نوع مقاله : مقاله پژوهشی

نویسندگان

گروه محیط زیست، دانشکده منابع طبیعی، دانشگاه تهران، تهران، ایران

چکیده

سابقه و هدف:
تغییر در کیفیت هوا و خطر­های آن با رشد سریع مناطق شهری و صنعتی و تغییر در سایر کاربری‌ها در دهه‌های اخیر در رابطه است. یکی از مهم‌ترین تاثیر­ها، تغییرپذیری­ های  کاربری سرزمین فرسایش بادی و در نتیجه افزایش ذرات معلق، در مناطق مسکونی است. به این دلیل،  تاثیر تغییرپذیری­ های کاربری سرزمین، بر افزایش غلظت ذرات معلق در هوای شهرها بخصوص تهران دارای اهمیت است.
مواد و روش­ ها:
تغییر پذیری ­های کاربری سرزمین و متریک‌های سیمای سرزمین  در سال‎های 1985، 2000 و 2014 بررسی شد. سپس رابطه بین تغییر در کاربری سرزمین با غلظت ذرات معلق در شهر تهران با استفاده از روش‌های تحلیل روند مورد ارزیابی قرار گرفت. برای تعیین مهم‌ترین جهت‌های باد و تغییر در کاربری سرزمین که بر کیفیت هوای شهر تهران تأثیر گذاشته از شاخص‌های تابع احتمال شرطی (1CPF) و شدت نسبی جهتی (2DRS) استفاده شد.
نتایج و بحث:
نتایج نشان داد که مساحت کاربری کشاورزی در دوره 1985 تا 2000 دارای روند افزایشی  بوده در حالی که این روند در 2000 تا 2014  وارونه بوده است. تغییر در مساحت زمین­ های بایر روندی معکوس نسبت به کاربری کشاورزی در دو دوره زمانی ذکر شده داشت. همچنین کاربری شهری در کل دوره، روند افزایشی داشته است. نتایج متریک ­های سرزمین، به وجود آمدن لکه‌های کوچک‌تر و سیمای سرزمین لکه لکه شده را نشان داد. نتایج تحلیل روند بیان کرد که غلظت ذرات معلق در کل روند افزایشی داشته اما در سال 2007 یک افزایش ناگهانی در غلظت ذرات معلق دیده شد. مقایسه بین غلظت ذرات معلق قبل و بعد از سال 2007 گویای این بود که بین این دو دوره اختلاف معنی‌داری وجود دارد. همچنین نتایج CPF و DRS قبل از سال 2007 نشان داد که جهت خاصی برای ­منبع­­ های انتشار ذرات معلق وجود ندارد. اما برای سال‌های بعد از 2007، ارزش نمودار CPF و DRS در جهت­ های خاصی مانند جنوب تا غرب افزایش یافته است.
نتیجه‌گیری:
نتایج، نشان‌دهنده این است که جهت‌های خاصی بر افزایش غلظت 10PM در شهر تهران مؤثرند که با جهت بیشترین تغییرپذیری­ ها در کاربری سرزمین مطابقت دارد. در نتیجه تغییرپذیری­ ها کاربری سرزمین از عوامل مؤثر در افزایش میزان ذرات معلق شهر تهران به شمار می­ رود.

کلیدواژه‌ها

عنوان مقاله [English]

Effects of land use/cover changes on Tehran’s air quality

نویسندگان [English]

  • Abutaleb Sabr
  • Mazaher Moeinaddini
  • Hossein Azarnivand

Department of environment, Faculty of Natural Resources, University of Tehran, Tehran, Iran

چکیده [English]

