Estimation of biomass energy consumption in rural China

Abstract

[Objective] Rural biomass energy is vital for implementing the rural revitalization and carbon neutrality strategies. However, the absence of a biomass energy statistical system hindered data-based academic research and targeted decision making. [Methods] To fill this research gap, this study integrated various micro household survey data and established a large-sample multi-source heterogeneous dataset—the Chinese Rural Household Energy Consumption dataset. We then applied the Bayesian spatiotemporal model to estimate the historical data of China’s rural biomass energy consumption from 1992 to 2016. [Results] The results show that: (1) During 1992-2016, biomass consumption in rural areas of China experienced a decline, from 195 million tons of standard coal in 1992 to 125 million tons in 2016, with an annual average decline of 1.7%. Since the “energy consumption revolution” initiative was put forward, the decline of rural biomass consumption has obviously accelerated, with an annual average decline of 3.8%, indicating that the “energy consumption revolution” initiative has been very effective and greatly promoted the transformation of rural energy consumption. (2) During 1992-2016, the number of rural households using biomass also continued to decline, with the number of households using firewood and straw reduced by nearly 50%. (3) Biomass consumption is mainly concentrated in the western and northeastern regions, where firewood consumption accounts for about 80% of national consumption, and straw consumption accounts for about 65%-70%. [Conclusion] The framework and methods of this study are helpful for solving the problem of missing data in academic research, and the research conclusions can provide a theoretical support for improving the level of high-quality energy use in remote rural areas of China.

Keywords

• |rural energy|biomass consumption|multi-source heterogeneous database|statistical inference|bayesian spatiotemporal model|china