Evaluation and Zoning of Airborne Pollution Using AHP and ANP Methods (Case Study: Tabriz City)

جغرافیا و مخاطرات محیطی

Article 9, Volume 8, Issue 1 - Serial Number 29, June 2018, Pages 153-169   

Document Type: Research Article

DOI: 10.22067/geo.v0i0.75734

Authors

Behroz Sobhani^* ; Elham Shokrzadeh Fard; Elnaz Piroozi

University of Mohaghegh Ardabili

Abstract

1 Introduction
Urban development and air pollution are among the most important issues related to the climate (Shkakoie, 2006). In spite of statistics comparing Tabriz's pollutants with world standards. The claim is not far from reality. One of the main environmental problems of Tabriz is air pollution. Tabriz, with an area of 135 square kilometers in the northwest of the country, has been located on the topographic surfaces between 1300 and 1750 meters in length. In this research, we have tried to use the ANP model and AHP model, fuzzy logic and compare them. A suitable model for the leveling of different regions of Tabriz should be created and graded in terms of acute and mildness and the effect of each of these factors on damaging Tabriz, will be analyzed by the above models.
2 Material and Method
In this study, the effective factors in polluting the study area were identified through the study of documentary and library resources (East Azarbaijan Environmental Protection Agency report, air pollution monitoring stations report), digital resources related to the research subject and field studies. These include precipitation, altitude, distance from green space, distance from industrial centers, distance from commercial centers, distance from communication routes, crowding, land use.
In the next step, the information layers for each of the factors in the GIS environment were prepared. The use of digital maps is to extract the required data from the map text (including topographic maps, land use, etc.). To evaluate the criteria, the membership function method was used in fuzzy sets. The weighting of the data was also done using the Paired Comparison Method in the framework of Expert selection and CRITIC method. ArcGIS 10, Excel 2007, Super Decision 2.0.8, MATLAB7.11.0 software were used to conduct the research. The results of studying parameters in the studied area is shown in the form of digital maps. With regard to the evaluation models for pollution, the mapping of the parameters of the studied area wasre-classified. Using these maps and descriptive information about the region, a database was developed to analyze sources of pollution.
Analytic Hierarchy Process (AH)
Analytic hierarchy process is one of the most comprehensive systems designed for decision making by multiple criteria, first introduced by Thomas (1980). This technique provides the possibility of formulating the problem in a hierarchical manner, and it is also possible to take into account different quantitative and qualitative criteria in problem. This process involves various options in decision making and allows for sensitivity analysis on criteria and sub criteria. In addition to being based on a paired comparison that facilitates judgment and computing as well as the degree of compatibility and incompatibility, it shows the advantages of this technique in multi-criteria decision making (Ghodspour, 2005). With the knowledge of the principles, the AHP method consists of the following steps:

Creating a Hierarchy of AHP, 2. Creating a Binary Comparison Matrix, 3. Calculating Standard Weights, 4. Calculating Inconsistency Rate, 5. Spatial Modeling and Layout Composition

ANP model
The ANP method is a developed form of the AHP method that correlates elements in a decision making process and calculate the internal effects of the components involved in the decision making process. Therefore, due to this feature, this technique is distinct and superior to the previous models. The ANP method has two main parts that integrates these two parts in one process. The first part consists of combinations of control criteria and sub criteria, as well as a group of volunteers.  The second part, a network of vectors and an arc which indicates dependencies and correlations as well as feedback in the decision-making system. The ANP model can be considered as the most comprehensive multi-criteria decision-making method (Razmi, 2008, cited in Mehdizadeh, 2011). ANP has four steps:

Determinig the criteria and indicators including rainfall, height, distance from green space, distance from industrial centers, distance from commercial centers, distance from communication paths, crowd, and land use.
Determining relationship between elements and cluster.
Comparisons between elements and clusters.
Super-matrix formation.

