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不同能源政策下苏浙沪能源消费碳排放高峰估计 被引量:7

PROJECTION OF ENERGY CONSUMPTION CARBON EMISSION PEAK FOR JIANGSU, ZHEJIANG AND SHANGHAI UNDER DIFFERENT ENERGY POLICIES
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摘要 中国要实现2030年左右达到CO2排放峰值目标,最终要落实到区域层面上。长三角地区作为中国经济的领头羊,其节能减排政策制定对其它省区具有示范作用。基于经济平稳增长模型对江苏省、浙江省和上海市未来的能源消费碳排放量进行了估计,并模拟了不同能源政策情景对能源消费碳排放的影响。研究表明:(1)基准情景下,江苏省、浙江省和上海市的能源消费碳排放高峰分别出现在2034年、2033年和2032年。(2)不同的能源政策对碳高峰的影响不同。能源结构调整情景和能源效率提高情景下,江苏省、浙江省和上海市的能源消费碳排放高峰都能提前到2030年以前,完成2030年碳排放达到峰值的目标。综合能源政策情景模拟结果显示,同时调整能源结构和提高能源效率,碳减排效果更加明显。 To achieve the target of peaked CO2 emission around 2030, China eventually needs to implement the policies at the regional level. Jiangsu, Zhejiang and Shanghai as the pioneer of China's economy, their energy conservation and emissions reduction policy plays a demonstration role for other provinces. Based on balanced economic growth model, in this paper we projected future energy consumption carbon emissions for Jiangsu, Zhejiang and Shanghai, simulated carbon emissions trend under different energy policy scenarios, and compared the carbon emission reduction effect from energy consumption with the baseline scenario. The results show that:(1)under the benchmark scenario, Jiangsu, Zhejiang and Shanghai's energy consumption carbon emissions peak appears in 2034, 2033 and 2032, respectively.(2)The impact of different energy policies on carbon peak is different. Under energy structure adjustment scenario and energy efficiency improvement scenarios, energy consumption carbon peak of Jiangsu, Zhejiang and Shanghai, appear before 2030, which could complete the target reaching carbon emissions peak in 2030. Comprehensive energy policy scenario simulation results show that while adjusting energy structure and improving energy efficiency, carbon emission reduction effect is more obvious.
出处 《长江流域资源与环境》 CAS CSSCI CSCD 北大核心 2017年第1期15-25,共11页 Resources and Environment in the Yangtze Basin
基金 国家自然科学基金重点项目(41430635) 中国博士后科学基金面上项目(2016M600429) 江苏省高校自然科学研究面上项目(16KJB170003)~~
关键词 能源消费 碳排放 能源结构 能效提高 energy consumption carbon emissions energy structure energy consumption efficiency
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