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Greenhouse Effect: Greenhouse Gases and Their Impact on Global Warming

The Greenhouse effect is a leading factor in keeping the Earth warm because it keeps some of the planet's heat that would otherwise escape from the atmosphere out to space. The study report on the Greenhouse gases and their impact on Global warming. Without the greenhouse effect the Earth's average global temperature would be much colder and life on Earth as we know it would be impossible. Greenhouse gases include water vapor, CO 2 , methane, nitrous oxide (N 2 O) and other gases. Carbon dioxide (CO 2) and other greenhouse gases turn like a blanket, gripping Infra-Red radiation Mini-review Article

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International Journal of Environmental Monitoring and Analysis

ahmad el zein

Dr. Rajen Barua

Our planet Earth is facing a serious problem called Global Warming; the Earth's surface temperature is getting warmer and warmer, which is changing the Earth's climate everywhere with devastating affects on weather patterns across globe. It has a range of potential ecological, physical and health impacts, including extreme weather events (such as floods, droughts, storms, and heatwaves); melting of the ice caps causing sea-level rise; altered crop growth; and disrupted water systems and others. The climate change that we are witnessing is one of the greatest challenge facing humanity today. This may also put out many species at high risk of extinction, threatening the collapse of marine food chain and ecosystem. Shortage of food and water may trigger massive movements of people leading to migration, conflict and famine. Scientists generally agree that unless we address this problem now the situation will get worse and eventually will threaten the very life on earth. Scientist also generally agree that one major contributor to this global warming is the higher concentration of the greenhouse gas carbon dioxide CO2 in the atmosphere. This brings us to the important and interesting climatic phenomenon called the Greenhouse effect. Normally the Earth's atmosphere is very cold, so cold that normally life on Earth is not feasible. Today, it is possible for us to live on the Earth only because of what is called this Greenhouse effect where the so-called greenhouse gases. (GHG:water vapor, carbon dioxide, methane, nitrous oxide, and ozone.) in the atmosphere trap some of the Sun's radiation and radiate these back to the Earth. The process is called the Greenhouse effect, a term taken from the operation of the greenhouses. However, this is somewhat a misnomer; a greenhouse is not primarily warmed by the Greenhouse effect. Anyhow, our Earth is one of the few planets in our Solar system where this Greenhouse effect occurs. Other planets where this Greenhouse effect occur are Venus, Mars and Titan. Without this Greenhouse effect, the average temperature of the Earth's surface would have been very cold, about −18 °C (0 °F) rather than the present average of 15 °C (59 °F) which is comfortable for human life. This present average of 15 °C (59 °F) may be called the normal temperature of the Earth for human civilization. The Greenhouse effect works by preventing absorbed heat from leaving the earth through radiative transfer. Normally, the Earth receives energy from the Sun in the form of ultraviolet, visible, and near-infrared radiation. About 26% of the incoming solar energy is reflected back to space by the atmosphere while about 19% is absorbed by the atmosphere. Most of the remaining 55% energy is absorbed by the surface of the Earth and some are radiated back. Because the Earth's surface is colder than the Sun, it radiates back infrared light at wavelengths that are much longer than the wavelengths that were received. The atmosphere in turn radiates back some of this energy downwards depending on the strength of the greenhouse gases. This leads to a higher equilibrium temperature of the Earth surface than if the atmosphere were absent. The strength of the Greenhouse effect-how much extra energy it directs toward the Earth's surface-depends on how many greenhouse gas (GHG) molecules there are in the atmosphere. When GHG concentrations are high, they absorb a greater percentage of the Earth's infrared energy emissions. This means that more energy gets reemitted back toward the Earth's surface, raising its average surface temperature. We can think of the atmosphere as a heat-trapping grid surrounding the Earth. Water vapor, Carbon dioxide and other GHG are the solid bars of the grid while non-greenhouse1 gases (nitrogen and oxygen) are the open spaces between the grid bars. When infrared energy hits an open space of the grid, it escapes into outer space and dissipates; but when it hits a solid bar, the bar heats up and reradiates some portion of the energy back toward the Earth, raising its overall temperature. The more GHG molecules there are in the atmosphere, the more wide are the bars of the grid, shrinking the open spaces and making it harder for infrared energy to escape into space. The tighter the grid, the more energy it absorbs, and the hotter the Earth gets. We need to note that CO2 is not the biggest contributor of the GHG. Water vapor in the form of clouds is the greatest contributor with (32-76%). of these GHG. However, while we humans don't have any control on the natural process of formation of the water vapors (clouds) which are formed based of the surface temperature of the oceans, we humans have control in formation of the next biggest contributor of the GHG, the CO2 which contribute as much as (9-26%) of the GHG. Carbon dioxides also essential for life-animals exhale it, plants absorb and sequester it. There is a natural carbon cycle in the Earth's atmosphere. Carbon is absorbed from the atmosphere when photosynthesizing organisms such as plants, algae, and some kinds of bacteria pull it out of the air and combine it with water to form carbohydrates. It is returned to the atmosphere as CO2 when humans and other animals breathe it out, or when plants die and decompose. For the past thousands of years, this balance of intake and emission has kept the amount of carbon dioxide CO2 in the atmosphere constant. But in modern times, by burning an ever-increasing amount of fossil fuels, we are putting our finger on the scale, tipping the balance toward more CO2 emission. When we mine fossil fuels and burn them for energy, we are

Integrated Science & Technology Program

Vincent Moron

Energy & Environment

Antero Ollila

https://www.ijrrjournal.com/IJRR_Vol.4_Issue.3_March2017/Abstract_IJRR004.html

International Journal of Research & Review (IJRR)

Many investigators have expressed urgent need for pollution control measures which are effective and acceptable. Many harmful gases cause different health problems to human beings. Gases such as carbon dioxide, sulphur dioxide and hydrogen sulphide can be removed from exhaust gases by different methods. Greenhouse gases allow shortwave radiations to pass through the earth's atmosphere and heat the land and oceans. The long wave radiation emitted from earth surface cannot pass through atmosphere due to these greenhouse gases. This phenomenon leads to greenhouse effect. Vehicular and industrial pollution is main contributor to the greenhouse gases and global warming. Water vapor plays a very important role in energy transport by convection. Combination of solar radioactive heating and the strength of the greenhouse effect determine the surface temperature of a planet.

Amir Samimi

Tellus A: Dynamic Meteorology and Oceanography

Syukuro Manabe

Physical Science International Journal

The greenhouse effect concept explains the Earth’s elevated temperature. The IPCC endorses the anthropogenic global warming theory, and it assumes that the greenhouse (GH) effect is due to the longwave (LW) absorption by GH gases and clouds. The IPCC’s GH definition lets to understand that the LW absorption is responsible for the downward radiation to the surface. According to the energy laws, it is not possible that the LW absorption of 155.6 Wm-2 by the GH gases could re-emit downward LW radiation of 345.6 Wm-2 on the Earth’s surface. When the shortwave (SW) absorption is decreased from this total LW radiation, the rest of the radiation is 270.6 Wm-2. This LW radiation downward is the imminent cause for the GH effect increasing the surface temperature by the 33°C. It includes LW absorption by the GH gases and clouds in the atmosphere and the latent and sensible heating effects. Without the latent and sensible heating impacts in the atmosphere, the downward LW radiation could not c...

We are entering a new era of carbon and nitrogenous waste management. There is one particular biochemical phenomena of interest in this ‘tug-of-war’ for preserving life on Earth as we know it: the greenhouse effect. The greenhouse effect is a process by which thermal radiation from a planetary surface is absorbed by atmospheric greenhouse gases (carbon dioxide, methane, water vapour, nitrous oxide), and is re-radiated in all directions. It is not a new phenomena.

Scientists are still debating the reasons for “global warming”. The author questions the validity of the calculations for the models published by the Intergovernmental Panel on Climate Change (IPCC) and especially the future scenarios. Through spectral calculations, the author finds that water vapour accounts for approximately 87% of the greenhouse (GH) effect and only 10% of CO2. A doubling of the present level of CO2 would increase the global temperature by only 0.51 °C without water feedback. The IPCC claims that a temperature increase of 0.76 °C for 2005 was caused in part by water (about 50%), because relative humidity (RH) stays constant in their model. The calculations prove that CO2 would have increased the temperature by only 0.2 °C since 1750 and that the measured decrease in water since 1948 has compensated for this increase. This study has also produced results indicating a negative feedback for relative humidity. The simulations of this study propose that the IPCC’s model atmospheres could be approximately 50% too dry.

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RELATED PAPERS

Dinesh Sharma

Abrupt reduction in shipping emission as an inadvertent geoengineering termination shock produces substantial radiative warming

Tianle Yuan ORCID: orcid.org/0000-0002-2187-3017 1 , 2 ,
Hua Song ORCID: orcid.org/0000-0003-2499-0566 2 , 3 ,
Lazaros Oreopoulos ORCID: orcid.org/0000-0001-6061-6905 2 ,
Robert Wood ORCID: orcid.org/0000-0002-1401-3828 4 ,
Huisheng Bian 1 , 2 ,
Katherine Breen 2 , 5 ,
Mian Chin ORCID: orcid.org/0000-0003-3384-8115 2 ,
Hongbin Yu 2 ,
Donifan Barahona 2 ,
Kerry Meyer 2 &
Steven Platnick 2

Communications Earth & Environment volume 5 , Article number: 281 ( 2024 ) Cite this article

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Atmospheric chemistry
Climate and Earth system modelling

Human activities affect the Earth’s climate through modifying the composition of the atmosphere, which then creates radiative forcing that drives climate change. The warming effect of anthropogenic greenhouse gases has been partially balanced by the cooling effect of anthropogenic aerosols. In 2020, fuel regulations abruptly reduced the emission of sulfur dioxide from international shipping by about 80% and created an inadvertent geoengineering termination shock with global impact. Here we estimate the regulation leads to a radiative forcing of $+0.2\pm 0.11$ Wm −2 averaged over the global ocean. The amount of radiative forcing could lead to a doubling (or more) of the warming rate in the 2020 s compared with the rate since 1980 with strong spatiotemporal heterogeneity. The warming effect is consistent with the recent observed strong warming in 2023 and expected to make the 2020 s anomalously warm. The forcing is equivalent in magnitude to 80% of the measured increase in planetary heat uptake since 2020. The radiative forcing also has strong hemispheric contrast, which has important implications for precipitation pattern changes. Our result suggests marine cloud brightening may be a viable geoengineering method in temporarily cooling the climate that has its unique challenges due to inherent spatiotemporal heterogeneity.

Thermosteric and dynamic sea level under solar geoengineering

International shipping in a world below 2 °C

The influence of emissions scenarios on future Antarctic ice loss is unlikely to emerge this century

Introduction.

The Earth’s atmosphere has warmed because of human activities increasing the concentration of greenhouse gasses that trap thermal radiative energy in the climate system, creating a positive climate forcing. Human activities have also increased the concentration of aerosol particles that can affect the amount of reflected solar radiation back to space either directly or indirectly by interacting with clouds, which has an overall cooling effect on the climate 1 . The magnitude of the aerosol cooling effect has significant implications for estimating how sensitive our climate is to greenhouse gas forcing and the amount of expected future warming for a given increase of greenhouse gas concentrations 2 . The effectiveness of anthropogenic aerosols in cooling the climate also has direct implications for solar radiation modification geoengineering schemes 3 , 4 . Such methods aim to produce temporary cooling of the climate through enhanced reflection of solar radiation to space. They are not solutions to greenhouse gas induced global warming and have uncertain and complex additional consequences besides the intended short-term cooling effect 4 , 5 , 6 , 7 .

Marine cloud brightening (MCB) is a type of solar radiation modification scheme where marine low clouds are seeded with aerosols to become brighter 8 , 9 . Examples of small scale, opportunistic MCB experiments were discovered in early satellite observations of ship-tracks, linear features of brighter oceanic clouds because of ship-emitted aerosols 10 , 11 . The addition of aerosols from ship emissions results in more cloud droplets, leading to more reflective clouds for a given amount of total In-cloud liquid water, or liquid water path (LWP) 12 . More recent studies show that aerosols can also change LWP and total cloud fraction (CF), which also greatly affect the amount of solar radiation reflected by clouds 2 , 13 , 14 , 15 , 16 .

Aerosols sourced from global shipping industry affect clouds and we can view the shipping emission as a long-running inadvertent MCB experiment. On January 1, 2020, new International Maritime Organization (IMO) regulations on the sulfur content of international shipping fuel took effect. The IMO 2020 regulation (IMO2020) reduced the maximum sulfur content from 3.5% to 0.5% 17 . While IMO2020 is intended to benefit public health by decreasing aerosol loading, this decrease in aerosols can temporarily accelerate global warming by dimming clouds across the global oceans. IMO2020 took effect in a short period of time and likely has global impact. IMO2020 effectively represents a termination shock for the inadvertent geoengineering experiment through a reverse MCB, i.e., marine cloud dimming through reducing cloud droplet number concentration (N d ) (Fig. 1 ). Observations of ship-tracks suggest that IMO2020 has reduced the occurrence and modified the properties of ship-tracks across global oceans, demonstrating that a regulation intended to reduce pollution had collateral effects on cloud microphysics 18 . Analyses of remote sensing data have shown evidence of cloud dimming in the South Atlantic shipping lane 19 . Outside the South Atlantic, the effect of IMO2020 does not have a distinct spatial structure 18 , 19 , which makes direct observation of the impact more challenging.

A simulated annual mean aerosol optical depth change induced by IMO2020 using NASA GOES-GOCART. B the ratio of aerosol optical depth changes between that induced by IMO2020 and that between 1750 and 2005 2 . C map of simulated annual mean N d change due to IMO2020. D ) same as B , but for N d change.

Here we combine satellite observations and a chemical transport model to quantify the radiative forcing of the inadvertent geoengineering event induced by IMO2020 and estimate its climate impacts. We simulate the impact of IMO2020 on maritime aerosol concentrations with the NASA GEOS-GOCART model. Figure 1 shows the modeled reduction in aerosol optical depth due to decreased SO 2 emission from the international shipping industry. The AOD reduction reaches peak values of around 0.01 in the South China Sea and Eastern North Atlantic off the coasts of Western Europe. In the South Atlantic the regulations create AOD reductions that follow the shape of shipping routes. We then calculate the ratio between the AOD change due to IMO2020 and that between pre-industrial and present day. Over most of the ocean, the ratio is smaller than 10% because of sparse shipping outside the major shipping routes. Over the North Pacific and North Atlantic, on the other hand, it can exceed 10% and reaches 25% in the Norwegian Sea and off the western European and northwestern African coasts. In these regions, the total anthropogenic aerosol concentration is relatively low because of declining emissions of aerosols and their precursors since the 1980s, making ship-emitted aerosols an important component of the anthropogenic maritime aerosols. The IMO2020 is therefore effective in reducing total aerosol loading for these regions. The impact of IMO2020 on the cloud droplet number concentration (N d ) of low-level maritime clouds as shown in Fig. 1C (see Methods). Globally, IMO2020 leads to a modest reduction of 0.5 cm −3 in mean modeled N d . Regionally, however, the reduction is more pronounced. The strongest reduction occurs in the North Atlantic, the Caribbeans and the South China Sea, reaching 3 cm −3 . These are regions with the busiest shipping lanes and thus strongest reduction of ship emissions. The reduction in the South Atlantic shows the most well-defined shipping lane shapes likely due to the unique circulation pattern in this region 18 , 20 . Figure 1D shows the ratio between IMO2020 induced Nd decrease and estimated Nd difference between preindustrial and present day. The ratio is small over the major outflow areas downwind of major continental sources, but becomes substantially larger in more remote oceans, reaching 30%. In the tropical North Atlantic, IMO2020 induced change in Nd can be more than 50% of the total anthropogenic change.

We combine N d changes due to IMO2020 with satellite observations to estimate the forcing introduced by the inadvertent geoengineering event 21 . We consider both the Twomey effect and the effects of cloud liquid water path (LWP) and cloud fraction adjustments to N d (see Methods section). The LWP and cloud fraction adjustments follow the functional forms derived from a large sample of ship-tracks 21 that depend on the background cloud N d , sea surface temperature (SST), estimated inversion strength, and background low cloud fraction (see Methods). Figure 2 shows the pattern of annual mean of forcing resulting from N d decrease due to IMO2020 averaged over different LWP and cloud fraction adjustment functional forms. The total forcing is + $0.2\pm 0.11$ Wm −2 averaged over the global ocean with the Twomey effect contributing 40%, the LWP adjustment being near neutral, and the cloud fraction adjustment contributing 60%. The positive radiative forcing has strong regional variations. The North Atlantic experiences the strongest radiative forcing peaking around 1.4Wm −2 and whose basin-wide mean is around 0.56Wm −2 . Weaker but still notable radiative forcing is seen in the North Pacific and the South Atlantic. This ordering is consistent with the amount of ship traffic and low cloud fraction in these regions. Our estimate of radiative forcing from IMO2020 is well within the range of estimates of the total forcing from shipping emissions in the literature 22 , 23 , 24 , 25 . We also compare our estimate with that from a recent observational study in the core shipping lane in the South Atlantic that used a different approach 19 . The two completely independent approaches yield very similar radiative forcing in the core shipping lane (supporting online material, SOM), which serves as a cross-validation. Similar global forcing, i.e., on the order of 0.1Wm −2 , is reported by multiple modeling groups 26 .

