While controls over the Earth's climate system have undergone rigorous hypothesis-testing since the 1800s, questions over the scientific consensus of the role of human activities in modern climate change continue to arise in public settings. We update previous efforts to quantify the scientific consensus on climate change by searching the recent literature for papers sceptical of anthropogenic-caused global warming. From a dataset of 88125 climate-related papers published since 2012, when this question was last addressed comprehensively, we examine a randomized subset of 3000 such publications. We also use a second sample-weighted approach that was specifically biased with keywords to help identify any sceptical peer-reviewed papers in the whole dataset. We identify four sceptical papers out of the sub-set of 3000, as evidenced by abstracts that were rated as implicitly or explicitly sceptical of human-caused global warming. In our sample utilizing pre-identified sceptical keywords we found 28 papers that were implicitly or explicitly sceptical. We conclude with high statistical confidence that the scientific consensus on human-caused contemporary climate change—expressed as a proportion of the total publications—exceeds 99% in the peer reviewed scientific literature.
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Environmental Research Letters covers all of environmental science, providing a coherent and integrated approach including research articles, perspectives and review articles.
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Mark Lynas et al 2021 Environ. Res. Lett. 16 114005
Seth Wynes and Kimberly A Nicholas 2017 Environ. Res. Lett. 12 074024
Current anthropogenic climate change is the result of greenhouse gas accumulation in the atmosphere, which records the aggregation of billions of individual decisions. Here we consider a broad range of individual lifestyle choices and calculate their potential to reduce greenhouse gas emissions in developed countries, based on 148 scenarios from 39 sources. We recommend four widely applicable high-impact (i.e. low emissions) actions with the potential to contribute to systemic change and substantially reduce annual personal emissions: having one fewer child (an average for developed countries of 58.6 tonnes CO2-equivalent (tCO2e) emission reductions per year), living car-free (2.4 tCO2e saved per year), avoiding airplane travel (1.6 tCO2e saved per roundtrip transatlantic flight) and eating a plant-based diet (0.8 tCO2e saved per year). These actions have much greater potential to reduce emissions than commonly promoted strategies like comprehensive recycling (four times less effective than a plant-based diet) or changing household lightbulbs (eight times less). Though adolescents poised to establish lifelong patterns are an important target group for promoting high-impact actions, we find that ten high school science textbooks from Canada largely fail to mention these actions (they account for 4% of their recommended actions), instead focusing on incremental changes with much smaller potential emissions reductions. Government resources on climate change from the EU, USA, Canada, and Australia also focus recommendations on lower-impact actions. We conclude that there are opportunities to improve existing educational and communication structures to promote the most effective emission-reduction strategies and close this mitigation gap.
John Cook et al 2013 Environ. Res. Lett. 8 024024
We analyze the evolution of the scientific consensus on anthropogenic global warming (AGW) in the peer-reviewed scientific literature, examining 11 944 climate abstracts from 1991–2011 matching the topics 'global climate change' or 'global warming'. We find that 66.4% of abstracts expressed no position on AGW, 32.6% endorsed AGW, 0.7% rejected AGW and 0.3% were uncertain about the cause of global warming. Among abstracts expressing a position on AGW, 97.1% endorsed the consensus position that humans are causing global warming. In a second phase of this study, we invited authors to rate their own papers. Compared to abstract ratings, a smaller percentage of self-rated papers expressed no position on AGW (35.5%). Among self-rated papers expressing a position on AGW, 97.2% endorsed the consensus. For both abstract ratings and authors' self-ratings, the percentage of endorsements among papers expressing a position on AGW marginally increased over time. Our analysis indicates that the number of papers rejecting the consensus on AGW is a vanishingly small proportion of the published research.
John Cook et al 2016 Environ. Res. Lett. 11 048002
The consensus that humans are causing recent global warming is shared by 90%–100% of publishing climate scientists according to six independent studies by co-authors of this paper. Those results are consistent with the 97% consensus reported by Cook et al (Environ. Res. Lett. 8 024024) based on 11 944 abstracts of research papers, of which 4014 took a position on the cause of recent global warming. A survey of authors of those papers (N = 2412 papers) also supported a 97% consensus. Tol (2016 Environ. Res. Lett. 11 048001) comes to a different conclusion using results from surveys of non-experts such as economic geologists and a self-selected group of those who reject the consensus. We demonstrate that this outcome is not unexpected because the level of consensus correlates with expertise in climate science. At one point, Tol also reduces the apparent consensus by assuming that abstracts that do not explicitly state the cause of global warming ('no position') represent non-endorsement, an approach that if applied elsewhere would reject consensus on well-established theories such as plate tectonics. We examine the available studies and conclude that the finding of 97% consensus in published climate research is robust and consistent with other surveys of climate scientists and peer-reviewed studies.
