Agricultural GHG emission and calorie intake nexus among different socioeconomic households of rural eastern India

A study was conducted to examine the interrelationships among socioeconomic factors, household consumption patterns, calorie intake and greenhouse gas emissions factors in rural eastern India based on household survey data. Findings indicated that higher monthly per capita incomes (12.1–80.1$) were associated with greater average calorie intakes (2021–2525 kcal d^?1). As estimated by the FEEDME model, in total 17.2% of the population was calorie malnourished with a regional disparity of 29.4–18.2% malnourishment. Greenhouse gas (GHG) emissions were calculated only on the basis of crop and livestock production and consumption. Rice accounted for the highest share of total GHG emissions, on average 82.6% on a production basis, which varied from 58.1% to 94.9% in regional basis. Rice contributed the greatest share (~?65% and 66.2%) in terms of both calories and GHG emissions (CO₂ eq y^?1), respectively, on a consumption basis. We conclude that extensive rice farming and increasing animal product consumption are dominant factors in the higher carbon footprint in this region and are likely to further increase with increase in per capita income. This study provides useful information to help for better crop planning and for fine-tuning food access policy, to reduce carbon footprint and calorie malnutrition.

     

基于碳足迹的江西省农田生态系统碳源/汇时空差异

利用2001~2010年江西省农业投入和农作物统计数据,采用碳排放系数法计算了江西省农田生态系统碳源/汇及碳足迹,分析了江西省农田生态系统碳源/汇时空特征,并进一步分析了碳足迹变化特征及原因。结果表明：(1)2001~2010年,江西省农业投入引起的碳排放量从2001年的11910 1×106 t,增加至2010年的5872 8×106 t,增加了103倍,农业机械化对碳排放总量贡献率最大。碳排放强度呈现先增加后减少的趋势。2008年赣州市碳排放量最多,景德镇市最少;(2)2001~2010年江西省农田生态系统碳吸收量先减少,后逐年增加,到2010年又减少,整个2001~2010年间增加3209 9×106 t。各类农作物中,水稻碳吸收量最多。2009年碳吸收量最多的是宜春市,最少的是萍乡市;(3)江西省农田生态系统碳足迹从2001年的07518×106 C〖DK〗·hm-2〖DK〗·a-1,增加至2009年的1473 4×106 C〖DK〗·hm-2〖DK〗·a-1,单位面积碳足迹呈现逐年增加的趋势。2008年碳足迹最多的是赣州市,最少的是萍乡市。南昌市、景德镇市、吉安市和宜春市表现为生态盈余,其余表现为生态赤字。江西省应减少农药、化肥等的使用,控制农业机械化,特别是赣州市,从而达到减少碳排放的目的     

中国电力行业的全周期碳足迹

在碳达峰与碳中和目标下,国家层面与各省份均在积极推动碳减排。电力行业作为我国最大的排放部门成为减排重点之一,然而电力行业存在的隐含碳排放造成实际排放低估,省际间碳转移导致省级碳减排不公平问题突出。因此识别电力行业全周期碳足迹,尤其是不同省份的隐含碳足迹以及省际间的转移碳足迹特征,有助于正确评估电力行业碳排放,科学界定不同省份的碳减排责任并合理分配。通过构建电力行业全周期点-流模型以揭示电力产业链中存在的能源活动,进而明确基于用电侧考虑的2018年全周期碳足迹,并刻画碳隐含度与碳转移依赖度指标来分析电力行业的隐含碳排放与省间转移碳排放。研究表明:(1)我国电力行业全周期碳排放系数为689 g/(kW·h),排放量为4.747×10⁹t,其中北方大部分地区排放系数偏高,山东最高达891 g/(kW·h),南方地区偏低,云南最低仅101 g/(kW·h)。(2)全国电力行业全周期碳隐含度为8.95%,东南沿海贫煤省与煤炭生产高排放省的碳隐含度偏高,贵州最高达14.63%,西北、华北富煤省的碳隐含度偏低,新疆最低仅4.94%;全国隐含碳排放量为4.25×10⁸t,广东隐含碳排放量最高达5.0×10⁷t,青海最低仅1.17×10⁶t。(3)全国电力行业全周期碳转移量为9.26×10⁸t,约占排放总量的19.5%,电力与煤炭自给率越低的省区对外碳转移依赖度越高,其中北京最高达71.24%;内蒙古、山西、陕西、宁夏、安徽、新疆、贵州是主要碳转入省,总转入7.11×10⁸t,其中内蒙古最高达2.64×10⁸t;江苏、浙江、广东、山东、河北、北京、辽宁、河南、上海是主要碳转出省,总转出6.92×108t,其中江苏最高达1.12×10⁸t;全国共有240对省存在碳转移,其中有102对的转移量超过1.0×10⁶t。在研究基础上,提出相应建议推动省级电力行业公平合理低碳发展。     

