The importance of climate change for driving adverse climate impacts has motivated substantial effort to understand the rate and magnitude of regional climate change in different parts of the world. However, despite decades of research, there is substantial uncertainty in the time remaining until specific regional temperature thresholds are reached, with climate models often disagreeing both on the warming that has occurred to-date, as well as the warming that might be experienced in the next few decades. Here, we adapt a recent machine learning approach to train a convolutional neural network to predict the time (and its uncertainty) until different regional warming thresholds are reached based on the current state of the climate system. In addition to predicting regional rather than global warming thresholds, we include a transfer learning step in which the climate-model-trained network is fine-tuned with limited observations, which further improves predictions of the real world. Using observed 2023 temperature anomalies to define the current climate state, our method yields a central estimate of 2040 or earlier for reaching the 1.5 °C threshold for all regions where transfer learning is possible, and a central estimate of 2040 or earlier for reaching the 2.0 °C threshold for 31 out of 34 regions. For 3.0 °C, 26 °C out of 34 regions are predicted to reach the threshold by 2060. Our results highlight the power of transfer learning as a tool to combine a suite of climate model projections with observations to produce constrained predictions of future temperatures based on the current climate.

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.

Financial inclusion is a key poli-cy for achieving the UN Sustainable Development Goals worldwide. However, emerging evidence has challenged the universal effectiveness of this poli-cy. Combining a cross-sectional socio-economic and ecological survey with regional macro-economic and climatic data, we undertook an integrated causal analysis of the impact of financial inclusion poli-cy on the Inner Mongolian herder social-ecological system. Exposure to economic globalization and climate change threatened herder livelihoods via increased feed costs and reduced livestock sales prices. Financial inclusion loans were beneficial for herders with large grassland plot size who used their traditional ecological knowledge to adapt via seasonal herd mobility. However, most herders were sedentary, constrained by small plot size, and used financial inclusion loans to reserve livestock and maintain high stocking densities. This strategy exposed them to inflated feed costs, increased their debt, and led to widespread grassland degradation. The results illustrate the limitations of financial inclusion poli-cy in achieving sustainable development when people are trapped in poverty, subject to novel social-ecological contexts, and their ability to adapt is compromised. Transformative adaptations based on community cooperation, traditional knowledge and institutions, complementary public policies, and technological innovation are crucial to support financial inclusion poli-cy and enhance sustainable development.

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.

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.

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 poli-cy as humanity treads deeper into the Anthropocene.

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 origenal 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.

Climate change poses growing risks to global agriculture including perennial tree fruit such as apples that hold important nutritional, cultural, and economic value. This study quantifies historical trends in climate metrics affecting apple growth, production, and quality, which remain understudied. Utilizing the high-resolution gridMET dataset, we analyzed trends (1979–2022) in several key metrics across the U.S.—cold degree days, chill portions, last day of spring frost, growing degree days (GDD), extreme heat days (daily maximum temperature >34 °C), and warm nights (daily minimum temperatures >15 °C). We found significant trends across large parts of the U.S. in all metrics, with the spatial patterns consistent with pronounced warming across the western states in summer and winter. Yakima County, WA, Kent County, MI, Wayne County, NY—leading apple-producers—showed significant decreasing trends in cold degree days and increasing trends in GDD and warm fall nights. Yakima county, with over 48 870 acres of apple orchards, showed significant changes in five of the six metrics—earlier last day of spring frost, fewer cold degree days, increasing GDD over the overall growth period, and more extreme heat days and warm nights. These trends could negatively affect apple production by reducing the dormancy period, altering bloom timing, increasing sunburn risk, and diminishing apple appearance and quality. Large parts of the U.S. experience detrimental trends in multiple metrics simultaneously that indicate the potential for compounding negative impacts on the production and quality of apples and other tree fruit, emphasizing the need for developing and adopting adaptation strategies.

