Full Text:   <2699>

Summary:  <1902>

CLC number: X511

On-line Access: 2017-01-24

Received: 2015-10-21

Revision Accepted: 2016-06-23

Crosschecked: 2017-01-10

Cited: 1

Clicked: 4315

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

-   Go to

Article info.
Open peer comments

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)


Share this article to: More <<< Previous Article|

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.

@article{title="Characteristics and origins of a typical heavy haze episode in Baotou, China: implications for the spatial distribution of industrial sources",
author="Bi-xin Chen, Si Wang, Wei-dong Yang, Ren-chang Yan, Xuan Chen, Qing-yu Zhang",
journal="Journal of Zhejiang University Science A",
volume="18",
number="2",
pages="151-162",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1500284"
}

%0 Journal Article
%T Characteristics and origins of a typical heavy haze episode in Baotou, China: implications for the spatial distribution of industrial sources
%A Bi-xin Chen
%A Si Wang
%A Wei-dong Yang
%A Ren-chang Yan
%A Xuan Chen
%A Qing-yu Zhang
%J Journal of Zhejiang University SCIENCE A
%V 18
%N 2
%P 151-162
%@ 1673-565X
%D 2017
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1500284

TY - JOUR
T1 - Characteristics and origins of a typical heavy haze episode in Baotou, China: implications for the spatial distribution of industrial sources
A1 - Bi-xin Chen
A1 - Si Wang
A1 - Wei-dong Yang
A1 - Ren-chang Yan
A1 - Xuan Chen
A1 - Qing-yu Zhang
J0 - Journal of Zhejiang University Science A
VL - 18
IS - 2
SP - 151
EP - 162
%@ 1673-565X
Y1 - 2017
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1500284


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

Reference

[1]Ashbaugh, L.L., Malm, W.C., Sadeh, W.D., 1985. A residence time probability analysis of sulfur concentrations at Grand Canyon National Park. Atmospheric Environment (1967), 19(8):1263-1270.

[2]Chan, C.K., Yao, X., 2008. Air pollution in mega cities in China. Atmospheric Environment, 42(1):1-42.

[3]Chen, L., Pryor, S.C., Li, D.L., 2012. Assessing the performance of Intergovernmental Panel on Climate Change AR5 climate models in simulating and projecting wind speeds over China. Journal of Geophysical Research: Atmospheres, 117(D24):106-113.

[4]Cheng, I., Zhang, L., Blanchard, P., et al., 2013. Concentration-weighted trajectory approach to identifying sources of speciated atmospheric mercury at an urban coastal site in Nova Scotia, Canada. Atmospheric Chemistry & Physics, 13:6031-6048.

[5]Cheng, X.J., Yan, X.J., Zhang, Y.X., et al., 2000. An investigation into the effect of air pollution on resident’s health in Baotou city. Research of Environmental Sciences, 13(4):62-64 (in Chinese).

[6]Dockery, D.W., Pope, C.A., 1994. Acute respiratory effects of particulate air pollution. Annual Review of Public Health, 15(1):107-132.

[7]Engelcox, J.A., Hoff, R.M., Haymet, A.D.J., 2004. Recommendations on the use of satellite remote-sensing data for urban air quality. Journal of the Air & Waste Management Association, 54(11):1360-1371.

[8]Gao, S., Pan, X.S., Madaniyazi, L., et al., 2014. Source apportion of atmospheric PM10 and PM2.5 in Donghe District of Baotou. Journal of Environmental Hygiene, 4(1):69-72 (in Chinese).

[9]Huang, R.J., Zhang, Y., Bozzetti, C., et al., 2014. High secondary aerosol contribution to particulate pollution during haze events in China. Nature, 514(7521):218-222.

[10]Karnae, S., John, K., 2013. Sources affecting PM2.5 concentrations at a rural semi-arid coastal site in South Texas. Journal of Environmental Protection, 4:152-162.

[11]Kim, E., Hopke, P.K., 2004. Source apportionment of fine particles in Washington, DC, utilizing temperature-resolved carbon fractions. Journal of the Air & Waste Management Association, 54(7):773-785.

[12]Lan, X.J., 2011. Analysis on the Characteristics of Air Quality and Pollution Controlling Methods in Baotou City. MS Thesis, Inner Mongolia University, Hohhot, China (in Chinese).

[13]Liu, G., Li, J., Wu, D., et al., 2015. Chemical composition and source apportionment of the ambient PM2.5 in Hangzhou, China. Particuology, 18:135-143.

[14]Liu, N., Yu, Y., He, J., et al., 2013. Integrated modeling of urban-scale pollutant transport: application in a semi-arid urban valley, Northwestern China. Atmospheric Pollution Research, 4(3):306-314.

[15]Liu, X.G., Li, J., Qu, Y., et al., 2013. Formation and evolution mechanism of regional haze: a case study in the megacity Beijing, China. Atmospheric Chemistry & Physics, 13(9):4501-4514.

[16]Ma, X., 2004. Theory and Method of Environmental Planning. Chemical Industry Press, Beijing, China, p.23-54 (in Chinese).

[17]Mao, Y., Zhang, X., Wang, L., 2006. Fuzzy pattern recognition method for assessing groundwater vulnerability to pollution in the Zhangji area. Journal of Zhejiang University-SCIENCE A, 7(11):1917-1922.

