基于双LMDI模型和情景分析的浙江省碳排放影响因素研究
PDF下载 (219)张 浩,郁 丹,唐 人,郭雨涵,朱维骏,何勇玲.基于双LMDI模型和情景分析的浙江省碳排放影响因素研究[J].宁波大学学报(理工版),2023,36(3):114-120.DOI:
ZHANG Hao,YU Dan,TANG Ren,GUO Yuhan,ZHU Weijun,HE Yongling.Study on the influencing factors of carbon emission in Zhejiang Province based on LMDI dual model and scenario analysis[J].Journal of Ningbo University(Natural Science & Engineering Edition),2023,36(3):114-120.DOI:
| Title: | Study on the influencing factors of carbon emission in Zhejiang Province based on LMDI dual model and scenario analysis |
| 作者: | 张 浩, 郁 丹, 唐 人, 郭雨涵, 朱维骏, 何勇玲 |
| Author(s): | ZHANG Hao, YU Dan, TANG Ren, GUO Yuhan, ZHU Weijun, HE Yongling |
| 关键词: | 碳排放; LMDI模型; 情景分析; 浙江省 |
| Keywords: | carbon emissions; LMDI model; scenario analysis; Zhejiang Province |
| 分类号: | X24 |
| 文献标识码: | A |
| 摘要: | 浙江省低碳发展条件相对优越, 可作为率先实现碳达峰和碳中和(“双碳”)的示范省份. 本文采用对数平均迪氏指数分解法(LMDI), 从经济活动和居民生活两方面分别考量, 对浙江省2000—2019年碳排放变化量的驱动因素进行分解. 通过情景分析, 即浙江省分别在2060年(国家战略)和2050年(区域率先)实现“双碳”目标, 对未来浙江省人均碳排放量趋势进行预测, 并结合历史分解结果对两种情景下碳排放变化量的驱动因素进行分解预测. 结果表明 (1)经济活动方面, 人均GDP增加是碳排放的主要驱动因素(累计增量520 Mt), 而单位GDP能耗降低是碳排放的主要抑制因素(累计减量210 Mt); (2)居民生活方面, 人均能耗增加是碳排放的主要驱动因素(累计增量12.6 Mt), 而能源结构低碳化则是主要的碳排放抑制因素(累计减量1.5 Mt); (3)为实现碳中和目标, 两种情景下减排重点均是能源结构的低碳转型, 但转型关键时间线有所不同; 对于2060年和2050年碳中和情景的转型关键时间线分别在于2031—2045年和2036—2050年. |
| Abstract: | With relatively favorable conditions for carbon reduction, Zhejiang Province as a pioneer is believed to be the leading province in reaching the target for carbon neutrality. Based on the collected data, logarithmic Mean Divisia Index (LMDI) is used to analyze the driving factors of the change of economic activities and residential carbon emission in Zhejiang Province from 2000 to 2019 in which time the two scenarios are projected. Using the scenario analysis, the trend of per capita carbon emissions in Zhejiang Province in the future is predicted, and the driving factors of carbon emissions change under the two scenarios are decomposed and projected based on the historical decomposition results. The results show that 1) In terms of economic activities, the per capital GDP effect is the main driving factor for carbon emissions (cumulative increase of 520 Mt), while the energy intensity effect is the main inhibiting factor of carbon emissions (cumulative reduction of 210 Mt); 2) In terms of residential activities, the energy intensity effect is the main driving factor of carbon emissions (cumulative increase of 12.6 Mt), while the energy mix effect is the main inhibiting factor of carbon emissions (cumulative reduction of 1.5 Mt); 3) In order to achieve carbon neutrality, the focus of emission reduction in both scenarios is the low-carbon transformation of energy mix, but the key time period of the transformation is different. The key transition timelines for the 2060 carbon neutral scenario and the 2050 carbon neutral scenario are 2031-2045 and 2036-2050, respectively. |
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| 备注/Memo: | 收稿日期:2022-09-09.宁波大学学报（理工版）网址:http://journallg.nbu.edu.cn/ 基金项目:上海市软科学重点计划项目（21692105000）. 第一作者:张浩（1970－）,男,浙江湖州人,高级工程师,主要研究方向:碳电协同与电网规划.E-mail:864408897@qq.com *通信作者:郁丹（1982－）,男,江苏扬州人,高级工程师,主要研究方向:综合能源与电网规划.E-mail:610829794@qq.com 宁波大学学报（理工版）网址：http://journallg.nbu.edu.cn/ |
