Health effects of shrinking hyper-saline lakes: spatiotemporal modeling of the Lake Urmia drought on the local population, case study of the Shabestar County
Manisalidis, L., Stavropoulou, E., Stavropoulos, A. & Bezirtzoglou, E. Environmental and health impacts of air pollution: A review. Front. Public Health https://doi.org/10.3389/fpubh.2020.00014 (2020).
Remoundou, K. & Koundouri, P. Environmental effects on public health: An economic perspective. Int. J. Environ. Res. Public Health https://doi.org/10.3390/ijerph6082160 (2009).
WHO. World Health Organisation. Air Pollution. Available online at: http://www.who.int/airpollution/en/ (2019).
Fradelos, E. C., Papathanasiou, I. V., Mitsi, D., TsarasK, K. C. F. & Kourkouta, L. Health based geographic information systems (GIS) and their applications. Acta Inform. Med. 22(6), 402 (2014).
Sterner, S. W., Keeler, B., Polasky, S., Poudel, R. & Rhude, K. Ecosystem services of Earth’s largest freshwater lakes. Ecosyst. Serv. https://doi.org/10.1016/j.ecoser.2019.101046 (2020).
Feizizadeh, B. et al. Scenario-based analysis of the impacts of lake drying on food production. Sci. Rep. Nat. https://doi.org/10.1038/s41598-022-10159-2 (2022).
Feizizadeh, B., Kazamei Garajeh, M., Blaschke, T. & Lakes, T. A deep learning convolutional neural network algorithm for detecting saline flow sources and mapping the environmental impacts of the Urmia Lake drought in Iran. CATENA https://doi.org/10.1016/j.catena.2021.105585 (2021).
Aili, A. & Nguyen Thi, K. O. Effects of dust storm on public health in desert fringe area: Case study of northeast edge of Taklimakan Desert, China. Atmos. Pollut. Res. 6, 805T814 (2015).
WMO. World Meteorological Organization. Sand and Dust Storms. Available online: https://public.wmo.int/en/our-mandate/focus-areas/environment/SDS (2021).
Schepanski, K. Transport of mineral dust and ist impact on climate. Geoscience 8, 151 (2018).
Opp, C., Groll, M., Abbasi, H. & Ahmadi, F. M. Causes and effects of sand and dust storms: What has past research taught us? A survey. J. Risk Financ. Manag. 14, 326. https://doi.org/10.3390/jrfm14070326 (2021).
Palencia, I. A. et al. Associations of urban environment features with hypertension and blood pressure across 230 Latin American cities. Environ. Health Perspect. https://doi.org/10.1289/EHP7870 (2022).
Sakiev K.Z. On evaluation of public health state in Aral Sea area. Meditsina Truda i Promyshlennaia Ekologiia. 1–4. PMID: 25549450 (2014).
Kazemi Garajeh, M. et al. An automated deep learning convolutional neural network algorithm applied for soil salinity distribution mapping in Lake Urmia, Iran. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2021.146253 (2021).
Beelen, R. et al. Effects of long-term exposure to air pollution on natural-cause mortality: An analysis of 22 European cohorts within the multicentre ESCAPE project. Lancet 383(9919), 785–795 (2014).
Saadat, S., Sadeghian, S., Lotfi, M. & Najafi, M. A. Urban air pollution and emergency visits and in hospital mortality in Tehran heart center, International Society for Environmental Epidemiology (ISEE). Abstract Indication in Environmental Health Perspective. https://doi.org/10.1289/isee.2011.00484 (2011).
Serensen, M. et al. Long-term exposure to traffic-related air pollution associated with blood pressure and self-reported hypertension in a Danish Cohort. Environ. Health Perspect. 120(30), 418–424 (2012).
Foraster, M. et al. High blood pressure and long-term exposure to indoor noise and air pollution from road traffic. Environ. Health Perspect. 122(4), 404–411 (2014).
Hashizume, M. et al. Health effects of Asian dust: A systematic review and meta-analysis. Environ. Health Perspect. https://doi.org/10.1289/EHP5312 (2020).
