School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China.
State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
Sci Total Environ. 2017 Feb 15;580:283-296. doi: 10.1016/j.scitotenv.2016.12.127. Epub 2016 Dec 23.
In order to alleviate extreme haze pollution, understanding the origin of fine particulate matter (PM) is crucial. In this study, we applied Particulate Matter Source Apportionment Technology (PSAT) in CAMx (Comprehensive Air Quality Model with Extensions) to quantify the impacts of emissions from different regions on PM concentrations in Beijing for haze episodes during January 6-23, 2013. Emission inventory was developed by Tsinghua University. Evolution of local and Regional contributions during local and non-local dominated haze episodes were discussed, separately. In the meanwhile, average contribution of other every city in Jing-Jin-Ji region to PM concentrations larger than 75μgm in Beijing urban for each range of local contribution percent was analyzed. The results indicate that local emissions contributed 83.6% of PM at the urban center of Beijing, while regional transport from surrounding cities and parts of Shandong, Henan and Anhui provinces contributed 9.4%; long-range transport contributed the remaining 7.0% mainly from areas >750km away to the south of Beijing during this study period. Compared to non-local-dominated haze episodes, local-dominated heavy haze episodes in Beijing were easily resulted from unfavorable meteorological conditions with much lower PBL and wind velocity. Furthermore, local contribution is more easily to cause a sharp increase or sharp reduction of PM concentration in central Beijing, reflecting that Beijing local has much stronger potential to form extremely heavy haze episodes. The results indicated that controlling local emissions is a much more important measure to alleviate the extreme haze episodes in Beijing, like that on the night of Jan 12, 2013. Furthermore, emission control in Jing-Jin-Ji region, especially in Tangshan, Tianjin, Baoding, Langfang, Shijiazhuang and Cangzhou, as well as Henan and Shandong province, are important to reduce the PM concentrations and the occurrence of haze episodes in Beijing.
为了缓解极端霾污染,了解细颗粒物(PM)的来源至关重要。在这项研究中,我们应用了颗粒物源分配技术(PSAT)在 CAMx(带扩展的综合空气质量模型)中,以量化不同地区的排放对 2013 年 1 月 6 日至 23 日北京霾期间 PM 浓度的影响。排放清单由清华大学开发。讨论了本地和非本地主导霾期间本地和区域贡献的演变。同时,分析了京津冀地区每个城市对北京城区大于 75μgm 的 PM 浓度的平均贡献,以及本地贡献百分比的每个范围。结果表明,本地排放贡献了北京市中心 83.6%的 PM,而周边城市和山东、河南、安徽部分地区的区域输送贡献了 9.4%;在研究期间,长距离输送贡献了剩余的 7.0%,主要来自北京以南 750km 以外的地区。与非本地主导的霾期相比,北京本地主导的强霾期更容易由于气象条件不利,边界层和风速较低而形成。此外,本地贡献更容易导致北京市中心 PM 浓度的急剧增加或急剧减少,反映出北京本地形成极端强霾的潜力更大。结果表明,控制本地排放是缓解北京极端霾事件的更重要措施,就像 2013 年 1 月 12 日晚上一样。此外,控制京津冀地区的排放,特别是唐山、天津、保定、廊坊、石家庄和沧州,以及河南和山东省的排放,对于降低北京的 PM 浓度和霾事件的发生非常重要。