William F Lamb et al 2021 Environ. Res. Lett. 16 073005
Global greenhouse gas (GHG) emissions can be traced to five economic sectors: energy, industry, buildings, transport and AFOLU (agriculture, forestry and other land uses). In this topical review, we synthesise the literature to explain recent trends in global and regional emissions in each of these sectors. To contextualise our review, we present estimates of GHG emissions trends by sector from 1990 to 2018, describing the major sources of emissions growth, stability and decline across ten global regions. Overall, the literature and data emphasise that progress towards reducing GHG emissions has been limited. The prominent global pattern is a continuation of underlying drivers with few signs of emerging limits to demand, nor of a deep shift towards the delivery of low and zero carbon services across sectors. We observe a moderate decarbonisation of energy systems in Europe and North America, driven by fuel switching and the increasing penetration of renewables. By contrast, in rapidly industrialising regions, fossil-based energy systems have continuously expanded, only very recently slowing down in their growth. Strong demand for materials, floor area, energy services and travel have driven emissions growth in the industry, buildings and transport sectors, particularly in Eastern Asia, Southern Asia and South-East Asia. An expansion of agriculture into carbon-dense tropical forest areas has driven recent increases in AFOLU emissions in Latin America, South-East Asia and Africa. Identifying, understanding, and tackling the most persistent and climate-damaging trends across sectors is a fundamental concern for research and policy as humanity treads deeper into the Anthropocene.
Kerstin K Zander et al 2018 Environ. Res. Lett. 13 084009
The world's population is increasingly urban, with more than half the global population already living in cities. The urban population is particularly affected by increasing temperatures because of the urban heat island (UHI) effect. Increasing temperatures cause heat stress in people, even when not directly exposed to heat, since outdoor meteorological conditions also affect conditions inside, particularly in non-air-conditioned environments. Heat stress harms people's health, can impair their well-being and productivity, and may cause substantial economic losses. In this study, we investigate how people in urban areas across the Philippines are affected by heat, using data from 1161 responses obtained through an online survey. We found that almost all respondents (91%) are already experiencing heat stress quite severely and that the level of heat stress is correlated with population density. Controlling, in a multiple log it model, for variables commonly associated with heat stress, such as age, health, physical exertion and climate, we found that those least likely to be severely affected by heat live in areas with fewer than ∼7000 people per km2. Air-conditioning use at home relieved heat stress mostly for people in low-density areas but not where population density was high. The results provide evidence for the social impacts of increasing heat in urban areas, complementing understanding of well-known physical impacts such as the UHI effect.
Geoffrey Supran and Naomi Oreskes 2017 Environ. Res. Lett. 12 084019
This paper assesses whether ExxonMobil Corporation has in the past misled the general public about climate change. We present an empirical document-by-document textual content analysis and comparison of 187 climate change communications from ExxonMobil, including peer-reviewed and non-peer-reviewed publications, internal company documents, and paid, editorial-style advertisements ('advertorials') in The New York Times. We examine whether these communications sent consistent messages about the state of climate science and its implications—specifically, we compare their positions on climate change as real, human-caused, serious, and solvable. In all four cases, we find that as documents become more publicly accessible, they increasingly communicate doubt. This discrepancy is most pronounced between advertorials and all other documents. For example, accounting for expressions of reasonable doubt, 83% of peer-reviewed papers and 80% of internal documents acknowledge that climate change is real and human-caused, yet only 12% of advertorials do so, with 81% instead expressing doubt. We conclude that ExxonMobil contributed to advancing climate science—by way of its scientists' academic publications—but promoted doubt about it in advertorials. Given this discrepancy, we conclude that ExxonMobil misled the public. Our content analysis also examines ExxonMobil's discussion of the risks of stranded fossil fuel assets. We find the topic discussed and sometimes quantified in 24 documents of various types, but absent from advertorials. Finally, based on the available documents, we outline ExxonMobil's strategic approach to climate change research and communication, which helps to contextualize our findings.
