A satellite-based geographically weighted regression model for regional PM2.5 estimation over the Pearl River Delta region in China

Remote Sensing of Environment

Volumn 154, Issue , 2014, Pages 1-7

  Song, Weize ^a   Jia, Haifeng ^a   Huang, Jingfeng ^b   Zhang, Yiyue ^a  

^a TSINGHUA UNIVERSITY   (China)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

Aerosol optical depth; Geographically weighted regression; Pearl River Delta region; Satellite remote sensing

Indexed keywords

ATMOSPHERIC AEROSOLS; LINEAR REGRESSION;

AEROSOL OPTICAL DEPTHS; CORRELATIVE RELATIONSHIP; GENERAL LINEAR REGRESSION MODELS (GLM); GEOGRAPHICALLY WEIGHTED REGRESSION; GEOGRAPHICALLY WEIGHTED REGRESSION MODELS; METEOROLOGICAL PARAMETERS; PEARL RIVER DELTA REGION; SATELLITE REMOTE SENSING;

SATELLITES;

AEROSOL PROPERTY; CONCENTRATION (COMPOSITION); OPTICAL DEPTH; PARTICLE SIZE; PARTICULATE MATTER; REGRESSION ANALYSIS; RELATIVE HUMIDITY; SATELLITE IMAGERY; AEROSOL; ESTIMATION METHOD; METEOROLOGY; NUMERICAL MODEL; REMOTE SENSING; SPATIAL VARIATION;

CHINA; GUANGDONG; ZHUJIANG DELTA;

EID: 84906761359     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2014.08.008     Document Type: Article

References (41)

