Morino Yu, Iijima Akihiro, Chatani Satoru, Sato Kei, Kumagai Kimiyo, Ikemori Fumikazu, Ramasamy Sathiyamurthi, Fujitani Yuji, Kimura Chisato, Tanabe Kiyoshi, Sugata Seiji, Takami Akinori, Ohara Toshimasa, Tago Hiroshi, Saito Yoshinori, Saito Shinji, Hoshi Junya
National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Takasaki City University of Economics, 1300 Kaminamie, Takasaki, Gunma 370-0801, Japan.
Sci Total Environ. 2023 Dec 15;904:166034. doi: 10.1016/j.scitotenv.2023.166034. Epub 2023 Aug 16.
Organic aerosol (OA) is a dominant component of PM, and accurate knowledge of its sources is critical for identification of cost-effective measures to reduce PM. For accurate source apportionment of OA, we conducted field measurements of organic tracers at three sites (one urban, one suburban, and one forest) in the Tokyo Metropolitan Area and numerical simulations of forward and receptor models. We estimated the source contributions of OA by calculating three receptor models (positive matrix factorization, chemical mass balance, and secondary organic aerosol (SOA)-tracer method) using the ambient concentrations, source profiles, and production yields of OA tracers. Sensitivity simulations of the forward model (chemical transport model) for precursor emissions and SOA formation pathways were conducted. Cross-validation between the receptor and forward models demonstrated that biogenic and anthropogenic SOA were better reproduced by the forward model with updated modules for emissions of biogenic volatile organic compounds (VOC) and for SOA formation from biogenic VOC and intermediate-volatility organic compounds than by the default setup. The source contributions estimated by the forward model generally agreed with those of the receptor models for the major OA sources: mobile sources, biomass combustion, biogenic SOA, and anthropogenic SOA. The contributions of anthropogenic SOA, which are the main focus of this study, were estimated by the forward and receptor models to have been between 9 % and 15 % in summer 2019. The observed percent modern carbon data indicate that the amounts of anthropogenic SOA produced during daytime have substantially declined from 2007 to 2019. This trend is consistent with the decreasing trend of anthropogenic VOC, suggesting that reduction of anthropogenic VOC has been effective in reducing anthropogenic SOA in the atmosphere.
有机气溶胶（OA）是细颗粒物（PM）的主要成分，准确了解其来源对于确定具有成本效益的PM减排措施至关重要。为了准确地对OA进行源解析，我们在东京都市区的三个地点（一个城市、一个郊区和一个森林）进行了有机示踪剂的实地测量，并对正向模型和受体模型进行了数值模拟。我们通过使用OA示踪剂的环境浓度、源谱和生成产率，计算三种受体模型（正定矩阵因子分解、化学质量平衡和二次有机气溶胶（SOA）示踪剂法）来估算OA的源贡献。对前体排放和SOA形成途径的正向模型（化学传输模型）进行了敏感性模拟。受体模型和正向模型之间的交叉验证表明，与默认设置相比，使用更新的生物挥发性有机化合物（VOC）排放模块以及生物源VOC和中等挥发性有机化合物生成SOA的模块的正向模型，能更好地再现生物源和人为源SOA。正向模型估算的主要OA源（移动源、生物质燃烧、生物源SOA和人为源SOA）的源贡献与受体模型的结果总体一致。本研究主要关注的人为源SOA的贡献，正向模型和受体模型估计在2019年夏季为9%至15%。观测到的现代碳百分比数据表明，2007年至2019年期间，白天产生的人为源SOA数量大幅下降。这一趋势与人为源VOC的下降趋势一致，表明减少人为源VOC对减少大气中的人为源SOA是有效的。