Resnik, D. B. Human health and the environment: in harmony or in conflict?. Health Care Anal. HCA J. Health Philos. Policy 17(3), 261–276 (2009).
Boldt, J. The concept of vulnerability in medical ethics and philosophy. Philos. Ethics Humanit. Med. PEHM 14(1), 6. https://doi.org/10.1186/s13010-019-0075-6 (2019).
Reid, C. E. et al. Mapping community determinants of heat vulnerability. Environ. Health Perspect. 117(11), 1730–1736 (2009).
Fletcher Lartey, S. & Caprarelli, G. Application of GIS technology in public health: Successes and challenges. Parasitology 143(4), 401–415 (2016).
Musa, G. J. et al. Use of GIS mapping as a public health tool—From cholera to cancer. Health Serv. Insights 6, HSI-S10471 (2013).
Sharma S. K. Role of remote sensing and GIS in integrated water resources management (IWRM). In Ground Water Development-Issues and Sustainable Solutions 211–227 (Springer, 2019).
Parsinejad, M. et al. 40-years of Lake Urmia restoration research: Review, synthesis and next steps. Sci. Total Environ. 832(1), 155055 (2022).
Feizizadeh, B. et al. Impacts of the Urmia Lake drought on soil salinity and erosion risk: An integrated Geoinformatics analysis and monitoring approach. Remote Sens. 14, 3407. https://doi.org/10.3390/rs14143407 (2022).
Hassanzadeh, E., Zarghami, M. & Hassanzadeh, Y. Determining the main factors in declining the Urmia Lake level by using system dynamics modeling. Water Resour. Manag. 26, 129–145. https://doi.org/10.1007/S11269-011-9909-8 (2012).
Alizade Govarchin Ghale, Y., Altunkaynak, A. & Unal, A. Investigation anthropogenic impacts and climate factors on drying up of Urmia Lake using water budget and drought analysis. Water Resour. Manag. 32, 325–337. https://doi.org/10.1007/S11269-017-1812-5 (2018).
Pooralihossein, S. & Delavar, M. A multi-model ensemble approach for the assessment of climatic and anthropogenic impacts on river flow change. Hydrol. Sci. J. 65(1), 71–86. https://doi.org/10.1080/02626667.2019.1682148 (2020).
Isazade, V., Qasimi, A. B. & Kaplan, G. Investigation of the effects of salt dust caused by drying of Urmia Lake on the sustainability of urban environments. J. Clean WAS 5(2), 78–84 (2021).
Alizadeh Motaghi, F., Hamzehpour, N., Mola Ali Abasiyan, S. & Rahmati, M. The wind erodibility in the newly emerged surfaces of Urmia Playa Lake and adjacent agricultural lands and its determining factors. CATENA 194, 10467 (2020).
Roshan, G., Samakosh, J. & Orosa, J. The impacts of drying of Lake Urmia on changes of degree day index of the surrounding cities by meteorological modelling. Environ Earth Sci. https://doi.org/10.1007/S12665-016-6200-6 (2016).
Mehrian, M. R., Hernandez, R. P., Yavari, A. R., Faryadi, S. & Salehi, E. Investigating the causality of changes in the landscape pattern of Urmia Lake basin, Iran using remote sensing and time series analysis. Environ. Monit. Assess. 188(8), 462 (2016).
Valizadeh, K. & Namdari, S. Temporal-spatial analysis of aerosols trend in the zone of influence Urmia aerosols by processing of satellite imageries in 2000–2015 (case study: East Azerbaijan and West Azerbaijan). Geogr. Plan. 24(72), 427–446 (2020).
Hamidi, S. M., Fürst, C., Nazmfar, H., Rezayan, A. & Yazdani, M. H. A future study of an Environment Driving Force (EDR): The impacts of Urmia Lake water-level fluctuations on human settlements. Sustainability 13, 11495. https://doi.org/10.3390/su132011495 (2021).
Hassan, N. A., Hashim, Z. & Hashim, J. H. Impact of climate change on air quality and public health in urban areas. Asia Pac. J. Public Health 28(2_suppl), 38S-48S (2016).
