首页|基于情景分析法的安徽省能源消耗及碳排放分析

基于情景分析法的安徽省能源消耗及碳排放分析

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为了从区域层面开展能源消耗和碳排放量预测分析,以安徽省能源消耗和碳排放量为研究对象,通过构建LEAP-Anhui预测模型,设计了基准情景(BAS)、发展规划情景(DPS)、节能减排情景(ERS)3种情景,预测了安徽省未来3种不同的发展路径.结果显示:到2035年,BAS情景下能源消耗总量达到23 459×104t(以吨标准煤计),相比BAS情景,DPS与ERS情景能源消耗总量分别下降了 20.6%、30.7%,其中ERS情景的能源消耗总量于2030年实现达峰,峰值为16 416×104t;BAS情景下,安徽省碳排放总量到2035年已达到512.2×106t,年均增长率为2.6%.DPS与ERS情景下,碳排放总量分别于2030年(389.1×106t)、2025年(357.2×106t)达到峰值,均能够完成我国提出的争取在2030年前实现碳达峰的目标承诺.基于碳约束目标对于安徽省能源结构进行了优化分析,在约束路径下,分配给三大系统清洁能源的比例分别为:第三产业39.3%、居民生活23.3%、第二产业37.4%,最小清洁能源需求量为107×1016J,在能源需求总量中的占比为20.6%.
Analysis of energy consumption and carbon emissions in Anhui Province based on scenario analysis
In order to conduct energy consumption and carbon emission prediction analysis at the regional level,energy consumption and carbon emissions in Anhui Province were taken as the research object.By constructing a LEAP Anhui prediction model,three scenarios including baseline scenario(BAS),development planning scenario(DPS),and energy conservation and emission reduction scenario(ERS),were designed to predict three different development paths in Anhui Province.The prediction results show that by 2035,the total energy consumption under BAS scenario will reach 2.345 9× 108 t(energy consumption is calculated based on standard coal),and compared to BAS scenario,the total energy consumption under DPS and ERS scenarios will decrease by 20.6%and 30.7%,respectively.The total energy consumption under ERS scenario will reach its peak in 2030,with a peak of 1.641 6 ×108t.Under BAS scenario,the total carbon emissions in Anhui Province will reach 5.122×108t by 2035,with an average annual growth rate of 2.6%.Under DPS and ERS scenarios,the total carbon emissions will peak in 2030 and 2025,with 3.891×108t and 3.572×108t,respectively,both of which were able to fulfill China's commitment to achieve carbon peak before 2030.Based on the carbon constraint target,an optimization analysis was conducted on the energy structure of Anhui Province.Under the constraint path,the proportion of clean energy allocated to the three major systems is 39.3%for the tertiary industry,23.3%for residential living,and 37.4%for the secondary industry.The minimum demand for clean energy is 1.07×1018 J,accounting for 20.6%of the total energy demand.

development path predictionLEAP modelscenario analysisclean energyenergy structure optimization

陆彪、郝永康、陈德敏、王索军、张雨

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安徽工业大学建筑工程学院

中冶华天南京工程技术有限公司

发展路径预测 LEAP模型 情景分析 清洁能源 能源结构优化

国家自然科学基金安徽省住房城乡建设科学技术计划安徽省住房城乡建设科学技术计划安徽省高等学校科研项目

516080012022-YF0882022-YF057YJS20210352

2024

环境工程技术学报
中国环境科学研究院

环境工程技术学报

CSTPCD北大核心
影响因子:1
ISSN:1674-991X
年,卷(期):2024.14(3)
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