浏览全部资源
扫码关注微信
Received：27 September 2019，
Published：07 November 2020
移动端阅览
大气细颗粒物（PM
2.5
）质量浓度是重要的空气质量指标之一。为了促进区域PM
2.5
浓度监测的研究，同时拓展利用CE318太阳光度计等光学传感器反演的大气气溶胶产品的应用领域，本文首先基于北京地区2014年—2017年大气气溶胶反演的粒径尺度谱分布产品，计算表征PM
2.5
的粒子体积，并结合同一时间北京地区35个空气质量站点提供的PM
2.5
质量浓度参考值计算转换系数，对样本区间进行划分以构建转换模型。其次，利用各CE318站点数据所得转换系数及其相对精度，对研究区PM
2.5
质量浓度估算误差空间分布，以及转换系数偏差对估值误差贡献情况进行评价。研究结果表明，由CE318站PM
2.5
粒子体积与其临近空气质量站PM
2.5
质量浓度联合建立的转换系数是一种与气溶胶理化属性密切相关的参数指标，可将时间和空间维度上PM
2.5
体积与PM
2.5
质量浓度之间的关系映射到由理化属性主导的维度上，可用于对估值模型进行细化和分类，构建分段转换函数模型，使得各分段区间内具有较高的模型拟合精度。基于转换系数的北京地区PM
2.5
浓度估值的相对误差多年均值介于12.8 %—28.7 %，而转换系数相对偏差对PM
2.5
质量浓度估值相对误差的影响显著，二者之间具有“
r
”型结构。当转换系数相对偏差介于-16.3 %至24.5 %时，该偏差的出现概率约为66.5 %，使得PM
2.5
质量浓度估值误差在20 %以内，表明采用此种方法对相应站点的PM
2.5
质量浓度进行估值具有相当的精度和稳定性。以上研究结果可为地面观测站稀少区域利用卫星光学遥感开展空气质量大范围监测应用提供理论前提和技术支持。
The mass concentration of atmospheric fine particles (PM
2.5
) is an important indicator of air quality. This study aimed to promote regional PM
2.5
mass concentration monitoring and expand the applications of CE318 sun photometer and other optical sensors in the inversion of atmospheric aerosol products. This study used the size distribution data of atmospheric aerosol particles from Beijing’s 2014—2017 atmospheric aerosol product data to extract the volume of PM
2.5
. These data were combined with the reference values of PM
2.5
mass concentrations from 35 air quality measurement stations in Beijing to calculate the conversion coefficient
thereby establishing a conversion model. The conversion coefficients obtained from all CE318 stations and their relative deviations were used to evaluate the spatial distribution of PM
2.5
concentration errors in Beijing. Results show that the conversion coefficients that were jointly created using PM
2.5
volume from CE318 stations and the PM
2.5
mass concentration from nearby air quality stations are closely associated with aerosol physiochemical characteristics. These conversion coefficients can be used for the classification and refinement of the correlation between PM
2.5
volume and PM
2.5
mass concentration. This correlation is utilized to establish a piecewise conversion function model
so that each segment has high model fitting accuracy. The mean relative errors of the estimated PM
2.5
mass concentrations in Beijing based on the conversion coefficient range from 12.9% to 33.8%. The relative deviation of the conversion coefficients significantly affects the relative error of estimated PM
2.5
mass concentrations because of the existence of an “
r
” structure between them. The probability of this deviation appearing is approximately 66.5% when the relative deviation of conversion coefficient ranges from -16.3% to 24.5%. This condition causes the errors of PM
2.5
mass concentration estimation to be lower than 20%. Results show that our method is relatively accurate and stable when used to estimate PM
2.5
mass concentrations at the corresponding stations. The study results can provide corresponding theoretical support and data reference for the research on ground- and satellite-based optical remote sensing of regional PM
2.5
mass concentrations.
