مدل‌سازی پراکنش ذرات معلق هوای شهر اصفهان با بهره‌گیری از روش‌های IDW و Cokriging
محورهای موضوعی :
آلودگی هوا
سحر حیدری اصل
1
,
حسین مرادی
2
,
محسن سلیمانی
3
1 - کارشناسی ارشد علوم و مهندسی محیط زیست، گروه محیط زیست، دانشگاه صنعتی اصفهان، اصفهان، ایران. * (مسوول مکاتبات)
2 - استادیار علوم و مهندسی محیط زیست، گروه محیط زیست، دانشگاه صنعتی اصفهان، اصفهان، ایران.
3 - دانشیار علوم و مهندسی محیط زیست، گروه محیط زیست، دانشگاه صنعتی اصفهان، اصفهان، ایران.
تاریخ دریافت : 1398/10/23
تاریخ پذیرش : 1399/05/14
تاریخ انتشار : 1400/06/01
کلید واژه:
ذرات معلق,
درون‌یابی,
Cokriging,
IDW,
پهنه‌بندی,
چکیده مقاله :
زمینه و هدف: شهر اصفهان به دلیل شرایط جغرافیایی خاص، توپوگرافی و ازدیاد مواد آلاینده از آلوده‌ترین شهرهای ایران محسوب می‌شود. صنایع، ترافیک، آلاینده‌های خانگی و تجاری از منابع عمده‌ی آلاینده‌ی هوای شهر اصفهان به شمار می‌رود. از روش‌های رایج برای پیش‌بینی و برآورد آلودگی هوا روش‌های درون‌یابی است. هدف از انجام این مطالعه، بررسی الگوهای پراکنش و مدل‌سازی ذرات‌معلق PM2.5 و PM10 هوای شهر اصفهان با استفاده از روش‌های درون یابی IDW و Cokriging است.
روش بررسی: در راستای این پژوهش، غلظت آلاینده‌های PM2.5 و PM10 در فصول زمستان و تابستان سال های 1396و1397 در 137 نقطه از محدوده‌ی شهری به صورت مسیری خطی و به‌وسیله‌ی دستگاه پرتابل اندازه‌گیری ذرات معلق آلودگی هوا (مدل CEM) اندازه‌گیری شد. نقشه‌های پهنه‌بندی برای هر آلاینده در دو فصل سرد و گرم در محیط Arc GIS 10.6 تهیه شد. به‌منظور فرآیند صحت‌سنجی 30% از داده‌ها به صورت تصادفی کنار گذاشته شد. هم‌چنین مقادیر RMSE در هر دو روش درون‌یابی مذکور موردمقایسه قرار گرفت.
یافته‌ها: نتایج به‌دست‌آمده در مورد توزیع آلاینده‌ها با منابع انتشار مهم ازجمله مناطق با ترافیک بالا و بعضی از مناطق نزدیک به مسیر رودخانه‌ی زاینده رود مطابقت داشت. روش Cokriging از نظر مقادیر RMSE کم‌تر از روش IDW عملکرد بهتری داشت اگرچه در فرآیند صحت‌سنجی، بین برازش روش های IDW و Cokriging اختلاف چندانی مشاهده نشد.
بحث و نتیجه‌گیری: در نقشه‌های پهنه بندی، نقاط داغ آلودگی (حداکثرغلظت) در مناطق مرکزی محدوده مطالعاتی مشاهده شد که سهم عمده ای از آن به تردد بسیار وسایل نقلیه در سطح شهر اختصاص دارد.
چکیده انگلیسی:
Background and Objective: Isfahan is one of the most contaminated cities in Iran due to its special geographical conditions, topography and proliferation of pollutants. Industries, traffic, domestic and commercial pollutants are considered the main sources of air pollutants in Isfahan. The methods used to predict and estimate air pollution are methods interpolation. The aim of this study is to investigate the scattering patterns and modeling of particular matter PM2.5 and PM10 in the city of Isfahan using interpolation IDW and Cokriging methods.
