98%
921
2 minutes
20
Forecasting alterations in ambient air pollution and the consequent health implications is crucial for safeguarding public health, advancing environmental sustainability, informing economic decision making, and promoting appropriate policy and regulatory action. However, predicting such changes poses a substantial challenge, requiring accurate data, sophisticated modeling methodologies, and a meticulous evaluation of multiple drivers. In this study, we calculate premature deaths due to ambient fine particulate matter (PM) exposure in India from the 2020s (2016-2020) to the 2100s (2095-2100) under four different socioeconomic and climate scenarios (SSPs) based on four CMIP6 models. PM concentrations decreased in all SSP scenarios except for SSP3-7.0, with the lowest concentration observed in SSP1-2.6. The results indicate an upward trend in the five-year average number of deaths across all scenarios, ranging from 1.01 million in the 2020s to 4.12-5.44 million in the 2100s. Further analysis revealed that the benefits of reducing PM concentrations under all scenarios are largely mitigated by population aging and growth. These findings underscore the importance of proactive measures and an integrated approach in India to improve atmospheric quality and reduce vulnerability to aging under changing climate conditions.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/acs.est.4c02264 | DOI Listing |
Bidens macroptera symbolizes the change of a season, marking the transition from the rainy season to autumn, heralding the new year for Ethiopians. Despite a general understanding of its geographic regions, significant gaps remain in identifying the habitat distribution and key predictor variables of Bidens macroptera through species distribution modeling (SDM) in the context of climate change. We developed an ensemble species distribution model using 2 statistical and 3 machine learning algorithms.
View Article and Find Full Text PDFBiology (Basel)
August 2025
Guizhou Institute of Forest Inventory and Planning, Guiyang 550003, China.
Global warming is accelerating the poleward and upward shifts in climatically suitable ranges of species. (switchgrass) is recognized for its dual value in China's dual-carbon strategy: mitigating food-energy land competition and restoring marginal ecosystems. However, the accuracy of habitat projections is constrained by three limitations: reliance on North American provenance data, uncalibrated model parameters, and insufficient scenario coverage.
View Article and Find Full Text PDFSci Data
September 2025
Global Data Lab, Economics, Institute for Management Research, Radboud University, Nijmegen, the Netherlands.
This data descriptor presents the GVI Projections Database with projections of socioeconomic vulnerability for the period 2020-2100 along three Shared Socioeconomic Pathways (SSPs) for almost all countries of the world. The projections are based on the GDL Vulnerability Index (GVI), a composite index for monitoring the human components of vulnerability to climate change, natural disasters and other shocks for societies and geographic areas across the globe. The GVI is based on an additive formula that summarizes the essence of seven major socioeconomic dimensions of vulnerability into one number.
View Article and Find Full Text PDFNat Commun
August 2025
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, , CA, USA.
Extreme cold surges, very large temperature drops over a short period of time, have serious impacts on human health, energy supply and ecosystems. While changes in temperature variability and cold extremes in a warming climate are well understood, changes in extreme cold surges and their driving mechanisms are not. Here we show that extreme cold surges have robustly weakened in middle-to-high latitude continents during autumn and winter but have remained almost unchanged in lower latitudes.
View Article and Find Full Text PDFSci Rep
August 2025
School of Geographical Sciences, Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China.
Global warming and the rising frequency of extreme climate events pose significant threats to food security. We examine the influence of climate change on food security in Sub-Saharan Africa, with a specific emphasis on four key crops: maize, rice, wheat, and soybeans. We employ a random forest model to estimate spatial and temporal yield trends based on climate variables, land‑use patterns, and irrigation ratios.
View Article and Find Full Text PDF