Bigi A and Ghermandi G . 2011 . Particle number size distribution and weight concentration of background urban aerosol in a Po valley site. Water, Air, and Soil Pollution, 220( 1 / 4 ): 265 - 278 [ DOI: 10.1007/s11270-011-0752-6 http://dx.doi.org/10.1007/s11270-011-0752-6 ]
Cao Q F , Shen L , Chen S C and Pui D Y H . 2018 . Wrf modeling of PM 2.5 remediation by salscs and its clean air flow over Beijing terrain . Science of the Total Environment , 626 : 134 - 146 [ DOI: 10.1016/j.scitotenv.2018.01.062 http://dx.doi.org/10.1016/j.scitotenv.2018.01.062 ]
Chen B , Wang Q , Zhong Q and Yang K . 2014 . Comparison of standard gravimetric measurement method for PM 2.5 between China, United State and Europe . Environmental Science and Technology , 37 ( 11 ): 196 - 200
陈斌 , 王强 , 钟琪 , 杨凯 . 2014 . 中美欧PM 2.5 手工重量法对比及借鉴 . 环境科学与技术 , 37 ( 11 ): 196 - 200 [ DOI: 10.3969/j.issn.1003-6504.2014.11.038 http://dx.doi.org/10.3969/j.issn.1003-6504.2014.11.038 ]
Chen H , Li Q , Wang Z T , Sun Y , Mao H Q and Cheng B . 2018 . Utilization of MERSI and MODIS data to monitor PM 2.5 concentration in Beijing-Tianjin-Hebei and its surrounding areas . Journal of Remote Sensing , 22 ( 5 ): 822 - 832
陈辉 , 厉青 , 王中挺 , 孙云 , 毛慧琴 , 程斌 . 2018 . MERSI和MODIS卫星监测京津冀及周边地区PM 2.5 浓度 . 遥感学报 , 22 ( 5 ): 822 - 832 [ DOI: 10.11834/jrs.20187123 http://dx.doi.org/10.11834/jrs.20187123 ]
Chu D A , Kaufman Y J , Zibordi G , Chern J D , Mao J T , Li C C and Holben B N . 2003 . Global monitoring of air pollution over land from the Earth Observing System-Terra Moderate Resolution Imaging Spectroradiometer (MODIS). Journal of Geophysical Research, 108 (D 21 ): 4661 [ DOI: 10.1029/2002jd003179 http://dx.doi.org/10.1029/2002jd003179 ]
Chu Y Y , Liu Y S , Li X Y , Liu Z Y , Lu H , Lu Y A , Mao Z F , Chen X , Li N , Ren M , Liu F F , Tian L Q , Zhu Z G and Xiang H . 2016 . A review on predicting ground PM 2.5 concentration using satellite aerosol optical depth . Atmosphere , 7 ( 10 ): 129 [ DOI: 10.3390/atmos7100129 http://dx.doi.org/10.3390/atmos7100129 ]
Deng X J , Zhou X J , Wu D , Tie X X , Tan H B , Li F , Bi X Y , Deng T and Jiang D H . 2011 . Effect of atmospheric aerosol on surface ozone variation over the Pearl River Delta region . Science China : Earth Sciences , 54 ( 5 ): 744 - 752
邓雪娇 , 周秀骥 , 吴兑 , 铁学熙 , 谭浩波 , 李菲 , 毕雪岩 , 邓涛 , 蒋德海 . 2011 . 珠江三角洲大气气溶胶对地面臭氧变化的影响 . 中国科学 : 地球科学 , 41 ( 1 ): 93 - 102 [ DOI: 10.1007/s11430-011-4172-7 http://dx.doi.org/10.1007/s11430-011-4172-7 ]
Dubovik O , Herman M , Holdak A , Lapyonok T , Tanré D , Deuzé J L , Ducos F , Sinyuk A and Lopatin A . 2011 . Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations . Atmospheric Measurement Techniques , 4 ( 5 ): 975 - 1018 [ DOI: 10.5194/amt-4-975-2011 http://dx.doi.org/10.5194/amt-4-975-2011 ]
Emetere M E , Akinyemi M L and Akin-Ojo O . 2015 . Parametric retrieval model for estimating aerosol size distribution via the AERONET, LAGOS station . Environmental Pollution , 207 : 381 - 390 [ DOI: 10.1016/j.envpol.2015.09.047 http://dx.doi.org/10.1016/j.envpol.2015.09.047 ]
