Abstract
This study aimed to assess the impacts of climate change on residential energy consumption in Dhaka city of Bangladesh. The monthly electricity consumption data for the period 2011–2014 and long-term climate variables namely monthly rainfall and temperature records (1961–2010) were used in the study. An ensemble of six global circulation models (GCMs) of coupled model intercomparison project phase 5 (CMIP5) namely, BCCCSM1-1, CanESM2, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, and NorESM1-M under four representative concentration pathway (RCP) scenarios were used to project future changes in rainfall and temperature. The regression models describing the relationship between historical energy consumption and climate variables were developed to project future changes in energy consumptions. The results revealed that daily energy consumption in Dhaka city increases in the range of 6.46–11.97 and 2.37–6.25 MkWh at 95% level of confidence for every increase of temperature by 1 °C and daily average rainfall by 1 mm, respectively. This study concluded that daily total residential energy demand and peak demand in Dhaka city can increase up to 5.9–15.6 and 5.1–16.7%, respectively, by the end of this century under different climate change scenarios.
Similar content being viewed by others
References
Chang, Y. (2015). Energy and environmental policy. The Singapore Economic Review, 60(03), 1–19.
Krigger, J., & Dorsi, C. (2005). Residential Energy: Upper Saddle River. Upper Saddle River: Prentice Hall.
Krese, G., Prek, M., & Butala, V. (2012). Analysis of building electric energy consumption data using an improved cooling degree day method. Strojniški-vestnik Journal of Mechanical Engineering, 58(2), 107–114.
Gong, X., Akashi, Y., & Sumiyoshi, D. (2012). Optimization of passive design measures for residential buildings in different Chinese areas. Building and Environment, 58, 46–57.
Santin, O. G., Itard, L., & Visscher, H. (2009). The effect of occupancy and building characteristics on energy use for space and water heating in Dutch residential stock. Energy and Buildings, 41(11), 1223–1232.
Fabi, V., Andersen, R. V., Corgnati, S., & Olesen, B. W. (2012). Occupants’ window opening behaviour: a literature review of factors influencing occupant behaviour and models. Building and Environment, 58, 188–198.
CIBSE. (2006). Environmental design CIBSE Guide A. London: Chartered Institution of Building Services Engineers.
Genjo, K., Tanabe, S., Matsumoto, S., Hasegawa, K., & Yoshino, H. (2005). Relationship between possession of electric appliances and electricity for lighting and others in Japanese households. Energy and Buildings, 37(3), 259–272.
Wiesmann, D., Lima Azevedo, I., Ferrão, P., & Fernández, J. E. (2011). Residential electricity consumption in Portugal: findings from top-down and bottom-up models. Energy Policy, 39(5), 2772–2779.
Bartusch, C., Odlare, M., Wallin, F., & Wester, F. (2012). Exploring variance in residential electricity consumption: household features and building properties. Applied Energy, 92, 637–643.
Wyatt, P. (2013). A dwelling-level investigation into the physical and socio-economicdrivers of domestic energy consumption in England. Energy Policy, 60, 540–549.
Leahy, E., & Lyons, S. (2010). Energy use and appliance ownership in Ireland. Energy Policy, 38(8), 4265–4279.
Bedir, M., Hasselaar, E., & Itard, L. (2013). Determinants of electricity consumption in Dutch dwellings. Energy and Buildings, 58, 194–207.
McLoughlin, F., Duffy, A., & Conlon, M. (2012). Characterising domestic electricity consumption patterns by dwelling and occupant socio-economic variables: an Irish case study. Energy and Buildings, 48, 240–248.
Hamilton, I. G., Steadman, P. J., Bruhns, H., Summerfield, A. J., & Lowe, R. (2013). Energy efficiency in the British housing stock: energy demand and the homes energy efficiency database. Energy Policy, 60, 462–480.
Tso, G. K. F., & Yau, K. K. W. (2003). A study of domestic energy usage patterns in Hong Kong. Energy, 28(15), 1671–1682.
Tso, G. K. F., & Yau, K. K. W. (2007). Predicting electricity energy consumption: a comparison of regression analysis, decision tree and neural networks. Energy, 32(9), 1761–1768.
Kavousian, A., Rajagopal, R., & Fischer, M. (2013). Determinants of residential electricity consumption: using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants’ behavior. Energy, 55, 184–194.
Rosenthal, D. H., Gruenspecht, H. K., & Moran, E. A. (1995). Effects of global warming on energy use for space heating and cooling in the United States. The Energy Journal, 16, 77–96.
Colombo, A. F., Etkin, D., & Karney, B. W. (1999). Climate variability and the frequency of extreme temperature events for nine sites across Canada: implications for power usage. Journal of Climate, 12(8), 2490–2502.
EIA (2005). Impacts of temperature variation on energy demand in buildings. Issues in Focus, AEO2005. Retrieved on 15 December 2015 from http://www.eia.gov/oiaf/aeo/otheranalysis/aeo_2005analysispapers/vedb.html.
