ارزیابی و اولویت‌بندی معیار‌های توسعه بام سبز به روش بهترین-بدترین

نوع مقاله : علمی - پژوهشی

نویسندگان

1 استادیار - دانشکده عمران و معماری. دانشگاه سجاد. مشهد. ایران

2 دانشجوی کارشناسی ارشد . دانشکده عمران و معماری. دانشگاه سجاد مشهد

چکیده

در سالهای اخیر، سطح فضای سبز در شهرهای بزرگ به دلیل افزایش تمایل به شهرنشینی و نیاز به ساخت مجتمع‌های مسکونی رو به کاهش بوده است. به منظور رفع این معضل و ایجاد توسعه پایدار شهری، بام سبز به عنوان یکی از راه‌های مفید پیشنهاد شده است. بنابراین ضرورت دارد که توجه ویژه‌ای به استفاده از آن گردد تا بتوان ایجاد امکانات و رفاه شهری را در کنار حفظ سلامت شهروندان شاهد باشیم . هدف این تحقیق ارزیابی و اولویت‌بندی معیارهای مؤثر در توسعه بام سبز بوده است. بدین جهت با بهره‌جویی از مطالعات کتابخانه‌ای و نظرات خبرگان، معیارها در سه گروه محیط زیستی، اقتصادی و اجتماعی و مشتمل بر سیزده زیرمعیار استخراج و طبقه‌بندی گردید. پس از بررسی و تایید روایی و پایایی و جمع آوری پرسش‌نامه‌های توزیع شده بین خبرگان، آنالیز داده‌ها به کمک روش بهترین-بدترین معرفی انجام شد. نتایج نشان داد که شاخص اقتصادی مقدم بر دو شاخص دیگر است. ثانیاً، مهمترین زیرمعیار در گروه‌های محیط زیستی، اقتصادی و اجتماعی به ترتیب افزایش کیفیت هوا و کاهش آلاینده‌ها، افزایش عمر پوسته بام و ارتقای سلامت عمومی افراد بوده است. در نهایت، با در نظر گرفتن کل معیارها، افزایش عمر پوسته بام به عنوان نخستین و گسترش و تنوع زیستگاه جانداران به عنوان آخرین معیار رتبه‌بندی شدند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Evaluation and prioritization of green roof development criteria by using Best-Worst method

نویسندگان [English]

  • Majid Alipour 1
  • Ali Gohari 2
1 Assistant professor. Department of civil and architecture. Sadjad university. Mashhad. Iran
2 Ms.c student. Department of civil and architecture. Sadjad university. Mashhad. Iran
چکیده [English]

Megacities recently are experiencing a shortage of green spaces basically due to an increase in both urbanization demand and residential complexes. In order to solve this problem and create sustainable urban development, green roofs have been suggested as one of the useful options. Therefore, it is necessary to pay special attention to its use so that we can witness the creation of urban facilities and welfare along with the preservation of citizens' health. The purpose of this research is to evaluate and prioritize effective criteria in the development of green roof. For doing so, by using library studies and experts' opinions, the criteria were extracted and classified into three environmental, economic and social groups, consisting of thirteen sub-criteria. After checking and confirming validity and reliability and collecting questionnaires distributed among experts, data analysis has been done using the best-worst method. The results shows that economic indicator attract the highest priority among others. Additionally, the most important sub-criteria in environmental, economic, and social groups was air quality, roof longevity, and public health, respectively. Finally, the respective highest and lowest scores were assigned to roof longevity and biodiversity when all criteria were considered. However these results may change in other countries .

کلیدواژه‌ها [English]

