Enhancing Environmental Public Health Tracking with Satellite-Driven Particle Exposure Data Public

Abstract

Background: PM2.5 poses a threat to human health which demands implementation of
emission and quality standards. Unfortunately, current ground-level ambient air monitors
lack spatial coverage across rural, suburban, and even urban areas, necessitating the use
of remote sensing in air quality monitoring. Moderate Resolution Imaging
Spectroradiometer (MODIS) instrumentation estimates an aerosol optical depth (AOD),
which is correlated with PM2.5 concentrations. MODIS gives one central AOD estimate
for 10 km x 10 km pixels across the globe. However, it is not yet understood how well
the satellite-driven PM2.5 estimate represents such a large pixel. The goal of the current
study is to analyze MODIS resolution in its ability to detect PM2.5 spatial heterogeneity;
the more spatially heterogeneous a pixel, the less likely one central MODIS estimate
accurately represents the varying concentrations in that pixel.
Methods: Three ground-level PM2.5 samplers were deployed in two separate pixels: one
pixel with historically 'average' PM means, and one with historically 'elevated' means.
2.5
As MODIS estimates AOD from the center of the pixel, one sampler was set at each pixel
centroid in order to determine MODIS estimate accuracy. Daily PM2.5 concentrations
were compared across the three sites in the same pixel in order to explore the level of
spatial heterogeneity in concentrations.
Results: Overall, almost all pairwise Spearman's correlation coefficients were indicative
of strong correlations between site concentrations. The 'elevated' pixel's centroid was
moderately correlated with MODIS estimates ( R= 0.52). Correlations between the
'average' centroid and MODIS estimate were very strong ( R= 0.75), suggesting MODIS
accuracy at the centroid. Concentrations in the 'average' pixel were also found to be
heterogeneous across the three sites. This heterogeneity supports the hypothesis that a
pixel sized 10 km2 experiences a large variation in PM2.5 concentrations that current
spatial resolution of MODIS instrumentation fails to capture.

Table of Contents

TABLE OF CONTENTS

BACKGROUND: ............................................................................................................................ 1
METHODS: ..................................................................................................................................... 5
Monitoring Program Overview .................................................................................................... 5
Site Selection ................................................................................................................................ 6
Ground-level Sampling Protocol ................................................................................................. 6
Gravimetric Analysis ................................................................................................................... 8
Quality Assurance/Quality Control ............................................................................................. 9
MODIS Data Retrieval ................................................................................................................ 9
Data Analysis ............................................................................................................................. 10
RESULTS and DISCUSSION: ...................................................................................................... 11
CONCLUSION .............................................................................................................................. 21
REFERENCES .............................................................................................................................. 23
APPENDIX .................................................................................................................................... 25

About this Master's Thesis

Rights statement

• Permission granted by the author to include this thesis or dissertation in this repository. All rights reserved by the author. Please contact the author for information regarding the reproduction and use of this thesis or dissertation.

School	Rollins School of Public Health
Department	Environmental Health
Degree	MPH
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Public Health
Mot-clé	air quality atmospheric remote sensing particulate matter MODIS
Committee Chair / Thesis Advisor	Sarnat, Jeremy, Emory University
Committee Members	Tolbert, Paige, Emory University
Partnering Agencies	Does not apply (no collaborating organization)

Dernière modification

Primary PDF

Thumbnail	Title	Date Uploaded	Actions
	Enhancing Environmental Public Health Tracking with Satellite-Driven Particle Exposure Data ()	2018-08-28 11:46:02 -0400	Press to Select an action Download

Supplemental Files

Thumbnail	Title	Date Uploaded	Actions