Document Detail

Source region identification using kernel smoothing.
MedLine Citation:
PMID:  19569335     Owner:  NLM     Status:  MEDLINE    
As described in this paper, nonparametric wind regression is a source-to-receptor source apportionment model that can be used to identify and quantify the impact of possible source regions of pollutants as defined by wind direction sectors. It is described in detail with an example of its application to SO2 data from East St. Louis, IL. The model uses nonparametric kernel smoothing methods to apportion the observed average concentration of a pollutant to sectors defined by ranges of wind direction and speed. Formulas are given for the uncertainty of all of the important components of the model, and these are found to give nearly the same uncertainties as blocked bootstrap estimates of uncertainty. The model was applied to data for the first quarter (January, February, and March) of 2003, 2004, and 2005. The results for East St. Louis show that almost 50% of the average SO2 concentration can be apportioned to two 30 degrees wide wind sectors containing a zinc smelter and a brewery; a nearby steel mill did not appearto have a significant impact on SO2 during this period.
Ronald Henry; Gary A Norris; Ram Vedantham; Jay R Turner
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Environmental science & technology     Volume:  43     ISSN:  0013-936X     ISO Abbreviation:  Environ. Sci. Technol.     Publication Date:  2009 Jun 
Date Detail:
Created Date:  2009-07-02     Completed Date:  2009-07-27     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0213155     Medline TA:  Environ Sci Technol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  4090-7     Citation Subset:  IM    
Department of Civil and Environmental Engineering, University of Southern California, 3620 S. Vermont Ave., Los Angeles, California 90089-2531, USA.
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MeSH Terms
Air Pollutants / chemistry*
Air Pollution*
Environmental Monitoring / methods*
Models, Theoretical*
Reg. No./Substance:
0/Air Pollutants

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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