پژوهش های اقلیم شناسی

پژوهش های اقلیم شناسی

اولویت بندی ریسک‌های ناشی از تغییرات اقلیمی در ایران

نوع مقاله : مقاله پژوهشی

نویسندگان
مهدی صالح آبادی 1
مریم ایلانلو 2
سحر رضائیان 3
1 دانشجوی کارشناسی ارشد، رشته حقوق محیط زیست، واحد الکترونیکی، دانشگاه آزاد اسلامی، تهران، ایران
2 گروه جغرافیا، واحد ماهشهر، دانشگاه آزاد اسلامی، ماهشهر، ایران
3 دانشیار، گروه محیط زیست، دانشگاه آزاد اسلامی واحد شاهرود، تهران، ایران
10.22034/jcr.2024.186507
چکیده
در بین ده عامل تهدیدآمیزی که بشر را در قرن 21 تهدید می‌کنند، اکنون پدیدة تغییر اقلیم در رتبة نخست قرار دارد. مسئلة اصلی در بروز این پدیده پیامدهای آن برای طبیعت و زندگی بشر است. هدف از این پژوهش شناسایی مهمترین‌ ریسک‌های ناشی از تغییرات اقلیمی و اولویت‌بندی آنها با روش‌های تصمیم‌گیری چندمعیاره پرداخته شده است. به منظور آشنایی با اثرات اقلیمی و آزمون فرضیات، پرسشنامه‌ای برای اولویت‌بندی اثرات اقلیمی تهیه شده است. ‌در‌ این ‌میان ‌از‌ گفتگوهای ‌جمعی ‌اطلاعات ‌مفیدی‌ جهت‌ تحلیل و بررسی ‌مساله‌ به ‌دست‌ آمد. برای طراحی پرسش‌نامه از نطرات 25 کارشناسی و خبره استفاده‌گردید. پاسخ پرسش شوندگان به صورت اولویت بندی اثرات اقلیمی براساس روش AHP فازی و رتبه‌بندی مناطق اقلیمی براساس روش Waspas مورد بررسی قرار گرفت. نتایج نشان می‌دهد، ضریب t در تمامی شاخص‌ها بیشتر از صفر و حد متوسط می‌باشد، بدین ترتیب بین تمام شاخص‌ها و ریسک تغییر اقلیم رابطه معنادار مشاهده می‌شود. بیشترین ضریب متعلق به مخاطرات محیطی با ضریب 9/35 می‌باشد. نتایج همبستگی پیرسون نشان داد، میانگین تمامی شاخص ها بیشتر از عدد چهار می‌باشد و رابطه تمام شاخص‌ها با یکدیگر مثبت می‌باشد که این مسئله بیانگر تأثیر تک تک این شاخص ها برروی یکدیگر می‌باشد. بیشترین وزن نهایی شاخص‌های شش‌گانه در روش AHP FUZZY متعلق به مخاطرات محیطی با وزن 201/0 و سپس منابع آبی با وزن 193/0، اقتصادی 170/0 می‌باشد. رتبه‌بندی مناطق اقلیمی با استفاده از روش واسپاس نشان داد، به لحاظ ریسک‌پذیری تغییر اقلیم در شاخص‌های شش‌گانه به ترتیب منطقه نیمه خشک، خشک، مدیترانه‌ای، نیمه‌مرطوب، فراخشک، مرطوب و سرد و کوهستانی در رتبه‌های1تا7 قرار گرفته‌اند
کلیدواژه‌ها
تغییر اقلیم
ایران
سیلاب
خشکسالی
AHP FUZZY

عنوان مقاله English

Prioritizing the risks caused by climate change in Iran

نویسندگان English

Mehdei SalhABADEI 1
Maraym Ilanloo 2
sahar rezaeian 3
1 1. دانشجوی کارشناسی ارشد، رشته حقوق محیط زیست، واحد الکترونیکی، دانشگاه آزاد اسلامی، تهران، ایران
2 گروه جغرافیا، واحد ماهشهر، دانشگاه آزاد اسلامی، ماهشهر، ایران
3 Associate Professor, Department of Environment, Islamic Azad University, Shahroud Branch, Tehran, Iran
چکیده English

