AIMC Topic: Ozone
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Predicting plateau atmospheric ozone concentrations by a machine learning approach: A case study of a typical city on the southwestern plateau of China.
Environmental pollution (Barking, Essex : 1987)
Oct 4, 2024
Atmospheric ozone (O) has been placed on the priority control pollutant list in China's 14th Five-Year Plan. Due to their unique meteorological conditions, plateau regions contain high concentrations of atmospheric O. However, traditional experimenta...
Unraveling the complex interactions between ozone pollution and agricultural productivity in China's main winter wheat region using an interpretable machine learning framework.
The Science of the total environment
Sep 14, 2024
Surface ozone has become a significant atmospheric pollutant in China, exerting a profound impact on crop production and posing a serious threat to food security. Previous studies have extensively explored the physiological mechanisms of ozone damage...
Unraveling the Influence of Satellite-Observed Land Surface Temperature on High-Resolution Mapping of Ground-Level Ozone Using Interpretable Machine Learning.
Environmental science & technology
Aug 27, 2024
Accurately mapping ground-level ozone concentrations at high spatiotemporal resolution (daily, 1 km) is essential for evaluating human exposure and conducting public health assessments. This requires identifying and understanding a proxy that is well...
Use of machine learning algorithms to determine the relationship between air pollution and cognitive impairment in Taiwan.
Ecotoxicology and environmental safety
Aug 15, 2024
Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This study used m...
The Lag -Effects of Air Pollutants and Meteorological Factors on COVID-19 Infection Transmission and Severity: Using Machine Learning Techniques.
Journal of research in health sciences
Jul 31, 2024
BACKGROUND: Exposure to air pollution is a major health problem worldwide. This study aimed to investigate the effect of the level of air pollutants and meteorological parameters with their related lag time on the transmission and severity of coronav...
Prediction of hydroxyl radical exposure during ozonation using different machine learning methods with ozone decay kinetic parameters.
Water research
Jul 10, 2024
The abatement of micropollutants by ozonation can be accurately calculated by measuring the exposures of molecular ozone (O) and hydroxyl radical (OH) (i.e., ∫[O]dt and ∫[OH]dt). In the actual ozonation process, ∫[O]dt values can be calculated by mon...
Innovative approaches for accurate ozone prediction and health risk analysis in South Korea: The combined effectiveness of deep learning and AirQ.
The Science of the total environment
Jun 21, 2024
Short-term exposure to ground-level ozone (O) poses significant health risks, particularly respiratory and cardiovascular diseases, and mortality. This study addresses the pressing need for accurate O forecasting to mitigate these risks, focusing on ...
Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950-2014.
Environmental pollution (Barking, Essex : 1987)
Jun 19, 2024
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...
Identifying Driving Factors of Atmospheric NO with Machine Learning.
Environmental science & technology
Jun 18, 2024
Dinitrogen pentoxide (NO) plays an essential role in tropospheric chemistry, serving as a nocturnal reservoir of reactive nitrogen and significantly promoting nitrate formations. However, identifying key environmental drivers of NO formation remains ...
Coastal ozone dynamics and formation regime in Eastern China: Integrating trend decomposition and machine learning techniques.
Journal of environmental sciences (China)
Jun 6, 2024
Machine-learning is a robust technique for understanding pollution characteristics of surface ozone, which are at high levels in urban China. This study introduced an innovative approach combining trend decomposition with Random Forest algorithm to i...
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