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.

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.

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.

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.

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.

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.

Global aviation emissions have been growing despite international efforts to limit climate change. Quantifying the status quo of domestic and international aviation emissions is necessary for establishing an understanding of current emissions and their mitigation. Yet, a majority of the United Nations framework convention on climate change (UNFCCC)-ratifying parties have infrequently disclosed aviation emissions within the international framework, if at all. Here, we present a set of national aviation emission and fuel burn inventories for these 197 individual parties, as calculated by the high-resolution aviation transport emissions assessment model (AviTeam) model. In addition to CO₂ emissions, the AviTeam model calculates pollutant emissions, including NOx, SOx, unburnt hydrocarbons, black carbon, and organic carbon. Emission inventories are created in aggregated and gridded format and rely on Automatic Dependent Surveillance–Broadcast combined with schedule data. The cumulative global fuel burn is estimated at 291 Tg for the year 2019. This corresponds to CO₂ emissions of 920 Tg, with 306 Tg originating from domestic aviation. We present emissions from 151 countries that have yet to report their emissions for 2019, which sum to 417 TgCO₂. The improved availability of national emissions data facilitated by this inventory could support mitigation efforts in developed and developing countries and shows that such tools could bolster sector reporting to the UNFCCC.

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.

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.

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.

Warming permafrost has been detected worldwide and is projected to continue during the next century by many modelling studies. In mountain regions, this can lead to potentially hazardous impacts on short time-scales by an increased tendency for slope instabilities. However, time scales of permafrost thaw and the role of the ice content are less clear, especially in heterogeneous mountain terrain, where ice content can vary between zero and supersaturated conditions over small distances. Warming of permafrost near the freezing point shows therefore complex inter-annual behaviour due to latent heat effects during thawing and the influence of the snow-cover, which is governed by highly non-linear processes itself. Here, we demonstrate a preconditioning effect within near-surface layers in mountain permafrost that causes non-linear degradation and accelerates thaw. We hypothesise that a summer heat wave, as has occurred in the Central European summers 2003, 2015 and 2022, will enhance permafrost degradation if the active layer and the top of the permafrost layer are already preconditioned, i.e. have reduced latent heat content. This preconditioning can already be effectuated by a singular warm year, leading to exceptionally strong melting of the ground ice. On sloping terrain this ice-loss can be considered as irreversible, as large parts of the melted water will drain during the process, and an equivalent build-up of ice in cold years does not happen on similar time-scales as the melting. We propose a simple geophysical approach based on electrical resistivity tomography surveys that can assess the state of preconditioning in the absence of boreholes. In addition, we will show that resistivity data from a total of 124 permafrost sites in the Andes, Europe, and Antarctic adhere to a distinct power law behaviour between unfrozen and frozen states, which confirms the consistent electrical behaviour of permafrost and active layer materials over a wide range of landforms and material composition.

Tourism is a highly important economic sector worldwide, yet it is often less than optimally represented in terms of detailed spatial information. An accurate spatial representation of tourism can provide valuable insights into the spatial distribution of tourism vulnerabilities and exposure, allowing policymakers to make informed decisions and develop effective strategies for disaster risk reduction and climate change adaptation policies. Here, we stress the need for and propose a first prototype of an open-access spatially-explicit gridded database based on social media data for over 150 different tourism-related classes that depicts tourism density (supply and demand) and perceived satisfaction in Europe. We showcase the potential benefits of such database by mapping the exposure of specific tourism sectors to a range of weather extremes, including floods, windstorms, and heat stress. Based on these results, we argue that a homogeneous spatially-explicit database of tourism is essential to support efficient investments in preparedness and disaster resilience.

