基于LMDI和系统动力学的陕西省终端CO2减排潜力估算[j]。

Q2 Environmental Science
Lie-Long Zheng, Qiang Zhang, Fang-She Yang, Xing-Yun Zhao, Jia-Xin Luo, Zhi-Hui Shi, Tin-Tin Fan, Guo-Qin Lei, Xu-Peng Jiang
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引用次数: 0

摘要

采用扩展对数平均Dee’s指数(LMDI)模型和系统动力学(SD)模型,探讨了2007 - 2021年陕西省二氧化碳排放的影响因素,并对2022 - 2035年陕西省二氧化碳减排潜力进行了预测。结果表明:①陕西省二氧化碳排放量从2007年的10314 Mt增加到2021年的33687 Mt,年均增长率为7.14%,各部门碳强度总体呈下降趋势;②在LMDI分解结果中,人均GDP增长对CO2排放的促进作用最大,其次是能源结构增长和民用汽车保有量增长。能源强度对CO2排放的抑制作用最大,其次是产业结构、居民能源强度和汽车平均产值。③在基线情景下,陕西省二氧化碳排放量将持续增长至2035年,是2021年的1.75倍。④在综合减排措施下,该地区可在2030年达到碳排放峰值。在基线情景下,2030年陕西省碳强度将比2007年降低71.67%。⑤单一减排政策中,经济规模减排效果最好,结构优化减排效果次之。此外,能源强度优化和新能源汽车场景潜力较小。本研究为陕西省制定低碳政策,推进碳减排,尽快实现碳排放峰值提供了有效的数据支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Estimation of Terminal CO2 Emission Reduction Potential in Shaanxi Province Based on LMDI and System Dynamics].

The extended logarithmic mean Dee's index (LMDI) model and system dynamics (SD) model were used to explore the influencing factors of CO2 emissions in Shaanxi Province from 2007 to 2021 and to predict the emission reduction potential of Shaanxi Province from 2022 to 2035. The results showed that: ① The CO2 emissions in Shaanxi Province increased from 103.14 Mt in 2007 to 336.87 Mt in 2021, with an average annual growth rate of 7.14%, and the carbon intensity of various sectors generally showed a downward trend. ② In the LMDI decomposition results, the growth of per capita GDP had the greatest promoting effect on CO2 emissions, followed by that of energy structure and civilian vehicle ownership. Energy intensity had the greatest inhibitory effect on CO2 emissions, followed by that of industrial structure, residents' energy intensity, and average vehicle output value. ③ Under the baseline scenario, CO2 emissions in Shaanxi Province will continue to grow until 2035, and its emissions will be 1.75 times that of 2021. ④ Under comprehensive emission reduction measures, the region could achieve carbon emission peak in 2030. Under the baseline scenario, the carbon intensity of Shaanxi Province in 2030 will be reduced by 71.67% compared with that in 2007. ⑤ Among the single emission reduction policies, the economic scale scenario was the most effective, followed by the structural optimization scenario. In addition, the energy intensity optimization and new energy vehicle scenarios have less potential. This study provides effective data support for Shaanxi Province to formulate low-carbon policies, promote carbon emission reduction, and achieve carbon emission peak as soon as possible.

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来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
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