Research On Influencing Factors And Scenario Prediction Of China’s Carbon Emission Intensity Under The Background Of Peaking Target

With the continuous growth of energy consumption demand,China’s carbon emissions have grown significantly.It is imperative to fully implement carbon emission reduction actions as the situation of achieving emissions peak target has become increasingly severe.Reducing carbon emission intensity(CEI)is an important task of China’s carbon emission reduction work.Studying the influencing factors and evaluating the future development trend of CEI have important practical significance and theoretical value for the realization of China’s carbon emission reduction targets.Therefore,this dissertation focused on China’s CEI,and applied Kaya identity to construct an analysis framework for drivers of China’s CEI based on China’s energy consumption and related carbon emissions data from 2000 to 2019.The effects of carbon emission coefficient,fossil energy structure,electricity consumption,heat consumption,energy intensity and industrial structure were analyzed from the perspectives of sectors,provinces,and regions.The development trend of China’s CEI was predicted based on two main factors including energy intensity and fossil energy structure.The contents and main conclusions are as follows:(1)Based on the multiplicative Logarithmic Mean Divisia Index(LMDI)decomposition and attribution model,this dissertation constructed a framework and expanded a new dimension for analyzing the influencing factors of China’s carbon emission intensity from the perspective of industry sectors.First,this dissertation evaluated the drivers of China’s CEI and found that energy intensity is the dominant factor promoting the reduction of China’s CEI.Then,based on the attribution model,according to the national economic sector classification(GB/T-4754),the impact of various factors on CEI was attributed to 41 sectors.The results showed that the energy intensity and fossil energy structure of 6 energy-intensive sectors have played significant roles in the decline of China’s CEI.Therefore,focusing on energy-intensive sectors,developing energy-saving technologies,and increasing the proportion of clean energy consumption such as natural gas are effective ways to reduce China’s CEI.(2)Based on the temporal-spatial index decomposition analysis(ST-IDA)model,this dissertation constructed a research framework and and explored a new perspective for the analysis of the influencing factors of China’s provincial CEI.First,the influencing factors of CEI in 30 provinces were analyzed from temporal perspective.Furthermore,through the Multi-regional(M-R)comparison framework,the influencing factors of China’s provincial CEI were explored from spatial perspective.The results showed that energy intensity and fossil energy structure are the main factors for the provincial differences in CEI.Energy intensity and the proportion of coal consumption in Shanxi,Inner Mongolia,Ningxia and Xinjiang is significantly higher than other provinces.Therefore,it is necessary to improve the energy efficiency,reduce energy intensity,restrain the growth of coal consumption,and promote the fossil energy structure optimization in these provinces.(3)This dissertation quantified the inter-regional and intra-regional differences in China’s CEI through Theil index,and applied Theil decomposition model to discuss the drivers of inter-regional and intra-regional differences in China’s CEI,revealing the relationship between regional economic development patterns and carbon emissions.The results showed that during 2000-2019,the regional differences mainly derived from the Northwest and middle reaches of the Yellow River of China.Inter-regional differences accounted for more than 55% of the overall differences.Energy intensity is the main factor for regional differences in China’s CEI,and its impact on regional differences fluctuated between 0.035 and 0.053 from 2000 to 2019.Therefore,the government should strengthen inter-regional technical cooperation and promote the development of energy-saving technologies in the northwest and the middle reaches of the Yellow River to promote the continuous decline of their energy intensity.(4)Given that energy intensity and fossil energy structure are the main factors for the decline of China’s CEI,this dissertation constructed six scenarios considering these two factors.Then,the Kaya identity was applied to predict the future trend of China’s CEI and the situation of emissions peak target under these six scenarios.The results showed that China’s CEI will drop to 0.40-0.77 tons per 10,000 tons in 2040.China’s carbon emissions will peak at 10.965-12.569 billion tons in 2025-2030.All provinces can reach their carbon emission peaks by 2030 under at least one scenario,but Ningxia and Xinjiang have not achieved their CEI reduction targets in all scenarios;With the exception of the Northwest,the other seven regions can meet the 2030 carbon peaking target under all scenarios.Therefore,the government should develop clean energy and promote the clean development of the fossil energy structure.