Estellés V , Campanelli M , Smyth T J , Utrillas M P and Martínez-Lozano J A . 2010 . AERONET and Euroskyrad (ESR) aerosol optical depth intercomparison on Cimel CE318 and Prede POM01 radiometers // Proceedings Volume 7827 , Remote Sensing of Clouds and the Atmosphere XV. Toulouse, France : SPIE [ DOI: 10.1117/12.865039 http://dx.doi.org/10.1117/12.865039 ]
Fu X X . 2015 . Influence of PM2.5 major components on aerosol acidity and light extinction in the Pearl River Delta region . Guangzhou :
Guangzhou Institute of Geochemistry , Chinese Academy of Sciences 付晓辛 . 2015 . 珠江三角洲地区PM2.5浓度组成变化及其对粒子酸度和消光的影响 . 广州 : 中国科学院广州地球化学研究所
Guo J P , Wu Y R , Zhang X Y and Li X W . 2013 . Estimation of PM 2.5 over eastern China from MODIS aerosol optical depth using the back propagation neural network . Environmental Science , 34 ( 3 ): 817 - 825
郭建平 , 吴业荣 , 张小曳 , 李小文 . 2013 . BP网络框架下MODIS气溶胶光学厚度产品估算中国东部PM 2.5 . 环境科学 , 34 ( 3 ): 817 - 825
Guo J P , Xia F , Zhang Y , Liu H , Li J , Lou M Y , He J , Yan Y , Wang F , Min M and Zhai P M . 2017 . Impact of diurnal variability and meteorological factors on the PM 2.5 -AOD relationship: implications for PM 2.5 remote sensing . Environmental Pollution , 221 : 94 - 104 [ DOI: 10.1016/j.envpol.2016.11.043 http://dx.doi.org/10.1016/j.envpol.2016.11.043 ]
Gupta P , Christopher S A , Wang J , Gehrig R , Lee Y and Kumar N . 2006 . Satellite remote sensing of particulate matter and air quality assessment over global cities . Atmospheric Environment , 40 ( 30 ): 5880 - 5892 [ DOI: 10.1016/j.atmosenv.2006.03.016 http://dx.doi.org/10.1016/j.atmosenv.2006.03.016 ]
Han B X , Zhang G H , Bi X H , Wang X M , Sheng G Y and Fu J M . 2015 . Pollution characteristics of atmospheric particle size and number concentrations during summer in urban area of Guangzhou . Research of Environmental Sciences , 28 ( 2 ): 198 - 204
韩冰雪 , 张国华 , 毕新慧 , 王新明 , 盛国英 , 傅家谟 . 2015 . 广州城区夏季大气颗粒物数浓度谱分布特征 . 环境科学研究 , 28 ( 2 ): 198 - 204 [ DOI: 10.13198/j.issn.1001-6929.2015.02.05 http://dx.doi.org/10.13198/j.issn.1001-6929.2015.02.05 ]
Holben B N , Eck T F , Slutsker I , Tanré D , Buis J P , Setzer A , Vermote E , Reagan J A , Kaufman Y J , Nakajima T , Lavenu F , Jankowiak I and Smirnov A . 1998 . Aeronet-a federated instrument network and data archive for aerosol characterization . Remote Sensing of Environment , 66 ( 1 ): 1 - 16 [ DOI: 10.1016/s0034-4257(98)00031-5 http://dx.doi.org/10.1016/s0034-4257(98)00031-5 ]
Hu X F , Waller L A , Lyapustin A , Wang Y J , AI-Hamdan M Z , Crosson W L , Estes M G , Estes S M , Quattrochi D A , Puttaswamy S J and Liu Y . 2014 . Estimating ground-level PM 2.5 concentrations in the Southeastern United States using MAIAC AOD retrievals and a two-stage model . Remote Sensing of Environment , 140 ( 1 ): 220 - 232 [ DOI: 10.1016/j.rse.2013.08.032 http://dx.doi.org/10.1016/j.rse.2013.08.032 ]
Lee H J , Chatfield R B and Strawa A W . 2016 . Enhancing the applicability of satellite remote sensing for PM 2.5 estimation using MODIS deep blue AOD and land use regression in California, United States . Environmental Science and Technology , 50 ( 12 ): 6546 - 6555 [ DOI: 10.1021/acs.est.6b01438 http://dx.doi.org/10.1021/acs.est.6b01438 ]
Ji H Z , Chen S Y , Zhang Y C , Chen H , Guo P and Zhao P T . 2018 . Comparison of air quality at different altitudes from multi-platform measurements in Beijing . Atmospheric Chemistry and Physics , 18 : 10645 - 10653 [ DOI: 10.5194/acp-18-10645-2018 http://dx.doi.org/10.5194/acp-18-10645-2018 ]
