Source apportionment of fine particulate matter over the Eastern U.S. Part I: source sensitivity simulations using CMAQ with the Brute Force method
Source apportionment of fine particulate matter over the Eastern U.S. Part I: source sensitivity simulations using CMAQ with the Brute Force method
复制标题
DOI：
10.5094/apr.2011.036
复制
发表时间：
2011-07-01
影响因子：
4.5
通讯作者：
Zhang, Yang
中科院分区：
文献类型：
--
作者：
Burr, Michael J.;Zhang, Yang
暴露于高水平的细颗粒物(PM2.5)被发现与对人类健康、气候变化和能见度的不利影响有关。确定PM2.5的主要来源是制定有效减排战略的重要一步。本研究利用美国环保局的社区多尺度空气质量(CMAQ)模式系统，结合蛮力方法(BFM)，在12公里水平网格分辨率下，对2002年1月和7月美国东部地区10个源类别的PM2.5进行源解析。生物质燃烧对全域PM2.5的贡献最大，其月平均贡献率接近14%(1.1微克m~(-3))。紧随其后的两大贡献者是杂面源和燃煤，贡献率分别接近12%(0.9微克m(-3))和11%(0.9微克m(-3))。在7月份，燃煤、面源杂源和工业加工是贡献率最高的三个因素(分别接近31%(2.3微克m(-3))、相似9%(0.7微克m(-3))和近7%(0.5微克m(-3)。特定地点的来源贡献表明，工业过程和生物质燃烧分别是1月份城市和农村地点PM2.5的最重要来源，而7月份这两个地点的PM2.5主要是煤炭燃烧。虽然BFM在理论上很简单，可以捕捉真实大气中前体污染物和二次污染物之间相互作用所产生的间接影响，但它的计算代价很高，并假设对每一排放类别的源贡献是相加的。这一假设不适用于二次PM组分，因为前体排放和所有二次PM组分之间的高度非线性关系，因此，源解析没有提供任何关于减排对二次PM的可能影响的有用信息(C)作者(S)，2011年。本作品是在知识共享署名3.0许可下分发的。
Exposure to elevated levels of fine particulate matter (PM2.5) is found to be associated with adverse effects on human health, climate change, and visibility. Identification of major sources contributing to PM2.5 is an important step in the formulation of effective reduction strategies. This study uses the U.S. EPA's Community Multiscale Air Quality (CMAQ) modeling system with the brute-force method (BFM) to conduct source apportionment of PM2.5 for 10 source categories over the eastern U.S. at a 12 km horizontal grid resolution for both January and July of 2002. Biomass burning is found to be the greatest contributor to domainwide PM2.5 with a monthly-mean domainwide contribution of similar to 14% (1.1 mu g m(-3)). The next two largest contributors in January are miscellaneous area sources and coal combustion with contributions of similar to 12% (0.9 mu g m(-3)) and similar to 11% (0.9 mu g m(-3)), respectively. In July, coal combustion, miscellaneous area sources, and industrial processes are the top three contributors (by similar to 31% (2.3 mu g m(-3)), similar to 9% (0.7 mu g m(-3)), and similar to 7% (0.5 mu g m(-3)), respectively). Site-specific source contributions indicate that industrial processes and biomass burning are the most important sources of PM2.5 at urban and rural sites, respectively, in January, while coal combustion dominates at both sites in July. While the BFM is theoretically simple and can capture indirect effects resulting from the interactions among precursor and secondary pollutants in the real atmosphere, it is computationally expensive and assumes that the source contributions to each emission category are additive. This assumption does not hold for secondary PM components because of the highly non-linear relationships between precursor emissions and all secondary PM components and, therefore, source apportionment provides no useful information whatsoever on the possible effect of emission reductions on secondary PM. (c) Author(s) 2011. This work is distributed under the Creative Commons Attribution 3.0 License.