摘要:秦皇岛地处河北省东北部，是环渤海重要的港口城市，在近几年京津冀地区减排效果较好的情况下，于2019年1月出现了多次持续细颗粒物（PM2.5）污染过程。因此本文利用耦合了数值源解析模块ISAM（Integrated Source Apportionment Method）的区域空气质量模式RAMS-CMAQ（Regional Atmospheric Modeling System–Community Multiscale Air Quality），对2019年1月秦皇岛地区PM2.5进行模拟，并将PM2.5质量浓度高于（低于）75 μg m－3的时段划分为污染（清洁）时段，分别探讨了两个时段本地排放源对秦皇岛市PM2.5质量浓度的贡献情况，并且进一步探讨了秦皇岛各区县及外地排放源对秦皇岛市4个国控环境监测站点（第一关站、北戴河站、市监测站、建设大厦站）PM2.5质量浓度的区域传输特征。结果表明，秦皇岛地区PM2.5质量浓度整体呈“南高北低”式分布。清洁时段，PM2.5质量浓度受本地贡献较大，青龙县、卢龙县大部分地区贡献为40%～50%，海港区、抚宁区、北戴河区、第一关区及昌黎县大部分地区贡献在60%以上；4个国控环境监测站点受跨界输送贡献占34.7%～41.6%。污染时段，秦皇岛市本地贡献相对于清洁时段整体下降10%左右，当地大气污染受到跨界区域传输影响增加；而在4个国控站中，北戴河站、第一关站受到跨界输送贡献分别下降1.0%和2.3%；市监测站、建设大厦站受到跨界输送贡献分别上升2.9%和2.0%。
关键词:PM2.5/
源解析/
CMAQ模式/
ISAM模块
Abstract:Qinhuangdao is an important port city located in the northeast of Hebei province, China. In recent years, emission reductions were effective in improving the air quality over the North China Plain. However, a heavy PM2.5 pollution event appeared in Qinhuangdao area in January. (In contrast, continuous pollution that contained PM2.5 particles was evident during January 2019 at Qinhuangdao.) In this paper, the regional air quality model RAMS-CMAQ coupled with the integrated source apportionment method (ISAM) was employed to simulate the PM2.5 pollution process and analyze the impact of local sources on PM2.5 mass concentration. Two periods were defined: (1) Clean period in which the PM2.5 mass concentration over Qinhuangdao was below 75 μg m?3 and (2) pollution period in which the PM2.5 mass concentration over Qinhuangdao was above 75 μg m?3. Contributions of local emission sources to PM2.5 mass concentration between the two periods were then compared, and the regional transport pattern of PM2.5 particles from different areas to four air quality monitoring sites was evaluated. The results showed that a high PM2.5 mass burden was distributed in the south part of Qinhuangdao. During the clean period, PM2.5 concentration was greatly contributed by local areas, with the contribution of 40%–50% in most areas of Qinglong and Lulong, and more than 60% in most areas of Haigang, Funing, Beidaihe, Tiiguan, and Changli.(Local emission sources of Qinglong greatly contributed to the PM2.5 mass burden. Lulong contributed 40%–50% and Haigang, Funing, Beidaihe, Diyiguan, and Changli together contributed more than 60% of the PM2.5 mass burden.) Regional transport during the clean period accounted for 34.7%–41.6% of the concentration of PM2.5 at the four monitoring sites. Compared with the clean period, the PM2.5 mass concentration from local areas decreased by approximately 10% and the effect of regional transport increased during the pollution period. Among the four monitoring sites, the PM2.5 concentration contributed by regional transport at Beidaihe and Diyiguan sites decreased by 1.0% and 2.3%, respectively while the contribution from surrounding regions increased by 2.9% and 2.0% at Shijiance and Jianshedasha sites, respectively.
Key words:PM2.5/
Source Apportionment/
CMAQ (Community Multiscale Air Quality)/
ISAM (Integrated Source Apportionment Method)
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http://www.iapjournals.ac.cn/qhhj/article/exportPdf?id=042675cb-02b8-4286-9768-bc607c14db14