Helmut Haberl et al 2020 Environ. Res. Lett. 15 065003
Strategies toward ambitious climate targets usually rely on the concept of 'decoupling'; that is, they aim at promoting economic growth while reducing the use of natural resources and GHG emissions. GDP growth coinciding with absolute reductions in emissions or resource use is denoted as 'absolute decoupling', as opposed to 'relative decoupling', where resource use or emissions increase less so than does GDP. Based on the bibliometric mapping in part I (Wiedenhofer et al, 2020 Environ. Res. Lett. 15 063002), we synthesize the evidence emerging from the selected 835 peer-reviewed articles. We evaluate empirical studies of decoupling related to final/useful energy, exergy, use of material resources, as well as CO2 and total GHG emissions. We find that relative decoupling is frequent for material use as well as GHG and CO2 emissions but not for useful exergy, a quality-based measure of energy use. Primary energy can be decoupled from GDP largely to the extent to which the conversion of primary energy to useful exergy is improved. Examples of absolute long-term decoupling are rare, but recently some industrialized countries have decoupled GDP from both production- and, weaklier, consumption-based CO2 emissions. We analyze policies or strategies in the decoupling literature by classifying them into three groups: (1) Green growth, if sufficient reductions of resource use or emissions were deemed possible without altering the growth trajectory. (2) Degrowth, if reductions of resource use or emissions were given priority over GDP growth. (3) Others, e.g. if the role of energy for GDP growth was analyzed without reference to climate change mitigation. We conclude that large rapid absolute reductions of resource use and GHG emissions cannot be achieved through observed decoupling rates, hence decoupling needs to be complemented by sufficiency-oriented strategies and strict enforcement of absolute reduction targets. More research is needed on interdependencies between wellbeing, resources and emissions.
Christine Shearer et al 2016 Environ. Res. Lett. 11 084011
Nearly 17% of people in an international survey said they believed the existence of a secret large-scale atmospheric program (SLAP) to be true or partly true. SLAP is commonly referred to as 'chemtrails' or 'covert geoengineering', and has led to a number of websites purported to show evidence of widespread chemical spraying linked to negative impacts on human health and the environment. To address these claims, we surveyed two groups of experts—atmospheric chemists with expertize in condensation trails and geochemists working on atmospheric deposition of dust and pollution—to scientifically evaluate for the first time the claims of SLAP theorists. Results show that 76 of the 77 scientists (98.7%) that took part in this study said they had not encountered evidence of a SLAP, and that the data cited as evidence could be explained through other factors, including well-understood physics and chemistry associated with aircraft contrails and atmospheric aerosols. Our goal is not to sway those already convinced that there is a secret, large-scale spraying program—who often reject counter-evidence as further proof of their theories—but rather to establish a source of objective science that can inform public discourse.
Diana Ivanova et al 2020 Environ. Res. Lett. 15 093001
Background. Around two-thirds of global GHG emissions are directly and indirectly linked to household consumption, with a global average of about 6 tCO2eq/cap. The average per capita carbon footprint of North America and Europe amount to 13.4 and 7.5 tCO2eq/cap, respectively, while that of Africa and the Middle East—to 1.7 tCO2eq/cap on average. Changes in consumption patterns to low-carbon alternatives therefore present a great and urgently required potential for emission reductions. In this paper, we synthesize emission mitigation potentials across the consumption domains of food, housing, transport and other consumption. Methods. We systematically screened 6990 records in the Web of Science Core Collections and Scopus. Searches were restricted to (1) reviews of lifecycle assessment studies and (2) multiregional input-output studies of household consumption, published after 2011 in English. We selected against pre-determined eligibility criteria and quantitatively synthesized findings from 53 studies in a meta-review. We identified 771 original options, which we summarized and presented in 61 consumption options with a positive mitigation potential. We used a fixed-effects model to explore the role of contextual factors (geographical, technical and socio-demographic factors) for the outcome variable (mitigation potential per capita) within consumption options. Results and discussion. We establish consumption options with a high mitigation potential measured in tons of CO2eq/capita/yr. For transport, the options with the highest mitigation potential include living car-free, shifting to a battery electric vehicle, and reducing flying by a long return flight with a median reduction potential of more than 1.7 tCO2eq/cap. In the context of food, the highest carbon savings come from dietary changes, particularly an adoption of vegan diet with an average and median mitigation potential of 0.9 and 0.8 tCO2eq/cap, respectively. Shifting to renewable electricity and refurbishment and renovation are the options with the highest mitigation potential in the housing domain, with medians at 1.6 and 0.9 tCO2eq/cap, respectively. We find that the top ten consumption options together yield an average mitigation potential of 9.2 tCO2eq/cap, indicating substantial contributions towards achieving the 1.5 °C–2 °C target, particularly in high-income context.