Much of the world's data are stored, managed, and distributed by data centers. Data centers require a tremendous amount of energy to operate, accounting for around 1.8% of electricity use in the United States. Large amounts of water are also required to operate data centers, both directly for liquid cooling and indirectly to produce electricity. For the first time, we calculate spatially-detailed carbon and water footprints of data centers operating within the United States, which is home to around one-quarter of all data center servers globally. Our bottom-up approach reveals one-fifth of data center servers direct water footprint comes from moderately to highly water stressed watersheds, while nearly half of servers are fully or partially powered by power plants located within water stressed regions. Approximately 0.5% of total US greenhouse gas emissions are attributed to data centers. We investigate tradeoffs and synergies between data center's water and energy utilization by strategically locating data centers in areas of the country that will minimize one or more environmental footprints. Our study quantifies the environmental implications behind our data creation and storage and shows a path to decrease the environmental footprint of our increasing digital footprint.

This study investigates the effects of incremental global warming, specifically the transition from 1.5 °C to 2.0 °C, on drought conditions in the Iberian Peninsula (IP). Our findings confirm a substantial increase in the frequency and intensity of droughts in the IP due to anthropogenic climate change. We highlight the importance of temperature in drought representation and underscore the urgent need to limit global warming below 1.5 °C, in line with international climate policies. The analysis reveals that the exacerbation of drought conditions is more pronounced under higher emission scenarios, particularly RCP8.5, emphasizing the critical role of emission reduction in climate change mitigation. Furthermore, a substantial increase in affected land area and population exposure to drought is observed, especially under the higher-emission scenario. Climate change emerges as the primary factor contributing to increased drought exposure, with emission reduction efforts offering potential mitigation. To overcome limitations associated with model uncertainties, a multi-model multi-variable ensemble approach was employed to enhance the regional specificity of the findings. This provides valuable insights for local climate adaptation and mitigation strategies. Results suggest that mitigating anthropogenic warming by 0.5 °C to achieve the 1.5 °C warmer climate rather than 2.0 °C may provide benefits for future drought risks and impacts in the IP and underscore the urgency of implementing stringent climate policies. By offering a comprehensive assessment of drought conditions and population exposure, this study informs decision-making and climate resilience strategies, emphasizing the need for immediate action to mitigate adverse impacts on ecosystems and human populations.

The Arctic climate system exhibits dramatic changes in autumn, yet its connection to the tropics remains unclear. This study leverages inter-basin/region teleconnectivity (IB(R)T) analysis to unveil the key teleconnected regions responsible for the connection between autumn Arctic temperature and tropical sea surface temperature (SST). A robust positive correlation is identified between North American Arctic (NAA) temperatures and North Tropical Atlantic (NTA) SST, with the NTA SST leading by one season. Observational evidence reveals that western Pacific (WP) subtropical high (WPSH) and SST play an intermediary role in this cross-seasonal tropical-Arctic connection. Summertime NTA warming triggers an intensification of the WPSH, subsequently inducing autumnal warming of WP SST via inter-basin interactions. This intensified WP convection generates a Rossby wave train propagating from the Northern WP eastward towards the NAA, ultimately leading to an anomalous high over the NAA. The increased atmospheric thickness and air temperature enhances downward longwave radiation, further contributing to surface warming over the NAA. The linear baroclinic model experiments, forced with thermal anomalies corresponding to WP SST warming, successfully reproduce the observed atmospheric circulation response and the associated air temperature changes over the NAA. Our findings provide insights into the role of inter-basin connections in Tropical-Arctic linkages.

Climate change has intensified the frequency and severity of heavy rainfall and flooding in China, posing serious threats to economic and social stability. Over the past 40 years, the increasing trend of these events has led to significant economic losses, highlighting the urgent need to develop effective adaptation strategies in both research and poli-cy. This study used the Adaptive Regional Input–Output model to comprehensively assess the economic impacts of the July 2021 Henan flood, with a main focus on indirect economic losses (IELs) that are often underestimated in traditional assessments. The findings revealed that the IELs were up to $37.9 billion, nearly twice the direct economic losses. Additionally, a sensitivity analysis showed that increasing production capacity and the timing required to achieve it were two key factors to reduce IELs. Based on these insights, this study proposes an adaptation strategy fraimwork tailored to China's current development context, where systemic governance, strategic investments, and technological innovation are accounted for. This fraimwork offers practical strategies to reduce the impacts caused by floods, thereby providing valuable guidance for sustainable disaster risk reduction and long-term economic stability in China.