The spatial patterns of three components of forcing from cloud adjustments: A the Twomey effect, B LWP adjustment, and C cloud fraction adjustment.

Using an energy balance model 27 , we calculate the expected amount of transient temperature increase due to warming resulting from IMO2020. For simplicity, we ignore the heat uptake by the deep ocean during the short-term, i.e. O(10) years. 0.2 W m −2 translates to around 0.16 K of warming with a timescale of 7 years. It is equivelant to 0.24 K/decade, which is more than double the average warming rate since 1880 and 20% higher than the mean warming rate since 1980, linear trend of 0.19 K/decade. We also calculated the lower and upper bounds of the forcing and corresponding expected warming (Fig. 3 ). The IMO2020 is expected to provide a substantial boost to the warming rate of global mean temperature in the 2020 s. The rate of warming is expected to ramp up quickly from 2020 and asymptotes to the longer-term trend line at the end of 2020 27 . The 2023 record warmth is within the ranges of our expected trajectory. The magnitude of IMO2020 induced warming means that the observed strong warming in 2023 will be a new norm in the 2020 s. The mean temperature anomaly of the 2020 s will be 0.3 K higher than that of the 2010s. Regionally, the warming effect from IMO2020 on SST is harder to estimate since basin-wide SST changes can be affected by variations in factors like other aerosol concentration, ocean circulation, and air-sea interactions. However, the strong geographical variations in the forcing suggest the impact of IMO2020 on SST may have significant variation among ocean basins. For example, the North Atlantic SST may be disproportionally warmed more by the IMO2020 given the radiative forcing is more than three times the global average, which is likely a contributing factor to the pronounced warming of the North Atlantic SST in recent years 28 . A more robust quantitative estimate of the contribution of IMO2020 to regional SST warming requires coupled global climate models that have good representation of aerosol indirect effects.

The trend line is dashed. The expected warming trajectory from the combination of the linear trend and the calculated warming effect from IMO 2020 shock based on the energy balance model. The upper and lower bounds of the expected warming are shown in shades. The baseline period for temperature anomaly is between 1951 and 1980.

The IMO2020-induced radiative forcing exhibits considerable seasonal variations. This is evident in the North Atlantic where the IMO2020 produced the strongest forcing. Figure 4 shows the monthly mean time series of forcing and its three components. We use a simple functional form for cloud adjustments that only depends on background N d to illustrate the point. The total forcing varies between 0.19Wm −2 and 0.38Wm −2 , a 100% relative change. The seasonal variation of incoming solar radiation is the dominant driver for this (SOM). But seasonal variations of background CF, N d , and ΔN d due to IMO2020 also contribute as they affect the magnitude of the Twomey effect and macrophysical (LWP and CF) cloud adjustments. We estimate the contribution from each variable after removing the seasonal change in solar insolation, and report the results in Fig. 4B–D (see Methods). ΔN d induced by IMO2020 is the strongest contributor. Its variations can affect the forcing by more than 30% in some months such as Jan, Apr, and Dec. Its impact on LWP and CF adjustments contributes equally to the total radiative forcing. The seasonal variation of background N d is also an important factor (Fig. 4C ). Background CF also meaningfully contributes to the seasonal variations through mostly affecting the Twomey effect (Fig. 4D ).

A The areal mean of forcing from IMO2020 in the North Atlantic (0 o −80 o W, 0 o ~ 60 o N) and its break down in three components. B – D sensitivity tests to gauge the impacts of seasonal variations in ΔN d , background N d , and cloud fraction, respectively. In each test, we use an annual mean map instead of seasonally changing fields to calculate the radiative forcing and plot their difference from the baseline. Details in Methods section.

We compare the radiative forcing due to IMO2020 and its effect on radiative energy balance with observed changes in relevant quantities. The comparison does not prove causality but provides a context to assess the impact of IMO2020. The low cloud dimming forcing of 0.2 Wm −2 from the IMO2020 represents a strong temporary shock to the net planetary heat uptake (Fig. 5A ) that has been increasing at a rate of ~0.05 Wm −2 /yr 29 in measurements. The net planetary heat uptake has increased by 0.25 Wm −2 since 2020, making the 0.2 Wm −2 due to IMO2020 nearly 80% of the total increase. The long-term trend of CERES TOA net radiation is 0.46 Wm −2 /decade while it changes to 0.67 Wm −2 /decade since IMO2020 took effect. The difference is 0.21 Wm −2 that is consistent with our estimated forcing. However, the record since 2020 is too short to ascertain the impact of IMO2020 on the long-term trend of the energy balance given its large interannual variations. The IMO2020 effect also has an asymmetric impact on aerosol loading in the northern and southern hemispheres because of higher baseline ship emissions in the northern hemisphere. This creates interhemispheric contrast in the resulting radiative forcing, which has important implications for deliberate geoengineering schemes because interhemispheric forcing contrast can create significant perturbations in precipitation patterns 6 . We calculate the interhemispheric contrast in IMO2020 induced warming effect to be around 0.22 Wm −2 , with the northern hemisphere at 0.32 Wm −2 and the southern hemisphere at 0.1 Wm −2 . The 0.22 Wm −2 contrast is substantial when compared with recent measured changes in the interhemispheric contrast in absorbed solar radiation. Figure 5B, C shows measured time series of top-of-atmosphere (TOA) absorbed solar radiation of both hemispheres and their contrast, respectively. Since IMO2020 took effect, the northern hemisphere (NH) absorbed solar radiation has increased by 0.5 Wm −2 from a plateau between 2017 and 2020 while the southern hemisphere (SH) increased at a much slower rate. The low cloud dimming effect of IMO2020 represents around 60% of increase in NH absorbed solar radiation. The interhemispheric contrast in absorbed solar radiation has increased by ~0.2 Wm −2 based on measurements, one of the highest rates of increase during the whole record, which is almost the same as that induced by low cloud dimming effect of IMO2020. Another rapid increase period is associated with a phase shift in Pacific Decadal Oscillation (PDO) starting 2014/2015 followed by a strong El-Nino event 29 . The PDO entered a negative phase in 2020, which would favor a further decrease in the contrast rather than the observed increase. It is worth noting that in addition to modes of ocean variability such as PDO and El-Nino Southern Oscillation may contribute to variations in these quantities 6 .

A the planetary heat uptake; B trailing 48-month mean of absorbed solar radiation for both hemispheres. The 48-month mean is applied to remove high-frequency noise. C Time series of Interhemispheric contrast in absorbed solar radiation. The vertical dotted line marks the Jan 2020—details in the Methods section.

The combination of modeled $\varDelta {N}_{d}$ and observed relationship for LWP and cloud fraction adjustments show that IMO2020 as a termination shock for the inadvertent geoengineering experiment of shipping emissions has had a non-trivial warming effect on the climate. The National Academy of Sciences, Engineering, and Medicines 4 recommended the impact of any outdoor solar radiation management experiment on global mean temperature to be within 1 × 10 −7 K. The forcing magnitude of this inadvertent shock has exceeded this limit by a large margin. However, it does suggest that MCB is a viable solar radiation modification scheme in temporarily slowing the rate of climate warming. Our analysis also points to strong spatiotemporal heterogeneities in the forcing produced by the event. Such heterogeneities need to be considered in any MCB scheme to minimize their potential undesired impacts on regional climate in addition to the desired slowing of climate warming rate. Important part of the heterogeneity exists because of background low cloud distribution and its spatiotemporal variability creating an interhemispheric contrast of radiative forcing having similar magnitude as the global mean radiative forcing. Understanding this contrast is important because to achieve the goal of substantially slowing down the warming rate or limit the maximum warming to be within 1.5 30 , much larger forcing than that of IMO2020, but of the opposite sign, would be needed. As a result, the interhemispheric contrast needs to be minimized to avoid substantial perturbations to regional monsoons and other precipitation patterns. It should be noted that the forcing due to IMO2020 will take time for it to be directly detectable at the global scale in the observation records, but regionally, e.g., in the North Atlantic, its impact may be detectable sooner. Regional radiative forcing is already detectable in the Southeast Atlantic shipping lane 19 . Finally, an important open question for policy makers to consider is the trade-off between the benefits of better air quality and the potential cost of additional warming as different parts of the world have reduced and are going to reduce aerosol pollution 31 , 32 . The trade-off consideration is also relevant for deliberate geoengineering schemes to select the right properties of emitted aerosols.

There are several sources of uncertainties in our estimate of the radiative forcing via cloud dimming induced by IMO2020. A key source is the magnitude of N d change. Here the N d change is modeled with a chemical transport model and not constrained with actual observations. The annual mean change in N d (0.5 cm −3 ) is small compared to the background N d (28 cm −3 ) and its variability. Counterfactual analyses of satellite-based N d changes due to ship emissions in the South Atlantic may provide useful regional constraint on $\varDelta {N}_{d}$ once there are additional years of observations 19 . Although adjustments of LWP and cloud fraction are robust given the large number of samples, they have their own limitations as detailed in previous studies 14 , 33 , 34 , 35 , 36 . One way to gauge the possible range of uncertainty for our forcing estimate is to compare ours with that from Diamond (2023) 19 in the South Atlantic (SOM). In the core shipping lane, the forcing is estimated to peak around 0.5Wm −2 , the Twomey effect being the dominant factor in this region (see Fig. 2 ), in our analysis in excellent agreement with theirs 19 . The inadvertent nature of IMO2020 means that the ratio between radiative forcing and changes in aerosol mass is not optimized. Here we report 0.2Wm −2 for around 3.7 Tg of S reduction, which is much less efficient than a more optimized scheme due to factors such as emitted aerosol size distribution and the spatial distribution of emission changes 9 . Finally, our analysis does not consider feedback processes. The additional warming of the ocean can induce positive feedbacks from low clouds 37 , 38 , which can only be addressed in a coupled climate model.

In summary, IMO2020 represents a termination shock for the inadvertent geoengineering by global ship emissions through a reverse MCB and produces a positive forcing of + 0.2 ± 0.11 Wm −2 . It is expected to provide strong additional warming rate this decade, more than doubling the long-term mean warming rate. The forcing has pronounced spatiotemporal heterogeneity. The IMO2020 effect also contributes to a strong temporary increase to the planetary heat uptake through cloud dimming, and it is around 80% of the measured increase in interhemispheric contrast of absorbed solar radiation since 2020. Our results offer useful guidance for MCB and aerosol-cloud interaction research.

GEOS-GOCART simulation of IMO impact on aerosol fields

All simulation experiments were run with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol module 39 , 40 in NASA Goddard Earth Observing System (GEOS) Earth System Model (ESM). The GEOS model has a one-moment cloud microphysics module and a rapid radiation transfer model for general circulation models (RRTMG). Sea surface temperature (SST) for the atmospheric dynamic circulation is provided by the GEOS Atmospheric Data Assimilation System (ADAS) that incorporates satellite and in situ SST observations. The model is run in the replay mode using meteorological fields from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) reanalysis 41 . “Replay” mode sets the model dynamic state (winds, pressure, and temperature) every 6 h to the balanced states provided by the Meteorological Reanalysis Field of the Modern Research and Applications Reanalysis Version 2 (MERRA-2). We run GEOS at a global horizontal resolution of approximately 50 km on a cubic sphere grid and 72 vertical layers from the surface to 0.01 hPa. The time step for dynamic calculation is 450 s. The temporal resolution of the radiation is 1 h. All experiments run from 201910 to 202012, with the first three months as the spin up period. We use monthly results in our estimation of forcing.

We have two set of experiments: business as usual (BAU) and Covid impact (Covid) emissions. The BAU used anthropogenic emissions of aerosols and precursor gases from the Community Emission Data System (CEDS) 42 but repeat the 2019 emissions for 2020. The dataset includes nine emission sectors (energy, industry, road transportation, residential, waste, agriculture, solvent, shipping, and air traffic). Biomass burning emissions were taken from the GSFC-developed Quick Fire Emission Dataset (QFED) 43 . Volcanic emissions come from the dataset that is based on the satellite volcanic SO2 observations from the OMI instrument on board the Aura satellite. Biogenic emissions were calculated with the Model of Emissions of Gases and Aerosols from Nature (MEGAN) that is embedded in GEOS model. The wind-driven emissions, such as dust and sea salt, were calculated on-line. Time varying greenhouse gases, such as CO 2 , CH 4 , N 2 O and ozone-depleting substances, were provided by CMIP5 project.

The second set of experiments (Covid) adjusted BAU anthropogenic emission to reflect the impact of Covid. Using mobility data from Google and Apple 44 , daily scale factors in 2020 were derived on sector bases for ten species including important aerosols and their precursors. Because of the rapidly changing emissions due to various timing and strength of lockdown measures, daily scale factors were provided not only to scale down emission amounts but also to move emissions from monthly to daily. The Covid adjusted daily anthropogenic emissions were generated by applying these scale factors to CEDS 2019 monthly emission.

A summary of S emissions under different scenarios is provided in Table S1 . For each set of experiments, there are three scenarios: full ship emissions, reduced ship emissions using the IMO2020 standards, and no ship emission of S. Other emissions are kept the same. We take the difference in aerosol loading between with full ship emissions of SO 2 and with reduction due to IMO2020 as the impact of IMO2020. The difference in aerosol loading is translated into N d changes with method in the following subsection.

Deep learning-based N d

The operational version of NASA’s Global Earth Observing System (GEOS) runs single moment cloud and aerosol microphysical schemes. They do not predict cloud condensation nuclei (CCN) and cloud droplet number concentrations (N d ). We estimate N d using a diagnostic deep learning-based approach, involving the usage of two neural network (NN) parameterizations. The first NN (termed MAMnet) is an emulator for the Modal Aerosol Module, which takes bulk aerosol mass for 5 externally-mixed species (sulfates, sea salt, dust, black carbon, and organics) and the atmospheric state (temperature, pressure) as input, and predicts the number concentration and composition for 7 internally-mixed lognormal modes (accumulation, aitken, coarse/fine dust, coarse/fine sea salt, primary carbon matter). MAMnet was trained on 5 years of data from a GEOS simulation implementing the MAM7 aerosol module, and validated against ground observations. The CCN concentration at a given supersatureation can be readily estimated using the 7-modal size distribution and composition 45 . A second NN model (Wnet) is used to estimate N d . Estimation of N d requires the characteristic vertical wind velocity (W) at the scale of individual parcels, typically proportional to its subgrid-scale standard deviation (σ W ). Wnet takes the atmospheric state, as well as coarse metrics of turbulence (Richardson number and total scalar diffusivity) as inputs and predicts σ W for each grid cell. Wnet was trained on 2 years of a global, non-hydrostatic, storm-resolving simulation of the GEOS model and physically constrained by ground-based observations of σ W from around the world using a novel generative approach 46 . The aerosol size distribution predicted from MAMnet as well as σ W are used to predict N d using the Abdul-Razzak and Ghan scheme 47 . Our NN-based method emphasizes observations and conservation of known physics during the development of the NNs and ensures a robust prediction of CCN and N d .

Calculating aerosol indirect forcing

We use the same methodology reported in Yuan et al. 21 . We consider the Twomey effect and effects of cloud fraction and LWP adjustments. Without considering aerosol effects on cloud fractions, cloud albedo sensitivity to aerosols can be taken as the sum of the Twomey effect and aerosol induced LWP adjustments:

where S is the susceptibility of cloud albedo (A c ) to droplet number concentration ${N}_{d}$ 16 .

We then have

Aerosol indirect forcing from the Twomey effect and LWP adjustment is therefore:

To consider the effect of Cf adjustment due to aerosols, we consider the sensitivity of scene albedo (A) to N d . $A={A}_{{ac}}{{Cf}}_{{total}}+{A}_{s}(1-{{Cf}}_{{total}})$ . We have:

where A is the scene albedo, i.e., including both cloudy, A ac, and clear, A s , parts; ${{Cf}}_{{total}}$ and ${Cf}$ are all cloud and low cloud fraction obtained from the MYD08_M3 data; A s is the surface albedo, derived from the CERES EBAF-TOA data 48 ; $1-{{Cf}}_{{high}}$ is used to take into account of effect of overlap on Cf adjustment. We assume a maximum overlap between high and low clouds. We assume minimum aerosol effects on high clouds. The estimation is done at monthly time scales.