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Chiara Castelli et al 2024 Environ. Res. Lett. 19 053003
This study conducts a comprehensive review of macroeconomic models within the Water, Energy, Food, and Ecosystem (WEFE) nexus, considering four different approaches: computable general equilibrium (CGE) models, integrated assessment models (IAMs), agent-based models (ABMs), and dynamic stochastic general equilibrium (DSGE) models. Specifically, we examine how macroeconomic models represent not only the WEFE nexus as a whole but also its individual components and their combinations. Spanning a collection of 77 papers published in the last 20 years, this review underscores the prevalence of CGE models and IAMs, followed by ABMs, as dominant avenues of research within this field. CGE models frequently investigate interconnections between pairs of WEFE elements, while IAMs focus on the whole nexus. At the same time, ABMs do not exhibit a clear pattern, whereas DSGE models predominantly concentrate on the energy component alone. Overall, our findings indicate that the development of DSGE models and ABMs is still in its early stages. DSGE models potentially allow the analysis of uncertainty and risk in this field, while ABMs might offer new insights into the complex interactions between natural and human systems but still lack a common framework.
Gaige Hunter Kerr et al 2024 Environ. Res. Lett. 19 054052
The United States (U.S.) Clean Air Act seeks to prevent and abate ambient air pollution, while also providing a framework to identify and address violations. Little research has examined where or how frequently violations of the Clean Air Act occur and how marginalized communities may bear a disproportionate share of these violations, despite the fact that marginalized communities experience persistent, disproportionate pollution levels and associated health impacts. Here, we leverage data on Clean Air Act enforcement and compliance together with demographic data to show that the most serious violations of the Act—high priority violations (HPVs)—predominantly occur in communities of color throughout the U.S. Specifically, we find that the number of facilities with an HPV within communities with the largest proportion of people of color is nearly two times greater than in communities with the smallest proportion. Only 6% of facilities with an HPV address their violations within the timeframe mandated by the U.S. Environmental Protection Agency, and a larger share of facilities with an HPV in disadvantaged communities do not address their violations within this timeframe compared to facilities with an HPV in non-disadvantaged communities. Enforcing agencies should improve how violations are communicated and addressed. To this end, we suggest several ways to empower individuals and communities with easy-to-access data related to Clean Air Act violations and that enforcement practices and reporting be standardized across enforcing agencies.
Hongxiong Xu et al 2024 Environ. Res. Lett. 19 054051
In the realm of weather forecasting, the implementation of Artificial Intelligence (AI) represents a transformative approach. However, AI weather forecasting method still faces challenges in accurately predicting meso- and smaller-scale processes and failing to directly capture extreme precipitation due to regression algorithm's nature, coarse resolution, and limitations in key variables like precipitation. Therefore, we propose a state-of-the-art technology which integrates the strengths of the Pangu-weather AI weather forecasting with the traditional regional weather model, focusing specifically on enhancing the prediction of extreme precipitation events, as mainly exemplified by an unprecedented precipitation in North China from 29 July to 1 August 2023, and an additional extraordinary precipitation event as a supplementary validation to further ensure the accuracy of this technology. The results show that the AI-driven approach exhibits superior performance in capturing the spatial and temporal dynamics of extreme precipitation events. Remarkably, with a threshold of 400 mm, the AI-driven model secures a Threat Score (TS) of 0.1 for forecast lead time reaching up to 8.5 d. This performance notably surpasses the performance of traditional GFS-Driven models, which achieve a similar TS only within a limited 3-day forecast lead time. This considerable enhancement in forecast accuracy, especially over extended lead times illustrates the AI-driven model's potential to advance in long-term forecasts of extreme precipitation, previously considered challenging, emphasizing the potential of AI in augmenting and refining traditional weather prediction.
