基于STIRPAT模型的大连市全流程碳足迹溯源

doi:10.11930/j.issn.1004-9649.202310008

中国电力 ›› 2024, Vol. 57 ›› Issue (1): 133-139.DOI: 10.11930/j.issn.1004-9649.202310008

• 新型电力系统低碳规划与运行 • 上一篇下一篇

基于STIRPAT模型的大连市全流程碳足迹溯源

张娜¹(), 赵琳¹(), 商文颖¹(), 吉星¹, 李佳²(), 黄玉辉³

1. 国网辽宁省电力有限公司经济技术研究院，辽宁沈阳　110015
2. 上海交通大学中英国际低碳学院，上海　201306
3. 上海交通大学电子信息与电气工程学院，上海　200240

收稿日期:2023-10-08 出版日期:2024-01-28 发布日期:2024-01-23
作者简介:张娜（1986—），女，博士，高级工程师，从事电力市场建设研究，E-mail：zn_jyy@126.com
赵琳（1987—），女，硕士，高级工程师，从事高比例新能源并网后的电力系统规划运行研究，E-mail：zhaolin@ln.sgcc.com.cn
商文颖（1980—），女，硕士，高级工程师，从事电力市场、电力价格机制研究，E-mail：jx@ln.sgcc.com.cn
李佳（1980—），男，通信作者，博士，副教授，从事碳管理与城市规划等研究，E-mail：weee@sjtu.edu.cn
基金资助:
国家电网有限公司科技项目（5400-202128572A-0-5-SF）。

Whole Process Carbon Footprint Traceability of Dalian City Based on STIRPAT Model

Na ZHANG¹(), Lin ZHAO¹(), Wenying SHANG¹(), Xing JI¹, Jia LI²(), Yuhui HUANG³

1. State Grid Liaoning Electric Power Company Limited Economic Research Institute, Shenyang 110015, China
2. China-UK Low Carbon College, Shanghai Jiao Tong University, Shanghai 200240, China.
3. School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received:2023-10-08 Online:2024-01-28 Published:2024-01-23
Supported by:
This work is supported by Science and Technology Project of SGCC (No.5400-202128572A-0-5-SF).

摘要/Abstract

摘要：

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。

关键词: 碳足迹, 碳排放, 碳足迹产值, 碳足迹强度

Abstract:

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.

Key words: carbon footprint, carbon emissions, value of carbon footprint, carbon footprint intensity

张娜, 赵琳, 商文颖, 吉星, 李佳, 黄玉辉. 基于STIRPAT模型的大连市全流程碳足迹溯源[J]. 中国电力, 2024, 57(1): 133-139.

Na ZHANG, Lin ZHAO, Wenying SHANG, Xing JI, Jia LI, Yuhui HUANG. Whole Process Carbon Footprint Traceability of Dalian City Based on STIRPAT Model[J]. Electric Power, 2024, 57(1): 133-139.

