Document Detail

Remote sensing of ambient particles in Delhi and its environs: estimation and validation.
MedLine Citation:
PMID:  22162895     Owner:  NLM     Status:  Publisher    
Recent advances in atmospheric remote sensing offer a unique opportunity to compute indirect estimates of air quality, particularly for developing countries that lack adequate spatial-temporal coverage of air pollution monitoring. The present research establishes an empirical relationship between satellite-based aerosol optical depth (AOD) and ambient particulate matter (PM) in Delhi and its environs. The PM data come from two different sources. Firstly, a field campaign was conducted to monitor airborne particles ≤ 2.5 μm and ≤10 μm in aerodynamic diameter (PM(2.5) and PM(10) respectively) at 113 spatially dispersed sites from July to December 2003 using photometric samplers. Secondly, data on eight hourly PM(10) and total suspended particulate (TSP) matter, collected using gravimetric samplers, from 2000 to 2005 were acquired from the Central Pollution Control Board (CPCB). The aerosol optical depths were estimated from MODIS data, acquired from NASA's Goddard Space Flight Center Earth Sciences Distributed Active Archive Center from 2000 to 2005. Both the PM and AOD data were collocated by time and space: PM mass ± 150 min of AOD time, and ± 2.5 and 5 km radius (separately) of the centroid of the AOD pixel for the 5 and 10 km AOD, respectively. The analysis here shows that PM correlates positively with the 5 km AOD; a 1% change in the AOD explains 0.52% ± 0.20% and 0.39% ± 0.15% changes in PM(2.5) within 45 and 150 min intervals (of AOD data) respectively. At a coarser spatial resolution, however, the relationship between AOD and PM is relatively weak. But, the relationship turns significantly stronger when monthly estimates are analysed over a span of six years (2000 to 2005), especially for the winter months, which have relatively stable meteorological conditions.
N Kumar; A Chu; A Foster
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Publication Detail:
Journal Detail:
Title:  International journal of remote sensing     Volume:  29     ISSN:  0143-1161     ISO Abbreviation:  -     Publication Date:  2008 Jun 
Date Detail:
Created Date:  2011-12-13     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9878707     Medline TA:  Int J Remote Sens     Country:  -    
Other Details:
Languages:  ENG     Pagination:  3383-3405     Citation Subset:  -    
Department of Geography, 316 Jessup Hall, University of Iowa, Iowa City, IA 52242, USA.
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Grant Support
R21 HD046571-01A1//NICHD NIH HHS; R21 HD046571-02//NICHD NIH HHS

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