency in economic development, industrial policies and environmental regulations. Their sample size is 74 countries from 1993 to 2019. These countries cover different geographical, economic and industrial development stages, affecting the combined effect of robots on environmental pollution. In terms of the maturity of industrial robots, the maturity of industrial robot technology has undergone tremendous changes from 1993 to 2019. In the early stages, industrial robot technology was immature, which might cause environmental pollution. In recent years, industrial robot technology has gradually matured, and its operating characteristics have become environmentally friendly. Their impact on environmental pollution has gradually improved. This paper mainly conducts research on the mature stage of industrial robot technology. Their research covers the transition period from immature to mature industrial robot technology. The primary reason that the use of industrial robots can reduce environmental pollution is: The use of industrial robots has a substitution effect on labor force, which reduces the raw materials needed for manual operation. For example, in the industrial spraying of manufacturing industry, the spraying robot can improve the spraying quality and material utilization rate, thereby reducing the waste of raw materials by manual operation. Zhang et al. 57 argued that energy consumption has been the primary source of environmental pollution. Coal is the main energy in China, and the proportion of clean energy is low 58 . In 2022, clean energy such as natural gas, hydropower, wind power and solar power in China accounts for only 25.9% of the total energy consumption, which can cause serious environmental pollution problems. Industrial robots can promote the use of clean energy in industrial production and the upgrading of energy structure 24 . The reduction of raw materials and the upgrading of energy structure can control pollutant emissions in front-end production. On September 1, 2021, the World Economic Forum (WEF) released the report “ Using Artificial Intelligence to Accelerate Energy Transformation ”. The report points out that industrial robots can upgrade pollution monitoring equipment and sewage equipment, which reduces pollutant emissions in end-of-pipe treatment. Ye et al. 59 also share the same viewpoint.

The use of industrial robots can reduce environmental pollution through green technology innovation, which is consistent with hypothesis 2. Industrial robots promote the integration of knowledge, which helps enterprises to carry out green technology innovation activities. Meanwhile, Jung et al. 60 suggested that industrial robots can lower production costs for companies, allowing them to invest in green technology research. The level of green technology innovation is improved. Green technology innovation reduces environmental pollution through the following three aspects: Firstly, the improvement of energy utilization efficiency. China’s utilization efficiency of traditional energy sources such as coal is not high. The report of “ 2013-Global Energy Industry Efficiency Research ” points out that China’s energy utilization rate is only ranked 74th in the world in 2013. Low energy efficiency brings serious environmental pollution problems 61 . Du et al. 62 found that the innovation of green technologies, such as clean coal, can enhance energy efficiency and decrease environmental pollution. Secondly, the production of green products. Green technology innovation accelerates the green and recyclable process of production, thereby reducing the pollutants generated in production process. Thirdly, the improvement of enterprise competitive advantage. Green technology innovation can enable enterprises to gain greater competitive advantage in green development 63 . The supply of environmentally friendly products increases, which not only meets the green consumption needs of consumers, but also reduces the emission of pollutants.

Industrial robots can reduce environmental pollution by optimizing the structure of employment skills, which is consistent with hypothesis 3. Autor et al. 64 contended that industrial robots would replace conventional manual labor positions, reducing the demand for low-skilled labor. Industrial robots represent the development of numerical intelligence. With the continuous development of digital intelligence, the demand for high-skilled labor in enterprises has increased. Koch et al. 65 demonstrated that the use of industrial robots in Spanish manufacturing firms leads to an increase in the number of skilled workers. In February 2020, the Ministry of Human Resources and Social Security, the State Administration of Market Supervision and the National Bureau of Statistics jointly issues 16 new professions such as intelligent manufacturing engineering and technical personnel, industrial Internet engineering and technical personnel, and virtual reality engineering and technical personnel to the society. These new occupations increase the demand for highly skilled labor. The reduction of low-skilled labor and increase of high-skilled labor optimize the structure of employment skills. The optimization of employment skill structure narrows the wage gap between employees, reducing the communication cost of employees. Employees learn and exchange technology with each other, which not only improves the absorption capacity of clean technology. It also improves the production efficiency of enterprises and increases corporate profits, so that enterprises can use more funds for clean technology research and development, thereby reducing environmental pollution.

