Abstract:Based on the method of the Intergovernmental Panel on Climate Change, it calculated the carbon emissions of energy consumption in Heilongjiang Province from 2005 to 2020. By using the Logarithmic Mean Divisia Index (LMDI) decomposition model and the STIRPAT model, it analyzed the relationship between energy carbon emissions and driving factors such as the economy and population in depth. Scenario simulations were conducted to explore reasonable paths for the future development of Heilongjiang Province. According to the results of the LMDI factor decomposition, the economic level factor had the greatest cumulative effect on energy carbon emissions. Through the STIRPAT model and scenario simulation analysis, the comprehensive scenario was identified as the optimal scenario among the four scenarios. Finally, based on the "dual carbon" goal and research results, it provided the suggestions for relevant regulatory strategies.
[1] 关雪凌,周敏.城镇化与能源消费的耦合发展研究[J]. 中国矿业大学学报, 2019,48(6):1391-1398. Guan X L, Zhou M. Coupling development of urbanization and energy consumption [J]. Journal of China University of Mining & Technology, 2019,48(6):1391-1398. [2] Zhang Q X, Liao H, Hao Y. Does one path fit all? An empirical study on the relationship between energy consumption and economic development for individual Chinese provinces [J]. Energy, 2018, 150:527-43. [3] 潘栋,李楠,李锋等.基于能源碳排放预测的中国东部地区达峰策略制定[J]. 环境科学学报, 2021,41(3):1142-1152. Pan D, Li N, Li F, et al. Mitigation strategy of Eastern China based on energy-source carbon emission estimation [J]. Acta Scientiae Circumstantiae, 2021,41(3):1142-1152. [4] Ang B W, Choi K H. Decomposition of aggregate energy and gas emission intensities for industry: a refined Divisia index method [J]. Energy, 1997,18(3):59-73. [5] Ang B W, Liu F L. A new energy decomposition method: perfect in decomposition and consistent in aggregation [J]. Energy, 2001,26(6): 537-548. [6] Shi L Y, Sun J, Lin J Y, Zhao Y. Factor decomposition of carbon emissions in Chinese megacities [J]. Journal of Environmental Sciences, 2019,75:209-215. [7] 潘崇超,王博文,侯孝旺,等.基于LMDI-STIRPAT模型的中国钢铁行业碳达峰路径研究[J]. 工程科学学报, 2023,45(6):1034-1044. Pan C C, Wang B W, Hou X W, et al. Carbon peak path of the Chinese iron and steel industry based on the LMDI−STIRPAT model [J]. Chinese Journal of Engineering, 2023,45(6):1034-1044. [8] 陈亮,张楠,王一帆,等.京津冀地区碳排放强度变化的驱动因素及其归因分析—基于细分行业与五年规划的视角[J/OL]. 中国环境科学: 1-17[2023-06-13]. Chen L, Zhang N, Wang Y F, et al. Driving factors and attribution analysis of carbon emission intensity change of Beijing-Tianjin-Hebei region: based on the perspective of subdivided industries and Five-Year Plan [J/OL]. China Environmental Science: 1-17[2023-06-13]. [9] 冉光圭,杨宣.西部地区能源消费碳排放时空格局演变及影响因素分析[J]. 贵州民族研究, 2022,43(6):56-61. Ran G G, Yang X. Temporal and spatial pattern evolution and influencing factors of carbon emission from energy consumption in western China [J]. Guizhou Ethnic Studies, 2022, 43(6):56-61. [10] 李云燕,张硕.中国城市碳排放强度时空演变与影响因素的时空异质性[J]. 中国环境科学, 2023,43(6):3244-3254. Li Y Y, Zhang S. Spatio-temporal evolution of urban carbon emission intensity and spatiotemporal heterogeneity of influencing factors in China [J]. China Environmental Science, 2023,43(6):3244-3254. [11] 吴一帆,许杨,唐洋博,等.长江经济带二氧化碳净排放时空演变特征及脱钩效应[J]. 环境科学, 2023,44(3):1258-1266. Wu Y F, Xu Y, Tang Y B, et al. Temporal and spatial characteristics of net CO2 emissions and decoupling analysis in Yangtze River Economic Belt [J]. Environmental Science, 2023,44(3):1258-1266. [12] York R, Rosa E A, Dietz T. STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts [J]. Ecological Economics, 2003,46(3):351-65. [13] 刘让群,牛靖,姚鹏.东北地区产业发展的回顾与展望[J]. 区域经济评论, 2021,51(3):143-150. Liu R Q, Niu J, Yao P. Retrospect and prospect of industrial development in Northern China [J]. Regional Economic Review, 2021, 51(3):143-150. [14] IPCC, 2006 IPCC Guidelines for National Greenhouse Gas Inventories [R]. [15] IPCC, 2019 Refinement to the 2006IPCC Guidelines for National Greenhouse Gas Inventories [R]. [16] 蒯鹏,束克东,成润禾.我国工业部门环境污染排放变化的驱动因素——基于“十二五”工业排放数据的实证研究[J]. 