CF and LWP adjustments, $\frac{{dCf}}{d{N}_{d}}$ and $\frac{d{{{{{\mathrm{ln}}}}}}{LWP}}{{dln}{N}_{d}}$ , are derived from our previous work based on large number of ship-track samples 21 . The assumption is that clouds with similar properties respond similarly to addition of aerosols and ship-tracks detected under diverse background cloud conditions can be used to effectively derive these adjustments. Our results are based on the responses from observed ship-track sampled under diverse set of environmental conditions, which allows us to derive robust cloud adjustments based on numerous ship-track samples 21 . There are a few assumptions and approximations as noted in our previous study 21 and we reiterate them here. We used SW downwelling at the surface from CERES instead of SW downwelling at the cloud top, which underestimates the total forcing since SW downwelling at the cloud top is larger. The LWP and Cf adjustments can be sensitive to more variables that those considered here. We assume the derived $\frac{{dCf}}{d{N}_{d}}$ and $\frac{d{{{{{\mathrm{ln}}}}}}{LWP}}{{dln}{N}_{d}}$ and their dependence on background variables apply to regions that have less ship-track samples. Also, potential semi-direct effects due to absorbing aerosols from ship-emissions are not explicitly addressed in this study since we do not have enough observations.

The cloud adjustments used here can depend on the background cloud N d , SST, EIS, and background N d and thus they have spatiotemporal variations due to background changes. The dependence of cloud adjustments can also be parameterized with one or more variables. The N d -only functional form provides a lower bound on the forcing calculation 21 and we explore different 2-variable combinations to provide a range of estimates. We combine the cloud adjustments with the simulated $\varDelta {N}_{d}$ due to IMO2020 and observations of clouds and other parameters in 2020 to calculate its forcing. We report the mean forcing from all five functional forms of cloud adjustments as well as the standard deviation. We also report the warming effect expected from both the upper and lower bounds in Fig. 3 . Due to the N d -dependent nature of cloud adjustments, the same $\varDelta {N}_{d}$ can result in different magnitude of radiative forcing 21 , 49 .

There is systematic difference between GEOS-modeled and MODIS observed climatology of N d . At each grid point, we calculate the ratio between modeled and observed N d based on monthly data and scale the modeled $\varDelta {N}_{d}$ with the ratio before using above equations to calculate the forcing. The global mean values change by 10% between scaled and non-scaled $\varDelta {N}_{d}$ , all coming from the CF adjustment since the LWP adjustment and the Twomey effect depend on $\varDelta {N}_{d}/{N}_{d}$ that does not change with scaling. Regionally, the difference can be as large as 30%, e.g., in the Southeast Atlantic.

The CERES EBAF-TOA data 48 provides monthly and climatological averages of observed top-of-atmosphere and computed cloud radiative effect and absorbed solar radiation. The top-of-atmosphere net fluxes provides constraints to the ocean heat storage. It is used here to calculate the interhemispheric contrast in absorbed solar radiation and energy balance. We note that although the interhemispheric contrast is a residue of two large numbers, e.g., the amount of mean absorbed solar radiation in both hemispheres, the observed variation of the contrast is always small. Therefore, even though we cannot directly attribute the variations in the interhemispheric contrast to IMO 2020, it is reasonable to discuss their temporal evolutions and compare the IMO 2020 impact with the observed changes.

Transient warming of IMO2020

We consider the simple one-layer energy balance model 27 :

where C is the heat capacity of the well-mixed ocean layer, T is the temperature anomaly from the equilibrium, t is time, F is the forcing, and $\lambda$ is the climate feedback parameter. For an abrupt forcing, the solution is:

Using C = 8.2 W yr/m2/K and $\lambda$ = 1.2 Wm −2 K −1 , for a forcing of F = 0.2Wm −2 , we get the temperature change at the new equilibrium is 0.17 K with a time scale of C/ $\lambda$ = 7 years. The warming rate is F/C = 0.2/8.2 K/yr = 0.024 K/yr or 0.24 K/decade. $\lambda$ has uncertainty associated with it and its 1- $\sigma$ is 0.25 Wm −2 K −1 . With this, we can estimate equilibrium $T$ to be between 0.14 and 0.21 K. Equation 6 is used to calculate the expected warming trajectory in the 2020 s when combined with a simple long-term upward trend in Fig. 3 . The observed global mean temperature is from the National Aeronautics and Space Administration (NASA) Goddard Institute of Space Studies.

Contributions of background N d , CF, and $\varDelta {N}_{d}$

We calculate the annual mean of incoming solar radiation for each oceanic grid in the North Atlantic and use this map of seasonally invariant incoming solar radiance to calculate IMO2020 forcing (see section c of Methods). The seasonal cycle of forcing using the seasonally invariant solar radiation is shown in Figure S1 , which differs substantially from Fig. 3a , highlighting the impact of seasonal cycle in solar radiation. The peak season for the forcing is now wintertime instead of summertime. This serves as our baseline to test sensitivity of forcing to different variables.

The sensitivity of the forcing to each factor is assessed through the following procedure. We first calculate the seasonal variations of the forcing using observations that contain its seasonal variations. We then calculate a map of annual mean for each variable and use it to calculate the forcing, effectively removing its impact on the seasonal changes. The relative difference between these two calculations can be taken as a measure of how much each variable contributes to the seasonal changes.

Data availability

MODIS, CERES, and MERRA-2 data are public available at their respective websites: https://ladsweb.modaps.eosdis.nasa.gov/ , https://ceres.larc.nasa.gov/ , https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/data_access/ . The GOCART simulation data can be found here: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/H0ZFK9 .

Code availability

The codes are available here: https://zenodo.org/records/11094677 .

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T.Y. conceived the idea, designed the experiments, and wrote the draft. H.S. analyzed the data and made plots. H.B. and K.B. ran simulations. T.Y. wrote the manuscript draft and L.O., R.W., M.C., H.Y., D.B, K.M., and S.P. contributed to writing of the manuscript.

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Yuan, T., Song, H., Oreopoulos, L. et al. Abrupt reduction in shipping emission as an inadvertent geoengineering termination shock produces substantial radiative warming. Commun Earth Environ 5 , 281 (2024). https://doi.org/10.1038/s43247-024-01442-3

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Can Sovereign Green Bonds Accelerate the Transition to Net-Zero Greenhouse Gas Emissions?

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Published: 07 June 2024

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Giusy Chesini ORCID: orcid.org/0000-0002-2310-2638 1

This paper focuses on sovereign green bonds issued in Europe. By issuing green bonds, European governments commit themselves to realizing environmentally friendly projects and encourage other entities, including private-sector ones, to do the same, thus increasing further domestic investments in addressing climate change. However, considering that governments could pursue their sustainable goals by also issuing conventional bonds, this begs the question of why governments should prefer green bonds. A dataset of European sovereign green bonds was retrieved from the Bloomberg Fixed Income database to answer this question. The data cover all European sovereign green bonds issued until the end of 2023. Quantitative analysis confirms the existence of a small green premium for the issuers, representing an incentive to increase the issuances of sovereign green bonds. Furthermore, the government's carbon emissions reduction, the power sector decarbonization, and good climate policies, measured by the Government Climate Risk Score, contribute to further reducing a country's climate risk and consequently the costs of the issuance, thus triggering a virtuous circle which could, in turn, accelerate the transition to net-zero emissions. Despite these benefits, hurdles still exist, and have curbed the development of the market. Examples include divergence between the use of funds raised through green bonds, which should be earmarked exclusively for climate and environmental projects, and the fungibility requirements for proceeds from sovereign debt and fiscal revenues.

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Introduction

Green bonds are an innovative financial tool for addressing environmental and climate challenges. They refer to debt securities whose proceeds are exclusively used to partly or entirely finance or refinance new or existing eligible environment-friendly investment projects (International City/County Management Association, 2021 ).

To understand the need for sovereigns to invest directly in environmentally friendly projects, it is worthwhile to preliminarily emphasize the dramatic impact of climate change on the entire economy and the consequent commitment of each nation to prevent the adverse effects resulting from global warming, such as droughts, wildfires, and floods. The commitments primarily derive from the nationally determined contributions (NDCs) submitted by the European Union (EU) and its member states, together with other nations, following the Paris Agreement under the United Nations (UN) Convention on Climate Change (United Nations, 2015a ). In December 2020, an update of the agreement set a binding target of a net domestic reduction of at least 55% in greenhouse gas (GHG) emissions by 2030 compared to the 1990 level (Tolliver et al., 2019 ; World Bank, 2022 ). The NDCs require substantial funding and are part of an even more substantial financial need to meet the Sustainable Development Goals (SDGs) in the 2030 Agenda for Sustainable Development of the UN Development Programme (United Nations, 2015b ).

Therefore, countries have assumed commitments to reducing GHG emissions to levels consistent with the Paris Agreement, and green bonds could be a valuable financial vehicle to stimulate a net-zero emissions economy by financing climate-smart infrastructures, such as renewable energy generation and climate-smart technology research and development (World Bank, 2022 ). Moreover, by issuing such bonds, countries effectively demonstrate their national commitment to sustainability as a strong signal to the market, indicating the direction of investments to stakeholders and fostering the private sector to follow suit (Heine et al., 2019 ).

Having ascertained that countries need to raise funds to address the challenge of climate change, it is unclear why they should choose green bonds instead of conventional bonds. In the private sector, green bonds represent one of the most substantial innovations in sustainable finance in the past 15 years. In contrast, green bond issuances at the sovereign level are relatively recent, triggered mainly by commitments required by the international agreements mentioned previously. Not surprisingly, the first sovereign green bond issuance can be attributed to the Polish government in late 2016, shortly after the agreements were approved.

Among the main arguments favoring government-issued green bonds is that they facilitate the distribution of burdens for climate change mitigation between generations. Indeed, climate change is, by definition, an intergenerational problem, given that greenhouse gases are long-lived, and their impacts are felt well after the emissions are generated (Sartzetakis, 2021 ). Furthermore, considering that the economic costs of investing in climate change mitigation and adaptation measures could represent a central political obstacle for governments, the issue of green bonds should face less public opposition than broad-based taxes that require an immediate sacrifice (Kantorowicz et al., 2024 ).

In addition, the issuance of sovereign green bonds could also respond to the need of sovereigns to finance their investments with longer maturities (given the potentially longer horizon of green projects) and maybe at a lower borrowing cost relative to conventional bonds, reflecting what is commonly known as the "greenium". The latter is highly questionable because, in principle, it is difficult to figure out why green bonds should be priced differently than any other bond issued by the same issuer. Green projects do not generally present a lower risk than other governmental projects. Furthermore, it is not easy to argue that these bonds fund projects that otherwise would not have been financed with conventional sovereign bonds (Grzegorczyk & Wolff, 2022 ).

Even if there are some favorable conditions for the issuance of sovereign green bonds, currently, they are not as relevant in the bond markets (Giglio et al., 2021 ), probably because of the lack of a strict international set of guidelines outlining what constitutes a green bond. This lack of guidance leads to the risk of fund mismanagement, commonly known as greenwashing (Ando et al., 2022 ). The latter is possible because the issuers, under current regulations, would not receive any substantial penalty if their green promises are not kept (Grzegorczyk & Wolff, 2022 ). To diminish the perception of possible greenwashing, the issuance of green bonds is usually accompanied by a second-party opinion to ensure compliance with established green bond principles and standards. The cost of the opinion should be considered as part of the overall issuance expenses, and can vary from one issuance to another.

Despite some hurdles, European sovereign green issuances have risen substantially, particularly in the last three years. Thus, it is interesting to examine their characteristics and potential to support countries' efforts to finance the low-carbon transition. Consequently, this study investigates the possibility of sovereign green bonds contributing effectively to managing climate risks, accelerating the transition to the aims of the Paris Agreement.

The first research question concerns the fact that sovereign issuers have entered the playing field later than other kinds of issuers, and some Eastern European countries seem more committed to these issuances than others. Thus, the first research question is: Which countries have issued green sovereign bonds thus far?

Next, it is logical to investigate the motivations that induce different countries to finance green projects by issuing specific green bonds instead of conventional bonds. Thus, the second research question is: What motivations can induce a sovereign to issue green bonds?

One of the motivations could be the greenium, i.e., the market premium on the price of the green bond. The latter would suggest that investors are willing to receive a lower market premium for their green investments. Therefore, this research contributes to the literature by investigating the pricing implications of the green label on the primary market for a sample of green sovereign bonds. These considerations suggest another research question requiring quantitative analysis. Does the yield of sovereign green bonds differ from the yield of conventional bonds?

With quantitative analysis, it is also possible to investigate whether the climate risk-reduction measures expressly set up by a government could affect the yield of green bonds. In particular, the government's progress on carbon reduction and its commitments to net-zero target pledges should be appreciated by the financial markets and make the green issuances less costly for the sovereigns. Thus, a fourth research question will address this consideration. Could the government's climate risk score, calculated and updated by Bloomberg every six months, provide evidence of the government's climate change improvements and affect the yield of green bonds relative to conventional bonds?

A final research question arises because sovereigns are the latest type of issuers to enter the green market, where they could have played a role in greening the economy much earlier. Consequently, the fifth research question explores obstacles to the growth of the market. In particular, what obstacles exist in developing a European sovereign green bond market?

Literature Review

Sovereign green bond issuances have emerged as a relatively recent phenomenon. The limited number of bonds issued has deterred extensive scholarly examination, making quantitative analyses extremely difficult. Existing research primarily focuses on issuers from other sectors (e.g., Apergis et al., 2023 ), where a higher volume of bonds provides a more robust foundation for study.

In the literature, two topics have been investigated the most. Both focused on the differences in bond yields. The first concerns whether there is a greenium (i.e., a premium for the issuer) for green bonds compared to similar conventional bonds. The second compares bonds that are simply self-labeled green with those that carry an external review or a second-party opinion. Furthermore, it is possible to distinguish between the broader literature that includes all categories of green bonds and the more recent and specific stream of research dedicated exclusively to sovereign green bonds, which includes the present study.

Examining the broader literature on the greenium, definitive conclusions regarding its existence remain elusive. The findings within the literature vary, influenced by the geographical samples, periods under analysis, and the specific characteristics of issuers and financial markets, whether in the primary or secondary market (Sheng et al., 2021 ).

Several studies exploring the presence of a greenium found that green bond yields were equivalent to those of similar conventional bonds. Consequently, the absence of a green bond premium (greenium) was evident (Flammer, 2021 ; Hyun et al., 2019 ; Kapraun et al., 2021 ; Lau et al., 2022 ).

On the contrary, other papers indicated that investors are willing to pay a premium, signifying a higher price (while accepting a lower yield) than equivalent conventional bonds, driven by their commitment to specific environmental objectives. This results in issuers receiving a premium (referred to as the greenium) on the issuance cost. Consequently, environmentally conscious investors are willing to sacrifice some yield to support bonds offering environmental or climate benefits (Baker et al., 2018 ; Fatica et al., 2021 ; Gianfrate & Peri, 2019 ).

Finally, investors may demand a higher yield when investing in green bonds due to the innovative and riskier nature of the underlying green projects. In such cases, green bonds yield higher returns for investors compared to conventional bonds. Therefore, a form of negative premium exists for issuers, as environmentally conscious investors perceive increased risk and demand higher returns (Bachelet et al., 2019 ; Karpf & Mandel, 2017 ).

As for studies exploring the impact of external audits or second-party opinions on green bond performance, one of the first was conducted by Bachelet et al. ( 2019 ). They showed that through external green audits, private issuers could increase their reputation as sustainable companies, decrease suspicion of greenwashing among investors and, as a result, decrease average returns for investors. A similar result was obtained by Dorfleitner et al. ( 2022 ), who found that investors rewarded green bonds approved by external auditors with a premium in terms of lower returns and higher bond prices. Consequently, external reviews appear to be one of the main factors in improving the integrity and credibility of the green bond market.

With a specific focus on sovereign green bonds, the literature is remarkably limited. In particular, there are no studies on second-party opinions, as almost all sovereign green bonds issued in Europe have received an external review of their framework and allocation and impact reports. Most studies focused on comparing green and conventional bonds issued by the same government. These studies often examined public financial management, with a prevalence of qualitative research methodologies. However, it is essential to note that quantitative analyses are not entirely neglected. For example, Doronzo et al. ( 2021 ) used a regression model to analyze a global sample of 14 countries. Their results indicated no substantial evidence of pronounced greenium. Synthetically, they showed that greenium typically tends toward negativity in the primary market but shows slight positivity (0.5 bps) in the secondary market. Likewise, looking exclusively at European countries, Grzegorczyk and Wolff ( 2022 ) identified ten precise matches between green sovereign bonds and conventional bonds. Their results revealed a consistently lower yield for green sovereign bonds, which they attribute to a behavioral response of investors willing to include green bonds in their portfolios, even at the cost of accepting a lower yield.

