WANG Xi; CHEN Ren Jie; CHEN Bing Heng; KAN Hai Dong

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

WANG Xi, CHEN Ren Jie, CHEN Bing Heng, KAN Hai Dong

文章导航 > Biomedical and Environmental Sciences > 2013 > 26(8): 638-646

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

doi: 10.3967/0895-3988.2013.08.002

基金项目: 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)

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

School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China

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)

摘要: 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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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.
- Statistical distribution /
- PM10 concentration /
- Lognormal

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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

刊出日期: 2013-08-20

关键词:

Statistical distribution /

PM10 concentration /

Lognormal

摘要: 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.

English Abstract

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

School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China

Publish Date: 2013-08-20

Keywords:

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.

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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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

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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

English Abstract

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

School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China

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