Among the ten threatening factors that threaten humanity in the 21st century, the phenomenon of climate change ranks first. The main issue in the emergence of this phenomenon is its consequences for nature and human life. The purpose of this research is to identify the most important risks caused by climate change and prioritize them with multi-criteria decision making methods. In order to familiarize with climatic effects and test hypotheses, a questionnaire has been prepared for prioritizing climatic effects. In the meantime, useful information was obtained from group discussions to analyze and investigate the issue. The opinions of 25 experts and experts were used to design the questionnaire. The responses of the respondents were evaluated in the form of prioritizing climatic effects based on the fuzzy AHP method and ranking the climatic regions based on the Waspas method. The results show that the coefficient of t in all indicators is greater than zero and the average limit, thus a significant relationship is observed between all indicators and the risk of climate change. The highest coefficient belongs to environmental hazards with a coefficient of 35.9. Pearson's correlation results showed that the average of all indicators is greater than four and the relationship between all indicators is positive, which indicates the influence of each of these indicators on each other. The highest final weight of the six indicators in the AHP FUZZY method belongs to environmental hazards with a weight of 0.201, followed by water resources with a weight of 0.193, and economy with a weight of 0.170. The ranking of climatic regions using the Waspas method showed that in terms of climate change risk in six indicators, semi-arid, dry, Mediterranean, semi-humid, ultra-arid, wet and cold and mountainous regions are ranked 1-7 respectively.

Among the ten threatening factors that threaten humanity in the 21st century, the phenomenon of climate change ranks first. The main issue in the emergence of this phenomenon is its consequences for nature and human life. The purpose of this research is to identify the most important risks caused by climate change and prioritize them with multi-criteria decision making methods. In order to familiarize with climatic effects and test hypotheses, a questionnaire has been prepared for prioritizing climatic effects. In the meantime, useful information was obtained from group discussions to analyze and investigate the issue. The opinions of 25 experts and experts were used to design the questionnaire. The responses of the respondents were evaluated in the form of prioritizing climatic effects based on the fuzzy AHP method and ranking the climatic regions based on the Waspas method. The results show that the coefficient of t in all indicators is greater than zero and the average limit, thus a significant relationship is observed between all indicators and the risk of climate change. The highest coefficient belongs to environmental hazards with a coefficient of 35.9. Pearson's correlation results showed that the average of all indicators is greater than four and the relationship between all indicators is positive, which indicates the influence of each of these indicators on each other. The highest final weight of the six indicators in the AHP FUZZY method belongs to environmental hazards with a weight of 0.201, followed by water resources with a weight of 0.193, and economy with a weight of 0.170. The ranking of climatic regions using the Waspas method showed that in terms of climate change risk in six indicators, semi-arid, dry, Mediterranean, semi-humid, ultra-arid, wet and cold and mountainous regions are ranked 1-7 respectively.

Among the ten threatening factors that threaten humanity in the 21st century, the phenomenon of climate change ranks first. The main issue in the emergence of this phenomenon is its consequences for nature and human life. The purpose of this research is to identify the most important risks caused by climate change and prioritize them with multi-criteria decision making methods. In order to familiarize with climatic effects and test hypotheses, a questionnaire has been prepared for prioritizing climatic effects. In the meantime, useful information was obtained from group discussions to analyze and investigate the issue. The opinions of 25 experts and experts were used to design the questionnaire. The responses of the respondents were evaluated in the form of prioritizing climatic effects based on the fuzzy AHP method and ranking the climatic regions based on the Waspas method. The results show that the coefficient of t in all indicators is greater than zero and the average limit, thus a significant relationship is observed between all indicators and the risk of climate change. The highest coefficient belongs to environmental hazards with a coefficient of 35.9. Pearson's correlation results showed that the average of all indicators is greater than four and the relationship between all indicators is positive, which indicates the influence of each of these indicators on each other. The highest final weight of the six indicators in the AHP FUZZY method belongs to environmental hazards with a weight of 0.201, followed by water resources with a weight of 0.193, and economy with a weight of 0.170. The ranking of climatic regions using the Waspas method showed that in terms of climate change risk in six indicators, semi-arid, dry, Mediterranean, semi-humid, ultra-arid, wet and cold and mountainous regions are ranked 1-7 respectively.