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参考文献 25

1	苏志鹏, 王莉, 梁欣怡, 等. 考虑阶梯式碳交易及综合需求响应的虚拟电厂优化调度[J]. 中国电力, 2023, 56 (12): 174- 182.
	SU Zhipeng, WANG Li, LIANG Xinyi, et al. Optimal dispatch of virtual power plant considering stepped carbon trading and comprehensive demand response[J]. Electric Power, 2023, 56 (12): 174- 182.
2	李强, 王尧, 胡迎迎, 等. 考虑碳交易成本的输储多阶段协调规划方法[J]. 中国电力, 2023, 56 (12): 199- 205.
	LI Qiang, WANG Yao, HU Yingying, et al. Multi-stage coordinated planning method for transmission network and energy storage considering carbon trading cost[J]. Electric Power, 2023, 56 (12): 199- 205.
3	贺文, 陈珍萍, 胡伏原, 等. 基于一致性的综合能源系统低碳经济调度[J]. 电力系统保护与控制, 2023, 51 (19): 42- 53.
	HE Wen, CHEN Zhenping, HU Fuyuan, et al. Consensus-based low-carbon economic dispatching of integrated energy systems[J]. Power System Protection and Control, 2023, 51 (19): 42- 53.
4	马君亮, 王智冬, 张述铭. 考虑县域光伏潜力评估的源网荷储协同规划[J]. 东北电力大学学报, 2023, 43 (3): 82- 90.
	MA Junliang, WANG Zhidong, ZHANG Shuming. Collaborative planning of source-grid-load-storage considering county PV potential assessment[J]. Journal of Northeast Electric Power University, 2023, 43 (3): 82- 90.
5	朱灿元, 杨超, 李舒涛, 等. 考虑清洁能源与储能的分布式数据中心低碳调度策略[J]. 智慧电力, 2023, 51 (2): 16- 23.
	ZHU Canyuan, YANG Chao, LI Shutao, et al. Low-carbon scheduling strategy for distributed data centers considering clean energy and energy storage[J]. Smart Power, 2023, 51 (2): 16- 23.
6	TOMÁS M, LÓPEZ L A, MONSALVE F. Carbon footprint, municipality size and rurality in Spain: inequality and carbon taxation[J]. Journal of Cleaner Production, 2020, 266, 121798. DOI
7	杨传明. 新旧常态中国产业全碳足迹复杂网络比较[J]. 自然资源学报, 2020, 35 (2): 313- 328. DOI
	YANG Chuanming. A comparative study on the complex networks of China’s industrial total carbon footprint in the new and old normal periods[J]. Journal of Natural Resources, 2020, 35 (2): 313- 328. DOI
8	张运洲, 张宁, 代红才, 等. 中国电力系统低碳发展分析模型构建与转型路径比较[J]. 中国电力, 2021, 54 (3): 1- 11.
	ZHANG Yunzhou, ZHANG Ning, DAI Hongcai, et al. Model construction and pathways of low-carbon transition of China’s power system[J]. Electric Power, 2021, 54 (3): 1- 11.
9	FU W, LUO M C, CHEN J C, et al. Carbon footprint and carbon carrying capacity of vegetation in ecologically fragile areas: a case study of Yunnan[J]. Physics and Chemistry of the Earth, Parts A/B/C, 2020, 120, 102904. DOI
10	孙丽文, 韩莹, 杜娟. 京津冀高能耗产业碳足迹的影响因素: 基于de Bruyn模型[J]. 技术经济, 2019, 38 (8): 86- 92, 118.
	SUN Liwen, HAN Ying, DU Juan. Influencing factors of carbon footprint of high energy consumption industry in Beijing, Tianjin and Hebei: based on de Bruyn model[J]. Technology Economics, 2019, 38 (8): 86- 92, 118.
11	石羽, 运迎霞, 刘冲, 等. 辽宁中部城市群建筑碳足迹[J]. 应用生态学报, 2017, 28 (6): 2040- 2046.
	SHI Yu, YUN Yingxia, LIU Chong, et al. Carbon footprint of buildings in the urban agglomeration of central Liaoning, China[J]. Chinese Journal of Applied Ecology, 2017, 28 (6): 2040- 2046.
12	ONAT N C, KUCUKVAR M. Carbon footprint of construction industry: a global review and supply chain analysis[J]. Renewable and Sustainable Energy Reviews, 2020, 124, 109783. DOI
13	SCHUELER M, HANSEN S, PAULSEN H M. Discrimination of milk carbon footprints from different dairy farms when using IPCC Tier 1 methodology for calculation of GHG emissions from managed soils[J]. Journal of Cleaner Production, 2018, 177, 899- 907. DOI
14	陈家兴, 王春玲, 刘春明. 基于改进碳排放流理论的电力系统动态低碳调度方法[J]. 中国电力, 2023, 56 (3): 162- 172.
	CHEN Jiaxing, WANG Chunling, LIU Chunming. Dynamic low-carbon dispatching method of power system based on improved carbon emission flow theory[J]. Electric Power, 2023, 56 (3): 162- 172.
15	陈厚合, 茅文玲, 张儒峰, 等. 基于碳排放流理论的电力系统源-荷协调低碳优化调度[J]. 电力系统保护与控制, 2021, 49 (10): 1- 11.
	CHEN Houhe, MAO Wenling, ZHANG Rufeng, et al. Low-carbon optimal scheduling of a power system source-load considering coordination based on carbon emission flow theory[J]. Power System Protection and Control, 2021, 49 (10): 1- 11.
16	黄大为, 李赛龙, 孔令国. 计及中长期合同电量分解与风电报价的日前市场出清模型研究[J]. 东北电力大学学报, 2023, 43 (4): 45- 56.
	HUANG Dawei, LI Sailong, KONG Lingguo. Research on day-ahead electricity market clearing ModelConsidering medium and long-term ContractsDecomposition and wind power producer bidding[J]. Journal of Northeast Electric Power University, 2023, 43 (4): 45- 56.
17	HU J M, LIU G Y, MENG F X, et al. Subnational carbon flow pattern analysis using multi-scale input-output model[J]. Ecological Modelling, 2020, 431, 109138. DOI
18	彭水军, 张文城, 孙传旺. 中国生产侧和消费侧碳排放量测算及影响因素研究[J]. 经济研究, 2015, 50 (1): 168- 182.
	PENG Shuijun, ZHANG Wencheng, SUN Chuanwang. China’s production-based and consumption-based carbon emissions and their determinants[J]. Economic Research Journal, 2015, 50 (1): 168- 182.
19	黄景光, 熊华健, 李振兴, 等. 基于生命周期法和碳权交易的综合能源系统低碳经济调度[J]. 电测与仪表, 2022, 59 (3): 82- 91.
	HUANG Jingguang, XIONG Huajian, LI Zhenxing, et al. Low-carbon economic dispatch of integrated energy system based on life cycle method and carbon trading[J]. Electrical Measurement & Instrumentation, 2022, 59 (3): 82- 91.
20	LUO W, ZHANG Y R, GAO Y L, et al. Life cycle carbon cost of buildings under carbon trading and carbon tax system in China[J]. Sustainable Cities and Society, 2021, 66, 102509. DOI
21	杨花, 杜斌, 吕锋骅, 等. 基于IPCC排放清单和LEAP模型的山西省CO₂排放研究[J]. 环境污染与防治, 2014, 36 (3): 103- 109.
	YANG Hua, DU Bin, LV Fenghua, et al. Study on CO₂ emissions in Shanxi Province base on IPCC listing and LEAP model[J]. Environmental Pollution & Control, 2014, 36 (3): 103- 109.
22	张国兴, 苏钊贤. 黄河流域交通运输碳排放的影响因素分解与情景预测[J]. 管理评论, 2020, 32 (12): 283- 294.
	ZHANG Guoxing, SU Zhaoxian. Analysis of influencing factors and scenario prediction of transportation carbon emissions in the Yellow River Basin[J]. Management Review, 2020, 32 (12): 283- 294.
23	王兴民, 吴静, 白冰, 等. 中国CO₂排放的空间分异与驱动因素: 基于198个地级及以上城市数据的分析[J]. 经济地理, 2020, 40 (11): 29- 38.
	WANG Xingmin, WU Jing, BAI Bing, et al. Spatial differentiation and driving factors of CO₂ emissions: analysis based on 198 cities at prefecture level and above in China[J]. Economic Geography, 2020, 40 (11): 29- 38.
24	曲嘉伟, 朱乐为, 刘泽宇, 等. 计及压缩空气储能的综合能源微网可靠性评估[J]. 东北电力大学学报, 2022, 42 (6): 8- 18, 105.
	QU Jiawei, ZHU Lewei, LIU Zeyu, et al. Reliability assessment for integrated energy microgrid system with compressed air energy storage[J]. Journal of Northeast Electric Power University, 2022, 42 (6): 8- 18, 105.
25	李怀慎, 夏能弘, 张俊. 地铁杂散电流影响下的地表电位计算及敏感性因素分析[J]. 电力科学与技术学报, 2023, 38 (2): 105- 113.
	LI Huaishen, XIA Nenghong, ZHANG Jun. Calculation of surface potential and analysis of sensitivity factors under the influence of stray current in metro systems[J]. Journal of Electric Power Science and Technology, 2023, 38 (2): 105- 113.

