呼包鄂城市群PM2.5质量浓度统计分布特性
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摘要
呼包鄂(呼和浩特市,包头市,鄂尔多斯市)城市群位于内蒙古自治区中西部,三市有着非常密切的经贸联系以及相似的气候特征.对呼包鄂三市2014年1月-2017年12月间PM2.5日均质量浓度进行统计性分析.采用四种双参数分布,即Log-normal分布,Weibull分布,Birnbaum-Saunders分布,Gamma分布,拟合三市PM2.5日均质量浓度.用极大似然估计和矩估计估计各分布参数,研究最优理论分布.并对三市PM2.5日均质量浓度作比较.估计结果表明无论是以年为单位还是以四年为整体,三市PM2.5日均质量浓度用Log-normal分布模拟最优;PM2.5日均质量浓度由高到低依次为包头市,呼和浩特市,鄂尔多斯市;包头市和呼和浩特市PM2.5日均质量浓度相似度较高.
Hohhot-Baotou-Ordos Region is located in midwest of Inner Mongolia. There is a close relationship in the fields of economy, trade and climate. We analyze the statistical characteristics of the PM2.5 data measured from January 2014 to December 2017. Four two-parameter distributions, i.e., Log-normal distribution, Weibull distribution, BirnbaumSaunders distribution and Gamma distribution, are used to fit PM2.5 concentration of the three cities. The maximum likelihood estimation and moment estimation are used to calculate the unknown parameters. The research showns that the Log-normal distribution is the optimal model to simulate PM2.5 under the maximum likelihood estimation, whether in years or in four years as a whole. The order from high to low of PM2.5 is Baotou, Hohhot and Ordos. the Pearson correlation coefficient betweem Baotou and Hohhot are of high similarity
Hohhot-Baotou-Ordos Region is located in midwest of Inner Mongolia. There is a close relationship in the fields of economy, trade and climate. We analyze the statistical characteristics of the PM2.5 data measured from January 2014 to December 2017. Four two-parameter distributions, i.e., Log-normal distribution, Weibull distribution, BirnbaumSaunders distribution and Gamma distribution, are used to fit PM2.5 concentration of the three cities. The maximum likelihood estimation and moment estimation are used to calculate the unknown parameters. The research showns that the Log-normal distribution is the optimal model to simulate PM2.5 under the maximum likelihood estimation, whether in years or in four years as a whole. The order from high to low of PM2.5 is Baotou, Hohhot and Ordos. the Pearson correlation coefficient betweem Baotou and Hohhot are of high similarity
引文
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[23] Garcia A, Torres J L, Prieto E, et al. Fitting wind speed distributions:a case study[J]. Solar Energy, 1998, 62(2):139-144.
[24]苏布达,姜彤,董文杰.长江流域极端强降水分布特征的统计拟合[J].气象科学,2008, 28(6):625-629.
[25] Hassan M U, Stockhammar P. Fitting probability distributions to economic growth:a maximum likelihood approach[J]. Journal of Applied Statistics, 2016, 43(9):1583-1603.
[26] Kan H D,Chen B H. Statistical distributions of ambient air pollutants in Shanghai, China[J].Biomedical and Environmental Sciences, 2004, 3(17):366-372.
[27] Mdyusof N F F, Ramli N A, Yahaya A S, et al. Central fitting distributions and extreme value distributions for prediction of high PM10 concentration[C]//International Conference on Multimedia Technology IEEE, 2011:6263-6266.
[28]邓启红,黄柏良,唐猛,等.长沙市大气颗粒物PM10质量浓度的统计分布特性[J].中南大学学报(自然科学版),2012, 43(4):1567-1573.
[29] Tian P C. Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application[J]. Applied Energy, 2011, 88(1):272-282.
[30] Marani A, Lavagnini I, Buttazzoni C. Statistical Study of Air Pollutant Concentrations via Generalized Gamma Distributions[J]. Air Repair, 1986, 36(11):1250-1254.
[31] Leiva V, Barros M, Paula G A, et al. Generalized Birnbaum-Saunders distributions applied to air pollutant concentration[J]. Environmetrics, 2008, 19(3):235-249.
