Estimating PM2.5 Concentration and Evaluating National Ambient Air Quality Standard in Johannesburg Area, South Africa Público

Du, Linlin (Spring 2020)

Permanent URL: https://etd.library.emory.edu/concern/etds/w9505154d?locale=pt-BR
Published

Abstract

It is well recognized that fine particle (PM2.5) from multiple sources, including fuel combustion, vehicle emission and domestic burning, is strongly associated with a large burden of illness in South Africa, especially respiratory diseases, yet few studies well characterized ambient PM2.5 concentration with high spatiotemporal resolution in South Africa. We developed a random forest model to estimate daily PM­2.5 concentration at 1 km2 resolution in the Johannesburg Area, combining satellite AOD, meteorological factors and land-use variables, and evaluated the impact of implementation of national air quality standard on PM2.5 concentration. Overall cross-validation R2 was 0.67, indicating a good fit between model estimation and ground measurements. Mean PM2.5 for ground measurements was 28.15 µg/m3 and mean estimated PM2.5 concentration was 28.24 µg/m3. MAIAC AOD, total precipitation, winter, population, population, spring, summer, policy, temperature at 2-meter, relative humidity at planetary boundary layer height, and wind speed at planetary boundary layer height were the most important predictors. Estimation from the model has captured the temporal pattern for ground monitoring stations. Mpumalanga had a lower annual PM2.5 concentration than Gauteng. The maximum annual PM2.5 concentration appeared in the region between Pretoria and Bronkhorstspruit. By comparing PM2.5 concentration, we concluded that the implementation of national air quality standards has not achieved the goal of reducing PM2.5 concentration.

Table of Contents

1.Introduction 1

2.Method 4

2.1 Study Area 4

2.2 Ground measurement 4

2.3 Satellite AOD 5

2.4 Meteorological data 5

2.5 Land use 6

2.6 Temporal Variables 6

2.7 Modelling 7

2.8 Policy Analysis 7

3.Results 7

3.1 Ground Measurements 7

3.2 Gap Filled MAIAC AOD 8

3.3 Random Forest Model Performance 9

3.4 PM2.5 Prediction 9

3.5 PM2.5 Concentration Changes in Implementation of New Standard 11

4.Discussion 11

5.Conclusion 15

6.Reference 16

7.Figures and Tables 19

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