Validation of observed gridded precipitation datasets sourced from satellites or reanalysis over Africa remains a challenge due to the dearth of in-situ products that can act as a true estimate. To address this gap, this study compares the performance of different precipitation products (gauge, reanalysis, and satellite-based) sourced from the Frequent Rainfall Observations on GridS (FROGS) database over Africa. Satellite products are classified as corrected (incorporating gauge observations into their algorithms) or uncorrected, which implies that temporal variations depend entirely on the satellite. The main aim is to identify regions where precipitation products depict minimal uncertainties, supporting the use of the datasets in understanding precipitation variability in the specific regions. This is achieved by applying the triple collocation approach, which takes advantage of three collocated datasets of the same variable to derive the mean square error without requiring knowledge of the true value. The results show that light precipitation (1–5 mm d⁻¹) was prevalent in most regions of Africa during the study duration (2001–2016). Estimating the spatial distribution of daily precipitation greater than the 90th percentiles suggests that extreme precipitation is mainly detected over the Central Africa region and coastal regions of West Africa, where the majority of uncorrected satellite products show consistent performance. The satellite product CMORPH_V1_RAW shows higher estimates of 90th percentile precipitation among the uncorrected satellite products. The ability of precipitation products to detect rainy or non-rainy days shows that corrected satellite products depict notable agreement for probability of detection and false alarm ratio over most regions of Africa. Overall, better performance is demonstrated by the IMERG products, ARCv2, CHIRPSv2 and PERSIANN_CDRv1r1 (corrected), and GPCC, CPC_v1.0 and REGEN_ALL (gauge) during the study period. Among the reanalysis products, ERA5 datasets shows good performance in estimating daily precipitation over Africa. The optimal maps that show the classification of products in regions where they depict reliable performance can be recommended for various usage by different stakeholders.

As the transportation sector continues to decarbonize through electrification, there is growing interest in quantifying potential tradeoffs in air pollution and health impacts due to potential excess emissions from the power sector. This study investigates air pollution and health impacts of policy-driven changes in the transportation sector and the associated power generation demand in the Northeast and Mid-Atlantic United States. Five illustrative scenarios were designed to capture the effects of different policies under the first mandatory market-based program to reduce greenhouse gases in the US power sector (Regional Greenhouse Gas Initiative—RGGI) and the Transportation and Climate Initiative (TCI). Considering future power generation with new renewable energy investments to meet demands from decarbonized transportation, the scenarios were framed using: 1. 2030 reference cases for both sectors and a hybrid TCI portfolio, 2. Departure from the reference cases defined by Pennsylvania included or not in RGGI, and 3. Power grid emissions estimated under clean energy standard (CES) policy and hybrid TCI portfolio. While the cross-sectoral policy effect on domain-wide concentrations is modest (max ΔPM_2.5 ∼ 0.06 μg m³, ΔNO₂ ∼ 0.3 ppbv, ΔO₃ ∼ 0.15 ppbv), substantial increases in Ohio and West Virginia were attributed to Pennsylvania joining RGGI. With CES enacted and Pennsylvania in RGGI, significant reductions are seen in average concentrations (max ΔPM_2.5 ∼ 1.2 μg m³, ΔNO₂ ∼ 1.1 ppbv, ΔO₃ ∼ 1.7 ppbv) except for Louisiana and Mississippi with corresponding disbenefits. When focusing exclusively on emissions reductions from transportation, the hybrid TCI portfolio had health benefits of 530 avoided adult deaths, and 46 000 avoided asthma exacerbations. With a 'business as usual' power grid, these benefits remain comparable and are mainly driven by NO₂, followed by PM_2.5 and O₃. However, if Pennsylvania joins RGGI, total health benefits and spatial distribution change substantially, with a large portion of adverse health impacts moving from TCI states to Ohio and West Virginia. The overall monetized impact of a CES scenario can substantially exceed the estimated average range of 66–69 Billion US$, depending on the interaction with transportation decarbonization strategies and other drivers of exposure.

The warming climate-induced intensification of hydrological cycle is amplifying extreme precipitation and increasing flood risk at regional and global scales. The evaluation of flood risk, which depends on assessment indicators, weights, as well as data quality, is the first step toward mitigation flood disasters. In this study, we accepted ten risk assessment indicators concerning hazard of disaster-causing factors, sensitivity of hazard-forming environments, and vulnerability of disaster-bearing bodies. We used a combined weighting method based on the analytic hierarchy process and entropy weight (AHP-EW) technique to evaluate rainstorm-induced flood risks across the Yellow River Basin (YRB) from 2000 to 2018. We observed flood hazards are intensifying across the YRB. Specifically, areas with medium flood hazards expanded from the lower to the middle and upper YRB. The sensitivity to floods exhibited a spatial pattern of increasing from southeast to northwest (lower to upper YRB). The increase in vegetation coverage in the middle and upper reaches of the YRB reduces the sensitivity to flood disasters. Flood vulnerability shows an increasing trend, with higher vulnerability mainly observed in the middle and lower YRB. The overall flood risk in the YRB shows an increasing trend, with a 9-fold increase in flood risk from 2000 to 2018. Medium to high flood risk and vulnerability can mainly be identified in the middle and lower YRB, where population and gross domestic product are concentrated. The intensifying rainstorm-induced flood risks over urban areas in these regions should arouse public concern.

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.

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.

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%.

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.

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.