Dominguez-Jimenez and Lehmann's research ( 2021 ) focused on EU countries, particularly emphasizing sovereign debt. They advocated for increased transparency and comprehensive information regarding the climate-related aspects of these countries' public budgets. According to their perspective, enhanced transparency would promote stability and improve the functionality of green bond markets. Notably, environmentally conscious investors prefer more detailed information about the specific expenditures within EU countries' budgets that qualify as green.

Ando et al. ( 2022 ) explored the advantages of issuing sovereign green bonds and provided an estimate of the sovereign greenium. The methodology applied by the authors differs for Germany because it adopted a practice not initially followed by other countries, called the issuance of twin bonds. The latter consists of the issuance of two bonds (one green and one conventional) with identical coupons and maturity dates. In their analysis, Germany's greenium fluctuated between 2 and 5 basis points. For the other countries, the authors differentiated between emerging and advanced economies, considering only Euro and United States dollar (USD)-denominated bonds. The greenium was reported as 3.7 and 30.4 basis points for Euro and USD-denominated bonds, respectively. This discrepancy was attributed to the fact that USD-denominated green bonds were issued by a more substantial number of emerging countries.

In 2023, the same authors refined their research by publishing an International Monetary Fund working paper (Ando et al., 2023 ), again distinguishing between twin bonds, which were issued not only by Germany but also by Denmark, and the other sovereign green bonds. The greenium resulting from the analysis of twin bonds was positive but small (around three bps). Through a panel regression analysis, they studied the yields of the other sovereign green bonds, comparing them to a dataset of conventional bonds and confirming the previous results.

Cheng et al. ( 2022 ) centered their research on the challenges sovereigns face in issuing green bonds. Utilizing the Bank for International Settlement (BIS) sustainable database, they elucidated the tensions arising from the prescribed use of proceeds for sovereign green bonds and the fungibility of public debt. Additionally, they highlighted the prominent role played by sovereign issuers in advancing best practices within the green bond market. Specifically, they observed that the inaugural issuance of a sovereign green bond stimulated an increase in green corporate issuances, particularly those accompanied by second-party opinions.

Finally, the relationship dynamics between sovereign green bonds and country value and risk, though partially unexplored, formed the focus of the investigation of Dell’Atti et al. ( 2022 ). Their empirical analysis delved into stock and credit default swap market responses to green bond issuances by ten EU countries between 2016 and 2021. Their findings revealed that investors perceived the issuance of a sovereign green bond as a value-enhancing and risk-reducing action, signaling the country's commitment to a low-carbon economy and accruing social and reputational benefits. Thus, sovereign green bond issuance is a mechanism to mitigate a country's climate risk.

In this context, the present research contributes to the literature on sovereign green bonds in four key dimensions. First, it brings attention to the inhomogeneity in data and strategies among European sovereigns, attributed to the presence of both advanced and emerging economies, each adopting distinct approaches to the green bond markets. Second, it confirms the existence of a small greenium for sovereign green bonds by analyzing a dataset composed of green and conventional bonds for 10 European countries, selected among the green bond issuers for their strong presence in the bond markets. Third, it finds that the issuance of green bonds and the set-up of other green measures and policies are recognized by the markets as a mitigation mechanism for country climate risk that can induce investors to accept a lower yield. Last, from a regulatory standpoint, the research emphasizes the absence of a robust recognition system for determining a bond's green status.

Recent Growth in Sovereign Green Bond Issuances

In Europe, 16 countries issued 54 green debt securities of different maturities and outstanding amounts as of 31 December 2023. The maturity range is between three and 30 years, except for a recent series of green Austrian T-bills with a shorter maturity.

As Table 1 shows, the largest number of sovereign green debt securities, 36 out of 54, are EUR-denominated. The other currencies used are the Hungarian Forint (HUF), the Swedish Krona (SEK), the Japanese Yen (JPN), the Chinese Renminbi (CNY), the Great British Pound (GBP), the Swiss Franc (CHF) and the Danish Krone (DKK).

At the close of 2016, leveraging the momentum generated by the 2015 Paris Agreement, Poland emerged as the inaugural issuer of sovereign green bonds, followed by France in 2017 (Tsonkova, 2019 ). Since then, numerous other sovereigns have entered the green bond market. While developed countries dominate most issuances, emerging nations (Poland, Hungary, Lithuania, and Serbia) contribute substantially to the overall issuances (Ando et al., 2022 ).

From 2020 onward, the European sovereign green market experienced rapid expansion, with Germany issuing seven green bonds and Hungary issuing 11, surpassing other countries in bond numbers.

Germany and Hungary present different economic characteristics (Chesini, 2023 ). In fact, developed and emerging economies tend to approach financial markets differently owing to multiple factors, such as inherent risks, different levels of liquidity, and depth of financial markets. On average, emerging markets have issued sustainable debt at much higher coupons and shorter tenors than advanced economies because of the weaker credit ratings (Goel et al., 2022 ). Consequently, even if both Germany and Hungary issued more green bonds than other European sovereigns, they did so by pursuing different strategies.

Considering the emerging countries, Poland, as a trailblazer in this sector, issued four green bonds between 2016 and 2019. Looking at the green-eligible sectors where the proceeds from the bonds should be employed (Table 2 ), it appears that Polish green bonds undertook appropriate agri-climate-environmental activities by supporting sustainable agricultural operations, afforestation, national parks, and reclamation of heaps (State Treasury of the Republic of Poland, 2016 ). This selection reflects the fact that more than 93% of Poland consists of rural areas inhabited by around 39% of total Polish citizens. In particular, afforestation implies the conversion to forest of land that historically was not forested. The aim of the reclamation of heaps is very particular and unique in the European context, representing expenditures on the restoration of degraded lands affected by mining.

In April 2018, the Government of Lithuania issued its first 10-year green bond amounting to EUR 20 million through the domestic auction. In 2020, the issue was tapped twice, and its final nominal value reached EUR 68 million. The green bond proceeds were expected to cover the financing gap for the Soviet-era multi-apartment building energy upgrades, achieving broad national objectives for energy efficiency in this way. In the full detailed impact reporting at the end of 2022, it emerged that the government had already used all the proceeds to renovate 170 buildings, reporting high energy savings per year (Ministry of Finance of the Republic of Lithuania, 2023 ).

Following the UN Climate Agreement in Paris (United Nations, 2015a ), Hungary has proven to be particularly sensitive to international requirements seeking to address climate change. In 2016, it became the first European country to ratify legislation to support the Paris Agreement and broke with its traditional European Visegrad Group allies: Poland, the Czech Republic, and Slovakia. In fact, in the past, these countries tended to stick together in resisting measures that would price out the dirtiest fossil fuels. However, Hungary was less coal-reliant than some of its central and eastern European neighbors and, indeed, more inclined to take a position in the new international green market.

In particular, in 2018, the rising costs of EU carbon prices, after years of lagging, motivated Hungary toward a climate strategy to reduce carbon emissions by replacing fossil fuels, improving energy efficiency, developing a green economy, and adding forests. Consequently, in June 2020, Hungary began to issue green bonds after setting a climate neutrality goal for 2050 in a law signaling support for the net zero emission strategy (Government Debt Management Agency of Hungary, 2020 ). The bulk of funds raised with the first issuance was earmarked to run, maintain, and upgrade the Hungarian railway system.

In December 2021, Hungary received permission from the Bank of China to issue the first green sovereign panda bond denominated in Chinese yuan. Moreover, at the beginning of 2022, Hungary became the first foreign sovereign issuer to enter the yen green bond market. At the end of 2022, Hungary had issued one green bond in EUR, three in HUF, two in CNY, and five in YEN. The strategy pursued by the Hungarian Government is oriented toward expanding its international scope in financial markets while implementing broad and overreaching climate, energy, and environmental policies to transition the country to a low-carbon and environmentally friendly economy (Government Debt Management Agency of Hungary, 2020 ).

Serbia, the last emerging country considered, issued its first green bond in 2021. Analyzing the Green Bond Framework, the green sectors eligible for expenditure are not dissimilar to those declared by most developed countries. In fact, Serbia did not prioritize a specific green sector like other emerging economies. Serbia issued €1 billion in its first green bond sale, and this seven-year bond achieved the lowest annual coupon rate in its history. The green bond issue was subscribed to more than three times. Examining the second-party opinion provided by Institutional Shareholder Services (ISS) Corporate, 100% of the proceeds were earmarked for green assets as of December 2023, and the issuer followed a transparent process for allocating the proceeds (ISS-Corporate, 2024 ).

Considering the advanced economies and the amount of funds raised by each one, France is the most relevant issuer regarding funds raised through green bonds, followed by Germany. France issued its first sovereign bond in January 2017, following Poland, which preceded it by only one month. France had started playing the role of leader in this market with a substantial issuance serving as testimony and proof of the authoritative role played in 2015 when France was the host and convenor of the historic Paris Agreement. The first French sovereign bond raised Paris's sustainable finance profile among European countries and worldwide (Climate Bonds Initiative, 2018 ).

Germany, the second largest issuer, has been nearly a latecomer in tapping into the potential of green sovereign bonds, contrasting with its reputation as an energy transition pioneer. Specifically, it has been issuing twin bonds since September 2020. The twin-bonds approach involves issuing a conventional and a green bond with the same maturity date and coupon. The main difference is that proceeds from the green bond are earmarked for green projects (Federal Ministry of Finance, 2020 ). However, there are other differences. The green bond's issuance volume is generally smaller, and the issuance date is later than the related conventional bond. The German government launched twin bonds to attract investors into the sustainable finance market without disadvantaging them with respect to other investors. The twin bond concept allows investors to swap conventional German government bonds with green bonds and vice versa, if deemed necessary, for example, for liquidity purposes (Climate Bonds Initiative, 2021 ).

Furthermore, through the issuance of twin bonds, Germany's strategy aims to establish the yields of green federal securities as the reference for the Euro green finance market. Seven twin bonds were on the market as of the end of 2023. Doronzo et al. ( 2021 ) noted that in German twin bonds the greenium is consistently positive and does not seem to react much to large uncertainty shocks, such as the Russian invasion of Ukraine in February 2022.

In 2022, another country, the Kingdom of Denmark, started issuing sovereign green bonds as twin bonds in line with the twin bond concept introduced by Germany in 2020. Towards the end of 2023, Denmark issued another green bond with the same characteristics.

Finally, a recent novelty deserves mention, that of the issuance of green sovereign money market instruments, commonly called T-bills, by a pioneer country in this market segment, the Republic of Austria. It issued its first sovereign bond (4 billion EUR of debt due 2049) in May 2022. After a few months, in October, Austria completed the country's green funding requirement for that year, becoming the first European country to issue green T-bills. The first T-bill was a 4-month maturity instrument, redeemed in February 2023. It was followed by other issuances on a rolling three-month period from February to May, May to August, August to November, November to February, and onwards.

In summary, issuances of sovereign green bonds have involved many European countries with advanced and emerging economies (Chesini, 2023 ). The benefits of tackling the challenge of climate change that both types of countries derive from green bond issuances are considerable. Besides signaling their international green commitments, emerging countries can obtain even more substantial benefits by involving new international investors, improving ratings, and consequently lowering funding costs (World Bank, 2022 ).

Empirical Analysis

The quantitative analysis empirically investigates the factors influencing green bond yields. A dataset of sovereign green bonds was compiled from Bloomberg's Fixed Income database (Bloomberg, 2023 ). The dataset covers all green sovereign bonds properly identified by Bloomberg and comprises 54 European sovereign green bonds issued by 16 sovereigns from December 2016 to December 2023 (Table 1 ). To compare the yields of green and conventional bonds, another dataset of conventional bonds issued by the same sovereigns in the same years was compiled (Ando et al., 2023 ).

The analysis focused on the primary market because green bonds tend to be bought mainly by institutional investors and held to maturity. For statistical reasons, after a qualitative analysis, the issuers with fewer conventional and green bonds were eliminated. In addition, the green T-bills issued by the Austrian government were eliminated as well. Consequently, the analysis focused on only ten sovereigns and 306 bonds, as shown in Table 3 . In this restricted dataset, each sovereign issued at least two green bonds and a more relevant number of conventional bonds. Consequently, the final unbalanced dataset is composed of 36 green bonds and 270 conventional bonds.

To find possible differences in yields between green and conventional sovereign bonds, and to investigate the drivers of these differences, a model similar to those presented by Fatica et al. ( 2021 ) and Kapraun et al. ( 2021 ) was adopted. The baseline panel regression specification is as follows,

where Yieldi,t,b refers to the yield to maturity at the time of issuance of bond b issued by issuer i in time t . Greeni,t,b is our primary variable of interest, which equals one if a bond is green and zero otherwise. Xb,i,t is a vector that includes a set of bond characteristics that may affect the yield. Finally, Zi,t is a vector of macroeconomic variables concerning countries/sovereigns that may affect the bonds' yield.

In particular, the dependent variable in the model is the yield to maturity ( Yield ), while the independent variables are those indicated in Table 4 . The independent variable, called the Government Climate Risk (GCR) score ( Govt_climate_risk_score ), to the best of our knowledge, has not previously been used in the literature and is the result of three equally weighted score pillars. First is a measure of carbon transition, i.e., a measure of the government's progress on carbon reduction, carbon per capita and gross domestic product (GDP), and the gap from a country's NDC (Paris Agreement). This measure provides insight on the region's historical, current and forward-looking emissions target.

Second is a measure of power sector transition, i.e., a score measuring a government's progress and future effort towards power sector decarbonization. It includes country-level capacity and generation data, as well as the outlook for wind and solar capacity additions and clean energy investment dollars. Third is a measure of climate policies, i.e., the government's commitment to Net-Zero targets' pledges, green debt issuance, and renewable energy policy frameworks.

Moving on to the model, the regressions for both fixed and random effects panel data were run. The Hausmann test was employed to decide which regression best fits the data. The test rejected the alternate hypothesis of fixed effects in the model. Therefore, only the random-effects model results are reported in Table 5 .

To measure the greenium, a dummy variable ( dummy_green ) was introduced. The dummy_green variable is statistically significant (at the 0.01 level) and negative (b =-0.6819113). The negative sign of the coefficient suggests that when the dummy variable becomes 1 from 0 (i.e., the bond is green), the yield the sovereign pays is lower than that of conventional bonds. Thus, a greenium does exist. One possible explanation for this result is that the simple characterization of a bond as green is recognized by investors as a reason to accept a lower yield. The presence of a small greenium in sovereign green bonds is also found in Doronzo et al. ( 2021 ), Grzegorczyk and Wolff ( 2022 ), and Ando et al. ( 2022 ).

Considering the independent variables, Rating is statistically significant (0.0656**) and positive. In the analysis, the value 1 was attributed to AAA. Higher values were attributed to the lower ratings, meaning that the lower the number indicating the rating, the higher the rating and, consequently, the lower the yield.

Issue_px is statistically significant (- 0.0627***) and negative because the higher the price of the bond, the lower the yield. The estimated coefficient for CPN is statistically significant and positive (b = 0.223***). As CPN increases, Yield increases as well. Years is also statistically significant and positive (0.00983**). As Years increases, Yield increases as well, as in other papers (e.g., Apergis et al., 2022 ).

Then the macroeconomic variables were considered, i.e., the variables not representing the individual bond but the country. GDPcapita is statistically significant and negative (-0.000000858*) indicating that when the GDP per capita is lower, the country should be poorer. Consequently, the debt is riskier and the yield is higher.

Govt_climate_risk_score measures a government's decarbonization transition efforts and its preparedness to meet the global Paris Agreement goals. The score ranges from 0 to 10, where 10 is the best. The variable representing the score is statistically significant and negative (- 0.330**). The higher the score, the lower the yield. This result is highly understandable considering the methodology used by Bloomberg ( 2023 ), where the less climate risky sovereigns have higher scores. Thus, the climate risk score shows that the sovereign issuance of green bonds also acts as a mitigation mechanism for country risk and, with a completely different methodology, the present analysis confirms the result of Dell’Atti et al. ( 2022 ).

The variable Ln_Amount is not significant, but the sign is correct (- 0.0128). The higher the amount of the bond, the higher the liquidity and the lower the yield (Apergis et al., 2021 ).

Finally, the analysis introduces another dummy variable concerning the bond's currency to verify if the greenium is higher for green bonds issued in Euro. The dummy_crncy is statistically significant and negative (- 0.8241***), indicating a lower yield for bonds issued in Euro (Ando et al., 2022 ). To confirm the results, different panel regressions were run excluding one or more countries from the dataset, and the results did not change.

