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Variation of household electricity consumption and potential impact of outdoor PM2.5 concentration: A comparison between Singapore and Shanghai

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  • You, Siming
  • Neoh, Koon Gee
  • Tong, Yen Wah
  • Dai, Yanjun
  • Wang, Chi-Hwa

Abstract

The auto-regressive distributed lag (ARDL) bound testing approach was used to study the relationships between the monthly household electricity consumption and outdoor PM2.5 concentration with the consideration of ambient temperature and the number of rainy days for Singapore and Shanghai. It is shown that there are significant long-run relationships between the household electricity consumption and the regressors for both Singapore and Shanghai. For Singapore, a 20% increase in the PM2.5 concentration of a single month is in the long-run significantly related to a 0.8% increase in the household electricity consumption. This corresponds to an electricity overconsumption of 5.0GWh, a total of 0.7–1.0million USD in electricity cost, and 2.1kilotons of CO2 emission associated with electricity generation. For Shanghai, a 20% decrease in the PM2.5 concentration of a single month is in the long-run significantly related to a 2.2% decrease in the household electricity consumption. This corresponds to a 35.0GWh decrease in the overall household electricity consumption, 1.6–5.1million USD decrease in electricity cost, and 17.5kilotons of CO2 emission. The results suggest that the cost of electricity consumption should be included in the economic cost analysis of PM2.5 pollution in the future. A 1°C increase in the monthly temperature is in the long-run significantly related to a 13.6% increase in the monthly electricity consumption for Singapore, while a 30 degree days increase in heating & cooling days (HCDD) is in the long-run significantly related to a 24.9% increase in the monthly electricity consumption for Shanghai. A 5-day increase in the number of rainy days per month is in the long-run significantly related to a 3.0% and 5.8% increase in the monthly electricity consumption for Singapore and Shanghai, respectively.