Material and Methodology: in this study, the concentration of PM2.5 and PM10 pollutants in winter and summer of 2018 were measured at 137 points of urban area and in linear path by portable device measurement of air pollution (CEM model). Zoning maps for each pollutant in the cold and hot season were in Arc GIS 10.6 environment. In order to verify the accuracy of 30% of the data, the RMSE in both methods was compared.
Findings: the result of pollutants distribution with important emission sources, such as high traffic areas and close areas were consistent with the zayanderood river route. Cokriging method has better performance than IDW method in values of RMSE, although in the validation process, there was little difference between fitting the IDW and Cokriging methods.
Discussion and Conclusion: in the zoning maps, hot spots of pollution (maximum concentration) were observed in central regions of the study area, which is a major contribution to most of the vehicles around the city.
منابع و مأخذ:
Jerrett, M., Arain, A., Kanaroglou, P., Beckerman, B., Potoglou, D., Sahsuvaroglu, T., Morrison, J., Giovis, C., 2005. A review and evaluation of intraurban air pollution exposure models. Journal of Exposure Science and Environmental Epidemiology, Vol. 15, pp. 185.
Wang, L.K., Pereira, N.C., Hung, Y.T. eds., 2004. Air pollution control engineering. Totowa, NJ: Humana press, London, Vol. 1, pp. 501.
Akita, Y., Baldasano, J. M., Beelen, R., Cirach, M., De Hoogh, K., Hoek, G., De Nazelle, A., 2014. Large scale air pollution estimation method combining land use regression and chemical transport modeling in a geostatistical framework. Environmental science & technology, Vol. 48, pp. 4452-4459.
Gupta, P., Christopher, S. A., 2008. An evaluation of Terra-MODIS sampling for monthly and annual particulate matter air quality assessment over the Southeastern United States. Atmospheric Environment, Vol. 26, pp. 6465-6471.
Goodchild, M. F., 1993. The state of GIS for environmental problem-solving. Environmental modeling with GIS, Vol. 2. 8-15.
Borge, R., Narros, A., Artinano, B., Yague, C., Gómez-Moreno, F. J., de la Paz, D., Quaassdorff, C., 2016. Assessment of microscale spatio-temporal variation of air pollution at an urban hotspot in Madrid (Spain) through an extensive field campaign. Atmospheric environment, Vol. 140, pp. 432-445.
Yuan, T. H., Shie, R. H., Chin, Y. Y., Chan, C.C., 2015. Assessment of the levels of urinary 1-hydroxypyrene and air polycyclic aromatic hydrocarbon in PM2.5 for adult exposure to the petrochemical complex emissions. Environmental research, Vol. 136, pp. 219-226.
Shad, R., Ashoori, H., Afshari, N., 2008. Evaluation of optimum methods for predicting pollution concentration in GIS Environment. Remote Sensing and Spatial Information Sciences, Vol. 1, pp. 33-49.
Akbari, A., Fakheri, M., Efatpoor, G., Akbari, Z., 2015. Monthly zoning of air pollution and its relationship with climate factors (Case study: Mashhad). Journal of Natural Environment, Vol. 4, pp. 533-547. (In Persian)
Esmailnejad, M., Eskandari, M., Barzman, S., 2015. Evaluation and Zoning of Tabriz Metropolitan Air Pollution. Regional Planning Quarterly, Vol. 19, pp. 173-186. (In Persian)
Hadipoor, M., Poorebrahim, Sh., 2012. Residential areas in urban transportation planning using GIS and mathematical modeling of air pollution. Understanding the environment, Vol. 59, pp. 135-148.
Shi, X., 2010. Selection of bandwidth type and adjustment side in kernel density estimation over inhomogeneous backgrounds. International Journal of Geographical Information Science, Vol. 24, pp. 643-660.
