A Comprehensive Platform for Air Pollution Control System Operation in Smart Cities of Developing Countries: A Case Study of Tehran
DOI:
https://doi.org/10.15157/EIL.2023.1.1.10-27Keywords:
Air pollution, Smart cities, Developing countries, Control System, SustainabilityAbstract
Controlling air pollution in megacities is crucial from both a health and environmental perspective. Air pollution is a pervasive problem in these densely populated cities and must be effectively managed to promote sustainability. This study presents a framework for the intelligent management of air pollution control systems in developing nations. The framework was developed through the use of an expert agreement model involving five managers from Tehran. The results indicate that the Decision Support System (DSS) is equipped with calibrated sensors for monitoring air quality. Additionally, the concentration of air pollutants can be determined through the application of machine learning algorithms and the analysis of historical data. Rapid response methods are then applied to mitigate the acute and chronic effects of air pollution. The DSS also incorporates citizens' feedback to evaluate the effectiveness of air pollution control measures. Implementing this model in developing nations' smart cities can help achieve several of the United Nations' Sustainable Development Goals (SDGs), such as good health and well-being, sustainable cities and communities, climate action, and life on land.
References
Gheibi M, Karrabi M, Mohammadi A, Dadvar A. Controlling air pollution in a city: A perspective from SOAR-PESTLE analysis. Integr Environ Assess Manag. 2018 Jul;14(4):480-488. doi: https://doi.org/10.1002/ieam.4051. Epub 2018 May 16. PMID: 29663693.
Song, P., Mao, X., Li, Z., & Tan, Z. (2023). Study on the optimal policy options for improving energy efficiency and Co-controlling carbon emission and local air pollutants in China. Renewable and Sustainable Energy Reviews, 175, 113167.
Mayank Pratap Singh, D. K. Chaturvedi. Prediction of Air Quality Index (AQI) using Neural Approach, 31 January 2023, PREPRINT (Version 1) available at Research Square, https://doi.org/10.21203/rs.3.rs-2525975/v1
Yang, W., Johnson, M. B., Liao, H., Liu, Z., Zheng, X., & Lu, C. (2023). Combined effect of preconceptional and prenatal exposure to air pollution and temperature on childhood pneumonia: A case-control study. Environmental Research, 216, 114806.
Cory-Slechta, D. A., Merrill, A., & Sobolewski, M. (2023). Air pollution–related neurotoxicity across the life span. Annual Review of Pharmacology and Toxicology, 63, 143-163.?
Bose, A., & Roy Chowdhury, I. (2023). Investigating the association between air pollutants’ concentration and meteorological parameters in a rapidly growing urban center of West Bengal, India: a statistical modeling-based approach. Modeling Earth Systems and Environment, 1-16.
Ju, T., Lei, M., Guo, G., Xi, J., Zhang, Y., Xu, Y., & Lou, Q. (2023). A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification. Frontiers of Environmental Science & Engineering, 17(1), 8.?
Salvaraji, L., Avoi, R., Jeffree, M. S., Saupin, S., Toha, H. R., & Shamsudin, S. B. (2023). Effects of ambient air pollutants on cardiovascular disease hospitalization admission. Global Journal of Environmental Science and Management, 9(1), 157-172.?
Wang, Y., Gao, C., Zhao, T., Jiao, H., Liao, Y., Hu, Z., & Wang, L. (2023). A comparative study of three models to analyze the impact of air pollutants on the number of pulmonary tuberculosis cases in Urumqi, Xinjiang. PloS one, 18(1), e0277314.
Gupta, N. S., Mohta, Y., Heda, K., Armaan, R., Valarmathi, B., & Arulkumaran, G. (2023). Prediction of Air Quality Index Using Machine Learning Techniques: A Comparative Analysis. Journal of Environmental and Public Health, 2023.?
Campanile, L., Cantiello, P., Iacono, M., Lotito, R., Marulli, F., & Mastroianni, M. (2021). Applying machine learning to weather and pollution data analysis for a better management of local areas: the case of Napoli, Italy. In Proceedings of the 6th International Conference on Internet of Things, Big Data and Security. SciTePress.?
