Gigatonnes Missing Biomass Energy Consumption in Rural China

To provide a more comprehensive reconstruction of China’s energy consumption, this paper built a machine-learning-based geospatial model that shows great accuracy in recovering historical biomass consumption data using the household survey dataset for China, combined with province-level characteristics and spatiotemporal information. Our study suggested that 6.9 ± 2.6 giga-tons of coal equivalent of biomass were uncounted in China’s statistics, representing 15.9 ± 6.0 percent for China and 2.5 ± 0.9 percent for global final energy consumption. This new estimate significantly reshaped our understanding of China’s energy composition, sectoral mix, indoor air pollutants, and the factors driving energy consumption. These findings provide a replicable template for developing countries hoping to uncover the biomass demand to better design public policy to achieve Sustainable Development Goals. JEL Classification: Q41, Q53, R12, C81, O13

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Publication Details

Journal
The Energy Journal
Published
2024-08-09
DOI
https://doi.org/10.1177/01956574241266970
Citations
6
Primary Topic
Energy and Environment Impacts
Type
article
Field-Weighted Citation Impact
0.80

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article

Gigatonnes Missing Biomass Energy Consumption in Rural China

Xi Lu, Shimei Wu, Andreas Löschel, Xiao Han et al.
6 citations
The Energy Journal
Energy and Environment Impacts
0.80
article

Gigatonnes Missing Biomass Energy Consumption in Rural China

Xi Lu, Shimei Wu, Andreas Löschel, Xiao Han, Limin Du, Chu Wei, Xinye Zheng, Chuan-Zhong Li
article en
6 citations

Abstract

To provide a more comprehensive reconstruction of China’s energy consumption, this paper built a machine-learning-based geospatial model that shows great accuracy in recovering historical biomass consumption data using the household survey dataset for China, combined with province-level characteristics and spatiotemporal information. Our study suggested that 6.9 ± 2.6 giga-tons of coal equivalent of biomass were uncounted in China’s statistics, representing 15.9 ± 6.0 percent for China and 2.5 ± 0.9 percent for global final energy consumption. This new estimate significantly reshaped our understanding of China’s energy composition, sectoral mix, indoor air pollutants, and the factors driving energy consumption. These findings provide a replicable template for developing countries hoping to uncover the biomass demand to better design public policy to achieve Sustainable Development Goals. JEL Classification: Q41, Q53, R12, C81, O13

The Energy JournalVol. 45(5)
Uppsala University (SE), Hunan University (CN), Renmin University of China (CN), Ruhr University Bochum (DE), Zhejiang University of Finance and Economics (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hunan Province
Affordable and clean energy
Openalex Percentile: Top 35%
Energy and Environment Impacts
0.80
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