Super matrix is a matrix of relationships between network components that are derived from the initial vectors of these relationships. Super matrix in ANP, a measure of relative importance values, such as AHP, is performed with paired comparisons with the help of the spectrum from 1 to 9. Number 1 indicates the same importance between the two factors and number 9 indicates the acute importance of one factor relative to the other factor (Kiani et al.,2010). Finally, air pollution potential map was prepared in the framework of the above models. To prepare an air pollution level map, the first step is to create an information layer for the element. In this study, eight criteria or elements were used. Then we ranked, rotated and standardized them using the fuzzy function. Then, using final coefficients of the ANP and AHP models, multiplying  coefficient of each element into the same element map by the Raster Calculator function, and  combining the information layers together, the air pollution potentiality map was prepared in the above form.
3 Results and Discussion
In order to provide a risk map, eight criteria were used in this study. First, maps were prepared for each of the criteria. We then ranked, rendered, and standardized them using the fuzzy function.  Using the steps of the AHP model and the final coefficients of the ANP network model, multiplying each elemental map by the Raster Calculator function and combining the information layers together, air pollution of the area was prepared separately on the basis of ANP and AHP outputs. The final modeling was carried out in the Super Decision software. The domain value of the model was calculated for determining the potential air pollution in Tabriz. Final weights were obtained for assessing air pollution. Finally, the studied area was classified into five groups of very high, high, moderate, low and very low risk. Based on the ANP output, areas with very high levels of pollution include the northern and north-western regions, and areas with high levels of pollution include the central regions of the city. Small regions of the south and south-east are low in pollution, while the output of the AHP model shows that areas with a high risk include the entire central region and the northern and western parts, and the area with high pollution is a small region of north and northwest.
4 Conclusion
The industrialization of societies in the last century has caused many problems, including air pollution, which is due to the inability of the environment to absorb contaminants. In this study, AHP and ANP models were used as multi-criteria decision analysis method in studying the potential of pollutants in Tabriz. The Multi-criteria Evaluation Methodology (MCE) is one of the most principle-based decision-making methods in GIS (Bogdardi et al., 1996), which is used as spatial decision making for land planning. According to the final map of the ANP model the vast majority are in the northern and north-western regions, due to the fact that factories in Tabriz are located in these areas. Highly polluted areas are the central regions of the city. The area that peaked during the day with increasing traffic and exhausts, contaminated air was area 8. The most used were educational, cultural, health, administrative, commercial and communication, and the least use were residential, green spaces which increased pollution. As the map of altitude levels showed, the northern areas of Tabriz have a sharp slope, which is also seen in the south of the city. The central and western parts of the city are smooth, and these factors increase pollution in these areas. Given the map of congestion, despite the fact that a large number of inhabitants live in northern parts of the city, due to the concentration of most services, businesses in the city center, overcrowding has grown throughout the day in the central regions of the city which increases traffic of vehicles and pollution. The results of the AHP model indicate that areas with a high risk include the whole central region and the north-west regions, and the region with high contamination includes a small area from the north and north-west. It should be acknowledged that among the factors influencing the contamination, communication paths with the coefficient of 0.69 is the most valuable and important for contamination.  Population congestion with a coefficient of 539% of land use with 0.460 coefficient are other important factors respectively. Rainfall and altitude factors with respect to weight coefficients have little effect on pollution. In the case of green space agent, it should be noted that parts of the North-West and South-West have a low distribution of green space, the largest distribution of green space in the southern parts, which is less contaminated than the rest of the regions. Therefore, it can be said that the ANP model, in comparison with the AHP model, accurately realizes the relations of the criteria and their coefficient of influence, and the results of the model are closer to the research goal.
 

Keywords

Air Pollution; zoning; Tabriz city; AHP; ANP

References

بیگدلی، آتوسا؛ 1380. تأثیر اقلیم و آلودگی هوای تهران و بیماری سکته قلبی (دوره 5 ساله 1990-1994). فصلنامه تحقیقات جغرافیایی. سال شانزدهم. شماره3. صفحه140-126.

درّی، بهروز؛ حمزه‌ای، احسان؛ 1389. تعیین استراتژی پاسخ به ریسک در مدیریت ریسک به وسیلۀ تکنیک (ANP) مطالعۀ موردی: پروژۀ توسعۀ میدان نفتی آزادگان شمالی. دورۀ2. شمارۀ 4. صص 92-75.

