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2016 | 25 | 3 |
Tytuł artykułu

Land use regression modelsusing satellite aerosol optical depth observations and 3D building data from the central cities of Liaoning Province, China

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Słowa kluczowe
Wydawca
-
Rocznik
Tom
25
Numer
3
Opis fizyczny
p.1015-1026,fig.,ref.
Twórcy
autor
  • State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, People’s Republic of China
  • University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
autor
  • State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, People’s Republic of China
autor
  • State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, People’s Republic of China
autor
  • State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, People’s Republic of China
autor
  • State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, People’s Republic of China
autor
  • Department of Land Surveying and Geo-Informatics, the Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
autor
  • State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, People’s Republic of China
autor
  • State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, People’s Republic of China
  • University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
autor
  • State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, People’s Republic of China
  • University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
Bibliografia
  • 1. HOEK G., BEELEN R., DE HOOGH K., VIENNEAU D., GULLIVER J., FISCHER P., BRIGGS D. A review of landuse regression models to assess spatial variation of outdoor air pollution. Atmos Environ, 42, 7561, 2008.
  • 2. AMINI H., TAGHAVI-SHAHRI S.M., HENDERSON S.B., NADDAFI K., NABIZADEH R., YUNESIAN M. Land use regression models to estimate the annual and seasonal spatial variability of sulfur dioxide and particulate matter in Tehran, Iran. Sci Total Environ, 488-489, 343, 2014.
  • 3. CHUDNOVSKY A.A., KOUTRAKIS P., KLOOG I., MELLY S., NORDIO F., LYAPUSTIN A., WANG Y., SCHWARTZ J. Fine particulate matter predictions using high resolution Aerosol Optical Depth (AOD) retrievals. Atmos Environ, 89, 189, 2014.
  • 4. KIM Y., GULDMANN J.-M. Land-use regression panel models of NO2 concentrations in Seoul, Korea. Atmos Environ, 107, 364, 2015.
  • 5. BERTAZZON S., JOHNSON M., ECCLES K., KAPLAN G. G. Accounting for spatial effects in land use regression for urban air pollution modeling. Spatial and Spatio-temporal Epidemiology, 14-15, 9, 2015.
  • 6. LI X., LIU W., CHEN Z., ZENG G.M., HU C.M., LE N.T., LIANG J., HUANG G.H., GAO Z.H., LI Z., YAN W.F., HE X.X., LAI M.Y., HE Y.B. The application of semicircularbuffer-based land use regression models incorporating wind direction in predicting quarterly NO2 and PM10 concentrations. Atmos Environ, 103, 18, 2015.
  • 7. CHUDNOVSKY A.A., KOSTINSKI A., LYAPUSTIN A., KOUTRAKIS P. Spatial scales of pollution from variable resolution satellite imaging. Environ Pollut, 172, 131, 2013.
  • 8. LI J., CARLSON B.E., LACIS A.A. How well do satellite AOD observations represent the spatial and temporal variability of PM2.5 concentration for the United States? Atmos Environ, 102, 260, 2015.
  • 9. LIN C.Q., LI Y., YUAN Z.B., LAU A.K.H., LI C.C., FUNG J.C.H. Using satellite remote sensing data to estimate the high-resolution distribution of ground-level PM2.5. Remote Sens Environ, 156, 117, 2015.
  • 10. HAN Y., WU Y.H., WANG T.J., ZHUANG B.L., LI S., ZHAO K. Impacts of elevated-aerosol-layer and aerosol type on the correlation of AOD and particulate matter with ground-based and satellite measurements in Nanjing, southeast China. Sci Total Environ, 532, 195, 2015.
  • 11. YOU W., ZANG Z.L., ZHANG L.F., LI Z.J., CHEN D., ZHANG G. Estimating ground-level PM10 concentration in northwestern China using geographically weighted regression based on satellite AOD combined with CALIPSO and MODIS fire count. Remote Sens Environ, 168, 276, 2015.
  • 12. WANG J., CHRISTOPHER S.A. Intercomparison between satellite - derived aerosol optical thickness and PM2.5 mass: implications for air quality studies. Geophys Res Lett, 30, 2095, 2003.
  • 13. XIN J.Y., ZHANG Q., WANG L.L., GONG C.S., WANG Y.S., LIU Z.R., GAO W.K. The empirical relationship between the PM2.5 concentration and aerosol optical depth over the background of North China from 2009 to 2011. Atmos Res, 138, 179, 2014.
  • 14. FARRELL W.J., DEVILLE CAVELLIN L., WEICHENTHAL S., GOLDBERG M., HATZOPOULOU M. Capturing the urban canyon effect on particle number concentrations across a large road network using spatial analysis tools. Building and Environment, 92, 328, 2015.
  • 15. RICHMOND-BRYANT J., REFF A. Air pollution retention within a complex of urban street canyons: A two-city comparison. Atmos Environ, 49, 24, 2012.