Al-Kinani, A., Eftekhari, M., Gheibi, M. and Chamsaz, M., 2018. Polyaniline-coated cerium oxide nanoparticles as an efficient adsorbent for preconcentration of ultra-trace levels of cadmium (??) followed by electrothermal atomic absorption spectrometry. Spectroscopy Letters, 51(6), pp.287-296.
Zhang, B., Yin, S., Lu, X., Wang, S., & Xu, Y. (2023). Development of city-scale air pollutants and greenhouse gases emission inventory and mitigation strategies assessment: A case in Zhengzhou, Central China. Urban Climate, 48, 101419.
Zhang, F., Li, H., Xu, W., Song, G., Wang, Z., Mao, X., ... & Zhang, Y. (2023). Sulfur dioxide may predominate in the adverse effects of ambient air pollutants on semen quality among the general population in Hefei, China. Science of The Total Environment, 161472.
Liu, T., Clegg, S. L., & Abbatt, J. P. (2020). Fast oxidation of sulfur dioxide by hydrogen peroxide in deliquesced aerosol particles. Proceedings of the National Academy of Sciences, 117(3), 1354-1359.
Abolhasani, E., Hachinski, V., Ghazaleh, N., Azarpazhooh, M. R., Mokhber, N., & Martin, J. (2023). Air Pollution and Incidence of Dementia: A Systematic Review and Meta-analysis. Neurology, 100(2), e242-e254.
Thürkow, M., Banzhaf, S., Butler, T., Pültz, J., & Schaap, M. (2023). Source attribution of nitrogen oxides across Germany: Comparing the labelling approach and brute force technique with LOTOS-EUROS. Atmospheric Environment, 292, 119412.
Li, M., Shan, B., Peng, X., Chang, H., & Cui, L. (2023). An urgent health problem of indoor air pollution: results from a 15-years carbon monoxide poisoning observed study in Jinan City. Scientific Reports, 13(1), 1619.
Manisalidis, I., Stavropoulou, E., Stavropoulos, A., & Bezirtzoglou, E. (2020). Environmental and health impacts of air pollution: a review. Frontiers in public health, 14.
Karagulian, F. (2023). New Challenges in Air Quality Measurements. In Air Quality Networks: Data Analysis, Calibration & Data Fusion (pp. 1-18). Cham: Springer International Publishing.
Adegunwa, A. O., Adebiyi, F. M., Asubiojo, O. I., & Ore, O. T. (2023). Chemical Speciation, Bioavailability and Risk Assessments of Potentially Toxic Metals in Rainwaters as Indicators of Air Pollution. Pollution, 9(1), 316-331.
Kwon, H. S., Ryu, M. H., & Carlsten, C. (2020). Ultrafine particles: unique physicochemical properties relevant to health and disease. Experimental & molecular medicine, 52(3), 318-328.
Zhang, S., Wang, S., Xue, R., Zhu, J., He, S., Duan, Y., ... & Zhou, B. (2023). Impacts of Omicron associated restrictions on vertical distributions of air pollution at a suburb site in Shanghai. Atmospheric Environment, 294, 119461.
Liao, H., Murithi, R. G., Lu, C., Yang, W., Liu, Z., & Cao, L. (2023). Long-term exposure to traffic-related air pollution and temperature increases gynecological cancers. Building and Environment, 109989.
Yang, H., Huang, X., Westervelt, D. M., Horowitz, L., & Peng, W. (2023). Socio-demographic factors shaping the future global health burden from air pollution. Nature Sustainability, 6(1), 58-68.
Nie, W., Sun, N., Liu, Q., Guo, L., Xue, Q., Liu, C., & Niu, W. (2022). Comparative study of dust pollution and air quality of tunnelling anchor integrated machine working face with different ventilation. Tunnelling and Underground Space Technology, 122, 104377.
