Abstract
The design of an air quality monitoring network (AQMN) is the mandatory step to manage air pollution in megacities. Several studies are being done on the location selection of AQMNs based on topography, meteorology, and pollution density. Still, the critical research gap that needs to be addressed is the role of pollutants’ importance and prioritization in AQMN. This study aims to utilize the sphere of influence (SOI) method to design an AQMN in a megacity based on particulate matter (PM) as the most serious urban pollutant. Model evaluation was done by employing annual emission inventory data of PM in Tabriz, an industrial and crowded megacity with high exposure to salt particulates, considering 3549 square blocks with a size of 500 m * 500 m. Then, the SOI methodology utilizing the utility function (UF) approach is applied using MATLAB software calculations to determine optimal air quality monitoring network configurations. A range of numbers of utility functions was yielded for every spot on the map. It resulted in grid city maps with final spots for PM10, PM2.5, and intersecting spots. As a result, ten sites are selected as the best possible locations for the AQMN of a 2 million population city. These results could play a precise and significant role in urban air quality decision-making and management.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Al‐Adwani, S., Elkamel, A., Duever, T., & Abdul-wahab, S. (2015). A surrogate‐based optimization methodology for the optimal design of an air quality monitoring network. The Canadian Journal of Chemical Engineering, 93. https://doi.org/10.1002/cjce.22205.
Alsahli, M. M., & Al-Harbi, M. (2018). Allocating optimum sites for air quality monitoring stations using GIS suitability analysis. Urban Climate, 24, 875–886. https://doi.org/10.1016/j.uclim.2017.11.001
Andria, G., Cavone, G., & Lanzolla, A. M. L. (2008). Modelling study for assessment and forecasting variation of urban air pollution. Measurement, 41(3), 222–229. https://doi.org/10.1016/j.measurement.2007.06.004
Arbeloa Serón, F. J., Pérez Caseiras, C., & Latorre Andrés, P. M. (1993). Air quality monitoring: Optimization of a network around a hypothetical potash plant in open countryside. Atmospheric Environment Part A General Topics, 27(5), 729–738. https://doi.org/10.1016/0960-1686(93)90190-A
Asif, Z., & Chen, Z. (2019). An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit metal mine. Frontiers of Environmental Science and Engineering, 13, 1–14. https://doi.org/10.1007/s11783-019-1156-x
Azarafza, M., & Ghazifard, A. (2016). Urban geology of Tabriz City: Environmental and geological constraints. Advances in Environmental Research, 5(2), 95–108. https://doi.org/10.12989/aer.2016.5.2.095
Baldauf, R. W. (2000). Ambient air quality monitoring network design for assessing human health impacts from exposures to airborne particulate matter. (Order No. 9998061, University of Kansas). ProQuest Dissertations and Theses, 318. Retrieved from https://login.proxy.lib.ul.ie/login?url=https://www.proquest.com/dissertations-theses/ambient-air-quality-monitoring-network-design/docview/304625042/se-2. Accessed 07 June 2023.
Barzeghar, V., Sarbakhsh, P., Hassanvand, et al. (2020). The long-term trend of ambient air PM10, PM2.5, and O3 and their health effects in Tabriz city, Iran, during 2006–2017. Sustainable Cities and Society, 54(2), 101988. https://doi.org/10.1016/j.scs.2019.101988
Barzeghar, V., Hassanvand, M. S., Faridi, S., Abbasi, S., & Gholampour, A. (2022). Long-term trends in ambient air pollutants and the effect of meteorological parameters in Tabriz, Iran. Urban Climate, 42, 101119. https://doi.org/10.1016/j.uclim.2022.101119
Batzias, F., & Gkionakis, A. (2016). Multiobjective optimization of floating observational buoys location/allocation for limiting marine pollution impact caused by hydrocarbons release. International Journal of Environmental Science, 1, 300–308.