Jiang Q , Wang F , Zhang H D , Wang F , Lü M Y and He J B . 2017 . The characteristics of PM 2.5 , reactive gas and aerosol size distributions of Beijing from 2013 to 2015 . China Environmental Science , 37 ( 10 ): 3647 - 3657
江琪 , 王飞 , 张恒德 , 王飞 , 吕梦瑶 , 何佳宝 . 2017 . 2013—2015年北京市PM 2.5 、反应性气体和气溶胶粒径的特性分析 . 中国环境科学 , 37 ( 10 ): 3647 - 3657 [ DOI: 10.3969/j.issn.1000-6923.2017.10.005 http://dx.doi.org/10.3969/j.issn.1000-6923.2017.10.005 ]
Li J , Carlson B E and Lacis A A . 2015 . How well do satellite AOD observations represent the spatial and temporal variability of PM 2.5 concentration for the United States . Atmospheric Environment , 102 : 260 - 273 [ DOI: 10.1016/j.atmosenv.2014.12.010 http://dx.doi.org/10.1016/j.atmosenv.2014.12.010 ]
Li Z Q , Zhang Y , Shao J , Li B S , Hong J , Liu D , Li D H , Wei P , Li W , Zhang F X , Guo J , Deng Q , Wang B X , Cui C L , Zhang W C , Wang Z Z , Lv Y , Xu H , Chen X F , Li L and Qie L L . 2016 . Remote sensing of atmospheric particulate mass of dry PM 2.5 near the ground: method validation using ground-based measurements . Remote Sensing of Environment , 173 : 59 - 68 [ DOI: 10.1016/j.rse.2015.11.019 http://dx.doi.org/10.1016/j.rse.2015.11.019 ]
Lv B L , Zhang B and Bai Y Q . 2016 . A systematic analysis of PM 2.5 in Beijing and its sources from 2000 to 2012 . Atmospheric Environment , 124 : 98 - 108 [ DOI: 10.1016/j.atmosenv.2015.09.031 http://dx.doi.org/10.1016/j.atmosenv.2015.09.031 ]
Madrigano J , Kloog I , Goldberg R , Coull B A , Mittleman M A and Schwartz J . 2013 . Long-term exposure to PM 2.5 and incidence of acute myocardial infarction . Environmental Health Perspectives , 121 ( 2 ): 192 - 196 [ DOI: 10.1289/ehp.1205284 http://dx.doi.org/10.1289/ehp.1205284 ]
Smirnov A , Holben B N , Eck T F , Dubovik O and Slutsker I . 2000 . Cloud-screening and quality control algorithms for the AERONET database . Remote Sensing of Environment , 73 ( 3 ): 337 - 349 [ DOI: 10.1016/S0034-4257(00)00109-7 http://dx.doi.org/10.1016/S0034-4257(00)00109-7 ]
Tao J H , Zhang M G , Chen L F , Wang Z F , Su L , Ge C , Han X and Zou M M . 2013 . A method to estimate concentrations of surface-level particulate matter using satellite-based aerosol optical thickness . Science China : Earth Sciences , 56 ( 8 ): 1422 - 1433
陶金花 , 张美根 , 陈良富 , 王子峰 , 苏林 , 葛萃 , 韩霄 , 邹铭敏 . 2013 . 一种基于卫星遥感AOT估算近地面颗粒物的方法 . 中国科学 : 地球科学 , 43 ( 1 ): 143 - 154 [ DOI: 10.1007/s11430-012-4503-3 http://dx.doi.org/10.1007/s11430-012-4503-3 ]
Tian X P , Sun L , Liu Q and Li X H . 2018 . Retrieval of high-resolution aerosol optical depth using Landsat 8 OLI data over Beijing. Journal of Remote Sensing , 22 ( 1 ): 51 - 63
田信鹏 , 孙林 , 刘强 , 李秀红 . 2018 . 北京地区Landsat 8 OLI高空间分辨率气溶胶光学厚度反演 . 遥感学报 , 22 ( 1 ): 51-63 [ DOI: 10.11834/jrs.20186362 http://dx.doi.org/10.11834/jrs.20186362 ]
Van Donkelaar A , Martin R V and Park R J . 2006 . Estimating ground-level PM 2.5 using aerosol optical depth determined from satellite remote sensing. Journal of Geophysical Research: Atmospheres, 111 (D 21 ): D 21201 [ DOI: 10.1029/2005JD006996 http://dx.doi.org/10.1029/2005JD006996 ]
