AIMC Topic: Climate Change

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Assessment of climate change impacts on arsenic contamination in groundwater through machine learning, remote sensing, and GIS: a review.

Environmental geochemistry and health
More than 50% of the world's largest countries and cities depend on groundwater for their daily needs. In particular, 80% of the largest cities in the Middle East, South Asia, and Central Asia rely on groundwater for drinking, irrigation, and industr...

Harnessing multi-omics and genome-editing technologies for climate-resilient agriculture: bridging AI-driven insights with sustainable crop improvement.

Plant molecular biology
Environmental challenges such as drought, salinity, heavy metal contamination, and nutrient deficiencies threaten global agricultural productivity and food security. These stressors drastically reduce crop yields, necessitating innovative solutions. ...

Machine learning predictions of climate change effects on nearly threatened bird species (Crithagra xantholaema) habitat in Ethiopia for conservation strategies.

Scientific reports
Endemic and endangered bird species, such as Salvadori serin (C. xantholaema), are vulnerable to environmental and anthropogenic changes. Understanding the impact of climate change on ecological niches is essential for effective conservation. This st...

Identifying Priority Nutrients for Achieving Water Quality Improvement and Climate Change Mitigation.

Environmental science & technology
Riverine and lake ecosystems are sources of global non-CO greenhouse gases (GHGs) and serve as sinks for pollutants, facing the dual challenges of mitigating GHG emissions and controlling water pollution. However, interactions between pollutant input...

Detection of climate change signals using precipitation and temperature time series by a hybrid deep learning framework.

Environmental monitoring and assessment
Climate change is one of the most extreme challenges of the twenty-first century. Precipitation (pr) and temperature variability are key indicators of climate change detection. Whereas hybrid deep learning (DL) models have been widely applied, their ...

Declining ocean greenness and phytoplankton blooms in low to mid-latitudes under a warming climate.

Science advances
Marine phytoplankton are crucial to oceanic ecosystems, yet trends in their activity, monitored through chlorophyll a, remain uncertain due to observational limitations. We generated an ocean chlorophyll a dataset (2001 to 2023) across low to mid-lat...

Analysis of spatial heterogeneity in Xi'an's urban heat island effect using multi-source data fusion.

PloS one
In the context of global climate change, this study aims to investigate the spatial heterogeneity and driving mechanisms of the urban heat island (UHI) effect within Xi'an's second ring road area. We constructed a novel multi-source data fusion frame...

A scoping review of future research trends and priorities in health systems.

Health research policy and systems
BACKGROUND: Health systems worldwide are increasingly influenced by rapid and complex changes across various domains. Anticipating and responding to these changes is critical to ensuring the sustainability and effectiveness of health systems. Future-...

Climate change and its impact on spatial and temporal distribution of visceral leishmaniasis transmission risk in Nepal.

BMC infectious diseases
Visceral leishmaniasis (VL), also known as kala-azar, has posed significant challenges to elimination efforts due to increased reporting of new cases from high mountain and previously considered non-endemic areas in Nepal. Understanding the potential...

Design of global climate control based on fuzzy systems with concept of carbon emissions.

PloS one
The global carbon-climate system is a highly complex and dynamic network characterized by multiple feedback loops between interconnected components. Addressing the risks of climate change requires active intervention across these components (Atmosphe...