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Investigating the spatial distribution of land surface temperature as related to air pollution level in Tehran metropolis | ||
Pollution | ||
دوره 9، شماره 1، فروردین 2023، صفحه 1-14 اصل مقاله (1004.21 K) | ||
نوع مقاله: Original Research Paper | ||
شناسه دیجیتال (DOI): 10.22059/poll.2022.330381.1181 | ||
نویسندگان | ||
Saeedeh Nasehi؛ Ahmadreza Yavari* ؛ Esmael Salehi | ||
School of Environment, College of Engineering, University of Tehran, Tehran, Iran | ||
چکیده | ||
Urban Heat Island (UHI) is a common urban problem associated with a wide variety of factors, including air pollution. This study investigated the relationship between Land Surface Temperature (LST) and air pollution as two spatial phenomena affecting urban areas. LST was estimated from OLI sensor images taken on 01/07/2020 using the single-channel algorithm. Air pollution was assumed to be indicated by the concentrations of NOX, NO2, NO, PM2.5 and SO2, which were obtained by Inverse Distance Weighting (IDW) interpolation from the data recorded on the same date as satellite images. Correlations were measured in terms of R and R2 and errors were estimated in terms of RMSE, MAE and MBE. The highest R and R2 were obtained for SO2 (20.89 and 45.99, respectively). The results showed that despite the high correlation between SO2 and LST, PM2.5 has a much better error distribution. Therefore, further research should be conducted on the relationship between these indices. | ||
کلیدواژهها | ||
Surface temperature؛ Interpolation؛ Air pollutants؛ Correlation؛ Tehran | ||
مراجع | ||
Atabi, F., Karbasi, A., Haji, M. H. S. and Abbaspour, M. (2007). Modeling the emission of particulate matter using ADMS-Urban. J. Environ. Sci. Technol, 9(1), 1-15. Atkinson, D. M., Deadman, P., Dudycha, D. and Traynor, S. (2005). Multi-criteria evaluation and least cost path analysis for an arctic all-weather road. Applied Geography, 25(4), 287-307. Callender, G. (1938). The artificial production of carbon dioxide and its influence on temperature. Q J R Meteorol Soc, 64, 223– 240. Chen, Y., Yang, K., He, J., Qin, J., Shi, J., Du, J. and He, Q. (2011). Improving land surface temperature modeling for dry land of China. J. Geophys Res. Atmos, 116 (D20). Fang, Y. and Gu, K. (2021). Exploring coupling effect between urban heat island effect and PM2. 5 concentrations from the perspective of spatial environment. Environ. Eng. Res.1-32 Feng, H. and Zou, B. (2019). Satellite-based estimation of the aerosol forcing contribution to the global land surface temperature in the recent decade. Remote Sens. Environ, 232, 111299. Feizizadeh, B. and Blaschke, T. (2013). Land suitability analysis for Tabriz County, Iran: a multi-criteria evaluation approach using GIS. J. Environ. Plan. Manag, 56(1), 1-23. Franchini, M., Mengoli, C., Cruciani, M., Bonfanti, C. and Mannucci, P. M. (2016). Association between particulate air pollution and venous thromboembolism: A systematic literature review. Eur. J. Intern. Med, 27, 10-13. Fu, P. and Weng, Q. (2016). A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery. Remote Sens. Environ, 175, 205-214. Ganesh, K. S., Unnikrishnan, B., Nagaraj, K. and Jayaram, S. (2010). Determinants of pre-eclampsia: a case control study in a district hospital in South India. Indian J. Community Med: official publication of Indian Association of Preventive & Social Medicine, 35(4), 502. Ghozikali, M. G., Heibati, B., Naddafi, K., Kloog, I., Conti, G. O., Polosa, R. and Ferrante, M. (2016). Evaluation of chronic obstructive pulmonary disease (COPD) attributed to atmospheric O3, NO2, and SO2 using Air Q Model (2011–2012 year). Environ. Res., 144, 99-105 