Evaluation of PM2.5 Emissions in Tehran by Means of Remote Sensing and Regression Models

Document Type : Original Research Paper

Authors

Department of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran

Abstract

Defined as any substance in the air that may harm humans, animals, vegetation, and materials, air pollution poses a great danger to human health. It has turned into a worldwide problem as well as a huge environmental risk. Recent years have witnessed the increase of air pollution in many cities around the world. Similarly, it has become a big problem in Iran. Although ground-level monitoring can provide accurate PM2.5 measurements, it has limited spatial coverage and resolution. As a result, Satellite Remote Sensing (RS) has emerged as an approach to estimate ground-level ambient air pollution, making it possible to monitor atmospheric particulate matters continuously and have a spatial coverage of them. Recent studies show a high correlation between ground level PM2.5, estimated by RS on the one hand, and measurements, collected at regulatory monitoring sites on the other. As such, the present study addresses the relation between air pollution and satellite images. For so doing, it derives RS estimates, using satellite measurements from Landsat satellite images. Monitoring data is the daily concentration of PM2.5 contaminants, obtained from air pollution stations. The relation between the concentration of pollutants and the values of various bands of Landsat satellite images is examined through 19 regression models. Among them, the Ensembles Bagged Trees has the lowest Root-Mean-Square Error (RMSE), equal to 21.88. Results show that this model can be used to estimate PM2.5 contaminants, based on Landsat satellite images.

