Skip to main content

Advertisement

SpringerLink
Log in

Advancing the mapping of optimal land use structure in industrialized areas: incorporating AERMOD modeling and MCE approach

  • Published:
GeoJournal Aims and scope Submit manuscript

Abstract

Land use planning has been mainly implemented based on land capabilities but rarely on land limitations such as air pollution. This study aims to simulate the optimal land use structure by incorporating the air quality into the land use planning process using MCE and MOLA in an industrialized area in Isfahan province, central Iran. To do so, we developed two scenarios as 'with-' and 'without-' considering the air pollution criterion. The optimal land use planning was applied for agricultural, urban, and industrial land uses. PM10 and NOX seasonal (winter) dispersion maps were used as the air pollution criterion which was simulated by AERMOD. We applied the Best Worst Method (BWM) to standardize and weight the physical, ecological, and socio-economic criteria. Accordingly, we used an Ordered Weighted Average (OWA) technique to combine the factors. Assuming 1% (1100 ha) of the land area available for future allocation to each land use, we compared the outcomes of both scenarios revealed a significant difference between the coverage of capable areas. The results of the “with” scenario indicated that approximately 11, 17, and 54% of the area that were, in fact, incapable for agricultural, industrial, and urban developments, respectively. These areas are detected as capable if we leave the air pollution criterion out. The findings demonstrated that to achieve sustainable development, it is necessary to consider dynamic physical land components including air pollution along with ecological, physical, and socio-economic factors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability

The supplementary materials contain additional information and data pertinent to this article.

References

  • Ajtai, N., Stefanie, H., Botezan, C., Ozunu, A., Radovici, A., Dumitrache, R., et al. (2020). Support tools for land use policies based on high resolution regional air quality modelling. Land Use Policy. https://doi.org/10.1016/j.landusepol.2019.03.022

    Article  Google Scholar 

  • Arefiev, N., Terleev, V., & Badenko, V. (2015). GIS-based fuzzy method for urban planning. Procedia Engineering, 117, 39–44.

    Article  Google Scholar 

  • Arku, R. E., Brauer, M., Ahmed, S. H., AlHabib, K. F., Avezum, Á., Bo, J., et al. (2020). Long-term exposure to outdoor and household air pollution and blood pressure in the Prospective Urban and Rural Epidemiological (PURE) study. Environmental Pollution. https://doi.org/10.1016/j.envpol.2020.114197

    Article  Google Scholar 

  • Ashtari, F., Esmaeil, N., Mansourian, M., Poursafa, P., Mirmosayyeb, O., Barzegar, M., & Pourgheisari, H. (2018). An 8-year study of people with multiple sclerosis in Isfahan, Iran: Association between environmental air pollutants and severity of disease. Journal of Neuroimmunology, 319, 106–111.

    Article  Google Scholar 

  • Bartkowski, B., Beckmann, M., Drechsler, M., Kaim, A., Liebelt, V., Müller, B., et al. (2020). Aligning agent-based modelling with multi-objective land-use allocation: Identification of policy gaps and feasible pathways to biophysically optimal landscapes. Frontiers in Environmental Science. https://doi.org/10.3389/fenvs.2020.00103

    Article  Google Scholar 

  • Bayat, R., Ashrafi, K., Motlagh, M. S., Hassanvand, M. S., Daroudi, R., Fink, G., & Künzli, N. (2019). Health impact and related cost of ambient air pollution in Tehran. Environmental Research. https://doi.org/10.1016/j.envres.2019.108547

    Article  Google Scholar 

  • Bergstra, A. D., Brunekreef, B., & Burdorf, A. (2018). The effect of industry-related air pollution on lung function and respiratory symptoms in school children. Environmental Health, 17(1), 1–9.

    Article  Google Scholar 

  • Brunekreef, B. (2010). Air pollution and human health: From local to global issues. Procedia-Social and Behavioral Sciences, 2(5), 6661–6669.

    Article  Google Scholar 

  • Cai, J., Yu, S., Pei, Y., Peng, C., Liao, Y., Liu, N., et al. (2018). Association between airborne fine particulate matter and residents’ cardiovascular diseases, ischemic heart disease and cerebral vascular disease mortality in areas with lighter air pollution in China. International Journal of Environmental Research and Public Health. https://doi.org/10.3390/ijerph15091918

    Article  Google Scholar 

  • Chatterjee, P., & Stević, Ž. (2019). A two-phase fuzzy AHP-fuzzy TOPSIS model for supplier evaluation in manufacturing environment. Operational Research in Engineering Sciences: Theory and Applications, 2(1), 72–90.

