Spatiotemporal dynamic interpolation simulation and prediction method of fine particulate matter based on multi-source pollution model

Interpolation and Prediction of Spatiotemporal Data Based on XML Integrated with Grey Dynamic Model

Interpolation and prediction of spatiotemporal data are integral components of many real-world applications. Thus, approaches of interpolating and predicting spatiotemporal data have been extensively investigated. Currently, the grey dynamic model has been used to enhance the performance of interpolating and predicting spatiotemporal data. Meanwhile, the Extensible Markup Language (XML) has uni...

Transboundary Pollution: Ozone and Fine Particulate Matter in the Northeast

Atmospheric lead pollution in fine particulate matter in Shanghai, China.

The Pb-monitoring program was extended for 6 years from 2002 to 2007 at 17 representative urban sites (6 traffic, 5 industrial, and 6 residential sites), and 3 suburban sites to assess the lead pollution in fine particulate matter (PM2.5) after phasing out leaded gasoline in Shanghai. Compared with Pb levels reported in other places, the Pb pollution in Shanghai is still serious after phasing o...

Spatiotemporal Changes in Fine Particulate Matter Pollution and the Associated Mortality Burden in China between 2015 and 2016

In recent years, research on the spatiotemporal distribution and health effects of fine particulate matter (PM2.5) has been conducted in China. However, the limitations of different research scopes and methods have led to low comparability between regions regarding the mortality burden of PM2.5. A kriging model was used to simulate the distribution of PM2.5 in 2015 and 2016. Relative risk (RR) ...

Estimating Population Exposure to Fine Particulate Matter in the Conterminous U.S. using Shape Function-based Spatiotemporal Interpolation Method: A County Level Analysis.

This paper investigates spatiotemporal interpolation methods for the application of air pollution assessment. The air pollutant of interest in this paper is fine particulate matter PM2.5. The choice of the time scale is investigated when applying the shape function-based method. It is found that the measurement scale of the time dimension has an impact on the quality of interpolation results. B...