Pietro Marconi and Lorenzo Rosa 2024 Environ. Res. Lett. 19 054050
Meeting the anticipated 50% increase in global food demand by 2050 requires a crucial reassessment of agricultural practices, particularly in terms of nitrogen fertilizers inputs. This study analyzes the technical potential of nitrogen recovery from livestock manure and crop residues, bringing attention to the often-overlooked resource of digestate derived from anaerobic digestion. Our analysis highlights the significant capacity of the anaerobic digestion process, yielding approximately 234 ± 5 million metric tons (Mt) of nitrogen annually, sourced 93% from livestock manure and 7% from crop residues. Additionally, we estimated that substituting synthetic nitrogen with nitrogen from anaerobic digestion has the potential to reduce greenhouse gas emissions by 70% (185 Mt CO2-eq yr−1). Lastly, 2.5 billion people could be sustained by crops grown using nitrogen from anaerobic digestion of manure and crop residues rather than synthetic nitrogen fertilizers. Although agricultural residues have double the technical potential of current synthetic nitrogen fertilizer production, 30% of croplands encounter difficulties in satisfying their nitrogen needs solely through crop residues and anaerobic digestion manure. This deficiency primarily results from inefficient reuse attributed to geographical mismatches between crop and livestock systems. This underscores the urgent need to reconnect livestock and cropping systems and facilitate the transport and reuse of manure in crop production. In conclusion, the mobilization of these large amounts of nitrogen from livestock manure and crop residues will require to overcome the nitrogen from anaerobic digestion green premium with incentives and subsidies.
Mathilde Chen et al 2024 Environ. Res. Lett. 19 054049
High-dimensional climate data collected on a daily, monthly, or seasonal time step are now commonly used to predict crop yields worldwide with standard statistical models or machine learning models. Since the use of all available individual climate variables generally leads to calculation problems, over-fitting, and over-parameterization, it is necessary to aggregate the climate data used as predictors. However, there is no consensus on the best way to perform this task, and little is known about the impacts of the type of aggregation method used and of the temporal resolution of weather data on model performances. Based on historical data from 1981 to 2016 of soybean yield and climate on 3447 sites worldwide, this study compares different temporal resolutions (daily, monthly, or seasonal) and dimension reduction techniques (principal component analysis (PCA), partial least square regression, and their functional counterparts) to aggregate climate data used as inputs of machine learning and linear regression (LR) models predicting yields. Results showed that random forest models outperformed and were less sensitive to climate aggregation methods than LRs when predicting soybean yields. With our models, the use of daily climate data did not improve predictive performance compared to monthly data. Models based on PCA or averages of monthly data showed better predictive performance compared to those relying on more sophisticated dimension reduction techniques. By highlighting the high sensitivity of projected impact of climate on crop yields to the temporal resolution and aggregation of climate input data, this study reveals that model performances can be improved by choosing the most appropriate time resolution and aggregation techniques. Practical recommendations are formulated in this article based on our results.
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Chiara Castelli et al 2024 Environ. Res. Lett. 19 053003
This study conducts a comprehensive review of macroeconomic models within the Water, Energy, Food, and Ecosystem (WEFE) nexus, considering four different approaches: computable general equilibrium (CGE) models, integrated assessment models (IAMs), agent-based models (ABMs), and dynamic stochastic general equilibrium (DSGE) models. Specifically, we examine how macroeconomic models represent not only the WEFE nexus as a whole but also its individual components and their combinations. Spanning a collection of 77 papers published in the last 20 years, this review underscores the prevalence of CGE models and IAMs, followed by ABMs, as dominant avenues of research within this field. CGE models frequently investigate interconnections between pairs of WEFE elements, while IAMs focus on the whole nexus. At the same time, ABMs do not exhibit a clear pattern, whereas DSGE models predominantly concentrate on the energy component alone. Overall, our findings indicate that the development of DSGE models and ABMs is still in its early stages. DSGE models potentially allow the analysis of uncertainty and risk in this field, while ABMs might offer new insights into the complex interactions between natural and human systems but still lack a common framework.
Aswin Giri J and Shiva Nagendra S M 2024 Environ. Res. Lett. 19 053002
Air pollution is perceived through sensory stimuli and interpreted by our brain. Perception is highly subjective and varies from person to person. As many direct and indirect factors influence air pollution perception, it is difficult to unearth the underlying mechanisms. Many studies have tried to understand the mechanisms and relations affecting perception, and it is important to evaluate those different approaches. We systematically reviewed 104 studies on air pollution perception, following the preferred reporting items for systematic reviews and meta-analyses guidelines. There is a difference between the public's subjective perception and objective air quality measurements. This discrepancy has been found to occur due to varied socio-economic characteristics, knowledge, emotions, etc. The advent of social media and the internet has had a significant effect on risk perception. All these influencing factors create differences between the public's perception and the scientific community/policymakers. This gap can be fixed by tailoring science-backed information for better communication. Based on past studies, we highlight the need for tailored data dissemination, integration of big data for urban management, development of robust frameworks to incorporate perception and use of a perception index for better communication.
