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Climate Change

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Artificial intelligence in the era of planetary health: insights on its application for the climate change-mental health nexus in the Philippines.

International review of psychiatry (Abingdon, England)
This review explores the transformative potential of Artificial Intelligence (AI) in the light of evolving threats to planetary health, particularly the dangers posed by the climate crisis and its emerging mental health impacts, in the context of a c...

A hybrid SWAT-ANN model approach for analysis of climate change impacts on sediment yield in an Eastern Himalayan sub-watershed of Brahmaputra.

Journal of environmental management
The current study focuses on analyzing the impacts of climate change and land use/land cover (LULC) changes on sediment yield in the Puthimari basin, an Eastern Himalayan sub-watershed of the Brahmaputra, using a hybrid SWAT-ANN model approach. The a...

Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950-2014.

Environmental pollution (Barking, Essex : 1987)
Due to a lack of long-term observations in China, reports on historical ozone concentration are severely limited. In this study, by combining observation, reanalysis and model simulation data, XGBoost machine learning algorithm is used to correct the...

Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HEAT Center study protocol.

BMJ open
INTRODUCTION: African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, compounded by increasing temperatures due to climate change. This study aims to understand the compl...

Comparative assessment of deep belief network and hybrid adaptive neuro-fuzzy inference system model based on a meta-heuristic optimization algorithm for precise predictions of the potential evapotranspiration.

Environmental science and pollution research international
Accurately predicting potential evapotranspiration (PET) is crucial in water resource management, agricultural planning, and climate change studies. This research aims to investigate the performance of two machine learning methods, the adaptive netwo...

Machine learning and CORDEX-Africa regional model for assessing the impact of climate change on the Gilgel Gibe Watershed, Ethiopia.

Journal of environmental management
Climate change is one of the most pressing challenges of our time, profoundly impacting global water resources and sustainability. This study aimed to predict the long-term effects of climate change on the Gilgel Gibe watershed by integrating machine...

Investigating the effect of climate factors on fig production efficiency with machine learning approach.

Journal of the science of food and agriculture
BACKGROUND: This study employs a machine learning approach to investigate the impact of climate change on fig production in Turkey. The eXtreme Gradient Boosting (XGBoost) algorithm is used to analyze production performance and climate variable data ...

Development and application of machine learning models for prediction of soil available cadmium based on soil properties and climate features.

Environmental pollution (Barking, Essex : 1987)
Identifying the key influencing factors in soil available cadmium (Cd) is crucial for preventing the Cd accumulation in the food chain. However, current experimental methods and traditional prediction models for assessing available Cd are time-consum...

An evaluative technique for drought impact on variation in agricultural LULC using remote sensing and machine learning.

Environmental monitoring and assessment
Drought events threaten freshwater reservoirs and agricultural productivity, particularly in semi-arid regions characterized by erratic rainfall. This study evaluates a novel technique for assessing the impact of drought on LULC variations in the con...