Chen Guo-Lei, Zhou Ying, Cheng Shui-Yuan, Yang Xiao-Wen, Wang Xiao-Qi
Key Laboratory of Beijing on Regional Air Pollution Control, College of Environmental and Energy Engineering, Beijing University of Technology, Beijing 100124, China.
Huan Jing Ke Xue. 2016 Nov 8;37(11):4069-4079. doi: 10.13227/j.hjkx.201605088.
In this study, detailed activity level of typical sector in Chengde in 2013 was obtained through a full-coverage investigation. A comprehensive emission inventory with country-level resolution in 2013 was developed based on guide of atmospheric pollutant emission inventory and updated emission factors. Then, the emission inventory within 1 km×1 km grid was generated using source-based spastial surrogates including population, road network and landuse date. Furthemore, meteorology-air quality modeling system (WRF-CMAx) including Particulate Source Apportionment Technology (PSAT) module was established in order to evaluate the impact of topical sector (e. g., electric power, the production of construction materials, the metallurgical industry, etc.) on PM concentration in January, April, July and October which were considered as the representative months of winter, spring, summer and autumn. The results showed the total emission of SO, NO, TSP, PM, PM, CO, VOCs and NH in Chengde in 2013 was respectively 81134 t, 72556 t, 368750 t, 119974 t, 51152 t, 1281371 t, 170642 t and 81742 t. Industrial source was the main emission contributor of SO, NO, CO, VOCs, accounting for 89.5%, 51.9%, 82.5% and 45.6% of total emissions, respectively. The major emission source of NO also included on-road and non-road mobile source, respectively accounting for 26.7% and 10.8%. The major emission source of TSP, PM and PM was fugitive dust, accounting for 76.7%, 65.6% and 46.54%, respectively. Ammonia emissions from animals and farm accounted for 67.1% and 15.8% of total emissions, respectively. The numerical simulation result showed that the fugitive dust, the others, the metallurgical industry and boilers industry had relatively higher contributions to PM concentration, accounting for 23.1%, 20.6%, 13.3% and 11.2%, respectively. These emission sources should be paid more attention during the decision-making with respect to control strategies.
本研究通过全覆盖调查获取了2013年承德市典型行业的详细活动水平。基于大气污染物排放清单编制指南和更新后的排放因子，编制了2013年具有国家层面分辨率的综合排放清单。然后，利用包括人口、道路网络和土地利用数据在内的基于源的空间替代物生成了1公里×1公里网格内的排放清单。此外，建立了包括颗粒物源解析技术（PSAT）模块的气象-空气质量模拟系统（WRF-CMAx），以评估典型行业（如电力、建材生产、冶金行业等）对1月、4月、7月和10月PM浓度的影响，这几个月分别被视为冬季、春季、夏季和秋季的代表月份。结果表明，2013年承德市SO、NO、TSP、PM、PM、CO、VOCs和NH的总排放量分别为81134吨、72556吨、368750吨、119974吨、51152吨、1281371吨、170642吨和81742吨。工业源是SO、NO、CO、VOCs的主要排放贡献者，分别占总排放量的89.5%、51.9%、82.5%和45.6%。NO的主要排放源还包括道路和非道路移动源，分别占26.7%和10.8%。TSP、PM和PM的主要排放源是扬尘，分别占76.7%、65.6%和46.54%。动物和养殖场的氨排放分别占总排放量的67.1%和15.8%。数值模拟结果表明，扬尘、其他源、冶金行业和锅炉行业对PM浓度的贡献相对较高，分别占23.1%、20.6%、13.3%和11.2%。在制定控制策略的决策过程中，应更多关注这些排放源。
