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Refining emission rate estimates using a coupled receptor-dispersion modeling approach
Published in
2010
Volume: 44
   
Issue: 32
Pages: 3935 - 3941
Abstract
Receptor modeling techniques like chemical mass balance are used to attribute pollution levels at a point to different sources. Here we analyze the composition of particulate matter and use the source profiles of sources prevalent in a region to estimate quantitative source contributions. In dispersion modeling on the other hand the emission rates of various sources together with meteorological conditions are used to determine the concentrations levels at a point or in a region. The predictions using these two approaches are often inconsistent. In this work these differences are attributed to errors in emission inventory. Here an algorithm for coupling receptor and dispersion models is proposed to reduce the differences of the two predictions and determine the emission rates accurately. The proposed combined approach helps reconcile the differences arising when the two approaches are used in a stand-alone mode. This work is based on assuming that the models are perfect and uses a model-to-model comparison to illustrate the concept. © 2010 Elsevier Ltd.
About the journal
JournalAtmospheric Environment
ISSN13522310
Open AccessNo
Concepts (36)
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    Chemical mass balance
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    Coupled models
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    COUPLED RECEPTORS
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    Dispersion model
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    DISPERSION MODELING
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    DISPERSION MODELS
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    Emission inventories
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    Emission rates
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    Meteorological condition
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    MODEL-TO-MODEL COMPARISON
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    Particulate matter
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    POLLUTION LEVEL
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    RECEPTOR MODEL
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    RECEPTOR MODELING
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    Source contributions
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    Source profiles
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    STAND-ALONE MODES
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    Atmospheric movements
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    Forecasting
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    Optimization
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    Particulate emissions
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    Dispersions
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    Algorithm
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    Atmospheric pollution
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    DISPERSION
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    Emission control
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    Emission inventory
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    ENVIRONMENTAL MODELING
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    Estimation method
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    Meteorology
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    Accuracy
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    Article
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    Model
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    Pollution
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    Priority journal
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    Quantitative analysis