Can MODIS AOD be employed to derive PM2.5 in Beijing-Tianjin-Hebei over China?

Abstract The fine particular matter (PM) concentrations in China have increased considerably due to the rapid economic growth and urbanization in the last few decades, especially in the most populated and industrialized regions. Beijing-Tianjin-Hebei is one of the most polluted regions in China, so to monitor the PM2.5 concentrations over this region is quite critical for human health. By making use the new released hourly PM2.5 mass concentration from ground-based observations in Beijing-Tianjin-Hebei over China, and collocated MODIS level 2 AOD data from April 2014 to March 2015, we explored the relation between surface PM2.5 mass concentration and MODIS AOD and possibility to derive the surface PM2.5 from satellite retrieval in the region. Our study show that the relation strongly depend on the seasons due to distinct seasonal characteristics of PM2.5 and AOD, with a relatively better correlation in spring and summertime (correlation coefficient r ranging from 0.52 to 0.79) than autumn and wintertime (r can be low as to 0.23 in site Baoding). Our analysis gave evidence that worse relationship and/or smaller number of sample in wintertime is associated with the significantly high PM2.5 concentration and a lot of missing data occurring in MODIS AOD, implying that current MODIS AOD retrieval scheme does not work very well in highly polluted cases. The derived PM2.5 mass concentration from MODIS AOD in summertime can basically capture the major observed features of the time series and about 20% large bias of the derived values compared to the observation is expected to be reduced if longer time period data is available and used for analysis.

[1]  D. Dockery,et al.  Air pollution and life expectancy in China and beyond , 2013, Proceedings of the National Academy of Sciences.

[2]  Daniel Krewski,et al.  Cardiovascular Mortality and Exposure to Airborne Fine Particulate Matter and Cigarette Smoke: Shape of the Exposure-Response Relationship , 2009, Circulation.

[3]  Jun Wang,et al.  Intercomparison between satellite‐derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies , 2003 .

[4]  Wenjun Jiang,et al.  Inhalable Microorganisms in Beijing’s PM2.5 and PM10 Pollutants during a Severe Smog Event , 2014, Environmental science & technology.

[5]  B. Holben,et al.  Validation of MODIS aerosol optical depth retrieval over land , 2002 .

[6]  Michal Krzyzanowski,et al.  Satellite-based estimates of ground-level fine particulate matter during extreme events: A case study of the Moscow fires in 2010 , 2011 .

[7]  R. Martin,et al.  Estimating ground-level PM2.5 using aerosol optical depth determined from satellite remote sensing , 2006 .

[8]  Jun Wang,et al.  Potential application of VIIRS Day/Night Band for monitoring nighttime surface PM 2.5 air quality from space , 2016 .

[9]  Jun Wang,et al.  Opposite seasonality of the aerosol optical depth and the surface particulate matter concentration over the north China Plain , 2016 .

[10]  F. Yu,et al.  Seasonal variability of aerosol vertical profiles over east US and west Europe: GEOS-Chem/APM simulation and comparison with CALIPSO observations , 2014 .

[11]  E. Vermote,et al.  Second‐generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance , 2007 .

[12]  B. Brunekreef,et al.  Air pollution and health , 2002, The Lancet.

[13]  G. Leeuw,et al.  Exploring the relation between aerosol optical depth and PM 2.5 at Cabauw, the Netherlands , 2008 .

[14]  B. Holben,et al.  Global monitoring of air pollution over land from the Earth Observing System-Terra Moderate Resolution Imaging Spectroradiometer (MODIS) , 2003 .

[15]  Daniel Krewski,et al.  Rejoinder: Reanalysis of the Harvard Six Cities Study and American Cancer Society Study of Particulate Air Pollution and Mortality , 2003 .

[16]  P. Zhao,et al.  Long-term visibility trends and characteristics in the region of Beijing, Tianjin, and Hebei, China , 2011 .

[17]  Kenneth Sassen,et al.  Lidar Backscatter Depolarization Technique for Cloud and Aerosol Research , 2000 .

[18]  Po-Hsiung Lin,et al.  Estimating ground-level PM 2.5 in eastern China using aerosol optical depth determined from the GOCI satellite instrument , 2015 .

[19]  D. Jacob,et al.  Improved algorithm for MODIS satellite retrievals of aerosol optical depths over western North America , 2008 .

[20]  Liangfu Chen,et al.  Estimating Ground-Level PM2.5 Using Fine-Resolution Satellite Data in the Megacity of Beijing, China , 2015 .

[21]  R. Koelemeijer,et al.  Comparison of spatial and temporal variations of aerosol optical thickness and particulate matter over Europe , 2006 .

[22]  Jassim A. Al-Saadi,et al.  Integrating lidar and satellite optical depth with ambient monitoring for 3-dimensional particulate characterization , 2006 .

[23]  Robert C. Levy,et al.  Optimal estimation for global ground‐level fine particulate matter concentrations , 2013 .

[24]  Jun Wang,et al.  Improved algorithm for MODIS satellite retrievals of aerosol optical thickness over land in dusty atmosphere: Implications for air quality monitoring in China , 2010 .

[25]  Basil W. Coutant,et al.  Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality , 2004 .

[26]  Jun Wang,et al.  Satellite remote sensing of particulate matter and air quality assessment over global cities , 2006 .

[27]  Sundar A. Christopher,et al.  The effects of non‐sphericity on geostationary satellite retrievals of dust aerosols , 2003 .

[28]  Jun Wang,et al.  Influence of relative humidity on aerosol composition: Impacts on light extinction and visibility impairment at two sites in coastal area of China , 2015 .

[29]  Jun Wang,et al.  Effect of cold wave on winter visibility over eastern China , 2015 .

[30]  Tongwen Wu,et al.  Effect of the strengthened western Pacific subtropical high on summer visibility decrease over eastern China since 1973 , 2013 .

[31]  Zhanqing Li,et al.  Aircraft measurements of the vertical distribution and activation property of aerosol particles over the Loess Plateau in China , 2015 .

[32]  Alan D. Lopez,et al.  A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010 , 2012, The Lancet.

[33]  E. Vermote,et al.  The MODIS Aerosol Algorithm, Products, and Validation , 2005 .

[34]  Qifan Liu,et al.  Characterization of submicron aerosols during a month of serious pollution in Beijing, 2013 , 2014 .

[35]  S. Christopher,et al.  Remote Sensing of Particulate Pollution from Space: Have We Reached the Promised Land? , 2009, Journal of the Air & Waste Management Association.

[36]  Chunsheng Zhao,et al.  Characterizations of aerosols over the Beijing region: A case study of aircraft measurements , 2006 .

[37]  D. Dockery,et al.  An association between air pollution and mortality in six U.S. cities. , 1993, The New England journal of medicine.

[38]  E. Vermote,et al.  Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer , 1997 .

[39]  R. Burnett,et al.  Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. , 2009, Research report.