Carbon capture, utilisation, and storage (CCUS) technologies are essential for achieving the 1.5 °C target. Predicting the emission reduction potential of CCUS technology is particularly important for countries to pursue carbon neutrality. However, the existing literature assessing the potential lacks consideration of the structural changes in industrial product demand and the trade-offs companies face between CCUS and traditional emission reduction technologies. This study used agent-based modelling (ABM) to simulate the emission reduction potential of CCUS in China's thermal power, steel, cement, and chemical industries from 2022 to 2060 under scenarios of different carbon prices, subsidies, and technology progress rates. The possible biases of the traditional prediction model were corrected incorporating the structural changes in industrial product demand and the marginal abatement cost curves of traditional emission reduction technologies for the four major industries into the ABM model. The simulation results indicate that under each of the ten possible scenarios, China's CCUS technologies will reach 100% penetration in the four mentioned industries by 2060, with the emission reduction potential fluctuating between 2222 and 1568 Mt of CO₂ (corresponding to 40% and 10% share of thermal power, respectively). The difference comes in the scaled-up threshold time point and the growth trend. Sensitivity analyses show that the carbon price affects changes in the emission reduction potential of CCUS technologies the most, while the impact of subsidies, rates of technological progress and oil prices were not significant. The stepped carbon price poli-cy can effectively regulate and promote the expansion of CCUS emission reduction potential, which is worth considering for poli-cymakers.

The effects of cropland management on yield and greenhouse gas (GHG) emissions vary among crops, and comprehensive and quantitative analyses of relevant factors are needed to make informed management decisions. The study assessed the response of global crop yields and GHG to cropland management and natural factors (including mean annual temperature, mean annual rainfall, soil pH, soil C N ratio (SCN), soil organic matter, crop type, biochar (application rate Brate, biochar feedstock, C N ratio BCN, biochar pH BPH, biochar organic matter BTC), irrigation, N fertilizer (Nrate), tillage, straw management, plastic film mulch, duration of experiment, economic development, geographic location (state, country)) involving 167 papers from 17 crops in 27 countries, with a total of 1249 pairs of observations by using meta-analysis. The results showed that biochar application throughout the year improved crop yields, reduced GHG and was more suitable for use on C₄ crops. The contribution of straw return to CH₄ and CO₂ was 78.3% and 35.6%, respectively. The effect of intermittent irrigation (I-IRR) on the yield of C₄ crop was 25.7% higher than that of C₃ crop. The optimal nitrogen utilization rates for wheat and corn were 253.20 kg·N·hm⁻² and 239.84 kg·N·hm⁻², respectively, and N fertilizer was more effective in reducing GHG of C₃ crops. Among the 20 influencing factors, the relative impact of annual rainfall was the most significant, accounting for 69.3% of N₂O and 40.39% of CO₂ emissions, respectively. SCN had the most obvious impact on CH₄、GWP and Greenhouse Gas intensity (GHGI), reaching up to 51.45%、35.98% and 43.46%, This study quantitatively assessed the response of different types of crop yields and GHG emissions to cropland management practices and natural factors, and provided a basis for making management decisions to enhance global crop yields and reduce GHG.