Kelishadi, R. & Poursafa, P. Air pollution and non-respiratory health hazards for children. Arch. Med. Sci. AMS 6(4), 483 (2010).
Barzegar, R. et al. Heavy metal (loid) s in the groundwater of Shabestar area (NW Iran): Source identification and health risk assessment. Expo. Health 11(4), 251–265 (2019).
NIFHR: National Institute for Health Research Islamic Republic Iran. https://nih.tums.ac.ir (2020).
RITUMS: Research Institute of Tehran University of Medical Sciences. Atlas of Non-Communicable Diseases Risk-Factors Surveillance in the Islamic Republic of Iran: STEPs 2016. https://en.tums.ac.ir/ (2016).
Kolahi, A. A., Moghisi, A. & Ekhtiari, Y. S. Socio-demographic determinants of obesity indexes in Iran: Findings from a nationwide STEPS survey. Health Promot. Perspect. 8(3), 187 (2018).
Zinab, H. E., Kalantari, N., Ostadrahimi, A., Tabrizi, J. S. & Pourmoradian, S. A Delphi study for exploring nutritional policy priorities to reduce prevalence of non-communicable diseases in Islamic Republic of Iran. Health Promot. Perspect. 9(3), 241 (2019).
Kazemi Shishavan, M., Asghari Jafarabadi, M., Aminisani, N., Shahbazi, M. & Alizadeh, M. The association between self-care and quality of life in hypertensive patients: Findings from the Azar cohort study in the North West of Iran. Health Promot Perspect. 8(2), 139–146 (2018).
Feizizadeh, B., Omarzadeh, D., Kazemi Garajeh, M., Lakes, T. & Blaschke, T. Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine. J. Environ. Plan. Manag. https://doi.org/10.1080/15481603.2021.2000350 (2021).
Feizizadeh, B., Ronagh, Z., Pourmoradian, S., Gheshlaghi, H. A. & LakesT, B. T. An efficient GIS-based approach for sustainability assessment of urban drinking water consumption patterns: A study in Tabriz city, Iran. Sustain. Cities Soc. 64, 102584 (2021).
Sazib, N., Mladenova, I. & Bolten, J. Leveraging the google earth engine for drought assessment using global soil moisture data. Remote Sens. 10(8), 1265 (2018).
Fu, W. J., Jiang, P. K., Zhou, G. M. & Zhao, K. L. Using Moran’s I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China. Biogeosciences 11(8), 2401–2409 (2014).
Nazmfar, H., Alavi, S., Feizizadeh, B. & Mostafavi, M. A. Analysis of spatial distribution of crimes in urban public spaces. J. Urban Plan. Dev. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000549 (2020).
Yuan, Y., Cave, M. & Zhang, C. Using Local Moran’s I to identify contamination hotspots of rare earth elements in urban soils of London. Appl. Geochem. https://doi.org/10.1016/j.apgeochem.2017.07.011 (2017).
Zhang, T. & Lin, G. A decomposition of Moran’s I for clustering detection. Comput. Stat. Data Anal. 51(12), 6123–6137 (2007).
Abdollahizad, S., Balafar, M. A., Feizizadeh, B., SangarA, B. & Samadzamini, K. Using hybrid artificial intelligence approach based on a neuro-fuzzy system and evolutionary algorithms for modeling landslide susceptibility in East Azerbaijan Province, Iran. Earth Sci. Inform. https://doi.org/10.1007/s12145-021-00644-z (2021).
Ebrahimy, H., Feizizadeh, B., Salmani, S. & Azadi, H. A comparative study of land subsidence susceptibility mapping of Tasuj plane, Iran, using boosted regression tree, random forest and classifcation and regression tree methods. Environ. Earth Sci. https://doi.org/10.1007/s12665-020-08953-0 (2020).
Malczewski, J & Rinner, C.. Introduction to GIS-mcda. In Multicriteria Decision Analysis in Geographic Information Science 23–54 (Springer, 2015).
Abedi Gheshlaghi, H., Feizizadeh, B. & Blaschke, T. GIS-based forest fire risk mapping using the analytical network process and fuzzy logic. J. Environ. Plan. Manag. 63(3), 481–499 (2020).
