Spatiotemporal evolution and ecological risk assessment of heavy metals in agricultural black soils of Northeast China.

The patterns and drivers of Oropouche virus and its primary vector invasions in Asia under global change.

Caribbean Small Island Developing States (SIDS) are on the frontline of climate-induced coastal risks, where rising sea levels and intensifying storm surges converge with concentrated socioeconomic exposure. The inherent spatial constraints, economic dependency on tourism, and infrastructure clustering in coastal zones exacerbate systemic vulnerability. This study establishes an integrated high-resolution compound coastal risk framework by coupling hydrodynamic storm surge simulations with sea level projections and socioeconomic exposure data. The framework evaluates systemic risks across diverse return periods and Shared Socioeconomic Pathways including SSP1-1.9, SSP2-4.5, and SSP5-8.5, utilizing a modified static inundation model to integrate sea level rise and surge extremes for generating spatially explicit vulnerability assessments. Results revealed spatial heterogeneity and a distinctive ‘high-exposure–high-density–high-sensitivity’ configuration across several SIDS. Under SSP5–8.5, annual economic losses exceed USD 300 million in Jamaica and Cuba, and over 30,000 people may be affected in Dominica. Mitigation pathways consistent with a 1.5 °C warming limit (SSP1–1.9) reduce potential losses by 30–50%, while adaptation strategies, such as coastal ecosystem restoration and early-warning systems, deliver up to 40% carbon co-benefits. Beyond risk quantification, this framework supports climate-resilient infrastructure planning. By correlating spatial risks with adaptation finance, this research supports the Paris Agreement and Sustainable Development Goals (SDGs).

Climate change and ocean acidification outweigh local stressors in Mediterranean mussels: a multi-method convergence analysis.

Egypt possesses substantial potential for renewable energy generation, prompting heavy national investments to increase the share of wind power in its overall energy portfolio. Consequently, it is crucial to evaluate the long-term vulnerability of future wind energy production to climate change. This study fills a critical gap in regional climate-energy modelling by providing a novel quantification of turbine-specific capacity ratios across four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). Through a comparative assessment of 23 CMIP6 Global Climate Models (GCMs), EC-Earth3-Veg, EC-Earth3, and CESM2-WACCM were identified as the most reliable models against historical ERA5-Land data using the Kling-Gupta Efficiency (KGE) metric, followed by Quantile Mapping for bias correction of both historical and future scenarios. Evaluating nine wind turbine models (T1-T9) revealed that T1 and T2 maintained the highest historical capacity ratios, peaking at 68.0-76.5% and 59.5-68.0%, respectively. By 2100, meteorological projections indicate a regional warming trend coupled with a decrease in mean wind speed; notably, the high-emission SSP5-8.5 scenario projects the highest mean temperature (28°C) and lowest mean wind speed (3.8m/s). Despite these declines, future projections for T1 and T2 indicate resilient power generation and localized increases in strategic locations, such as Ras Ghareb and southern Egypt, particularly under the SSP2-4.5 scenario. Ultimately, these findings provide essential data-driven insights for energy planners to optimize turbine selection and site development, ensuring the long-term resilience of Egypt's wind energy infrastructure.

Rhipicephalus microplus, a one-host tick species, serves as a principal vector of tick-borne diseases in agricultural ecosystems worldwide by harboring and transmitting various pathogens through blood-feeding. In China, the climatically suitable range of R. microplus has been gradually expanding. However, the climatic suitability of R. microplus under future climate change scenarios remains unclear. This study evaluates both current and projected climatic suitability of R. microplus by integrating climatic variables, thereby providing insight into shifts in climatic suitability under present and future climate conditions. The MaxEnt model was applied using 78 occurrence records of R. microplus collected from 1970 to 2023, along with 19 environmental variables obtained from WorldClim. By identifying the most influential environmental factors affecting the climatic suitability of R. microplus, we predicted future changes under three Shared Socioeconomic Pathways (SSP126, SSP245, SSP585) for three future periods (2021-2040, 2041-2060, and 2061-2080). This study indicates that the current climatically suitable areas for R. microplus are mainly located in southern China, covering approximately 1,051,406 km2, which accounts for about 10.91% of China's total land area. The minimum temperature of the coldest month (Bio06, 69.6%) and precipitation of the warmest quarter (Bio18, 20.1%) were identified as the most influential climatic variables. Under future climate scenarios, the suitable habitat for R. microplus is projected to expand and shift northward. By 2061-2080 under the SSP585, the suitable area could reach up to 2,994,700 km2, representing a 2.85-fold increase relative to its current extent. This study projects a significant northward expansion of climatic suitability for R. microplus in mainland China under future climate scenarios, driven primarily by rising minimum winter temperatures. These findings highlight an urgent need for proactive, climate-integrated surveillance and adaptive control strategies to mitigate the growing threat of this tick vector and its associated diseases in newly vulnerable regions.