Keywords


Alizadeh-Choobari, O., Bidokhti, A. A., Ghafarian, P. and Najafi, M. S. (2016). Temporal and spatial variations of particulate matter and gaseous pollutants in the urban area of Tehran. Atmospheric Environment, 141, 443-453.
Ansari, N. and Seifi, A. (2013). A system dynamics model for analyzing energy consumption and CO2 emission in Iranian cement industry under various production and export scenarios. Energy Policy, 58, 75-89.
Arceo, E., Hanna, R. and Oliva, P. (2016). Does the Effect of Pollution on Infant Mortality Differ Between Developing and Developed Countries? Evidence from Mexico City. The Economic Journal, 126(591), 257-280.
Asghari, M. and Nematzadeh, H. (2016). Predicting air pollution in Tehran: Genetic algorithm and back propagation neural network. Journal of AI and Data Mining, 4(1), 49-54.
Behzadi, S. and Alesheikh, A. (2013). Introducing a novel model of belief–desire–intention agent for
Jafarian, H. and Behzadi, S.
528
urban land use planning. Engineering Applications of Artificial Intelligence, 26(9), 2028-2044.
Behzadi, S. and Alesheikh, A. (2014). Cellular Automata vs. Object-Automata in Traffic Simulation. International Journal of Remote Sensing Applications, 4(1), 61-69.
Block, M. L., Elder, A., Auten, R. L., Bilbo, S. D., Chen, H., Chen, J.-C., Cory-Slechta, D., Costa, D., Diaz-Sanchez, D., Dorman, D., Gold, D., Gray, K., Jeng, H., Kaufman, J., Kleinman, M., Kirshner, A., Lawler, C., Miller, D., Nadadur, S., Ritz, B., Semmens, E., Tonelli, L., Veronesi, B., Wright, R. and Wright, R. J. (2012). The outdoor air pollution and brain health workshop. NeuroToxicology, 33(5), 972-984.
Bourdrel, T., Bind, M.-A., Béjot, Y., Morel, O. and Argacha, J.-F. (2017). Cardiovascular effects of air pollution. Archives of Cardiovascular Diseases, 110(11), 634-642.
Brauer, M., Freedman, G., Frostad, J., van Donkelaar, A., Martin, R., Dentener, F., Van Dingenen, R., Estep, K., Amini, H., Schulz Apte, J., Balakrishnan, K., Barregard, L., Broday, D., Feigin, V., Ghosh, S., Hopke, P., David Knibbs, L., Kokubo, Y., Liu, Y. and Cohen, A. (2016). Ambient Air Pollution Exposure Estimation for the Global Burden of Disease 2013. Environmental Science & Technology, 50(1), 79-88.
Ebenstein, A., Fan, M., Greenstone, M., He, G. and Zhou, M. (2017). New evidence on the impact of sustained exposure to air pollution on life expectancy from China’s Huai River Policy. Proceedings of the National Academy of Sciences, 114(39), 10384-10389.
Greenstone, M. and Hanna, R. (2014). Environmental Regulations, Air and Water Pollution, and Infant Mortality in India. American Economic Review, 104(10), 3038-3072.
Guo, S., Hu, M., Zamora, M. L., Peng, J., Shang, D., Zheng, J., Du, Z., Wu, Z., Shao, M., Zeng, L., Molina, M. and Zhang, R. (2014). Elucidating severe urban haze formation in China. Proceedings of the National Academy of Sciences, 111(49), 17373-17378.
Gupta, P. and Christopher, S. A. (2008). Seven year particulate matter air quality assessment from surface and satellite measurements. Atmos. Chem. Phys., 8(12), 3311-3324.
Gupta, P., Christopher, S. A., Wang, J., Gehrig, R., Lee, Y. and Kumar, N. (2006). Satellite remote sensing of particulate matter and air quality assessment over global cities. Atmospheric Environment, 40(30), 5880-5892.
Hamraz, H., Sadeghi-Niaraki, A., Omati, M. and Noori, N. (2014). GIS-Based Air Pollution Monitoring using Static Stations and Mobile Sensor in Tehran/Iran. International Journal of Scientific Research in Environmental Sciences, 2(12), 435-448.
Hidy, G., Brook, J., Chow, J., Green, M., Husar, R., Lee, C., Scheffe, R., Swanson, A. and Watson, J. (2009). Remote Sensing of Particulate Pollution from Space: Have We Reached the Promised Land? Journal of the Air & Waste Management Association, 59(10), 1130-1139.
Kelly, F. J., Fuller, G. W., Walton, H. A. and Fussell, J. C. (2011). Monitoring air pollution: Use of early warning systems for public health. Respirology, 17(1), 7-19.
Kanada, M., Dong, L., Fujita, T., Fujii, M., Inoue, T., Hirano, Y., Togawa, T. and Geng, Y. (2013). Regional disparity and cost-effective SO2 pollution control in China: A case study in 5 mega-cities. Energy Policy, 61, 1322-1331.
Knittel, C. R., Miller, D. L. and Sanders, N. J. (2011). Caution, Drivers! Children Present: Traffic, Pollution, and Infant Health. Review of Economics and Statistics, 98(2), 350-366.
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D. and Pozzer, A. (2015). The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature, 525(7569), 367-371.
Martin, R. V. (2008). Satellite remote sensing of surface air quality. Atmospheric Environment, 42(34), 7823-7843.
Miller, K. A., Siscovick, D. S., Sheppard, L., Shepherd, K., Sullivan, J. H., Anderson, G. L. and Kaufman, J. D. (2007). Long-Term Exposure to Air Pollution and Incidence of Cardiovascular Events in Women. New England Journal of Medicine, 356(5), 447-458.
Mousavi, Z. and Behzadi, S. (2019a). Geo-Portal Implementation with a Combined Approach of AHP and SWOT. International Journal of Natural Sciences Research, 7(1), 22-31.
Mousavi, Z. and Behzadi, S. (2019b). Introducing an Appropriate Geoportal Structure for Managing Wildlife Location Data. International Journal of Natural Sciences Research, 7(1), 32-48.
Nabavi, S. O., Haimberger, L. and Abbasi, E. (2019). Assessing PM2.5 concentrations in Tehran, Iran, from space using MAIAC, deep blue, and dark target AOD and machine learning algorithms. Atmospheric Pollution Research, 10(3), 889-903.
Pollution, 6(3): 521-529, Summer 2020
Pollution is licensed under a "Creative Commons Attribution 4.0 International (CC-BY 4.0)"
529
Nafstad, P., Håheim, L. L., Oftedal, B., Gram, F., Holme, I., Hjermann, I. and Leren, P. (2003). Lung cancer and air pollution: a 27 year follow up of 16 209 Norwegian men. Thorax, 58(12), 1071-1076.
Pope, C. A., Burnett, R. T., Thun, M. J., Calle, E. E., Krewski, D., Ito, K. and Thurston, G. D. (2002). Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA, 287(9), 1132-1141.
Prud'homme, G., Dobbin, N. A., Sun, L., Burnett, R. T., Martin, R. V., Davidson, A., Cakmak, S., Villeneuve, P. J., Lamsal, L. N., van Donkelaar, A., Peters, P. A. and Johnson, M. (2013). Comparison of remote sensing and fixed-site monitoring approaches for examining air pollution and health in a national study population. Atmospheric Environment, 80, 161-171.
Shahgholian, K. and Hajihosseini, H. (2009). A dynamic model of air pollution, health, and population growth using system dynamics: A study on Tehran-Iran (with computer simulation by the software Vensim). World Academy of Science, Engineering and Technology, 59(35), 245-252.
Sohrabinia, M. and Khorshiddoust, A. M. (2007). Application of satellite data and GIS in studying air pollutants in Tehran. Habitat International, 31(2), 268-275.
Yousefi Kebria, D., Darvishi, G. and Haghighi, F. (2013). Estimation of Air Pollution in Urban Streets by Modeling of PM10, O3 and CO Pollutants according to Regression Method (Case study-Yadegar and Azadi streets intersection, Tehran, IRAN). Research Journal of Recent Sciences, 2(4), 36-45.