中国环境科学, 2018,38(6):2392-2400. Kuai P, Shu K D, Cheng R H. Driving force for the variation of pollution discharge in the Chinese industrial department: An empirical study based on pollution data during the 12th five-year plan period [J]. China Environmental Science, 2018,38(6):2392-2400. [17] Yang J, Cai W, Ma M D, et al. Driving forces of China’s CO2 emissions from energy consumption based on Kaya-LMDI methods [J]. Sci Total Environ, 2020,711:134569. [18] Wang C, Chen J N, Zou J. Decomposition of energy-related CO2 emission in China: 1957~2000[J]. Energy, 2005,30(1):73-83. [19] P.R. Ehrlich, J.P. Holdren. Impact of population growth [J]. Science, 1971,171(3977):1212-1217. [20] Poumanyvong P, Kaneko S. Does urbanization lead to less energy use and lower CO2 emissions? A cross-country analysis [J]. Ecological Economics, 2010,70(2):434-44. [21] T. Dietz, E.A. Rosa. Effects of population and affluence on CO2 emissions [J]. Proceedings of the National Academy of Sciences. 1997,94(1):175-179. [22] 吉兴全,赵国航,于一潇,等.基于4E平衡的碳排放因素分解与峰值预测方法[J]. 高电压技术, 2022,48(7):2483-2494. Ji X Q, Zhao G H, Yu Y X, et al. Carbon emission peak prediction and factor decompose method based on 4E equilibrium [J]. High Voltage Engineering, 2022,48(7):2483-2494. [23] 王立猛,何康林.基于STIRPAT模型的环境压力空间差异分析——以能源消费为例[J]. 环境科学学报, 2008,(5):1032-1037. Wang L M, He K L. Analysis of spatial variations in environmental impact based on the STIRPAT model——A case study of energy consumption [J]. Acta Scientiae Circumstantiae, 2008,(5):1032-1037. [24] 朱勤,彭希哲,陆志明,等.人口与消费对碳排放影响的分析模型与实证[J]. 中国人口·资源与环境, 2010,20(2):98-102. Zhu Q, Peng X Z, Lu Z M, et al. Analysis model and empirical study of impacts from population and consumption on carbon emissions [J]. China Population, Resources and Environment, 2010,20(2):98-102. [25] 中国国家统计局.中国能源统计年鉴[M].中国统计出版社, 2005-2020. China National Bureau of Statistics. China energy statistical yearbook [M]. China Statistics Press, 2005-2020. [26] 刘竹,耿涌,薛冰,等.城市能源消费碳排放核算方法[J]. 资源科学, 2011,33(7):1325-1330. Liu Z, Geng Y, Xue B, et al. A calculation method of CO2 emission from urban energy consumption [J]. Resources Science, 2011,33(7): 1325-1330. [27] 中国国家统计局.中国统计年鉴[M]. 中国统计出版社, 2005-2020. China National Bureau of Statistics. China statistical yearbook [M]. China Statistics Press, 2005-2020. [28] 黑龙江省统计局.黑龙江统计年鉴[M]. 中国统计出版社, 2005-2020. Heilongjiang Bureau of Statistics [M]. China Statistics Press, 2005-2020. [29] 王巍,路春艳,王英哲.黑龙江省资源型城市人口流失问题与对策[J]. 中国人口·资源与环境, 2018,28(S2):63-66. Wang W, Lu C Y, Wang Y Z. Problems countermeasures of population loss in resource-based cities in Heilongjiang [J]. China Population, Resources and Environment, 2018,28(S2):63-66. [30] 王胜今,张磊,杨静.黑龙江省流出人口就业特征及其影响因素分析[J]. 人口学刊, 2019,41(2):67-76. Wang S L, Zhang L, Yang J. Analysis on the employment characteristics and influencing factors of out-migration in Heilongjiang Province [J]. Population Journal, 2019,41(2):67-76. [31] 杨楠.岭回归分析在解决多重共线性问题中的独特作用[J]. 统计与决策, 2004,(3):14-15. Yang N. The unique role of ridge regression analysis in solving multicollinearity problems [J]. Statistics & Decision, 2004,(3):14-15. [32] 国家发展和改革委员会.“十四五”规划《纲要》主要指标之3|常住人口城镇化率[EB/OL]. https://www.ndrc.gov.cn/fggz/fzzlgh/ gjfzgh/202112/t20211225_1309650.html. The National Development and Reform Commission. The third main indicators of the outline of the 14th Five Year Plan| Urbanization rate of permanent population [EB/OL]. https://www.ndrc.gov.cn/fggz/ fzzlgh/gjfzgh/202112/t20211225_1309650.html. [33] 国家发展和改革委员会.国家人口发展规划(2016~2030年) [EB/OL]. https://www.ndrc.gov.cn/fggz/fzzlgh/gjjzxgh/201705/t20170502_1196730. html. The National Development and Reform Commission. National population development plan (2016-2030) [EB/OL]. https://www. ndrc.gov.cn/fggz/fzzlgh/gjjzxgh/201705/t20170502_1196730.html. [34] 黑龙江省人民政府.黑龙江省人民政府关于印发黑龙江省国民经济和社会发展第十四个五年规划和二〇三五年远景目标纲要的通知[EB/OL]. https://www.hlj.gov.cn/hlj/c108376/202103/c00_31185821.shtml. The People's Government of Heilongjiang Province. Notice of the people's government of Heilongjiang Province on issuing the 14th Five Year Plan for national economic and social development and the outline of long range objectives for 2035 in Heilongjiang Province [EB/OL]. https://www.hlj.gov.cn/hlj/c108376/202103/c00_31185821. shtml. [35] 国家发展和改革委员会.“十四五”现代能源体系规划[EB/OL]. http://www.nea.gov.cn/1310524241_16479412513081n.pdf. The National Development and Reform Commission. The 14th Five Year Plan for modern energy system planning [EB/OL]. http://www. nea.gov.cn/1310524241_16479412513081n.pdf.