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Air Pollutants

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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...

A new attention-based CNN_GRU model for spatial-temporal PM prediction.

Environmental science and pollution research international
Accurately predicting the spatial-temporal distribution of PM is challenging due to missing data and selecting an appropriate modeling method. Effective imputation of missing data must consider the relationships between variables while preserving the...

Accurate PM urban air pollution forecasting using multivariate ensemble learning Accounting for evolving target distributions.

Chemosphere
Over the past decades, air pollution has caused severe environmental and public health problems. According to the World Health Organization (WHO), fine particulate matter (PM), a key component reflecting air quality, is the fourth leading cause of de...

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...

Spatial source, simulating improvement, and short-term health effect of high PM exposure during mutation event in the key urban agglomeration regions in China.

Environmental pollution (Barking, Essex : 1987)
Air quality in China has significantly improved owing to the effective implementation of pollution control measures. However, mutation events caused by short-term spikes in PM in urban agglomeration regions continue to occur frequently. Identifying t...

Elevating hourly PM forecasting in Istanbul, Türkiye: Leveraging ERA5 reanalysis and genetic algorithms in a comparative machine learning model analysis.

Chemosphere
Rapid urbanization and industrialization have intensified air pollution, posing severe health risks and necessitating accurate PM predictions for effective urban air quality management. This study distinguishes itself by utilizing high-resolution ERA...

Do machine learning methods improve prediction of ambient air pollutants with high spatial contrast? A systematic review.

Environmental research
BACKGROUND & OBJECTIVE: The use of machine learning for air pollution modelling is rapidly increasing. We conducted a systematic review of studies comparing statistical and machine learning models predicting the spatiotemporal variation of ambient ni...

Prediction of PM concentration based on a CNN-LSTM neural network algorithm.

PeerJ
Fine particulate matter (PM) is a major air pollutant affecting human survival, development and health. By predicting the spatial distribution concentration of PM, pollutant sources can be better traced, allowing measures to protect human health to b...

Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models.

The Science of the total environment
This study aims to address accuracy challenges in assessing air pollution health impacts using Environmental Benefits Mapping and Analysis Program (BenMap), caused by limited meteorological factor data and missing pollutant data. By employing data in...

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...