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曹妃甸工业区空气污染来源及其对周边地区污染贡献的数值模拟研究
作者:
作者单位:

1.北京师范大学环境学院,北京100875;2.中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室,北京 100029;3.中国科学院城市环境研究所区域大气环境研究卓越创新中心,厦门 361021;4.中国环境监测总站,北京100012

作者简介:

李欣怡,女,1997年出生,硕士研究生,主要从事空气质量模拟研究。E-mail: lixysherry@163.com

通讯作者:

杨文夷,E-mail: yangwenyi@mail.iap.ac.cn

基金项目:

国家重点研发计划项目2017YFC0213000,环境保护部公益性行业科研专项201509001


Modeling Study of PM2.5 Source Apportionment over the Caofeidian Industrial Zone and Surrounding Areas
Author:
Affiliation:

1.School of Environment, Beijing Normal University, Beijing 100875;2.State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;3.Center for Excellence in Urban Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021;4.China National Environmental Monitoring Center, Beijing 100012

Fund Project:

National Key Research and Development Program Grant 2017YFC0213000;Special Foundation for the Public Service Industry of Ministry of Environmental Protection of China Grant 201509001National Key Research and Development Program (Grant 2017YFC0213000), Special Foundation for the Public Service Industry of Ministry of Environmental Protection of China (Grant 201509001)

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    摘要:

    为了深入研究曹妃甸工业区的建立和大型工业企业的迁入对京津冀地区空气质量的影响,利用嵌套网格空气质量预报模式系统NAQPMS(Nested Air Quality Prediction Modeling System)研究该工业区和周边地区在2016年秋、冬季空气质量状况,并对PM2.5(空气动力学当量直径小于等于2.5 μm的颗粒物,即细颗粒物)来源与区域输送进行分析。结果表明:模式能很好地再现气象要素和污染物浓度分布特征;曹妃甸地区本地排放在1月和10月的月均贡献分别为17.8%和25.8%。当空气质量为优良时,曹妃甸地区PM2.5主要受短距离周边传输影响,唐山和天津贡献率之和达23%~53%;当空气出现轻度及以上污染时,曹妃甸地区PM2.5浓度主要受到长距离输送的影响,河北中南部和山东地区贡献之和达40%~50%。曹妃甸工业园区排放对周边地区PM2.5浓度贡献相对较小,对唐山和天津地区贡献为3%~7%,对京津冀地区其他城市PM2.5浓度贡献可忽略不计。空气质量转差时,曹妃甸、北京和天津地区PM2.5中一次排放占比相较于空气质量优良时明显下降,二次生成的无机盐类和二次有机气溶胶贡献率增加;曹妃甸地区10月二次生成硫酸盐贡献率较1月明显增加,月均贡献率为22%。因此,在致力于削减京津冀地区PM2.5一次排放的同时,对SO2、NOx等进行控制,能有效改善该地区空气质量。

    Abstract:

    The impacts on air quality and source apportionment of PM2.5 in Beijing-Tianjin-Hebei region during the autumn and winter of 2016 after the establishment of the Caofeidian industrial zone were investigated using the nested air quality prediction modeling system (NAQPMS). The model results agreed well with the observed PM2.5concentrations and meteorological factors.The local emission of Caofeidian was one of the main contributors of PM2.5, and its average percentages in winter and autumn were 17.8% and 25.8%, respectively. The results showed that Caofeidian was mainly affected by short-distance neighbor transport when the PM2.5 concentrations were under 75 μg/m3, and the total contributions from Tangshan and Tianjin reached 23%-53%. However, when the PM2.5 concentrations in Caofiedian were above 75 μg/m3, the contributions from long-distance transport, which were mainly from central and southern Hebei, became dominant. In general, the Caofeidian industrial zone had a relatively small PM2.5 contribution to the surrounding areas. The contributions from Caofeidian only accounted for 3%-7% in Tangshan and Tianjin and were almost negligible in the remaining land areas. During pollution episodes, the emission of primary particulate matter significantly decreased, while the contributions from secondary-production increased, including inorganic salts and organic aerosols in PM2.5, compared with those during good air quality period. The contribution of secondary sulfate in Caofeidian area in autumn was 22% on average, which was significantly higher than that in winter. Therefore, while focusing on reducing the primary emission of PM2.5 in Beijing-Tianjin-Hebei areas, controlling SO2 and NOx can also effectively improve the air quality in this region

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引用本文

李欣怡,向伟玲,陈学舜,朱莉莉,王自发,杨文夷.2019.曹妃甸工业区空气污染来源及其对周边地区污染贡献的数值模拟研究[J].气候与环境研究,24(4):469-481. LI Xinyi, XIANG Weiling, CHEN Xueshun, ZHU Lili, WANG Zifa, and YANG Wenyi.2019. Modeling Study of PM2.5 Source Apportionment over the Caofeidian Industrial Zone and Surrounding Areas[J]. Climatic and Environmental Research (in Chinese],24(4):469-481.

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  • 收稿日期:2018-11-09
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  • 在线发布日期: 2019-08-08
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