Review and Assessment of Air Pollution Modeling Methodologies - Focused on Mobile Sources -
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초록
Since negative health impacts related to urban air quality were generally acknowledged, diverse pollution modeling techniques have been developed for the estimation of temporal and spatial pollution hot spots. This paper reviews the three categories of air pollution modeling studies, including conventional mathematical dispersion models, recently developed land use regression (LUR) models, and other statistical models with the consideration of time‐series autocorrelation. The conventional mathematical modeling approaches using emission inventory and pollutant dispersion algorithms have been widely developed, but these methods have limitations in implementing because of high computational burden and large data demand. With the advancement of geographic information techniques, an alternative approach, LUR model, has been developed and proved for applying high-resolution pollution mapping. Besides these two approaches, other statistical studies considering time-series data have been developed. The contents, strength, and weakness of these three pollution modeling studies will be reviewed and then future research agenda will be discussed.
Abstract
Since negative health impacts related to urban air quality were generally acknowledged, diverse pollution modeling techniques have been developed for the estimation of temporal and spatial pollution hot spots. This paper reviews the three categories of air pollution modeling studies, including conventional mathematical dispersion models, recently developed land use regression (LUR) models, and other statistical models with the consideration of time‐series autocorrelation. The conventional mathematical modeling approaches using emission inventory and pollutant dispersion algorithms have been widely developed, but these methods have limitations in implementing because of high computational burden and large data demand. With the advancement of geographic information techniques, an alternative approach, LUR model, has been developed and proved for applying high-resolution pollution mapping. Besides these two approaches, other statistical studies considering time-series data have been developed. The contents, strength, and weakness of these three pollution modeling studies will be reviewed and then future research agenda will be discussed.
참고문헌 (49)
- Aguilera, I., "Estimation of outdoor NOx, NO2, and BTEX exposure in a cohort of pregnant women using land use regression modeling", Environmental Science & Technology, 42(3), pp.815~821 (2008)
- Beelen, R., "Estimated long-term outdoor air pollution concentrations in a cohort study", Atmospheric Environment, 41(7), pp.1343~1358 (2007)
- Beelen, R., "Mapping of background air pollution at a fine spatial scale across the european union", Science of the Total Environment, 407(6), pp.1852~1867 (2009)
- Berkowicz, R., "Traffic pollution modelling and emission data", Environmental Modelling and Software, 21(4), pp.454~460 (2006)
- Berkowicz, R., "Street scale models, in Urban air pollution- European aspects", pp.223~251 (1998), Kluwer Academic Publishers
- Berkowicz, R., "OSPM-A parameterised street pollution model", Environmental Monitoring and Assessment, 65(1), pp.323~331 (2000)
- Briggs, D., "The role of GIS: Coping with space(and time) in air pollution exposure assessment", Journal of Toxicology & Environmental Health: Part A, 68(13), pp.1243~1261 (2005)
- Briggs, D., "The use of GIS to evaluate trafficrelated pollution", Occupational and Environmental Medicine, 64(1), pp.1~2 (2007)
- Briggs, D., "Mapping urban air pollution using GIS: A regression-based approach", International Journal of Geographical Information Science, 11(7), pp.699~718 (1997)
- Briggs, D., "A regression‐based method for mapping traffic-related air pollution: Application and testing in four contrasting urban environments", The Science of the Total Environment, 253(1), pp.151~167 (2000)
- Cameron, E., "ArcGIS 9" (2005), ESRI
- Chock, D. P., "Timeseries analysis of riverside, California air quality data", Atmospheric Environment, 9, pp.978~989 (1975)
- Connell, D. P., "The Steubenville comprehensive air monitoring program (SCAMP): Associations among fine particulate matter, copollutants, and meteorological conditions", Journal of the Air & Waste Management Association, 55(4), pp.1064~1074 (2005)
- Coyle, M., "Quantifying the spatial distribution of surface ozone concentration in the UK", Atmospheric Environment, 36(6), pp.1013~1024 (2002)
- Elbir, T., "A GIS based decision support system for estimation, visualization and analysis of air pollution for large turkish cities", Atmospheric Environment, 38(27), pp.4509~4517 (2004)
- Elbir, T., "Estimation of emission strengths of primary air pollutants in the city of Izmir, Turkey", Atmospheric Environment, 38(13), pp.1851~1857 (2004)
- Environmental Systems Research Institute., "ArcGIS 9- using ArcGIS desktop" (2006), ESRI
- Gilbert, N. L., "Assessing spatial variability of ambient nitrogen dioxide in montreal, canada, with a land-use regression model", Journal of the Air & Waste Management Association, 55(8), pp.1059~1063 (2005)
- Gregg, J. W., "Urbanization effects on tree growth in the vicinity of New York city", Nature, 424(6945), pp.183~187 (2003)