Campos, P., Esteves, A., Leitao, A., & Pires, J. (2021). Design of air quality monitoring network of Luanda, Angola: Urban air pollution assessment. Atmospheric Pollution Research, 12, 101128. https://doi.org/10.1016/j.apr.2021.101128
Carratù, M., Ferro, M., Pietrosanto, A., & Sommella, P. (2018). Wireless sensor network for low-cost air quality measurement. Journal of Physics Conference Series, 1065, 192004. https://doi.org/10.1088/1742-6596/1065/19/192004
Chen, M., Wang, S., & Xu, Q. (2015). Multiobjective optimization for air-quality monitoring network design. Industrial and Engineering Chemistry Research, 54(31), 7743–7750. https://doi.org/10.1021/acs.iecr.5b00875
D’Elia, G., et al. (2022). Influence of concept drift on metrological performance of low-cost NO2 sensors. IEEE Transactions on Instrumentation and Measurement, 71, 1–11. https://doi.org/10.1109/TIM.2022.3188028
Elkamel, A., Fatehifar, E., Taheri, M., Al-Rashidi, M. S., & Lohi, A. (2008). A heuristic optimization approach for air quality monitoring network design with the simultaneous consideration of multiple pollutants. Journal of Environmental Management, 88, 507–516. https://doi.org/10.1016/j.jenvman.2007.03.029
Environmental Protection Agency. (1991). AP-42: Compilation of air pollutant emission factors.
Erel, Y., Tirosh, O., Kessler, N., Dayan, U., Belkin, S., Stein, M., Sandler, A., & Schauer, J. J. (2013). Atmospheric particulate matter (PM) in the Middle East: Toxicity, trans-boundary transport, and influence of synoptic conditions. In Air Pollution and Health. https://doi.org/10.1007/978-94-007-4372-4_3
Ezekiel, M. (1941). Methods of correlation analysis (2nd ed.). John Wiley & Sons.
Farahat, A. (2016). Air pollution in the Arabian Peninsula (Saudi Arabia, the United Arab Emirates, Kuwait, Qatar, Bahrain, and Oman): Causes, effects, and aerosol categorization. Arabian Journal of Geosciences, 9, 1–17. https://doi.org/10.1007/s12517-015-2203-y
Fatehifar, E., Elkamel, A., & Taheri, M. (2006). A MATLAB-based modeling and simulation program for dispersion of multipollutants from an industrial stack for educational use in a course on air pollution control. Computer Applications in Engineering Education, 14, 300–312. https://doi.org/10.1002/cae.20089
Feizizadeh, B., Omarzadeh, D., Sharifi, A., Rahmani, A., Lakes, T., & Blaschke, T. (2022). A GIS-based spatiotemporal modeling of urban traffic accidents in Tabriz City during the COVID-19 pandemic. Sustainability, 14(12), 7468. https://doi.org/10.3390/su14127468
Griffo, G., Piper, L., Lay-Ekuakille, A., & Pellicanó, D. (2014). Design of buoy station for marine pollutant detection. Measurement, 47, 1024–1029. https://doi.org/10.1016/J.MEASUREMENT.2013.09.039
Gupta, S., Mateu, J., Degbelo, A., & Pebesma, E. (2018). Quality of life, big data, and the power of statistics. Statistics and Probability Letters, 136. https://doi.org/10.1016/j.spl.2018.02.030.
Hao, Y., & Xie, S. (2018). Optimal redistribution of an urban air quality monitoring network using atmospheric dispersion model and genetic algorithm. Atmospheric Environment, 177, 222–233. https://doi.org/10.1016/j.atmosenv.2018.01.011
Heo, J., Wu, B., Abdeen, Z., Qasrawi, R., Sarnat, J., Sharf, G., Shpund, K., & Schauer, J. J. (2017). Source apportionments of ambient fine particulate matter in Israeli, Jordanian, and Palestinian cities. Environmental Pollution, 225, 1–11. https://doi.org/10.1016/j.envpol.2017.01.081
Huang, Z., Yu, Q., Ma, W., & Chen, L. (2019). Surveillance efficiency evaluation of air quality monitoring networks for air pollution episodes in industrial parks: Pollution detection and source identification. Atmospheric Environment, 215, 116874. https://doi.org/10.1016/j.atmosenv.2019.116874
Kainuma, Y., Shiozawa, K., & Okamoto, S. (1990). Study of the optimal allocation of ambient air monitoring stations. Atmospheric Environment Part B Urban Atmosphere, 24(3), 395–406. https://doi.org/10.1016/0957-1272(90)90047-X
Kaur, A. (2022). Long-range air pollution monitoring. Rangahau Aranga: AUT Graduate Review, 1(1). https://doi.org/10.24135/rangahau-aranga.v1i1.43.