In summary, the statistical analysis indicates that sovereign green bonds tend to be issued with a small greenium. In addition, the more a country can implement new climate policies, reduce GHG emissions, and deploy decarbonization processes, the lower its climate risk, and, consequently, the higher the greenium in respect to the funding costs in the market. Combining both results, European sovereigns should issue green bonds and transparently implement green projects and policies. In doing so, they can be funded by providing a lower yield to the investors concerning conventional bonds. Moreover, these improvements are recognized in their respective climate risk score. In turn, they can issue new green bonds with lower risk and lower yields. Furthermore, it should not be overlooked that the issuance of sovereign green bonds is an essential signal to the market and incentivizes other issuers in the private sector to follow suit and make more effort to reach the aims of the Paris Agreement.

Main Hurdles to the Issuance of Sovereign Green Bonds

It is possible to identify two relevant obstacles to developing the market of sovereign green bonds until now. The first involves almost all green bond issuers, while the second is related explicitly to the sovereigns.

The first hurdle is a regulatory issue. The European regulation did not provide a strict definition of green bonds. Until now, the financial sector has relied extensively on authoritative guidelines issued by different private entities. In particular, in 2014, the International Capital Market Association (ICMA) began to provide guidelines and green project categories. It proposed the Green Bond Principles (GBPs), which have quickly become the most-used references by operators (ICMA, 2021 ; Sartzetakis, 2021 ).

Other similar principles have been issued for self-regulation in the green financial industry. For example, the Climate Bonds Initiative (CBI) built its own Climate Bonds Standards (CBSs), providing a sector-specific definition of green in early 2012 (Climate Bonds Initiative, 2019 ). This framework is specifically aimed at climate bonds, which can be categorized as a subset of green bonds. While green bonds are usually issued to raise money for environmental projects, climate bonds more narrowly focus on raising funds for investments in emission reductions or climate change adaptation. The GBPs and the CBSs provide many recommendations but no obligations, essentially because they result from private initiatives. Bond issuers' compliance remains voluntary, leading to the possibility of misused funds, commonly known as greenwashing (Mosionek-Schweda & Szmelter, 2019 ; Rose, 2021 ).

In this context, in December 2019, the European Commission launched the European Green Deal to promote and facilitate the transition to a climate-friendly environment while pursuing the economy's growth. To reach this ambitious goal, a comprehensive mix of legislative and non-legislative measures were scheduled and progressively implemented (Claeys et al., 2019 ). According to this ambitious strategy, in July 2021, the European Commission presented a proposal for regulation of European green bonds defining the European Green Bond Standard (EU GBS), i.e., a set of voluntary standards applicable to any green bond issuer, aiming to help scale up and support the environmental ambitions of the green bond market. The fundamental intention is to impose stricter sustainability requirements on issuers when they raise funds to protect investors from greenwashing (European Commission, 2021 ). In November 2023, the EU GBS Regulation was finally published (Official Journal of the European Union, 2023 ). From 2025, the EU GBS will start applying. It is more rigorous than other existing green bond standards, particularly regarding the allocation of bond proceeds, and will minimize the concern about greenwashing.

The second challenge, unique to sovereign issuers, revolves around the fungibility of fiscal revenues. The inception of the green sovereign bond segment in late 2016 is likely attributed to this significant hurdle. Sovereign issuers grapple with the tensions between allocating funds expressly designated for green projects and meeting the fungibility demands of financial resources (Doronzo et al., 2021 ).

The fungibility of fiscal revenues is one of the main principles of public financial management, and it poses a challenge for many potential sovereign issuers of green bonds. Such issuers cannot legally commit themselves to using the proceeds of the bond for a specific green purpose. Even if this restriction does not apply to all sovereigns (Dominguez-Jimenez & Lehmann, 2021 ), practically public budgets are subject to frequent changes and, thus, potentially to uses other than those envisaged for the proceeds of an existing green bond issuance (Cheng et al., 2022 ). Consequently, the current framework for most sovereign green bonds does not guarantee that new green investments will be made using the bond proceeds. Often, the funds are used to refinance past expenditures. Some sovereigns have tried to address this issue by committing some portion (e.g., at least 50% of the proceeds) for same-year spending or a combination of current and future expenditures (Cheng et al., 2022 ).

In summary, the issuance of sovereign green bonds requires increased efforts and imposes additional transparency obligations compared to conventional bond issuances. At times, a substantial investment in government operations is necessary for the efficient and successful issuance of green bonds. Additionally, it is crucial to consider the direct tangible costs associated with the preparation of the allocation and impact reports and related second-party opinions. Lastly, reputational costs should be treated as if the government will fail to fulfill its commitments related to green projects (Lindner & Chung, 2023 ).

Conclusions

This research aims to answer the question of whether sovereign green bonds can accelerate the transition to a greener economy. It also presents an overview of the recent development of the European sovereign green bond market, describing the existing barriers to further market development. Furthermore, it contributes to the literature because the market is still in its infancy, and few studies have focused only on European sovereign green bonds. Even though the European sovereign green bond market remains small, it has increased steadfastly in the last few years mainly because governments, like other market participants, are asked for more credible policies to face the challenge of climate change.

Among the benefits of sovereign green bond issuances, it is worth underscoring their role as a benchmark in domestic sustainable markets. The supply is not keeping up with demand. Usually they have been oversubscribed due to the growing ESG investor clientele demanding more and more ESG assets. Of course, demand dynamics vary according to the prevailing economic and geopolitical backdrop and the size and maturity of different securities. For example, the first French issuance of sovereign green bonds presented a demand eight times higher than the supply.

The presence of emerging economies among issuers necessitates an exploration of their motivations for entering this market. It appears that green bonds tend to be issued with a longer maturity, so the refinancing risk is lower, and the benefits may be more considerable for emerging European countries with less stable demand for extra-long maturities. In addition to signaling their commitment to sustainability goals, emerging economies can diversify their investor base and achieve better pricing. The case of Hungary, with its issuances in the Chinese and Japanese financial markets, illustrates this phenomenon quite well. On the other hand, Serbia, for example, achieved the lowest annual coupon rate in its history with its first issuance of green bonds.

The panel regression analysis indicates that sovereign green bonds, on average, are issued with a small greenium with respect to conventional bonds, as other scholars have already documented. The result is more remarkable for green bonds issued in euros. The analysis also considers a new score, computed and updated by Bloomberg ( 2023 ), which measures the efforts of a country towards the goals indicated in the Paris Agreement. The panel analysis demonstrates that the commitments and actions of governments related to carbon reduction, power sector decarbonization and the adoption of climate policies contribute to reducing a country's climate risk and, consequently, the costs of the issuances. This should further incentivize the governments to finance new green projects by issuing green bonds.

Two main obstacles have prevented European countries from paving the way in issuing sovereign green bonds until now. First, due to fungibility requirements, most sovereign debt legal frameworks do not allow the earmarking of proceeds to specific green projects. In fact, unlike sovereign conventional bonds, whose proceeds can be used for general purposes, the proceeds from green bonds need to finance specific green projects, tying the hands of the issuer. Second, until now, there have been no uniform and strict green bond standards within the EU, and this may have curbed the segment's growth. In this regard, the new EU GBS, which take effect in 2025, will better ensure that European issuers can benefit from green financing and that investors can find the green investments they seek without the risk of greenwashing.

Data Availability

Data available on request from the author.

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Chesini, G. Can Sovereign Green Bonds Accelerate the Transition to Net-Zero Greenhouse Gas Emissions?. Int Adv Econ Res (2024). https://doi.org/10.1007/s11294-024-09900-6

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Assessment of ammonia emissions and greenhouse gases in dairy cattle facilities: a bibliometric analysis.

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Ferraz, P.F.P.; Ferraz, G.A.e.S.; Ferreira, J.C.; Aguiar, J.V.; Santana, L.S.; Norton, T. Assessment of Ammonia Emissions and Greenhouse Gases in Dairy Cattle Facilities: A Bibliometric Analysis. Animals 2024 , 14 , 1721. https://doi.org/10.3390/ani14121721

Ferraz PFP, Ferraz GAeS, Ferreira JC, Aguiar JV, Santana LS, Norton T. Assessment of Ammonia Emissions and Greenhouse Gases in Dairy Cattle Facilities: A Bibliometric Analysis. Animals . 2024; 14(12):1721. https://doi.org/10.3390/ani14121721

Ferraz, Patricia Ferreira Ponciano, Gabriel Araújo e Silva Ferraz, Jacqueline Cardoso Ferreira, João Victor Aguiar, Lucas Santos Santana, and Tomas Norton. 2024. "Assessment of Ammonia Emissions and Greenhouse Gases in Dairy Cattle Facilities: A Bibliometric Analysis" Animals 14, no. 12: 1721. https://doi.org/10.3390/ani14121721

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Research papers: greenhouse gas emissions.

By Antonio M. Bento, Richard Klotz

Environmental Science & Technology

Lifecycle analysis (LCA) metrics of greenhouse gas emissions are increasingly being used to select technologies supported by climate policy. However, LCAs typically evaluate the emissions associated with a technology or product, not the impacts of policies. Here, we show that policies supporting the same technology can lead to dramatically different emissions impacts per unit of technology added, due to multimarket responses to the policy. Using a policy-based consequential LCA, we find that the lifecycle emissions impacts of four US biofuel policies range from a reduction of 16.1 gCO 2 e to an increase of 24.0 gCO 2 e per MJ corn ethanol added by the policy. The differences between these results and representative technology-based LCA measures, which do not account for the policy instrument driving the expansion in the technology, illustrate the need for policy-based LCA measures when informing policy decision making.

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Sustainable approach of biological treatment of landfill leachate by Anaerobic Ammonium Oxidation: A review

Murhunzi, B. A.
Olukanni, D. O.
Oyegbile, B. A.

An upsurge in living standards, rising industrialization and urbanization, the protection of water environment has become a priority. Anaerobic ammonium oxidation process has drawn a lot of attention since it demonstrated substantial advantages over conventional nitrogen removal techniques, including a 100% reduction in the amount of organic carbon required, a 60% reduction in the amount of aeration needed, and a 90% reduction in the amount of sludge produced. Effective treatment of landfill leachate is extremely important as leachate is a threat to the environment. Municipal waste management is still a challenging situation in developing countries. Uncontrolled waste disposal results in greenhouse gases emissions which worsens climate change as the leachate will pollute water bodies, soil and a significant air pollution which impacts on human health will be released. This paper reviewed several published research works in Scopus dealing with the leachate treatment by Anammox process combined with some other systems and highlighted some common challenges found with the application of this new technology. Treating landfill leachate resulted in an excellent ammonium NH 4 + -N removal efficiency. However, it has been highlighted that most of the research reviewed reported some limitations of the technology on a small scale such as the low start-up time affecting the growth of bacteria in the reactors and the instability of the system when pH and temperature decrease. Biological treatment, Anammox method included, offers a cost-effective, eco-friendly, and an effective solution for nitrogen removal.

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Climate Change and the Impact of Greenhouse Gasses: CO 2 and NO, Friends and Foes of Plant Oxidative Stress

Here, we review information on how plants face redox imbalance caused by climate change, and focus on the role of nitric oxide (NO) in this response. Life on Earth is possible thanks to greenhouse effect. Without it, temperature on Earth’s surface would be around -19°C, instead of the current average of 14°C. Greenhouse effect is produced by greenhouse gasses (GHG) like water vapor, carbon dioxide (CO 2 ), methane (CH 4 ), nitrous oxides (N x O) and ozone (O 3 ). GHG have natural and anthropogenic origin. However, increasing GHG provokes extreme climate changes such as floods, droughts and heat, which induce reactive oxygen species (ROS) and oxidative stress in plants. The main sources of ROS in stress conditions are: augmented photorespiration, NADPH oxidase (NOX) activity, β-oxidation of fatty acids and disorders in the electron transport chains of mitochondria and chloroplasts. Plants have developed an antioxidant machinery that includes the activity of ROS detoxifying enzymes [e.g., superoxide dismutase (SOD), ascorbate peroxidase (APX), catalase (CAT), glutathione peroxidase (GPX), and peroxiredoxin (PRX)], as well as antioxidant molecules such as ascorbic acid (ASC) and glutathione (GSH) that are present in almost all subcellular compartments. CO 2 and NO help to maintain the redox equilibrium. Higher CO 2 concentrations increase the photosynthesis through the CO 2 -unsaturated Rubisco activity. But Rubisco photorespiration and NOX activities could also augment ROS production. NO regulate the ROS concentration preserving balance among ROS, GSH, GSNO, and ASC. When ROS are in huge concentration, NO induces transcription and activity of SOD, APX, and CAT. However, when ROS are necessary (e.g., for pathogen resistance), NO may inhibit APX, CAT, and NOX activity by the S-nitrosylation of cysteine residues, favoring cell death. NO also regulates GSH concentration in several ways. NO may react with GSH to form GSNO, the NO cell reservoir and main source of S-nitrosylation. GSNO could be decomposed by the GSNO reductase (GSNOR) to GSSG which, in turn, is reduced to GSH by glutathione reductase (GR). GSNOR may be also inhibited by S-nitrosylation and GR activated by NO. In conclusion, NO plays a central role in the tolerance of plants to climate change.

Introduction

Life on Earth, as it is, relies on the natural atmospheric greenhouse effect. This is the result of a process in which a planet’s atmosphere traps the sun radiation and warms the planet’s surface.

Greenhouse effect occurs in the troposphere (the lower atmosphere layer), where life and weather occur. In the absence of greenhouse effect, the average temperature on Earth’s surface is estimated around -19°C, instead of the current average of 14°C ( Le Treut et al., 2007 ). Greenhouse effect is produced by greenhouse gasses (GHG). GHG are those gaseous constituents of the atmosphere that absorb and emit radiation in the thermal infrared range ( IPCC, 2014 ). Traces of GHG, both natural and anthropogenic, are present in the troposphere. The most abundant GHG in increasing order of importance are: water vapor, carbon dioxide (CO 2 ), methane (CH 4 ), nitrous oxides (N x O) and ozone (O 3 ) ( Kiehl and Trenberth, 1997 ). GHG percentages vary daily, seasonally, and annually.

GHG Contribute Differentially to Greenhouse Effect

Water vapor.

Water is present in the troposphere both as vapor and clouds. Water vapor was reported by Tyndal in 1861 as the most important gaseous absorber of variations in infrared radiation (cited in Held and Souden, 2000 ). Further accurate calculation estimate that water vapor and clouds are responsible for 49 and 25%, respectively, of the long wave (thermal) absorption ( Schmidt et al., 2010 ). However, atmospheric lifetime of water vapor is short (days) compared to other GHG as CO 2 (years) ( IPCC, 2014 ).

Water vapor concentrations are not directly influenced by anthropogenic activity and vary regionally. However, human activity increases global temperatures and water vapor formation indirectly, amplifying the warming in a process known as water vapor feedback ( Soden et al., 2005 ).

Carbon Dioxide (CO 2 )

Carbon dioxide is responsible for 20% of the thermal absorption ( Schmidt et al., 2010 ).

Natural sources of CO 2 include organic decomposition, ocean release and respiration. Anthropogenic CO 2 sources are derived from activities such as cement manufacturing, deforestation, fossil fuels combustion such as coal, oil and natural gas, etc. Surprisingly, 24% of direct CO 2 emission comes from agriculture, forestry and other land use, and 21% comes from industry ( IPCC, 2014 ).

Atmospheric CO 2 concentrations climbed up dramatically in the past two centuries, rising from around 270 μmol.mol -1 in 1750 to present concentrations higher than 385 μmol.mol -1 ( Mittler and Blumwald, 2010 ; IPCC, 2014 ). Around 50% of cumulative anthropogenic CO 2 emissions between 1750 and 2010 have taken place since the 1970s ( IPCC, 2014 ). It is calculated that the temperature rise produced by high CO 2 concentrations, plus the water positive feedback, would increase by 3–5°C the global mean surface temperature in 2100 ( IPCC, 2014 ).

Methane (CH 4 )

Methane (CH 4 ) is the main atmospheric organic trace gas. CH 4 is the primary component of natural gas, a worldwide fuel source. Significant emissions of CH 4 result from cattle farming and agriculture, but mainly as a consequence of fossil fuel use. Concentrations of CH 4 were multiplied by two since the pre-industrial era. The present worldwide-averaged concentration is of 1.8 μmol.mol -1 ( IPCC, 2014 ).

Although its concentration represents only 0.5% that of CO 2 , concerns arise regarding a jump in CH 4 atmospheric release. Indeed, it is 30 times more powerful than CO 2 as GHG ( IPCC, 2014 ). CH 4 generates O 3 (see below), and along with carbon monoxide (CO), contributes to control the amount of OH in the troposphere ( Wuebbles and Hayhoe, 2002 ).

