Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China.
Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing 210044, China.
Sci Total Environ. 2022 Mar 20;813:151922. doi: 10.1016/j.scitotenv.2021.151922. Epub 2021 Nov 24.
The response of summertime O to changes in the nitrogen oxides (NO) and volatile organic compounds (VOC) emissions, and contributions of different NO and VOC sources to O in China are studied using a highly condensed photochemical mechanism in the Statewide Air Pollution Research Center (SAPRC) family (CS07A) and two popular anthropogenic emission inventories, the Multi-resolution Emission Inventory for China (MEIC) and Regional Emission inventory in ASia (REAS). Although CS07A predicts slightly lower O concentrations than the standard fix-parameter version of the SAPRC-11 mechanism, the two mechanisms predict almost identical relative responses to daily maximum 8-hour O (O-8h) due to NO and VOC emission reductions. A source-oriented version of the CS07A is applied to determine source contributions of NO and VOCs to O using MEIC and REAS. The two inventories lead to similar model performance of O, with MEIC predicting higher O in Beijing and Shanghai, especially on high O days. Source apportionment results show that industry and transportation are the top two contributors to non-background O for both inventories, followed by power and biogenic emissions. In general, the two inventories lead to similar source contribution estimations to O attributable to NO. However, their estimations of relative contributions to VOC-related O differ for the industrial and transportation sectors. Differences in the source apportionment results are more significant in some urban areas, although both emissions capture the spatial variations in the source contributions. Our results suggest that future emission control policies should be assessed using multiple emission inventories, and the condensed CS07A is suitable for policy applications when a large number of simulations are needed.
研究了使用高度浓缩的光化学反应机制（CS07A）和两个流行的人为排放清单，即多分辨率排放清单（MEIC）和亚洲区域排放清单（REAS），研究了夏季 O 对氮氧化物（NO）和挥发性有机化合物（VOC）排放变化的响应，以及不同的 NO 和 VOC 源对中国 O 的贡献。尽管 CS07A 预测的 O 浓度略低于 SAPRC-11 机制的标准固定参数版本，但由于 NO 和 VOC 排放减少，这两种机制预测的 O-8h 的相对响应几乎相同。应用 CS07A 的面向源版本，使用 MEIC 和 REAS 确定 NO 和 VOC 对 O 的源贡献。这两个清单导致 O 的模型性能相似，MEIC 预测北京和上海的 O 更高，尤其是在高 O 日。源分配结果表明，工业和交通运输是两个清单中除背景 O 之外的首要贡献者，其次是电力和生物源排放。一般来说，这两个清单导致了归因于 NO 的 O 的相似的源贡献估计。然而，它们对工业和交通部门与 VOC 相关的 O 的相对贡献的估计有所不同。尽管这两个排放清单都捕捉到了源贡献的空间变化，但在一些城市地区，源分配结果的差异更为显著。我们的结果表明，未来的排放控制政策应该使用多个排放清单进行评估，而当需要大量模拟时，浓缩的 CS07A 适合政策应用。
