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CLC number: X511

On-line Access: 2017-01-24

Received: 2015-10-21

Revision Accepted: 2016-06-23

Crosschecked: 2017-01-10

Cited: 1

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Bi-xin Chen

http://orcid.org/0000-0002-8294-5643

Qing-yu Zhang

http://orcid.org/0000-0002-6509-1869

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Journal of Zhejiang University SCIENCE A 2017 Vol.18 No.2 P.151-162

http://doi.org/10.1631/jzus.A1500284


Characteristics and origins of a typical heavy haze episode in Baotou, China: implications for the spatial distribution of industrial sources


Author(s):  Bi-xin Chen, Si Wang, Wei-dong Yang, Ren-chang Yan, Xuan Chen, Qing-yu Zhang

Affiliation(s):  Department of Environmental Engineering, Zhejiang University, Hangzhou 310058, China; more

Corresponding email(s):   qy_zhang@zju.edu.cn

Key Words:  Air pollution, Haze, Industrial sources, Backward trajectory, Conditional probability function (CPF)


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Bi-xin Chen, Si Wang, Wei-dong Yang, Ren-chang Yan, Xuan Chen, Qing-yu Zhang. Characteristics and origins of a typical heavy haze episode in Baotou, China: implications for the spatial distribution of industrial sources[J]. Journal of Zhejiang University Science A, 2017, 18(2): 151-162.

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publisher="Zhejiang University Press & Springer",
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Abstract: 
air pollution has become the predominant environmental problem caused by rapid industrialization and urbanization in China. In this study, measurements of the concentrations of PM2.5, PM10, SO2, NO2, CO, and O3 at six monitoring stations in Baotou, China were used to investigate the characteristics of heavy haze pollution in Dec. 12–25, 2013. Source locations of PM2.5 in Baotou were identified using satellite remote sensing data, an air mass trajectory model, and a conditional probability function (CPF). The results showed that the average concentrations of PM2.5 and PM10 were (113.8±84.0) μg/m3 and (211.1±149.2) μg/m3, respectively. The similar trends in temporal variation of the air pollutants PM2.5, PM10, SO2, NO2, and CO suggested they may share common sources. The results of satellite observations and backward trajectories supported the hypothesis that the pollutants causing the haze event originated mainly from local anthropogenic sources. According to the CPF analysis, low-speed winds from the south and southwest, upwind industrial emissions, and the northern mountains were mainly responsible for the formation of haze in Baotou. The study provides some insights to help governments optimize industrial layouts for improving air quality in the future.

It is of great interest and importance to study on air pollution in Baotou, a city with lots of industrial emission sources and located in northwest China. The pollution characteristics of Baotou is absolutely different with those in Beijing, where a lot of studies have been done.

包头市重灰霾特征分析及对重工业布局的启示

目的:工业排放是大气中PM2.5的重要来源,是灰霾形成的主要贡献者之一。通过分析包头市一次典型灰霾时段的污染来源及特征,研究本地工业布局在此次灰霾时段对灰霾形成的影响,并讨论城市工业布局的合理性。
创新点:针对我国典型重工业城市包头市进行案例分析,研究本地城区灰霾形成的原因及重工业布局对灰霾形成的影响,并为合理布局工业提供了新的启示。
方法:1. 结合污染物观测数据、卫星遥感数据及后向轨迹模式的结果,揭示此次重灰霾发生时段的污染特征,找出此次重灰霾的主要来源。2. 采用风向条件概率函数研究城区高浓度PM2.5与本地重工业布局间的关系。
结论:1. 在此次重灰霾时段,PM2.5浓度的变化趋势与其他污染物相似,说明污染主要来自人为源,且在同样发生重灰霾的情况下,PM2.5占PM10的比例较其他沿海城市低,说明粗颗粒物对包头PM10污染的贡献较其他城市大。2. 结合卫星遥感数据与后向轨迹模式的结果,可以排除外来污染物的输入,并断定形成此次重灰霾的主要原因为本地人为源。3. 风向条件概率函数分析结果显示本地重工业分布以及低风速的西南风(非盛行风)是造成此次重灰霾发生的主要原因。4. 揭示了包头市在布局重工业或进行高强度的工业活动时不能只考虑避开盛行风,因为出现次数不多的低风速非盛行风同样会引起重灰霾的爆发;这可为包头市乃至其他工业城市在进一步调整工业布局时提供参考。

关键词:空气污染;灰霾;工业布局;后向轨迹;风向条件概率函数

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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