Nitrous Oxides (NxO)

Nitrous oxide (N 2 O) and nitric oxide (NO) are GHG. During the last century, their global emissions have rised, due mainly to human intervention ( IPCC, 2014 ). The soil emits both N 2 O and NO. N 2 O is a strong GHG, whereas NO contributes indirectly to O 3 synthesis. As GHG, N 2 O is potentially 300 times stronger than CO 2 . Once in the stratosphere, the former catalyzes the elimination of O 3 ( IPCC, 2014 ). In the atmosphere, N 2 O concentrations are climbing up due mainly to microbial activity in nitrogen (N)-rich soils related with agricultural and fertilization practices ( Hall et al., 2008 ).

Anthropogenic emissions (from combustion of fossil fuels) and biogenic emissions from soils are the main sources of NO in the atmosphere ( Medinets et al., 2015 ). In the troposphere, NO quickly oxidizes to nitrogen dioxide (NO 2 ). NO and NO 2 (termed as NO x ) may react with volatile organic compounds (VOCs) and hydroxyl, resulting in organic nitrates and nitric acid, respectively. They access ecosystems through atmospheric deposition that has an impact on the N cycle as a result of acidification or N enrichment ( Pilegaard, 2013 ).

NO Sources and Chemical Reactions in Plants

Two major pathways for NO production have been described in plants: the reductive and the oxidative pathways. The reductive pathway involves the reduction of nitrite to NO by NR under conditions such as acidic pH, anoxia, or an increase in nitrite levels ( Rockel et al., 2002 ; Meyer et al., 2005 ). NR-dependent NO formation has been involved in processes such as stomatal closure, root development, germination and immune responses. In plants, nitrite may also be reduced enzymatically by other molybdenum enzymes such as, xanthine oxidase, aldehyde oxidase, and sulfite oxidase, in animals ( Chamizo-Ampudia et al., 2016 ) or via the electron transport system in mitochondria ( Gupta and Igamberdiev, 2016 ).

The oxidative pathway produces NO through the oxidation of organic compounds such as polyamines, hydroxylamine and arginine. In animals, NOS catalyzes arginine oxidation to citrulline and NO. Many efforts were made to find the arginine-dependent NO formation in plants, as well as of plant NOS ( Frohlich and Durner, 2011 ). The identification of NOS in the green alga Ostreococcus tauri ( Foresi et al., 2010 ) led to high-throughput bioinformatic analysis in plant genomes. This study shows that NOS homologs were not present in over 1,000 genomes of higher plants analyzed, but only in few photosynthetic microorganisms, such as algae and diatoms ( Di Dato et al., 2015 ; Kumar et al., 2015 ; Jeandroz et al., 2016 ). In summary, although an arginine-dependent NO production is found in higher plants, the specific enzyme/s involved in the oxidative pathways remain elusive.

Ozone (O 3 )

Ozone (O 3 ) is mainly found in the stratosphere, but a little amount is generated in the troposphere. Stratospheric ozone (namely the ozone layer) is formed naturally by chemical reactions involving solar ultraviolet (UV) radiation and O 2 . Solar UV radiation breaks one O 2 molecule, producing two oxygen atoms (2 O). Then, each of these highly reactive atoms combines with O 2 to produce an (O 3 ) molecule. Almost 99% of the Sun’s medium-frequency UV light (from about 200 to 315 nm wavelength) is absorbed by the (O 3 ) layer. Otherwise, they could damage exposed life forms near the Earth surface 1 .

The majority of tropospheric O 3 appears when NOx, CO and VOCs, react in the presence of sunlight. However, it was reported that NOx may scavenge O 3 in urban areas ( Gregg et al., 2003 ). This dual interaction between NOx and O 3 is influenced by light, season, temperature and VOC concentration ( Jhun et al., 2015 ).

Besides, the oxidation of CH 4 by OH in the troposphere gives way to formaldehyde (CH 2 O), CO, and O 3 , in the presence of high amounts of NOx 1 .

Tropospheric O 3 is harmful to both plants and animals (including humans). O 3 affects plants in several ways. Stomata are the cells, mostly on the underside of the plant leaves, that allow CO 2 and water to diffuse into the tissue. High concentrations of O 3 cause plants to close their stomata ( McAdam et al., 2017 ), slowing down photosynthesis and plant growth. O 3 may also provoke strong oxidative stress, damaging plant cells ( Vainonen and Kangasjärvi, 2015 ).

Global Climate Change: an Integrative Balance of the Impact on Plants

Anthropogenic activity alters global climate by interfering with the flows of energy through changes in atmospheric gasses composition, more than the actual generation of heat due to energy usage ( Karl and Trenberth, 2003 ). Short-term consequences of GHG increase in plants are mainly associated with the rise in atmospheric CO 2 . Plants respond directly to elevated CO 2 increasing net photosynthesis, and decreasing stomatal opening ( Long et al., 2004 ). To a lesser extent, O 3 uptake by plants may reduce photosynthesis and induce oxidative stress. In the middle and long term, prognostic consensus about climate change signal a rise in CO 2 concentration and temperature on the Earth’s surface, unexpected variations in rainfall, and more recurrent and intense weather conditions, e.g., heat waves, drought and flooding events ( Mittler and Blumwald, 2010 ; IPCC, 2014 ). These brief episodes bring plants beyond their capacity of adaptation; decreasing crop and tree yield ( Ciais et al., 2005 ; Zinta et al., 2014 ).

Here we will not discuss plants capacity of adaptation to novel environmental conditions when considering large scales and long-term periods. Ecosystems are being affected by climate change at all levels (terrestrial, freshwater, and marine), and it was already reported that species are under evolutionary adaptation to human-caused climate change (for a review see Scheffers et al., 2016 ). Migration and plasticity are two biological mechanisms to cope with these changes. Data indicate that each population of a species has limited tolerance to sharp climate variations, and they could migrate to find more favorable environments. Habitat fragmentation limits plant movement, being other big threat for adaptation ( Stockwell et al., 2003 ; Leimu et al., 2010 ). Despite the fact that individual plants are immobile, plant populations move when seeds are dispersed, resulting in differences in the general distribution of the species ( Corlett and Westcott, 2013 ). In this sense, anthropogenic activities also contribute to seed dispersal.

Plasticity is a characteristic related to phenology and phenotype. Phenology is the timing of phases occurrence in the life cycle, and phenotypic plasticity is the range of phenotypes that a single genotype may express depending on its environment ( Nicotra et al., 2010 ). Plasticity is adaptive when the phenotype changes occur in a direction favored by selection in the new environment.

Climate Change and ROS

Reactive Oxygen Species (ROS) are continuously generated by plants under normal conditions. However, they are increased in response to different abiotic stresses. One of the most important effects of climate change-related stresses at the molecular level is the increase of ROS inside the cells ( Farnese et al., 2016 ). Among ROS, the most studied are superoxide anion ( O 2 •– ), H 2 O 2 and the hydroxyl radical (⋅OH - ).

Reactive Oxygen Species cause damage to proteins, lipids and DNA, affecting cell integrity, morphology, physiology, and, consequently, the growth of plants ( Frohnmeyer and Staiger, 2003 ). The main sources of ROS in stress conditions are: augmented photorespiration, NADPH oxidase (NOX) activity, β-oxidation of fatty acids and disorders in the electron transport chains of mitochondrias and chloroplasts ( Apel and Hirt, 2004 ; AbdElgawad et al., 2015 ). Hence, higher plants have evolved in the presence of ROS and have acquired pathways to protect themselves from its toxicity. Plant antioxidant system (AS) includes the activity of ROS detoxifying enzymes [e.g., superoxide dismutase (SOD), ascorbate peroxidase (APX), catalase (CAT), glutathione peroxidase (GPX), and peroxiredoxin (PRX)], as well as antioxidant molecules such as ascorbic acid (ASC) and glutathione (GSH) that are present in almost all subcellular compartments (reviewed by Choudhury et al., 2017 ).

In this context, plants have also developed a tight interaction between ROS and NO as a mechanism to reduce the deleterious consequences of these ROS-induced oxidative injuries. NO orchestrates a wide range of mechanisms leading to the preservation of redox homeostasis in plants. Consequently, NO at low concentration is considered a broad-spectrum anti-stress molecule ( Lamattina et al., 2003 ; Tossi et al., 2009 ; Correa-Aragunde et al., 2015 ). Figure Figure1 1 shows the relationship among the different GHG and their impact on plants.

An external file that holds a picture, illustration, etc.
Object name is fpls-09-00273-g001.jpg

Simplified scheme showing greenhouse gasses (GHG) and their effects on plants. GHG (H 2 O vapor, clouds, CO 2 , CH 4 , N 2 O, and NO) have both natural and anthropogenic origin, contributing to greenhouse effect. Short-term effects of GHG increase is mainly CO 2 rise, that activates photosynthesis (PS) and inhibits stomatal opening (SO). Long-term effects of GHG increase are extreme climate changes such as floods, droughts, heat. All of them induce the generation of reactive oxygen species (ROS) and oxidative stress in plants. Nitric oxide (NO) could alleviate oxidative stress by scavenging ROS and/or regulating the antioxidant system (AS). GHG and volatile organic compounds (VOC) react in presence of sunlight (E#) to give tropospheric O 3 . Although tropospheric O 3 is prejudicial for life, stratospheric O 3 is beneficial, because filters harmful UV-B radiation. The size of arrows are representative of the GHG concentration.

CO 2 and NO Contribute to Regulate Redox Homeostasis in Plants

Co 2 increasing: advantages and disadvantages.

Increased CO 2 was suggested to have a “fertilization” effect, because crops would increase their photosynthesis and stomatal conductance in response to elevated CO 2 . This belief was supported by studies performed in greenhouses, laboratory controlled-environment chambers, and transparent field chambers, where emitted CO 2 may be held back and readily controlled ( Drake et al., 1997 ; Markelz et al., 2014 ). However, more realistic results, obtained by Free-Air Concentration Enrichment (FACE) technology, suggest that the fertilization response due to CO 2 increase is probably dependent on genetic and environmental factors, and the duration of the study ( Smith and Dukes, 2013 ). An extensive review of the literature in this field made by Xu et al. (2015) concluded that augmented CO 2 normally increases photosynthesis in C3 species such as rice, soybean and wheat. On the other hand, they pointed out that a negative feedback of photosynthesis could take place in augmented CO 2 , as a result of overload of chemical and reactive generated substrates, leading to an imbalance in the sink:source carbon ratio. Moreover, the energetic cost of carbohydrate exportation increases in elevated CO 2 level.

The most important photosynthetic enzyme is the ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO). Rubisco is located in mesophyll cells of C3 plants, in direct contact with the intercellular air space linked to the atmosphere by epidermal stomatal pores. Photosynthesis increases at high CO 2 , because Rubisco is not CO 2 saturated and CO 2 inhibits the oxygenation reactions and photorespiration ( Long et al., 2006 ). However, long-term high concentration of CO 2 may down regulate Rubisco activity because ribulose-1,5-bisphosphate is not regenerated. Hexokinase (HXK), a sensor of extreme photosynthate, may participate in the down regulation of Rubisco concentration ( Xu et al., 2015 ). Moreover, severe abiotic stresses, such as temperature and drought, may restrain Rubisco carboxylation and foster oxygenation ( Xu et al., 2015 ).

In C4 crops, such as maize and sorghum, the elevated concentration of CO 2 inside the bundle sheath cells could prevent a large increase of Rubisco activity at higher atmospheric CO 2 and, thereby, photosynthetic activity is not augmented. However, at high CO 2 levels, the water status of C4 plants under drought conditions is improved, increasing photosynthesis and biomass accumulation ( Long et al., 2006 ; Mittler and Blumwald, 2010 ). That envisages potential advantages for the C4 species in future climatic change scenarios, particularly in arid and semiarid areas.

In addition, high CO 2 has the benefit of reducing stomatal conductance, decreasing 10% evapotranspiration in both C3 and C4 plants. Simultaneously, the cooling decreased resulting from reduced transpiration causes elevated canopy temperatures of around 0.7°C for most crops. Biomass and yield rise due to high CO 2 in all C3 plants, but not in C4 plants exception made when water is a restraint. Yields of C3 grain crops jump around 19% on average at high CO 2 ( Kimball, 2016 ).

Some reports analyze the contribution of CO 2 in the responses of plants to the combination of multiple stresses. For Arabidopsis thaliana , the combination of heat and drought induces photosynthesis inhibition of 62% under ambient CO 2 , but the drop in photosynthesis is just 40% at high CO 2 . Moreover, the protein oxidation increases significantly during a heat wave and drought, and this effect is repressed by increased CO 2 . Photorespiration is also reduced by high CO 2 ( Zinta et al., 2014 ).

Studying grasses ( Lolium perenne, Poa pratensis ) and legumes ( Medicago lupulina, Lotus corniculatus ) exposed to drought, high temperature and augmented CO 2 , AbdElgawad et al. (2015) demonstrated that drought suppresses plant growth, photosynthesis and stomatal conductance, and promotes in all species the synthesis of osmolytes and antioxidants. Instead, oxidative damage is more markedly observed in legumes than in grasses. In general, warming amplifies drought consequences. In contrast, augmented CO 2 diminishes stress impact. Reduction in photosynthesis and chlorophyll, as a result of drought and elevated temperature, were avoided by high CO 2 in the grasses. Noxious effects of oxidative stress, i.e., lipid peroxidation, are phased down in all species by augmented CO 2 . Normally, a reduced impact of oxidative stress is due to decreased photorespiration and diminished NOX activity. In legumes, a rise in levels of antioxidant molecules (flavonoids and tocopherols) contribute as well to the stress mitigation caused by augmented CO 2 . The authors draw the conclusion that these different responses point at an unequal future impact of climate change on the production of agricultural-scale legumes and grass crops.

Kumari et al. (2015) assessed the impact of various levels of CO 2 , ambient (382 ppm) and augmented (570 ppm), and O 3 , ambient (50 ppb) and augmented (70 ppb) on the potato physiological and biochemical responses ( Solanum tuberosum ). They observed that augmented CO 2 cut down O 3 uptake, enhanced carbon assimilation, and curbed oxidative stress. Elevated CO 2 also mitigated the noxious effect of high O 3 on photosynthesis.

Although some molecular mechanisms underpinning CO 2 actions are unknown, the results presented highlight the importance of CO 2 as a regulator that mitigates the potential climate change-induced deleterious consequences in plants. Recent reports suggest that some CO 2 -associated responses may be mediated by NO.

Du et al. (2016) determined that 800 μmol.mol -1 of CO 2 increased the NO concentration in Arabidopsis leaves, through a mechanism related to nitrate availability. Moreover, NO increase, as a consequence of high CO 2 levels, was reported as a general procedure to improve iron (Fe) nutrition in response to Fe deficiency in tomato roots ( Jin et al., 2009 ).

The gas exchange between the atmosphere and plants is mainly regulated by stomata. But structure and physiology of stomata are also influenced by gasses ( García-Mata and Lamattina, 2013 ). Elevated CO 2 regulate stomatal density and conductance. Moreover, there is increasing evidence that this response is modified by interaction of CO 2 with other environmental factors ( Xu et al., 2016 ; Yan et al., 2017 ). Wang et al. (2015) reported that 800 μmol.mol -1 of CO 2 increases the NO concentration in A. thaliana guard cells, inducing stomatal closure. Both NR and NO synthase (NOS)-like activities are necessary for CO 2 -induced NO accumulation. Comprehensive pharmacological and genetic results obtained in Arabidopsis by Chater et al. (2015) , show that when CO 2 concentration is around 700–1000 ppm, stomatal density and closure are reduced. They also illustrate that those elements necessary for this process are: activation of both ABA biosynthesis genes and the PYR/RCAR ABA receptor, and ROS increase. However, Shi et al. (2015) provide genetic and pharmacological evidence that high CO 2 concentration induces stomatal closure by an ABA-independent mechanism in tomato. They show that 800 μmol.mol -1 of CO 2 increase the expression of the protein kinase OPEN STOMATA 1 (OST1), NOX, and nitrate reductase (NR) genes. They also show that the sequential production of NOX-dependent H 2 O 2 and NR-produced NO are mainly dependent of OST1, and are involved in the CO 2 -induced stomatal closure.

In ABA-dependent mechanisms, ABA is increased by CO 2. The binding of ABA to its receptor (PYR/RCAR) inactivates PP2C, activating OST1. In ABA-independent mechanism, OST1 will be transcriptionally induced by CO 2 . Once activated, OST1 along with Ca 2 + , activates NOX, increasing ROS ( Kim et al., 2010 ). The rise of guard cells ROS enhances NO, cytosolic free Ca 2 + , and pH ( Song et al., 2014 ; Xie et al., 2014 ). ROS and NO release Ca 2 + from internal reservoirs, or influx external Ca 2 + through plasma membrane Ca 2 + in channels. Cytosolic free Ca 2 + inactivate inward K + channels (K + in ) to prevent K + uptake and activate outward K + channels (K + out ) and Cl - (anion) channels (Cl - ) at the plasma membrane ( Blatt, 2000 ; García-Mata et al., 2003 ). Ca 2 + also activates slow anion channel homolog 3 (SLAH3), slow anion channel-associated 1 (SLAC1) and aluminum activated malate transporters (ALMT) ( Roelfsema et al., 2012 ). The consequence of the regulation of cation/anion channels is the net efflux of K + /Cl - /malate and influx of Ca 2 + , making guard cells lose turgor by water outlet, causing stomatal closure.

