فاکتورهای محیطی مؤثر بر ابتلای به بیماری کووید-19: بررسی شکاف‌ مطالعاتی (مورد پژوهی: شهر تبریز)

نوع مقاله : پژوهشی-مطالعه موردی

نویسندگان

• شیوا غفاری جباری ¹
• عباس یزدانفر ¹
• محمدعلی خانمحمدی ¹
• همایون صادقی بازرگانی ²
• مصطفی فرح بخش ³

¹ دانشکده معماری و شهرسازی، دانشگاه علم و صنعت ایران، تهران، ایران

² گروه آمار و اپیدمیولوژی، مرکز تحقیقات پیشگیری از آسیبهای ترافیکی، دانشگاه علوم پزشکی تبریز، تبریز، ایران

³ مرکز تحقیقات روانپزشکی و علوم رفتاری، دانشگاه علوم پزشکی تبریز، تبریز، ایران

https://doi.org/10.22067/jgusd.2022.76265.1187

چکیده

به منظور کنترل همه‌گیری کووید-19، متخصصان تلاش داشته­اند تا عوامل محیطی مؤثر بر شیوع همه­گیری را شناسایی کنند. اما مروری بر ادبیات موضوع نشان می­دهد در شناسایی این عوامل، نظر عموم افراد چندان مدنظر  نبوده است. درصورتیکه، ایشان به دلیل تعامل مداوم، می‌توانند آگاهی بیشتری نسبت به عوامل تهدیدکننده در محیط زندگیشان داشته باشند. هدف این تحقیق، شناسایی عوامل محیطی است که با وجود اینکه از طریق اختلال در فاصله‌گذاری اجتماعی، باعث ایجاد احساس خطر ابتلا به کووید-19 می‌شوند، در ادبیات موضوع مورد توجه نبوده‌اند. تحقیق حاضر از نوع اکتشافی است که درآن با استفاده از پرسشنامه‌ای باز، عوامل محیطی مختل‌کننده بررسی شده‌اند. سپس، با استفاده از روش تحلیل محتوا، پاسخ‌ها کدگذاری و با استفاده از روش آنتروپی‌شانون، وزندهی شده‌اند. درنهایت، با مقایسه متغیر پراهمیت با متغیرهای حاصل از مرور ادبیات، شکاف مطالعاتی مورد بحث قرار گرفته است. نتایج نشان می‌دهد که از میان ویژگی‌های  محیط ساخته شده، برخی از کاربری‌ها (نظیر نانوایی‌ها)، ویژگی‌های مسیرهای رفت‌وآمد (نظیر ماشین‌های پارک شده) و تسهیلات شهری (نظیر زیرساخت‌های خرید آنلاین) از نظر عموم افراد می‌توانند بر احتمال ابتلا تأثیرگذار باشند. همچنین عواملی نظیر آلودگی صوتی نیز می‌توانند با تأثیر بر سلامت روانی بر احساس خطر ابتلا در محیط بیافزایند. بعلاوه، بر اساس نتایج، توجه به میزان رعایت بهداشت فردی و جمعی و برخی از رفتارهای عمومی، در ارتباط با مقوله فرهنگی-اجتماعی، و  توجه به دستفروشی، در ارتباط با مقوله ناهنجاری­های اجتماعی، نیز ضروری بنظر می آید. در ضمن، در تحقیق حاضر عوامل محیطی جدیدتری نیز معرفی شدند که در برنامه­ریزی شهری چندان مورد توجه نبوده­اند.

کلیدواژه‌ها

• یزان ابتلا
• کووید-19
• محیط ساخته شده
• عوامل اجتماعی-فرهنگی
• ناهنجاری‌های اجتماعی

موضوعات

• برنامه ریزی شهری

عنوان مقاله [English]

Evaluating Energy Efficiency in Urban Rules and Regulations with an Emphasis on Zoning Model (Case Study: District 6 of Tehran City)

نویسندگان [English]

• Shiva Ghafari Jabari ¹
• Abass Yazdanfar ¹
• Mohamad Ali Khan Mohammadi ¹
• Homayoun Sadeghi Bazargani ²
• Mostafa Farah Bakhsh ³

¹ Architecture Department, Iran University of Science and Technology, Tehran, IRAN

² Road Traffic Injury Prevention Research Center, Tabriz University of Medical Sciences, Tabriz, Iran

³ Research Center of Psychiatry and Behavioral Sciences, Tabriz University of Medical Sciences, Tabriz, Iran

