An Investigation of the Relationship between Urban Heat Island and Air Pollution in the City of Isfahan

Document Type : Research Article

Author

• Abbasali Arvin

Payame Noor University

10.22067/geo.v7i1.64590

Abstract

1. Introduction
Urban heat island refers to an area where the temperature is higher than of the surrounding environment. It is referred to as an island since the temperature of a point or an area of the earth's surface (the city) is more than of the surrounding environment, which mostly has, a homogenous and uniform temperature. Therefore, this island, which can be separated and distinguished from the surrounding environment of the city, is named the city of heat island. Urban heat island can be due to growing population and its concentration in the urban centers, and consequently the increase in air pollution. Changes in land use can be regarded as one of the underlying causes of the occurrence of urban heat island. For example, using satellite images to study the heat island in the city of Mashhad, by Mousavi Bayeghi et al. (2012) showed that along with the land use change from the garden level to the city one, there has been a rise in the temperature. Frequent pollution in the city of Isfahan in recent years has led to the development of some hypotheses assuming some relationship between urban heat island and pollution. In this regard, the growing population density and the vertical expansion of the city, as well as urban development, have resulted in the development of the idea that the study of urban heat island in relation to air pollution can be very important as it can help cope with and decrease the degree of urban heat island. With this objective in mind, this study is designed to address this important concern.
The growing intensity of the thermal island due to air pollution in addition to the undesirable effects on human health can seriously damage the valuable historical works in the popular tourist city of Isfahan. It is hoped that the results of this research could help reduce the effects of the thermal island, leading to the development a better living environment in the city of Isfahan accordingly. Methods based on Satellite images can be regarded as one of the best ones for studying the thermal island; in fact, such methods have been used in many studies inside and outside the country. In this research, the thermal island in the city of Isfahan has also been analyzed using satellite imagery.
2. Materials and Methods
In order to study urban heat island in the city of Isfahan, a series of landsat 8 satellite images with good resolution were used. This satellite conducts imaging through 11 spectral bands. The bands 1 to 9, which are known as OLI, carry out imaging in color and NIR spectra. The bands 10 and 11 are well-known as TIRS thermal bands. They do imaging within long infrared waves. In this study, the bands 4, representing red, and 5, representing the near-infrared, and the thermal bands 10 and 11 were used to study the urban island in the city of Isfahan. The data related to AQI air quality index was used to check days with air pollution. Due to the restrictions over the passage of satellite within a period of 16 days over the city of Isfahan, the limited number of days with extremely high pollution in the city, and the non-conformity between polluted days and the time of satellite passage, images of three days representing the very unhealthy (the red condition), unhealthy (the orange condition), and healthy (yellow condition) air were thus used. In this study, Subrino Split-Window algorithm was used as the technique to calculate the Earth's surface temperature. This method is based on the calculation of brightness temperature of the bands 10 and 11 as well as the vegetation index of the bands 4 and 5. For this purpose, Arc_GIS10.3 software was used to compute the Earth's surface temperature and the air temperature of the city. ENVI software was also used for the atmospheric correction.
3. Results and Discussion
Isfahan, due to climatic conditions and a flat topography, has a relatively quiet atmosphere throughout the year. Although Mount Soffeh is located in the south-west of the city, this mountain can only help reduce the speed of westward winds over the city as it is a single peak with a low height. In addition, the vertical expansion of buildings in all parts of the city causes the wind speed to be slow due to the increased friction. High buildings with greater height than the other points, especially in the western part of Isfahan, have led to the considerable reduction of wind speed, which is an important parameter. On the other hand, population growth and its concentration in the central part of the city have increased the intensity of urban heat island. To address the possible relationship between air pollution and urban heat island, the date of January 22nd, 2014 was chosen for investigation. On this day, the temperature calculated from satellite images of the city was within the range of 3 and 17 degrees Celsius. In general, the temperature fluctuated between 5 and 9 ° C in most parts of the city, and the 7° C isotherm bypassed most parts of the city.
The correlation coefficient between vegetation index (NDVI) and land surface temperature, LST, was equal to the 0/37064, which was significant at the confidence level of 99%. Given that the urban heat island is based on urban atmospheric temperature, not the temperature of emitting or reflecting surfaces, some empirical relationships were used to convert surface temperature to air temperature. Accordingly, it was found that the air temperature in the city fluctuated between +5.5 and -1.8 ° C on January 22nd, 2014.
The comparison of the city thermal island map with the map of pollution distribution confirmed the increase in the city temperature as a result of urban air pollution.
That is, the highest concentration of pollution in the East and North East of related to the areas with the higher air temperature. The observed maximum temperature shown by the color red in the map was 13.8 degrees and this was 10.6 degrees in the suburbs. Temperature difference between the city heat-island and suburban areas on this days reached to 3.2 degrees Celsius.
The highest rates of pollution were observed in the stations located in the Eastern Isfahan, including the Ahmadabad SQ and Kharazi Highway. Correlation analysis between the earth's surface temperature map and the map of the distribution of air quality index in the city of Isfahan showed a correlation coefficient of 0.242 at 99% confidence level on January 22nd, 2014. On this day, air pollution AQI index was between 117 to 169, and the temperature ranged from 8.5 to 13.7 degrees Celsius.
4. Conclusions
The city of Isfahan, due to stable climatic conditions at most times of the year and the spread of pollution, is one of the most polluted cities in Iran. The increased intensity of thermal island is one consequence of this phenomenon. In this study, Landsat 8 satellite images with a high resolution were used to estimate the surface temperature of the Earth. The temperature calculated by the model was compared with the soil temperature at the meteorological stations. A slight difference between the temperature in soil at the depth of 5 centimeters and the LST obtained through satellite images, which ranged from a maximum of 6 to a minimum of 1.8, showed that the Subrino's Split Window method could be suitable for estimating the surface temperature of the earth. Finally, the urban heat island in the city of Isfahan was obtained based on the statistical relationships between the land surface temperature (LST) and the air temperature. The analysis of topographic profile related to thermal island temperature showed the promotion of the thermal island in the city as compared with the surrounding area. That is, the temperature inside the city was 7.3 degrees and 9.5 degrees Celsius warmer than the surrounding area respectively, which could show the city's urban heat island clearly. The difference between the temperature of the city's thermal island and the city's surrounding temperature was higher at the time of the maximum pollution. The comparison of the temperature maps of Isfahan with the pollution distribution maps revealed the maximum correlation between temperature and the pollutant areas. The correlation coefficient between the pollution distribution map and the urban temperature map was positive and significant. In more polluted days, the linear relationship between the pollution increase and urban air temperature increase was stronger. As a result of the increased air pollution, the intensity of the thermal island of the city was aggravated. The study of air pollution distribution in the city of Isfahan showed that the eastern regions had more contamination. This was influenced by the urban topography. This is because the southern and western parts of Isfahan are at a higher elevation due to the presence of Mount Soffeh, and the pollution due to mass weight tends to subside in the lower northern and eastern regions of Isfahan. On the other hand, pollution is more concentrated in the eastern regions of the city due to the slow prevailing western winds. The comparison of the thermal map of the thermal Island in the city of Isfahan to the pollution distribution map confirmed the effect of pollution on the increase of urban air temperature. Therefore, the most pollution was concentrated in the eastern and northeastern Isfahan, which were the areas with the higher air temperature. The observed maximum temperature reached to 13.8 degrees, whereas it was 10.6 degrees in the suburbs of Isfahan.