Mei, S. J., Zhao, Y., Talwar, T., Carmeliet, J., & Yuan, C. (2023). Neighborhood scale traffic pollutant dispersion subject to different wind-buoyancy ratios: A LES case study in Singapore. Building and Environment, 228, 109831.
Buccolieri, R., Carlo, O. S., Rivas, E., Santiago, J. L., Salizzoni, P., & Siddiqui, M. S. (2022). Obstacles influence on existing urban canyon ventilation and air pollutant concentration: A review of potential measures. Building and Environment, 108905.
Wolkoff, P. (2018). Indoor air humidity, air quality, and health–An overview. International journal of hygiene and environmental health, 221(3), 376-390.
Ismail, I. M., Rashid, M. I., Ali, N., Altaf, B. A. S., & Munir, M. (2022). Temperature, humidity and outdoor air quality indicators influence COVID-19 spread rate and mortality in major cities of Saudi Arabia. Environmental Research, 204, 112071.
Zhao, Y., Xi, M., Zhang, Q., Dong, Z., Ma, M., Zhou, K., ... & Zhang, L. (2022). Decline in bulk deposition of air pollutants in China lags behind reductions in emissions. Nature Geoscience, 15(3), 190-195.
Lemaitre, J., Pasetto, D., Perez-Saez, J., Sciarra, C., Wamala, J. F., & Rinaldo, A. (2019). Rainfall as a driver of epidemic cholera: comparative model assessments of the effect of intra-seasonal precipitation events. Acta tropica, 190, 235-243.
Luo, Z., Wang, Y., Lv, Z., He, T., Zhao, J., Wang, Y., ... & Liu, H. (2022). Impacts of vehicle emission on air quality and human health in China. Science of The Total Environment, 813, 152655.
? Yavuz, V., Özen, C., Çapraz, Ö., Özdemir, E. T., Deniz, A., Akbay?r, ?., & Temur, H. (2022). Analysing of atmospheric conditions and their effects on air quality in Istanbul using SODAR and CEILOMETER. Environmental Science and Pollution Research, 1-20.
Xiang, X., Fahad, S., Han, M. S., Naeem, M. R., & Room, S. (2022). Air quality index prediction via multi-task machine learning technique: spatial analysis for human capital and intensive air quality monitoring stations. Air Quality, Atmosphere & Health, 1-13.
Moradi, H., Talaiekhozani, A., Kamyab, H., Chelliapan, S., & Nadda, A. K. (2022). Development of equations to predict the concentration of air pollutants indicators in Yazd City, Iran. Journal of Inorganic and Organometallic Polymers and Materials, 1-10.
Akbarian H, Jalali FM, Gheibi M, Hajiaghaei-Keshteli M, Akrami M, Sarmah AK. A sustainable Decision Support System for soil bioremediation of toluene incorporating UN sustainable development goals. Environ Pollut. 2022 Aug 15;307:119587. doi: 10.1016/j.envpol.2022.119587. Epub 2022 Jun 6. PMID: 35680063.
Gheibi, M.; Taghavian, H.; Moezzi, R.; Waclawek, S.; Cyrus, J.; Dawiec-Lisniewska, A.; Koci, J.; Khaleghiabbasabadi, M. Design of a Decision Support System to Operate a NO2 Gas Sensor Using Machine Learning, Sensitive Analysis and Conceptual Control Process Modelling. Chemosensors 2023, 11, 126. https://doi.org/10.3390/chemosensors11020126
Gheibi, M., Eftekhari, M., Akrami, M., Emrani, N., Hajiaghaei-Keshteli, M., Fathollahi-Fard, A.M. and Yazdani, M., 2022. A sustainable decision support system for drinking water systems: Resiliency improvement against cyanide contamination. Infrastructures, 7(7), p.88.
Shahsavar, M.M., Akrami, M., Kian, Z., Gheibi, M., Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M. and Behzadian, K., 2022. Bio-recovery of municipal plastic waste management based on an integrated decision-making framework. Journal of Industrial and Engineering Chemistry, 108, pp.215-234.
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