عنوان مقاله [English]
In the present study, in order to monitor and project climate change impacts on model of the bioclimatic design, a comparative study was conducted between the Middle East and Eurasia as two different climates. This paper used the basic data from 1990 to 2010, and the CMIP5 climate models have been used to project the climate data (radiation, temperature, wind speed, and relative humidity) from the outputs of CanEMS2 model, which its values have been dynamically downscaled using the RegCM4.6 climate model for the period from 2020 to 2049. In this study, the scenario RCP4.5 was used. The results of this study showed that the average annual temperature for the period 2020–2049 as compared with the present decade can be increased
3.27 °C and 4.71 °C for Tehran and Moscow, respectively. On the other hand, relative humidity changes in future compared to base period can be decreased 4% for Tehran and increased 10.5% for Moscow. The total assessment on climate change in the coming decades can lead to a change in bioclimatic design strategies of buildings for both study areas. Generally, with regard to future climate change for both study areas, the percentage of days needed to provide bioclimatic design strategies in the heating sector can be reduced; however, the need for providing cooling strategies for Tehran can significantly be increased. Although these conditions for Moscow can not change significantly, dehumidification strategies in Moscow can be more significant than of those in Tehran for the coming period.
Aljawabra, F. and Nikolopoulou, M., 2018, Thermal comfort in urban spaces: a cross-cultural study in the hot arid climate. Int. J. Biometeorol, 62, (10), 1901-1909.
Bauer, N., McGlade, C. and Hilaire, J., 2018, Divestment prevails over the green paradox when anticipating strong future climate policies. Nat. Clim. Chang., 8, 130–134.
Belcher, S., Hacker, J. and Powell, D., 2005, Constructing design weather data for future climates. Build. Serv. Eng. Res. Technol, 26 (1), 49–61.
Eewell, J., McCollum, D. and Emmerling, J., 2018, Limited emission reductions from fuel subsidy removal except in energy-exporting regions. Nature, 554, 229–233.
Gunningham, N., 2017, Building norms from the grassroots up: divestment, expressive politics and climate change. Law & Policy, 39, 372–392.
Ghanghermeh, A., Roshan, G., Orosa, J. A., Calvo-Rolle, J. L. and Costa, Á. M., 2013, New climatic indicators for improving urban sprawl: a case study of Tehran city. Entropy, 15(3), 999-1013.
Iran Energy Balance, 2010, Iran Central Bank.
Iyengar, K., 2015, Sustainable architectural Design: an overview. Routledge.
Klimenko, V. V., Fedotova, E. V. and Tereshin A. G., 2017, Vulnerability of the Russian power industry to the climate, change. Energy, doi: 10.1016/j. energy. 2017.10.069
Klimenko, V. V., Ginzburg, A. S., Demchenko, P. F., Tereshin, A. G., Belova, I. N. and Kasilova, E. V., 2016, Impact of Urbanization and Climate Warming on Energy Consumption in Large Cities. Doklady Akademii Nauk, 470, 519–524.
Köhler, M. and Michaelowa, A., 2014, Limiting climate change by fostering net avoided emissions. Carbon Clim. Law. Rev., 8, 55–64.
Lazarus, M. and van Asselt, H., 2018, Fossil fuel supply and climate policy: exploring the road less taken, Climatic Change, 150, (1-2), 1–13.
Liggett, R. and Milne, M., 2017, Climate Consultant Help. University of California at Los Angeles (UCLA).
McGlade, C. and Ekins, P., 2015, The geographical distribution of fossil fuels unused when limiting global warming to 2°C. Nature, 517, 187–190
Varentsov, M. I., Konstantinov, P. I. and Samsonov, T. E., 2017, Mesoscale modelling of the summer climate response of Moscow metropolitan area to urban expansion. IOP Conf. Ser.: Earth Environ. Sci. 96 012009
Moshiri, S., Atabi, F., Panjeshahi, M. H. and lechtenboehmer, S., 2012, Long run energy demand in Iran: a scenario analysis. Int. J. Energy Sect. Manag, 6(1), 120–144.
Pierangioli, L., Cellai, G., Ferrise, R., Trombi, G. and Bindi, M., 2017, Effectiveness of passive measures against climate change: Case studies in Central Italy, Build Simul., 10, 459–79.
Rogelj, J., den Elzen, M. and Höhne, N., 2016, Paris agreement climate proposals need a boost to keep warming well below 2 °C. Nature, 534, 631–639.