Keywords

• Thermal Island
• Isfahan
• Air Pollution
• Estimation of Temperature
• Satellite image

---

References

منابع

امینی‌بازیانی، سمیرا؛ زارع‌ابیانه، حمید؛ اکبری، مهدی؛ 1393. برآورد دما و شاخص پوشش گیاهی سطح زمین با استفاده از داده‌های سنجش از دور (مطالعة موردی: استان همدان). پژوهش‌های جغرافیای طبیعی، سال 46 شماره 3 ، 348-333.

جاجرمی، کاظم؛ 1391. اقلیم و شهر، تألیف ژیزل اسکورو . اندیشه‌های گوهربار. تهران.

جویباری‌مقدم، یاسر؛ آخوندزاده، مهدی؛ سراجیان، محمدرضا؛ 1394. ارائه یک الگوریتم پنجره مجزا نوین به منظور تخمین دمای سطح زمین از داده‌های ماهواره لندست 8 . نشریه علوم و فنون نقشه‌برداری، دوره پنجم شماره 1، 226-215.

حجازی‌زاده، زهرا؛ ضیائیان، پرویز؛ شیرخانی‌ریا، علیرضا؛ 1392. مقایسه تخمین دمای سطح با استفاده از داده‌های باند حرارتی سنجنده‌های ماهواره‌ای در غرب استان تهران قزوین. فصلنامه جغرافیا (انجمن جغرافیای ایران)، سال یازدهم شماره 38 ، 49-33.

حسین‌زاده، سیدرضا؛ نداف‌سنگانی، مهوش؛ 1391. ارزیابی دقّت مدل‌های رقومی ارتفاع (DEM) حاصل از نقشه-های توپوگرافی و مقایسه‌ی تطبیقی آن با DEM های ماهوارهای (مطالعه‌ی موردی DEM های توپوگرافی و ASTER منطقه‌ی آبغه در خراسان رضوی) . پژوهش‌های جغرافیای طبیعی، سال 45 شماره 1، 86-71.

