Synergy of satellite and ground based observations in estimation of particulate matter in eastern China

Science of the Total Environment

Volumn 433, Issue , 2012, Pages 20-30

  Wu, Yerong ^a   Guo, Jianping ^b   Zhang, Xiaoye ^b   Tian, Xin ^c   Zhang, Jiahua ^b   Wang, Yaqiang ^b   Duan, Jing ^b   Li, Xiaowen ^a  

^a BEIJING NORMAL UNIVERSITY   (China)

^b STATE KEY LABORATORY OF SEVERE WEATHER   (China)

^c RESEARCH INSTITUTE OF FORESTRY   (China)

Author keywords

AOD; BP ANN; PBLH; PM; Synergy

Indexed keywords

AEROSOL OPTICAL DEPTHS; AIR POLLUTION MONITORING; ANN ALGORITHM; AOD; BACK PROPAGATION ARTIFICIAL NEURAL NETWORK (BPANN); BAYESIAN REGULARIZATION; BP ANN; EASTERN CHINA; GROUND OBSERVATIONS; GROUND-BASED OBSERVATIONS; NANNING; PARTICULATE MATTER; PBLH; PLANETARY BOUNDARY LAYERS; R VALUE; SATELLITE SENSORS; SEASONAL SCALE; SEASONAL VARIATION; SPATIAL AVERAGING; SPATIAL SCALE; SPATIO-TEMPORAL SCALE; STRONG CORRELATION; SYNERGY; TEMPORAL AVERAGING;

ATMOSPHERIC AEROSOLS; BACKPROPAGATION ALGORITHMS; NEURAL NETWORKS; PROMETHIUM; SATELLITES;

ESTIMATION;

AEROSOL; ALGORITHM; ARTIFICIAL NEURAL NETWORK; ATMOSPHERIC POLLUTION; BACK PROPAGATION; BAYESIAN ANALYSIS; BOUNDARY LAYER; CONCENTRATION (COMPOSITION); GROUND-BASED MEASUREMENT; OPTICAL DEPTH; PARTICLE SIZE; PARTICULATE MATTER; POLLUTION MONITORING; SATELLITE IMAGERY; SATELLITE SENSOR; SPATIOTEMPORAL ANALYSIS;

ACCURACY; AIR POLLUTION; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; BAYESIAN LEARNING; CHINA; CONCENTRATION (PARAMETERS); CONTROLLED STUDY; PARTICLE SIZE; PARTICULATE MATTER; POLLUTION MONITORING; PRIORITY JOURNAL; PROCESS DEVELOPMENT; REPRODUCIBILITY; SEASONAL VARIATION;

CHINA; HENAN; LUSHAN; TAIWAN; ZHENGZHOU;

EID: 84863219189     PISSN: 00489697     EISSN: 18791026     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2012.06.033     Document Type: Article

References (45)

