Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation
Source apportionment of PM2.5 in Guangzhou combining observation data analysis and chemical transport model simulation
复制标题
DOI：
10.1016/j.atmosenv.2015.06.054
复制
发表时间：
2015-09-01
影响因子：
5
通讯作者：
He, Kebin
中科院分区：
文献类型：
--
作者：
Cui, Hongyang;Chen, Weihua;He, Kebin
采用观测数据分析与化学输送模型模拟相结合的混合方法，对广州市PM2.5源解析结果进行了分析。考虑了PRO地区四个主要的人为排放部门，包括移动、电力、工业和居民。通过对广州市某城市采样点2013年PM2.5逐日监测数据的分析，得到了PM2.5中硫酸盐、硝酸盐、氨氮、SO_3、POA和EC六种主要组分的比例(Ps)。利用WRF/CHEM模型得到了各排放部门对SO2、NOx、NH3、VOCs、POA和EC等6种主要污染物浓度的贡献率。然后计算了四个源对广州PM2.5质量的CRS。结果表明，固定污染源(工业和电力)对广州PM2.5的贡献率最大(枯水期22.2%，丰水期44.4%)。流动部门是主要贡献者，旱季平均贡献率为20.7%，雨季平均贡献率为37.4%。广州的PM2.5浓度几乎全部是由珠江三角洲地区雨季的排放造成的。但在旱季，PRO区域排放的污染物和珠江三角洲以北地区输送的污染物都起到了重要作用。(C)2015爱思唯尔有限公司。保留所有权利。
A hybrid method combining observation data analysis and chemical transport model simulation was used in this study to provide the PM2.5 source apportionment result of Guangzhou. Four main anthropogenic emission sectors in PRO region were taken into consideration, including mobile, power, industrial and residential. The proportions (Ps) of six major components (sulfate, nitrate, ammonium, SOA, POA and EC) in PM2.5 were acquired by analyzing the daily PM2.5 monitoring data collected in the year of 2013 at an urban sampling site in Guangzhou. WRF/Chem model was used to get the contribution ratios (CRs) of each emission sector to the concentrations of six related primary pollutants, including SO2, NOx, NH3, VOCs, POA and EC. Then the CRs of the four sources to Guangzhou's PM2.5 mass were calculated. It was found that stationary sources (industrial and power) still had the largest contribution (22.2% in dry season, 44.4% in wet season) to PM2.5 in Guangzhou. Mobile sector was the predominant single contributor, with an average contribution of 20.7% in dry season and 37.4% in wet season. Almost all the PM2.5 concentration in Guangzhou was caused by the emissions within PRD region in wet season. In dry season, however, the emissions emitted within PRO region and the pollutants transported from the areas north of PRD region both played important roles. (C) 2015 Elsevier Ltd. All rights reserved.