Omarzadeh, D. et al. A GIS-based multiple ecotourism sustainability assessment of West Azerbaijan province, Iran. J. Environ. Plan. Manag. https://doi.org/10.1080/09640568.2021.1887827 (2021).
Morra, P., Bagli, S. & Spadoni, G. The analysis of human health risk with a detailed procedure operatingin a GIS environment. Environ. Int. 32, 444–454 (2006).
Poggio, L. & Vrscaj, B. A GIS-based human health risk assessment for urban green space planning—An example from Grugliasco (Italy). Sci Total Environ. 407(23), 5961–5970 (2009).
Ekenberg, L., Mihai, M., Fasth, T., Komendantova, N. & Danielson, M. A multi-criteria framework for pandemic response measures. Front. Public Health https://doi.org/10.3389/fpubh.2021.583706 (2021).
Lopes, D. F., Marques, J. L. & Castro, E. A. A MCDA/GIS-based approach for evaluating accessibility to health facilities. In Computational Science and Its Applications, ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science Vol. 12952 (eds Gervasi, O. et al.) (Springer, 2021). https://doi.org/10.1007/978-3-030-86973-1_22.
Devarakonda, P., Sadasivuni, R., Nobrega, R. A. A. & Wu, G. Application of spatial multicriteria decision analysis in healthcare: Identifying drivers and triggers of infectious disease outbreaks using ensemble learning. J. Multi-Criteria Decis. Anal. https://doi.org/10.1002/mcda.1732 (2021).
Saaty, T. L. & Vargas, L. G. Decision Making with the Analytic Network Process: Economic, Political, Social and Technological Applications with Benefits, Opportunities, Costs and Risks Vol. 195 (Springer Science and Business Media, 2013).
Naboureh, A. et al. Traffic accident spatial simulation modeling for planning of road emergency services. ISPRS Int. J. Geo Inf. 8, 371 (2019).
Mohamadzadeh, P., Pourmoradian, S., Feizizadeh, B., Sharifi, A. & Vogdrup-Schmidt, M. A GIS-based approach for spatially-explicit sustainable development assessments in East Azerbaijan Province, Iran. Sustainability https://doi.org/10.3390/su122410413 (2020).
Valizadeh, K. K., Feizizadeh, B., Khorrami, B. & Ebadi, Y. A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping. Appl. Geomat. https://doi.org/10.1007/s12518-021-00393-0 (2021).
Gu, H., Lao, X. & Shen, T. Research progress on spatial demography. In Spatial Synthesis 125–145 (2020).
Kahraman, C., Onar, S. C. & Oztaysi, B. Fuzzy multicriteria decision-making: A literature review. Int. J. Comput. Intell. Syst. 8(4), 637–666 (2015).
Feizizadeh, B. & Blaschke, T. An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping. Int. J. Geogr. Inf. Sci. 28(3), 610–638 (2014).
Ligmann-Zielinska, A. & Jankowski, P. Spatially-explicit integrated uncertainty and sensitivity analysis of criteria weights in multicriteria land suitability evaluation. Environ. Model. Softw. 57, 235–247 (2014).
Keenan, P. B. & Jankowski, P. Spatial decision support systems: Three decades on. Decis. Support Syst. 116, 64–76 (2019).
Haghshenas, E., Gholamalifard, M., Mahmoudi, N. & Kutser, T. Developing a GIS-based decision rule for sustainable marine aquaculture site selection: An application of the ordered weighted average procedure. Sustainability 13(5), 2672 (2021).
Feizizadeh, B. & Blaschke, T. GIS-multicriteria decision analysis for landslide susceptibility mapping: Comparing three methods for the Urmia lake basin, Iran. Nat. Hazards 65(3), 2105–2128 (2013).
Feizizadeh, B. & Kienberger, S. Spatial explicit sensitivity and uncertainty analysis for multicriteria based vulnerability assessment. J. Environ. Plan. Manag. 60(11), 2013–2035 (2017).