All together, the results discussed here suggest that CO 2 -induced NO increase is a common plant physiological response to oxidative stresses. Figure Figure2 2 shows the importance of CO 2 and NO in these processes.

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Interplay between CO 2 and NO in plant redox physiology: CO 2 enters to the leaves by stomata. Once in mesophyll cells, CO 2 increase photosynthesis (PS) through the CO 2 -unsaturated Rubisco activity. When plants are in stress environments, ROS could be augmented by Rubisco-induced photorespiration and NADPH oxidase (NOX) activities. NOX- induced O 2 •– , in the apoplast is immediately transformed to H 2 O 2 by the superoxide dismutase (SOD). Plasma membrane is permeable to H 2 O 2 . CO 2 moderates oxidative stress in mesophyll cells by inhibiting both Rubisco photorespiration (PR) and NOX activities. Besides, NO is induced by CO 2 and ROS, alleviating the consequences of oxidative stress by scavenging ROS and activating or inhibiting the antioxidant system (AS). In guard cells, CO 2 increases the expression and activity of OPEN STOMATA 1 (OST1), in both ABA-dependent and independent mechanisms. OST1 activates NOX, producing ROS and consequently NO increase by nitrate reductase (NR), and NOS-like activities. NO prevents ROS increase by direct scavenging, and inhibiting NOX. NO-dependent Ca 2 + regulated ion channels induces stomatal closure, modulating O 3 and CO 2 uptake, decreasing evapotranspiration, and rising leaf temperature.

Abiotic Stress, ROS Generation, and Redox Balance: The Key Role of NO

Reactive oxygen species are generated in apoplast, plasma membrane, chloroplasts, mitochondria, and peroxisomes ( Farnese et al., 2016 ). It was proposed that each stress produces its own “ROS signature” ( Choudhury et al., 2017 ). For instance, drought may reduce the activity of Rubisco, decreasing CO 2 fixation and NADP+ regeneration by the Calvin cycle. As a consequence, chloroplast electron transport is altered, generating ROS by electron leakage to O 2 ( Carvalho, 2008 ). In drought stress, ROS increase is produced by NOX activity ( Farnese et al., 2016 ). In flooding, ROS generation is an ethylene-promoted process that involves calcium (Ca 2+ ) flux, and NOX activity ( Voesenek and Bailey-Serres, 2015 ).

In heat stress, a NOX-dependent transient ROS rise is an early event ( Königshofer et al., 2008 ). Then, endogenous ROS are sensed through histidine kinases, and an Arabidopsis heat stress factor (HsfA4a) appears to sense exogenous ROS. As a result, the MAPK signal pathway is activated ( Qu et al., 2013 ). Moreover, functional decrease in photosynthetic light reaction induces ROS concentration by high electron leakage from the thylakoid membrane ( Hasanuzzaman et al., 2013 ). In this process, O 2 is the acceptor, generating O 2 •– .

Thus, individual stresses or their different combinations may produce particular “ROS signatures.” Besides their deleterious effects, ROS are recognized as a signal in the plant reaction to biotic and abiotic stressors. ROS may induce programed cell death (PCD) to avoid pathogen spread ( Mur et al., 2008 ), trigger a systemic defense response signal ( Dubiella et al., 2013 ), or avoid the chloroplast antenna overloading by electrons divert ( Choudhury et al., 2017 ).

Whatever the origin and function, ROS concentration must be adequately regulated to avoid excessive concentration and consequent cellular damages. Depending on NO and ROS concentrations, NO has the dual capacity to activate or inhibit the ROS production, and is a key molecule for keeping cellular redox homeostasis under control ( Beligni and Lamattina, 1999a ; Correa-Aragunde et al., 2015 ). NO has a direct ROS-scavenging activity because it holds an unpaired electron, reaching elevated reactivity with O 2 , O 2 •– , and redox active metals. NO can mitigate OH formation by scavenging either Fe or O 2 •– ( Lamattina et al., 2003 ). However, NO reacting with ROS (mainly O 2 •– ) may generate reactive nitrogen species (RNS). An excess of RNS originates a nitrosative stress ( Corpas et al., 2011 ). To avoid the toxicity of nitrosative stress, NO is stored as GSNO in the cell.

GSH as a Redox Buffer. GSNO as NO Reservoir. SNO and S-Nitrosylation

Glutathione (GSH) is a small peptide with the sequence γ-l-glutamyl-l-cysteinyl-glycine that has a cell redox homeostatic impact in most plant tissues. It is a soluble small thiol considered a non-enzymatic antioxidant. It exists in the reduced (GSH) or oxidized state (GSSG), in which two GSH molecules are joined by a disulfide bond ( Rouhier et al., 2008 ). GSH alleviates oxidative damages in plants generated by abiotic stresses, including salinity, drought, higher, low temperature, and heavy metals. GSH is precursor of phytochelatins, polymers that chelate toxic metals and transport them to the vacuole ( Grill et al., 1989 ). Studies shown that GSH contributes to tolerate nickel, cadmium, zinc, mercury, aluminum and arsenate heavy metals in plants ( Asgher et al., 2017 ). Moreover, GSH has a role in the detoxification of ROS both directly, interacting with them, or indirectly, participating of enzymatic pathways. GSH is involved in glutathionylation, a posttranslational modification that causes a mixed disulfide bond between a Cys residue and GSH.

GSH can be oxidized to GSSG by H 2 O 2 and can react with NO to form the nitrosoglutathione (GSNO) derivative. GSNO is an intracellular NO reservoir. It is also a vehicle of NO throughout the cell and organs, spreading NO biological function. GSNO is the largest low-molecular-mass S-nitrosothiol (SNO) in plant cells ( Corpas et al., 2013 ). GSNO metabolism and its reaction with other molecules involve S-nitrosylation and S-transnitrosation which consist of the binding of a NO molecule to a cysteine residue in proteins. Thioredoxin produces protein denitrosylation ( Correa-Aragunde et al., 2013 ). GSNO could be decomposed by the GSNO reductase (GSNOR) to GSSG which, in turn, is reduced to GSH by glutathione reductase (GR).

Glutathione also participates in the GSH/ASC cycle, a series of enzymatic reactions that degrade H 2 O 2 . APX degrades H 2 O 2 using ASC, the other major antioxidant in plants, as cofactor. The oxidized ASC is reduced by monodehydroascorbate reductase (MDHAR) in an NAD(P)H-dependent manner and by dehydroascorbate reductase (DHAR) employing GSH as electron donor. The resulting GSSG is reduced in turn to GSH by GR ( Foyer and Noctor, 2011 ).

Different Effects of NO in the Regulation of Antioxidant Enzymes

The application of NO donors alleviates oxidative stress in plants challenged to abiotic and/or biotic stresses ( Laxalt et al., 1997 ; Beligni and Lamattina, 1999b , 2002 ; Shi et al., 2007 ; Xue et al., 2007 ; Leitner et al., 2009 ).

Besides the direct ROS-scavenging activity of NO, its beneficial effect is exerted by the regulation of the antioxidant enzymes activity that controls toxic levels of ROS and RNS ( Uchida et al., 2002 ; Shi et al., 2005 ; Song et al., 2006 ; Romero-Puertas et al., 2007 ; Bai et al., 2011 ). NO can modulate cell redox balance in plants through the regulation of gene expression, posttranslational modification or by its binding to the heme prosthetic group of some antioxidant enzymes.

SOD catalyzes the dismutation of stress-generated O 2 •– in one of two less harmful species: either molecular oxygen (O 2 ) or hydrogen peroxide (H 2 O 2 ). APX and CAT are the most important enzymes degrading H 2 O 2 in plants. They transform H 2 O 2 to H 2 O and O 2 . APX isoforms are primarily found in the cytosol and chloroplasts, while the CAT isoforms are found in peroxisomes. APX has strong affinity for H 2 O 2 and uses ASC as an electron donor. In contrast, CAT removes H 2 O 2 generated in the peroxisomal respiratory pathway without the need to reduce power. Even though CAT affinity for H 2 O 2 is low, its elevated rate of reaction offers an effective way to detoxify H 2 O 2 inside the cell. PRX may reduce both hydroperoxide and peroxynitrite.

Many reports on different plant species demonstrate that NO induces the transcription and activity of antioxidative enzymes in response to oxidative stress. The tolerance to drought and salt-induced oxidative stress in tobacco is related to the ABA-triggered production of H 2 O 2 and NO. In turn, they induce transcripts and activities of SOD, CAT, APX, and GR ( Zhang et al., 2009 ). UV-B-produced oxidative stress in Glycine max was alleviated by NO donors, which induced transcription and activities of SOD, CAT, and APX ( Santa-Cruz et al., 2014 ). Furthermore, in bean leaves, SOD, CAT, and APX activities are increased by NO donors, and protected from the oxidative stress generated by UV-B irradiation ( Shi et al., 2005 ). Drought tolerance in bermudagrass is improved by ABA-dependent SOD and CAT activities. This effect is regulated by H 2 O 2 and NO, NO acting downstream H 2 O 2 ( Lu et al., 2009 ).

Several antioxidant enzymes have been identified as target of S-nitrosylation, resulting in a change of their biological activity ( Romero-Puertas et al., 2008 ; Bai et al., 2011 ; Fares et al., 2011 ). For instance, NO reinforces recalcitrant seed desiccation tolerance in Antiaris toxicaria by activating the ascorbate-glutathione cycle through S-nitrosylation to control H 2 O 2 accumulation. Desiccation treatment reduced the level of S-nitrosylated APX, GR, and DHAR proteins. Instead, NO gas exposure activated them by S-nitrosylation ( Bai et al., 2011 ). Furthermore, APX was S-nitrosylated at Cys32 during saline stress and biotic stress, enhancing its enzymatic activity ( Begara-Morales et al., 2014 ; Yang et al., 2015 ). In addition, auxin-induced denitrosylation of cytosolic APX provoked inhibition of its activity, followed by an increase of H 2 O 2 concentration and the consequent lateral root formation in Arabidopsis ( Correa-Aragunde et al., 2013 ). Moreover, an inhibitory impact of S-nitrosylation on APX activity was also reported during programmed cell death in Arabidopsis ( de Pinto et al., 2013 ). CAT was identified to be S-nitrosylated in a proteomic study of isolated peroxisomes ( Ortega-Galisteo et al., 2012 ). A decrease of S-nitrosylated CAT under Cd treatment was reported. In addition, in vitro experiments demonstrated a reversible inhibitory effect of APX and CAT activities by NO binding to the Fe of the heme cofactor ( Brown, 1995 ; Clark et al., 2000 ). In addition, NOXs have been involved in plant defense, development, hormone biosynthesis and signaling ( Marino et al., 2012 ). Whereas S-nitrosylation did not affect SOD activities, nitration inhibited Mn-SOD1, Fe-SOD3, and CuZn-SOD3 activity to different degrees ( Holzmeister et al., 2015 ). SOD isoforms could also regulate endogenous NO availability by competing for the common substrate, O 2 •– , and it was demonstrated that bovine SOD may release NO from GSNO ( Singh et al., 1999 ). When GSNO is decomposed by GSNOR, it produces GSSG. GSNOR is also regulated by NO. Frungillo et al. (2014) demonstrated that NO-derived from nitrate assimilation in Arabidopsis inhibited GSNOR1 by S-nitrosylation, preventing GSNO degradation. They proposed that (S)NO controls its own generation and scavenging by modulating nitrate assimilation and GSNOR1 activity. It was also shown that chilling treatment in poplar increased S-nitrosylation of NR, along with a significant decrease of its activity ( Cheng et al., 2015 ).

The dual activity of Prx, suggests a role for this enzyme both in ROS and RNS regulation. S-nitrosylation of Arabidopsis PrxIIE inhibits its peroxynitrite activity, increasing peroxynitrite-mediated tyrosine nitration ( Romero-Puertas et al., 2007 ). Pea mitochondrial PrxIIF was S-nitrosylated under salt stress, and its peroxidase activity was reduced by 5 mM GSNO ( Camejo et al., 2013 ).

An interesting study demonstrated that NO controls hypersensitive response (HR) through S-nitrosylation of NOX, inhibiting ROS synthesis. This triggers a feedback loop limiting HR ( Yun et al., 2011 ).

Other proteins related to abiotic stress response are regulated by S-nitrosylation (For a review see Fancy et al., 2017 ).

Figure Figure3 3 is a simplified diagram that illustrates the main oxidative and nitrosative effects that modulate the activities of key cell components, thus maintaining cell redox balance. Note the feedback and positive-negative regulatory processes occurring in the main pathways. They involve posttranslational modifications that activate and inhibit the components involved in cell antioxidant system.

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Molecules and mechanisms involved in NO-mediated redox balance. H 2 O 2 is generated mainly by NOX and SOD as a response to (a)biotic stress. APX and CAT are the main H 2 O 2 -degrading enzymes. NO is increased by H 2 O 2 through the induction of NR/NOS-like activities, and may scavenge ROS or induce both the transcription and activity of SOD, CAT, and APX. In parallel, NO is combined with GSH to form nitrosoglutathione GSNO. GSNO regulates many enzymatic activities by the posttranslational modification of cysteine residues through S-Nitrosylation. NOX and CAT activities are inhibited by S-nitrosylation, whereas APX is either activated or inhibited by S-nitrosylation. NO also inhibits APX by binding to heme group. GSNO is degraded by GSNOR, which could be inhibited by H 2 O 2 and S-nitrosylation.NR could be inhibited by S-nitrosylation. GR reduces GSSG to GSH, and it is activated by S-nitrosylation. Ascorbate (ASC) is a cofactor of APX. Reduced ASC is generated by MDHAR and DHAR, using GSH as electron donor. Both enzymes are inhibited by S-nitrosylation. Reactive Nitrogen Species (RNS) may be originated by NO and O 2 •– reaction. SOD regulate RNS dismutating O 2 •– . Peroxiredoxins (Prx) reduce both ROS AND RNS. RNS are degraded by PrxIIe, and H 2 O 2 by PrxIIF. Both enzymes are inhibited by S-nitrosylation. Red lines: H 2 O 2 -regulated reactions. Purple lines: NO-regulated reactions. Green lines: GSNO-regulated reactions.

Conclusions and Perspectives

The accelerating rate of climate change, together with habitat fragmentation caused by human activity, are part of the selective pressures building a new Earth’s landscape.

Climate change is a multidimensional and simultaneous variation in duration, frequency and intensity of parameters like temperature and precipitation, altering the seasons and life on the Earth. In this scenario, plant species with increased adaptive plasticity will be better equipped to tolerate changes in the frequency of extreme weather events. GHG are one of the forces driving climate change. However, CO 2 and NO may contribute to maintaining the cell redox homeostasis, regulating the amount of ROS, GSH, GSNO, and SNO.

In this manuscript, we summarize the available evidence supporting the presence of broad spectrum anti-stress molecules, as NO in plants, for coping with unprecedented changes in environmental conditions. Future research should focus in better understanding the influence of GHG on plant physiology.

Author Contributions

RC conceived the project and wrote the manuscript. MN drew figures and collaborated in writing the manuscript. NC-A and LL supervised and complemented the drafting. All the persons entitled to authorship have been named and have approved the final version of the submitted manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MCR-P and handling Editor declared their shared affiliation.

Acknowledgments

We thank ANPCYT for MN fellowship. We also thank Marta Terrazo for helping with the language revision of the manuscript.

Funding. This work was supported by grants from the Consejo Nacional de Investigaciones Cientificas y Tecnicas, the Agencia Nacional de Promoción Científica y Tecnológica, and the Universidad Nacional de Mar del Plata, Argentina. NC-A, LL, and RC are permanent members of the Scientific Research career of CONICET. MN is doctoral fellow of the ANPCYT.

1 https://ozonewatch.gsfc.nasa.gov/facts/ozone.html

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OpenAI Offers a Peek Inside the Guts of ChatGPT

ChatGPT developer OpenAI’s approach to building artificial intelligence came under fire this week from former employees who accuse the company of taking unnecessary risks with technology that could become harmful.

Today, OpenAI released a new research paper apparently aimed at showing it is serious about tackling AI risk by making its models more explainable. In the paper , researchers from the company lay out a way to peer inside the AI model that powers ChatGPT. They devise a method of identifying how the model stores certain concepts—including those that might cause an AI system to misbehave.

Although the research makes OpenAI’s work on keeping AI in check more visible, it also highlights recent turmoil at the company. The new research was performed by the recently disbanded “superalignment” team at OpenAI that was dedicated to studying the technology’s long-term risks.