Suggested Citation

  • You, Siming & Neoh, Koon Gee & Tong, Yen Wah & Dai, Yanjun & Wang, Chi-Hwa, 2017. "Variation of household electricity consumption and potential impact of outdoor PM2.5 concentration: A comparison between Singapore and Shanghai," Applied Energy, Elsevier, vol. 188(C), pages 475-484.
    • Handle: RePEc:eee:appene:v:188:y:2017:i:c:p:475-484
    DOI: 10.1016/j.apenergy.2016.12.019
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    as
    1. Chen, Sheng-Tung & Kuo, Hsiao-I & Chen, Chi-Chung, 2007. "The relationship between GDP and electricity consumption in 10 Asian countries," Energy Policy, Elsevier, vol. 35(4), pages 2611-2621, April.
    2. Sun, Sizhong & Anwar, Sajid, 2015. "Electricity consumption, industrial production, and entrepreneurship in Singapore," Energy Policy, Elsevier, vol. 77(C), pages 70-78.
    3. Loi, Tian Sheng Allan & Loo, Soh Leng, 2016. "The impact of Singapore’s residential electricity conservation efforts and the way forward. Insights from the bounds testing approach," Energy Policy, Elsevier, vol. 98(C), pages 735-743.
    4. Finenko, Anton & Cheah, Lynette, 2016. "Temporal CO2 emissions associated with electricity generation: Case study of Singapore," Energy Policy, Elsevier, vol. 93(C), pages 70-79.
    5. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    6. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    7. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
    8. Ziramba, Emmanuel, 2008. "The demand for residential electricity in South Africa," Energy Policy, Elsevier, vol. 36(9), pages 3460-3466, September.
    9. Yumeng Wang & Shuoli Zhao & Zhihai Yang & Donald J. Liu, 2015. "Food versus crude oil: what do prices tell us? Evidence from China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 7(3), pages 435-447, September.
    10. Pilli-Sihvola, Karoliina & Aatola, Piia & Ollikainen, Markku & Tuomenvirta, Heikki, 2010. "Climate change and electricity consumption--Witnessing increasing or decreasing use and costs?," Energy Policy, Elsevier, vol. 38(5), pages 2409-2419, May.
    11. Moral-Carcedo, Julian & Vicens-Otero, Jose, 2005. "Modelling the non-linear response of Spanish electricity demand to temperature variations," Energy Economics, Elsevier, vol. 27(3), pages 477-494, May.
    12. Ang, B.W. & Goh, T.N. & Liu, X.Q., 1992. "Residential electricity demand in Singapore," Energy, Elsevier, vol. 17(1), pages 37-46.
    13. Wu, Yang & Yu, Zichao & Ngan, H.W. & Tan, Zhongfu, 2014. "Sustaining China׳s electricity market development," Energy Policy, Elsevier, vol. 73(C), pages 30-37.
    14. Paresh Kumar Narayan, 2005. "The saving and investment nexus for China: evidence from cointegration tests," Applied Economics, Taylor & Francis Journals, vol. 37(17), pages 1979-1990.
    15. Li, Ying & Lukszo, Zofia & Weijnen, Margot, 2016. "The impact of inter-regional transmission grid expansion on China’s power sector decarbonization," Applied Energy, Elsevier, vol. 183(C), pages 853-873.
    16. ., 2016. "Fantasizing authoritarian capitalism: a brief history," Chapters, in: Authoritarian Capitalism in the Age of Globalization, chapter 2, pages 14-28, Edward Elgar Publishing.
    17. Bartusch, Cajsa & Odlare, Monica & Wallin, Fredrik & Wester, Lars, 2012. "Exploring variance in residential electricity consumption: Household features and building properties," Applied Energy, Elsevier, vol. 92(C), pages 637-643.
    18. Ozturk, Ilhan & Acaravci, Ali, 2011. "Electricity consumption and real GDP causality nexus: Evidence from ARDL bounds testing approach for 11 MENA countries," Applied Energy, Elsevier, vol. 88(8), pages 2885-2892, August.
    19. Tonn, Bruce & Hawkins, Beth & Schweitzer, Martin & Eisenberg, Joel, 2013. "Process evaluation of the home performance with ENERGY STAR Program," Energy Policy, Elsevier, vol. 56(C), pages 371-381.
    20. Yee Yan, Yuk, 1998. "Climate and residential electricity consumption in Hong Kong," Energy, Elsevier, vol. 23(1), pages 17-20.
    21. Narayan, Paresh Kumar & Smyth, Russell, 2005. "The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration," Energy Policy, Elsevier, vol. 33(4), pages 467-474, March.
    22. Liang, Zhuoran & Tian, Zhan & Sun, Laixiang & Feng, Kuishuang & Zhong, Honglin & Gu, Tingting & Liu, Xiaochen, 2016. "Heat wave, electricity rationing, and trade-offs between environmental gains and economic losses: The example of Shanghai," Applied Energy, Elsevier, vol. 184(C), pages 951-959.
    23. Anders Rahbek & Rocco Mosconi, 1999. "Cointegration rank inference with stationary regressors in VAR models," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 76-91.
    24. OrtizBeviá, M.J. & RuizdeElvira, A. & Alvarez-García, F.J., 2014. "The influence of meteorological variability on the mid-term evolution of the electricity load," Energy, Elsevier, vol. 76(C), pages 850-856.
    25. Fung, W.Y. & Lam, K.S. & Hung, W.T. & Pang, S.W. & Lee, Y.L., 2006. "Impact of urban temperature on energy consumption of Hong Kong," Energy, Elsevier, vol. 31(14), pages 2623-2637.
    26. Inglesi, Roula, 2010. "Aggregate electricity demand in South Africa: Conditional forecasts to 2030," Applied Energy, Elsevier, vol. 87(1), pages 197-204, January.
    27. Jin-Feng Wang & Mao-Gui Hu & Cheng-Dong Xu & George Christakos & Yu Zhao, 2013. "Estimation of Citywide Air Pollution in Beijing," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-6, January.
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