1. Barman S.C., Singh R., Negi M.P.S., Bhargava S.K. Fine particles (PM2.5) in residential areas of Lucknow city and factors influencing the concentration. Clean-Soil Air Water 2008, 36:111-117. 10.1002/clen.200700047.
2. Benas N., Beloconi A., Chrysoulakis N. Estimation of urban PM10 concentration, based on MODIS and MERIS/AATSR synergistic observations. Atmospheric Environment 2013, 79:448-454. 10.1016/j.atmosenv.2013.07.012.
3. Brunsdon C., Fotheringham A.S., Charlton M.E. Geographically weighted regression: A method for exploring spatial nonstationarity. Geographical Analysis 1996, 28:281-298. 10.1111/j.1538-4632.1996.tb00936.x.
4. Chu D.A., Kaufman Y.J., Ichoku C., Remer L.A., Tanré D., Holben B.N. Validation of MODIS aerosol optical depth retrieval over land. Geophysical Research Letters 2002, 29:1617-1620. 10.1029/2001GL013205.
5. Dawson J.P., Adams P.J., Pandis S.N. Sensitivity of PM2.5 to climate in the Eastern US: A modeling case study. Atmospheric Chemistry and Physics 2007, 7:4295-4309. 10.5194/acpd-7-6487-2007.
6. De Leeuw J., Jia H., Yang L., Liu X., Schmidt K., Skidmore A.K. Comparing accuracy assessments to infer superiority of image classification methods. International Journal of Remote Sensing 2006, 27(1):223-232. 10.1080/01431160500275762.
7. Donkelaar A.V., Martin R.V., Brauer M., Kahn R., Levy R., Verduzco C., Villeneuve P.J. Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: Development and application. Environmental Health Perspectives 2010, 118:847-855. 10.1289/ehp.0901623.
8. Donkelaar A.V., Martin R.V., Park R.J. Estimating ground-level PM2.5 using aerosol optical depth determined from satellite remote sensing. Journal of Geophysical Research 2006, D21. 10.1029/2005JD006996.
9. Engel-Cox J.A., Holloman C.H., Coutant B.W., Hoff R.M. Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality. Atmospheric Environment 2004, 38:2495-2509. 10.1016/j.atmosenv.2004.01.039.
10. Fotheringham A.S., Charlton M., Brunsdon C. The geography of parameter space: An investigation of spatial non-stationarity. International Journal of Geographical Information Systems 1996, 10:605-627. 10.1080/02693799608902100.
11. Guo J.P., Zhang X.Y., Che H.Z., Gong S.L., An X.Q., Cao C.X., Guang J., Zhang H., Wang Y.Q., Zhang X.C., Xue M., Li X.W. Correlation between PM concentrations and aerosol optical depth in eastern China. Atmospheric Environvionment 2009, 43:5876-5886. 10.1016/j.atmosenv.2009.08.026.
12. Gupta P., Christopher S.A. Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: 2. A neural network approach. Journal of Geophysical Research 2009, D20205. 10.1029/2008JD011497.
13. Gupta P., Christopher S.A., Wang J., Gehrig R., Lee Y., Kumar N. Satellite remote sensing of particulate matter and air quality assessment over global cities. Atmospheric Environvionment 2006, 40:5880-5892. 10.1016/j.atmosenv.2006.03.016.
14. Hu X.F., Waller L.A., Al-Hamdan M.Z., Crosson W.L., Estes M.G., Estes S.M., Quattrochi D.A., Sarnat J.A., Liu Y. Estimating ground-level PM2.5 concentrations in the southeastern U.S. using geographically weighted regression. Environmental Research 2013, 121:1-10.
15. Jia H.F., Liu X.H. Environmental Remote Sensing Principles and Applications 2006, Tsinghua University Press, Beijing, (in Chinese).
16. Kaufman Y.J., Tanre D., Boucher O. A satellite view of aerosols in the climate system. Nature 2002, 419:215-223. 10.1038/nature01091.
17. Koelemeijer R.B.A., Homan C.D., Matthijsen J. Comparison of spatial and temporal variations of aerosol optical thickness and particulate matter over Europe. Atmospheric Environment 2006, 40:5304-5315. 10.1016/j.atmosenv.2006.04.044.
18. Kumar N., Chu A., Foster A. An empirical relationship between PM2.5 and aerosol optical depth in Delhi Metropolitan. Atmospheric Environment 2007, 41:4492-4503. 10.1016/j.atmosenv.2007.01.046.
19. Lee H.J., Liu Y., Coull B.A., Schwartz J., Koutrakis P. A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations. Atmospheric Chemistry and Physics 2011, 11:7991-8002.
20. Levy R.C., Remer L.A., Kleldman R.G., Mattoo S., Ichoku C., Kahn R., Eck T.F. Global evaluation of the collection 5 MODIS dark-target aerosol products over land. Atmospheric Chemistry and Physics 2010, 10:14815-14873. 10.5194/acp-10-10399-2010.
21. Levy R.C., Remer L.A., Mattoo S., Vermote E.F., Kaufman Y.J. Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of moderate resolution imaging spectroradiometer spectral reflectance. Journal of Geophysical Research 2007, 112:D13. 10.1029/2006JD007811.
