| 京津冀区域PM2.5污染相互输送特征 |
| 摘要点击 5638 全文点击 1611 投稿时间：2017-03-31 修订日期：2017-06-22 |
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| 中文关键词 PM2.5 CAMx-PSAT 京津冀 区域传输矩阵 本地贡献 |
| 英文关键词 PM2.5 CAMx-PSAT Jingjinji Region regional transport matrix local source |
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| 中文摘要 |
| 基于CAMx-PSAT空气质量模型，对2015年京津冀区域PM2.5污染及相互输送特征进行定量模拟，建立了京津冀13个城市的PM2.5传输矩阵.结果表明，在年均尺度上京津冀区域PM2.5以本地污染源贡献为主（21.49%~68.74%），传输贡献为辅，其中区域内传输贡献约为13.31%~54.62%，区外贡献约为13.32%~45.02%.PM2.5传输特征呈现显著的时空差异性，区域中部城市唐山、北京、天津、保定和石家庄PM2.5受本地贡献主导，在冬季尤其明显，而受传输影响较大的城市多分布在区域边界且在南部集中.区内作为汇的城市有廊坊、衡水、承德、秦皇岛和邢台，作为源的城市有天津、沧州、唐山、北京、石家庄和邯郸，张家口和保定对区内城市输出和受区内输入基本持平.典型城市分析证明城市间PM2.5污染交互影响，北京与廊坊、保定、承德、天津和沧州等城市之间，天津与廊坊、唐山、北京、沧州和保定等城市之间，石家庄与邢台、衡水、保定、邯郸和廊坊之间均存在显著的PM2.5相互输送. |
| 英文摘要 |
| By coupling particle source apportionment technology (PSAT) with a comprehensive air quality model with extensions (CAMx), the regional transport matrix of PM2.5 was built for 13 cities in the Jingjinji Region in 2015. Results showed that the major contributor to PM2.5 was local source emissions, contributing 21.49%-68.74%, The internal transport from in-region sources contributed 13.31%-54.62% and the external transport from out-region sources contributing 13.32%-45.02% were also significant. The spatio-temporal distribution of the PM2.5 transport matrix was characterized by geographical, meteorological, and source patterns. Local emissions exerted the most significant impact on the central part of Jingjinji in winter, while regional transport contributed more to the southern region in other seasons. By assessing the input/output and activity of PM2.5 transport, Langfang, Hengshui, Chengde, Qinhuangdao, and Xingtai were receptors; Tianjin, Cangzhou, Tangshan, Beijing, Shijiazhuang, and Handan were sources, and Zhangjiakou and Baoding had a balanced transportation mode. The seasonal matrix of PM2.5 showed significant transport between Beijing and Langfang, Baoding, Chengde, Tianjin, Cangzhou, while the city list for Tianjin and Shijiazhuang differed slightly. |
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