The former group’s coleads, Ilya Sutskever and Jan Leike—both of whom have left OpenAI —are named as coauthors. Sutskever, a cofounder of OpenAI and formerly chief scientist, was among the board members who voted to fire CEO Sam Altman last November, triggering a chaotic few days that culminated in Altman’s return as leader.

ChatGPT is powered by a family of so-called large language models called GPT, based on an approach to machine learning known as artificial neural networks. These mathematical networks have shown great power to learn useful tasks by analyzing example data, but their workings cannot be easily scrutinized as conventional computer programs can. The complex interplay between the layers of “neurons” within an artificial neural network makes reverse engineering why a system like ChatGPT came up with a particular response hugely challenging.

“Unlike with most human creations, we don’t really understand the inner workings of neural networks,” the researchers behind the work wrote in an accompanying blog post . Some prominent AI researchers believe that the most powerful AI models, including ChatGPT, could perhaps be used to design chemical or biological weapons and coordinate cyberattacks. A longer-term concern is that AI models may choose to hide information or act in harmful ways in order to achieve their goals.

OpenAI’s new paper outlines a technique that lessens the mystery a little, by identifying patterns that represent specific concepts inside a machine learning system with help from an additional machine learning model. The key innovation is in refining the network used to peer inside the system of interest by identifying concepts, to make it more efficient.

OpenAI proved out the approach by identifying patterns that represent concepts inside GPT-4, one of its largest AI models. The company released code related to the interpretability work, as well as a visualization tool that can be used to see how words in different sentences activate concepts, including profanity and erotic content, in GPT-4 and another model. Knowing how a model represents certain concepts could be a step toward being able to dial down those associated with unwanted behavior, to keep an AI system on the rails. It could also make it possible to tune an AI system to favor certain topics or ideas.

The Snowflake Attack May Be Turning Into One of the Largest Data Breaches Ever

By Matt Burgess

Microsoft’s Recall Feature Is Even More Hackable Than You Thought

By Andy Greenberg

Microsoft Will Switch Off Recall by Default After Security Backlash

By Matthew Gault

Even though LLMs defy easy interrogation, a growing body of research suggests they can be poked and prodded in ways that reveal useful information. Anthropic, an OpenAI competitor backed by Amazon and Google, published similar work on AI interpretability last month. To demonstrate how the behavior of AI systems might be tuned, the company's researchers created a chatbot obsessed with San Francisco's Golden Gate Bridge . And simply asking an LLM to explain its reasoning can sometimes yield insights .

“It’s exciting progress,” says David Bau , a professor at Northeastern University who works on AI explainability, of the new OpenAI research. “As a field, we need to be learning how to understand and scrutinize these large models much better.”

Bau says the OpenAI team’s main innovation is in showing a more efficient way to configure a small neural network that can be used to understand the components of a larger one. But he also notes that the technique needs to be refined to make it more reliable. “There’s still a lot of work ahead in using these methods to create fully understandable explanations,” Bau says.

Bau is part of a US government-funded effort called the National Deep Inference Fabric , which will make cloud computing resources available to academic researchers so that they too can probe especially powerful AI models. “We need to figure out how we can enable scientists to do this work even if they are not working at these large companies,” he says.

OpenAI’s researchers acknowledge in their paper that further work needs to be done to improve their method, but also say they hope it will lead to practical ways to control AI models. “We hope that one day, interpretability can provide us with new ways to reason about model safety and robustness, and significantly increase our trust in powerful AI models by giving strong assurances about their behavior,” they write.

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Broadband Internet Access, Economic Growth, and Wellbeing

Between 2000 and 2008, access to high-speed, broadband internet grew significantly in the United States, but there is debate on whether access to high-speed internet improves or harms wellbeing. We find that a ten percent increase in the proportion of county residents with access to broadband internet leads to a 1.01 percent reduction in the number of suicides in a county, as well as improvements in self-reported mental and physical health. We further find that this reduction in suicide deaths is likely due to economic improvements in counties that have access to broadband internet. Counties with increased access to broadband internet see reductions in poverty rate and unemployment rate. In addition, zip codes that gain access to broadband internet see increases in the numbers of employees and establishments. In addition, heterogeneity analysis indicates that the positive effects are concentrated in the working age population, those between 25 and 64 years old. This pattern is precisely what is predicted by the literature linking economic conditions to suicide risk.

We are grateful to participants at the Association of Public Policy and Management and the Washington Area Labor Symposium conferences for their helpful comments. Any errors or conclusions are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

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Staff Working Papers Working Paper 24-03: The Lock-In Effect of Rising Mortgage Rates

Ross M. Batzer, Jonah R. Coste, William M. Doerner, and Michael J. Seiler

Abstract:

People can be “locked-in” or constrained in their ability to make appropriate financial changes, such as being unable to move homes, change jobs, sell stocks, rebalance portfolios, shift financial accounts, adjust insurance policies, transfer investment profits, or inherit wealth. These frictions—whether institutional, legislative, personal, or market-driven—are often overlooked. Residential real estate exemplifies this challenge with its physical immobility, high transaction costs, and concentrated wealth. In the United States, nearly all 50 million active mortgages have fixed rates, and most have interest rates far below prevailing market rates, creating a disincentive to sell. This paper finds that for every percentage point that market mortgage rates exceed the origination interest rate, the probability of sale is decreased by 18.1%. This mortgage rate lock-in led to a 57% reduction in home sales with fixed-rate mortgages in 2023Q4 and prevented 1.33 million sales between 2022Q2 and 2023Q4. The supply reduction increased home prices by 5.7%, outweighing the direct impact of elevated rates, which decreased prices by 3.3%. These findings underscore how mortgage rate lock-in restricts mobility, results in people not living in homes they would prefer, inflates prices, and worsens affordability. Certain borrower groups with lower wealth accumulation are less able to strategically time their sales, worsening inequality.

Mortgage lock-in data are available below in two formats at the bottom of this webpage. The first file offers a data supplement that could be used to recreate figures shown in the working paper. The second file offers additional developmental data aggregates produced from estimations in the working paper. Both files are subject to change with working paper revisions. Our FAQs address common questions about the datasets. Please cite this working paper when using either dataset.

Supplemental data for figures (1 MB)
Developmental data aggregates (45 MB)

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F. Goltz presenting new research on the construction of climate portfolios at our recent conference
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Design, technology, and management of greenhouse: A review
Other research on greenhouse multi-span demonstrates that as the number of spans increases, so does the ventilation rate, demonstrating a falling link between the two metrics, and multi-span has a lower differential between windward and leeward roof pressures (Chu et al., 2017; Dayan et al., 1993; Kacira et al., 2004; Lee et al., 2016; Ogunlowo ...
(PDF) Greenhouse design: Concepts and trends
environmental effects. The term "greenhous e design" includes too many aspects to. be covered in one paper, therefore, this paper mainly addresses developments. related to possible effects of ...
(PDF) Greenhouse Effect: Greenhouse Gases and Their ...
The clear effect of the greenhouse gases is the. stable heating of Earth's atmosphere and surface, thus, global warming. The abi lity of certain gases, greenhouse gases, to be transparent to ...
(PDF) GREENHOUSE TECHNOLOGY: INTRODUCTION, TYPE AND PLANNING
GREENHOUSE TECHNOLOGY: INTRODUCTION, TYPE AND PLANNING. January 2022. In book: Recent Advances in Agricultural Science and Technology for Sustainable India Part-I (pp.11-18) Publisher: Mahima ...
The Greenhouse Effect: Science and Policy
Abstract. Global warming from the increase in greenhouse gases has become a major scientific and political issue during the past decade. That infrared radiation is trapped by greenhouse gases and particles in a planetary atmosphere and that the atmospheric CO 2 level has increased by some 25 percent since 1850 because of fossil fuel combustion ...
PDF The Greenhouse Effect: Science and Policy
The greenhouse effect, despite all the controversy that surrounds the term, is actually one of the most well-established theories in atmospheric science. For example, with its dense CO2 atmosphere, Venus has temperatures near 700 K at its surface. Mars, with its very thin CO2 atmosphere, has temperatures of only 220 K.
(PDF) Automation and monitoring of greenhouse
Automation and monitoring of greenhouse. December 2017. December 2017. DOI: 10.1109/ICICT.2017.8320190. Conference: 2017 International Conference on Information and Communication Technologies ...
Robotics in greenhouses. Scoping review
The classification diagram (Fig. 3) is proposed to present a clear and well-defined picture and to make it easier to understand the different technologies applied to robots for greenhouses, their interactions and relationships in each research paper. 2.1. Context. The research papers were classified into four broad categories based on the ...
Greenhouse emission reduction and sustainable development
Greenhouse emission reduction and sustainable development. December 2003. International Journal of Social Economics 30 (12):1233-1248. DOI: 10.1108/03068290310500643. Authors: R. Sathiendrakumar ...
Developing a Modern Greenhouse Scientific Research Facility—A ...
In this paper, we present the system architecture and design of a modern scientific greenhouse research facility for the purpose of Croatian Science Foundation's Project Urtica—BioFuture. Several sensor nodes are proposed in different locations: nutrient solution, environmental (inside and outside the greenhouse), and sensor nodes for ...
(PDF) Greenhouse Effect: Greenhouse Gases and Their Impact on Global
The greenhouse effect was first discovered by Joseph Fourier in 1827, experimentally verified by John Tyndall in 1861, and quantified by Svante Arrhenius in 1896 [5]. [6] has published a paper on (A Synopsis on the Effects of Anthropogenic Greenhouse Gases Emissions from Power Generation and Energy Consumption).
Journal of Geophysical Research: Biogeosciences
1 Introduction. The most recent report by the Intergovernmental Panel on Climate Change stated that increases in well-mixed greenhouse gases such as carbon dioxide (CO 2), methane (CH 4), and nitrous oxide (N 2 O) have contributed 1.0-2.0°C of warming to Earth's climate in the past century (IPCC, 2021).After CO 2, CH 4 is the largest contributor, with a global warming potential 84-86 ...
Design, technology, and management of greenhouse: A review
This paper presents an overview of current design trends in construction, current development technology for controlling and monitoring greenhouse microclimates, and the various systems available for managing greenhouse environments. First, it discusses different processes of the greenhouse geometry, orientation, and cladding material for ...
Abrupt reduction in shipping emission as an inadvertent ...
303 See Other. openresty
Can Sovereign Green Bonds Accelerate the Transition to Net ...
This paper focuses on sovereign green bonds issued in Europe. By issuing green bonds, European governments commit themselves to realizing environmentally friendly projects and encourage other entities, including private-sector ones, to do the same, thus increasing further domestic investments in addressing climate change. However, considering that governments could pursue their sustainable ...
Assessment of Ammonia Emissions and Greenhouse Gases in Dairy ...
A deeper understanding of gas emissions in milk production is crucial for promoting productive efficiency, sustainable resource use, and animal welfare. This paper aims to analyze ammonia and greenhouse gas emissions in dairy farming using bibliometric methods. A total of 187 English-language articles with experimental data from the Scopus and Web of Science databases (January 1987 to April ...
Greenhouse Gas Emissions
Research Papers: Greenhouse Gas Emissions Climate Policy Decisions Require Policy-Based Lifecycle Analysis. ... 2014. Lifecycle analysis (LCA) metrics of greenhouse gas emissions are increasingly being used to select technologies supported by climate policy. However, LCAs typically evaluate the emissions associated with a technology or product ...
PDF Abstract: Keywords: Greenhouse Environment, Sensors, Control ...
Green House Environment Monitoring and Control System. Anuradha A. Pandit1 and Avinash V. Mancharkar2. 1Department of Physics, Ahmednagar College, Ahmednagar- 414001, INDIA. 2Department of Physics, New Arts, Commerce and Science College, Parner- 414302, INDIA. Abstract: Greenhouse Environment, used to grow plants under controlled climatic ...
Departmental Papers
Following the 2022 energy crisis, this paper investigates whether Europe's ongoing efforts to cut greenhouse gas emissions can also enhance its energy security. The global computational general equilibrium model analysis finds that individual policy tools, including carbon pricing, energy efficiency standards, and accelerated permitting procedures for renewables, tend to improve energy security.
Emissions of greenhouse gases and climate change
Despi te a growing. number of policies to mitigate climate change, the annual GHG emissions grew on. average 0,4 giga ton s of ca rbon dioxide equivalent (GtCO2eq) (1,3 %) per year from. 1970 ...
Sustainable approach of biological treatment of landfill leachate by
This paper reviewed several published research works in Scopus dealing with the leachate treatment by Anammox process combined with some other systems and highlighted some common challenges found with the application of this new technology. Treating landfill leachate resulted in an excellent ammonium NH 4 +-N removal efficiency. However, it has ...
European Journal of Operational Research
The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making. EJOR …. View full aims & scope. $3290. Article publishing charge.
New Paper Redefining Characteristics of Lightning-Initiated ...
Twenty-six years of lightning data were paired with over 68,000 LIW reports to understand lightning flash characteristics responsible for ignition in between 1995 and 2020. Results indicate that 92% of LIW were started by negative cloud-to-ground (CG) lightning flashes and 57% were single stroke flashes. Moreover, 62% of LIW reports did not ...
Researchers plan to retract landmark Alzheimer's paper containing
A version of this story appeared in Science, Vol 384, Issue 6700. Authors of a landmark Alzheimer's disease research paper published in Nature in 2006 have agreed to retract the study in response to allegations of image manipulation. University of Minnesota (UMN) Twin Cities neuroscientist Karen Ashe, the paper's senior author, acknowledged ...
Climate Change and the Impact of Greenhouse Gasses: CO
Life on Earth is possible thanks to greenhouse effect. Without it, temperature on Earth's surface would be around -19°C, instead of the current average of 14°C. Greenhouse effect is produced by greenhouse gasses (GHG) like water vapor, carbon dioxide (CO 2), methane (CH 4), nitrous oxides (N x O) and ozone (O 3). GHG have natural and ...
Software that detects 'tortured acronyms' in research papers ...
In 2022, IOPP retracted nearly 500 papers from conference proceedings after the PPS flagged tortured phrases in the papers. When Eggleton and her team investigated, they found reams of other problems—fake identity, citation cartels in which researchers insert irrelevant references to one another, and even entirely fabricated research.
OpenAI Offers a Peek Inside the Guts of ChatGPT
Days after former employees said the company was being too reckless with its technology, OpenAI released a research paper on a method for reverse engineering the workings of AI models.
Broadband Internet Access, Economic Growth, and Wellbeing
Broadband Internet Access, Economic Growth, and Wellbeing. Kathryn R. Johnson & Claudia Persico. Working Paper 32517. DOI 10.3386/w32517. Issue Date May 2024. Between 2000 and 2008, access to high-speed, broadband internet grew significantly in the United States, but there is debate on whether access to high-speed internet improves or harms ...
Studies on environmental control of greenhouse for crop production
Environmental control can be achieved if greenhouse is designed. accordingly by considering the optimum responses of the crop. Since the natural environment and the. in put availability may not be ...
Working Paper 24-03: The Lock-In Effect of Rising Mortgage Rates
This paper finds that for every percentage point that market mortgage rates exceed the origination interest rate, the probability of sale is decreased by 18.1%. This mortgage rate lock-in led to a 57% reduction in home sales with fixed-rate mortgages in 2023Q4 and prevented 1.33 million sales between 2022Q2 and 2023Q4.

Greenhouse Effect: Greenhouse Gases and Their Impact on Global Warming

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Can Sovereign Green Bonds Accelerate the Transition to Net-Zero Greenhouse Gas Emissions?

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Introduction

Literature Review

Recent Growth in Sovereign Green Bond Issuances

Empirical Analysis

Main Hurdles to the Issuance of Sovereign Green Bonds

Conclusions

Data Availability

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Sustainable approach of biological treatment of landfill leachate by Anaerobic Ammonium Oxidation: A review

Climate Change and the Impact of Greenhouse Gasses: CO 2 and NO, Friends and Foes of Plant Oxidative Stress

Introduction

GHG Contribute Differentially to Greenhouse Effect

Carbon Dioxide (CO 2 )

Methane (CH 4 )

Nitrous Oxides (NxO)

NO Sources and Chemical Reactions in Plants

Ozone (O 3 )

Global Climate Change: an Integrative Balance of the Impact on Plants

Climate Change and ROS

CO 2 and NO Contribute to Regulate Redox Homeostasis in Plants

Abiotic Stress, ROS Generation, and Redox Balance: The Key Role of NO

GSH as a Redox Buffer. GSNO as NO Reservoir. SNO and S-Nitrosylation

Different Effects of NO in the Regulation of Antioxidant Enzymes

Conclusions and Perspectives

Author Contributions

Conflict of Interest Statement

Acknowledgments

OpenAI Offers a Peek Inside the Guts of ChatGPT

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