Salehi, B. Isfahan air pollution zoning. MSc in Environmental Pollution, Department of Environment, Faculty of Natural Resources, Isfahan University of Technology, Iran, 2011; pp. 100. (In Persian)
Garavandi, S., Zalghi, A., Goodarzi, G., Mohammadi, M., Yari, A., Noorzadeh, H.M., 2015. Exposure to particulate matter less than 10 microns and its effect on the incidence of respiratory and cardiovascular diseases in Isfahan. Journal of Health System Research, Vol. 11, pp.730-725. (In Persian)
Noroozi, S., Khademi, H., 2015. Spatial and temporal variations of dust deposition rate in Isfahan city and its relation to some climatic parameters. Journal of Agricultural Science and Technology, Water and Soil Science, Vol. 72, pp.149-161. (In Persian)
Mohammadi, J., Kanaani, M., 2015. Isfahan Metropolitan Strategic Planning in the Framework of Green City Approach with Emphasis on Air Component. Geographical Space Scientific Quarterly, Vol. 58, pp. 149-168. (In Persian)
Sheikhbeiglo, R., Mohammadi, J., 2010. Analysis of Climatic Elements of Wind and Rainfall with Emphasis on Urban Design Case Study of Isfahan City. Journal of Geography and Environmental Planning, Vol. 3, pp. 61-82. (In Persian)
Jha, D. K., Sabesan, M., Das, A., Vinithkumar, N. V., Kirubagaran, R., 2011. Evaluation of Interpolation Technique for Air Quality Parameters in Port Blair, India. Universal journal of environmental research & technology, Vol. 1, pp 2-15.
Willmott, C. J., Matsuura, K., 1995. Smart interpolation of annually averaged air temperature in the United States. Journal of Applied Meteorology, Vol. 34, pp. 2577-2586.
Akhavan, R., Khorramabadi, M. K., Soosani, J., 2012. Application of Kriging and IDW methods in mapping of crown cover and density of coppice oak forests (case study: Kakareza region, Khorramabad). Iranian Journal of Forest, Vol. 3, pp. 305-316. (In Persian)
Jamei, M. Evaluation of introspection methods in regional estimation of reference evaporation and transference and comparison with the available results from satellite images in the central and northern plains of Khuzestan. MSc in Agricultural Meteorology, Islamic Azad University. Tehran Science and Research Branch, Iran, 2009; pp. 102. (In Persian)
Tolosana-Delgado, R., Egozcue, J. J., Sachez-Arcilla, A., Gomez, J., 2011. Wave height data assimilation using non-stationary kriging. Computers & geosciences, Vol. 37, pp. 363-370.
Hengl, T., Heuvelink, G. B., Rossiter, D. G., 2007. About regression-kriging: From equations to case studies. Computers & geosciences, Vol. 33, pp. 1301-1315.
De Mesnard, L., 2013. Pollution models and inverse distance weighting: Some critical remarks. Computers & Geosciences, Vol. 52, pp. 459-469.
Nerini, D., Monestiez, P., & Mante, C., 2010. Cokriging for spatial functional data. Journal of Multivariate Analysis, Vol. 101, pp. 409-418.
Belkhiri, L., Boudoukha, A., Mouni, L., 2011. A multivariate statistical analysis of groundwater chemistry data. International Journal of Environmental Research, Vol. 52, pp. 537-544.
Moran, D., Kanemoto, K., 2016. Tracing global supply chains to air pollution hotspots. Environmental Research Letters, Vol. 14, pp.11-16.
Singh, V., Carnevale, C., Finzi, G., Pisoni, E., & Volta, M., 2011. A cokriging based approach to reconstruct air pollution maps, processing measurement station concentrations and deterministic model simulations. Environmental Modelling & Software, Vol. 26, pp. 778-786.
Basagana, X., Rivera, M., Aguilera, I., Agis, D., Bouso, L., Elosua, R., Foraster, M., de Nazelle, A., Nieuwenhuijsen, M., Vila, J. and Kunzli, N., 2012. Effect of the number of measurement sites on land use regression models in estimating local air pollution. Atmospheric environment, Vol. 54, pp.634-642.
Fadavi, G., Bazrafshan, J., Gahraman, N. 2015. Comparison of regional methods of minimum air temperature estimation (case study: Isfahan province). Meteorological Journal, Vol. 3, pp.14-24.
Miri, M., Ghaneian, M., Gholizadeh, A., Yazdani, M., Nikonahad, A., 2015. Analysis and zoning of air pollution in Mashhad using different models of spatial analysis. Journal of Environmental Health Engineering, Vol. 3, pp. 143-154.