[32] Balakrishnan N, Kateri M. On the maximum likelihood estimation of parameters of Weibull distribution based on complete and censored data[J]. Statistics Probability Letters, 2008, 17(78):2971-2975.
[33] Mohammadi K, Alavi O, Mostafaeipour A, et al. Assessing different parameters estimation methods of Weibull distribution to compute wind power density[J]. Energy Conversion and Management,2016, 108:322-335.
[34] Amin Z H. A note on the parameter estimation for the lognormal distribution based on progressively type I interval censored samples[J]. Model Assisted Statistics Applications, 2008, 3(3):169-176.
[35] Liu Z. Estimation based on likelihood depth with application to the shape parameter of Gamma distribution[J]. Journal of Information Computational Science, 2015, 12(10):3907-3914.
[36]徐晓岭,王蓉华,顾蓓青.全样本场合下两参数Birnbaum-Saunders疲劳寿命分布的统计分析[J].浙江大学学报(理学版),2017, 44(6):692-704.
[2] Wallner P, Hutter H P, Moshammer H. Worldwide associations between air quality and health endpoints:are they meaningful?[J]. International Journal of Occupational Medicine and Environmental Health, 2014, 27(5):716-721.
[3] Jhun I, Coull B A, Zanobetti A, et al. The impact of nitrogen oxides concentration decreases on ozone trends in the USA[J]. Air Quality Atmosphere and Health, 2015, 8(3):283-292.
[4] Jakubiak-Lasocka J, Lasocki J, Siekmeier R, et al. Impact of traffic-related air pollution on health[J].Oxygen-Transport to Tissue XXXIII, 2015, 834:21-29.
[5] Yorifuji T, Kashima S, Doi H. Acute exposure to fine and coarse particulate matter and infant mortality in Tokyo, Japan(2002-2013)[J]. Science of the Total Environment, 2016, 551-552:66-72.
[6] Zheng S, Pozzer A, Cao C X, et al. Long-term(2001-2012)fine particulate matter(PM2.5)and the impact on human health in Beijing, China[J]. Atmospheric Chemistry and Physics Discussions,2014, 14(21):5715-5725.
[7] Yang W S, Zhao H, Wang X, et al. An evidence-based assessment for the association betweenlong-term exposure to outdoor air pollution and the risk of lung cancer[J]. European Journal of Cancer Prevention, 2016, 25(3):163-172.
[8] Shen F, Ge X, Hu J, et al. Air pollution characteristics and health risks in Henan Province, China[J].Environmental Research, 2017, 1(156):625-634.
[9] Wang M, Zhu T, Zhang J P, et al. Using a mobile laboratory to characterize the distribution and transport of sulfur dioxide in and around Beijing[J]. Atmospheric Chemistry Physics, 2011, 11(22):11631-11645.
[10] Ni X,Cao L, Zhou Y, et al. Spatio-Temporal Pattern Estimation of PM2.5 in Beijing-TianjinHebei Region Based on MODIS. AOD and Meteorological Data Using the Back Propagation Neural Network[J]. Atmosphere, 2018, 3(9):213-226.
[11] Zhang Z, Ma Z, Kim S, et al. Significant Decrease of PM2.5 in Beijing Based on Long-Term Records and Kolmogorov-Zurbenko Filter Approach[J]. Aerosol and Air Quality Research, 2018,3(18):711-718.
[12]郭梦萦.天津市PM2.5的统计分析[D].南开大学,2015.
[13] Xu L Z, Batterman S, Chen F, et al. Spatiotemporal characteristics of PM2.5 and PM10 at urban and corresponding background sites in 23cities in China[J]. Science of the Total Environment, 2017,599(600):2074-2084.
[14]王海燕,王明仕.呼和浩特市大气污染物污染特征及污染物的相关性分析[J].环境与可持续发展,2016,41(5):182-183.
[15] Huang Y H, Yu C, Mao H Y, et al. Emission Factor and Size Distribution of Fugitive Dust from Construction Sites in Hohhot[J]. Journal of Inner Mongolia University, 2011, 42(2):230-235.
[16] Tian Y Z, Wang J, Peng X, et al. Estimation of the direct and indirect impacts of fireworks on the physicochemical characteristics of atmospheric PM10 and PM2.5[J]. Atmospheric Chemistry and Physics, 2014, 14(18):9469-9479.
