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Analysis of energy-related CO2 emissions in China’s mining industry: Evidence and policy implications

Miao Wang and Chao Feng

Resources Policy, 2017, vol. 53, issue C, 77-87

Abstract: The primary objective of this paper is to explore the main factors driving CO2 emissions in China's mining industry and its subsectors. By utilizing the Log-Mean Divisia Index (LMDI) decomposition method, this paper decomposes changes in energy-related CO2 emissions into an industrial scale effect, an energy intensity effect, an energy structure effect, and a CO2 emissions coefficient effect in both the overall mining industry and its subsectors. The main results indicate that (1) CO2 emissions in China's mining industry rose by approximately 95.74 million tons during 2000–2014. The mining and washing of coal (MWC) and the extraction of petroleum and natural gas (EPNG) were the top two emitters, accounting for approximately 80% of total CO2 emissions in China's mining industry. (2) From the overall mining industry perspective, the industrial scale effect made the largest contribution to increasing CO2 emissions, while the energy intensity effect was the most important factor in reducing CO2 emissions. Additionally, the energy structure effect played a small role in inhibiting CO2 emissions. (3) From the subsector perspective, the industrial scale effect increased CO2 emissions in five subsectors, especially the MWC, while the energy intensity effect was the dominant factor inhibiting CO2 emissions in the five subsectors. The energy structure effect impacted CO2 emissions negatively in the EPNG, the MWC and the mining and processing of non-ferrous metal ores (MPNFMO); it impacted CO2 emissions positively in the mining and processing of ferrous metal ores (MPFMO) and the mining and processing of non-metal ores (MPNO). Policy recommendations related to energy intensity and energy structure adjustments were provided.

Keywords: LMDI method; Five subsectors; Energy structure effect; Energy intensity effect (search for similar items in EconPapers)
Date: 2017
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