چکیده [English]

Extended Abstract

Introduction

Energy consumption in Iran is currently very high and the energy efficiency of cities is low. Therefore, it seems necessary to prepare urban rules and regulations at the most executive level of urban policy making to increase energy efficiency in zoning as the main output of detailed plans. This research was conducted with the aim of exploring and measuring energy efficiency in urban rules and regulations with an emphasis on the zoning model. This research tried to see the relationship between the concepts of urban rules and regulations and energy efficiency and determine what parameters impact upon energy efficiency in urban rules and regulations. It also tried to examine the energy efficiency evaluation framework in urban zoning rules and regulations, their criteria, indicators, and final weights and to see how the energy efficiency of the existing urban fabric and the rule-based simulated urban fabric can be evaluated and compared.

Method

This applied, descriptive-analytical research used a mixed method of qualitative and quantitative methods. To carry out this research, library and field studies, including questionnaire and secondary data analysis and Analytical Hierarchy Process (AHP) were used. GIS software and Expert Choice software were also used for this purpose. District 6 of Tehran city was selected as the case to be studied in this study.

Results

The results showed that the energy efficiency evaluation criteria in urban rules and regulations that emphasize on the zoning model are as follow in terms of priority, importance, and weight obtained from the Analytical Hierarchy Process (AHP): Land use zoning, passive urban design for making thermal comfort, compactness, and connected network.

Discussion and Conclusion

Exploring energy efficiency in both scenarios (the current situation and the simulated context based on the implementation of the zoning rules and regulations of the detailed plan) and comparing them showed that since there is not any rules and regulations pertaining to the main criteria of this study (passive urban design for the creation of thermal comfort and connected network in the zoning of the detailed plan of 2019 of District 6 of Tehran city), the two criteria have been considered to be fixed in both scenarios. So, if we suppose that zoning rules and regulations are fully executed, no change will happen in the status quo of the scenarios. That is, both criteria have similar energy efficiency in both scenarios.
Moreover, the energy efficiency based on the density criterion in the simulated scenario has increased by 39.85% compared to the existing scenario. This means that regarding this criterion, implementing zoning rules and regulations (including employment level and building density) have increased the density of the fabric compared. The zoning rules and regulations of the detailed plan in District 6 of Tehran, based on the density criterion, have played an effective role in increasing the energy efficiency of the simulated scenario. Moreover, comparing the status-quo scenario and the detailed plan zoning scenario regarding the other variable criterion (that is, land use zoning, which is also considered the most significant criterion of this research) showed that energy efficiency decreased when zoning rules and regulations have been implemented. The issue, in turn, clearly shows that the rules and regulations do not guarantee energy efficiency based on land use zoning indicators (such as green and open spaces, mixed areas, and housing type). Comparing the scenarios clearly showed that the energy efficiency based on land use zoning criteria in the zoning scenario of the detailed plan has decreased by 45.55% compared to the existing scenario.
The most significant finding of this study clearly showed that the energy efficiency has decreased by 22.25%, considering the weighted overlap of criteria in District 6 of Tehran in the zoning scenario and assuming the application of the related urban criteria. Considering this decrease, one can conclude that the urban rules and regulations are not effective in terms of energy efficiency. That is, if the rules are executed, they will increase energy consumption in urban areas and make worse the environmental consequences.
Taking account the findings, it is suggested that when establishing zoning laws and regulations, which is a criterion for the implementation of all future constructions, their undeniable role in energy efficiency be considered, and then all decisions be made based on criteria related to energy efficiency. This study evaluated the energy efficiency in urban rules and regulations with an emphasis on zoning in District 6 of Tehran. Considering the results, the following suggestions are made: The establishment of zoning rules and regulations that are compatible with various types of climates in Iran, and considering such applied factors as population density, density of residential units, general pattern of road network, the size of urban blocks, the length of urban blocks, the orientation of main streets, the orientation of buildings, and types of houses. The final aim is to improve energy efficiency.
 
 
 

کلیدواژه‌ها [English]

• Keywords: Energy Efficiency
• Urban Rules and Regulations
• Zoning
• Tehran
• GIS Software

©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0).

مراجع

1.  