کلیدواژه‌ها English

climate change
Iran
flood
drought
AHP FUZZY
  1. Andric, I., Koc, M., Sami, G., & Ghamdi, A. (2019). A review of climate change implications for built environment: Impacts, mitigation measures and associated challenges in developed and developing countries. Journal of Cleaner Production, 42(211), 83-102, https://doi.org/10.1016/j.jclepro.2018.11.128
  2. Bakshi, N, (2014), Perspective of the legal system of climate change: the positions of developing countries with emphasis on Iran's three scenarios, master's thesis in the field of law - International Law, Payam or University, supervisor Dr. Mojtabi Babaei.
  3. Collins, M., Sutherland, M., Bouwer, L., Cheong, S.-M., Frolicher, ¨ T., Jacot Des Combes, H., Koll Roxy, M., Losada, I., McInnes, K., Ratter, B., Rivera-Arriaga, E., Susanto, R. D., Swingedouw, D., & Tibig, L. (2019). Extremes, abrupt changes and managing risk. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate.
  4. Cronin, J., Anandarajah, G., Dessens, O., (2018). Climate change impacts on the energy system: a review of trends and gaps. Clim. Chang. 151(2), 79–93. https://doi.org/10.1007/s10584-018-2265-4
  5. Daron, J.D., & Stainforth, D.A. (2015). On quantifying the climate of the nautomous Lorenz-63 model. Chaos. 25(4), 043103. https://doi.org/10.1063/1.4916789.
  6. Dubey, R., Altay, N., Gunasekaran, A., Blome, C., Papadopoulos, T., & Childe, S. J. (2018). Supply chain agility, adaptability and alignment: Empirical evidence from the Indian auto components industry. International Journal of Operations and Production Management,  38(1), 129–148.
  7. Dubey, R., Gunasekaran, A., Bryde, D., Dwivedi, Y. K., & Papadopoulos, T. (2020). Blockchain techlogy for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting. International Journal of Production Research, 58(11), 3381–3398.
  8. Dubey, R., Gunasekaran, A., Childe, S. J., Wamba, S. F., Roubaud, D., & Foropon, C. (2021). Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. International Journal of Production Research, 59(1),110–128.
  9. Dubey, R., Gunasekaran, A., Childe, S. J., Blome, C., & Papadopoulos, T. (2019), Big data and predictive analytics and manufacturing performance: Integrating institutional theory, resource-based view and big data culture. British Journal of Management, 30(2), pp 341–361.
  10. El-Kassar, A. N., & Singh, S. K. (2018). Green invation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices. Techlogical Forecasting and Social Change, 144(4), 483–498.
  11. Er Kara, M., Ghadge, A., & Bititci, U. S. (2020). Modelling the impact of climate change risk on supply chain performance. International Journal of Production Research, 22(2). 1–19.
  12. Farmer, J.D., Hepburn, C., Ives, M.C., Hale, T., Wetzer, T., Mealy, P., Rafaty, R., Srivastav, S., Way, R., (2019). Sensitive intervention points in the post-carbon, transition. Science, 364(6436), 132–134. https://doi.org/10.1126/science. aaw7287.
  13. Fleurbaey, M., Ferranna, M., Budolfson, M., Dennig, F., Mintz-Woo, K., Socolow, R., Spears, D., Zuber, S., (2019). The social cost of carbon: valuing inequality, risk, and population for climate policy. Monist.  102 (1) 84–109.
  14. Gebrewahid, Y., Sengal, S., Meresa, E., Eyasu, G., Abay, K., Gebreab, G., Kidanemariam, K., Adissu, G., Abrha, G., & Darcha, G. (2020). Current and future predicting potential areas of Oxytenanthera abyssinica (A. Richard) using MaxEnt model under climate change in rthern Ethiopia. Ecol. Process.  9(15) ,1-17.  https://doi. org/10.1186/s13717-019-0210-8
  15. Hansen, L. P. (2022). Central banking challenges posed by uncertain climate change and natural disasters, Journal of Monetary Ecomics, 32(125),1–15, https://doi.org/10.1016/j.jmoneco.2021.09.010
