Graphical techniques for constraining estimates of aerosol emissions from motor vehicles using air monitoring network data

For a source that emits several pollutants, the concentration ratios of the pollutants have characteristic values that are unaffected by dilution when mixing in clean air. Starting from this simple principle, and taking into account how physical and chemical processes affect observed concentrations...

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Veröffentlicht in:Atmospheric environment (1994) 2004-03, Vol.38 (10), p.1491-1500
1. Verfasser: Bentley, S.T.
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description For a source that emits several pollutants, the concentration ratios of the pollutants have characteristic values that are unaffected by dilution when mixing in clean air. Starting from this simple principle, and taking into account how physical and chemical processes affect observed concentrations during transport from source to receptor, two simple and general techniques for analysing hourly data to detect emissions representative of nearby source emissions, are described. These techniques are applied to air quality monitoring data to provide independent real-world constraints upon emissions inventories of primary aerosol from motor vehicles. Applying one technique to Californian data indicates that the 1995 Los Angeles inventory may overestimate such emissions. The other technique is used to derive an estimate of total yearly vehicular emissions of primary aerosol for Hong Kong, given the corresponding total emissions of oxides of nitrogen.
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ispartof Atmospheric environment (1994), 2004-03, Vol.38 (10), p.1491-1500
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1873-2844
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source Elsevier ScienceDirect Journals
subjects Aerosols
Air monitoring
Air pollution
Air quality
Applied sciences
Atmospheric pollution
Cleaning
Emission analysis
Emissions inventory verification
Exact sciences and technology
Exploratory data analysis
Monitoring
Motor vehicles
NO x
PM 10
Pollutants
Pollution
Pollution sources. Measurement results
Transports
title Graphical techniques for constraining estimates of aerosol emissions from motor vehicles using air monitoring network data
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