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In an effort to address climate change, in 2013 China launched the world’s largest government-driven carbon emission reduction programme, the National Low Carbon Industrial Parks Pilot Programme (LCIPPP). This paper analyses this newly developed pilot program. To deepen our understanding of the causes and the impact of industrial park CO 2 emissions, we use the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model and data from 20 pilot industrial parks involved in the LCIPPP for the period 2012–2016. This study quantitatively evaluates the effect of CO 2 emissions on output, energy structure, energy intensity, industrial structure, R&D intensity, and population change in different regions and nationally through an elasticity coefficient method. The results confirm that an increase in output and energy intensity is a dominant contributor to the growth of CO 2 emissions whereas an increase of the share of tertiary industry and R&D intensity has significant effects on reducing CO 2 emissions. The elasticity of energy intensity and renewable energy consumption on CO 2 emissions in the eastern region of China is the highest, indicating that using renewable energy to reduce CO 2 emissions for the industrial parks is more effective in the eastern region as compared to the central and western regions of the country. The elasticity of population is significantly negative in both the central and western areas while it is positive in eastern part of China, thereby illustrating that promoting labour intensive industries will be an effective way to reduce CO 2 emissions for the industrial parks in China’s central and western regions. Our study reveals that differentiated low carbon development pathways should be adopted. Concrete policy implications for reducing CO 2 emissions are also provided. [ABSTRACT FROM AUTHOR]

Accurately understanding the real situation of China’s carbon emissions at the provincial level is not only crucial for realizing carbon mitigation in China, but also of great importance for tackling climate change on a global scale. This paper uses detailed energy consumption data subdivided within each fuel type and sector-specific emission factors, to calculate both direct and indirect energy-related CO 2 emissions for China’s provinces, and offers provincially-targeted policy proposals on emission reductions. The results uncover large divergences in calculation of provincial CO 2 emissions between production-based and consumption-based accounting approaches. Considering the large amount of interprovincial CO 2 emission transfers embodied in secondary energy deployment, the consumption-based accounting performs better in reflecting the actual features and responsibilities of carbon emissions in the provinces of China. From the consumption perspective, Shandong, Hebei, Jiangsu, Inner Mongolia, Guangdong, Henan, Liaoning and Shanxi contributed to the majority of China’s carbon emission growth during the period of 1996–2013, while Xinjiang, Sichuan, Anhui, Tianjin and Hunan were playing an increasingly important role. These two groups of provinces should be regarded as the key regions for national emissions abatement. Meanwhile, the energy industry was the top sectoral contributor to CO 2 emissions growth in most provinces, while service and household sectors made increasingly significant impacts on driving up provincial emissions. Together with ongoing efforts in the energy sector, the mitigation of CO 2 emissions in service and household sectors deserves much more attention, especially in the transportation and urban household sectors. Furthermore, the temporal trends of carbon emissions in various provinces, as well as their factor and sectoral driving forces, varied greatly with each other. Therefore, each of the provinces should formulate emission reduction policies according to their own situation, and target the key driving factors and sectors of carbon emissions at the current stage or in the near future. [ABSTRACT FROM AUTHOR]

In a joint U.S.–China statement on climate change , the Chinese government declared to peak CO 2 emissions around 2030. This demonstrates the government's determination to deal with carbon emission and climate change. Although the food industry is not a carbon emission-intensive industry, its large scale makes the emission reduction in the industry very important. Based on the input–output structural decomposition method, this paper calculates the CO 2 emissions of China's food industry from 1991 to 2012, and decomposes the change in CO 2 emissions of the industry during 1992–1997, 1997–2002, 2002–2007 and 2007–2010 into four main effects: emission factor, energy structure, energy intensity, and total output (including four sub-effects: intermediate use, domestic final demand, import substitution and export extension). The results show that changes in CO 2 emissions in the food industry mainly depends on total output effect and energy intensity effect. Energy intensity effect is the most important factor reducing CO 2 emissions, as it reduced cumulative 213 million tons (Mt) CO 2 emissions of the industry. Among total output effect, the effects of intermediate use and domestic final demand are the two biggest contributors to carbon emissions. Finally, we provide some policy advices for constraining and reducing CO 2 emissions of China's food industry. The advices include increasing R&D investment and the substitution of energy with other input factors to decrease energy intensity, increasing the added value of the food industry, optimizing the energy structure with more clean and low-carbon energy, and maintaining the prices of raw materials of the food industry (i.e. agricultural products) with taxes or subsidies. [ABSTRACT FROM AUTHOR]