   1. پورمحمدی، م.ر.، و جام کسری، م. (1389). ارزیابی ناپایداری در توسعة فضایی متروپل تبریز. مطالعات و پژوهش‌های شهری و منطقه‌ای، 4(1)، 18-1.
   2. رنجبر، ه.، حقدوست، ع.‌ا.، صلصالی، م.، خوشدل، ع.، سلیمانی، م.ع.، و بهرامی، ن. (1391). نمونه‌گیری در پژوهش‌های کیفی: راهنمایی برای شروع. دانشگاه علوم پزشکی ارتش جمهوری اسلامی ایران، 3(1)، 250-238.
   3. صحراگرد منفرد، ن. (1394). مدل مؤلفه‌های طراحی مرکز محله مشارکت محور با رویکرد ادراکی (نمونه موردی: مرکز محله چیذر). پایان­نامه دکتری، تهران: دانشگاه علم و صنعت ایران.
   4. مجتبایی، م. (1400). گروه‌بندی جدید مشاغل صنفی برای تعطیلی کرونایی https://donya-e-eqtesad.com.

    

   5. Andersen, L. M., Harden, S. R., Sugg, M. M., Runkle, J. D., & Lundquist, T. E. (2021). Analyzing the spatial determinants of local Covid-19 transmission in the United States. Science of the Total Environment, 754, 1-14.
   6. Blut, M., & Iyer, G. R. (2020). Consequences of Perceived Crowding: A Meta-Analytical Perspective. Journal of Retailing, 96(3), 362–382.
   7. Center of Disease Control. (2021, November 22). Risk for COVID-19 Infection, Hospitalization, and Death By Age Group. https://www.cdc.gov/coronavirus/2019-ncov/covid-data/investigations-discovery/hospitalization-death-by-age.html.
   8. Chang, T. S. (2021). Social distancing in retail: Influence of perceived retail crowding and self-efficacy on employees’ perceived risks. Journal of Retailing and Consumer Services, 62(2021), 1-9.
   9. Conger, A. J. (2017). Kappa and rater accuracy: Paradigms and parameters. Educational and Psychological Measurement, 77(6), 1019–1047.
   10. Cullen, W., Gulati, G., & Kelly, B. D. (2020). Mental health in the COVID-19 pandemic. An International Journal of Medicine, 113(5), 311–312.
   11. Duan, L., & Zhu, G. (2020). Psychological interventions for people affected by the COVID-19 epidemic. Lancet Psychiatry, 7, 300–302.
   12. Duhon, J., Bragazzi, N., & Kong, J. D. (2021). The impact of non-pharmaceutical interventions, demographic, social, and climatic factors on the initial growth rate of COVID-19: A cross-country study. Science of the Total Environment, 760, 1-9.
   13. Feizizadeh, B., & Blaschke, T. (2013). Land suitability analysis for Tabriz County, Iran : a multi-criteria evaluation approach using GIS. J. Environ. Plan. Manag, 56(1), 1–23.
   14. Ferrara, M., Langiano, E., Falese, L., De Marco, A., & De Vito, E. (2021). Quality of life and psychosocial impacts of the different restrictive measures during one year into the COVID-19 pandemic on patients with cancer in Italy: An ecological study. International Journal of Environmental Research and Public Health, 18(13), 1-14.
   15. Frank, L. D. L. D., Iroz-Elardo, N., MacLeod, K. E., & Hong, A. (2019). Pathways from the built environment to health: A conceptual framework linking behavior and exposure-based impacts. Journal of Transport & Health, 12, 319–335.
   16. Fraser, J., Bazuin, J. T., & Hornberger, G. (2015). The privatization of neighborhood governance and the production of urban space. Environment and Planning A, 48(5), 844–870.
   17. Gargiulo, C., Gaglione, F., Guida, C., Papa, R., Zucaro, F., & Carpentieri, G. (2020). The role of the urban settlement system in the spread of the Covid-19 pandemic. The Italian case. Tema - Journal of Land Use, Mobility, and Environment, 14, 189–212.
   18. Hamidi, S., Sabouri, S., & Ewing, R. (2021). Does Density Aggravate the Covid-19 Pandemic? Journal of the American Planning Association, 86(4), 495–509.
   19. Honigsbaum, M. (2020). The pandemic century: one hundred years of panic, hysteria, and hubris. US: W. W. Norton & Company.
   20. Kan, Z., Kwan, M. P., Wong, M. S., Huang, J., & Liu, D. (2021). Identifying the space-time patterns of COVID-19 risk and their associations with different built environment features in Hong Kong. Science of the Total Environment, 772, 145379.