22. Li C.C., Mao J.T., Liu Q.H. Remote sensing of high spatial resolution aerosol optical depth with MODIS data over Hong Kong. Chinese Journal of Atmospheric Sciences 2005, 29:335-342. (in Chinese).
23. Lim J.M., Jeong J.H., Lee J.H., Moon J.H., Chung Y.S., Kim K.H. The analysis of PM2.5 and associated elements and their indoor/outdoor pollution status in an urban area. Indoor Air 2011, 21:145-155. 10.1111/j.1600-0668.2010.00691.x.
24. Liu Y., Franklin M., Kahn R., Koutrakis P. Using aerosol optical thickness to predict ground-level PM2.5 concentrations in the St. Louis area: A comparison between MISR and MODIS. Remote Sensing of Environment 2007, 107:33-44.
25. Liu Y., Paciorek C., Koutrakis P. Estimating regional spatial and temporal variability of PM2.5 concentrations using satellite data, meteorology, and land use information. Environmental Health Perspectives 2009, 117:886-892. 10.1289/ehp.0800123.
26. Liu Y., Sarnat J.A., Kilaru V., Jacob D.J., Koutrakis P. Estimating ground-level PM2.5 in the eastern United States using satellite remote sensing. Environmental Science & Technology 2005, 39:3269-3278. 10.1021/es049352m.
27. Paciorek C.J., Liu Y., Moreno-Macias H., Kondragunta S. Spatiotemporal associations between GOES aerosol optical depth retrievals and ground-level PM2.5. Environmental Science & Technology 2008, 42:5800-5806. 10.1021/es703181j.
28. Pateraki S., Asimakopoulos D.N., Flocas H.A., Maggos T., Vasilakos C. The role of meteorology on different sized aerosol fractions (PM10, PM2.5, PM2.5-10). Science of the Total Environment 2012, 419:124-135.
29. Pelletier B., Santer R., Vidot J. Retrieving of particulate matter from optical measurements: A semiparametric approach. Journal of Geophysical Research 2007, 112:D6. 10.1029/2005JD006737.
30. Remer L.A., Kaufman Y.J., Tanre D., Mattoo S., Chu D.A., Martins J.V., Li R.R., Ichoku C., Levy R.C., Kleidman R.G., Eck T.F., Vermote E., Holben B.N. The MODIS aerosol algorithm, products, and validation. Journal of the Atmospheric Sciences 2005, 62:947-973. 10.1175/JAS3385.1.
31. Schaap M., Apituley A., Timmermans R.M.A., Koelemeijer R.B.A., Leeuw G.D. Exploring the relation between aerosol optical depth and PM2.5 at Cabauw, the Netherlands. Atmospheric Chemistry and Physics 2009, 9:909-925. 10.5194/acpd-8-17939-2008.
32. See S.W., Balasubramanian R. Chemical characteristics of fine particles emitted from different gas cooking methods. Atmospheric Environment 2008, 42:8852-8862. 10.1016/j.atmosenv.2008.09.011.
33. Tian J., Chen D.M. A semi-empirical model for predicting hourly ground-level fine particulate matter (PM2.5) concentration in southern Ontario from satellite remote sensing and ground-based meteorological measurements. Remote Sensing of Environment 2010, 114:221-229.
34. Vidot J., Santer R., Ramon D. Atmospheric particulate matter (PM) estimation from SeaWiFS imagery. Remote Sensing of Environment 2007, 111:1-10. 10.1016/j.rse.2007.03.009.
35. Wang Z.F., Chen L.F., Tao J.H., Zhang Y., Su L. Satellite-based estimation of regional particulate matter (PM) in Beijing using vertical-and-RH correcting method. Remote Sensing of Environment 2010, 114:50-63. 10.1016/j.rse.2009.08.009.
36. Wang J., Christopher S.A. Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies. Geophysical Research Letters 2003, 30:2095.
37. Wu Y., Guo J., Zhang X., Tian X., Zhang J., Wang Y., Duan J., Li X. Synergy of satellite and ground based observations in estimation of particulate matter in eastern China. Science of the Total Environment 2012, 433:20-30. 10.1016/j.scitotenv.2012.06.033.
38. Xiong X.X., Sun J.Q., Wu A.S., Chiang K.F., Esposito J., Barnes W. Terra and Aqua MODIS calibration algorithms and uncertainty analysis. Sensors, systems, and next-generation satellites IX. Proceedings of SPIE 2005, 5978. 10.1117/12.627631.
39. Yap X.Q., Hashim M. A robust calibration approach for PM10 prediction from MODIS aerosol optical depth. Atmospheric Chemistry and Physics 2013, 13:3517-3526. 10.5194/acp-13-3517-2013.
40. Zhao N., Yang Y.H., Zhou X.Y. Application of geographically weighted regression in estimating the effect of climate and site conditions on vegetation distribution in Haihe Catchment, China. Plant Ecology 2010, 209:349-359. 10.1007/s11258-010-9769-y.
41. Zheng Z., Chen L., Zheng J., Zhong L., Liu Q. Application of retrieved high-resolution AOD in regional PM monitoring in the Pearl River Delta and Hong Kong region. Acta Scientiae Circumstantiae 2011, 31:1154-1161. (in Chinese).