Heatwaves (HWs) are among the most impactful climate extremes affecting tropical urban environments, yet local‑scale assessments of their future characteristics remain scarce in the Amazon. Here, we quantify projected changes in key HW indicators for the Belém urban core, eastern Amazon, using a station‑referenced framework based on a carefully evaluated and bias‑corrected ensemble of CMIP6 global models. HWs are identified from daily maximum air temperature (Tmax) using a smoothed day‑of‑year 95th percentile threshold calculated over the 1994-2023 baseline period. Changes in annual frequency, event duration, and thermal intensity are assessed for near‑future (2025-2049) and far‑future (2050-2074) periods under four Shared Socioeconomic Pathways (SSP1‑2.6, SSP2‑4.5, SSP3‑7.0, and SSP5‑8.5). A multi‑metric performance evaluation is first applied to select the best‑performing CMIP6 models for Tmax over Belém, followed by bias correction using Quantile Delta Mapping calibrated against local observations. Results show a clear, scenario‑dependent intensification of HW hazards. In the current climate, 126 HW events were detected, with pronounced interannual variability and a marked increase during the last decade. Near‑future changes are modest and variable across scenarios. In contrast, far‑future projections under the high‑emission SSP5‑8.5 pathway reveal a substantial transformation of the HW regime: annual frequency more than doubles relative to the baseline, and the 99th percentile of event duration increases from approximately 19 to 65 days (Δ = +46 days), with a 14.5% probability that any given HW will exceed the current extreme threshold. Peak Tmax during HWs increases from 37.0°C to 37.55°C (Δ = +0.55°C), thus indicating an upper-tail amplification. Under the strong mitigation pathway SSP1‑2.6, changes in HW duration and intensity remain statistically indistinguishable from present‑day conditions. While this study does not assess impacts or adaptation capacity, the results provide a hazard‑based, scenario‑dependent characterization of future heatwave behavior in an Amazonian urban context, offering a quantitative foundation for subsequent assessments of climate risk in tropical cities.

Mapping climate-conditioned PM2.5 response under climate change in Taiwan using a high-resolution Geo-AI model.

Nonlinear maize yield responses to drought drive escalating regional vulnerabilities under climate change in China.

ABSTRACT Drought assessment is crucial for climate change adaptation. This study evaluated 10 CMIP6 climate models (MRI-ESM2, EC-EARTH3, CMCC-ESM2, INM-CM4-8, NorESM2-MM, MPI-ESM1.2-HR, INM-CM5, ACCESS-ESM1-5, IPSL-CM6A, and MIROC6) in representing droughts in the Capibaribe River Basin, Brazil. Drought characterization was assessed using the Standardized Precipitation Index (SPI) across multiple time scales (6–48 months) and statistical metrics (R, RB, MSE, RMSE, Kd, Kp). Results indicate that accuracy improves at longer time scales (SPI-24 and SPI-48). MIROC6 performed best overall, while INM-CM5, CMCC-ESM2, and ACCESS-ESM1-5 showed limited precision. Future projections under the Shared Socioeconomic Pathway 2–4.5 (SSP2–4.5) and Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) scenarios indicate a spatial divergence: coastal areas may face more frequent short-term droughts, while inland regions are likely to experience significantly more prolonged and intense multi-year events. These findings provide an evidence-based foundation for targeted water management to enhance water security against intensifying climate risks.