Conclusions and policy recommendations

Based on the panel data of 30 provinces in China from 2006 to 2019, this paper uses the panel data model and mediating effect model to empirically test the impact of industrial robots on environmental pollution and its transmission mechanism. This paper uses panel quantile model, regional samples and time samples to further analyze the heterogeneous impact of industrial robots on environmental pollution. The conclusions are as follows: (1) Industrial robots can significantly reduce environmental pollution. For every 1% increase in industrial robots, the emissions of industrial wastewater, industrial SO 2 , and industrial dust and smoke decrease by − 0.242%, − 0.0875%, and − 0.277%. This finding is contrary to that of Luan et al. 22 , who argued that the use of industrial robots exacerbates air pollution. The results of this paper provide a contrasting perspective, highlighting the potential value of industrial robots in mitigating environmental pollution. (2) Industrial robots can reduce environmental pollution by improving green technology innovation level and optimizing employment skills structure. In the impact of industrial robots on industrial wastewater discharge, the mediating effect of green technology innovation accounts for 8.17% of total effect. The mediating effect of employment skill structure accounts for 6.67% of total effect. In the impact of industrial robots on industrial SO 2 emissions, the mediating effect of green technology innovation accounts for 11.8% of total effect. The mediating effect of employment skill structure accounts for 20.66% of total effect. In the impact of industrial robots on industrial soot emissions, the mediating effect of green technology innovation accounts for 3.72% of total effect. The mediating effect of employment skill structure accounts for 15.53% of total effect. While Obobisa et al. 66 and Zhang et al. 67 highlighted the role of green technological innovation in addressing environmental pollution. Chiacchio et al. 68 and Dekle 69 focused on the effects of industrial robots on employment. The mediating impact of technology and employment in the context of robots affecting pollution hasn’t been addressed. Our research provides the first in-depth exploration of this crucial intersection. (3) Under different environmental pollution levels, the impact of industrial robots on environmental pollution is different. Among them, with the increase of industrial wastewater discharge, the impact of industrial robots on industrial wastewater discharge shows a “W-shaped” change. With the increase of industrial SO 2 emissions, the negative impact of industrial robots on industrial SO 2 emissions is gradually increasing. On the contrary, with the increase of industrial soot emissions, the negative impact of industrial robots on industrial soot emissions gradually weakens. (4) Industrial robots in different regions and different periods have heterogeneous effects on environmental pollution. Regarding regional heterogeneity, industrial robots in eastern region have the greatest negative impact on environmental pollution, followed by central region, and western region has the least negative impact on environmental pollution. Regarding time heterogeneity, the negative impact of industrial robots on environmental pollution in 2013–2019 is greater than that in 2006–2012. Chen et al. 5 and Li et al. 24 both examined the overarching impact of industrial robots on environmental pollution. They did not consider the varying effects of robots on pollution across different regions and time periods. Breaking away from the limitations of previous holistic approaches, our study offers scholars a deeper understanding of the diverse environmental effects of industrial robots.

According to the above research conclusions, this paper believes that the government and enterprises can promote emission reduction through industrial robots from the following aspects.

Increase the scale of investment in robot industry and promote the development of robot industry. China’s industrial robot ownership ranks first in the world. Its industrial robot installation density is lower than that of developed countries such as the United States, Japan and South Korea. The Chinese government should give some financial support to robot industry and promote the development of robot industry, so as to effectively reduce environmental pollution. The R&D investment of industrial robots should be increased so that they can play a full role in reducing raw material consumption, improving energy efficiency and sewage treatment capacity.

