AIMC Topic: Ozone

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Accurate and efficient prediction of atmospheric PM, PM, PM, and O concentrations using a customized software package based on a machine-learning algorithm.

Chemosphere
Particulate matter (PM) and ozone (O) pollution have been attracting increasing attention recently due to their severe harm to human health. PM and O are secondary pollutants, and there remain significant challenges in accurately and efficiently pred...

High spatiotemporal resolution estimation and analysis of global surface CO concentrations using a deep learning model.

Journal of environmental management
Ambient carbon monoxide (CO) is a primary air pollutant that poses significant health risks and contributes to the formation of secondary atmospheric pollutants, such as ozone (O). This study aims to elucidate global CO pollution in relation to healt...

3DVar sectoral emission inversion based on source apportionment and machine learning.

Environmental pollution (Barking, Essex : 1987)
Air quality models are increasingly important in air pollution forecasting and control. Sectoral emissions significantly impact the accuracy of air quality models and source apportionment. This paper studied the 3DVar (three-dimensional variational) ...

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)
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
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
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
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
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
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
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 ...