基于 STIRPAT 模型的大连市全流程碳足迹溯源

Translated title of the contribution: Whole Process Carbon Footprint Traceability of Dalian City Based on STIRPAT Model

Na ZHANG, Lin ZHAO, Wenying SHANG, Xing JI, Jia LI, Yuhui HUANG

Research output: Journal PublicationsJournal Article (refereed)peer-review

1 Citation (Scopus)

Abstract

以大连市为研究对象,测算大连市2010—2020年的能源消费碳足迹,计算碳足迹产值、碳足迹强度及生态压力,并以大连市2019年的数据为研究对象分析及计算电力等重点行业的碳排放。研究结果表明:1)从各能源类型来看,2010—2020年石油利用的碳足迹最大,煤炭次之,天然气占比最小;从重点行业来看,2019年电力行业最高,石化行业次之;大连的能源利用效率在2010—2014年不断提高,单位土地面积的产值提高较快,碳足迹带来的经济价值增长速度超过GDP增速,该阶段经济增长不依赖于化石能源;2)2010—2020年各种能源利用产生的碳足迹及其占比由高到低依次为煤炭、石油、天然气,煤炭利用所占的碳足迹比例逐年下降,石油与天然气与之相反。

Taking Dalian city as the research object, this paper measures the carbon footprint of energy consumption in Dalian city from 2010 to 2020, calculates the value of carbon footprint and carbon footprint intensity as well as the ecological pressure intensity, and analyzes the carbon emissions of the key industries with the data of Dalian city in 2019. The research results show that: (1) Based on energy types, petroleum is the largest, coal is the second and natural gas is the smallest in produced carbon footprint from 2010-2020; based on key industries, the power industry is the largest and the petrochemical industry is the second in produced carbon footprint in 2019; the energy utilization efficiency of Dalian city was improving from 2010-2014, and the output value of unit land area increased quickly with the economic value created by carbon footprint surpassing the growth rate of GDP, indicating that economic growth at this stage is independent of fossil energy. (2) The carbon footprint produced by various energy consumption and its percentage in 1995-2006 period decreases from coal to oil to natural gas, and the carbon footprint percentage produced by coal consumption decreases year by year while the oil and natural gas show the opposite.
Translated title of the contributionWhole Process Carbon Footprint Traceability of Dalian City Based on STIRPAT Model
Original languageChinese (Simplified)
Pages (from-to)133-139
Number of pages7
JournalZhongguo Dianli/Electric Power
Volume57
Issue number1
DOIs
Publication statusPublished - 28 Jan 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 Automation of Electric Power Systems Press. All rights reserved.

Funding

This work is supported by Science and Technology Project of SGCC (No.5400-202128572A-0-5-SF).

Keywords

  • carbon emissions
  • carbon footprint
  • carbon footprint intensity
  • value of carbon footprint

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