Give full play to the role of industrial robots in promoting green technology innovation. Industrial robots can reduce environmental pollution through green technology innovation. The role of industrial robots in innovation should be highly valued. The advantages of knowledge integration and data processing of industrial robots should be fully utilized. Meanwhile, the government should support high-polluting enterprises that do not have industrial robots from the aspects of capital, talents and technology, so as to open up the channels for these enterprises to develop and improve clean technology by using industrial robots.

Give full play to the role of industrial robots in optimizing employment skills structure. The use of industrial robots can create jobs with higher skill requirements and increase the demand for highly skilled talents. China is relatively short of talents in the field of emerging technologies. The education department should actively build disciplines related to industrial robots to provide talent support for high-skilled positions. Enterprises can also improve the skill level of the existing labor force through on-the-job training and job competition.

Data availability

The datasets used or analyzed during the current study are available from Yanfang Liu on reasonable request.

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Liu, Y. Impact of industrial robots on environmental pollution: evidence from China. Sci Rep 13 , 20769 (2023). https://doi.org/10.1038/s41598-023-47380-6

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One third of China's urban population at risk of city sinking, new satellite data shows

Land subsidence is overlooked as a hazard in cities, according to scientists from the University of East Anglia (UEA) and Virginia Tech.

Writing in the journal Science, Prof Robert Nicholls of the Tyndall Centre for Climate Change Research at UEA and Prof Manoochehr Shirzaei of Virginia Tech and United Nations University for Water, Environment and Health, Ontario, highlight the importance of a new research paper analysing satellite data that accurately and consistently maps land movement across China.

While they say in their comment article that consistently measuring subsidence is a great achievement, they argue it is only the start of finding solutions. Predicting future subsidence requires models that consider all drivers, including human activities and climate change, and how they might change with time.

The research paper, published in the same issue, considers 82 cities with a collective population of nearly 700 million people. The results show that 45% of the urban areas that were analysed are sinking, with 16% falling at a rate of 10mm a year or more.

Nationally, roughly 270 million urban residents are estimated to be affected, with nearly 70 million experiencing rapid subsidence of 10mm a year or more. Hotspots include Beijing and Tianjin.

Coastal cities such as Tianjin are especially affected as sinking land reinforces climate change and sea-level rise. The sinking of sea defences is one reason why Hurricane Katrina's flooding brought such devastation and death-toll to New Orleans in 2005.

Shanghai -- China's biggest city -- has subsided up to 3m over the past century and continues to subside today. When subsidence is combined with sea-level rise, the urban area in China below sea level could triple in size by 2120, affecting 55 to 128 million residents. This could be catastrophic without a strong societal response.

"Subsidence jeopardises the structural integrity of buildings and critical infrastructure and exacerbates the impacts of climate change in terms of flooding, particularly in coastal cities where it reinforces sea-level rise," said Prof Nicholls, who was not involved in the study, but whose research focusses on sea-level rise, coastal erosion and flooding, and how communities can adapt to these changes.

The subsidence is mainly caused by human action in the cities. Groundwater withdrawal, that lowers the water table is considered the most important driver of subsidence, combined with geology and weight of buildings.

In Osaka and Tokyo, groundwater withdrawal was stopped in the 1970s and city subsidence has ceased or greatly reduced showing this is an effective mitigation strategy. Traffic vibration and tunnelling is potentially also a local contributing factor -- Beijing has sinking of 45mm a year near subways and highways. Natural upward or downward land movement also occurs but is generally much smaller than human induced changes.

While human-induced subsidence was known in China before this study, Profs Nicholls and Shirzaei say these new results reinforce the need for a national response. This problem happens in susceptible cities outside China and is a widespread problem across the world.

They call for the research community to move from measurement to understanding implications and supporting responses. The new satellite measurements are delivering new detailed subsidence data but the methods to use this information to work with city planners to address these problems needs much more development. Affected coastal cities in China and more widely need particular attention.

"Many cities and areas worldwide are developing strategies for managing the risks of climate change and sea-level rise," said Prof Nicholls. "We need to learn from this experience to also address the threat of subsidence which is more common than currently recognised."

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