Xinyuan Wei et al 2024 Environ. Res. Lett. 19 053001
Inland waters receive large quantities of dissolved organic carbon (DOC) from soils and act as conduits for the lateral transport of this terrestrially derived carbon, ultimately storing, mineralizing, or delivering it to oceans. The lateral DOC flux plays a crucial role in the global carbon cycle, and numerous models have been developed to estimate the DOC export from different landscapes. We reviewed 34 published models and compared their characteristics to identify challenges in model applications and opportunities for future model development. We classified these models into three types: indicator-driven, hydrology-forced, and process-based DOC export simulation models. They differ mainly in their environmental inputs, simulation approaches for soil DOC production, leaching from soils to inland waters, and transit through inland waters. It is essential to consider landscape characteristics, climate conditions, available data, and research questions when selecting the most appropriate model. Given the substantial assumptions associated with these models, sufficient measurements are required to benchmark estimates. Accurate accounting of terrestrially derived DOC export to oceans requires incorporating the DOC produced in aquatic ecosystems and deposited with rainwater; otherwise, global export estimates may be overestimated by 40.7%. Additionally, improving the representation of mineralization and burial processes in inland waters allows for more accurate accounting of carbon sequestration through land ecosystems. When all the inland water processes are ignored or assuming DOC leaching is equivalent to DOC export, the loss of soil carbon through this lateral flux could be underestimated by 43.9%.
Tamara L Sheldon and Rubal Dua 2024 Environ. Res. Lett. 19 043004
Ride-hailing has expanded substantially around the globe over the last decade and is likely to be an integral part of future transportation systems. We perform a systematic review of the literature on energy and environmental impacts of ride-hailing. In general, empirical papers find that ride-hailing has increased congestion, vehicle miles traveled, and emissions. However, theoretical papers overwhelmingly point to the potential for energy and emissions reductions in a future with increased electrification and pooling. Future research addressing the gap between observed and predicted impacts is warranted.
Aurélie Méjean et al 2024 Environ. Res. Lett. 19 043003
While it is widely assumed that poor countries will suffer more from climate change, and that climate change will exacerbate inequalities within countries, systematic and large-scale evidence on this issue has been limited. In this systematic literature review, we examine and synthesize the evidence from the literature. Drawing from 127 individual papers, we find robust evidence that climate change impacts indeed increase economic inequality and disproportionately affect the poor, both globally and within countries on all continents. This result is valid across a wide range of physical impacts, types of economic inequality, economic sectors, and assessment methods. Furthermore, we highlight the channels through which climate change increases economic inequality. While the diversity of different approaches and metrics in the existing literature base precludes extracting a universal quantitative relation between climate change and economic inequality for use in future modelling, our systematic analysis provides an important stepping stone in that direction.
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Singh et al
Air pollution from coal-fired electricity generation is an important cause of premature mortality in India. Although pollution-related mortality from the sector has been extensively studied, the relative contribution of individual coal-fired units to the fleet-wide mortality burden remains unclear. Here, we find that emissions from a small number of units drive overall mortality. Units producing just 3.5% of total generation and constituting less than 3% of total capacity result in 25% of annual premature mortality from coal-fired generation. This is a direct consequence of the 200-fold variation that we find in the mortality intensity of electricity generation across units. We use a detailed emissions inventory, a reduced complexity air quality model, and non-linear PM2.5 concentration-response functions to estimate marginal premature mortality for over 500 units operational in 2019. Absolute annual mortality ranges from less than 1 to over 650 deaths/year across units, and the mortality intensity of generation varies from under 0.002 to 0.43 deaths/GWh. Our findings suggest the potential for large social benefits in the form of reduced PM2.5-related premature mortality in India if the highest mortality intensity units are prioritized for the implementation of pollution control technologies or accelerated retirement.