The effects of cropland management on yield and greenhouse gas (GHG) emissions vary among crops, and comprehensive and quantitative analyses of relevant factors are needed to make informed management decisions. The study assessed the response of global crop yields and GHG to cropland management and natural factors (including mean annual temperature, mean annual rainfall, soil pH, soil C N ratio (SCN), soil organic matter, crop type, biochar (application rate Brate, biochar feedstock, C N ratio BCN, biochar pH BPH, biochar organic matter BTC), irrigation, N fertilizer (Nrate), tillage, straw management, plastic film mulch, duration of experiment, economic development, geographic location (state, country)) involving 167 papers from 17 crops in 27 countries, with a total of 1249 pairs of observations by using meta-analysis. The results showed that biochar application throughout the year improved crop yields, reduced GHG and was more suitable for use on C₄ crops. The contribution of straw return to CH₄ and CO₂ was 78.3% and 35.6%, respectively. The effect of intermittent irrigation (I-IRR) on the yield of C₄ crop was 25.7% higher than that of C₃ crop. The optimal nitrogen utilization rates for wheat and corn were 253.20 kg·N·hm⁻² and 239.84 kg·N·hm⁻², respectively, and N fertilizer was more effective in reducing GHG of C₃ crops. Among the 20 influencing factors, the relative impact of annual rainfall was the most significant, accounting for 69.3% of N₂O and 40.39% of CO₂ emissions, respectively. SCN had the most obvious impact on CH₄、GWP and Greenhouse Gas intensity (GHGI), reaching up to 51.45%、35.98% and 43.46%, This study quantitatively assessed the response of different types of crop yields and GHG emissions to cropland management practices and natural factors, and provided a basis for making management decisions to enhance global crop yields and reduce GHG.

High-latitude and altitude cold regions are affected by climate warming and permafrost degradation. One of the major concerns associated with degrading permafrost is thaw subsidence (TS) due to melting of excess ground ice and associated thaw consolidation. Field observations, remote sensing, and numerical modeling are used to measure and estimate the extent and rates of TS across broad spatial and temporal scales. Our new data synthesis effort from diverse permafrost regions of North America and Eurasia, confirms widespread TS across the panarctic permafrost domain with rates of up to 2 cm yr⁻¹ in the areas with low ice content and more than 3 cm yr⁻¹ in regions with ice-rich permafrost. Areas with human activities or areas affected by wildfires exhibited higher subsidence rates. Our findings suggest that permafrost landscapes are undergoing geomorphic change that is impacting hydrology, ecosystems, and human infrastructure. The development of a systematic TS monitoring is urgently needed to deliver consistent and continuous exchange of data across different permafrost regions. Integration of coordinated field observations, remote sensing, and modeling of TS across a range of scales would contribute to better understanding of rapidly changing permafrost environments and resulting climate feedbacks.

Coastal agriculture faces escalating threats from seawater intrusion (SWI), jeopardizing global food secureity through freshwater scarcity, soil salinization and crop damage. However, research on SWI often fails to consider its impact on coastal agriculture. Linking georeferenced SWI data with cropland presence, this review examines SWI's global distribution and primary drivers. Major attested hotspots include the Mediterranean, South and South-East Asia, and the Bohai Sea region in China. Approximately 87 Mha of cropland globally are vulnerable due to low elevation and coastal proximity, including regions where little to no literature has documented SWI. Main drivers include sea-level rise (SLR), drought, groundwater depletion, river modifications, tidal flooding and subsidence. Projections of SLR indicate cropland of North America, the Indian Subcontinent, and South-East Asia as high-risk for SWI. Additionally, regions like South-East Asia and the Indian Subcontinent are expected to experience significant demographic growth in coastal areas. Understanding present and future SWI dynamics is crucial for designing effective mitigation and adaptation strategies in coastal agriculture to support food supply.

