Document Type : Original quantitative and Qualitative Research Article
Authors
1 Department of environmental sciences, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
2 Department of environmental science, Isfahan (Khorasgan) branch, Islamic Azad University, Isfahan, Iran
Abstract
Background and purpose: Regarding the status of air pollution in Isfahan, this study aims to evaluate the air quality of Isfahan due to Particulate Matter and find the relationship between landscape patterns and suspended particles.
Materials and methods: to measure the concentration of the suspended particles using a Met One dust meter in 52 points, the city was randomly sampled. The land use map of Isfahan city was prepared after downloading satellite images from the site of the United States Geological Survey. The land use map was generated in six classes with the maximum likelihood classification method in Terrset software. To create the distribution map of suspended particles, the information of 52 stations and inverse distance weighting method in ArcGIS 10.5 was used. Landscape metrics (Normalized Entropy, Edge Density, Patch Area, Relative Richness, and Patch Compactness) were used to quantify the pattern of landscape. The landscape metrics were quantified using FRAGSTATS software.
Results: The results showed that vegetation has a reducing effect on air pollution. A positive and significant correlation was observed between the amount of suspended particles and relative richness. Moreover, a significant negative correlation was observed between PM2.5 and (NDVI), which means that the amount of suspended particles decreased with increasing vegetation density.
Conclusion: In general, by calculating the concentration of suspended particles in Isfahan, it was found that the southwest, south, and southeast are exposed to more suspended particles. The high density of green space landscaping leads to a reduction of particulate matter pollution. From the analysis of changes in suspended particles in the region, it was inferred that the more we move to areas with weaker vegetation, the higher the concentration of suspended particles.
Keywords
- Talebi Amiri Sh, Azari Dehkordi F, Sadeghi S.H, Soofbaf S.R, 2009. Study on Landscape Degradation in Neka Watershed Using Landscape Metrics, Environmental Sciences, 3(6): 133-144. (Persian)
- Paudel S, Yuan F, 2012. Assessing landscape changes and dynamics using patch analysis and GIS modeling. International Journal of Applied Earth Observation and Geoinformatic, 16: 66-76.
- Hedayatzadeh F, Ildermi A., Hassanzadeh N. 2019. Air quality analysis based on PM2.5 and PM10 suspended particles by two methods USEPA-AQI and IND-AQI and EF factor in Ahvaz in 2016 and 2017. Journal of Environmental Health Engineering, Special Issue 2019, Year 7: 57 -75. (Persian)
- Sufyanian A, Mokhtari Z, Khajehddin J, Ziaei H. 2013. Gradient Analysis of Urban Landscape Model (Case Study: Isfahan). Human Geography Research, 45 (1): 87-104. (Persian)
- Wang, Y., Li, J., Fan, Z., Wang, X., 2008, GIS- based Urban Mosaic and Its Gradient Analysis, IEEE, the Second International Conference On Bioinformatics and Biomedical Engineering (ICBBE 2008), Shanghai, China.
- Lin, H., Ma, W., Qiu, H., Wang, X., Trevathan, E., Yao, Z., Dong, G.-H., Vaughn, M. G., Qian, Z., & Tian,L. (2017). Using daily excessive concentration hours to explore the short-term mortality effects of ambient PM2.5 in Hong Kong. Environmental Pollution, 229(Suppl. C), 896–901.
- Wong, T. W., Tam, W. S., Yu, T. S., & Wong, A. H. S. (2002). Associations between daily mortalities from respiratory and cardiovascular diseases and air pollution in Hong Kong, China. Occupational and Environmental Medicine, 59(1), 30–35.
- De Hoogh, K., Wang, M., Adam, M., Badaloni, C., Beelen, R., Birk, M.,... Dedele, A. (2013). Development of land use regression models for particle composition in twenty study areas in Europe. Environmental Science & Technology, 47(11), 5778–5786.
- Habermann, M., Billger, M., & Haeger-Eugensson, M. (2015). Land use regression as method to model air pollution. Previous results for Gothenburg/Sweden. Procedia Engineering, 115, 21–28.