صادقی‌نیا، علیرضا؛ علیجانی، بهلول؛ ضیائیان، پرویز؛ 1391. تحلیل فضایی- زمانی جزیره حرارتی کلان شهر تهران با استفاده از سنجش از دور و سیستم اطلاعات جغرافیایی. جغرافیا و مخاطرات محیطی، شماره چهارم، 17-1.

فرزندی، محبوبه؛ رضائی‌پژند، حجت؛ سیدنژادگلخطمی، نفیسه؛ 1393. تعیین نقطه‌ی شکست دمای سالانه با الگوی وابستگی سیستم خاکستری برای تحلیل جزیره حرارتی مشهد. مجله مخاطرات محیطی، سال سوم شماره چهارم، 59-49.

فیضی‌زاده، بختیار؛ دیده‌بان، خلیل؛ غلام نیا، خلیل؛ 1395. برآورد دمای سطح زمین و الگوریتم پنجره مجزا با استفاده از تصاویر ماهواره لندست8 مطالعه موردی: حوضه آبریز مهاباد. فصلنامه علمی پژوهشی اطلاعات جغرافیایی (سپهر) ، دوره25 شماره 98 ، 181-171.

المدرسی، سیدعلی؛ رحیم‌آبادی، ابوالفضل؛ خضری، صادق؛ 1393. پهنه‌بندی و مقایسه دمای سطح زمین با استفاده از دو باند حرارتی10 و 11 تصویر لندست8 (مطالعه موردی شهرستان بهشهر). نخستین همایش کاربرد مدل‌های پیشرفته تحلیل فضایی (سنجش از دور و GIS درآمایش سرزمین). دانشگاه آزاد اسلامی واحد یزد.

موسوی‌بایگی، محمد؛ اشرف، بتول؛ فرید، حسین؛ علیرضا‌میان‌آبادی، آمنه؛ 1391. بررسی جزیره حرارتی شهر مشهد با استفاده از تصاویر ماهواره‌ای و نظریه فرکتال. مجله جغرافیا و مخاطرات محیطی، شماره اول، 49-35.

Alhawiti RH, Mitsova D., 2016. Using Landsat-8 Data to Explore The Correlation Between Urban Heat Island and Urban Land Uses. IJRET. International Journal of Research in Engineering and Technology 5 (3): 457-466.

Aslan N, Koc-San D., 2016. Analysis of Relationship Between Urban Heat Island Effect and Land USE/COVER Type Using Landsat 7 ETM+ and Landsat 8 OLI Image. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Congress, 12–19 July, Prague, Czech Republic, XLI-B8, 821-288.

Elsayed ISM., 2012. Mitigation of the Urban Heat Island of the City of Kuala Lumpur, Malaysia. Middle-East Journal of Scientific Research 11 (11): 1602-1613.

Karenia CSG., 2015. Spatial Geo-technologies and GIS tools for urban planners applied to the analysis of urban heat island. Case Caracas city, Venezuela, ICUC9 - 9th International Conference on Urban Climate jointly with 12th Symposium on the Urban Environment, 1-5.

Lio Du T, Zhou MSLI, Gong DY., 2014. Urban heat island effects derived from dense Landsat thermal observations in Nanjing, China, 35th International Symposium on Remote Sensing of Environment (ISRSE35)

Lo CP, Quattrochi DA, Luvall JC., 2010. Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. International Journal of Remote Sensing 18(2).

Memon RA, Leung YCD, Chunho LIU., 2008. A review on the generation, determination and mitigation of Urban Heat Island. Journal of Environmental Sciences 20(1).

Qihao W, Dengsheng L, Jacquelyn S., 2004. Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment 89: 467–483.

Samuel NG., 2013. THERMAL BEHAVIOR OF URBAN LANDSCAPES AND THE URBAN HEAT ISLAND. Physical Geography, 2(1), 19-33.

Sham S., 1986. Application of Climatology to Urban Planning and Building Design in Malaysia. Sumber 2: 63-79.

Thomas CP, Timothy WO., 2005. Urban Heat Island Assessment. Journal of climate 81: 2637-2646.

Tsou J. Zhuang, J., Yu Li & Zhang, Y., 2017. Urban Heat Island Assessment Using the Landsat 8 Data: A Case Study in Shenzhen and Hong Kong. Urban Science 1(10): 1-22.

Yuan F, Marvin EB., 2007. Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sensing of Environment 106: 375-386.

Zanter K., 2016. Landsat 8 (L8) Data Users Handbook. USGS Science for Changing Word, EROS, Sioux Falls, South Dakota.