Title of article :
Seasonal NH3 emissions for the continental united states: Inverse model estimation and evaluation
Author/Authors :
Alice B. Gilliland، نويسنده , , K. Wyat Appel، نويسنده , , Robert W. Pinder، نويسنده , , Robin L. Dennis، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2006
Pages :
13
From page :
4986
To page :
4998
Abstract :
Significant uncertainty exists in the seasonal distribution of NH3 emissions since the predominant sources are animal husbandry and fertilizer application. Previous studies that estimated bottom–up and top–down NH3 emissions have provided the most comprehensive information available about the seasonality of NH3 emissions. In this study, this bottom–up and top–down emission information is combined with the most recent 2001 USEPA National Emission Inventory (NEI) to construct a best prior estimate of seasonal NH3 emissions. These emission estimates are then used in an annual 2001 USEPA Community Multiscale Air Quality (CMAQ) model simulation for the continental United States. A key objective of this study is to evaluate these prior NH3 emission estimates and test the top–down inverse modeling method for a different year and a larger modeling domain than used previously. Based on the final posterior NH3 emission estimates, the inverse modeling results suggest that the annual total NEI NH3 emissions are reasonable and that a previous high bias in older USEPA emission inventories has been addressed in the updated inventory. Inverse modeling results suggest that the prior NH3 emission estimates should be increased in the summer and decreased in the winter, while results for the spring and fall are questionable due to precipitation prediction biases. A final conclusion from this study is that total NHx (NH3 and aerosol NH4+) air concentration data are essential for quantitative top–down analyses of NH3 emissions that can extend beyond what is possible using precipitation chemistry data.
Keywords :
NH3 emissions , Inverse modeling , Top–down emission estimates , Seasonal variability , air quality modeling
Journal title :
Atmospheric Environment
Serial Year :
2006
Journal title :
Atmospheric Environment
Record number :
759676
Link To Document :
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