Hekkenberg, M., Benders, R. M. J., Moll, H. C., et al. (2009). Indications for a changing electricity demand pattern: the temperature dependence of the electricity demand in the Netherlands. Energy Policy, 37(4), 1542–1551.
Radhi, H. (2009). Evaluating the potential impact of global warming on the UAE residential buildings—a contribution to reduce the CO2 emissions. Building and Environment, 44, 2451–2462.
Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012). An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93, 485.
IPCC. (2013). Climate change 2013: The physical science basis. In T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, & P. M. Midgley (Eds.), Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge: Cambridge University Press.
Shahid, S. (2011). Trends in extreme rainfall events in Bangladesh. Theoretical and Applied Climatology, 104(3–4), 489–499.
Shahid, S., Minhans, A., & Puan, O. C. (2014). Assessment of greenhouse gas emission reduction measures in transportation sector of Malaysia. Jurnal Teknologi, 70(4).
Ouyang, J., & Hokao, K. (2009). Energy saving potential by improving occupants’ behavior in urban residential sector in Hangzhou City, China. Energy and Buildings, 41, 711–720.
Wilbanks, T. J. (2009). Effects of climate change on energy production and use in the United States. Darby: DIANE Publishing.
Xu, P., Huang, Y. J., Miller, N., Schlegel, N., & Shen, P. (2012). Impacts of climate change on building heating and cooling energy patterns in California. Energy, 44(1), 792–804.
Wang, H., & Chen, Q. (2014). Impact of climate change heating and cooling energy use in buildings in the United States. Energy and Buildings, 82, 428–436.
Dirks, J. A., Gorrissen, W. J., Hathaway, J. H., Skorski, D. C., Scott, M. J., Pulsipher, T. C., Huang, M., Liu, Y., & Rice, J. S. (2015). Impacts of climate change on energy consumption and peak demand in buildings: a detailed regional approach. Energy, 79, 20–32.
Sailor, D. J., & Munoz, J. R. (1997). Sensitivity of electricity and natural gas consumption to climate in the USA—methodology and results for eight states. Energy, 22(10), 987–998.
Mima, S., & Criqui, P. (2015). The costs of climate change for the European energy system, an assessment with the POLES model. Environmental Modeling and Assessment, 20(4), 303–319.
Shahid, S. (2012). Vulnerability of the power sector of Bangladesh to climate change and extreme weather events. Regional Environmental Change, 12(3), 595–606.
Rahman, M. M., Islam, M. N., Ahmed, A. U., & Georgi, F. (2012a). Rainfall and temperature scenarios for Bangladesh for the middle of 21st century using RegCM. Journal of Earth System Science, 121(2), 287–295.
Shahid, S., Wang, X.-J., Harun, S. B., Shamsudin, S. B., Ismail, T., & Minhans, A. (2016). Climate variability and changes in the major cities of Bangladesh: observations, possible impacts and adaptation. Regional Environmental Change, 16, 459–471.
Bangladesh Ministry of Environment and Forests (MOEF). (2009). National Adoptation Programme of action. Dhaka: MOEF and United Nations Development Programme.
Netherlands Environmental Assessment Agency (2014). CO2 time series 1990–2014 per capita for world countries. Retrieved on 30 November 2015 from http://edgar.jrc.ec.europa.eu/overview.php?v=CO2ts_pc1990-2014
Shahid, S. (2010). Recent trends in the climate of Bangladesh. Climate Research, 42(3), 185.
Bangladesh Bureau of Statistics (2012). Population and housing census 2011: Socio-economic and demographic report, National Report, Ministry of Planning, 4, 363.
Eusuf, A. Z. (1996). Urban centres in Bangladesh: their growth and change in rank order. In N. Islam & R. M. Ahsan (Eds.), Urban Bangladesh (pp. 7–20). Dhaka: Urban Studies Program.
Islam, N. (1994). Urban research in Bangladesh and Sri Lanka: towards an agenda for the 1990s. In R. Stren (Ed.), Urban research in developing world (pp. 101–169). Toronto: Centre for Urban and Community Studies, University of Toronto.
Alamgir, M. (2016). Climate change impacts on drought characteristics and risk in Bangladesh. PhD Thesis submitted to Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru, Malaysia. Ref: PSZ 19:16 (Pind. 1/07).
Kendall, M. G. (1975). Rank correlation methods. London: Griffin.
Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s tau. J. Amer. Stat. Assoc., 63, 1379–1389.
Fuller, W. A. (1976). Introduction to statistical time series. New York: Wiley.
Box, G. E. P., & Jenkins, G. (1976). Time series analysis: Forecasting and control. San Francisco: Holden-Day.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Shourav, M.S.A., Shahid, S., Singh, B. et al. Potential Impact of Climate Change on Residential Energy Consumption in Dhaka City. Environ Model Assess 23, 131–140 (2018). https://doi.org/10.1007/s10666-017-9571-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10666-017-9571-5