Roshan, Gh. R., Orosa, J. A. and Nasrabadi, T., 2012, Simulation of climate change impact on energy consumption in buildings, case study of Iran, Energy Policy, 49, 731-739.
Roshan, Gh. R., Shahraki, S. Z., Sauri, D., and Borna, R., 2010, Urban sprawl and climatic changes in Tehran, Environ. Health. Sci., 7(1), 43-52.
Roshan, G., Arab, M. and Klimenko, V. 2019, Modeling the impact of climate change on energy consumption and carbon dioxide emissions of buildings in Iran. J. Environ. Health. Sci. Engineer. 1-18. https://doi.org/10.1007/s40201-019-00406-6.
Roshydromet: http://www.global-climate- change.ru/index. php/ru/climate-rf/78-about- climate-rf/180-doklad-o-klimate-rf-za-2011.
Rubio-Bellido, C., Pérez-Fargallo, A. and Pulido-Arcas, J. A., 2016, Optimization of annual energy demand in office buildings under the influence of climate change in Chile. Energy, 114, 569–85.
Saboohi, R., Soltani, S. and Khodagholi, M. Saboohi, R., Soltani, S. and Khodagholi, M., 2012, Trend analysis of temperature parameters in Iran. Theor. Appl. Climatol., 109, 529–547.
Schipper, L., 2000, On the rebound: the interaction of energy efficiency, energy use and economic activity An introduction. Energy Policy, 28, 351–353.
Sharmin, T. and Steemers, K., 2018, Effects of microclimate and human parameters on outdoor thermal sensation in the high-density tropical context of Dhaka. Int. J. Biometeorol, https://doi.org/10.1007/ s0048.
Sharmina, M., Anderson, K. and Bows-Larkin, A., 2013, Climate change regional review: Russia. WIREs Clim. Change, 4, 373–396. doi: 10.1002/wcc.236.
Shifteh, Some’e, B., Ezani, A., and Tabari, H., 2012, Spatiotemporal trends and change point of precipitation in Iran. Atmos. Res., 113, 1–12.
Soltani, S., Saboohi, R. and Yaghmaei, L., 2011, Rainfall and rainy days trend in Iran. Clim. Chang., doi:10.1007/s10584-011-0146-1.
Stewart, R. B., Oppenheimer, M. and Rudyk, B., 2013, Reaching international cooperation on climate change mitigation: building a more effective global climate regime through a bottom-up approach, Theoretical Inq. L., 14, 273–307.
Sedov, V. E., 2012, On climatic fluctuations and climate trends of modern Moscow. Russ. Meteorol. Hydrol., 37, 537-545.
Tabari, H. and Hosseinzadeh Talaee, P., 2011a, Recent trends of mean maximum and minimum air temperatures in the western half of Iran. Meteor. Atmos. Phys., 111, 121–131.
Tabari, H. and Hosseinzadeh Talaee, P., 2011b, Temporal variability of precipitation over Iran: 1966–2005. J. Hydrol., 396(3–4), 313–320.
Tabari, H., Hosseinzadeh Talaee, P., Ezani, A. and Shifteh Some’e, B., 2011a, Shift changes and monotonic trends in autocorrelated temperature series over Iran. Theor. Appl. Climatol., 109, 95–108.
Tabari, H., Shifteh, Some’e, B. and Rezaeian, Z.M., 2011b, Testing for long-term trends in climatic variables in Iran. Atmos. Res., 100, 132–140.
UNDP (United Nations Development Program), 2010, Department of environment. Iran second national communication to United Nations framework convention on climate change (UNFCCC). National climate office, department of environment, Tehran.
Wang, H. and Chen, Q., 2014, Impact of climate change heating and cooling energy use in buildings in the United States, Energy Build, 82, 428–36.
Zarenistanak, M., Dhorde, A. and Kripalani, R. H., 2014a, Temperature analysis over southwest Iran: trends and projections. Theor. Appl. Climatol., 116, 103–117.
Zarenistanak, M., Dhorde, A. and Kripalani, R. H., 2014b, Trend analysis and change point detection of annual and seasonal precipitation and temperature series over southwest Iran. J. Earth. Syst. Sci., 123, 281-295.
Zhou, Y., Clarke, L., Eom, J., Kyle, P., Patel, P., and Kim, SH., 2014, Modeling the effect of climate change on U.S. state-level buildings energy demands in an integrated assessment framework. Appl Energy, 113, 1077–88.
Zhu, M., Pan, Y., Huang, Z. and Xu, P., 2016, An alternative method to predict future weather data for building energy demand simulation under global climate change. Energy Build, 113, 74–86.