- Ross, Z., English, P. B., Scalf, R., Gunier, R., Smorodinsky, S., Wall, S., & Jerrett, M. (2006). Nitrogen dioxide prediction in Southern California using land use regression modeling: Potential for environmental health analyses. Journal of Exposure Science and Environmental Epidemiology, 16(2), 106–114.
- Japelaghi M, Gholam Ali Fard M, Shayesteh K, 2017. Monitoring and analysis of Lorestan province land landscape model and its change process in GIS environment. Natural Environment, Iranian Journal of Natural Resources, 70 (1): 15-35. (Persian)
- Łowicki D, 2019. Landscape pattern as an indicator of urban air pollution of particulate matter in Poland. Ecological Indicators, 97: 17–24
- Shi Y, Ren C, Ka-Lun Lau K, 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, 189: 15–26
- Pielke, R. A., Marland, G., Betts, R. A., Chase, T. N., Eastman, J. L., Niles, J. O., & Running, S. W. (2002). The influence of land-use change and landscape dynamics on the climate system: Relevance to climate-change policy beyond the radiative effect of greenhouse gases. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 360(1797), 1705–1719.
- Weaver, C. P., & Avissar, R. (2001). Atmospheric disturbances caused by human modification of the landscape. Bulletin of the American Meteorological Society, 82(2), 269–281.
- Janhäll, S. (2015). Review on urban vegetation and particle air pollution – Deposition and dispersion. Atmospheric Environment, 105(Suppl. C), 130–137.
- Adams, M. D., & Kanaroglou, P. S. (2016). Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models. Journal of Environmental Management, 168,133–141.
- Hagler, G. S. W., Thoma, E. D., & Baldauf, R. W. (2010). High-resolution mobile monitoring of carbon monoxide and ultrafine particle concentrations in a near-road environment. Journal of the Air & Waste Management Association, 60(3), 328–336.
- Isakov, V., Touma, J. S., & Khlystov, A. (2007). A method of assessing air toxics concentrations in urban areas using mobile platform measurements. Journal of the Air & Waste Management Association, 57(11), 1286–1295.
- Westerdahl, D., Fruin, S., Sax, T., Fine, P. M., & Sioutas, C. (2005). Mobile platform measurements of ultrafine particles and associated pollutant concentrations on freeways and residential streets in Los Angeles. Atmospheric Environment, 39(20), 3597–3610.
- Xu, W., Riley, E. A., Austin, E., Sasakura, M., Schaal, L., Gould, T. R.,... Vedal, S. (2017). Use of mobile and passive badge air monitoring data for NOX and ozone air pollution spatial exposure prediction models. Journal of Exposure Science and Environmental Epidemiology, 27(2), 184–192.
- Shafaghi, S., Geography of Isfahan, University of Isfahan Press, 2002. (Persian)
- Atlas of Isfahan, Geographical and Cartographic Organization of Gita Studies, Tehran, 1997. (Persian)
- Javanmardi F, 2016. Familiarity with IDW interpolation method or inverse distance, GIS specialized site. https://gisman.ir/idw/. (Persian)
- Ahmadi Nodoshan M., Sufyanian A., Khajehddin J. 2010. Preparation of land cover map of Arak city using artificial neural network classification methods and maximum probability. Natural Geography Research, 41 (69): 1-12. (Persian)
- International Conference on Earth Sciences, Tehran, 2015. (Persian)
- Shi, Y., Lau, K. K.-L., & Ng, E. (2019). Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment. Environmental Research, 157, 17–29.
- Jaafari, S., Alizadeh Shabani, A., Moeinaddini, M., Danehkar, A., & Sakieh, Y. (2020). Applying landscape metrics and structural equation modeling to predict the effect of urban green space on air pollution and respiratory mortality in Tehran. Environ Monit Assess, 192:412, https://doi.org/10.1007/s10661-020-08377-0.
- Park, Y., Shin, J., & Lee, J.Y. (2021). Spatial Association of Urban Form and Particulate Matter. Int. J. Environ. Res. Public Health, 18, 9428. https://doi.org/10.3390/ijerph18189428.
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