Spatial scales of pollution from variable resolution satellite imaging

Alexandra A. Chudnovsky; Alex Kostinski; Alexei Lyapustin; Petros Koutrakis

doi:10.1016/j.envpol.2012.08.016

Spatial scales of pollution from variable resolution satellite imaging

Alexandra A. Chudnovsky, Alex Kostinski, Alexei Lyapustin, Petros Koutrakis

Research output: Contribution to journal › Article › peer-review

Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM_2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM _2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM_2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM_2.5 levels and wind speed.

Original language	English
Pages (from-to)	131-138
Number of pages	8
Journal	Environmental Pollution
Volume	172
DOIs	https://doi.org/10.1016/j.envpol.2012.08.016
State	Published - Jan 2013
Externally published	Yes

Keywords

Aerosol optical depth
Fine particulate matter
High resolution aerosol retrieval
Intra-urban pollution
MAIAC
MODIS
Particulate matter
Scales of pollution
Variability AOD-PM correlation

All Science Journal Classification (ASJC) codes

Toxicology
Pollution
Health, Toxicology and Mutagenesis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.envpol.2012.08.016

Cite this

@article{6319ea8f2da34e6b9068371390ca8cad,

title = "Spatial scales of pollution from variable resolution satellite imaging",

abstract = "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM2.5 levels and wind speed.",

keywords = "Aerosol optical depth, Fine particulate matter, High resolution aerosol retrieval, Intra-urban pollution, MAIAC, MODIS, Particulate matter, Scales of pollution, Variability AOD-PM correlation",

author = "Chudnovsky, {Alexandra A.} and Alex Kostinski and Alexei Lyapustin and Petros Koutrakis",

note = "Funding Information: This research was supported by a post-doctoral fellowship from the Environment Health Fund (EHF), Jerusalem, Israel . This work was also made possible by USEPA grant RD 83479801 . Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the USEPA. Further, USEPA does not endorse the purchase of any commercial products or services mentioned in the publication. This work was also supported in part by the NSF Grant AGS-1119164 . Authors greatly appreciate important comments of Dr. Mike Wolfson and Dr. Joy E. Lawrence. We also thank Dr. Yujie Wang for the MODIS data processing. Authors are also grateful to Prof. Pandey, A. Lappi and K. Wollan of Michigan Technological University. The authors also wish to thank the anonymous reviewers for their constructive comments.",

year = "2013",

month = jan,

doi = "10.1016/j.envpol.2012.08.016",

language = "الإنجليزيّة",

volume = "172",

pages = "131--138",

journal = "Environmental Pollution",

issn = "0269-7491",

publisher = "Elsevier Ltd.",

}

TY - JOUR

T1 - Spatial scales of pollution from variable resolution satellite imaging

AU - Chudnovsky, Alexandra A.

AU - Kostinski, Alex

AU - Lyapustin, Alexei

AU - Koutrakis, Petros

N1 - Funding Information: This research was supported by a post-doctoral fellowship from the Environment Health Fund (EHF), Jerusalem, Israel . This work was also made possible by USEPA grant RD 83479801 . Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the USEPA. Further, USEPA does not endorse the purchase of any commercial products or services mentioned in the publication. This work was also supported in part by the NSF Grant AGS-1119164 . Authors greatly appreciate important comments of Dr. Mike Wolfson and Dr. Joy E. Lawrence. We also thank Dr. Yujie Wang for the MODIS data processing. Authors are also grateful to Prof. Pandey, A. Lappi and K. Wollan of Michigan Technological University. The authors also wish to thank the anonymous reviewers for their constructive comments.

PY - 2013/1

Y1 - 2013/1

N2 - The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM2.5 levels and wind speed.

AB - The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM2.5 levels and wind speed.

KW - Aerosol optical depth

KW - Fine particulate matter

KW - High resolution aerosol retrieval

KW - Intra-urban pollution

KW - MAIAC

KW - MODIS

KW - Particulate matter

KW - Scales of pollution

KW - Variability AOD-PM correlation

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U2 - 10.1016/j.envpol.2012.08.016

DO - 10.1016/j.envpol.2012.08.016

M3 - مقالة

SN - 0269-7491

VL - 172

SP - 131

EP - 138

JO - Environmental Pollution

JF - Environmental Pollution

ER -

Spatial scales of pollution from variable resolution satellite imaging

Abstract

Keywords

All Science Journal Classification (ASJC) codes

UN SDGs

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