  • Green roof
  • Sustainable development
  • Indicator
  • Prioritization
  • Best-Worst
[1] Karteris, M. Theodoridou, I. Mallinis, G. Tsiros, E. and Karteris, A. (2016). Towards a green sustainable strategy for Mediterranean cities: Assessing the benefits of large-scale green roofs implementation in Thessaloniki, Northern Greece, using environmental modelling, GIS and very high spatial resolution remote sensing data. Renewable and Sustainable Energy Reviews, 58, 510-525. https://doi.org/10.1016/j.rser.2015.11.098.
[2] Wu, J. (2014). Urban ecology and sustainability: The state-of-the-science and future directions. Landscape and urban planning, 125, 209-221. https://doi.org/10.1016/j.landurbplan.2014.01.018.
[3] Refahi, A. H. and Talkhabi, H. (2015). Investigating the effective factors on the reduction of energy consumption in residential buildings with green roofs. Renewable Energy, 80, 595-603. https://doi.org/10.1016/j.renene.2015.02.030.
[4] Vijayaraghavan, K. (2016). Green roofs: A critical review on the role of components, benefits, limitations and trends. Renewable and sustainable energy reviews, 57, 740-752. https://doi.org/10.1016/j.rser.2015.12.119.
[5] Sangkakool, T. Techato, K. Zaman, R. and Brudermann, T. (2018). Prospects of green roofs in urban Thailand–A multi-criteria decision analysis. Journal of cleaner production, 196, 400-410. https://doi.org/10.1016/j.jclepro.2018.06.060.
[6] Guzmán-Sánchez, S. Jato-Espino, D. Lombillo, I. and Diaz-Sarachaga, J. M. (2018). Assessment of the contributions of different flat roof types to achieving sustainable development. Building and Environment, 141, 182-192. https://doi.org/10.1016/j.buildenv.2018.05.063.
[7] Mahdiyar, A. Tabatabaee, S. Durdyev, S. Ismail, S. Abdullah, A. and Rani, W.N.M.W.M. (2019). A prototype decision support system for green roof type selection: A cybernetic fuzzy ANP method. Sustainable cities and society, 48, p.101532. https://doi.org/10.1016/j.scs.2019.101532.
[8] Rosasco, P. and Perini, K. (2019). Selection of (green) roof systems: A sustainability-based multicriteria analysis. Buildings, 9(5), p.134. https://doi.org/10.3390/buildings9050134.
[9] Rowe, B. (2018). Chapter 3.5 - Green roofs for pollutants’ reduction. In: Nature based strategies for urban and building sustainability. Oxford: Butterworth-Heinemann, 141-148. https://doi.org/10.1016/B978-0-12-812150-4.00013-6.
[10] Whittinghill, L. J. Rowe, D. B. Schutzki, R. and Cregg, B. M. (2014). Quantifying carbon sequestration of various green roof and ornamental landscape systems. Landscape and Urban Planning, 123, 41-48. https://doi.org/10.1016/j.landurbplan.2013.11.015.
[11] Palla, A. and Gnecco, I. (2018). Chapter 3.11 - Green Roofs to Improve Water Management. In: Nature Based Strategies for Urban and Building Sustainability. Oxford: Butterworth-Heinemann, 203-213. https:// doi.org/10.1016/B978-0-12-812150-4.00019-7.
[12] Coma, J. Pérez, G. Cabeza, L.F. (2018). Chapter 4.8 - Life Cycle Assessment of Green Roofs. In: Nature Based Strategies for Urban and Building Sustainability. Oxford:    Butterworth-Heinemann, 341–351. https://doi.org/10.1016/B978-0-12-812150-4.00010-0.
[13] Eakin, C. J. Campa III, H. Linden, D. W. Roloff, G. J. Rowe, D. B. and Westphal, J. (2015). Avian response to green roofs in urban landscapes in the Midwestern USA. Wildlife Society Bulletin, 39(3), 574-582. https://doi.org/10.1002/wsb.566.
[14] Kahn, M. E. and Kok, N. (2014). The capitalization of green labels in the California housing market. Regional Science and Urban Economics, 47, 25-34. https://doi.org/10.1016/j.regsciurbeco.2013.07.001.
[15] Giulio, R.D. (2007). Manuale di manutenzione edilizia. In: Valutazione del Degrado e Programmazione della Manutenzione. 3rd ed. Rimini: Maggioli Editore.
[16] Mahdiyar, A. Tabatabaee, S. Abdullah, A. and Marto, A. (2018). Identifying and assessing the critical criteria affecting decision-making for green roof type selection. Sustainable cities andsociety, 39, 772-783. https://doi.org/10.1016/j.scs.2018.03.007.
[17] Baker, L. de Zeeuw, H. (2015). Cities and agriculture. In: Developing resilient urban food systems. New York and London: Routledge, 26–55.
[18] Connelly, M. and Hodgson, M. (2015). Experimental investigation of the sound absorption characteristics of vegetated roofs. Building and Environment, 92, 335-346. https://doi.org/10.1016/j.buildenv.2015.04.023.
[19] Sabbion, P. (2018). Green streets social and aesthetic aspects. In: Nature Based Strategies for Urban and Building Sustainability. Oxford: Butterworth-Heinemann, 283-290. https://doi.org/10.1016/B978-0-12-812150-4.00026-4. 
[20] Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. https://doi.org/10.1016/j.omega.2014.11.009.
[21] Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130. https://doi.org/10.1016/j.omega.2015.12.001.
[22] Zolfani, S. H. and Chatterjee, P. (2019). Comparative evaluation of sustainable design based on Step-Wise Weight Assessment Ratio Analysis (SWARA) and Best Worst Method (BWM) methods: a perspective on household furnishing materials. Symmetry, 11(1), 74. https://doi.org/10.3390/sym11010074.
[23] Rezaei, J. van Roekel, W. S. and Tavasszy, L. (2018). Measuring the relative importance of the logistics performance index indicators using Best Worst Method. Transport Policy, 68, 158-169. https://doi.org/10.1016/j.tranpol.2018.05.007.
[24] Tavasszy, L. van de Kaa, G. and Liu, W. (2020). Importance of freight mode choice criteria: An MCDA approach. Journal of Supply Chain Management Science, 1(1-2), 27-44. https://doi.org/10.18757/jscms.2020.4651.
[25] Singh, A. Asjad, M. Gupta, P. Khan, Z. A. and Siddiquee, A. N. (2021). Measuring the Relative Importance of Reconfigurable Manufacturing System (RMS) Using Best–Worst Method (BWM). In: Advances in Electromechanical Technologies. Singapore: Springer, 253-275. https://doi.org /10.1007/978-981-15-5463-6_24.
[26] Kaushik, V. Kumar, A. Gupta, H. and Dixit, G. (2020). Modelling and prioritizing the factors for online apparel return using BWM approach. Electronic Commerce Research, 1-31. https://doi.org/10.1007/s10660-020-09406-3.
[27] Ecer, F. (2021). Sustainability assessment of existing onshore wind plants in the context of triple bottom line: a best-worst method (BWM) based MCDM framework. Environmental Science and Pollution Research, 28(16), 19677-19693. https://doi.org/10.1007/s11356-020-11940-4.