Date of Graduation

Summer 2020

Degree

Master of Science in Geospatial Sciences

Department

Geography, Geology, and Planning

Committee Chair

Xiaomin Qiu

Keywords

Particulate Matter 2.5, PM2.5, China, Yangtze River Delta, IDW, GWTC-2, space-time pattern analysis, GIS

Subject Categories

Earth Sciences | Environmental Sciences | Statistics and Probability

Abstract

Particulate Matter 2.5 (PM2.5) is a growing concern in industrialized countries. In China, high concentrations of PM2.5 are causing devastating health and environmental effects for the people living there. Coal-burning for domestic and industrial purposes is the main culprit for decreasing air quality in China. The focus of this paper is on the Yangtze River Delta (YRD) located on the eastern coast of China. Hourly PM2.5 readings from March 2015 to June 2016 were obtained from 125 air quality monitoring stations (AQMS) in 23 cities in the YRD. In this study, PM2.5 readings were examined using TIBCO Spotfire and ArcGISPro. Space-time pattern analysis and inverse distance weighting (IDW) were adopted in observing space-time trends and dispersion of PM2.5 in the region. Inverse distance weighting (IDW) interpolation represents the distribution of PM2.5 in YRD, with peak values greater than 61 ug/m3 observed across the study area in December 2015, January 2016 and February 2016. Zhejiang had lower interpolated values in comparison with Jiangsu and Shanghai. Based on the space-time pattern analysis, PM2.5 demonstrated a downtrend along the Yangtze River during the study period. Furthermore, a relationship between global gridded weather type classification (GWTC-2) weather types was examined with declining PM2.5 concentrations. The results show Humid (H), Humid Warm (HW), and Warm (W) weather types are associated with declining levels of PM2.5 in Jiangsu and Shanghai in March, April, May, June 2015. While in March, April, May, June 2016, Warm (W), Humid (H), and Cold Front Passage (CFP) are associated with declining levels of PM2.5 in Zhejiang and only Warm (W) in Jiangsu.

Copyright

© Muhammad Abdullah

Open Access

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