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In recent years, China has proposed the goal of peaking carbon dioxide emissions by 2030 and achieving carbon neutrality by 2060, which will significantly alter its existing coal-based energy mix. Since coal is China's primary source of energy and the largest contributor to carbon emissions, coal reduction is an important measure toward carbon neutrality. In order to guarantee the stable development of economy and society in the process of coal reduction, the path and cost of coal reduction need to be studied in depth. Based on coal use in China, this paper examines and measures the stages and costs of coal reduction. It also gives a definition for coal reduction costs for the first time, including economic cost, environment and ecology cost, and health cost, as well as proposes a framework for analyzing the "full cost, full process, and full scenario". We measure the cost in combination with the KAYA formula, and take into account the time value of the cost. Based on the above measurement framework, we calculate the unit coal reduction cost and estimate the coal reduction cost between CNY 454.38 and 827.1 billion. [ABSTRACT FROM AUTHOR]

As the top emitter of carbon dioxide worldwide, China faces a considerable challenge in reducing carbon emissions to combat global warming. Carbon emissions from coal consumption is the primary source of carbon dioxide emissions in China. The decomposition of the driving factors and the quantification of regions and industries needs further research. Thus, this paper decomposed five driving factors affecting carbon emissions from coal consumption in China, namely, carbon emission intensity, energy structure, energy intensity, economic output, and population scale, by constructing a Kaya-Logarithmic Mean Divisia Index (Kaya-LMDI) decomposition model with data on coal consumption in China from 1997 to 2019. It was revealed that the economic output and energy intensity effects are major drivers and inhibitors of carbon emissions from coal consumption in China, respectively. The contribution and impact of these driving factors on carbon emissions from coal consumption were analyzed for different regions and industrial sectors. The results showed that carbon emissions from coal consumption increased by 3211.92 million tons from 1997 to 2019. From a regional perspective, Hebei Province has the most significant impact on carbon emissions from coal consumption due to the effect of economic output. Additionally, the industrial sector had the most pronounced influence on carbon emissions from coal consumption due to the economic output effect. Finally, a series of measures to reduce carbon emissions including controlling the total coal consumption, improving the utilization rate of clean energy, and optimizing the energy structure is proposed based on China's actual development. [ABSTRACT FROM AUTHOR]

China's green credit has mostly been invested in new energy areas with positive environmental externalities in recent years, while coal power enterprises have been neglected. This paper constructs a tripartite evolutionary game model among government, coal power enterprises, and banks to clarify the key factors and mechanisms for coal power enterprises undergoing green transformation. The research results show that: Firstly, to realize the spontaneous green transformation of coal power enterprises, spontaneous profitability must be achieved before the removal of policy incentives, which is reflected in the continuous increase in electricity price, carbon emission trading price, and decrease in green transformation cost. Secondly, the green credit adjustment factor cannot determine whether a company chooses to undertake green transition, but it provides a valuable window of green transition for companies. When the relative benefits of green transformation projects are greater than the relative costs, coal power enterprises will undergo green transformation spontaneously. Thirdly, lower green credit interest rates are not better. An optimal green credit interest rate exists, that allows coal power enterprises to obtain the longest transition window in which to achieve spontaneous profitability for green transition projects. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate CO2 emissions in the production of coal sources at the prefecture level and to analyze their spatial distribution and regional differences based on the spatial autocorrelation and standard deviational ellipse analysis. The results indicate that Chinese coal production from 2018 will most likely generate 485.23 million tons of CO2 emissions, and there still exists an obvious gap between the five coal development districts in terms of their CO2 emissions. A significant clustering pattern and positive spatial autocorrelation are revealed in the coal production-based carbon emissions in China. In addition, the spatial pattern of coal production-based CO2 emissions has an obvious central tendency and directional trend, and the ellipse direction is quite consistent with the Aihui–Tengchong Line. Our findings suggest that energy policy-makers should be concerned about the carbon emission effect when implementing regional coal development plans and actively guide the formation of a low-carbon spatial strategic pattern of coal production with a directional distribution of CO2 emissions perpendicular to the Aihui–Tengchong Line. [ABSTRACT FROM AUTHOR]

Coal's green mining and scientific utilization is the key to achieve the national vision of carbon peak by 2030 and carbon neutrality by 2060. Clarifying the CO2 flow of coal production is the core part of decarbonization. This study uses an environmental extended multi-regional input–output (EEMRIO) model to analyze the impact of embodied emissions on the indirect CO2 emission intensity of coal production between China's coal mining sector and 141 countries/regions. It is found that the CO2 emission intensity of China's coal production was 34.14 gCO2/MJ in 2014, while the direct and indirect emission intensities were 16.22 gCO2/MJ and 17.92 gCO2/MJ, respectively. From 2007 to 2014, the direct emission intensity of China's coal production increased by 23%, while the indirect emission intensity decreased by 30%. The key material and service inputs affecting indirect carbon emissions of coal production in China are electricity service, metal manufacturing, chemical products, coal mining, and transport, which accounted for 85.5% of the total indirect emission intensity of coal production in 2014. Globally, a large portion of CO2 from Chinese coal production is emitted to meet foreign direct and indirect demands for material and service inputs. Policy implications related to this outcome are further discussed in the study. [ABSTRACT FROM AUTHOR]

The current study employs a Granger causality test within a Quantile approach investigating CO2 emission determinants in China. Results show urbanization, financial development and openness to trade are leading determinants of CO2 emissions in China. These results highlight climate change issues while taking advantage of a new methodology to fill a gap in the current literature. Our findings show key implications for PRC government policy related to pollutant reduction policy. [ABSTRACT FROM AUTHOR]