Alimahmodi, M., Moaeiri, M., Joybari, Sh., Rashki, A., 2018. Estimation of air pollution (PM10) using weather data (Case study: Ahvaz city). Natural Environment, Natural Resources of Iran, Vol. 3, pp. 385-397.
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Jerrett, M., Arain, A., Kanaroglou, P., Beckerman, B., Potoglou, D., Sahsuvaroglu, T., Morrison, J., Giovis, C., 2005. A review and evaluation of intraurban air pollution exposure models. Journal of Exposure Science and Environmental Epidemiology, Vol. 15, pp. 185.
Wang, L.K., Pereira, N.C., Hung, Y.T. eds., 2004. Air pollution control engineering. Totowa, NJ: Humana press, London, Vol. 1, pp. 501.
Akita, Y., Baldasano, J. M., Beelen, R., Cirach, M., De Hoogh, K., Hoek, G., De Nazelle, A., 2014. Large scale air pollution estimation method combining land use regression and chemical transport modeling in a geostatistical framework. Environmental science & technology, Vol. 48, pp. 4452-4459.
Gupta, P., Christopher, S. A., 2008. An evaluation of Terra-MODIS sampling for monthly and annual particulate matter air quality assessment over the Southeastern United States. Atmospheric Environment, Vol. 26, pp. 6465-6471.
Goodchild, M. F., 1993. The state of GIS for environmental problem-solving. Environmental modeling with GIS, Vol. 2. 8-15.
Borge, R., Narros, A., Artinano, B., Yague, C., Gómez-Moreno, F. J., de la Paz, D., Quaassdorff, C., 2016. Assessment of microscale spatio-temporal variation of air pollution at an urban hotspot in Madrid (Spain) through an extensive field campaign. Atmospheric environment, Vol. 140, pp. 432-445.
Yuan, T. H., Shie, R. H., Chin, Y. Y., Chan, C.C., 2015. Assessment of the levels of urinary 1-hydroxypyrene and air polycyclic aromatic hydrocarbon in PM2.5 for adult exposure to the petrochemical complex emissions. Environmental research, Vol. 136, pp. 219-226.
Shad, R., Ashoori, H., Afshari, N., 2008. Evaluation of optimum methods for predicting pollution concentration in GIS Environment. Remote Sensing and Spatial Information Sciences, Vol. 1, pp. 33-49.
Akbari, A., Fakheri, M., Efatpoor, G., Akbari, Z., 2015. Monthly zoning of air pollution and its relationship with climate factors (Case study: Mashhad). Journal of Natural Environment, Vol. 4, pp. 533-547. (In Persian)
Esmailnejad, M., Eskandari, M., Barzman, S., 2015. Evaluation and Zoning of Tabriz Metropolitan Air Pollution. Regional Planning Quarterly, Vol. 19, pp. 173-186. (In Persian)
Hadipoor, M., Poorebrahim, Sh., 2012. Residential areas in urban transportation planning using GIS and mathematical modeling of air pollution. Understanding the environment, Vol. 59, pp. 135-148.
Shi, X., 2010. Selection of bandwidth type and adjustment side in kernel density estimation over inhomogeneous backgrounds. International Journal of Geographical Information Science, Vol. 24, pp. 643-660.