  16. Hürlimann, Anna C., Nielsen, Josh., Moosavi, S., Bush, J., Georgia, W-M., & March, A. (2022). Climate change preparedness across sectors of the built environment – A review of literature. Environmental Science and Policy, 32(128), 277–289, https://doi.org/10.1016/j.envsci.2021.11.021
  17. Hurlimann, A., Moosavi, S., Browne, G., (2021). Climate change transformation: a defnition and typology to guide decision making in urban environments. Sustain. Cities Soc. 70(4). 323- 343.
  18. Mohammed, M., Humaiqani, Al., Sami, G., & Ghamdi, Al. (2022). The built environment resilience qualities to climate change impact: Concepts, frameworks, and directions for future research. Sustainable Cities and Society, 20(80), 103797. https://doi.org/10.1016/j.scs.2022.103797
  19. uri Imamzad, Hassan: Mireshkaran, Yahya, (2019), the effect of climate changes on the unrest resulting from water resource tension (case study: East of Isfahan), Climate Change Research Journal, 1(3),35-51.
  20. Oh, J.J., Choi, Y-S., sun Kim, G., & Kim, G-H. (2022). Assessment of the effects of projected climate change on the potential risk of wood decay in Korea, Journal of Cultural Heritage, 13)55(, 43–47. https://doi.org/10.1016/j.culher.2022.02.004
  21. Papadopoulos, T., & Balta, M.E.  (2022). Climate Change and big data analytics: Challenges and opportunities, International Journal of Information Management, 13(63), 102448, https://doi.org/10.1016/j.ijinfomgt.2021.102448
  22. Rising, J. A., Taylor. C., Matthew, C. Ives, c., & Robert E.T. (2022). Challenges and invations in the ecomic evaluation of the risks of climate change, Ecological Ecomics, 46(197), 107437, https://doi.org/10.1016/j.ecolecon.2022.107437
  23. Rohat, G., Johannes, R., Flacke, A., Dosio, S., Pedded, H., & Martinvan, M.  2019, Influence of changes in socioecomic and climatic conditions on future heat-related health challenges in Europe, Global and Planetary Change,  31, Vol 127, pp 45-59. https://doi.org/10.1016/j.gloplacha.2018.09.013
  24. Salehi, S., Pazukinejad, Z. (2021), adaptation of villagers to climate changes and its relationship with social factors (case study: villagers of Babolsar city - Mazandaran province, Iranian social issues strategic research journal, 10(1), 70 -47.
  25. Sina, D., Chang-Richards, A.Y., Wilkinson, S., & Potangaroa, R.  (2019). A conceptual framework for measuring livelihood resilience: relocation experience from Aceh. Indonesia. World Dev. 117(3), 253–265. https://doi.org/10.1016/j. worlddev.2019.01.003.
  26. Tavakoli, A, (2018), analysis of the factors affecting the emission of greenhouse gases (GHGs) and the potentials of emission reduction in Iran, Quarterly, Journal of Energy Ecomics Studies, 60(3). 10-77.
  27. Vahdat, B, (2018), Legal Effects of Iran's Joining the Paris Climate Agreement, Master's Degree (M.A) Thesis, Law, Public Law, Islamic Azad University, Bandar Abbas Branch, Supervisor Dr. Abdul Naeem Shahriari.
  28. Wang, P., Qiao, W., Wang, Y., Cao, Sh., & Zhang, Y. (2020). Urban drought vulnerability assessment – A framework to integrate socio-ecomic, physical, and policy index in a vulnerability contribution analysis. Sustain. Cities. Soc. 54(2), 102004 https://doi. org/10.1016/j.scs.2019.102004.
  29. Xian, Y., Liu, Guilin., & Zhong, L. (2022). Will citrus geographical indications face different climate change challenges in China? Journal of Cleaner Production, 87(356), 131885, https://doi.org/10.1016/j.jclepro.2022.131885
پژوهش های اقلیم شناسی
دوره 1403، شماره 57 - شماره پیاپی 57
سال پانزدهم | شماره 57| بهار 1403
پاییز 1403
صفحه 247-260