“双碳”目标下闽三角碳排放脱钩状态及驱动机制分析

快速城市化背景下,建设低碳城市群是实现"双碳"目标的最佳方式。在碳排放核算的基础上,使用Tapio脱钩模型和LMDI方法对闽三角以及厦门、漳州和泉州的脱钩状态和碳排放的驱动机制进行了研究。主要结论如下：（1）2005-2017年闽三角碳排放和人均碳排放均持续增加,二者有相同的变化趋势。闽三角的工业中心泉州有最高的碳排放和人均碳排放。发展型城市漳州碳排放最低,但碳排放和人均碳排放增长率均最高。服务型城市厦门碳排放增长率最低。（2）闽三角的脱钩状态逐渐改善,平均脱钩系数为1.03,脱钩状态为扩张性连接。厦门、漳州和泉州的平均脱钩系数分别为0.45、2.70和1.10,3个城市分别以弱脱钩、扩张负脱钩和扩张性连接状态为主。（3）人均GDP和人口规模是闽三角碳排放的正向因素,能源结构和能源强度是负向因素。正向因素的贡献在下降,负向因素的贡献在升高。人均GDP和能源结构分别对漳州和厦门碳排放有最强的促进和抑制效应。能源强度对3个城市碳排放变化的效应不同。（4）人口扩张促进碳排放增加,使碳排放与经济发展无法脱钩。人口规模对闽三角碳减排无脱钩努力。能源结构优化和能源强度下降有助于碳排放与经济发展脱钩,是闽三角碳减排的强脱钩努力和弱脱钩努力。能源强度对泉州碳减排无脱钩努力。优化能源结构是闽三角实现碳减排和"双碳"目标的关键。已经脱钩的厦门宜尽早制定碳达峰行动计划,引领闽三角的碳达峰行动。漳州可通过升级产业结构实现减排。泉州必须提升能源效率才能降低碳排放。     

Decoupling Analysis of Four Selected Countries

We examine decoupling conditions of domestic extraction of materials, energy use, and sulfur dioxide (SO₂) emissions from gross domestic product (GDP) for two BRIC (Brazil, Russia, India and China) countries (i.e., China and Russia) and two Organisation for Economic Co‐operation and Development (OECD) countries (Japan and the United States) during 2000–2007, using a pair of decoupling indicators for resource use (D_r) and waste emissions (D_e) and the decoupling chart, which can distinguish between absolute decoupling, relative decoupling, and non‐decoupling. We find that (1) during 2000–2007, decoupling between environmental indicators and GDP was higher in the two OECD countries as compared with the two BRIC countries. The key reason is that these countries were in different development stages with different economic growth rates. (2) Changes in environmental policies can significantly influence the degree of decoupling in a country. (3) China, Japan, and the United States were more successful in decoupling SO₂ emissions from GDP than in decoupling material and energy use from GDP. The main reason is that, unlike resource use, waste emissions (e.g., SO₂ emissions) can be reduced by effective end‐of‐pipe treatment. (4) The decoupling indicator is different from the changing rate of resource use and waste emissions. If two countries have different GDP growth rates, even though they may have similar values using the decoupling indicator, they may show different rates of change for resource use and waste emissions.     

基于IPSO-BP神经网络模型的山东省碳排放预测及生态经济分析

在低碳经济发展背景下,针对山东省碳排放数据更新迟缓、以往预测模型难以满足现实需求的问题,统计相关数据,根据政府间气候变化专门委员会(IPCC)推荐方法测算山东省2000—2017年碳排放量和排放强度,并借助脱钩分析、碳承载力和碳赤字探究碳排放的动态变化趋势;基于5项最重要的碳排放影响因素,建立改进的粒子群算法(IPSO...     

Development and Dematerialization: An International Study

Economic development and growth depend on growing levels of resource use, and result in environmental impacts from large scale resource extraction and emissions of waste. In this study, we examine the resource dependency of economic activities over the past several decades for a set of countries comprising developing, emerging and mature industrialized economies. Rather than a single universal industrial development pathway, we find a diversity of economic dependencies on material use, made evident through cluster analysis. We conduct tests for relative and absolute decoupling of the economy from material use, and compare these with similar tests for decoupling from carbon emissions, both for single countries and country groupings using panel analysis. We show that, over the longer term, emerging and developing countries tend to have significantly larger material-economic coupling than mature industrialized economies (although this effect may be enhanced by trade patterns), but that the contrary is true for short-term coupling. Moreover, we demonstrate that absolute dematerialization limits economic growth rates, while the successful industrialization of developing countries inevitably requires a strong material component. Alternative development priorities are thus urgently needed both for mature and emerging economies: reducing absolute consumption levels for the former, and avoiding the trap of resource-intensive economic and human development for the latter.     

Decoupling – shifts in ecological footprint intensity of nations in the last decade

The ecological price of economic growth is a heavily debated issue, where ideologies often neglect factual information. In this paper, through the relationship of the ecological footprint and GDP, we examine the tendencies of eco-efficiency in the first decade of the 21st century. We conclude that the average ecological footprint intensity of countries have improved significantly in the given period. In 2009, 50 percent less area was needed to produce a unit of GDP. Many countries could reach the so-called strong decoupling − these countries could increase GDP while decreasing the ecological footprint in absolute terms. We also repeated the analysis of a scientific article published in 2004. We managed to update data and identify ecologically positive tendencies. In ten years, the average of the world’s ecological footprint intensity has significantly improved, it halved all in all. We found that 90 percent of the countries started to move to the direction of sustainable development. Among the studied 131 countries, 40 experienced strong decoupling (absolute decrease of resource use), in 77 countries weak decoupling occurred (relative decrease of resource use), and there were only 14 countries, where no decoupling could be observed (relative increase of resource use).     

基于生态系统服务理论的中国绿色经济转型预测分析

着眼于中国绿色经济转型之路的科学预测与分析,借鉴传统环境负荷模型以及资源与经济脱钩理论、区位熵理论等,提出基于生态系统服务理论的有关绿色经济指标评价模型。应用该模型计算出2001—2010年全球及中国有关绿色经济指标,依照未来中国经济与社会发展规划目标,预计"十二五"末期中国经济发展中的资源消耗及环境损失成本、人均绿色GDP将分别达到3.11×1012美元、0.37×104美元,生态负荷强度、资源脱钩指数及绿色GDP的区位熵指数分别为0.38、0.66、75;2020年中国绿色GDP的区位熵指数将超越全球平均水平、2024年人均GDP将突破1万美元关口步入中等发达国家行列。计算结果表明中国生态系统压力逐年降低、资源利用效率、环境绩效与经济效益同步提高,逐渐在全球经济绿色转型过程中发挥重要作用;未来,中国仍需秉承"共同但有区别的责任"原则,处理好与其他国家的权责纷争;同时积极推进节能减排、经济结构调整工作,进一步协调好城乡之间、区域之间经济社会发展与自然资源及生态环境的关系。     

低碳经济计量模式

首先对"低碳经济"进行了讨论,进而提出了"碳循环经济"概念;对现有碳计量进行研究,提出了相应改进计算公式:碳绩效和碳经济密度。最后,对碳责任分担进行了探讨,提出了发达国家和发展中国家"责任共担、区别对待"的碳责任担负的计算模式。     

江西省能耗碳排放时空特征、脱钩关系及其驱动因素

查明碳排放时空演变成因、经济发展脱钩情形及其影响因素,对协调区域经济发展同时更好进行碳减排具有指导意义。以欠发达江西省为例,基于2002-2016年规模以上工业主要能源消费数据,用IPCC碳核算方法、Tapio脱钩模型及对数平均迪氏指数分解法（Logarithmic Mean Divisia Index,LMDI）对该域能耗碳排放时空演变特征、与经济发展脱钩关系及其驱动因素进行了分析。结果表明：（1）江西省碳排放量前期快速增长、中后期增长减缓,由2002年的6248.57×10⁴ t增加到2016年的18680.47×10⁴ t,增长率高达198.96%。碳排放强度处于前中期快速下降,后期缓慢下降的趋势,由5.604 t/万元降为0.552 t/万元。碳排放量和碳排放强度大体呈现着西北高东南低的空间分布特征。（2）2002-2009年和2009-2016年江西省经济增长与碳排放总体上呈现弱脱钩,脱钩弹性分别为0.177和0.105。2002-2009年江西省南部和北部地区脱钩情况不够理想;2009-2016年江西省除上饶市以外的东北部地区脱钩状况较差。（3）2002-2009年,能源结构对江西省碳排放脱钩有微弱的抑制作用,2009-2016年转变为微弱的促进作用,其对各地市碳排放脱钩的驱动方向有所不同。能源强度对碳排放脱钩起主导性作用,其在两个阶段的脱钩弹性分别为-0.329和-0.481。经济水平对碳排放脱钩有主要的抑制作用,在两个阶段的脱钩弹性分别为0.377和0.475。人口对碳排放脱钩具有较小的抑制作用。因此,江西省碳减排的重点在于改善能源结构与提高能效,推动新余、九江和萍乡等城市的传统工业转型升级,促进江西西北地区与东南地区城市的绿色协同发展。     

长三角城市群碳排放与城市用地增长及形态的关系

城市是一种重要的碳源,城市扩张过程中的用地面积增长和空间特征变化均会影响城市碳排放。分析1995—2015年长三角城市群碳排放重心转移,查明碳排放和城市用地增长的脱钩状态时空变化,并通过构建面板数据模型探究城市形态对碳排放的影响,得出以下结论:(1) 1995—2015年长三角城市群碳排放重心经历了西南向-西北向-东南向-西北向的转移过程,这种转移过程与其相应时期内部分城市的工业发展与产业结构调整有关;(2) 1995—2015年,长三角城市群碳排放与城市用地增长的脱钩状态存在着显著的时空异质性。研究区由以扩张负脱钩为主变化为以弱脱钩为主,2005年以后,区域之间的脱钩差异开始缩小,总体来看研究区脱钩状态趋向于同质。至2015年,近70%的城市已达到了脱钩,其中上海等城市实现了强脱钩;(3)连续完整的地块在区域内的主导程度会对城市碳排放产生负向的影响,而城市用地斑块的破碎化程度和聚集程度对碳排放有着正向的影响,且相对而言,聚集程度的正向影响更为显著。     

中国城市低碳发展水平评估方法研究

城市低碳发展水平评估对推动城市可持续发展,提高城市应对气候变化能力具有重要意义。基于低碳城市理念和内涵,构建了由6类(碳排放、经济发展、社会进步、交通、人居环境和自然环境)、13个具体指标组成的城市低碳发展评价指标体系及综合评价指数,并结合中国35个城市2010—2015年社会经济发展数据,对参评城市的低碳发展水平及趋势进行评价与分析。结果表明:多数参评城市的低碳发展水平呈现上升的趋势,其中,城市低碳发展水平最高和最低城市名单无明显变化,且深圳市在2010年和2015年均为低碳发展水平最高的城市。与2010年相比,杭州市、银川市、郑州市、石家庄市和昆明市的城市低碳发展指数相对持平,而成都市、长沙市、合肥市和大连市有所下降。城市低碳发展水平较低可能是由于城市碳排放、经济、社会、交通、人居环境和自然环境等方面之间协调发展程度不够造成的。最后,对如何提高我国城市低碳发展水平给出了对策和建议。     

The historical ecological footprint: From over-population to over-consumption

The ecological risk from over-population has been recognized since Malthus (1798). GDP growth per capita in agriculture disproved his pessimism but, since the Club of Rome and its case on Limits to Growth more recently there has been concern that there is a parallel risk from such growth in terms of ecological footprints (EF). Authors have developed a GDP/EF correlation function and calculated the ecological footprint (EF) from 10,000 B.C. till 1960, using historical statistics, with the method of backcasting (Brandes and Brooks, 2005).¹ In all major indicators growth patterns have been dominating, not only since the industrial revolution, but in the known history of mankind. From data since 1961, we calculate the correlation between GDP and the ecological footprint and have been able to determine long time data series of population, GDP, biocapacity and EF. Our findings are first: the main driver of growth and environmental degradation is not population per se, but consumption patterns and levels multiplied by the number of consumers, especially in developed economies, as the I = PAT equation recognized (Ehrlich and Holdren, 1971). In fact, as we approach to today, population, which used to be the key driver to growth and environmental degradation, becomes the least important driver, especially in the last two decades. Second: change is not incremental or linear as assumed in much mainstream economics: in line with Schumpeter's bunching and swarming and it jumps and leaps asymmetrically, as in our finding of such a leap (the 7th) between the 1930s and 1970s. Third: the dominant paradigm legitimizing growth (from the late 18th century) while already challenged by many since the Club of Rome and other reports should be revisited in terms of the concept of ‘fullness’ in the sense that while the earth in 1776 was roughly 10 per cent full, by 2008 this figure was over 150 per cent.     

Energy Efficiency and Structural Change in the Netherlands, 1980–1995

International agreement has been reached to reduce greenhouse gas emissions worldwide. One important way of decoupling CO₂ emissions from economic growth is by introducing technical measures to improve energy efficiency. In this article, we assess the influence of developments in energy efficiency and economic structure on the total primary energy consumption in the Netherlands over the period 1980– 1995. We find a distinct decoupling of the economic growth and energy consumption of 1.5% per year in the 15-year analysis period. We measure (technical) changes in energy efficiency by changes in the energy consumption per physical unit of production or activity. The aggregate rate of (technical) energy-efficiency improvement was 1.4% per year over the period 1980–1995. The use of physical production indicators makes it possible to measure energy-efficiency developments without detailed surveys at a very low level of aggregation. When we look at economic structural changes over this period, we find that (i) no substantial shift took place at the level of the economic sectors that we distinguish; (ii) the most energy intensive subsectors grew much faster than the total economy; and (iii) at the subsector level, on average, a sizable decoupling of physical production and value added occurred. We conclude that structural changes, that is, changes in the composition of the economy, did not lead to a net decrease in the energy intensity of the Netherlands over the period 1980–1995.     

Features and influencing factors of carbon emissions indicators in the perspective of residential consumption: Evidence from Beijing,China

This research establishes a residential indirect carbon emissions model through input–output structure decomposition analysis (IO-SDA) and LMDI, analyses the influencing factors affecting urban and rural residential carbon emissions indicators in Beijing through input–output tables from 2000 to 2010, and calculates the direct carbon emissions from residential consumption. As the results suggest, the total carbon emissions from residential consumption in Beijing showed volatility. Growing rural and urban differences in direct emissions, and for indirect emissions, mean that urban greatly exceeds rural in this regard. Rising per capita GDP and population, as well as intermediate demand and sectoral emissions intensity change induce growth in indirect emissions in both urban and rural settings: of which, per capita GDP contributes the most. Declining energy intensity contributes the most to emission reductions, followed by residential consumption rates, the rural to urban consumption ratio and consumption structure effects are much smaller.     

福建省行业碳排放驱动因素分解及其与经济增长脱钩关系

主要部门和重点行业的二氧化碳排放是区域碳排放的主要来源。厘清行业碳排放影响因素,分析其与区域经济增长相互关系及程度,从而推动部门和行业碳减排对于落实区域碳排放总量控制具有重要意义。本研究运用对数平均迪式指数分解法(LMDI)和Tapio脱钩模型对福建省1997—2017年13个主要碳排放行业进行碳排放驱动因素分解和脱钩分析。结果表明: 电力、热力的生产和供应业是福建省主要的碳排放行业,1997—2017年,其碳排放总量由18.89 Mt上升到120.63 Mt,增长量为101.74 Mt。有色金属冶炼及压延加工业、纺织业、黑色金属冶炼及压延加工业的碳排放增长速度最快,其年均增长率分别为18.1%、12.1%、12.1%。13个主要行业碳排放变动的驱动因素中,经济增长效应和人口规模效应是主要的正向驱动因素,能源结构效应、能源强度效应和产业结构效应的抑制作用在不断增强。从脱钩关系来看,13个主要碳排放行业的脱钩指数整体呈下降趋势。从“十一五”时期开始,部分行业开始出现不同程度的强脱钩。而在“十三五”时期,农、林、牧、渔、水利业表现为扩张负脱钩,电力、热力的生产和供应业表现为弱负脱钩。能源结构效应和能源强度效应对各行业实现脱钩的影响较大,产业结构效应的脱钩努力较小,人口规模效应未做出脱钩努力。     

贵州省碳吸收/碳排放时空变化特征及其与经济的脱钩效应

贵州省是我国喀斯特生态系统的典型分布区,生态敏感且脆弱,同时其也曾是我国的连片特困区,经济发展愿望迫切。对区域环境-经济发展状况及相互作用关系进行研究具有重要意义。研究从植被净生态系统生产力、土壤碳储量、岩溶碳通量三方面计算了贵州省陆地生态系统碳吸收,以能源燃烧排放的CO₂表征碳排放量,对区域碳吸收和碳排放的时空变化特征进行剖析,在此基础上构建环境碳负荷指数和脱钩弹性系数,用于解析贵州省碳收支状况及环境碳负荷与经济发展之间的脱钩关系。结果显示:(1)贵州省植被净生态系统生产力均值为257.72 g C/m²,呈逐步增强趋势,空间上呈现西高东低、南高北低的分布格局;岩溶碳通量的均值为6.71 t C/km²,年际波动较大,集中分布在研究区东北和西南部;土壤碳储量的均值为8.38 t/hm²,其高值区主要位于研究区南部和东部边缘;(2)区域碳排放呈现出了逐年增长的特征,表明了能源消耗的增强,形成了以城市高值区为中心向外辐射递减,各点之间以道路连通为特征的分布格局;(3)环境碳负荷指数呈逐年增长趋势,表征区域面临的环境压力越来越大,特别是在贵州省主城区出现了明显的收支不平衡,能源结构优化亟待加强;(4)综合脱钩状态整体以弱脱钩和扩张连接为主,且随时间推移脱钩状态由弱脱钩向扩张连接转变,说明环境保护滞后于经济发展,也就意味着贵州省经济的发展一定程度上牺牲了环境保护。未来应进一步强化生态修复工程的可持续性,同时发展绿色经济以促进区域生态-经济可持续发展。     

Natural and socioeconomic determinants of the embodied human appropriation of net primary production and its relation to other resource use indicators

Indicators of resource use such as material and energy flow accounts, emission data and the ecological footprint inform societies about their performance by evaluating resource use efficiency and the effectiveness of sustainability policies. The human appropriation of net primary production (HANPP) is an indicator of land-use intensity on each nation's territory used in research as well as in environmental reports. ‘Embodied HANPP’ (eHANPP) measures the HANPP anywhere on earth resulting from a nation's domestic biomass consumption. The objectives of this article are (i) to study the relation between eHANPP and other resource use indicators and (ii) to analyse socioeconomic and natural determinants of global eHANPP patterns in the year 2000. We discuss a statistical analysis of >140 countries aiming to better understand these relationships. We found that indicators of material and energy throughput, fossil-energy related CO₂ emissions as well as the ecological footprint are highly correlated with each other as well as with GDP, while eHANPP is neither correlated with other resource use indicators nor with GDP, despite a strong correlation between final biomass consumption and GDP. This can be explained by improvements in agricultural efficiency associated with GDP growth. Only about half of the variation in eHANPP can be explained by differences in national land-use systems, suggesting a considerable influence of trade on eHANPP patterns. eHANPP related with biomass trade can largely be explained by differences in natural endowment, in particular the availability of productive area. We conclude that eHANPP can deliver important complimentary information to indicators that primarily monitor socioeconomic metabolism.     

辽宁省能源消费和碳排放与经济增长的关系

在广泛收集资料的基础上,对辽宁省的能源利用效率、能源消费强度与经济增长的关系进行探索,其目的为辽宁省的节能与CO2减排及经济的快速发展提供科学依据。结果表明:辽宁整体单位GDP能耗高出全国水平52%—70%,第二产业单位GDP能耗是第三产业的5.67—8.41倍,第一产业的7.2—9.0倍;辽宁能源利用率只有全国平均水平的60%左右,第二产业能源利用效率只有第一产业的11.89%,第三产业的12.60%;GDP年增长速率大于能源消费量年增长速率,能源投入增加促进了国民生产总值的提高,但是经济增长并不是完全依赖能源消费的增长;能源消费量与经济增长的关系,呈现出"N型"曲线特征,随着GDP的增加,能源消费量出现反复上升和下降过程,辽宁省能源消费和经济增长关系没有达到长期的均衡性,尚处于非平衡的发展阶段。     

基于物质流分析方法的唐山市经济与环境关系的协整检验和分解

利用物质流分析方法(MFA)建立物质流账户,分析唐山市在经济 环境系统运行中物质投入量与产出量的阶段特征及物质投入和产出强度对经济发展的影响程度;使用计量经济学模型,分别对国内生产总值(GDP)、直接物质投入(DMI)和直接废弃物排放(DPO)进行单位根检验、Johansen协整检验、向量误差修正分析、脉冲响应和方差分解分析,探索了各指标之间的双向作用机制和长期关系.结果表明: 1992—2011年,唐山市DMI和DPO 均呈增长趋势,DMI的增幅高于DPO.DMI投入强度呈增长趋势,DPO产出强度呈波动下降趋势.GDP与DMI、DPO之间存在着长期稳定协整关系,指标间的作用关系经历了由波动到逐步平稳的过程.DMI与DPO在短期内会对经济发展起到较强的正向冲击作用,但是经济-环境系统会逐步消化这些影响,并对系统内外指标进行短期的动态调整,最终使系统表现出一种长期的均衡关系;经济发展受到经济规模效应的影响逐步增加.将各指标对GDP的贡献度予以分解,其中,DMI的贡献度上升,GDP的贡献度下降,DPO的贡献度变化不大.总体上,唐山市的经济发展遵循了资源型城市的传统生产轨迹,较大程度上依赖于物质投入,高能源消耗又加剧了环境污染.     

What are the possibilities for graphical presentation of decoupling? An example of economy-wide material flow indicators in the Czech Republic

The relationship between the environmental and economic domains has attracted researchers and politicians for at least several decades [Boulding, K., 1966. The economics of the coming spaceship earth. In: Boulding. K., et al. (Eds.), Environmental Quality in Growing Economy. Hopkins University Press, Baltimore, Marylang; Meadows, D.H., Meadows, D.L., Randers, J., Behrens, W.W., 1972. The Limits to Growth: A Report for the Club of Rome's Project on the Predicament of Mankind. Universe Books, New York; Schmidt-Bleek, F., 1994. Wieviel Umwelt Braucht der Mensch? MIPS—Das Mass für Ökologisches Wirtschaften. Birkhäuser-Verlag, Berlin, Basel, Boston]. The overall goal of sustainable economies is to reach a state where the general quality of life is growing while the environmental pressures go down [EC, 2001. A Sustainable Europe for a Better World: A European union Strategy for Sustainable Development. Commission of the European Communites, Brussels; EC, 2002. The Sixth Community Environment Action Programme. Commission of the European Communities, Brussels; EC, 2003a. 2003 Environmental Policy Review. Commission of the European Communities, Brussels; EC, 2003b. Towards a thematic strategy on the sustainable use of natural resources. Commission of the European Communities. Brussels; UN, 2002. Plan of Implementation of the World Sunnit on Sustainable Development. United Nations, New York.]. This phenomenon is called decoupling. To express decoupling, one usually aims to capture the mutual relation between an indicator of economic driving forces (most commonly Gross Domestic Product/GDP/, which is usually taken as a proxy of quality of life here) and an indicator of environmental pressure. When analysing decoupling, it is not quite clear how to proceed in terms of both selection of appropriate pressure indicators and presentation of decoupling. In this article, we focus on the issue of graphical presentation of decoupling analysis, particularly using economy-wide material flow indicators (EW-MFI) [Eurostat, 2001. Economy-Wide Material Flow Accounts And Derived Indicators: A Methodological Guide. Eurostat, Luxembourg]. One of the most commonly used methods for graphical presentation of decoupling by EW-MFI is to plot time series of indexed values of these indicators and GDP in a single chart. Here, however, it is difficult or even impossible to analyse causes of the different decoupling for particular indicators—to do this we propose to analyse time series of their components. To show the contribution of the components to the overall decoupling of an indicator, we suggest expressing the weighted share of particular components in overall indicator decoupling. For that we have tested the direct material input indicator (DMI), which is also recommended by OECD for decoupling analysis [OECD, 2002. Indicators to Measure Decoupling of Environmental Pressures from Economic Growth. OECD, Paris]. The expression of the weighted share of the indicator components in indicator decoupling has proved to be especially transparent in the case of this indicator, because the DMI belongs to the least aggregated material flow indicators. Nevertheless, the proposed method of expression can also be applied to other material flow indicators, as exemplified by the domestic material consumption indicator (DMC).     

Delinking indicators on regional industry development and carbon emissions: Beijing–Tianjin–Hebei economic band case

Based on the two-level Logarithmic Mean Divisia Index (LMDI) method and Tapio index, this paper constructed an expanded decomposition model for decoupling elasticity and effort index of industrial carbon emissions, and further quantitatively analyzed the delinking indicators on industry growth and environmental pressures in Beijing–Tianjin–Hebei (BTH) economic band from 1996 to 2010. The results indicate that: (1) together with the rapid economic growth, industrial energy-related carbon emissions in BTH region rose from 44477.43 × 10⁴ t in 1996 to 105602.33 × 10⁴ t in 2006 and then declined to 64426.71 × 10⁴ t in 2010, with an average annual growth rate of 2.94%. Our results also show that carbon emissions in BTH region were dominated by the secondary industry, which accounted for about 80% of total carbon emissions. (2) “Weak decoupling” was the main characteristic during the 9th Five-Year Plan period (1996–2000) and 11th Five-Year Plan period (2006–2010), particularly “strong decoupling” in 2007; while “weak coupling” was the main characteristic during the 10th Five-Year Plan period (2001–2005). (3) The rapid economic growth was the main factor responsible for industrial decoupling blocking. The energy structure and energy intensity made significant contributions to the industrial decoupling progress. The industrial structure effect had varied considerably over the years without showing a clear trend.