Salehi, B. Isfahan air pollution zoning. MSc in Environmental Pollution, Department of Environment, Faculty of Natural Resources, Isfahan University of Technology, Iran, 2011; pp. 100. (In Persian)
Garavandi, S., Zalghi, A., Goodarzi, G., Mohammadi, M., Yari, A., Noorzadeh, H.M., 2015. Exposure to particulate matter less than 10 microns and its effect on the incidence of respiratory and cardiovascular diseases in Isfahan. Journal of Health System Research, Vol. 11, pp.730-725. (In Persian)
Noroozi, S., Khademi, H., 2015. Spatial and temporal variations of dust deposition rate in Isfahan city and its relation to some climatic parameters. Journal of Agricultural Science and Technology, Water and Soil Science, Vol. 72, pp.149-161. (In Persian)
Mohammadi, J., Kanaani, M., 2015. Isfahan Metropolitan Strategic Planning in the Framework of Green City Approach with Emphasis on Air Component. Geographical Space Scientific Quarterly, Vol. 58, pp. 149-168. (In Persian)
Sheikhbeiglo, R., Mohammadi, J., 2010. Analysis of Climatic Elements of Wind and Rainfall with Emphasis on Urban Design Case Study of Isfahan City. Journal of Geography and Environmental Planning, Vol. 3, pp. 61-82. (In Persian)
Jha, D. K., Sabesan, M., Das, A., Vinithkumar, N. V., Kirubagaran, R., 2011. Evaluation of Interpolation Technique for Air Quality Parameters in Port Blair, India. Universal journal of environmental research & technology, Vol. 1, pp 2-15.
Willmott, C. J., Matsuura, K., 1995. Smart interpolation of annually averaged air temperature in the United States. Journal of Applied Meteorology, Vol. 34, pp. 2577-2586.
Akhavan, R., Khorramabadi, M. K., Soosani, J., 2012. Application of Kriging and IDW methods in mapping of crown cover and density of coppice oak forests (case study: Kakareza region, Khorramabad). Iranian Journal of Forest, Vol. 3, pp. 305-316. (In Persian)
Jamei, M. Evaluation of introspection methods in regional estimation of reference evaporation and transference and comparison with the available results from satellite images in the central and northern plains of Khuzestan. MSc in Agricultural Meteorology, Islamic Azad University. Tehran Science and Research Branch, Iran, 2009; pp. 102. (In Persian)
Tolosana-Delgado, R., Egozcue, J. J., Sachez-Arcilla, A., Gomez, J., 2011. Wave height data assimilation using non-stationary kriging. Computers & geosciences, Vol. 37, pp. 363-370.
Hengl, T., Heuvelink, G. B., Rossiter, D. G., 2007. About regression-kriging: From equations to case studies. Computers & geosciences, Vol. 33, pp. 1301-1315.
De Mesnard, L., 2013. Pollution models and inverse distance weighting: Some critical remarks. Computers & Geosciences, Vol. 52, pp. 459-469.
Nerini, D., Monestiez, P., & Mante, C., 2010. Cokriging for spatial functional data. Journal of Multivariate Analysis, Vol. 101, pp. 409-418.
Belkhiri, L., Boudoukha, A., Mouni, L., 2011. A multivariate statistical analysis of groundwater chemistry data. International Journal of Environmental Research, Vol. 52, pp. 537-544.
Moran, D., Kanemoto, K., 2016. Tracing global supply chains to air pollution hotspots. Environmental Research Letters, Vol. 14, pp.11-16.
Singh, V., Carnevale, C., Finzi, G., Pisoni, E., & Volta, M., 2011. A cokriging based approach to reconstruct air pollution maps, processing measurement station concentrations and deterministic model simulations. Environmental Modelling & Software, Vol. 26, pp. 778-786.
Basagana, X., Rivera, M., Aguilera, I., Agis, D., Bouso, L., Elosua, R., Foraster, M., de Nazelle, A., Nieuwenhuijsen, M., Vila, J. and Kunzli, N., 2012. Effect of the number of measurement sites on land use regression models in estimating local air pollution. Atmospheric environment, Vol. 54, pp.634-642.
Fadavi, G., Bazrafshan, J., Gahraman, N. 2015. Comparison of regional methods of minimum air temperature estimation (case study: Isfahan province). Meteorological Journal, Vol. 3, pp.14-24.
Miri, M., Ghaneian, M., Gholizadeh, A., Yazdani, M., Nikonahad, A., 2015. Analysis and zoning of air pollution in Mashhad using different models of spatial analysis. Journal of Environmental Health Engineering, Vol. 3, pp. 143-154.
Alimahmodi, M., Moaeiri, M., Joybari, Sh., Rashki, A., 2018. Estimation of air pollution (PM10) using weather data (Case study: Ahvaz city). Natural Environment, Natural Resources of Iran, Vol. 3, pp. 385-397.