[17] Wang K, Jia L, Huang L, et al. Pollution characteristics of water-soluble ions in PM2.5 and PM10under severe haze days[J]. Harbin Gongye Daxue Xuebao/journal of Harbin Institute of Technology,2014, 46(12):53-58.
[18] Li S, Guo Y, Williams G, et al. The association between ambient temperature and children's lung function in Baotou, China[J]. International Journal of Biometeorology, 2015, 59(7):791-798.
[19] Chen B X, Wang S, Yang W D, et al. Characteristics and origins of a typical heavy haze episode in Baotou, China:implications for the spatial distribution of industrial sources[J].浙江大学学报a辑(应用物理与工程)(英文版),2017, 18(2):151-162.
[20] Xiong H, Duan S Y, et al. Effect of current emission abatement strategies on air quality improvement in China:A case study of Baotou, a typical industrial city in Inner Mongolia[J]. Journal of Environmental Sciences, 2017, 57(7):383-390.
[21] Reza B K; James J, et al. Source apportionments of PM2.5 organic carbon during the elevated pollution episodes in the Ordos region, Inner Mongolia, China[J]. Environmental Science and Pollution Research, 2018, 13(25):13159-13172.
[22] Khuzestani R B, Schauer J J,Wei Y, et al. Quantification of the sources of long-range transport of PM2.5 pollution in the Ordos region, Inner Mongolia, China[J]. Environmental Pollution, 2017,93(229):1019-1031.
[23] Garcia A, Torres J L, Prieto E, et al. Fitting wind speed distributions:a case study[J]. Solar Energy, 1998, 62(2):139-144.
[24]苏布达,姜彤,董文杰.长江流域极端强降水分布特征的统计拟合[J].气象科学,2008, 28(6):625-629.
[25] Hassan M U, Stockhammar P. Fitting probability distributions to economic growth:a maximum likelihood approach[J]. Journal of Applied Statistics, 2016, 43(9):1583-1603.
[26] Kan H D,Chen B H. Statistical distributions of ambient air pollutants in Shanghai, China[J].Biomedical and Environmental Sciences, 2004, 3(17):366-372.
[27] Mdyusof N F F, Ramli N A, Yahaya A S, et al. Central fitting distributions and extreme value distributions for prediction of high PM10 concentration[C]//International Conference on Multimedia Technology IEEE, 2011:6263-6266.
[28]邓启红,黄柏良,唐猛,等.长沙市大气颗粒物PM10质量浓度的统计分布特性[J].中南大学学报(自然科学版),2012, 43(4):1567-1573.
[29] Tian P C. Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application[J]. Applied Energy, 2011, 88(1):272-282.
[30] Marani A, Lavagnini I, Buttazzoni C. Statistical Study of Air Pollutant Concentrations via Generalized Gamma Distributions[J]. Air Repair, 1986, 36(11):1250-1254.
[31] Leiva V, Barros M, Paula G A, et al. Generalized Birnbaum-Saunders distributions applied to air pollutant concentration[J]. Environmetrics, 2008, 19(3):235-249.
[32] Balakrishnan N, Kateri M. On the maximum likelihood estimation of parameters of Weibull distribution based on complete and censored data[J]. Statistics Probability Letters, 2008, 17(78):2971-2975.
[33] Mohammadi K, Alavi O, Mostafaeipour A, et al. Assessing different parameters estimation methods of Weibull distribution to compute wind power density[J]. Energy Conversion and Management,2016, 108:322-335.
[34] Amin Z H. A note on the parameter estimation for the lognormal distribution based on progressively type I interval censored samples[J]. Model Assisted Statistics Applications, 2008, 3(3):169-176.
[35] Liu Z. Estimation based on likelihood depth with application to the shape parameter of Gamma distribution[J]. Journal of Information Computational Science, 2015, 12(10):3907-3914.
[36]徐晓岭,王蓉华,顾蓓青.全样本场合下两参数Birnbaum-Saunders疲劳寿命分布的统计分析[J].浙江大学学报(理学版),2017, 44(6):692-704.