Date of Award

6-2018

Culminating Project Type

Thesis

Degree Name

Geography - Geographic Information Science: M.S.

Department

Geography and Planning

College

School of Public Affairs

First Advisor

Mikhail Blinnikov

Second Advisor

Jeffrey Torguson

Third Advisor

Jeffrey Cheng

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

The purpose of this paper is trying to use air monitoring data of Particulate Matter (PM 2.5) from 19 monitoring sites in Minnesota, to determine the correlations between PM 2.5 and the influencing factors, such as road traffic, tree space area, and rainfall. The study will be based on pollutant data which were from Environment Protection Agency (EPA) and Minnesota Pollution Control Agency (MPCA), then through regression analysis and Pearson correlation analysis to determine the correlations of all variables. The correlation analysis results between PM 2.5 concentration and three variables (tree space area, traffic volume, and rainfall) showed that tree space area ratio had a negative, traffic volume had a positive and rainfall had a negative, correlation with PM 2.5 in Minnesota urban. The air traffic volume had a positive correlation with PM 2.5 in airport areas.

In this study, GIS system is a useful tool for geostatistical analysis. It can be used for Normalized Difference Vegetation Index (NDVI) analysis, raster data geoprocessing, and kriging spatial analysis.

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