Khashoggi, B. F. & Murad, A. Issues of healthcare planning and GIS: A review. ISPRS Int. J. Geo Inf. 9(6), 352 (2020).
Pickle L.W. Spatial analysis of disease. In Biostatistical Applications in Cancer Research 113–115 (Springer, 2002).
Sarwar, S., Waheed, R., Sarwar, S. & Khan, A. COVID-19 challenges to Pakistan: Is GIS analysis useful to draw solutions. Sci. Total Environ. 730, 139089 (2020).
Bag, R., Ghosh, M., Biswas, B. & Chatterjee, M. Understanding the spatio-temporal pattern of COVID-19 outbreak in India using GIS and India’s response in managing the Pandemic. Reg. Sci. Policy Pract. https://doi.org/10.1111/rsp3.12359 (2020).
Wang, S., Zhang, L., Zhang, H., Han, X. & Zhang, L. Spatial-temporal wetland landcover changes of Poyang Lake derived from Landsat and HJ-1A/B data in the dry season from 1973–2019. Remote Sens. 12(10), 1595 (2020).
Gholampour, A. et al. Physicochemical characterization of ambient air particulate matter in Tabriz, Iran. Bull. Environ. Contam. Toxicol. 92(6), 738–744 (2014).
Gholampour, A., Nabizadeh, R., Hassanvand, M. S., Nazmara, S. & Mahvi, A. M. Characterization of saline dust emission resulted from Urmia Lake drying. J. Environ. Health Sci. Eng. https://doi.org/10.1186/s40201-015-0238-3 (2015).
Gholampour, A., Nabizadeh, R., Hassanvand, M. S., Nazmara, S. & Mahvi, A. M. Elemental composition of particulate matters around Urmia Lake, Iran. Toxicol. Environ. Chem. 99(1), 17–31. https://doi.org/10.1080/02772248.2016.116622 (2017).
Boroughani, M., Hashemi, H., Hosseini, S. H., Pourhashemi, S. & Berndtsson, R. Desiccating Lake Urmia: A new dust source of regional importance. IEEE Geosci. Remote Sens. Lett. 17(9), 1483–1487 (2019).
Boroughani, M., Hashemi, H., Hosseini, S. H., Pourhashemi, S. & Berndtsson, R. Desiccating Lake Urmia: A new dust source of regional importance. IEEE Geosci. Remote Sens. Lett. 17(9), 1483–1487. https://doi.org/10.1109/LGRS.2019.2949132 (2020).
Alizade Govarchin Ghale, Y., Tayanc, M. & Unal, A. Impacts of drying up of Urmia Lake, the second largest hypersaline lake in the world, on particulate concentration in the northwestern Iran. In 19th Annual CMAS Conference, Chapel Hill, NC, October 26–28, 2020 (2020).
Alizade Govarchin Ghale, Y., Tayanc, M. & Unal, A. Dried bottom of Urmia Lake as a new source of dust in the northwestern Iran: Understanding the impacts on local and regional air quality. Atmos. Environ. https://doi.org/10.1016/j.atmosenv.2021.118635 (2021).
Ghale, Y. A. G., Unal, A. & Baykara, M. Impacts of drying up of Urmia Lake, the second largest hypersaline lake in the world, on particulate matter concentration in northwestern Iran. In Conference: 19th Annual CMAS Conference, Chapel Hill, NC, October 26–28, 2020 (2020).
Ghale, Y. A. G., Tayanc, M. & Unal, A. Dried bottom of Urmia Lake as a new source of dust in northwestern Iran: Understanding the impacts on local and regional air quality. Atmos. Environ. 262, 118635 (2021).
Kirby, R. S., Delmelle, E. & Eberth, J. M. Advances in spatial epidemiology and geographic information systems. Ann. Epidemiol. 27(1), 1–9 (2017).
Zhou, C. et al. COVID-19: Challenges to GIS with big data. Geogr. Sustain. 1(1), 77–87 (2020).
Kokabisaghi, F. Assessment of the effects of economic sanctions on Iranians’ right to health by using human rights impact assessment tool: A systematic review. Int. J. Health Policy Manag. 7(5), 374–393 (2018).