行业名称	CO₂排放量/Mt	主要排放源	下调10%该指标影响下降的CO₂ 排放量/Mt	敏感性分析
电力行业	49.93	煤炭	4.99117	0.099963
		柴油	0.00105	0.000021
		燃料油	0.00023	0.000005
建材行业	5.59	烟煤	0.30580	0.054705
		电力	0.22719	0.040642
		燃料油	0.01107	0.001980
钢铁行业	4.69	煤炭	0.06713	0.014313
		焦炭	0.05038	0.010742
		熔剂消耗	0.02457	0.005239
有色行业	0.03	焦炭	0.00171	0.057000
		天然气	0.00078	0.026000
		煤	0.00008	0.002667
石化行业	24.02	热力购买量	0.74640	0.031074
		烟煤消费量	0.70766	0.029461
		无烟煤消费量	0.52065	0.021676
化工行业	6.96	烟煤	0.45860	0.065891
		热力	0.31253	0.044904
		电力	0.14783	0.021240
造纸行业	0.22	净电	0.00966	0.043909
		洗煤消费量	0.00827	0.037591
		生产过程排放	0.00258	0.011727
民航行业	0.01	燃料油	0.00039	0.039000
		煤油	0.00031	0.031000
		净电	0.00030	0.030000

行业名称	CO₂排放量/Mt	主要排放源	下调10%该指标影响下降的CO₂ 排放量/Mt	敏感性分析
电力行业	49.93	煤炭	4.99117	0.099963
		柴油	0.00105	0.000021
		燃料油	0.00023	0.000005
建材行业	5.59	烟煤	0.30580	0.054705
		电力	0.22719	0.040642
		燃料油	0.01107	0.001980
钢铁行业	4.69	煤炭	0.06713	0.014313
		焦炭	0.05038	0.010742
		熔剂消耗	0.02457	0.005239
有色行业	0.03	焦炭	0.00171	0.057000
		天然气	0.00078	0.026000
		煤	0.00008	0.002667
石化行业	24.02	热力购买量	0.74640	0.031074
		烟煤消费量	0.70766	0.029461
		无烟煤消费量	0.52065	0.021676
化工行业	6.96	烟煤	0.45860	0.065891
		热力	0.31253	0.044904
		电力	0.14783	0.021240
造纸行业	0.22	净电	0.00966	0.043909
		洗煤消费量	0.00827	0.037591
		生产过程排放	0.00258	0.011727
民航行业	0.01	燃料油	0.00039	0.039000
		煤油	0.00031	0.031000
		净电	0.00030	0.030000

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基于STIRPAT模型的大连市全流程碳足迹溯源

Whole Process Carbon Footprint Traceability of Dalian City Based on STIRPAT Model

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基于STIRPAT模型的大连市全流程碳足迹溯源

Whole Process Carbon Footprint Traceability of Dalian City Based on STIRPAT Model

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