Abstract
Intensifying climate change significantly impacts residential electricity consumption, especially in developing countries, such as China, that are experiencing rapid income growth. By combining meteorological and monthly household consumption survey data, this study explores the response function of residential electricity consumption to temperature in China from a micro perspective. Future residential electricity demands and related CO2 emissions are then forecast under different climate scenarios. Overall, the response function is U-shaped, and one additional day above 34 °C will increase monthly residential electricity consumption by 2.11%. Global warming will more likely increase the electricity burden on low-income groups. There will be notable seasonal changes in electricity demand in the future, and the largest increase will occur in August. The total demand for residential electricity caused by temperature change will show a fluctuating growth trend, from 0.8% and 1% in 2025 to 2% and 2.9% in 2060 under the RCP4.5 scenario and RCP8.5 scenario, respectively; meanwhile, this demand will be accompanied by a cumulative increase in carbon dioxide emissions.
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Data availability
The data that support the plots within this paper is available from the corresponding author upon reasonable request.
Code availability
The codes that support the methods of this study are available from the corresponding author upon reasonable request.
Notes
In contrast to developed countries, in China, the economic reform of the energy market has not been adequate, and electricity prices are still controlled by the government. In 2013, the step tariff system was gradually implemented in all provinces. In this study, the electricity price control variable relies on the electricity price in the different regions and periods corresponding to 300 kWh, which is the most frequent value encountered in electricity consumption data and can represent not only the electricity price faced by most households but also the step-change in electricity price.
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Funding
This work was supported by the National Natural Science Foundation of China (Grant numbers [72073014] and [71622012]) and the National Social Science Fund of China (Grant number [22AZD094]).
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Lan-Cui Liu and Juan-Juan Hou conceived the study and performed the analysis. Zheng-Yi Dong and Zhen Wang analyzed the data and implemented the model. Shi-Wei Yu contributed to the data collection and processing. Jiu-Tian Zhang worked on the review and editing. All authors approved and contributed to writing the paper.
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Appendix
Appendix
Response function results for the quantile temperature bins (note: the shaded area in the figure indicates the 95% confidence intervals)
Response function results for the different equidistant temperature bins (note: the figure on the left shows the results for the 5 °C equidistant temperature bins, and the figure on the right shows the results for the 6 °C equidistant temperature bins. The temperature range of the rightmost temperature bin is lower than 5 °C or 6 °C, so there is great uncertainty in the estimation results. However, it is certain that the overall shape of the response function remains consistent)
Forecast of the residential electricity demands for the different provinces under the RCP4.5 and RCP8.5 scenarios. a Liaoning. b Sichuan. c Guangdong. d Shanghai
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Hou, JJ., Liu, LC., Dong, ZY. et al. Response of China’s electricity consumption to climate change using monthly household data. Environ Sci Pollut Res 29, 90272–90289 (2022). https://doi.org/10.1007/s11356-022-21813-7
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DOI: https://doi.org/10.1007/s11356-022-21813-7