Happiness and footprints: assessing the relationship between individual well-being and carbon footprints

This study investigates the nature of the empirical link between an individual’s well-being and their carbon footprint. It employs a novel approach matching data from the Household, Income and Labour Dynamics in Australia survey, to household expenditure and greenhouse gas-based carbon footprints. The carbon footprints are calculated using environmental factor multipliers from the detailed and globally integrated multi-regional input–output (MRIO) tables provided by the Eora MRIO database. The results indicate that higher carbon footprints are associated with marginally lower levels of well-being. This relationship appears to be linear. Furthermore, this relationship does not differ greatly for individuals across the well-being distribution. The findings of this study both: (1) add to the body of knowledge on the link between carbon footprints and well-being; and (2) provide policy makers with evidence and strategic guidance on the well-being implications of mitigating carbon footprints.     

畜牧业“碳排放”到“碳足迹”核算方法的研究进展

全球变暖趋势日益加剧,不仅影响农业可持续发展,而且威胁到人类生存。畜牧业碳排放因其在农业碳排放中乃至全球碳排放中占比较大而日益备受关注。准确核算畜牧业碳排放是制定切实可行的碳减排政策的前提,也为我国在气候变化下承担共同但有差别的减排责任提供话语权。本文基于研究范式的演进,对畜牧业碳排放到碳足迹核算方法的研究发展进行了系统梳理,研究表明,在学者的不断研究与质疑下,畜牧业碳排放到碳足迹的核算方法经历了从OECD核算法、IPCC系数法到生命周期法与投入-产出法的演变与完善,学术界认为区域异质性、养殖规模与管理方式均影响碳足迹;散养比规模化养殖产生更多的碳排放,舍饲比户外放牧排放更多的碳。畜牧业碳足迹核算能够更加全面地反映畜牧业全生命周期的碳排放情况,但由于研究假设、研究方法及研究样本等差异导致不同区域、不同畜产品的碳排放核算结果存在不确定性。运用生命周期法和投入-产出法对欧盟成员国畜牧业碳排放的核算结果基本一致,但运用IPCC系数法和全生命周期法对中国畜牧业碳排放核算中,牛、猪和羊的碳排放量排序结果不尽一致。鉴于核算结果的差异性,本研究对不同核算方法的起源、最早采用时间、特点、局限性等方面进行了归纳总结,并建议后续研究探讨基于生命周期评价的畜牧业碳足迹研究边界的延伸性,标准化畜牧业碳排放或碳足迹核算,避免学者重复核算畜牧业碳排放,以便深入展开畜牧业碳排放其他方面的研究。     

林产品生物碳通量的动态生命周期评估

将时间因素和生物碳通量纳入林产品生命周期碳足迹评估,通过动态生命周期分析法(Dynamic Life Cycle Assessment,DLCA),确定林产品生产、使用和废弃阶段替代化石能源的净温室气体减排和对森林碳损失的净弥补时间。首先,建立温室气体排放和封存的动态生命周期清单,评估刨花板全生命周期的碳动态和碳足迹;其次,根据ISO 14040和PAS 2050标准提供的静态生命周期分析法分别核算包含与不包含碳储计算的碳足迹,量化时间因素和生物碳通量对于碳足迹结果差异的影响程度;最后,对比自然生长状态的森林碳汇情境,评估刨花板使用和废弃阶段替代化石燃料实现净气候减排所需的时间。研究表明:①时间因素和生物碳通量核算对碳足迹结果影响较大(223.34%),忽视时间因素会低估刨花板的减排贡献(18.98%)。②动态生命周期分析法可准确评估生物碳和温室气体排放的时间问题,但对时间范围非常敏感(75.19%和113.25%)。③生产、使用林产品以及林产品对化石能源的替代是实现长期气候减排的有效方式,在100a的时间范围能够弥补因森林砍伐造成的碳损失,从而实现碳中性。     

应对气候变化的碳足迹研究综述

由温室气体引起的全球变暖问题已引起国际社会的普遍关注,随着全球变暖成为社会关注的热点,碳足迹成为一个新的研究方法并迅速得到学术界的认可。本文从碳足迹的起源和各种定义入手,系统阐述了碳足迹的概念,并从不同角度探讨了碳足迹的各种分类。本文重点介绍了碳足迹的计算方法,主要包括投入产出分析方法、生命周期评价法、IPCC计算方法和碳足迹计算器等四大类,并总结和比较了四种方法的优缺点。在此基础上,对国内外相关研究系统地进行了归纳和总结,客观分析和评价了当前碳足迹的研究现状和存在的问题。本文还介绍了目前国际上四个主要的碳足迹评估标准:英国的PAS2050:2008标准、世界可持续发展商业协会和世界资源研究院共同发起制定的GHG议定书、日本的标准仕样书TS Q0010标准和ISO14067标准,并以GHG议定书和PAS2050两个标准为例分析了进行碳足迹评估的重要前提———边界界定问题。最后对碳足迹研究的重点领域和发展方向进行了展望。     

Uncovering blind spots in urban carbon management: the role of consumption-based carbon accounting in Bristol,UK

The rapid urbanisation of the twentieth century, along with the spread of high-consumption urban lifestyles, has led to cities becoming the dominant drivers of global anthropogenic greenhouse gas emissions. Reducing these impacts is crucial, but production-based frameworks of carbon measurement and mitigation—which encompass only a limited part of cities’ carbon footprints—are much more developed and widely applied than consumption-based approaches that consider the embedded carbon effectively imported into a city. Frequently, therefore, cities are left blind to the importance of their wider consumption-related climate impacts, while at the same time left lacking effective tools to reduce them. To explore the relevance of these issues, we implement methodologies for assessing production- and consumption-based emissions at the city-level and estimate the associated emissions trajectories for Bristol, a major UK city, from 2000 to 2035. We develop mitigation scenarios targeted at reducing the former, considering potential energy, carbon and financial savings in each case. We then compare these mitigation potentials with local government ambitions and Bristol’s consumption-based emissions trajectory. Our results suggest that the city’s consumption-based emissions are three times the production-based emissions, largely due to the impacts of imported food and drink. We find that low-carbon investments of circa £3 billion could reduce production-based emissions by 25% in 2035. However, we also find that this represents <10% of Bristol’s forecast consumption-based emissions for 2035 and is approximately equal to the mitigation achievable by eliminating the city’s current levels of food waste. Such observations suggest that incorporating consumption-based emission statistics into cities’ accounting and decision-making processes could uncover largely unrecognised opportunities for mitigation that are likely to be essential for achieving deep decarbonisation.

     

Energy consumption and emission projection for the road transport sector in Malaysia: an application of the LEAP model

This study has attempted to estimate the energy consumption and emission of pollutants namely carbon dioxide (CO₂), carbon monoxide (CO), nitrogen oxides (NOx) and non-methane volatile organic compounds (NMVOC) from the road transport sector in Malaysia from the year 2012 till 2040. This was done using the long-range energy alternatives planning (LEAP) model. Estimates of energy consumption and emissions were evaluated and analysed under a business-as-usual scenario and three other alternative fuel policy scenarios of biodiesel vehicles (BIO), natural gas vehicles (NGV) and hybrid electric vehicles (HEV). The aim of this study has been to identify the potential alternative fuel policies that would be effective in reducing the future growth of road transport energy consumption and emission in Malaysia. Results indicate that the NGV scenario contributes towards the highest reduction in road transport energy consumption followed by BIO and HEV. The NGV scenario also achieves highest mitigation of emission of all the four pollutants. In the case of CO₂ emission, BIO scenario attains second highest mitigation, whereas in the event of CO, NOx and NMVOC emission, HEV scenario achieves second highest mitigation.     