Introduction:
In recent decades, air quality change and its risks are correlated with the expansion of urban and industrial areas and other land-use changes. One of the important effects of land use/cover changes (LUCC) is wind erosion and as a result, an increase in particulate matter (PM) concentration in residential areas. For this reason, the effects of LUCC on PM concentration in Tehran’s airshed was studied.
Material and methods:
Data on LUCC and landscape metrics were studied in the years 1985, 2000 and 2014. Then, the relationship between LUCC and PM concentration in Tehran was investigated by trend analysis methods. To find the most important wind directions with strong effects on Tehran’s air quality, conditional probability function (CPF) and directional relative strength (DRS) were used.
Results and discussion:
LUCC results showed that the area of agricultural land-use has been expanded from 1985 to 2000, yet decreased from 2000 to 2014. The trend was vice versa for barren lands during the mentioned time periods. In addition, the urban area has increased in the whole period. The landscape metric results showed that landscape patches became smaller and the landscape has been fragmented. The results of the PM10 concentration trend analysis revealed that it has been increased dramatically since 2007. Comparison of the average concentration of PM10 before and after 2007 showed a significant difference. The results of CPF and DRS illustrated that no specific wind direction was detected before 2007, but afterwards both increased in specific directions (south to west), which is compatible with most LUCC and fragmented areas in these directions.
Conclusion:
Our results showed that specific wind directions may lead to an increase in the PM10 concentration which is compatible with LUCC directions. Therefore, LUCC could be a significant reason for the increase in PM10 concentration in Tehran.

کلیدواژه‌ها [English]

  • remote sensing
  • Land use/cover change (LUCC)
  • Particulate matter (PM)
  • Trends analysis
  • Tehran

Anderson, J., Hardy, E., Roach, J. and Witmer, R., 1976. A land use and land cover classification system for use with remote sensor data. Professional Papers-US Geological Survey (USA). 964, 1–41.

Bahiraei, H., Ayazi, S. M.H., Rajaei M.A. and Ahmadi, H., 2012. SYNOPTIC analysis of dust storm in Ahwaz city, IRAN. Journal of Human Geography. 4(1), 47-67.

Chan, Y.C., Hawas, O., Hawker, D., Vowles, P., Cohen, D.D., Stelcer, E., Simpson, R., Golding, G. and Christensen, E., 2011. Using multiple type composition data and wind data in PMF analysis to apportion and locate sources of air pollutants. Atmospheric Environment. 45(2), 439-449.

Chouvardas, D. and Vrahnakis, M., 2009. A semi-empirical model for the near future evolution of the Lake Koronia landscape. Journal of Environmental Protection and Ecology. 10, 867–886.

Engelstaedter, S., Kohfeld, K., Tegen, I. and Harrison, S., 2003. Controls of dust emissions by vegetation and topographic depressions: an evaluation using dust storm frequency data. Geophysical Research Letters. 30(6),123-131

Elkhrachy, I. 2015. Land use change detection using satellite images for Najran City, Kingdom of Saudi Arabia (KSA). The World Cadastre Summit, Istanbul Turkey.

Gilmore, S., Saleem, A. and Dewan, A., 2015. Effectiveness of DOS (dark-object subtraction) method and water index techniques to map wetlands in a rapidly urbanizing megacity with Landsat 8 data. Conference Research@ Locate'15. Brisbane, Australia.

Givehchi, R., Arhami, M. and Tajrishy, M., 2013. Contribution of the Middle Eastern dust source areas to PM10 levels in urban receptors: case study of Tehran, Iran. Atmospheric Environment. 75, 287-295.

Goudie, A. and Middleton, N.J., 2006. Desert dust in the global system: Springer Science and Business Media. 287.

Goudie, A., 2009. Dust storms: recent developments. Journal of Environmental Management. 90(1), 89-94.

Halek, F., Kianpour-Rad, M. and Kavousirahim, A., 2010. Seasonal variation in ambient PM mass and number concentrations (case study: Tehran, Iran). Environmental Monitoring and Assessment. 169, 501-507.

Jahani, H.R. and Reyhani, M., 2006. Role of groundwater in Tehran water crisis mitigation. International workshop on groundwater for emergency situations. Tehran: regional center on urban water management/UNESCO-IHP.

Jalali, M., Bahrami, H. and Darvishi bolurani, A., 2012. Investigation of the relationship between climatic and terrestrial factors with the occurrence of dust storms using MODIS satellite images (Case study: Khuzestan province). The first national desert conrerance. Tehran, Center for International Research of the University of Tehran.

Johnson, B., 2015. Remote sensing image fusion at the segment level using a spatially-weighted approach: applications for land cover spectral analysis and mapping. ISPRS International Journal of Geo-Information. 4(1), 172–184.

Khan, M.F., Hirano, K. and Masunaga, S., 2010. Quantifying the sources of hazardous elements of suspended particulate matter aerosol collected in Yokohama, Japan. Atmospheric Environment.44, 2646–2657.

Kendall, M.G., 1975. Rank correlation methods, Charles Griffin, London.