    Google Scholar 

  • Clougherty, J. E., Levy, J. I., Kubzansky, L. D., Ryan, P. B., Suglia, S. F., Canner, M. J., & Wright, R. J. (2007). Synergistic effects of traffic-related air pollution and exposure to violence on urban asthma etiology. Environmental Health Perspectives, 115(8), 1140–1146.

    Article  Google Scholar 

  • Colls, J., & Tiwary, A. (2010). Air pollution Measurment. Modeling and mitigation. Routlege.

    Google Scholar 

  • El Baroudy, A. A. (2016). Mapping and evaluating land suitability using a GIS-based model. CATENA, 140, 96–140.

    Article  Google Scholar 

  • Emberson, L. D., Ashmore, M. R., Murray, F., Kuylenstierna, J. C. I., Percy, K. E., Izuta, T., et al. (2001). Impacts of air pollutants on vegetation in developing countries. Water, Air, and Soil Pollution, 130(1), 107–118.

    Article  Google Scholar 

  • Emovon, I., & Oghenenyerovwho, O. S. (2020). Application of MCDM method in material selection for optimal design: A review. Results in Materials. https://doi.org/10.1016/j.rinma.2020.100115

    Article  Google Scholar 

  • Erfanmanesh, M., & Afyuni, M. (2012). Environmental pollution: Water, soil and air. Arkan Isfahan Publishing.

    Google Scholar 

  • Esmaeilzadeh, M., Bazrafshan, E., & Nasrabadi, M. (2013). Dispersion Modeling of NOX and SO2 Emissions from Tous Gas Power Plant. Iranian Journal of Health and Environment, 6(1), 77–90.

    Google Scholar 

  • Ghadirian, O., Moradi, H., Madadi, H., Lotfi, A., & Senn, J. (2019). Identifying noise disturbance by roads on wildlife: A case study in central Iran. SN Applied Sciences. https://doi.org/10.1007/s42452-019-0838-0

    Article  Google Scholar 

  • Hajehforooshnia, S., Soffianian, A., Mahiny, A. S., & Fakheran, S. (2011). Multi objective land allocation (MOLA) for zoning Ghamishloo Wildlife Sanctuary in Iran. Journal for Nature Conservation, 19(4), 254–262.

    Article  Google Scholar 

  • Han, L., Zhou, W., Li, W., Meshesha, D. T., Li, L., & Zheng, M. (2015). Meteorological and urban landscape factors on severe air pollution in Beijing. Journal of the Air & Waste Management Association, 65(7), 782–787.

    Article  Google Scholar 

  • Kang, B., Deng, Y., Hewage, K., & Sadiq, R. (2018). Generating Z-number based on OWA weights using maximum entropy. International Journal of Intelligent Systems. https://doi.org/10.1002/int.21995

    Article  Google Scholar 

  • Kelishadi, R., Moeini, R., Poursafa, P., Farajian, S., Yousefy, H., & Okhovat-Souraki, A. A. (2014). Independent association between air pollutants and vitamin D deficiency in young children in Isfahan. Iran. Paediatrics and International Child Health, 34(1), 50–55.

    Article  Google Scholar 

  • Khaniabadi, Y. O., Sicard, P., Taiwo, A. M., De Marco, A., Esmaeili, S., & Rashidi, R. (2018). Modeling of particulate matter dispersion from a cement plant: Upwind-downwind case study. Journal of Environmental Chemical Engineering. https://doi.org/10.1016/j.jece.2018.04.022

    Article  Google Scholar 

  • Khavarian-Garmsir, A. R., & Rezaei, M. R. (2015). Selection of appropriate locations for industrial areas using GIS-fuzzy methods. A case study of Yazd Township, Iran. Journal of Settlements and Spatial Planning, 6(1), 19–25.‏

  • Kleemann, J., Inkoom, J. N., Thiel, M., Shankar, S., Lautenbach, S., & Fürst, C. (2017). Peri-urban land use pattern and its relation to land use planning in Ghana, West Africa. Landscape and Urban Planning, 165, 280–294.

    Article  Google Scholar 

  • Krishna, A. K., & Govil, P. K. (2004). Heavy metal contamination of soil around Pali industrial area, Rajasthan. India. Environmental Geology, 47(1), 38–44.