  • 16. KWAK K.H., BAIK J.J., RYU Y.H., LEE S.H. Urban air quality simulation in a high-rise building area using a CFD model coupled with mesoscale meteorological and chemistry-transport models. Atmos Environ, 100, 167, 2015.
  • 17. HANG J., LI Y.G., SANDBERG M., BUCCOLIERI R., DI SABATINO S. The infl uence of building height variability on pollutant dispersion and pedestrian ventilation in idealized high-rise urban areas. Building and Environment, 56, 346, 2012.
  • 18. EEFTENS M., BEEKHUIZEN J., BEELEN R., WANG M., VERMEULEN R., BRUNEKREEF B., HUSS A., HOEK G. Quantifying urban street confi guration for improvements in air pollution models. Atmos Environ, 72, 1, 2013.
  • 19. SU J.G., BRAUER M., BUZZELLI M. Estimating urban morphometry at the neighborhood scale for improvement in modeling long-term average air pollution concentrations. Atmos Environ, 42, 7884, 2008.
  • 20. KR GER E.L., MINELLA F.O., RASIA F. Impact of urban geometry on outdoor thermal comfort and air quality from fi eld measurements in Curitiba, Brazil. Building and Environment, 46, 621, 2011.
  • 21. KONG S.F., DING X., BAI Z.P., HAN B., CHEN L., SHI J.W., LI Z.Y. A seasonal study of polycyclic aromatic hydrocarbons in PM2.5 and PM2.5–10 in five typical cities of Liaoning Province, China. J Hazard Mater, 183, 70, 2010.
  • 22. CHU D.A., FERRARE R., SZYKMAN J., LEWIS J., SCARINO A., HAINS J., BURTON S., CHEN G., TSAI T., HOSTETLER C., HAIR J., HOLBEN B., CRAWFORD J. Regional characteristics of the relationship between columnar AOD and surface PM2.5: Application of lidar aerosol extinction profiles over Baltimore-Washington Corridor during DISCOVER-AQ. Atmos Environ, 101, 338, 2015.
  • 23. LEBOEUF A., BEAUDOIN A., FOURNIER R.A., GUINDON L., LUTHER J.E., LAMBERT M.C. A shadow fraction method for mapping biomass of northern boreal black spruce forests using QuickBird imagery. Remote Sens Environ, 110, 488, 2007.
  • 24. PAN X.Z., ZHAO Q.G., CHEN J., LIANG Y., SUN B. Analyzing the variation of building density using high spatial resolution satellite images: the example of Shanghai City. Sensors, 8, 2541, 2008.
  • 25. TUCKER C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ, 8, 127, 1979.
  • 26. TUCKER C.J., SELLERS P.J. Satellite remote sensing of primary production. Int J Remote Sens, 7, 1395, 1986.
  • 27. DADVAND P., RIVAS I., BASAGA A.X., ALVAREZPEDREROL M., SU J., DE CASTRO PASCUAL M., AMATO F., JERRET M., QUEROL X., SUNYER J., NIEUWENHUIJSEN M.J. The association between greenness and traffic-related air pollution at schools. Sci Total Environ, 523, 59, 2015.
  • 28. XU L.Y., XIE X.D., LI S. Correlation analysis of the urban heat island effect and the spatial and temporal distribution of atmospheric particulates using TM images in Beijing. Environ Pollut, 178, 102, 2013.
  • 29. SU J.G., JERRETT M., BECKERMAN B. A distance-decay variable selection strategy for land use regression modeling of ambient air pollution exposures. Sci Total Environ, 407, 3890, 2009.
  • 30. PICARD R.R., COOK R.D. Cross-validation of regression models. Journal of the American Statistical Association, 79, 575, 1984.
  • 31. KUTNER M.H., NACHTSHEIM C., NETER J. Applied linear regression models: McGraw-Hill/Irwin, 2004.
  • 32. O’BRIEN R.M. A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41, 673, 2007.
  • 33. MATEOS D., CACHORRO V.E., TOLEDANO C., BURGOS M.A., BENNOUNA Y., TORRES B., FUERTES D., GONZ LEZ R., GUIRADO C., CALLE A. Columnar and surface aerosol load over the Iberian Peninsula establishing annual cycles, trends, and relationships in fi ve geographical sectors. Sci Total Environ, 518, 378, 2015.
  • 34. BRAUER M., HOEK G., VAN VLIET P., MELIEFSTE K., FISCHER P., GEHRING U., HEINRICH J., CYRYS J., BELLANDER T., LEWNE M., BRUNEKREEF B. Estimating long-term average particulate air pollution concentrations: application of traffic indicators and geographic information systems. Epidemiology, 14, 228, 2003
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.agro-02425289-8195-4fb7-bd5e-fb4163aea05c
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