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城市空气质量监测网络评估方法
Research on urban ambient air monitoring network assessment guidance
通过研究借鉴多个国家/城市的研究实践，提出了城市空气治理监测网络（UAAMNA）评估管理的方法，包括评估思路与流程，评估关键指标，针对不同污染物的评估方法等.以沈阳市及周边6个城市共46个国控监测站点的监测网络为背景，基于2013~2018年日尺度空气质量数据，考虑监测成本，对沈阳市PM2.5监测网络进行评估，结果表明，沈河区增加1个最高浓度站点，大东区增加1个高人口密度区站点，皇姑区增加1个跨界传输点；在沈阳-铁岭，沈阳-本溪，沈阳-辽阳方向增设跨区域站点.未来建立空气质量监测网络定期评估制度、加强跨区域边界站点布设、实施区分监测点位类型评估、区分污染物类型评估是UAAMN的发展方向.
Aiming at optimizing the Urban Ambient Air Monitoring Network (UAAMN), which borrowed from practices of many countries/cities, the general procedure of assessment management was put forward, the key index matrix of assessment was constructed, and the methodology of air quality monitoring network assessment for distinguishing pollutants was established. Taking 46 stations in Shenyang (including districts and counties) and six surrounding cities as an example, which took cost-benefit into account, this method was used to evaluate the monitoring network of PM2.5. The results showed that this method can be successfully applied to the optimization of UAAMNA, Shenhe District needed to add a maximum concentration station, Dadong District needed to add a high population density station, Huanggu District needed to add a cross border station. In addition, cross-city sites such as Shenyang-Tieling, Shenyang-Benxi and Shenyang-Liaoyang should be set up. In the future, the further research of urban air quality monitoring network assessment was about to establish regular assessment system of air quality monitoring network, implement classification assessment of monitoring stations and distinguish pollutant types.
different pollutants / guidance / key indicators / monitoring network assessment
[1] HJ 664-2013环境空气质量监测点位布设技术规范[S]. HJ 664-2013 Technical regulation for selection of ambient air quality monitoring stations[S].
[2] Fioccola G B, Sommese R, Tufano I, et al. Pollution:An efficient cloud-based management of IT devices for air quality monitoring[C]//International Forum on Research & Technologies for Society & Industry Leveraging a Better Tomorrow. IEEE, 2016.
[3] Zhu Z Q, Chen B, Qiu S H, et al. A data-driven approach for optimal design of integrated air quality monitoring network in a chemical cluster[J]. Royal Society Open Science, 2018,5(9):74-79.
[4] Cohen A J, Brauer M, Burnett R, et al. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution:an analysis of data from the global burden of diseases study 2015[J]. The Lancet, 2017,389(10082):1907-1918.
[5] Zoroufchi B K, Fatehifar E, Shafiei S, et al. Design of a sensitive air quality monitoring network using an integrated optimization approach[J]. Stochastic Environmental Research and Risk Assessment, 2016,30(3):779-793.
[6] 秦怡雯,钱瑜,荣婷婷.基于大气特征污染物的监测布点选址优化研究[J]. 中国环境科学, 2015,35(4):1056-1064. Qin Y W, Qian Y, Rong T T. Study on optimization of monitoring sites based on atmospheric characteristic pollutants[J]. China Environmental Science, 2015,35(4):1056-1064.
[7] He H D, Li M, Wang W L, et al. Prediction of PM2.5 concentration based on the similarity in air quality monitoring network[J]. Building and Environment, 2018,137:11-17.
[8] Benis K Z, Fatehifar E. Optimal design of air quality monitoring network around an oil refinery plant:a holistic approach[J]. International journal of Environmental Science and Technology, 2015,12(4):22-28.
[9] 吴也正.苏州市区大气监测点位调整中的相关性和聚类分析[J]. 干旱环境监测, 2016,30(2):49-53. Wu Y Z. Correlation analysis and clustering analysis to the adjustment of atmospheric monitoring sites in urban area of Suzhou[J]. Arid Environmental Monitoring, 2016,30(2):49-53.
[10] Atsushi I, Shintaro S, Atsushi M, et al. A cluster analysis of constant ambient air monitoring data from the Kanto Region of Japan[J]. International Journal of Environmental Research and Public Health, 2014,11(7):6844-6855.
[11] Qiu S, Chen B, Wang R, et al. Atmospheric dispersion prediction and source estimation of hazardous gas using artificial neural network, particle swarm optimization and expectation maximization[J]. Atmospheric Environment, 2018,178:158-163.
[12] Chen M, Wang S, Xu Q. Multiobjective optimization for air-quality monitoring network design[J]. Industrial & Engineering Chemistry Research, 2015,54(31):33-40.
[13] Benis K Z, Fatehifar E. Optimal design of air quality monitoring network around an oil refinery plant:a holistic approach[J]. International journal of Environmental Science and Technology, 2015,12(4):12-18.