    Article  Google Scholar 

  • Kuo, Y. C., Lu, S. T., Tzeng, G. H., Lin, Y. C., & Huang, Y. S. (2013). Using fuzzy integral approach to enhance site selection assessment–a case study of the optoelectronics industry. Procedia Computer Science, 17, 306–313.

    Article  Google Scholar 

  • Li, H., Tan, X., Guo, J., Zhu, K., & Huang, C. (2019). Study on an implementation scheme of synergistic emission reduction of CO2 and air pollutants in China’s steel industry. Sustainability. https://doi.org/10.3390/su11020352

    Article  Google Scholar 

  • Liu, R., Zhang, K., Zhang, Z., & Borthwick, A. G. (2014). Land-use suitability analysis for urban development in Beijing. Journal of Environmental Management, 145, 170–179.

    Article  Google Scholar 

  • Lu, D., Mao, W., Yang, D., Zhao, J., & Xu, J. (2018). Effects of land use and landscape pattern on PM2.5 in Yangtze River Delta, China. Atmospheric Pollution Research, https://doi.org/10.1016/j.apr.2018.01.012.‏

  • Makhdom, M. (1999). Fundamental of land use planning. Tehran: publication of Tehran University.

  • Masoudi, M., Centeri, C., Jakab, G., Nel, L., & Mojtahedi, M. (2021). GIS-Based Multi-Criteria and Multi-Objective Evaluation for Sustainable Land-Use Planning (Case Study: Qaleh Ganj County, Iran)“Landuse Planning Using MCE and Mola.” International Journal of Environmental Research, 15(3), 457–474.

    Article  Google Scholar 

  • Memarbashi, E., Azadi, H., Barati, A. A., Mohajeri, F., Passel, S. V., & Witlox, F. (2017). Land-use suitability in Northeast Iran: Application of AHP-GIS hybrid model. ISPRS International Journal of Geo-Information. https://doi.org/10.3390/ijgi6120396

    Article  Google Scholar 

  • Mendy, A., Wilkerson, J., Salo, P. M., Weir, C. H., Feinstein, L., Zeldin, D. C., & Thorne, P. S. (2019). Synergistic association of house endotoxin exposure and ambient air pollution with asthma outcomes. American Journal of Respiratory and Critical Care Medicine, 200(6), 712–720.

    Article  Google Scholar 

  • Mohammad shaeri, A., & Rahmati, A. R. (2013). Humans enviroment rules - provision criteria and standards. Hak.

    Google Scholar 

  • Moradi, H., Abbasi, M., & Soleimani, M. (2021). Bioaccumulation of heavy metals in Stachys inflata and Scariola orientalis affected by particulate matters of a cement factory in central Iran. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-13552-y

    Article  Google Scholar 

  • Norbäck, D., Lu, C., Zhang, Y., Li, B., Zhao, Z., Huang, C., et al. (2019). Sources of indoor particulate matter (PM) and outdoor air pollution in China in relation to asthma, wheeze, rhinitis and eczema among pre-school children: Synergistic effects between antibiotics use and PM10 and second hand smoke. Environment International, 125, 252–260.

    Article  Google Scholar 

  • Poursafa, P., Kelishadi, R., Amini, A., Amini, A., Amin, M. M., Lahijanzadeh, M., & Modaresi, M. (2011a). Association of air pollution and hematologic parameters in children and adolescents. Jornal De Pediatria. https://doi.org/10.2223/JPED.2115

    Article  Google Scholar 

  • Poursafa, P., Kelishadi, R., Moattar, F., Rafiee, L., Amin, M. M., Lahijanzadeh, A., & Javanmard, S. H. (2011b). Genetic variation in the association of air pollutants with a biomarker of vascular injury in children and adolescents in Isfahan. Iran. Journal of Research in Medical Sciences: THe Official Journal of Isfahan University of Medical Sciences, 16(6), 733–740.

    Google Scholar 

  • Rashidi, M., Ramesht, M. H., Zohary, M., Poursafa, P., Kelishadi, R., Rashidi, Z., & Rouzbahani, R. (2013). Relation of air pollution with epidemiology of respiratory diseases in isfahan, Iran from 2005 to 2009. Journal of Research in Medical Sciences: THe Official Journal of Isfahan University of Medical Sciences, 18(12), 1074–1079.

    Google Scholar 

  • Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega. https://doi.org/10.1016/j.omega.2014.11.009

    Article  Google Scholar 

  • Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega. https://doi.org/10.1016/j.omega.2015.12.001

    Article  Google Scholar 

  • Romano, G., Dal Sasso, P., Liuzzi, G. T., & Gentile, F. (2015). Multi-criteria decision analysis for land suitability mapping in a rural area of Southern Italy. Land Use Policy, 48, 131–143.