[18]Oh, M.S., Lee, T.J., Kim, D.S., 2011. Quantitative source apportionment of size-segregated particulate matter at urbanized local site in Korea. Aerosol and Air Quality Research, 11(3):247-264.

[19]Pope, C.A., Thun, M.J., Namboodiri, M.M., et al., 1995. Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults. American Journal of Respiratory and Critical Care Medicine, 151(3Pt1):669-674.

[20]Seinfeld, J.H., 1989. Urban air pollution: state of the science. Science, 243(4892):745-752.

[21]Shao, M., Tang, X.Y., Zhang, Y.H., et al., 2006. City clusters in China: air and surface water pollution. Frontiers in Ecology and the Environment, 4(7):353-361.

[22]Shen, G.F., Yuan, S.Y., Xie, Y.N., et al., 2014. Ambient levels and temporal variations of PM2.5 and PM10 at a residential site in the mega-city, Nanjing, in the western Yangtze River Delta, China. Journal of Environmental Science & Health Part A: Toxic/Hazardous Substances & Environmental Engineering, 49(2):171-178.

[23]Song, Y., Tang, X.Y., Xie, S.D., et al., 2007. Source apportionment of PM2.5 in Beijing in 2004. Journal of Hazardous Materials, 146(1-2):124-130.

[24]Tan, J., Duan, J., He, K., et al., 2009. Chemical characteristics of PM2.5 during a typical haze episode in Guangzhou. Journal of Environmental Sciences, 21(6):774-781.

[25]Tao, M., Chen, L., Su, L., et al., 2012. Satellite observation of regional haze pollution over the North China Plain. Journal of Geophysical Research: Atmospheres, 117(D12):48-50.

[26]Wang, F., Chen, D.S., Cheng, S.Y., et al., 2010. Identification of regional atmospheric PM10 transport pathways using HYSPLIT, MM5-CMAQ and synoptic pressure pattern analysis. Environmental Modelling & Software, 25(8):927-934.

[27]Wang, H., Zhu, B., Zhang, Z., et al., 2015. Mixing state of individual carbonaceous particles during a severe haze episode in January 2013, Nanjing, China. Particuology, 20:16-23.

[28]Wang, J., Hu, Z.M., Chen, Y.Y., et al., 2013. Contamination characteristics and possible sources of PM10 and PM2.5 in different functional areas of Shanghai, China. Atmospheric Environment, 68(2):221-229.

[29]Wang, X.H., Bi, X.H., Sheng, G.Y., et al., 2006. Chemical composition and sources of PM10 and PM2.5 aerosols in Guangzhou, China. Environmental Monitoring & Assessment, 119(1-3):425-439.

[30]Wang, Y.Q., Zhang, X.Y., Arimoto, R., 2006. The contribution from distant dust sources to the atmospheric particulate matter loadings at Xi’an, China during spring. Science of the Total Environment, 368(2-3):875-883.

[31]Watson, J.G., Chen, L.W.A., Chow, J.C., et al., 2008. Source apportionment: findings from the U.S. supersites program. Journal of the Air & Waste Management Association, 58(2):265-288.

[32]Xiao, C., Zhang, G., Huang, D., et al., 2012. Preliminary study on air pollution source identification in Xinzhen, Beijing, using NAA and PIXE. Journal of Radioanalytical & Nuclear Chemistry, 291(1):95-100.

[33]Yan, J., Peng, Z., Lu, S., et al., 2006. Removal of PCDDs/Fs from municipal solid waste incineration by entrained-flow adsorption technology. Journal of Zhejiang University-SCIENCE A, 7(11):1896-1903.

[34]Yan, R.C., Yu, S.C., Zhang, Q.Y., et al., 2015. A heavy haze episode in Beijing in February of 2014: characteristics, origins and implications. Atmospheric Pollution Research, 6(5):867-876.

[35]Yu, S.C., Mathur, R., Pleim, J., et al., 2014a. Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF-CMAQ: model description, development, evaluation and regional analysis. Atmospheric Chemistry and Physics, 14:11247-11285.

[36]Yu, S.C., Alapaty, K., Mathur, R., et al., 2014b. Attribution of the United States “warming hole”: aerosol indirect effect and precipitable water vapor. Scientific Reports, 4:6929.

[37]Yu, S.C., Zhang, Q.Y., Yan, R.C., et al., 2014c. Origin of air pollution during a weekly heavy haze episode in Hangzhou, China. Environmental Chemistry Letters, 12(4):543-550.

[38]Zhang, B.S., Zhang, W.T., 2014. Source apportionment of PM2.5 in ambient air of Baotou. Environmental Engineering, 4:71-74 (in Chinese).

[39]Zhang, Q.Y., Sun, G.J., Tian, W.L., et al., 2011. Mortality weighting-based method for aggregate urban air risk assessment. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 12(9):702-709.

[40]Zhang, R., Jing, J., Tao, J., et al., 2013. Chemical characterization and source apportionment of PM2.5 in Beijing: seasonal perspective. Atmospheric Chemistry & Physics, 13(14):7053-7074.

[41]Zhang, Y.L., Cao, F., 2015. Fine particulate matter (PM2.5) in China at a city level. Scientific Reports, 5:14884.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE