长江经济带碳达峰与工业稳增长协同路径研究

doi:10.3969/j.issn.1004-9479.2026.08.20241135

摘要/Abstract

摘要：

工业平稳增长与碳达峰目标的协同发展，是实现经济结构优化和绿色低碳转型的关键路径。本文基于系统动力学模型，设计不同政策情景组合方案来模拟预测经济发展、能源结构和工业占比等对碳达峰的影响，揭示长江经济带工业稳增长与碳达峰协同发展的最优路径。研究表明：①工业占比下降过快或过慢均不利于长江经济带实现工业稳增长和碳达峰的协同发展。②在基准情景和经济高速发展情景下，长江经济带难以实现2030年碳达峰目标，只有在能源优化情景下才能于2025年实现碳达峰目标。③长江经济带应以能源优化情景为参考实现碳达峰目标，并将工业占比保持在26.6%~29.1%之间，以此为支点，积极推进碳达峰和工业稳增长协同发展。④长江经济带各省市可基于自身资源禀赋，实现差异化碳达峰目标，进一步促进高技术、高附加值产业的发展，从而有效提高工业生产效率、降低碳排放水平，最终实现工业增长与碳达峰协同发展。

关键词: 工业稳增长, 碳达峰, 工业占比, 系统动力学

Abstract:

The coordination between steady industrial growth and the carbon peaking target constitutes a critical pathway to optimize economic structure and advance green and low-carbon transition. Using a system dynamics model, this paper designs alternative policy scenario combinations to simulate the impacts of economic development, energy mix, and industrial proportion on carbon peaking, and identifies the optimal pathway for reconciling steady industrial growth with carbon peaking in the YREB. Three findings emerge. First, both an overly rapid and an overly slow decline in the industrial share hinder the joint objective. Second, under the baseline and high-growth scenarios, the YREB is unlikely to peak emissions by 2030, whereas an energy-optimization scenario delivers a peak by 2025. Third, conditional on the energy-optimization path, an industrial share in the range of 26.6~29.1 percent serves as an effective fulcrum for reconciling carbon peaking with stable industrial expansion. Finally, based on their own resource endowments, provinces and municipalities in the Yangtze River Economic Belt can pursue differentiated carbon peaking targets, further boost the development of high-tech and high-value-added industries, effectively raise industrial production efficiency, lower carbon emissions, and achieve coordination between industrial development and carbon peaking.

Key words: steady industrial growth, carbon peaking, industrial proportion, system dynamics

陈志建, 李凯阳, 余颖, 张晓艳. 长江经济带碳达峰与工业稳增长协同路径研究[J]. 世界地理研究, 2026, 35(8): 92-109.

Zhijian CHEN, Kaiyang LI, Ying YU, Xiaoyan ZHANG. Research on the coordinated pathways of carbon peaking and steady industrial growth in the Yangtze River Economic Belt[J]. World Regional Studies, 2026, 35(8): 92-109.

图/表 13

参考文献 50

[1]	严金明.«长江经济带资源环境与绿色发展»评介.地理学报,2021,76(10):2605.
	YAN J. Review of resource environment and green development in the Yangtze River Economic Belt. Acta Geographica Sinica,2021,76(10):2605.
[2]	中国社会科学院工业经济研究所课题组.工业稳增长:国际经验、现实挑战与政策导向.中国工业经济,2022(2):5-26.
	Research Group of Institute of Industrial Economics of CASS. Stabilizing industrial growth: International experience, practical challenges and policy orientation. China Industrial Economics, 2022(2):5-26.
[3]	徐莉萍,孙文明.主体功能区生态预算系统:环境、结构与合作.经济学家,2013(9):43-51.
	XU L, SUN W. Ecological budget system of main functional areas: Environment, structure and cooperation. Economist, 2013(9):43-51.
[4]	王铮,孙翊.中国主体功能区协调发展与产业结构演化.地理科学,2013,33(6):641-648.
	WANG Z, SUN Y. A simulation on regional coordination and industrial structure evolution oriented to the main functional areas of China. Scientia Geographica Sinica, 2013,33(6):641-648.
[5]	孙翊,钟章奇,徐程瑾,等.中国生产控制型产业减排的居民福利和区域影响.地理科学,2015,35(9):1067-1076.
	SUN Y, ZHONG Z, XU C, et al. Impact of carbon abatement policies in manufacturing process control on household welfare and regional economic development. Scientia Geographica Sinica, 2015,35(9):1067-1076.
[6]	WOLF S, GHOSH R. A practice-centered analysis of environmental accounting standards: Integrating agriculture into carbon governance. Land Use Policy, 2020, 96: 103552.
[7]	田云,蔡艳蓉.长江经济带农业碳排放EKC检验及其驱动因素分析.长江流域资源与环境,2023,32(11):2403-2417.
	TIAN Y, CAI Y. EKC-based test for agricultural carbon emissions in Yangtze River Economic Belt and analysis of driving factors . Resources and Environment in the Yangtze Basin,2023,32(11):2403-2417.
[8]	何飞扬,刘天乐,周智杰,等.基于EKC理论下碳排放与经济增长的二者关系研究——浙江省与安徽省的对比分析.生态经济,2024,40(6):21-29.
	HE F, LIU T, ZHOU Z, et al. Research on the relationship between carbon emissions and economic growth based on EKC theory: A comparative analysis of Zhejiang province and Anhui province. Ecological Economy, 2024,40(6):21-29.
[9]	宋岚,王莉,邹方政.基于LMDI及STIRPAT模型的中国工业能源消费碳排放峰值预测研究.西部经济管理论坛,2023,34(6):90-99.
	SONG L, WANG L, ZOU F. Prediction of peak carbon emissions from industrial energy consumption in China based on LMDI and STIRPAT model. West Forum on Economy and Management,2023,34(6):90-99.
[10]	李清瑶,张勇,胡民泉,等."双碳"目标实现的省域实践:以浙江为例.生态与农村环境学报,2024,40(2):191-204.
	LI Q, ZHANG Y, HU M, et al. Provincial practice of achieving the "Dual Carbon" target: Taking Zhejiang province as an example. Journal of Ecology and Rural Environment,2024,40(2):191-204.
[11]	罗闯,黎林,王雨豪,等.基于LEAP模型的江苏省重点行业碳达峰碳中和情景.环境科学,2025,46(1):1-9.
	LUO C, LI L, WANG Y, et al. Carbon peak and carbon neutrality scenarios for key industries in Jiangsu province based on LEAP model. Environmental Science,2025,46(1):1-9.
[12]	胡剑波,罗志鹏,李峰."碳达峰"目标下中国碳排放强度预测——基于LSTM和ARIMA-BP模型的分析.财经科学,2022(2):89-101.
	HU J, LUO Z, LI F. Prediction of China's carbon emission intensity under the goal of carbon peak analysis based on LSTM and ARIMA-BP model. Finance & Economics,2022(2):89-101.
[13]	ZHU H, YUE J, WANG H. Will China's urbanization support its carbon peak goal?–A forecast analysis based on the improved GCAM. Ecological Indicators, 2024, 163: 112072.
[14]	柴麒敏,徐华清.基于IAMC模型的中国碳排放峰值目标实现路径研究.中国人口·资源与环境,2015,25(6):37-46.
	CHAI Q, XU H. Modeling carbon emission peaking pathways in China based on integrated assessment model IAMC. China Population, Resources and Environment, 2015, 25(6): 37-46.
[15]	王锋.中国碳排放峰值及其倒逼机制研究的发展动态.中国人口·资源与环境,2018,28(2):141-150.
	WANG F.Development trend of the study on China's carbon emission peak and its forcing mechanisms.China Population,Resources and Environment,2018,28(2):141-150.
[16]	陈志建,刘月梅,刘晓,等.经济平稳增长下长江经济带碳排放峰值研究——基于全球夜间灯光数据的视角.自然资源学报,2018,33(12):2213-2222.
	CHEN Z, LIU Y, LIU X, et al. Research on carbon emission peak in Yangtze River Economic Zone with steady economic growth: Based on data of global night-time light. Journal of Natural Resources,2018,33(12):2213-2222.
[17]	张兴龙.投入产出关联对资源错配损失效应的放大机理及实证——基于中国投入产出表的分析.产业经济研究,2019(4):23-36.
	ZHANG X. The mechanism and empirical research of how input-output relevancy amplify the losses of resource misallocation: Analyses based on China's input-output tables. Industrial Economics Research,2019(4):23-36.
[18]	史丹,李鹏."双碳"目标下工业碳排放结构模拟与政策冲击.改革,2021(12):30-44.
	SHI D, LI P. Industrial carbon emission structure simulation and policy impact under the target of "double carbon". Reform,2021(12):30-44.
[19]	杜传忠,侯佳妮."去工业化"对中国地区经济增长的影响:基于门槛效应的分析.现代财经(天津财经大学学报),2021,41(9):3-19.
	DU C, HOU J. Impact of deindustrialization on China's regional economic growth: An analysis based on threshold effect . Modern Finance and Economics-Journal of Tianjin University of Finance and Economics,2021,41(9):3-19.
[20]	杜传忠."十四五"时期我国制造业比重的合理区间探析.人民论坛,2021(26):73-77.
	DU C. Analysis of the reasonable range of the proportion of China's manufacturing industry in the "14th Five-Year Plan" period. People's Tribune,2021(26):73-77.
[21]	张杰.中国制造业增加值占GDP比重的变化趋势与内在规律.探索与争鸣,2021(5):57-72.
	ZHANG J. The changing trend and internal law of the proportion of added value of China's manufacturing industry in GDP. Exploration and Free Views,2021(5):57-72.
[22]	郭克莎,彭继宗.制造业在中国新发展阶段的战略地位和作用.中国社会科学,2021(5):128-149.
	GUO K, PENG J.The manufacturing sector's strategic position and role in China's new stage of development. Social Sciences in China,2021(5):128-149.
[23]	黄群慧,杨虎涛.中国制造业比重"内外差"现象及其"去工业化"涵义.中国工业经济,2022(3):20-37.
	HUANG Q, YANG H. Chinese "domestic-international differentials" in manufacturing value added and its meaning of "de-industrialization" . China Industrial Economics,2022(3):20-37.
[24]	叶振宇.中国制造业比重下降趋势探究与应对策略.中国软科学,2021(5):12-25.
	YE Z. Research on the decline of China's manufacturing proportion and its corresponding strategy.China Soft Science,2021(5):12-25.
[25]	郑江淮,张睿,孙冬卿.中国跨越"中高端制造业陷阱":一个制造业合理比重假说与政策选择.改革,2023(4):37-52.
	ZHENG J, ZHANG R, SUN D. China's crossing the "mid-to-high-end manufacturing trap": A reasonable manufacturing proportion hypothesis and policy choices. Reform,2023(4):37-52.
[26]	REKHA R, BABU S. Premature deindustrialisation and growth slowdowns in middle-income countries . Structural Change and Economic Dynamics, 2022, 62: 377-389.
[27]	陈诗一.节能减排与中国工业的双赢发展:2009—2049.经济研究,2010,45(3):129-143.
	CHEN S. Energy-Save and emission-abate activity with its impact on industrial win-win development in China:2009－2049. Economic Research Journal,2010,45(3):129-143.
[28]	程时雄,柳剑平,龚兆鋆.中国工业行业节能减排经济增长效应的测度及影响因素分析.世界经济,2016,39(3):166-192.
	CHENG S, LIU J, GONG Z. Measurement of the economic growth effect of energy saving and emission reduction in China's industrial sector and analysis of influencing factors. The Journal of World Economy,2016,39(3):166-192.
[29]	陈超凡.节能减排与中国工业绿色增长的模拟预测.中国人口·资源与环境,2018,28(4):145-154.
	CHEN C. The simulation and prediction of energy conservation,emission reduction and green growth of China's industry. China Population,Resources and Environment,2018,28(4):145-154.
[30]	张可云,朱春筱.中国工业结对集聚和空间关联性分析.地理学报,2021,76(4):1019-1033.
	ZHANG K, ZHU C.Coagglomeration and spatial relatedness of China's industry. Acta Geographica Sinica, 2021,76(4):1019-1033.
[31]	曹卫东,曹继,张文瑞,等.中国重大生产力布局演变与空间形态模拟.地理学报,2024,79(12):3030-3049.
	CAO W, CAO J, ZHANG W, et al. Evolution of major productive force layout and spatial form simulation in China. Acta Geographica Sinica,2024,79(12):3030-3049.
[32]	刘宇,吕郢康,周梅芳.投入产出法测算CO₂排放量及其影响因素分析.中国人口·资源与环境,2015,25(9):21-28.
	LIU Y, LV Y, ZHOU M. Analysis on the influence factors of computing CO₂ emission by input-output method. China Population,Resources and Environment,2015,25(9):21-28.
[33]	SHAN Y, HUANG Q, GUAN D, et al. China CO2 emission accounts 2016–2017. Scientific data, 2020, 7(1): 54.
[34]	浙江省散装水泥发展中心. 水泥脱碳报告发布:从生产和消费两端发力. (2023-08-25). .[Zhejiang Provincial Bulk Cement Development Center. Cement Decarbonization Report Released: Efforts Made on Both Production and Consumption Sides.(2023-08-25).
[35]	世界银行国务院发展研究中心联合课题组.2030年的中国:建设现代、和谐、有创造力的社会.北京:中国财政经济出版社,2013.
	Joint Research Group of the Development Research Centre of the State Council of the World Bank. China 2030: Building a modern, harmonious and creative society.BeiJing: China Finance and Economy Press,2013.
[36]	林毅夫,文永恒,顾艳伟.中国经济增长潜力展望:2020- 2035、2035-2050.金融论坛,2022,27(6):3-15.
	LIN Y, WEN Y, GU Y. Prospect of China's economic growth potential:2020- 2035、2035-2050. Finance Forum, 2022,27(6):3-15.
[37]	钞小静.未来十年增长潜力预测与"十四五"时期战略目标、战略重点.浙江工商大学学报,2020(5):125-133.
	CHAO X. Forecast of growth potential in the next ten years as well as strategic objectives and key points in the 14th five-year plan period. Journal of Zhejiang Gongshang University,2020(5):125-133.
[38]	中国社会科学院宏观经济研究中心课题组.未来15年中国经济增长潜力与"十四五"时期经济社会发展主要目标及指标研究.中国工业经济,2020(4):5-22.
	Research Group of the Macroeconomic Research Center of the CASS. Research on the potential growth of the chineses economy in the next 15 years and the main goals and indicators of economic and social development during the 14th five-year plan period. China Industrial Economics,2020(4):5-22.
[39]	白重恩,张琼.中国经济增长潜力预测:兼顾跨国生产率收敛与中国劳动力特征的供给侧分析.经济学报,2017,4(4):1-27.
	BAI C, ZHANG Q. China's growth potential to 2050: A supply-side forecast based on cross-country productivity convergence and its featured labor force. China Journal of Economics,2017,4(4):1-27.
[40]	章高敏,王腾,娄渊雨,等.基于LSTM神经网络的中国省级碳达峰路径分析.中国管理科学, 2025, 33(03):339-350.
	ZHANG G, WANG T, LOU Y, et al. Research on China's provincial carbon emission peak path based on a LSTM neural network approach. Chinese Journal of Management Science, 2025, 33(03): 339-350.
[41]	曾鹏,魏旭,黄丽露."双碳"目标约束下的中国城市群高质量发展SD模型与模拟.河海大学学报(哲学社会科学版),2022,24(5):52-61.
	ZENG P, WEI X, HUANG L. SD model and simulation of high-quality development of China's urban agglomeration under "dual carbon" goals. Journal of Hohai University(Philosophy and Social Sciences),2022,24(5):52-61.
[42]	陈卫.中国人口负增长与老龄化趋势预测.社会科学辑刊,2022(5):133-144.
	CHEN W. Forecasting negative population growth and population ageing in China. Social Science Journal,2022(5):133-144.
[43]	ZHU M, ZHANG Z, ZHU B, et al. Population and economic projections in the Yangtze River Basin based on shared socioeconomic pathways.Sustainability,2020,12(10):4202.
[44]	朱宇恩,李丽芬,贺思思,等.基于IPAT模型和情景分析法的山西省碳排放峰值年预测.资源科学,2016,38(12):2316-2325.
	ZHU Y, LI L, HE S,et al. Peak year prediction of Shanxi Province's carbon emissions based on IPAT modeling and scenario analysis. Resources Science,2016,38(12):2316-2325.
[45]	蒋昀辰,钟苏娟,王逸,等.全国各省域碳达峰时空特征及影响因素.自然资源学报,2022,37(5):1289-1302.
	JIANG Y, ZHONG S, WANG Y, et al. Spatio-temporal characteristics and influencing factors of carbon emission peak by province of China. Journal of Natural Resources,2022,37(5):1289-1302.
[46]	王少剑,莫惠斌,方创琳.珠江三角洲城市群城市碳排放动态模拟与碳达峰.科学通报,2022,67(7):670-684.
	WANG S, MO H, FANG C. Carbon emissions dynamic simulation and its peak of cities in the Pearl River Delta Urban Agglomeration . Chinese Science Bulletin, 2022,67(7):670-684.
[47]	曲建升,刘莉娜,曾静静,等.中国居民生活碳排放增长路径研究.资源科学,2017,39(12):2389-2398.
	QU J, LIU L, ZENG J,et al. A study on growth path for China's household CO2 emissions. Resources Science, 2017,39(12):2389-2398.
[48]	中国社会科学院工业经济研究所课题组.现代化进程中的中国工业:发展逻辑、现实条件与政策取向.中国工业经济,2024(3):5-23.
	Research Group of Institute of Industrial Economics of CASS, China's industry in the process of modernization: Logic of development, realistic conditions and policy orientation. China Industrial Economics,2024(3):5-23.
[49]	郑军,刘婷.主要发达国家碳达峰碳中和的实践经验及对中国的启示.中国环境管理,2023,15(4):18-25.
	ZHENG J, LIU T. The practice experience of carbon peak and carbon neutrality in major developed countries and its enlightenment for China. Chinese Journal of Environmental Management, 2023, 15(4): 18-25.
[50]	蔡浩,李海静,刘静.从国际比较看碳达峰对中国经济的启示.新金融,2021,(5):23-29.
	CAI H, LI H, LIU J. The Enlightenment of Carbon Peak to China's Economy from the Perspective of International Comparison. New Finance,2021,(5):23-29.

子系统	变量
经济	GDP、人均GDP、GDP增长率、GDP增加值、工业增加值、工业占比、固定资产投资增速、城镇化
人口	总人口数、出生率、死亡率、人口增长率、人口增加量、人口减少量
能源	万元工业增加值能耗、能源消费总量、能源强度、煤炭能源消费量、石油能源消费量、天然气能源消费量、煤炭碳排放量、石油碳排放量、天然气排放量
非能源排放	水泥生产量、水泥生产增长率、水泥增加值

子系统	变量
经济	GDP、人均GDP、GDP增长率、GDP增加值、工业增加值、工业占比、固定资产投资增速、城镇化
人口	总人口数、出生率、死亡率、人口增长率、人口增加量、人口减少量
能源	万元工业增加值能耗、能源消费总量、能源强度、煤炭能源消费量、石油能源消费量、天然气能源消费量、煤炭碳排放量、石油碳排放量、天然气排放量
非能源排放	水泥生产量、水泥生产增长率、水泥增加值

变量	变量及方程表达
GDP	INTEG(GDP增长量，初始值)/亿元
GDP增加值	GDP×GDP增长率/亿元
人均GDP	GDP/总人口/（万元/人）
总人口数	INTEG(出生人口－死亡人口，初始值)/万人
城镇化	年末城镇人口数/总人口数/%
工业增加值	GDP×工业占比/亿元
工业占比增长率	(工业占比-DELAY1I(工业占比，1，初始值))/DELAY1I(工业占比，1，初始值)/%
万元工业增加值能耗	能源消费总量/工业增加值/（吨标准煤/万元）
能源强度	能源消费总量/GDP/（吨标准煤/万元）
煤炭碳排放量	煤炭能源消费量*煤炭碳排放系数/万吨
石油碳排放量	石油能源消费量*石油碳排放系数/万吨
天然气碳排放量	天然气能源消费量*天然气碳排放系数/万吨
水泥生产量	INTEG(水泥增加值，初始值)/万吨
水泥碳排放量	水泥碳排放系数*水泥生产量/万吨
碳排放强度	碳排放量/GDP/（吨/万元）
碳排放量	煤炭碳排放量+石油碳排放量+天然气碳排放量+水泥碳排放量/万吨

变量	变量及方程表达
GDP	INTEG(GDP增长量，初始值)/亿元
GDP增加值	GDP×GDP增长率/亿元
人均GDP	GDP/总人口/（万元/人）
总人口数	INTEG(出生人口－死亡人口，初始值)/万人
城镇化	年末城镇人口数/总人口数/%
工业增加值	GDP×工业占比/亿元
工业占比增长率	(工业占比-DELAY1I(工业占比，1，初始值))/DELAY1I(工业占比，1，初始值)/%
万元工业增加值能耗	能源消费总量/工业增加值/（吨标准煤/万元）
能源强度	能源消费总量/GDP/（吨标准煤/万元）
煤炭碳排放量	煤炭能源消费量*煤炭碳排放系数/万吨
石油碳排放量	石油能源消费量*石油碳排放系数/万吨
天然气碳排放量	天然气能源消费量*天然气碳排放系数/万吨
水泥生产量	INTEG(水泥增加值，初始值)/万吨
水泥碳排放量	水泥碳排放系数*水泥生产量/万吨
碳排放强度	碳排放量/GDP/（吨/万元）
碳排放量	煤炭碳排放量+石油碳排放量+天然气碳排放量+水泥碳排放量/万吨

变量	变量内涵和依据
GDP增长率	衡量经济活动的增长。经济增长通常伴随能源需求增加，从而影响碳排放
人口增长率	一个地区人口规模的变化速度。人口增加会导致能源需求上升，进而可导致碳排放增加
万元工业增加值能耗	指每万元工业增加值所消耗的能源量。工业生产是碳排放的主要来源之一，万元工业增加值能耗高表示单位工业产值能源消耗量更大，可能导致较高的碳排放
煤炭消费量占比	指煤炭在总能源消费中的比例，衡量一个国家或地区能源结构中对煤炭的依赖程度。煤炭是高碳能源，其占比直接影响碳排放水平
城镇化率	指城镇人口占总人口的比例。城镇化通常伴随着基础设施建设、交通运输和工业活动的增加，这些活动会增加能源消耗和碳排放