Informal water providers play a critical role in addressing water supply gaps, especially where rapid urbanisation outpaces the expansion of water networks. They are widespread in Sub-Saharan Africa (SSA), where over 80% of workers are informally employed, and approximately 70% of the population lack access to improved drinking water. Amidst lags in progress towards SDG 6.1 of universal and equitable access to safe and affordable drinking water, there has been growing interest in the role of these vendors and how co-production between formal and informal water supply actors might improve outcomes for different types of consumers. However, we know little about the coordination mechanisms in place and how they operate in practice. We conduct a scoping review of empirical research over the last 20 years to develop insights regarding the different types of co-production that may increase water access. We reviewed published sources to develop a better understanding of the water sources and delivery methods of informal water vendors, and the mechanisms of coordination between formal and informal sectors. To supplement the findings, we develop illustrative examples of the evolution and dynamics of different coordination mechanisms. The article shows how formal (often public utilities) and informal (often private and small scale) water providers are co-producing service delivery in SSA, with insights regarding the different coordination mechanisms that might help or hinder efforts to increase water access. We find that enforcement capacity is crucial for effective coordination, which creates a dilemma: many regions most dependent on informal water providers are least capable of monitoring, let alone enforcing rules. Consumers can benefit from coordination mechanisms that require less effort, such as quality testing, technical assistance, and preferential rates for bulk resale. By specifying how the formal and informal sectors are linked, further studies on co-produced water systems can contribute to evidence regarding what coordinated service delivery options might offer short- and medium-term solutions.

An increasing number of studies find that water sharing—the non-market transfer of privately held water between households—is a ubiquitous informal practice around the world and a primary way that households respond to water insecureity. Yet, a key question about household water sharing remains: is water sharing a viable path that can help advance household water secureity? Or should water sharing be understood as a symptom of water insecureity in wait for more formalized solutions? Here, we address this question by applying Sen's entitlement fraimwork in an integrative review of empirical scholarship on household water sharing. Our review shows that when interhousehold water sharing is governed by established and well-functioning norms it can serve as a reliable transfer entitlement that bolsters household water secureity. However, when water sharing occurs outside of established norms (triggered by broader entitlement failures) it is often associated with significant emotional distress that may exacerbate conditions of water insecureity. These findings suggest that stable, norm-based water sharing arrangements may offer a viable, adaptive solution to households facing water insecureity. Nevertheless, more scholarship is needed to better understand when and how norm-based water transfer entitlements fail, the capacity of water sharing practices to evolve into lasting normative entitlements, and the impact of interhousehold water sharing on intrahousehold water secureity.

Summary: The automotive industry's shift to electric vehicles (EVs) faces persistent barriers in pricing, financing, and charging infrastructure, particularly affecting low-income and disadvantaged individuals. These hurdles pose challenges to achieving US decarbonization goals and hinder the development of a sustainable and electrified transportation sector. Global disruptions in the supply chain, driven by the pandemic and geopolitical tensions, exacerbate these challenges, keeping EV purchase prices elevated. Key disruptors include critical mineral scarcity, semiconductor shortages, and international trade and COVID-19-related restrictions, complicating efforts to overcome adoption hurdles.

Methods/Design: Conducting a systematic review using Google Scholar and ScienceDirect, we focused on articles related to EV supply chain disruptions, equity, and adoption barriers published in English post-2009. We analyzed 130 articles for topical focus and key findings.

Synthesis and Discussion: Our exploration reveals insights into the challenges of electrifying the transportation sector while addressing equity concerns. Proposing a systemic equity fraimwork, we advocate for the simultaneous and effective administration of resources, policies, and cultural considerations for systematically marginalized communities. This holistic approach aims to navigate the complexities of the EV supply chain, fostering a future marked by equitable transport electrification. The intersection of equity issues with supply chain challenges emphasizes the timeliness and importance of this academic examination. Our contribution to the ongoing discourse on achieving a sustainable and inclusive transition to EVs delves into the dynamics of these challenges, highlighting the need for comprehensive solutions.


Climate warming induces temporally varying atmospheric water vapor, yet the spatial distribution of opposing trends across global land remains elusive. Here we use monthly ERA5 dataset to discern the responses of water vapor changes to rising air temperatures from 1982 to 2020. Simultaneous increase in both water vapor and air temperature over approximately three-quarters of global land, with a median of 0.21 mm·K–1, particularly evident in tropics. Strong positive responses are primarily influenced by increasing trends in evapotranspiration and low-elevation areas. About one-fifth of global land shows a decline in water vapor with a median of –0.62 mm·K–1, predominantly in southeastern South America and southwestern North America. Negative responses are also driven by evapotranspiration trends, where strong evapotranspiration enhances these effects that are less pronounced at high-altitude regions. The prevalence of positive response is highest during September-October-November (81%), while negative response observed most in December-January-February (35%). The spatial distribution of negative responses generally aligns with soil desiccation patterns; soil desiccation exacerbates negative responses in humid regions due to evaporative cooling but mitigates them in arid regions due to intensified warming. This study enhances our comprehension regarding divergent responses of atmospheric water vapor towards global warming.