Gillespie, I. M., Haimberger, L., Compo, G. P. and Thorne, P. W. (2021). Assessing potential of sparse‐input re-analyses for centennial‐scale land surface air temperature homogenization. Int J Climatol, 41, E3000-E3020. Guo, G., Zhou, X., Wu, Z., Xiao, R. and Chen, Y. (2016). Characterizing the impact of urban morphology heterogeneity on land surface temperature in Guangzhou, Environ Model Softw, 84, 427-439. Hawkins, E. and Jones, P.D. (2013) On increasing global temperatures: 75 years after Callendar. Q. J. R. Meteorol. Soc, 139, 1961–1963. Hereher, M., Eissa, R., Alqasemi, A., El Kenawy, A.M. (2021). Assessment of air pollution at Greater Cairo in relation to the spatial variability of surface urban heat island. Environ. Sci. Pollut. Res, 1-14. Jiménez-Muñoz, J. C. and Sobrino, J. A. (2009). A single-channel algorithm for land-surface temperature retrieval from ASTER data. IEEE Geosci. Remote. Sens. Lett, 7(1), 176-179. Karimi, A., Pahlavani, P. and Bigdeli, B. (2019). Determining affective factors on land surface temperature of Tehran using Landsat images and integrating geographically weighted regression with genetic algorithm. J. Geo Spat Inf Tech, 7(3), 79-102 Kayet, N., Pathak, K., Chakrabarty, A. and Sahoo, S. (2016). Spatial impact of land use/land cover change on surface temperature distribution in Saranda Forest, Jharkhand. Model. Earth Syst. Environ, 2(3), 1-10. Khandelwal, S., Goyal, R., Kaul, N. and Mathew, A. (2018). Assessment of land surface temperature variation due to change in elevation of area surrounding Jaipur, India. Egypt. J. Remote Sens. Space Sci, 21(1), 87-94. Khaniabadi, Y. O., Daryanoosh, S. M., Amrane, A., Polosa, R., Hopke, P. K., Goudarzi, G. and Armin, H. (2017). Impact of Middle Eastern Dust storms on human health. Atmos. Pollut. Res, 8(4), 606-613. Li, H., Meier, F., Lee, X., Chakraborty, T., Liu, J., Schaap, M. and Sodoudi, S. (2018). Interaction between urban heat island and urban pollution island during summer in Berlin. Sci. Total Environ, 636, 818-828. Mahapatra, P. S., Sinha, P. R., Boopathy, R., Das, T., Mohanty, S., Sahu, S. C. and Gurjar, B. R. (2018). Seasonal progression of atmospheric particulate matter over an urban coastal region in peninsular India: role of local meteorology and long-range transport. Atmos. Res, 199, 145-158. Matkan, A. A., Shakiba, A. R., Purali, S. H. and Baharloo, I. (2009). Determination of spatial variation of CO and PM10 air pollutants, using GIS techniques (case study: Tehran, Iran) Remote Sens. GIS, 1(1), 57-72. Malbéteau, Y., Merlin, O., Gascoin, S., Gastellu, J. P., Mattar, C., Olivera-Guerra, L., ... & Jarlan, L. (2017). Normalizing land surface temperature data for elevation and illumination effects in mountainous areas: A case study using ASTER data over a steep-sided valley in Morocco. Remote Sens Environ, 189, 25-39. Mannucci, P. M. and Franchini, M. (2017). Health effects of ambient air pollution in developing countriesInt. J. Environ. Res. Public Health, 14(9), 1048. McDonnell M.J., MacGregor-Fors I. The ecological future of cities. Sci, 2016, 352, 936-938 Mukherjee, F. and Singh, D. (2020). Assessing land use–land cover change and its impact on land surface temperature using LANDSAT data: A comparison of two urban areas in India. Earth Syst and Environ, 4(2), 385-407. Najafzadeh, F., Mohammadzadeh, A., Ghorbanian, A., Jamali, S., (2021). Spatial and Temporal Analysis of Surface Urban Heat Island and Thermal Comfort Using Landsat Satellite Images between 1989 and 2019: A Case Study in Tehran. Remote Sens, 1-25. Ngarambe, J., Jeong Joen, S., Han, G., Yun, G. (2021). Exploring the relationship between particulate matter, CO, SO2, NO2, O3 and urban heat island in Seoul, Korea. J. Hazard. Mater. 