زنگی آبادی، علی؛ رخشانی نسب، حمیدرضا؛ 1388. تحلیل آماری – فضایی نماگرهای توسعه فضای سبز شهری (مطالعه موردی: مناطق شهری اصفهان). مجله محیط شناسی. سال سی و پنجم. شماره 49. صص 105-116.

زینالی، بتول؛ شکرزاده فرد، الهام؛ پیروزی، الناز؛ 1397. ارزیابی و پهنه‌بندی آلودگی هوا با استفاده از مدل ویکور. مجله مخاطرات محیط طبیعی. دوره 7. شماره 15. بهار 1397. صفحه 88-67.

شرعی پور، زهرا؛ بیدختی، عباسعلی؛ 1384. بررسی آلودگی هوای شهر تهران و ارتباط آن با پارامترهای هواشناسی. اولین همایش آلودگی هوا و اثرات آن بر سلامت. 25-1.

شکویی، حسین؛ 1385. محیط‌زیست، شهری. انتشارات موسسه تحقیقات اجتماعی و علوم انسانی. تبریز. 45 صفحه.

فرجی سبک بار، حسنعلی؛ سلمانی، محمد؛ فریدونی، فاطمه؛ کریم‌زاده، حسین؛ رحیمی، حسن؛ 1389. مکان‌یابی محل دفن بهداشتی زبالۀ روستایی با استفاده از مدل فرایند تحلیل شبکه‌ای (ANP) مطالعۀ موردی: نواحی روستایی شهرستان قوچان. فصل‌نامۀ مدرس علوم انسانی. دورۀ 14. شمارۀ 1. صص 149-127.

فطرس، محمدحسن؛ فتحی، ابوذر؛ بی تا. شهرنشینی و آلودگی هوا در ایران. دانشگاه ابوعلی سینا همدان.

کاظمی، خلیل الله؛ شاکری، مجتبی؛ رستگار، موسی؛ صیادی، سینا؛ 1393. آلودگی هوا و چالش‌های مدیریت شهری درکلا‌ن‌شهرها (کلانشهر مشهد). ششمین کنفرانس ملی برنامه ریزی و مدیریت شهری با تاکید بر مؤلفه‌های شهراسلامی.

گزارش استانداری استان آذربایجان‌شرقی؛ 1390. تعداد خانوار استان آذربایجان‌شرقی به تفکیک شهرستان‌ها.

مهدی زاده، جواد؛ 1391. تحلیل مخاطرات اقلیمی در شهر تبریز با استفاده از منطق فازی و مدلANP . پایان‌نامۀ کارشناسی ارشد رشتۀ جغرافیا. دانشگاه محقق اردبیلی. اردبیل. 152 صفحه.

نورزاده، فرهاد؛ 1386. آلودگی و منابع آلاینده هوا در سطح شهر تبریز. پایان‌نامه کارشناسی ارشد. دانشگاه زنجان.

نیازی، حسن؛ محمدزاده، رحمت؛ 1389. بررسی عوارض زیست‌محیطی و انسانی ترافیک درون شهری تبریز. نشریه علمی- پژوهشی جغرافیا و برنامه ریزی (دانشگاه تبریز). صص191- 219.

Alam, S., Fatima, A., 2007. Sustainable Development in Pakistan in the Context of Energy Consumption Demand and Environmental Degradation, Journal of Asian Economics, 18, pp.825- 837.

Breheny, M., 2001. Densities and Sustainable Cities: the UK Experience. In: Echenique, M., Saint, A. Cities for the New Millennium. Spon Press, London, pp.39-51.

Davari,H., Bolboliyan, L., 2014. Increased pollution from cars in Tabriz and increased use most of the energy, the National Conference of Architecture, Engineering and Physical Development.

Tor H, o., Markey, j., Kathy, T., Lsaac N, L., 2015. Assessing traffic and industrial contributions to ambient nitrogen dioxide and volatile organic compounds in a low pollution urban environment, Science of The Total Environment, Volume 529, pp.149–157.

Wijerane, I.K., Bijker, W., 2006. Mapping Dispersion of Urban Air Pollution with Remote Sensing, ISPRS Technical Commission II Symposium, Vienna, 12-14 July, PP125-130.

Williams, T., Crawford, E., 2006. smog and Population Health: Science and Technology Division, 28 march.