Ambient exposure to fine particulate matter (PM) is known to harm public health in China. Satellite remote sensing measurements of aerosol optical depth (AOD) were statistically associated with in-situ observations after 2013 to predict PM concentrat...
International journal of environmental research and public health
Dec 17, 2018
This review clarifies particulate matter (PM) pollution, including its levels, the factors affecting its distribution, and its health effects on passengers waiting at bus stations. The usual factors affecting the characteristics and composition of PM...
Ecotoxicology and environmental safety
Nov 17, 2018
Particulate matter with aerodynamic diameter less than 2.5 µm (PM) in indoor public spaces such as subway stations, has represented a major public health concern; however, forecasting future sequences of quantitative health risk is an effective metho...
Particulate matter with aerodynamic diameter less than 2.5 μm (PM) is a complex mixture of chemical constituents emitted from various emission sources or through secondary reactions/processes; however, PM is regulated mostly based on its total mass c...
Environmental pollution (Barking, Essex : 1987)
Oct 13, 2018
Urban population exposure to tropospheric ozone is a serious health concern in Europe countries. Although there are insufficient evidence to derive a level below which ozone has no effect on mortality WHO (World Health Organization) uses SOMO35 (sum ...
Environmental pollution (Barking, Essex : 1987)
Aug 11, 2018
Fine particulate matter (PM) has been recognized as a key air pollutant that can influence population health risk, especially during extreme cases such as wildfires. Previous studies have applied geospatial techniques such as land use regression to m...
Environmental pollution (Barking, Essex : 1987)
Jun 23, 2018
In order to improve the prediction accuracy and real-time of the air pollutant concentration prediction, this paper proposes self-adaptive neuro-fuzzy weighted extreme learning machine (ANFIS-WELM) based on the weighted extreme learning machine (WELM...
Journal of the Air & Waste Management Association (1995)
May 24, 2018
UNLABELLED: This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of ide...
BACKGROUND: Machine learning algorithms have very high predictive ability. However, no study has used machine learning to estimate historical concentrations of PM (particulate matter with aerodynamic diameter ≤ 2.5 μm) at daily time scale in China at...
Previous research suggested an association between maternal exposure to ambient air pollutants and risk of congenital heart defects (CHDs), though the effects of particulate matter ≤10μm in aerodynamic diameter (PM) on CHDs are inconsistent. We used ...
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