Khazini, L., Jamshidi Kalajahi, M., Rashidi, Y., & Mirzaei Ghomi, S. M. M. (2023). Real-world and bottom-up methodology for emission inventory development and scenario design in medium-sized cities. Journal of Environmental Sciences, 127, 114–132. https://doi.org/10.1016/j.jes.2022.02.035
Kheirizadeh Arouq, M., Esmaeilpour, M., & Sarvar, H. (2020). Vulnerability assessment of cities to earthquake based on the catastrophe theory: A case study of Tabriz city, Iran. Environmental Earth Sciences, 79(3), 354. https://doi.org/10.1007/s12665-020-09103-2
Li, Q. (2020). Particulate matter caused health risk in an urban area of the Middle East and the challenges in reducing its anthropogenic emissions. Retrieved from https://api.semanticscholar.org/CorpusID:249884967.
Li, J., Zhang, H., Luo, Y., Deng, X., Grieneisen, M. L., Yang, F., Di, B., & Zhan, Y. (2019). Stepwise genetic algorithm for adaptive management: Application to air quality monitoring network optimization. Atmospheric Environment, 215, 116894. https://doi.org/10.1016/j.atmosenv.2019.116894
Liu, M. K., Avrin, J., Pollack, R. I., et al., (1986). Methodology for designing air quality monitoring networks: I. Theoretical aspects. Environmental Monitoring and Assessment, 6. https://doi.org/10.1007/BF00394284.
Liu, B., Peng, Y., Wang, W., & Mao, N. (2023). Robust optimization for designing air quality monitoring network in coal ports under uncertainty. Atmospheric Environment, 304, 119792. https://doi.org/10.1016/j.atmosenv.2023.119792
Lozano, A., Usero, J., Vanderlinden, E., Raez, J., Contreras, J., & Navarrete, B. (2009). Air quality monitoring network design to control nitrogen dioxide and ozone, applied in Malaga, Spain. Microchemical Journal, 93(2), 164–172. https://doi.org/10.1016/j.microc.2009.06.005
Mabit, L., & Bernard, C. (2007). Assessment of spatial distribution of fallout radionuclides through geostatistics concept. Journal of Environmental Radioactivity, 97(2–3), 206–219. https://doi.org/10.1016/j.jenvrad.2007.05.008
Marques, G., Saini, J., Dutta, M., Singh, P. K., & Hong, W-C. (2020). Indoor air quality monitoring systems for enhanced living environments: A review toward sustainable smart cities. Sustainability, 12(10). https://doi.org/10.3390/su12104024.
Mocerino, L., Murena, F., Quaranta, F., & Toscano, D. (2020). A methodology for the design of an effective air quality monitoring network in port areas. Scientific Reports, 10. https://doi.org/10.1038/s41598-019-57244-7.
Modak, P. M., & Lohani, B. N. (1985). Optimization of ambient air quality monitoring networks. Environmental Monitoring and Assessment, 5, 289–298. https://doi.org/10.1007/BF00396393
Mofarrah, A., & Husain, T. (2010). A holistic approach for optimal design of air quality monitoring network expansion in an urban area. Atmospheric Environment, 44. https://doi.org/10.1016/j.atmosenv.2009.07.045.
Munir, S. (2022). Urban air quality monitoring, mapping, and modelling to determine the main drivers of air pollution. (Doctoral dissertation, University of Sheffield). Retrieved from https://etheses.whiterose.ac.uk/31920/. Accessed 18 Oct 2023.
Nejadkoorki, F., Nicholson, K., Lake, I., & Davies, T. (2008). An approach for modelling CO2 emissions from road traffic in urban areas. Science of the Total Environment, 406(1–2), 269–278. https://doi.org/10.1016/j.scitotenv.2008.07.055
Nejadkoorki, F., Nicholson, K., & Hadad, K. (2011). The design of long-term air quality monitoring networks in urban areas using a spatiotemporal approach. Environment Monitoring Assessment, 172, 215–223. https://doi.org/10.1007/s10661-010-1328-4
Ott (1978). Water quality indices: A survey of indices used in the United States.
Perez Caseiras, C. (1988). Métodos de Diseño de Redes de Medida de Contaminantes Atmosféricos en Ambientes Industriales y Urbanos. Escuela Técnica Superior de Ingenieros Industriales, Universidad de Zaragoza.
Pittau, M. G., Romano, D., Cirillo, M. C., & Coppi, R. (1999). An optimal design for air pollution monitoring network. Environmetrics, 10(3), 351–360. https://doi.org/10.1002/(SICI)1099-095X(199905/06)10:33.0.CO;2-6
Pope, R., & Wu, J. (2014). A multi-objective assessment of an air quality monitoring network using environmental, economic, and social indicators and GIS-based models. Journal of the Air & Waste Management Association, 64(6), 721–737. https://doi.org/10.1080/10962247.2014.888378
QA Handbook Vol II, Section 6.0 Revision No: 1, Page 1 of 14. (2008).
