This paper analyses the dynamic relationship between industrial structure and carbon emissions in Sichuan Province using VAR models, using data on industrial structure and 8 carbon emissions of major energy consumption in Sichuan Province from 2001-2018. The results of the study show that in the short term, the advanced industrial structure will suppress the growth of carbon emissions, and the change in industrial structure, i.e., the increase in the share of secondary industry, will lead to an increase in carbon emissions; in the long term, the optimization of industrial structure has a significant impact on carbon emissions and specifically shows a suppressive effect. Therefore, in the short term, upgrading the industrial structure will not immediately reduce carbon emissions, but in the long term, adjusting the industrial structure is an important measure to reduce carbon emissions. In order to develop a low-carbon economy and accelerate the construction of a "clean energy demonstration province", Sichuan Province needs to optimise and upgrade its industrial structure, and specific measures are suggested, including: strengthening the role of regional radiation and promoting the balanced development of industries between regions; making full use of the province's human resources, increasing investment in research and development, and creating an important industrial cluster in China; strengthening the cooperation between Chengdu and Chongqing to promote the transformation and upgrading of the industrial structure.

Qianxin Ye. Study on the Impact of Industrial Structure on Carbon Emissions in Sichuan Province -- Empirical Analysis Based on VAR Model. The Frontiers of Society, Science and Technology (2022) Vol. 4, Issue 3: 49-56. https://doi.org/10.25236/FSST.2022.040310.

[1] Gao Jixi, Hou Peng, Zhai Jun, Chen Yan, Gao Haifeng, Jin Dodu, Yang Min. Taking the opportunity of achieving the "double carbon target" and enhancing the double cycle to vigorously promote the high-quality development of China's economy [J]. China Development, 2021, 21(S1): 47-52. DOI:10.15885/j. cnki.cn11-4683/z.2021.s1.006.

[2] Wu Yiqing, Yao Lianqian. Evaluation of China's provincial economic growth mode based on carbon productivity [J]. Journal of Hebei University of Economics and Business, 2021, 42(04): 67-73. DOI: 10.14178/j.cnki.issn1007-2101.20210701.005.

[3] Hara Lulu, Xi Qiangmin, Sun Tieshan, Li Guoping. The impact of industrial structure on regional carbon emissions--an empirical analysis based on multi-country data [J]. Geography Research, 2016, 35(01): 82-94.

[4] Wang Zhao, Wang Lianghu. Research on the relationship between R&D input, industrial structure upgrading and carbon emission [J]. Industrial Technology Economics, 2019, 38(05): 62-70.

[5] Shaojian Wang, Guangdong Li, Chuanglin Fang. urbanization, economic growth, energy consumption, and CO^2 emissions: Empirical evidence from countries with different income levels [J]. Renewable and Sustainable Energy Reviews. 2018

[6] Ma Huiqiang, Liu Jiale, Gong Zhigang. Measurement of carbon emissions from tourism traffic and its evolution mechanism in Shanxi Province [J]. Economic Geography, 2019, 39(04): 223-231. DOI: 10.15957/j.cnki.jjdl.2019.04.027.

[7] Xu Chenglong, Ren Jianlan, Gong Canjuan. Impact of industrial restructuring on carbon emissions in Shandong Province [J]. Journal of Natural Resources, 2014, 29(02): 201-210.

[8] Zhao Yuhuan, Li Hao, Liu Ya, Cao Ye, Zhang Zhonghua, Wang Song. Beijing-Tianjin-Hebei CO^2 Study on the spatial and temporal differences of emissions and influencing factors [J]. Resource Science, 2018, 40(01): 207-215.

[9] Gu A-Lun, He Chong-Kai, Lu C-Q. Analysis of the impact of industrial structure changes on carbon emissions in China based on LMDI method [J]. Resource Science, 2016, 38(10): 1861-1870.

[10] Gao Jing, Liu Guoguang. Measurement, decomposition and allocation of power and responsibility of implied carbon emissions in global trade-a comparison based on single-region and multi-region input-output methods [J]. Shanghai Economic Research, 2016(01): 34-43+70. doi: 10.19626/j.cnki.cn31-1163/f.2016.01.004.

[11] Wang Shaojian, Huang Yongyuan. Spatial spillover effects and driving factors of carbon emission intensity in Chinese cities [J]. Journal of Geography, 2019, 74(06): 1131-1148.

[12] Hara Lulu, Xi Qiangmin, Sun Tieshan, Li Guoping. The impact of industrial structure on regional carbon emissions--an empirical analysis based on multi-country data [J]. Geography Research, 2016, 35(01): 82-94.

[13] Gu A-Lun, He Chong-Kai, Lu C-Q. Analysis of the impact of industrial structure changes on carbon emissions in China based on LMDI method [J]. Resource Science, 2016, 38(10): 1861-1870.

[14] Zhang Lei, Huang Yuanxi, Li Yanmei, Cheng Xiaoling. Analysis of regional patterns of carbon emissions in China and ways to reduce them [J]. Resource Science, 2010, 32(02): 211-217.

[15] Lan-Cui Liu, Ying Fan, Gang Wu, Yi-Ming Wei. Using LMDI method to analyze the change of China's industrial CO^2 emissions from final fuel use: An empirical analysis [J]. Energy Policy. 2007 (11)

[16] Yu Yihua, Zheng Xinye, Zhang Li. Economic development level, industrial structure and carbon emission intensity: An analysis of provincial panel data in China [J]. Economic theory and economic management, 2011(03): 72-81.

[17] Zhang Zhixin, Xue Qiao. Low-carbon economy, industrial structure and changes in China's development mode based on the data of 1996- 2009 in empirical analysis [J]. Energy Procedia. 2011

[18] Li Jian, Zhou Hui. Correlation analysis of carbon emission intensity and industrial structure in China [J]. China Population, Resources and Environment, 2012, 22(01): 7-14.