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Estimation of SO2 emissions using OMI retrievals

Estimation of SO2 emissions using OMI retrievals Satellite sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor, averaged over a period of several years, were compared with emissions inventories for major US sources. Low‐ and high‐ spatial frequency filtration was applied to OMI data to reduce the noise and bias to enhance and reveal weak SO2 signals that are otherwise not readily apparent. Averaging a large number of individual observations enables the study of SO2 spatial distributions near larger SO2 emissions sources with an effective resolution superior to that of an individual OMI observation and even to obtain rough estimates of the emissions level from those sources. It is demonstrated that individual sources (or multiple sources within 50 km) with annual SO2 emissions greater than about 70 kT y−1 produce a statistically significant signal in 3‐year averaged OMI data. A correlation of 0.93 was found between OMI SO2 integrated around the source and the annual SO2 emission rate for the sources greater than 70 kT y−1. OMI SO2 data also indicate a 40% decline in SO2 values over the largest US coal power plants between 2005–2007 and 2008–2010, a value that is consistent with the reported 46% reduction in annual emissions due to the implementation of new SO2 pollution control measures over this period. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Geophysical Research Letters Wiley

Estimation of SO2 emissions using OMI retrievals

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References (20)

Publisher
Wiley
Copyright
Copyright © 2011 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0094-8276
eISSN
1944-8007
DOI
10.1029/2011GL049402
Publisher site
See Article on Publisher Site

Abstract

Satellite sulfur dioxide (SO2) measurements from the Ozone Monitoring Instrument (OMI) satellite sensor, averaged over a period of several years, were compared with emissions inventories for major US sources. Low‐ and high‐ spatial frequency filtration was applied to OMI data to reduce the noise and bias to enhance and reveal weak SO2 signals that are otherwise not readily apparent. Averaging a large number of individual observations enables the study of SO2 spatial distributions near larger SO2 emissions sources with an effective resolution superior to that of an individual OMI observation and even to obtain rough estimates of the emissions level from those sources. It is demonstrated that individual sources (or multiple sources within 50 km) with annual SO2 emissions greater than about 70 kT y−1 produce a statistically significant signal in 3‐year averaged OMI data. A correlation of 0.93 was found between OMI SO2 integrated around the source and the annual SO2 emission rate for the sources greater than 70 kT y−1. OMI SO2 data also indicate a 40% decline in SO2 values over the largest US coal power plants between 2005–2007 and 2008–2010, a value that is consistent with the reported 46% reduction in annual emissions due to the implementation of new SO2 pollution control measures over this period.

Journal

Geophysical Research LettersWiley

Published: Nov 1, 2011

Keywords: ;

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