AIMC Topic: Climate Change

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Using machine learning to unravel chemical and meteorological effects on ground-level ozone: Insights for ozone-climate control strategies.

Environment international Jul 1, 2025
In the context of climate change, various countries/regions across East Asia have witnessed severe ground-level ozone (O) pollution, which poses potential health risks to the public. The complex relationships between O and its drivers, including the ...
Climate Change Meteorological Concepts Seasons Volatile Organic Compounds Environmental Monitoring Taiwan Air Pollution Ozone Air Pollutants Machine Learning
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Data-driven multi-hazard susceptibility and community perceptions assessment using a mixed-methods approach.

Journal of environmental management Jul 1, 2025
Assessing multi-hazard susceptibility and understanding community insights are important for effective disaster risk management; however, limited research has been conducted to study these aspects together. This study uses a data-driven approach to a...
Pakistan Climate Change Disaster Planning Geographic Information Systems Surveys and Questionnaires Landslides Perception Floods
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Modeling and prediction of climate change impacts on water resources vulnerability: A multi-model approach.

Journal of environmental management Jul 1, 2025
In a rapidly changing world, uncontrolled climate change worsens water scarcity disrupting hydrological cycles and hindering sustainable development. Addressing water resources vulnerability requires holistic approaches to better understand complex s...
Water Resources Climate Change Water Supply Machine Learning Models, Theoretical
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Intergenerational inequity from hydrological drought in a warming world.

Journal of environmental management Jul 1, 2025
As warmer temperatures enhance atmospheric moisture, hydrological droughts tend to intensify in most regions of the globe. Consequently, younger generations are expected to face a more severe risk of hydrological drought during their lifetimes, empha...
Climate Change Humans Droughts Hydrology
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The Biogeography of Soil Bacteria in Australia Exhibits Greater Resistance to Climate Change Than Fungi.

Global change biology Jun 1, 2025
Soil microorganisms are crucial to ecosystem health, and their composition and distribution are shaped by a range of environmental factors. However, the effects of accelerating climate change on soil microbiomes remain under-explored. This study exam...
Bacteria Microbiota Fungi Climate Change Soil Microbiology Australia
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Quantifying the impact of future climate change on the risk of coral rubble instability across the Great Barrier Reef by 2100.

Journal of environmental management Jun 1, 2025
Coral reef systems are facing unprecedented pressures due to climate change, and stable coral rubble substrates are crucial for facilitating large-scale coral regeneration. This study integrates the Sixth Phase of the Coupled Model Intercomparison Pr...
Anthozoa Climate Change Coral Reefs Animals
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Sustainable water allocation under climate change: Deep learning approaches to predict drinking water shortages.

Journal of environmental management Jun 1, 2025
Addressing sustainable urban water supply has become one of the most critical challenges for modern megacities, particularly in arid and semi-arid regions where rapid urbanization and climate change converge to exacerbate resource scarcity. Tehran, a...
Climate Change Groundwater Neural Networks, Computer Water Supply Drinking Water Iran Deep Learning Water Resources
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A multi-objective optimization model integrating machine learning and time-frequency analysis for supporting nitrogen and phosphorus pollution reduction in Guangzhou city, China.

Journal of environmental management Jun 1, 2025
The unbridled discharge of nitrogen and phosphorus (NP) pollutants is believed to have surpassed ecosystem resilience limits for many regions, which is of great concern to research and governmental communities. In this research, a multi-objective opt...
Environmental Monitoring Nitrogen Climate Change Phosphorus China Machine Learning Models, Theoretical
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Using supervised machine-learning approaches to understand abiotic stress tolerance and design resilient crops.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences May 29, 2025
Abiotic stresses such as drought, heat, cold, salinity and flooding significantly impact plant growth, development and productivity. As the planet has warmed, these abiotic stresses have increased in frequency and intensity, affecting the global food...
Supervised Machine Learning Crops, Agricultural Stress, Physiological Climate Change Plant Breeding
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Amazon's climate crossroads: analyzing air pollution and health impacts under machine learning-based temperature increase scenarios in Northern Mato Grosso, Brazil.

Environmental geochemistry and health May 14, 2025
Air pollution has long been a public health concern in South America, now increasingly linked to climate change. In Brazil, this issue is particularly acute in smaller cities with limited monitoring infrastructure. Sinop, located in the Amazon biome ...
Health Impact Assessment Temperature Brazil Seasons Humans Climate Change Ozone Environmental Monitoring Air Pollutants Public Health Machine Learning Air Pollution Cities Particulate Matter
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