Global trends in population exposure to outdoor artificial light at night and future projections.

Global warming is reshaping energy demand in buildings, one of the largest sectors for energy consumption and CO2 emissions. Yet widely used mitigation scenarios, such as those in the Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP-RCP) framework, often assume fixed historical climate baselines when projecting building energy use. This modeling convention, originally intended to isolate anthropogenic effects, now increasingly overlooks how rising temperatures systematically alter heating and cooling needs. Here we integrate updated Heating and Cooling Degree Days, derived from the latest Coupled Model Intercomparison Project Phase 6 climate projections, into the Global Change Analysis Model to assess the consequences of incorporating future warming into global mitigation pathways. We find that ignoring warming trends introduces substantial biases: cooling demand is underestimated by up to 23% in scenarios with low warming and 79% in scenarios with high warming, while heating demand is overestimated by up to 14% and 40%, respectively, by 2100. Importantly, these misestimates reshape global energy and emissions trajectories, reducing CO2 emissions by 83-1600 Mt CO2 year-1 in 2100 when warming trends are included across different SSP-RCP scenarios, but also underestimating the rise in F-gas emissions related to cooling, especially in warmer developing regions.

Projected Increases in Heat-Related Emergency Department Imaging Utilization Under Climate Change Scenarios.

Introduction Climate change is affecting the regional patterns of plant diseases worldwide, including pigeonpea sterility mosaic disease (PPSMD). Its prevalence, severity, and potential spread are being progressively influenced by changes in India's temperature and moisture regimes. Methods Using Coupled Model Intercomparison Project (CMIP6) projections for 2050 and 2070 under the shared socioeconomic pathways (SSP) 126 and SSP 585 scenarios, we applied a thorough Maximum Entropy Modelling (MaxEnt) modelling approach to evaluate the climatic appropriateness of PPSMD under present and future conditions, and to assess the effects of climate change on PPSMD. Results The model showed high predictive performance during testing using a random subsample, with an area under the curve (AUC) of 0.986, True skill statistics (TSS) of 0.945, and Continuous Boyce index (CBI) of 0.935. The most significant climate parameters for the disease's ecological niche were annual average temperature (BIO1, 39.3%), precipitation of the wettest month (BIO13, 24.2%), temperature seasonality (BIO4, 12.8%), and precipitation of the warmest quarter of the year (BIO18, 12%). Current suitability maps identified high-risk regions in Southern and Central India. Future forecasts indicated that the geographical extent of climatically suitable areas will increase by 18.4% under SSP126 (2050s and 2070s) and by 20.6% with SSP585 for the same time period. Discussion This findings imply that pigeonpea systems are increasingly susceptible to climate change. These results provide insightful information about how diseases and climate combine to affect PPSMD dynamics. Additionally, they offer a strong scientific basis for enhancing early warning systems, monitoring, and management tactics in response to potential future climatic scenarios.

We extend the quantification of the Shared Socioeconomic Pathways (SSPs) narratives by projecting 188 socioeconomic indicators for 188 countries to 2150 using the International Futures model. The variables span demographics, conflict, economics, education, health, infrastructure, and governance using a fully integrated model. We address existing limitations related to a) misalignment between quantification and scenario narratives; b) inconsistencies driven by use of unconnected models; c) the omission of indicators; and d) absence of projections into the 22nd century. Here we show projections highly correlated with existing forecasts that also lead to lower economic growth because they are driven by broader factors including conflict, governance, infrastructure, and human development, which in turn leads to lower resource demand. We also introduce government spending measures by sector that can be used to connect the SSPs to broader theoretical understandings of future patterns of mitigation and adaptation in the face of climate change.