江阴市近5年生态足迹计算与分析

生态足迹理论是通过跟踪区域的资源和能源消费,将它们转化为提供这种物质流所必须的生物生产性土地面积,并与生态承载力进行比较,以此衡量区域可持续发展状态。利用生态足迹理论,计算了江阴市1997～2001年5年间的生态足迹变化过程。结果表明,江阴市的人均生态足迹供给约为0.30 hm2·cap-1,而人均生态足迹消费从1997年的1.65 hm2·cap-1提高到2001年的2.04 hm2·cap-1,生态压力不断增大,生态赤字显著提高。对江阴市生态足迹构成进行分析,因素贡献大小依次排列为：化石能源>耕地>牧草地>水域>建筑用地>林地。化石能源消费的份额最大,超过50％,与江阴市高强度的经济活动有关;与此同时,食物生产消费也占较大份额。5年间单位GDP的生态足迹呈下降趋势,表明江阴市的资源利用效率明显提高。     

武汉市劳动力转移的环境效应分析

改革开放以来,农村劳动力被大量释放到城市,这部分劳动力在促进国民经济快速发展的同时,也对城市的生态环境产生了一定的影响。尤其是在城市常住人口不断增加、污染日益恶化的发展背景下,从劳动力转移的视角分析其生态环境效应具有重要价值和现实意义。通过利用武汉市转移人口调查数据,采用碳足迹分析方法从生产和消费两个方面研究外来劳动力对武汉市的环境影响,并进一步探究劳动力迁入前后的碳足迹差异及影响因素。结果表明,外来劳动力对武汉市的环境压力为1 768.53万t碳足迹,其中消费碳足迹194.72万t,生产碳足迹1 573.81万t;与迁入前相比,分别增加了45.58和1 439.41万t碳当量。这种碳足迹差异主要受到劳动力性别、年龄、非农工作时间和技术水平的影响,其中性别和年龄与碳足迹差异具有显著的负相关关系,而非农工作时间和技术水平具有正向影响。此外,劳动合同的签订及与当地居民语言交流的困难程度也增加了转移前后的碳足迹差异。     

基于LMDI的珠三角能源碳足迹因素分解

如何控制区域碳排放增长是当前全球关注的热点。分解各因素对碳足迹的作用及影响权重,找出其主导因素,对推动碳减排开展有积极意义。本文结合IPCC碳排放因子,计算出1998-2009年珠江三角洲能源碳足迹,然后基于Kaya恒等式,运用LMDI对珠三角能源碳足迹进行因素分解。结果表明:珠三角能源碳足迹从1998年11272万吨上升到2009年的24905万吨,总体呈现快速增长趋势;经济规模的扩大是珠三角碳足迹快速增长的主要推动力,经济效应受经济规模、国家政策与国际金融环境影响;人口增长对珠三角碳足迹的增长也起到推动作用;能源效率的提高,是抑制珠三角碳足迹增长的最重要因素;研究期间珠三角能源结构变化不大,导致能源结构效应的作用表现并不显著;发展低碳产业、提高能源效率是抑制珠三角能源碳足迹快速增长的主要手段,适度控制经济及人口规模也是必须的。     

A happiness Kuznets curve? Using model-based cluster analysis to group countries based on happiness,development, income,and carbon emissions

This exploratory study uses model-based cluster analysis to group sixty-one countries based on statistical similarities in terms of happiness, development, income, and carbon emissions. Model-based cluster analysis is appropriate for an initial identification of a pattern that is worthy of further investigation. A key finding is that there may be a Kuznets curve for happiness. The Kuznets curve graphs the proposition that, as an economy develops, economic inequality first increases and then decreases. Similarly, the authors find that clusters of countries at the extremes of the lowest and highest average levels of development and income have the highest self-reported levels of happiness. Clusters of countries in the middle of the development and income spectrum have the comparatively lowest average levels of happiness. Further, carbon emissions are not perfectly associated with happiness. For example, between two clusters with the highest average levels of development, income, and happiness there is a 43 % difference in carbon emissions. A highly developed cluster has roughly the same mean carbon emissions as a cluster with 83 % less income, and the least developed cluster has 93 % of the happiness as the most developed cluster yet 86 % less carbon emissions. Despite limitations of both data and methodology, the overall pattern—that there may be a happiness Kuznets curve and that development, income, and carbon emissions are not associated lockstep with happiness—contributes to the literature on decoupling development from growth in emissions.     

