Journal of environmental sciences (China)
Jun 14, 2020
Surface monitoring, vertical atmospheric column observation, and simulation using chemical transportation models are three dominant approaches for perception of fine particles with diameters less than 2.5 micrometers (PM) concentration. Here we explo...
The efficiency of disease prevention and medical care service necessitated the prediction of incidence. However, predictive accuracy and power were largely impeded in a complex system including multiple environmental stressors and health outcome of w...
International journal of environmental research and public health
Mar 19, 2020
Since operating urban air quality stations is not only time consuming but also costly, and because air pollutants can cause serious health problems, this paper presents the hourly prediction of ten air pollutant concentrations (CO, NH, NO, NO, NO, O,...
Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (<$300) air quality sensors could potentially offer an inexpensive and practic...
Environmental monitoring and assessment
Jun 28, 2019
PM air pollution is a significant issue for human health all over the world, especially in East Asia. A large number of ground-based measurement sites have been established over the last decade to monitor real-time PM concentration. However, even thi...
Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary linear regression. However, different algorithms hav...
We paired existing land use regression (LUR) models for ambient ultrafine particles in Montreal and Toronto, Canada with satellite images and deep convolutional neural networks as a means of extending the spatial coverage of these models. Our finding...
The safety and public health during nuclear power plant operation can be enhanced by accurately recognizing and diagnosing potential problems when a malfunction occurs. However, there are still obvious technological gaps in fault diagnosis applicatio...
This study presents a machine-learning-enhanced method of modeling PM personal exposures in a data-scarce, rural, solid fuel use context. Data collected during a cookstove (Africa Clean Energy (ACE)-1 solar-battery-powered stove) intervention program...
International journal of environmental health research
Mar 31, 2019
This study focuses on identifying environmental health risk factors related to acute respiratory diseases using deep learning method. Based on respiratory disease data, air pollution data and meteorological environmental data, cross-domain risk facto...