   21. Kwok, C. Y. T., Wong, M. S., Chan, K. L., Kwan, M. P., Nichol, J. E., Liu, C. H., Wong, J. Y. H., Wai, A. K. C., Chan, L. W. C., Xu, Y., Li, H., Huang, J., & Kan, Z. (2021). Spatial analysis of the impact of urban geometry and socio-demographic characteristics on COVID-19, a study in Hong Kong. Science of the Total Environment, 764, 1-15.
   22. Li, X., Zhou, L., Jia, T., Peng, R., Fu, X., & Zou, Y. (2020). Associating COVID-19 severity with urban factors: A case study of Wuhan. International Journal of Environmental Research and Public Health, 17(18), 1–20.
   23. Liu, L. (2020). Emerging study on the transmission of the Novel Coronavirus (COVID-19) from urban perspective: evidence from China. Cities, 103, 1-11.
   24. Lowe, A., Norris, A. C., Farris, A. J., & Babbage, D. R. (2018). Quantifying Thematic Saturation in Qualitative Data Analysis. Field Methods, 30(3), 191–207.
   25. Montes-González, D., Vílchez-Gómez, R., Barrigón-Morillas, J. M., Atanasio-Moraga, P., Rey-Gozalo, G., & Trujillo-Carmona, J. (2018). Noise and Air Pollution Related to Health in Urban Environments. Proceedings, 2(20), 1-5.
   26. Qiu, Y., Chen, X., & Shi, W. (2020). Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China. Journal of Population Economics, 33(4), 1127–1172.
   27. Szczygiel, B., & Hewitt, R. (2000). Nineteenth-Century Medical Landscapes: John H. Rauch, Frederick Law Olmsted, and the Search for Salubrity. Bulletin of the History of Medicine, 74(4), 708–734.
   28. UN-Habitat. (2021, March 12). Cities and Pandemics : Towards a More Just, Green and Healthy Future. https://unhabitat.org/sites/default/files/2021/03/cities_and_pandemics-towards_a_more_just_green_and_healthy_future_un-habitat_2021.pdf
   29. United Nations. (2018). Agglomerations with 300,000 Inhabitants or More in 2018, by country. United Nations: Department of Economic and Social Affairs, Population Division.
   30. Urban, R. C., & Nakada, L. Y. K. (2021). GIS-based spatial modeling of COVID-19 death incidence in São Paulo, Brazil. Environment & Urbanization, 33(1), 229–238.
   31. Vaz, E. (2021). COVID-19 in Toronto: A spatial exploratory analysis. Sustainability (Switzerland), 13(2), 1–15.
   32. Venter, Z. S., Barton, D. N., Gundersen, V., Figari, H., & Nowell, M. (2020). Urban nature in a time of crisis : recreational use of green space increases during the COVID-19 outbreak in Oslo, Norway. Environmental Research Letters. 15 (2020), 1-11.
   33. World Health Organization. (2009, December 26). Night Noise Guidelines for Europe. https://www.euro.who.int/__data/assets/pdf_file/0017/43316/E92845.pdf.
   34. World Health Organization. (2021, December 2). COVID-19 infection prevention and control guidance. https://www.who.int/westernpacific/emergencies/covid-19/technical-guidance/infection-prevention-control.
   35. Wu, X., Yin, J., Li, C., Xiang, H., Lv, M., & Guo, Z. (2021). Natural and Human Environment Interactively Drive Spread Pattern of COVID-19: A City-level Modeling Study in China. Science of the Total Environment, 756, 1-9.
   36. Xie, J., Luo, S., Furuya, K., & Sun, D. (2020). Urban Parks as Green Bu ff ers During the COVID-19 Pandemic. Sustainability (Switzerland), 12, 1–17.
   37. Yip, L. T., Huang, Y., & Liang, C. (2021). Built environment and the metropolitan pandemic: Analysis of the COVID-19 spread in Hong Kong. Building and Environment, 188, 1-17.
   38. You, H., Wu, X., & Guo, X. (2020). Distribution of COVID-19 morbidity rate in association with social and economic factors in Wuhan, China: Implications for urban development. International Journal of Environmental Research and Public Health, 17(10), 1-14.
   39. Zahir, A. M., Oli, A., Zhou, A., Sang, H., Liu, S., & Akbaruddin, A. (2020). Epidemic of COVID-19 in China and associated Psychological Problems. Asian Journal of Psychiatry, 51(2020), 1-7,