1-13. Nosrati, K., Zehtabian, G. R., Moradi, E.,& Shahbazi, A (2008), Evaluation of stochastic Simulation method for generating meteorological data, Geogr. Res.Q.J. 1-9. Peterson, T.c. and Owen, T.W. (2005). Urban heat island assessment: Metadata are important. J. Clim, 18(14) 2637-2646 Phan, T. N., Kappas, M. and Tran, T. P. (2018). Land surface temperature variation due to changes in elevation in northwest Vietnam. Clim, 6(2), 28. Qin, Z.; Karnieli, A.; Berliner, P. A. (2001). Mono-window algorithm for retrieving land surface temperature from landsat tm data and its application to the Israel-Egypt border region. Int. J. Remote Sens., 22, 3719–3746. Ranjbar, M. and Bahak, B. (2019). Time and Space Changes of Air Pollutants Using GIS (Case Study: North Semnan Tehran. J Geog, 17(60), 72-85. Sadidi, Javad, Rezaian, Hani, Borshan, Mohammad Reza (2017), Comparison of error distribution in recursive artificial neural networks Elman and Jordan in estimating the concentration of atmospheric particulate matter (PM10) using satellite imagery (MODIS Case Study: Ahvaz City, 17 (47). 155-169. Solangi, G. S., Siyal, A. A. and Siyal, P. (2019). Spatio-temporal dynamics of land surface temperature and its impact on the vegetation. Civ. Eng. J, 5(8), 1753-1763. Wang, Y., Guo, Zh. Han, J. (2021). The relationship between urban heat island and air pollutants and them with influencing factors in the Yangtze River Delta, China. Ecol. Indic, 1-10. Willmott, C. J. and Matsuura, K. (1995). Smart interpolation of annually averaged air temperature in the United States. Appl Meteorol Climatol, 34(12), 2577-2586. Wong, M., Nichol, J., Lee, K. H. and Li, Z. (2009). High resolution aerosol optical thickness retrieval over the Pearl River Delta region with improved aerosol modelling. Sci. China, D Earth sci, 52(10), 1641-1649. Xia, G., Cervarich, M. C., Roy, S. B., Zhou, L., Minder, J. R., Jimenez, P. A. and Freedman, J. M. (2017). Simulating impacts of real-world wind farms on land surface temperature using the WRF Model: Validation with observations. Mon Weather Rev, 145(12), 4813-4836. Yang, J., Menenti, M., Wu, Z., Wong, M. S., Abbas, S., Xu, Y. and Shi, Q. (2021). Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures. Int J Climatol, 41, E3219-E3238. Yang, J., Sun, J., Ge, Q. and Li, X. (2017). Assessing the impacts of urbanization-associated green space on urban land surface temperature: A case study of Dalian, China. Urban For Urban Green, 22, 1-10. Yang, J., Wong, M. S., Menenti, M. and Nichol, J. (2015). Study of the geometry effect on land surface temperature retrieval in urban environment. ISPRS J. Photogramm. Remote Sens, 109, 77-87. Yoo, J. M., Jeong, M. J., Kim, D., Stockwell, W. R., Yang, J. H., Shin, H. W., ... & Lee, S. D. (2015). Spatiotemporal variations of air pollutants (O 3, NO 2, SO 2, CO, PM 10, and VOCs) with land-use types. Atmos. chem. phys, 15(18), 10857-10885. Zhang, J., Reid, J. S., Christensen, M. and Benedetti, A. (2016). An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature. Atmos. Chem. Phys, 16(10), 6475-6494. Zhou, L., Tian, Y., Roy, S. B., Dai, Y. and Chen, H. (2013). Diurnal and seasonal variations of wind farm impacts on land surface temperature over western Texas. Clim Dyn, 41(2), 307-326. Zhou, L., Tian, Y., Roy, S. B., Thorncroft, C., Bosart, L. F. and Hu, Y. (2012). Impacts of wind farms on land surface temperature. Nat Clim Change, 2(7), 539-543. Ziaul, S. and Pal, S. (2018). Analyzing control of respiratory particulate matters on Land Surface Temperature in local climatic zones of English Bazar Municipality and Surroundings. Urban Clim, 24, 34-50. | ||
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