城乡居民食物碳消费变化与差异分析——以安徽省为例

经济的快速发展和居民人口的不断增长,给社会和生态环境带来了巨大压力,不可持续的居民食物碳消费是造成全球环境问题的重要原因之一。居民食物碳消费是环境碳循环研究和可持续消费的重要内容。采用政府宏观统计数据,研究了1985~2007年安徽省城乡居民食物碳消费结构和食物碳消费的变化趋势和影响因素,并对城乡差异进行了分析比较,结果表明：(1)城市居民家庭食物碳消费结构转变较农村显著,城市居民食物碳消费从以“粮食碳消费为主”的比较单一的消费模式转变为以“粮食、肉类、食用植物油碳消费为主”的多元消费模式;而农村居民食物碳消费从以“粮食碳消费为主”转变为以“粮食、食用植物油碳消费为主”的多元消费模式;(2)城市居民人均、户均食物碳消费量均呈下降趋势,但食物消费总量却呈上升趋势,加剧了食物碳消费的环境影响;农村人均和户均食物碳消费和碳消费总量呈下降趋势,但人均、户均食物碳消费仍高于城市,农村居民食物碳消费的生态压力依然较大。(3)Pearson乘积相关分析表明,影响城市居民人均食物碳消费的主要因素是恩格尔系数和人均可支配收入,而影响农村居民人均食物碳消费的主要因素是农村人均纯收入。研究结果对进一步探索可持续的居民消费模式和减轻环境影响具有重要的现实意义。
     

碳税对区域能源消费、经济增长和收入分配影响实证研究

碳税对区域能源消费、经济增长和收入分配影响的研究尚属空白,分别采用面板数据模型的方法和面板分位数回归模型结合对应分析的方法,对这些效应进行实证研究,发现后者能够明显的揭示出我国碳税政策效应的差异性。研究表明：除大西北地区外,碳税对区域能源消费和经济增长都具有显著的抑制效应,且效应由西至东逐渐增强;碳税在各区域都导致资本要素在总收入中的分配比例增加,劳动要素的分配份额降低,但该效应在大西北地区较弱。因此,制定我国碳税政策除了借鉴以碳税效应产业差异为导向的“欧洲经验”以外,还应该注意区域差异,对中西部地区相对倾斜的区域差异性碳税政策可以在控制碳排放的同时促进区域间经济协调发展     

不同返还情景下碳税对中国经济影响及减排效果——基于动态CGE的模拟分析

本文构建了多部门递归动态可计算一般均衡模型,考虑中国经济发展和碳减排的现实情况,以征收40元/吨碳税且无税收返还为基准情景,分析了碳税对中国经济和碳强度的影响;在此基础上,本文探讨六种税收返还情景(返还清洁能源部门部分碳税、返还服务业部分碳税、返还农村和城镇居民全部碳税、减免企业所得税、减免居民所得税、减免生产税)对碳税负效应的缓解作用,同时探讨税收返还政策下碳税对中国经济增长、社会福利、农村和城镇居民收入消费、各部门产出的影响差异,并从实现2020年和2030年减排目标的角度,比较不同返还情景下碳税对碳排放量、碳强度,以及对非化石能源占一次能源消费结构变化的长期影响。研究结果表明:基准情景下,碳税对经济确实存在负效应;六种返还政策均不同程度地降低碳税负效应,同时也能够保证实现2020年的减排目标且有利于实现2030年的目标;对单一部门(清洁能源部门或服务业)部分返还碳税能够促进相应部门的产出,但力度较小,与其他政策相比影响微弱,但都能够有效地促进这两大部门的发展,因此在制定补贴政策时应当考虑行业差异性,重点扶持符合绿色发展要求的行业;对农村和城镇居民的直接返还均能增加农村和城镇居民收入,刺激了消费进而带动社会经济发展,相比部门返还政策,这一政策更为有效的提高了社会福利,但也会进一步拉大农村与城镇居民之间的收入消费差距;减免企业所得税促进企业投资和产业结构调整;减免居民所得税极大的刺激居民消费;减免生产税促进进口、拉动就业率,降低化石能源部门产出,综合来看,相对于其他返还政策,减免生产税更有效可行。     