- Gualtieri, G., "Predicting urban traffic air pollution: A gis framework", Transportation Research Part D: Transport and Environment, 3(5), pp.329~336 (1998)
- Guldmann, J., "Modeling air quality in urban areas: A cell-based statistical approach", Geographical Analysis, 33(2), pp.156~180 (2001)
- Henderson, S. B., "Application of land use regression to estimate long-term concentrations of traffic-related nitrogen oxides and fine particulate matter", Environmental Science & Technology, 41(7), pp.2422~2428 (2007)
- Hochadel, M., "Predicting longterm average concentrations of traffic-related air pollutants using GIS-based information", Atmospheric Environment, 40(3), pp.542~553 (2006)
- Hoek, G., "A review of land-use regression models to assess spatial variation of outdoor air pollution", Atmospheric Environment, 42(33), pp.7561~7578 (2008)
- Jensen, S. S., "A Danish decision‐support GIS tool for management of urban air quality and human exposures", Transportation Research Part D: Transport and Environment, 6(4), pp.229~241 (2001)
- Jo, W., "Characteristics of roadside air pollution in Korean metropolitan city (Daegu) over last 5 to 6 years: Temporal variations, standard exceedances, and dependence on meteorological conditions", Chemosphere, 59(11), pp.1557~1573 (2005)
- Kahyaoğlu‐Koračin, J., "Application of a scenario-based modeling system to evaluate the air quality impacts of future growth", Atmospheric Environment, 43(5), pp.1021~1028 (2009)
- Kanaroglou, P. S., "Establishing an air pollution monitoring network for intra-urban population exposure assessment: A location-allocation approach", Atmospheric Environment, 39(13), pp.2399~2409 (2005)
- Karppinen, A., "A modelling system for predicting urban air pollution: Comparison of model predictions with the data of an urban measurement network in Helsinki", Atmospheric Environment, 34(22), pp.3735~3743 (2000)
- Karppinen, A., "A modelling system for predicting urban air pollution: Model description and applications in the Helsinki metropolitan area", Atmospheric Environment, 34(22), pp.3723~3733 (2000)
- Kukkonen, J., "Evaluation of the CAR-FMI model against measurements near a major road", Atmospheric Environment, 35(5), pp.949~960 (2001)
- Lin, M., "The application of GIS to air quality analysis in Taichung city, Taiwan, ROC", Environmental Modelling and Software, 17(1), pp.11~19 (2002)
- Liu, P. G., "Forecasting peak daily ozone levels-I. A regression with time series errors model having a principal component trigger to fit 1991 ozone levels", Journal of the Air & Waste Management Association, 52(9), pp.1064~1074 (2002)
- Madsen, C., "Modeling the intraurban variability of outdoor traffic pollution in Oslo, Norway-A GA 2 LEN project", Atmospheric Environment, 41(35), pp.7500~7511 (2007)
- May, A. D., "The development of the leeds quantifiable city model, in Evaluation of the built environmentfor sustainability (1st ed.)", pp.568~ (1997), E. & F.N. Spon.
- Millionis, A. E., "Regression and stochastic models for air pollution-I. review, comments and suggestions", Atmospheric Environment, 28(17), pp.2801~2810 (1994)
- Namdeo, A., "Development and evaluation of SBLINE, a suite of models for the prediction of pollution concentrations from vehicles in urban areas", Science of the Total Environment, 180, pp.311~320 (1996)
- Namdeo, A., "TEMMS: An integrated package for modelling and mapping urban traffic emissions and air quality", Environmental Modelling and Software, 17(2), pp.177~188 (2002)
- Potoglou, D., "Carbon monoxide emissions from passenger vehicles: Predictive mapping with an application to Hamilton, Canada", Transportation Research Part D, 10(2), pp.97~109 (2005)
- Ross, Z., "Nitrogen dioxide prediction in southern California using land use regression modeling: Potential for environmental health analyses", Journal of Exposure Science and Environmental Epidemiology, 16(2), pp.106~114 (2006)
- Ross, Z., "A land use regression for predicting fine particulate matter concentrations in the New York city region", Atmospheric Environment, 41(11), pp.2255~2269 (2007)
- Sahsuvaroglu, T., "A land use regression model for predicting ambient concentrations of nitrogen dioxide in Hamilton, Ontario, Canada", Journal of the Air & Waste Management Association, 56(8), pp.1059~1069 (2006)
- Schatzmann, M., "Wind tunnel experiments, in Urban air pollution-European aspects", pp.261~278 (1998), Kluwer Academic Publishers
- Seinfeld, J. H., "Urban air pollution: State of the science", Science, 243(4892), pp.745~752 (1989)
- Shen, K., "Airshed-based statistical modeling of the spatial distribution of air pollution: The case of sulfur dioxide", 박사, pp.2004
- Shi, J. P., "Regression modelling of hourly NOx and NO2 concentrations in urban air in London", Atmospheric Environment, 31(24), pp.4081~4094 (1997)
- Smith, L., "Use of GIS and ancillary variables to predict volatile organic compound and nitrogen dioxide levels at unmonitored locations", Atmospheric Environment, 40(20), pp.3773~3787 (2006)
- Xia, L., "Modelling of traffic flow and air pollution emission with application to Hong Kong island", Environmental-Modelling and Software, 20(9), pp.1175~1188 (2005)
- Yang, J., "Trends and variability of ground-level O3 in Connecticut over the period 1981-1997", Journal of the Air & Waste Management Association, 52, pp.1354~1361 (2002)