    Article  Google Scholar 

  • Sarwar, M. T., & Maqbool, A. (2019). Causes and control measures of urban air pollution in China. Environment & Ecosystem Science (EES), 3(1), 35–36.

    Article  Google Scholar 

  • Seangkiatiyuth, K., Surapipith, V., Tantrakarnapa, K., & Lothongkum, A. W. (2011). Application of the AERMOD modeling system for environmental impact assessment of NO2 emissions from a cement complex. Journal of Environmental Sciences, 23(6), 931–940.

    Article  Google Scholar 

  • Shafiezadeh, M., Moradi, H., & Fakheran, S. (2018). Evaluating and modeling the spatiotemporal pattern of regional-scale salinized land expansion in highly sensitive shoreline landscape of southeastern Iran. Journal of Arid Land, 10(6), 946–958.

    Article  Google Scholar 

  • Shafiezadeh, M., Moradi, H., Fakheran, S., Pourmanafi, S., & Senn, J. (2019). Integrated coastal-terrestrial conservation planning for landscape-scale reserve design in Southeastern Iran. Ecological Indicators. https://doi.org/10.1016/j.ecolind.2019.03.006

    Article  Google Scholar 

  • Shi, Y., Ren, C., Lau, K. K. L., & Ng, E. (2019). Investigating the influence of urban land use and landscape pattern on PM2. 5 spatial variation using mobile monitoring and WUDAPT. Landscape and urban planning, https://doi.org/10.1016/j.landurbplan.2019.04.004.‏

  • Siddika, N., Rantala, A. K., Antikainen, H., Balogun, H., Amegah, A. K., Ryti, N. R., et al. (2019). Synergistic effects of prenatal exposure to fine particulate matter (PM2.5) and ozone (O3) on the risk of preterm birth: A population-based cohort study. Environmental research, https://doi.org/10.1016/j.envres.2019.108549.

  • Vali, A. A., Mousavi, S. H., & Abbasi, H. (2019). Analysis and evaluation of landuse changes trend in Mobarakeh in order to achieve the sustainable development. Journal of Urban Social Geography, 6(2), 73–86.

    Google Scholar 

  • Wang, X., Manning, W., Feng, Z., & Zhu, Y. (2007). Ground-level ozone in China: Distribution and effects on crop yields. Environmental Pollution, 147(2), 394–400.

    Article  Google Scholar 

  • Wei, J., Guo, X., Marinova, D., & Fan, J. (2014). Industrial SO2 pollution and agricultural losses in China: Evidence from heavy air polluters. Journal of Cleaner Production, 64, 404–413.

    Article  Google Scholar 

  • Yaylalı-Abanuz, G. (2011). Heavy metal contamination of surface soil around Gebze industrial area. Turkey. Microchemical Journal, 99(1), 82–92.

    Article  Google Scholar 

  • Yu, Y., Jin, Z. X., & Jia, L. (2020). Low-carbon development path research on China’s power industry based on synergistic emission reduction between CO2 and air pollutants. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2020.123097

    Article  Google Scholar 

  • Zhang, Q., & Wang, K. (2010). Evaluating production risks for wheat producers in Beijing. China Agricultural Economic Review, 2(2), 200–211.

    Article  Google Scholar 

Download references

Acknowledgements

We thank Dr. Mohsen Soleimani and Alireza Mohseni for their assistance in providing data. We thank also Omid Ghadirian for helping during the air pollution modeling.

Author information

Authors and Affiliations

  1. Department of Natural Resources, Isfahan University of Technology, 84156-83111, Isfahan, Iran

    Reza Peykanpour Fard, Hossein Moradi, Ali Lotfi, Saeid Pourmanafi & Neda Bihamta Toosi

Authors
  1. Reza Peykanpour Fard
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hossein Moradi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ali Lotfi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Saeid Pourmanafi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Neda Bihamta Toosi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hossein Moradi.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest

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 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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Peykanpour Fard, R., Moradi, H., Lotfi, A. et al. Advancing the mapping of optimal land use structure in industrialized areas: incorporating AERMOD modeling and MCE approach. GeoJournal 88, 1979–1995 (2023). https://doi.org/10.1007/s10708-022-10716-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10708-022-10716-2

Keywords

Search

Navigation