Climate change threatens nitrogen cycling in agricultural ecosystems. Optimizing sowing dates and nitrogen management for maize–soybean intercropping is critical for sustainable production in the North China Plain (NCP). Using a calibrated Agricultural Production Systems Simulator (APSIM) model driven by three representative global climate models (GCMs) selected from 20 Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs, we evaluated management strategies under two Shared Socioeconomic Pathway scenarios (SSP2-4.5 and SSP5-8.5) across three climatic zones for near-term (2030–2059) and long-term (2070–2099) periods. Under SSP5-8.5, warming was 1.8–2.2 times greater than under SSP2-4.5, nitrate nitrogen (NO3−-N) leaching increased by 12.1%, and nitrate storage in the 100–150 cm soil layer rose by 53.4% in Zone III. Biological nitrogen fixation contributed 20.1–29.1% of soybean nitrogen uptake under low nitrogen and 14.9–23.4% under medium nitrogen. Optimal strategies were identified: sowing on 7 June (S3) with medium nitrogen (220.8 kg N ha−1) under SSP2-4.5, and advancing sowing to 28 May (S2) with medium nitrogen under SSP5-8.5 to alleviate heat stress. This study reveals a climate-driven “earlier supply–shortened demand–concentrated leaching” mismatch, providing adaptive management guidance for maize–soybean intercropping systems in the NCP.

Climate change profoundly affects plant habitats and ecological niches, particularly among Tertiary relict flora—remnants of warm and humid climatic conditions that prevailed during the Tertiary period—which are recognized as highly climate-sensitive lineages. The genus Lindera (Lauraceae), a representative group of deciduous broad-leaved trees in East Asian temperate forests, provides an ideal model for examining shifts in habitat suitability and changes in predicted suitable environments under future climate change scenarios. In this study, we developed ensemble species distribution models (SDMs) using six algorithms to predict the distributions of four Lindera species—L. obtusiloba, L. glauca, L. erythrocarpa, and L. sericea—under three Shared Socioeconomic Pathway (SSP) scenarios (SSP1–2.6, SSP3–7.0, SSP5–8.5). Among the three categories of environmental variables, climatic factors exerted the greatest influence on habitat suitability, with temperature seasonality (bio4) and growing-season precipitation (gsp) identified as the primary determinants. With intensifying climate change, suitable habitats shifted northward and upward, accompanied by pronounced habitat losses across southern and central Korea. Despite its broad geographic range, L. obtusiloba exhibited an 81% reduction in suitable habitat, whereas L. sericea, due to its localized distribution, showed a 91% decrease and was identified as the most climate-vulnerable species. Ecological niche overlap (Schoener’s D) declined across all scenarios, indicating increasing ecological differentiation among species. Although the four Lindera species exhibited distinct spatial responses, all consistently experienced range contractions and reduced overlap in predicted suitable environments, indicating high vulnerability to climate change. These results suggest that intrinsic ecological traits, climatic sensitivity, and niche stability—rather than current geographic range extent—are key determinants of species persistence. Accordingly, Lindera species in southern Korea should be considered climate-vulnerable taxa, and conservation strategies should integrate the protection of climatically stable refugia with complementary conservation measures beyond natural habitats to ensure long-term persistence under future climate change.

High-resolution projections of extreme heat and thermal stress in southeastern U.S.

Understanding how the grain trade redistributes environmental burdens across regions is critical for designing equitable food security and environmental stewardship policies. Using grain production, trade and environmental data from 1980 to 2020, we quantify environmental spillovers embedded in China's interprovincial grain trade, identify their socio-economic and climatic drivers, project future scenarios and estimate ecological compensation schemes. Interprovincial grain trade increased more than fivefold (from 22 to 128 million tonnes), and production shifted northwards, generating a 196% increase in virtual cropland displacement, a 415% rise in virtual water consumption and more than a 217% increase in embodied nitrogen losses and greenhouse gas emissions in China. Irrigation, mechanization and urbanization were the key drivers of these shifts, outweighing climatic influences. Continued reliance on northern grain exports could escalate environmental costs, and climate-induced yield declines may shrink trade networks. Addressing these inequitable regional ecological burdens may require south-to-north transfers of up to US$12.5 billion by 2060 under Shared Socioeconomic Pathway 2-4.5.

Spatiotemporal dynamics of leptospirosis in Europe: a retrospective observational study with prospective projections.