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Modeling and source apportionment of primary and secondary PM(2.5) in the atmosphere.

机译:大气中主要和次要PM(2.5)的建模和源分配。

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Source apportionment of PM2.5 is important to identify the source categories that are responsible for the concentrations observed at a particular receptor. Although receptor models have been used to do source apportionment, they do not fully take into account the chemical reactions (including photochemical reactions) involved in the formation of secondary fine particles. Secondary fine particles are formed from photochemical and other reactions involving precursor gases such as sulfur dioxide (SO 2), oxides of nitrogen (NOx), ammonia (NH3) and volatile organic compounds (VOC). The purpose of this research work was to model primary and secondary PM2.5 concentrations in the state of Tennessee (TN) and to identify the major source categories contributing to ambient fine particles.; On-road mobile and point source inventories for the state of TN were estimated and compiled by the research group at the University of Tennessee (UT). The national emissions inventory (NEI) for the year 1999 was used for the other states. The Models3/CMAQ modeling system was used for the photochemical/secondary particulate matter modeling. The modeling domain consisted of a nested 36-12-4 km domain. The 4 km domain covered the entire state of TN. The episode chosen for the modeling runs was August 29 to September 9, 1999. Different scenarios were run to quantify the contribution of the various source categories. The overall model performance was found to be satisfactory. On average, the coal-fired power plants formed the major source category accounting for about 29 to 39% of the 24-hr average total PM2.5 concentration. On-road mobile sources contributed around 17 to 24%, of which, about 60% was from fugitive dust on paved and unpaved roads. Non-road mobile sources contributed about 3 to 6%. Non-linearity issues were encountered and recommendations were made for further research. The results of this work will be helpful in addressing policy issues targeted at designing control strategies to meet the National Ambient Air Quality Standard (NAAQS) for PM2.5 in TN and the surrounding states.
机译:PM2.5的来源分配对于确定导致特定受体处观察到的浓度的来源类别很重要。尽管已将受体模型用于源分配,但它们并未完全考虑形成次级细颗粒的化学反应(包括光化学反应)。次级细颗粒是由光化学反应和其他涉及前体气体(例如二氧化硫(SO 2),氮氧化物(NOx),氨(NH3)和挥发性有机化合物(VOC))的反应形成的。这项研究工作的目的是对田纳西州(TN)的一次和二次PM2.5浓度进行建模,并确定造成环境细颗粒的主要来源类别。田纳西州的公路移动和点源清单是由田纳西大学(UT)的研究小组估算和编制的。其他州使用了1999年的国家排放清单(NEI)。 Models3 / CMAQ建模系统用于光化学/次级颗粒物建模。建模域由嵌套的36-12-4 km域组成。 4 km的范围覆盖了TN的整个状态。为模拟运行选择的插曲时间是1999年8月29日至9月9日。运行了不同的场景以量化各种来源类别的贡献。发现整体模型性能令人满意。平均而言,燃煤电厂是主要的源类别,约占24小时平均PM2.5总浓度的29%至39%。道路上的移动来源约占17%至24%,其中约60%来自铺装和未铺装道路上的扬尘。非道路移动源约占3%至6%。遇到非线性问题,并提出了进一步研究的建议。这项工作的结果将有助于解决旨在设计控制策略以达到田纳西州及周边州PM2.5的国家环境空气质量标准(NAAQS)的政策问题。

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