[14] 王陆平.大气质量评价模型和监测点位优化研究[D]. 西安:西安科技大学, 2017. Wang L P. The research on urban air quality evaluation model and monitoring point optimization[D]. Xi'an:Xi'an University of Science and Technology, 2017.
[15] 刘光艳.空气监测点位优化和大气质量评价的研究[D]. 济南:山东师范大学, 2003. Liu G Y. Study on air monitoring optimization site and air quality assessment[D]. Jinan:Shandong Normal University, 2003.
[16] 苗蕾.针对PM2.5的武汉市大气监测点位的布局研究[J]. 环境科学与管理, 2013,38(12):122-126. Miao L. Layout optimization for PM2.5 monitoring sites in Wuhan[J]. Environmental Science and Management, 2013,38(12):122-126.
[17] 李成才,周寅亮,李莹,等.利用卫星遥感大气气溶胶进行待建环境监测站点位评估[J]. 北京大学学报:自然科学版, 2014,50(5):825-834. Li C C, Zhou Y L, Li Y, et al Assessment of the location of one background monitoring station to be built with particulate matter remote sensing from space[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2014,50(5):825-834.
[18] 刘潘炜,郑君瑜,李志成,等.区域空气质量监测网络优化布点方法研究[J]. 中国环境科学, 2010,30(7):907-913. Chen P W, Zheng J Y, Li Z C, et al. Optimization of site locations of regional air quality monitoring network:methodology study[J]. China Environmental Science, 2010,30(7):907-913.
[19] Piersanti A, Vitali L, Righini G, et al. Spatial representativeness of air quality monitoring stations:A grid model based approach[J]. Atmospheric Pollution Research, 2015,6(6):953-960.
[20] 钟流举,郑君瑜,雷国强,等.空气质量监测网络发展现状与趋势分析[J]. 中国环境监测, 2007,23(2):113-118. Zhong L J, Zheng J Y, Lei G Q, et al. Analysis of current status and trends of air quality monitoring networks[J]. Environmental Monitoring in China, 2007,23(2):113-118.
[21] 乔纳森·R·汤普金斯.公共管理学说史-组织理论与公共管理[M]. 上海:上海译文出版社, 2010:28-37. Jonathan R. Thompkins. Organization theory and public management[M]. Shanghai:Shanghai Translation Publishing House, 2010:28-37.
[22] Hao Y, Xie S. Optimal redistribution of an urban air quality monitoring network using atmospheric dispersion model and genetic algorithm[J]. Atmospheric Environment, 2018,177(1):113-123.
[23] Ando B, Cammarata G, Fichera A, et al. A procedure for the optimization of air quality monitoring networks[J]. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 1999,29(1):157-163.
[24] Shivam G, Edzer P. Air quality monitoring network design optimization for robust land use regression models[J]. Sustainability, 2018,10(5):11-21.
[25] Zivin J G, Neidell M. Air pollution's hidden impacts[J]. Science, 2018,359(6371):39-40.
[26] Henriquez A, Osses A, Gallardo L, et al. Analysis and optimal design of air quality monitoring networks using a vibrational approach[J]. Tellus B:Chemical and Physical Meteorology, 2015,67(1):110-120.
[27] Senaratne H, Mobasheri A, Ali A L, et al. A review of volunteered geographic information quality assessment methods[J]. International Journal of Geographical Information Systems, 2017,31(1):29.
[28] Araki S, Iwahashi K, Shimadera H, et al. Optimization of air monitoring networks using chemical transport model and search algorithm[J]. Atmospheric Environment, 2015,122:22-30.
[29] Shivam G, Edzer P. Optimizing citizen-driven air quality monitoring networks for cities[J]. Geo-Inf, 2018,7(12):468.
[30] Sean M. R, Dana C. S, Michael C. M, et al. Ambient air monitoring network assessment guidance[R]. North Carolina:Environmental Protection Agency Office of Air Quality Planning and Standards Air Quality Assessment Division, 2007.
[31] 万显烈,杨凤林,王慧卿.利用人工神经网络对空气中O3浓度进行预测[J]. 中国环境科学, 2003,23(1):110-112. Wan X L, Yang F L, Wang H Q. The approach of artificial neural network applied in ambient ozone forecast[J]. China Environmental Science, 2003,23(1):110-112.
[32] Zoroufchi B K, Fatehifar E, Shafiei S, et al. Design of a sensitive air quality monitoring network using an integrated optimization approach[J]. Stochastic Environmental Research and Risk Assessment, 2016,30(3):779-793.
[33] He H D, Li M, Wang W L, et al. Prediction of PM2.5, concentration based on the similarity in air quality monitoring network[J]. Building and Environment, 2018,137:11-17.
[34] 庄欣,黄晓锋,陈多宏,等.基于日变化特征的珠江三角洲大气污染空间分布研究[J]. 中国环境科学, 2017,37(6):2001-2006. Zhuang X, Huang X F, Chen D H, et al. Studies on spatial distribution of air pollution in Pearl River Delta based on diurnal variation characteristics[J]. China Environmental Science, 2017,37(6):2001-2006.
国家重点研发计划项目（2017YFC02125）
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