Azimrayat Andrews et al
Microplastics are ubiquitous in marine environments and can be incorporated into biological aggregates including marine snows and faecal pellets. These aggregates are suspected to be a major removal mechanism for microplastics from the surface ocean, transporting them to deeper levels and the seafloor as they sink and remineralise. However, simple budget calculations, observations, and model parameter testing suggest that aggregation might also lead to retention of microplastics in the upper ocean, sustaining contamination in biologically-productive environments. The ability of the biological microplastic sink to reduce water column contamination has relevance to the setting of ocean plastics pollution reduction targets, as are currently under negotiation by the International Negotiating Committee of the United Nations Environment Assembly (UNEA). Here we apply 8 idealised global pollution reduction trajectories, from 1-100% per year, starting from the year 2026 and ending in the year 2100 to an Earth System Climate Model with a representation of ocean microplastics and their aggregation in biological particles. We find that the global ocean microplastic inventory and surface concentrations stabilize within this century for reduction rates exceeding 5% per year but the inventory does not substantially decrease under any trajectory. Furthermore, microplastics are retained by marine biology in the surface ocean, where concentrations stabilise to a non-zero value over decades. Lastly we find that irrespective of scenario, contamination of deeper ocean layers continues to increase for the duration of our simulations via the export of microplastics by biological aggregates. These results suggest that ambitious targets for pollution reduction exceeding 5\% per year will be required to progress the resolution of the UNEA to ``end plastic pollution'' in this century, and that ongoing microplastic contamination of the marine food web may be unavoidable.
Ramasamy et al
The spreading of crushed olivine-rich rocks in coastal seas to accelerate weathering reactions sequesters atmospheric CO2 and reduces atmospheric CO2 concentrations. Their weathering rates depend on different factors, including temperature and the reaction surface area. Therefore, this study investigates the variations in olivine-based enhanced weathering rates across 13 regional coasts worldwide. In addition, it assesses the CO2 sequestration within 100 years and evaluates the maximum net-sequestration potential based on varying environmental conditions. Simulations were conducted using the geochemical thermodynamic equilibrium modeling software PHREEQC. A sensitivity analysis was performed, exploring various combinations of influencing parameters, including grain size, seawater temperature, and chemistry. The findings reveal significant variation in CO2 sequestration, ranging from 0.13 to 0.94 metric tons (t) of CO2 per ton of distributed olivine-rich rocks over 100 years. Warmer coastal regions exhibit higher CO2 sequestration capacities than temperate regions, with a difference of 0.4 t CO2/ t olivine distributed. Sensitivity analysis shows that smaller grain sizes (10 µm) exhibit higher net CO2 sequestration rates (0.87 t/t) in olivine-based enhanced weathering across all conditions, attributed to their larger reactive surface area. However, in warmer seawater temperatures, olivine with slightly larger grain sizes (50 and 100 µm) displays still larger net CO2 removal rates (0.97 and 0.92 t/t), optimizing the efficiency of CO2 sequestration while reducing grinding energy requirements. While relying on a simplified sensitivity analysis that does not capture the full complexity of real-world environmental dynamics, this study contributes to understanding the variability and optimization of enhanced weathering for CO2 sequestration, supporting its potential as a sustainable CO2 removal strategy.
Sun et al
Marine heatwaves are the extreme anomalously warm water events which are projected to cause more and more disastrous impacts on ecosystems and economies under global ocean warming. Our ability to forecast marine heatwaves determines what effective measures can be taken to help reduce the vulnerability of marine ecosystems and human communities. In this study, we combine deep learning model explicitly the Convolutional Neural Network with a real-time sub-seasonal to seasonal physical forecast model, improving the MHW forecast skills of about 10% on global average in leading two weeks through correcting the physical model bias with the observational data. This improvement has a nearly consistent influence (~10%-20%) on a global scale, reflecting the wide-coverage promotion by deep learning. This work reveals advantages and prospects of the combination between deep learning and physical models in the ocean forecast in future.
Fu et al
The reduction in methane concentration is crucial for achieving the goals of the Paris Agreement. However, its annual growth rate is unstable, and understanding the reasons for changes in methane growth is essential for climate policy-making. Currently, there is considerable uncertainty regarding its attribution. Here, we utilize multi-source data and optimal fingerprinting methods to detect the contributions of several key drivers to the methane trend and interannual variability. We find that the methane growth trend is primarily influenced by anthropogenic emissions, while interannual variability is predominantly determined by wetland and biomass burning emissions. This result underscores the central role of anthropogenic emissions in methane dynamics, providing confidence in the effectiveness of human efforts to control methane atmospheric concentrations through emission reductions. It also helps alleviate concerns about the recent surge in atmospheric methane concentration, as it may be a short-term peak caused by increased wetland emissions rather than a trend change.