Volume 26 Issue 8
Aug.  2013
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WANG Xi, CHEN Ren Jie, CHEN Bing Heng, KAN Hai Dong. Application of Statistical Distribution of PM10 Concentration in Air Quality Management in 5 Representative Cities of China[J]. Biomedical and Environmental Sciences, 2013, 26(8): 638-646. doi: 10.3967/0895-3988.2013.08.002
Citation: WANG Xi, CHEN Ren Jie, CHEN Bing Heng, KAN Hai Dong. Application of Statistical Distribution of PM10 Concentration in Air Quality Management in 5 Representative Cities of China[J]. Biomedical and Environmental Sciences, 2013, 26(8): 638-646. doi: 10.3967/0895-3988.2013.08.002

Application of Statistical Distribution of PM10 Concentration in Air Quality Management in 5 Representative Cities of China

doi: 10.3967/0895-3988.2013.08.002
Funds:  the National Basic Research Program (973 program) of China(2011CB503802)%Gong-Yi Program of China Ministry of Environmental Protection(201209008)%the Program for New Century Excel ent Talents in University(NCET-09-0314)
  • Objective To estimate the frequency of daily average PM10 concentrations exceeding the air quality standard (AQS) and the reduction of particulate matter emission to meet the AQS from the statistical properties (probability density functions) of air pollutant concentration. Methods The daily PM10 average concentration in Beijing, Shanghai, Guangzhou, Wuhan, and Xi’an was measured from 1 January 2004 to 31 December 2008. The PM10 concentration distribution was simulated by using the lognormal, Weibull and Gamma distributions and the best statistical distribution of PM10 concentration in the 5 cities was detected using to the maximum likelihood method. Results The daily PM10 average concentration in the 5 cities was fitted using the lognormal distribution. The exceeding duration was predicted, and the estimated PM10 emission source reductions in the 5 cities need to be 56.58%, 93.40%, 80.17%, 82.40%, and 79.80%, respectively to meet the AQS. Conclusion Air pollutant concentration can be predicted by using the PM10 concentration distribution, which can be further applied in air quality management and related policy making.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Application of Statistical Distribution of PM10 Concentration in Air Quality Management in 5 Representative Cities of China

doi: 10.3967/0895-3988.2013.08.002
Funds:  the National Basic Research Program (973 program) of China(2011CB503802)%Gong-Yi Program of China Ministry of Environmental Protection(201209008)%the Program for New Century Excel ent Talents in University(NCET-09-0314)

Abstract: Objective To estimate the frequency of daily average PM10 concentrations exceeding the air quality standard (AQS) and the reduction of particulate matter emission to meet the AQS from the statistical properties (probability density functions) of air pollutant concentration. Methods The daily PM10 average concentration in Beijing, Shanghai, Guangzhou, Wuhan, and Xi’an was measured from 1 January 2004 to 31 December 2008. The PM10 concentration distribution was simulated by using the lognormal, Weibull and Gamma distributions and the best statistical distribution of PM10 concentration in the 5 cities was detected using to the maximum likelihood method. Results The daily PM10 average concentration in the 5 cities was fitted using the lognormal distribution. The exceeding duration was predicted, and the estimated PM10 emission source reductions in the 5 cities need to be 56.58%, 93.40%, 80.17%, 82.40%, and 79.80%, respectively to meet the AQS. Conclusion Air pollutant concentration can be predicted by using the PM10 concentration distribution, which can be further applied in air quality management and related policy making.

WANG Xi, CHEN Ren Jie, CHEN Bing Heng, KAN Hai Dong. Application of Statistical Distribution of PM10 Concentration in Air Quality Management in 5 Representative Cities of China[J]. Biomedical and Environmental Sciences, 2013, 26(8): 638-646. doi: 10.3967/0895-3988.2013.08.002
Citation: WANG Xi, CHEN Ren Jie, CHEN Bing Heng, KAN Hai Dong. Application of Statistical Distribution of PM10 Concentration in Air Quality Management in 5 Representative Cities of China[J]. Biomedical and Environmental Sciences, 2013, 26(8): 638-646. doi: 10.3967/0895-3988.2013.08.002

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