Qiao, F., Li, Q., & Lei, Y. (2018). Particulate matter caused health risk in an urban area of the Middle East and the challenges in reducing its anthropogenic emissions. Environment Pollution and Climate Change, 2, 145. https://doi.org/10.4172/2573-458X.1000145
Sakhrieh, Ahmad & Hamdan, Mohammad & Ata, Mohammad. (2021). Air quality assessment and forecasting using neural network model. Journal of Ecological Engineering, 22, 1–11. https://doi.org/10.12911/22998993/137444.
Sangeetha, A., & Amudha, T. (2021). A particle swarm optimization methodology to design an effective air quality monitoring network. Environment Development and Sustainability, 23. https://doi.org/10.1007/s10668-021-01312-4.
Soares, P., De Rezende, D. C. G., & De Almeida, K. N. (2021). Optimal designing of air quality monitoring network around a port, in Bahia State. In 2021 Congreso Colombiano y Conferencia Internacional de Calidad de Aire y Salud Pública (CASAP). https://doi.org/10.1109/CASAP54985.2021.9703396.
Soleimani, M., & Amini, N. (2017). Source identification and apportionment of air pollutants in Iran. Air Pollution and Health, 2. Retrieved from https://api.semanticscholar.org/CorpusID:5017161. Accessed 18 Oct 2023.
Venegas, L. E., & Mazzeo, N. A. (2006). Modelling of urban background pollution in Buenos Aires City (Argentina). Environmental Modelling and Software, 21(4), 577–586. https://doi.org/10.1016/j.envsoft.2004.08.013
Verghese, S., & Nema, A. K. (2022). Optimal design of air quality monitoring networks: A systematic review. Stochastic Environmental Research and Risk Assessment, 1–16. https://doi.org/10.1007/s00477-022-02187-1.
Wang, C.-F., Hu, M.-C., Lee, C.-H., & Yu, H.-L. (2019). Optimization of air quality monitoring network based on a spatiotemporal-spectrum manifold analysis. Stochastic Environmental Research and Risk Assessment, 33, 1835–1849. https://doi.org/10.1007/s00477-019-01730-x
Wang, W., Liu, B., Peng, Y., & Jiang, Z. (2023). Design of buoy network in port water area for monitoring air pollution: A robust optimization approach. Ocean and Coastal Management, 244, 106816. https://doi.org/10.1016/j.ocecoaman.2023.106816
Yicun, G., Khorshiddoust, A. M., Mohammadi, G., Sadr, A., & Aghlmand, F. (2020). The relationship between PM2.5 concentrations and atmospheric conditions in severe and persistent urban pollution in Tabriz, northwest of Iran. Arabian Journal of Geosciences, 13. https://doi.org/10.1007/s12517-020-5128-z.
Zhang, H., Zhang, D., & Zhang, A. (2020). An innovative multifunctional buoy design for monitoring continuous environmental dynamics at Tianjin Port. IEEE Access, 8, 171820–171833. https://doi.org/10.1109/ACCESS.2020.3024020
Zheng, J., Feng, X., Liu, P., Zhong, L., & Lai, S. (2011). Site location optimization of regional air quality monitoring network in China: Methodology and case study. Journal of Environmental Monitoring, 13, 3185. https://doi.org/10.1039/c1em10560d
ZoroufchiBenis, K., Fatehifar, E., Ahmadi, J., & Rouhi, A. (2015). Optimal design of air quality monitoring network and its application in an oil refinery plant: An approach to keep health status of workers. Health Promotion Perspectives, 5(4), 269–279. https://doi.org/10.15171/hpp.2015.032
Acknowledgements
The authors thank the Environmental Protection Directorate of East Azerbaijan Province for providing monitoring station data.
Funding
The authors declare that no funds, grants, or other support was received during the preparation of this manuscript.
Author information
Authors and Affiliations
Contributions
Pedram vousoughi: Conceptualization, Investigation, Writing- Original draft preparation.
Leila Khazini: Idea of research, Data curation, Supervision, Validation.
Yousef Ali Abedini: Data curation.
Corresponding author
Ethics declarations
Ethics approval
Not applicable.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors have no relevant financial or non-financial interests to disclose.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Vousoughi, P., Khazini, L. & Abedini, Y. An optimized development of urban air quality monitoring network design based on particulate matters. Environ Monit Assess 196, 16 (2024). https://doi.org/10.1007/s10661-023-12192-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10661-023-12192-8