长三角地区城市居民出行交通碳排放特征与影响机理

随着能源问题及全球变化关注,城市居民出行交通碳排放研究已成为多学科关注焦点。选择南京、宁波和常州作为长三角典型城市,基于典型居住小区问卷调查获取第一手的城市居民出行基础数据,估算与分析城市居民出行碳排放特征及影响机理。结果表明：长三角2010年城市居民人均出行交通碳排放约1 1219 kg CO2/人,日常通勤和远距离出行碳排放量之比为75[DK]∶25;城市居民日常通勤交通碳排放的主要影响因子为交通方式、出行距离、家庭年收入、年龄和性别;远距离出行交通碳排放的主要影响因子为出行距离、交通方式和家庭年收入。建议采用差别化的行政干预和经济杠杆有效调控家庭小汽车保有量增长速度,鼓励小排量汽车和清洁能源汽车消费,兼顾汽车产业发展、家庭小汽车刚性需求与节能减排需求之间的博弈平衡;优化城市功能格局,大力发展公共交通网络;加强节能减排与低碳意识宣传,鼓励与引导公共交通出行     

Spatial and temporal variation of energy carbon emissions in Yantai from 2001 to 2011

In order to understand the characteristics of spatial and temporal variation, as well as provide effective ideas on carbon emissions and regulatory policy in Yantai, this article analyzed spatial and temporal variation of carbon emissions in Yantai based on energy consumption statistics for a variety of energy sorts together with industrial sectors from 2001 to 2011. The results were as following: First of all, Yantai’s carbon emissions grew by an average of 5.5% per year during the last 10 years, and there was a peak of 10.48 million carbon in the year of 2011. Second, compared with the gross domestic product (GDP) growth rate, the figures for energy carbon emissions growth rate were smaller; however the problem of carbon emissions were still more obvious. Furthermore, carbon emissions in Yantai increased rapidly before 2008; while after 2008, it increased more slowly and gradually become stable. Third, the energy consumption was different among regions in Yantai. For instance, the energy consumption in Longkou city was the largest, which occupied 50% of the total carbon emissions in Yantai; and the energy consumption in Chang Island was generally less than 1% of the Longkou consumption. Finally, there were relative close relationships among the spatial difference of carbon emissions, regional resources endowment, economic development, industrial structure, and energy efficiency.     

城镇居民生活能耗与碳排放动态特征分析

居民家庭生活能源消费与碳排放越来越不容忽视,开展这方面研究对于促进居民可持续消费、寻找新的节能减排途径都具有十分重要的意义.本文在考察量化1999-2007年中国城镇居民生活直接、间接能源消费及其碳排放连续变化的基础上,探究了这段时期生活能耗与碳排放的动态变化特征,并分析其潜在的影响因素.研究主要结论包括:1999-2007年,中国城镇居民人均生活总能耗和碳排总量都呈现出逐年增加趋势,其中间接能耗与碳排始终大于直接能耗与碳排,但二者的差异正在逐年缩小;对于人均直接能耗与碳排来说,二者总量都呈逐年增加趋势,其中电力和煤炭是最主要的直接能源消费品种,也是最主要的碳排来源;对于人均间接能耗与碳排来说,虽然居民生活消费开支逐年递增,但由于各类消费项的单位产值能源强度在逐年下降,因此总的间接能耗与碳排并没呈现出一定的递增或递减趋势,而是出现波动性变化.其中"食品"、"教育文化娱乐服务"和"居住"3项是居民生活间接能耗与碳排的主要来源;人均住宅建筑面积是居民生活碳排变化的主要影晌因子.研究结论为引导可持续的家庭消费模式和节能减排措施的制定提供管理启示与科学依据.     

无锡市能源消费、碳排放与经济增长关系分析

经济增长对资源消耗存在很大的依赖性,研究能源消费、碳排放与经济增长关系,可为经济增长方式转变和低碳城市建设提供重要科学依据。基于IPCC国家温室气体排放清单指南中的方法估算了无锡市能源消费碳排放,并建立“脱钩”模型探讨能源消费、碳排放与经济增长之间的关系。结果表明：（1）2000~2010年,无锡市碳排放从84335万t增加到2 52804万t,总量不断增加,但趋势有所减缓,且各县市碳排放特征差异显著;（2）无锡市碳排放与经济增长整体处于弱脱钩状态,且脱钩状态有不断增强的趋势,市区经济发展已不依赖于能源消费,朝着环境友好方向发展,江阴和宜兴节能减排压力仍然很大;（3）优化产业结构、调整工业结构和提高能源利用效率是改善无锡市能源消费、碳排放和经济增长关系的有效途径,各县市根据具体情况,侧重点有所不同