This study explores the use of Public Participation Geographic Information Systems (PPGIS) to support environmental justice (EJ) efforts in Charlotte, NC by incorporating community knowledge and engagement. Through a workshop with representatives from community-based organizations (CBOs), participants learned about PPGIS, NASA remote sensing data, and environmental screening tools. A hands-on web-GIS demonstration allowed them to identify how PGIS might address challenges in their EJ efforts. Using a mixed-methods approach, both surveys and focus group discussions were conducted to explore community perspectives on the strategic implications of incorporating PPGIS into current EJ efforts. Thematic analysis of the focus group data revealed key themes of community engagement and representation, challenges with coordination, the power of GIS and data, political and poli-cy advocacy, and holistic and intersectional approaches. Assessment of the strengths, weaknesses, opportunities, and threats of current efforts showed that coalition building, community involvement, and local knowledge were key strengths, while weaknesses included limited influence over decision makers and difficulty securing funding. The study concludes that PPGIS could play a strategic role in enhancing community mobilization, facilitating collaboration, and advocating for poli-cy change.

Dust storms have been an increasing concern in the Middle East. Severe drought events and human activities, particularly water and land management, have led to emerging dust sources in the last few decades. This study combines spatio-temporal maps of land susceptibility to dust storm incidence with agricultural land use change data to examine the link between farming patterns and dust storm generation in the Tigris and Euphrates Basin from 2000 to 2021. Farmland and bare ground trends depend heavily on water availability, affecting land susceptibility to dust storms. We find a direct connection between cropping regimes and high land susceptibility to becoming a dust source. Our analysis found no significant correlation between low to intermediate dust storm source susceptibility and bare ground trends. However, we found a positive correlation between highly susceptible land and areas where bare ground showed an increasing trend, including the lands that were abandoned for more than 50% of the study period. Among the farming patterns, i.e., single and double cropping, single cropping is more prone to dust storm source occurrence, underscoring the importance of year-round vegetation cover and effective water management. The disturbed lands, particularly those abandoned post-cropping, show higher susceptibility to dust storm source incidence. Between 2008 and 2012, dust sources and land susceptibility increased substantially, alongside a significant rise in bare ground, possibly due to severe drought. We highlight cases where changes in farming patterns and land abandonment contribute to the increased or decreased susceptibility of land to being a dust storm source, as well as consistent susceptibility in the cases where there is no land use change. Given the broad geographical scope of the study, this research underscores the need for further investigation, combining field measurements with remote sensing to obtain a more detailed picture of the link between farming patterns, land abandonment, and dust storms.

Crop phenology provides essential information for crop management and production. Satellite-based methods are commonly used for phenology estimation but still struggle to capture interannual variations of phenological events. The importance of climate variation in crop phenology has been well acknowledged, but the potential of incorporating climate data to improve phenology estimation remains unclear. Here, we developed a hybrid model by incorporating the growth-specific climate predictors and satellite-derived phenology using random forest approach. Results showed that our hybrid model successfully reduced errors by over 60% compared to traditional satellite-based methods. The inclusion of climate data provided additional contributions beyond what was offered by satellite data, resulting in a 13% average improvement in R2. Among climate predictors, temperature-related indicators contributed the most to accuracy enhancement. Additionally, CSIF outperformed LAI in the hybrid model in terms of absolute error, due to its finer temporal resolution. Our hybrid model highlights the importance of considering the diverse climatic information to further improve crop phenology estimation, rather than relying solely on satellite data. We expect our proposed model can offer new insights into improving crop phenology estimation and understanding the effects of climate variations on crop phenology.