Wang J C , Zhu C J , Zhu Y and Chen S G . 2015 . Correlation between remote sensing aerosol parameters and PM 2.5 in Beijing . China Environmental Science , 35 ( 7 ): 1947 - 1956
王家成 , 朱成杰 , 朱勇 , 陈曙光 . 2015 . 北京地区多气溶胶遥感参量与PM 2.5 相关性研究 . 中国环境科学 , 35 ( 7 ): 1947 - 1956 [ DOI: 10.3969/j.issn.1000-6923.2015.07.005 http://dx.doi.org/10.3969/j.issn.1000-6923.2015.07.005 ]
Wang J L and Liu X L . 2006 . The discuss on relationship between visibility and mass concentration of PM 2.5 in Beijing . Acta Meteorologica Sinica , 64 ( 2 ): 221 - 228
王京丽 , 刘旭林 . 2006 . 北京市大气细粒子质量浓度与能见度定量关系初探 . 气象学报 , 64 ( 2 ): 221 - 228 [ DOI: 10.3321/j.issn:0577-6619.2006.02.010 http://dx.doi.org/10.3321/j.issn:0577-6619.2006.02.010 ]
WMO . 2003 . Aerosol Measurement procedures guidelines and recommendations . WMO No . 153 . Geneva: World Meteorological Organization: 24 - 37
Wu Y R , Guo J P , Zhang X Y , Tian X , Zhang J H , Wang Y Q , Duan J and Li X W . 2012 . Synergy of satellite and ground based observations in estimation of particulate matter in eastern China . Science of the Total Environment , 433 : 20 - 30 [ DOI: 10.1016/j.scitotenv.2012.06.033 http://dx.doi.org/10.1016/j.scitotenv.2012.06.033 ]
Xu J H and Jiang H . 2015 . Estimation of PM 2.5 concentration over the Yangtze delta using remote sensing: analysis of spatial and temporal variations . Environmental Science , 36 ( 9 ): 3119 - 3127
徐建辉 , 江洪 . 2015 . 长江三角洲 PM 2.5 质量浓度遥感估算与时空分布特征 . 环境科学 , 36 ( 9 ): 3119 - 3127 [ DOI: 10.13227/j.hjkx.2015.09.001 http://dx.doi.org/10.13227/j.hjkx.2015.09.001 ]
Yan X , Shi W Z , Li Z Q , Li Z Q , Luo N N , Zhao W J , Wang H F and Yu X . 2017 . Satellite-based PM 2.5 estimation using fine-mode aerosol optical thickness over China . Atmospheric Environment , 170 : 290 - 302 [ DOI: 10.1016/j.atmosenv.2017.09.023 http://dx.doi.org/10.1016/j.atmosenv.2017.09.023 ]
Zhang T H , Gong W , Wang W , Ji Y X , Zhu Z M and Huang Y S . 2016 . Ground level PM 2.5 estimates over China using satellite-based geographically weighted regression (GWR) models are improved by including NO 2 and enhanced vegetation index (EVI) . International Journal of Environmental Research and Public Health , 13 ( 12 ): 1215 [ DOI: 10.3390/ijerph13121215 http://dx.doi.org/10.3390/ijerph13121215 ]
Zhang Y and Li Z Q . 2013 . Estimation of PM 2.5 from fine-mode aerosol optical depth . Journal of Remote Sensing , 17 ( 4 ): 929 - 943
张莹 , 李正强 . 2013 . 利用细模态气溶胶光学厚度估计PM 2.5 . 遥感学报 , 17 ( 4 ): 929 - 943 [ DOI: 10.11834/jrs.20133063 http://dx.doi.org/10.11834/jrs.20133063 ]
Zhang Y and Li Z Q . 2015 . Remote sensing of atmospheric fine particulate matter (PM 2.5 ) mass concentration near the ground from satellite observation . Remote Sensing of Environment , 160 : 252 - 262 [ DOI: 10.1016/j.rse.2015.02.005 http://dx.doi.org/10.1016/j.rse.2015.02.005 ]
Zhao X , Pan J X , Liu B and Chen P . 2013 . Research of measuring technology for PM 2.5 based on the β-ray absorption method . Application of Electronic Technique , 39 ( 9 ): 74 - 76, 80
赵鑫 , 潘晋孝 , 刘宾 , 陈平 . 2013 . 基于β射线吸收法的PM 2.5 测量技术的研究 . 电子技术应用 , 39 ( 9 ): 74 - 76 , 80 [ DOI: 10.3969/j.issn.0258-7998.2013.09.025 http://dx.doi.org/10.3969/j.issn.0258-7998.2013.09.025 ]
相关文章
相关作者
相关机构
京公网安备11010802024621