1. Balls G.R., Palmer-Brown D., Sanders G.E. Investigating microclimatic influences on ozone injury in clover (Trifolium subterraneum) using artificial neural networks. New Phytol 1996, 132:271-280.
2. Chu D.A., Kaufman Y.J., Zibordi G., Chern J.D., Mao J., Li C.C., et al. Global monitoring of air pollution over land from the Earth Observing System-Terra Moderate Resolution Imaging Spectroradiometer (MODIS). J Geophys Res 2003, 108:4661.
3. 10 concentrations. J Environ Prot Ecol 2010, 11:1163-1171.
4. 10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region. Remote Sens Environ 2010, 114:2485-2499.
5. 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. Atmos Environ 2004, 38:2495-2509.
6. Engel-Cox J.A., Hoff R.M., Rogers R., Dimmick F., Rush A.C., Szykman J.J., et al. Integrating lidar and satellite optical depth with ambient monitoring for 3-dimensional particulate characterization. Atmos Environ 2006, 40:8056-8067.
7. Foresee F.D., Hagan M.T. Gauss-Newton approximation to Bayesian learning. Proceeding of the IEEE International Joint Conference on Neural Networks 1997, vol. 3:1930-1935.
8. Gardner M., Dorling S. Artificial neural networks (the multilayer perceptron)-a review of applications in the atmospheric sciences. Atmos Environ 1998, 32:2627-2636.
9. 2 concentrations in urban air in London. Atmos Environ 1999, 33:709-719.
10. Guo J.-P., Zhang X.-Y., Che H.-Z., Gong S.-L., An X., Cao C.-X., et al. Correlation between PM concentrations and aerosol optical depth in eastern China. Atmos Environ 2009, 43:5876-5886.
11. Guo J.P., Zhang X.Y., Cao C.X., Che H.Z., Liu H.L., Gupta P., et al. Monitoring haze episodes over the Yellow Sea by combining multisensor measurements. Int J Remote Sens 2010, 31:4743-4755.
12. Guo J.-P., Zhang X.-Y., Wu Y.-R., Zhaxi Y., Che H.-Z., La B., et al. Spatio-temporal variation trends of satellite-based aerosol optical depth in China during 1980-2008. Atmos Environ 2011, 45:6802-6811.
13. Gupta P. Particulate matter air quality assessment over southeast united states using satellite and ground measurements. The University Of Alabama In Huntsville 2008, 172.
14. Gupta P., Christopher S.A. Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: 2. A neural network approach. J Geophys Res-Atmos 2009, 114.
15. 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. Atmos Environ 2006, 40:5880-5892.
16. Hertz J., Krogh A., Palmer R.G. Introduction to the theory of neural computation 1991, Addison-Wesley Publisher, Redwood City, CA.
17. 2.5 observations through 3D spatial analyses. Atmos Environ 2008, 42:530-543.
18. Ichoku C., Chu D.A., Mattoo S., Kaufman Y.J., Remer L.A., Tanré D., et al. A spatio-temporal approach for global validation and analysis of MODIS aerosol products. Geophys Res Lett 2002, 29:8006.
19. Jiang X., Liu Y., Yu B., Jiang M. Comparison of MISR aerosol optical thickness with AERONET measurements in Beijing metropolitan area. Remote Sens Environ 2007, 107:45-53.
20. Kaufman Y.J., Tanre D., Boucher O. A satellite view of aerosols in the climate system. Nature 2002, 419:215-223.
21. Koelemeijer R.B.A., Homan C.D., Matthijsen J. Comparison of spatial and temporal variations of aerosol optical thickness and particulate matter over Europe. Atmos Environ 2006, 40:5304-5315.
22. Kondragunta S., Lee P., McQueen J., Kittaka C., Prados A., Ciren P., et al. Air quality forecast verification using satellite data. J Appl Meteorol Climatol 2008, 47:425-442.
23. 2.5 and aerosol optical depth in Delhi Metropolitan. Atmos Environ 2007, 41:4492-4503.
24. 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. J Geophys Res 2007, 112:D13211.
25. Li C., Mao J., Lau K.H.A., Chen J.C., Yuan Z., Liu X., et al. Characteristics of distribution and seasonal variation of aerosol optical depth in eastern China with MODIS products. Chin Sci Bull 2003, 48:2488-2495.
26. Li C., Mao J., Lau A., Yuan Z., Wang M., Liu X. Application of MODIS satellite products to the air pollution research in Beijing. Sci China D 2005, 48:209-219.
27. Li L.J., Wang Y., Zhang Q., Yu T., Zhao Y., Jin J. Spatial distribution of aerosol pollution based on MODIS data over Beijing, China. J Environ Sci 2007, 19:955-960.
28. 2.5 in the eastern United States using satellite remote sensing. Environ Sci Technol 2005, 39:3269-3278.
29. 2.5 concentrations in the St. Louis area: a comparison between MISR and MODIS. Remote Sens Environ 2007, 107:33-44.
30. Liu Y., Schichtel B.A., Koutrakis P. Estimating particle sulfate concentrations using MISR retrieved aerosol properties. IEEE J Sel Top Appl Earth Observations Remote Sens 2009, 2:176-184.
31. MacKay D.J.C. Bayesian interpolation. Neural Comput 1992, 4:415-447.
32. Mathur R., Yu S., Kang D., Schere K.L. Assessment of the wintertime performance of developmental particulate matter forecasts with the Eta-Community Multiscale Air Quality modeling system. J Geophys Res 2008, 113.
33. Nagendra S.M.S., Khare M. Artificial neural network based carbon monoxide persistence models for episodic urban air quality management. Environ Monit Assess 2008, 139:247-255.
34. 2.5. Proceedings of Envisat Symposium 2007, 3-27.
35. Pelletier B., Santer R., Vidot J. Retrieving of particulate matter from optical measurements: a semiparametric approach. J Geophys Res 2007, 112.
36. Reich S.L., Gomez D.R., Dawidowski L.E. Artificial neural network for the identification of unknown air pollution sources. Atmos Environ 1999, 33:3045-3052.
37. Remer L.A., Kaufman Y.J., Tanre D., Mattoo S., Chu D.A., Martins J.V., et al. The MODIS aerosol algorithm, products, and validation. J Atmos Sci 2005, 62:947-973.
38. Remer L.A., Kaufman Y., Tanré D., Mattoo S., Chu D., Martins J.V., et al. The MODIS aerosol algorithm, products, and validation 2010.
39. Schaap M., Timmermans R.M.A., Koelemeijer R.B.A., de Leeuw G., Builtjes P.J.H. Evaluation of MODIS aerosol optical thickness over Europe using sun photometer observations. Atmos Environ 2008, 42:2187-2197.
40. Seidel D.J., Ao C.O., Li K. Estimating climatological planetary boundary layer heights from radiosonde observations: comparison of methods and uncertainty analysis. J Geophys Res 2010, 115:D16113.
41. 2 concentrations using artificial neural networks. Energy Sources B-Econ Plann Policy 2006, 1:127-136.
42. 2.5) concentration in southern Ontario from satellite remote sensing and ground-based meteorological measurements. Remote Sens Environ 2010, 114:221-229.
43. 2.5 using aerosol optical depth determined from satellite remote sensing. J Geophys Res 2006, 111:D21201.
44. 2.5 mass: implications for air quality studies. Geophys Res Lett 2003, 30:2095.
45. Zhang X., Wang Y., Zhang X., Guo W., Gong S. Carbonaceous aerosol composition over various regions of China during 2006. J Geophys Res 2008, 113:D14111.