Implementation and evaluation of PM2.5 source contribution analysis in a photochemical model

被引:149
作者
Kwok, R. H. F. [1 ]
Napelenok, S. L. [1 ]
Baker, K. R. [1 ]
机构
[1] US EPA, Res Triangle Pk, NC 27711 USA
基金
美国国家环境保护局;
关键词
Source apportionment; CMAQ; Regional air quality modeling; Integrated Source Apportionment Method; ISAM; CHEMICAL-TRANSPORT MODEL; SENSITIVITY-ANALYSIS; SOURCE APPORTIONMENT; CMAQ; ALGORITHM; CHEMISTRY; ADJOINT; SYSTEM; REGION;
D O I
10.1016/j.atmosenv.2013.08.017
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Source culpability assessments are useful for developing effective emissions control programs. The Integrated Source Apportionment Method (ISAM) has been implemented in the Community Multiscale Air Quality (CMAQ) model to track contributions from source groups and regions to ambient levels and deposited amounts of primary and secondary inorganic PM2.5. Confidence in this approach is established by comparing ISAM source contribution estimates to emissions zero-out simulations recognizing that these approaches are not always expected to provide the same answer. The comparisons are expected to be most similar for more linear processes such as those involving primary emissions of PM2.5 and most different for non-linear systems like ammonium nitrate formation. Primarily emitted PM2.5 (e.g. elemental carbon), sulfur dioxide, ammonia, and nitrogen oxide contribution estimates compare well to zero-out estimates for ambient concentration and deposition. PM2.5 sulfate ion relationships are strong, but nonlinearity is evident and shown to be related to aqueous phase oxidation reactions in the host model. ISAM and zero-out contribution estimates are less strongly related for PM2.5 ammonium nitrate, resulting from instances of non-linear chemistry and negative responses (increases in PM2.5 due to decreases in emissions). ISAM is demonstrated in the context of an annual simulation tracking well characterized emissions source sectors and boundary conditions shows source contributions generally following bulk model seasonal trends and spatially corresponding to the geographic distribution of identified emissions source sectors. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:398 / 407
页数:10
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