Kim, N.K., Kim, Y.P. and Kang, C.H., 2011. Long-term Trend of aerosol composition and direct radiative forcing due to aerosols over Gosan: TSP, PM10, and PM2.5 Data between 1992 and 2008. Atmospheric Environment.45, 6107–6115.

Lau, A.K.H., Yuan, Z., Yu, J.Z. and Louie, P.K., 2010. Source apportionment of ambient volatile organic compounds in Hong Kong. Science of the Total Environment. 408(19), 4138-4149.

Mann, H.B., 1945. Nonparametric tests against trend, Econometrica. 13, 245-259.

Mansouri, B., Hoshyari, E. and Mansouri, A., 2011. Study on ambient concentrations of air quality parameters (O3, SO2, CO and PM10) in different months in Shiraz city, Iran. International Journal of Environmental Sciences. 1(7), 1439-1447.

Matsushita, B., Xu, M. and Fukushima, T., 2006. Characterizing changes in landscape structure in the Lake Kasumigaura Basin, Japan using a high-quality GIS dataset. Journal of Landscape and Urban Planning. 78(3), 241-250.

Mitchell, M.G., Suarez-Castro, A.F., Martinez-Harms, M., Maron, M., McAlpine, C., Gaston, K.J., Johansen, K. and Rhodes, J.R., 2015. Reframing landscape fragmentation’s effects on ecosystem services. Trends in Ecology and Evolution. 30(4), 190–198.

Moeinaddini, M., Sari, A.E., Chan, A.Y.C., Taghavi, S.M., Hawker, D. and Connell, D., 2014. Source apportionment of PAHs and n-alkanes in respirable particles in Tehran, Iran by wind sector and vertical profile. Environmental Science and Pollution Research. 21(12), 7757-7772.

Pantavou, K., Lykoudis, S. and Psiloglou, B., 2017. Air quality perception of pedestrians in an urban outdoor Mediterranean environment: A field survey approach. Science of the Total Environment. 574, 663-670.

Rajabzadeh, F., 2016. Land use change in southwest of tehran using remote sensing and markov chain. Protection of water and soil resources. 6(2), 59-71.(in persian with English abstract).

Saeifar, M.H. and Mohammadnia, M., 2015. Land use/land cover change detection in Tehran city using Landsat satellite images. Journal of Applied Environmental and Biological Sciences. 5(12), 199-207.

Saemian, S., 2013. Adaptation strategies to impacts of climate change and variability on Tehran water supply in 2021: an application of a decision support system (DSS) to compare adaptation strategies. Uppsala Universitet.

Safavi, S.R. and Alijani, B., 2007. Study geographical factors in Tehran air pollution. Reseach in Geography. 58, 99-112.

Schindler, S., Poirazidis, K. and Wrbka, T., 2008. Towards a core set of landscape metrics for biodiversity assessments: case study from Dadia National Park, Greece. Ecological Indicators. 8, 502–514.

Shariepour, Z. and Aliakbari Bidokhti, A., 2011. Investigation of spatial distribution of air pollutants in Tehran during the cold months of 2013-2011. Environmental Science and Technology.16 (1),149-166.

Superczynski, S.D. and Christopher, S.A., 2011. Exploring land use and land cover effects on air quality in Central Alabama using GIS and remote sensing. Remote Sensing. 3(12), 2552-2567.

Waked, A., Favez, O., Alleman, L.Y., Piot, C., Petit, J.E., Delaunay, T. and Leoz-Garziandia, E., 2014. Source apportionment of PM10 in a north-western Europe regional urban background site (Lens, France) using positive matrix factorization and including primary biogenic emissions. Atmospheric Chemistry and Physics. 14(7), 3325-3346.

World health organization (WHO)., 2016. Ambient air pollution: A global assessment of exposure and burden of disease.

Yu, L. and Gong, P., 2012. Google Earth as a virtual globe tool for earth science applications at the global scale: progress and perspectives. International Journal of Remote Sensing. 12(33), 3966-3986.

Zare, A.H., Bayat, V.M. and Maroufi, S., 2012. Investigating Water Table Depth Fluctuations in the Malayer Plain. Soil and water science, 22(2), 102-112.

Zou, X.K. and Zhai, P.M., 2004. Relationship between vegetation coverage and spring dust storms over northern China. Journal of Geophysical Research: Atmospheres, 109(D3), 1-9.