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Forecasting energy demand, structure, and CO2 emission: a case study of Beijing, China

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Abstract

The primary energy use in cities accounts for a large share of global energy consumption, leading to significant carbon emissions. Exploring the city’s current characteristics and future trends in energy demand has policy implications for carbon reduction policy-making. We establish a city-level energy forecast demand model to predict Beijing’s future energy demand. Results show that economic growth has strong positive correlations with energy consumption. Beijing’s energy demand is predicted to stay at a pretty high level by the end of 2020, between 98.72 and 121.60 Mtce, or between 4.12 and 5.08 tce per capita under three distinctive GDP growth (High, Medium and Low) scenarios. Comparing with the start of historical time series 1980, this is a huge increase of 563.50% (High), 489.90% (Medium) and 423.91% (Low) in terms of total demand, while is increases of 147.98%, 120.47% and 95.81% per capita. Based on an energy structure model estimated by a Markov-chain method, we find that our predictions would follow the current trend of energy structure, making Beijing’s coal demand decline towards zero share of energy consumption, natural gas rises approaching 50%, oil stays almost constant around 32.3%, electricity decreases below 20%, and other fuels keep in a small amount in 2035. We would expect to see almost 8000 kg per capita carbon emissions in Beijing if the GDP growth rate is high, and still over 6000 kg per capita if GDP growth is low. In terms of total carbon emissions, we show that though coal consumption will keep decreasing towards zero in the next years, total carbon emission still rises by 36.5–72.8% comparing with 2010. These findings can provide references for policymakers to implement some incentive policies to promote renewable and clean energy.

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Acknowledgements

The work was supported by the Beijing Social Science Foundation (21GLC062).

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Authors and Affiliations

  1. Institute of Circular Economy, Beijing University of Technology, Beijing, 100124, China

    Zhixiong Weng & Tingting Liu

  2. Harris School of Public Policy, The University of Chicago, Chicago, IL, 60637, USA

    Yuqi Song

  3. BGRIMM Technology Group, Beijing, 100160, China

    Hao Ma

  4. School of Environment and Natural Resources, Renmin University of China, Beijing, 100872, China

    Zhong Ma

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Weng, Z., Song, Y., Ma, H. et al. Forecasting energy demand, structure, and CO2 emission: a case study of Beijing, China. Environ Dev Sustain 25, 10369–10391 (2023). https://doi.org/10.1007/s10668-022-02494-1

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