Examining the impact factors of urban residential energy consumption and CO2 emissions in China – Evidence from city-level data

Rapid urbanization has exerted substantial pressure on China’s energy system and contributed to climate change. To find the key drivers of urban residential energy consumption and CO₂ emissions, this paper uses an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that employs city-level data to examine the influences of population scale, income level, population compactness and price on house-based residential energy consumption, energy-related CO₂ emissions and private vehicle ownership. The empirical results indicate that factors such as population scale, affluence, and population compactness can lead to increases in residential energy consumption and CO₂ emissions. In terms of transportation, income and population scale positively drive the growth of private vehicle ownership, while the fuel price negatively influences private vehicle ownership. Moreover, population scale is the most important factor in residential energy consumption and CO₂ emissions. Finally, policy recommendations are suggested for China’s urban development strategy and urban design and to encourage technology innovations that reduce residential energy consumption and CO₂ emissions.     

Environmental Kuznets curve for CO2 emissions in China: A spatial panel data approach

Different from previous studies which mainly focused on conventional estimation techniques, this paper examines the CO₂ EKC hypothesis of China using a spatial panel data model to avoid the coefficient estimation error covering the period of 1997–2012. Furthermore, a comparative analysis of the turning points between the non-spatial panel model and spatial panel model is conducted. The results show that the relationship between economic growth and CO₂ emissions shapes as an inverted-N trajectory. Spatial spillovers effects are confirmed to affect the shape of the CO₂ environmental Kuznets curve. There exists an apparent block distribution in spatial structure of China's provincial CO₂ emissions. Specifically, CO₂ emissions have a relatively sharp increase from the eastern regions to the central and the western regions of China. It has also been found that urbanization and coal combustion are main factors on increasing CO₂ emissions. While the trade openness contributes to slight decrease in CO₂ emissions. The government should make targeted carbon-reduction policies for CO₂ emission reduction.     

Quantifying the relationship between urban development intensity and carbon dioxide emissions using a panel data analysis

As a factor associated with urban management and planning, urban development intensity (UDI) could in fact form the basis for a new rationale in coordinating urban sustainable development and reducing CO₂ emissions. However, existing literature engaging in the task of quantifying the impacts of urban development intensity on CO₂ emissions is limited. Therefore, the goal of this study is to quantify the relationship between urban development intensity and CO₂ emissions for a panel made up of the five major cities in China (Beijing, Shanghai, Tianjin, Chongqing and Guangzhou) using time series data from 1995 to 2011. Firstly, this study calculated CO₂ emissions for the five selected cities and presented a comprehensive index system for the assessment of the level of urban development intensity based on six aspects (land-use intensity, economic intensity, population intensity, infrastructure intensity, public service intensity and eco-environmental intensity) using locally important socioeconomic variables. Panel data analysis was subsequently utilised in order to quantify the relationships between urban development intensity and CO₂ emissions. The empirical results of the study indicate that factors such as land-use intensity, economic intensity, population intensity, infrastructure intensity and public service intensity exert a positive influence on CO₂ emissions. Further, the estimated coefficients suggest that land-use intensity is the most important factor in relation to CO₂ emissions. Conversely, eco-environmental intensity was identified as having a major inhibitory effect on CO₂ emission levels. The findings of this study hold important implications for both academics and practitioners, indicating that, on the path towards developing low-carbon cities in China, the effects of urban development intensity must be taken into consideration.     

CO2 emissions and urbanization correlation in China based on threshold analysis

Urbanization and CO₂ emissions trends are driven by worldwide economic development. Studies indicate a direct correlation between urbanization and CO₂ emissions increases with both stimulating and inhibiting factors exhibited in the urbanization process and with periodic and regional characteristics exhibited with CO₂ emission. The relationship between urbanization and CO₂ emissions specifically in China from 1979 to 2013 is researched in this paper The novel points of this paper lies in utilizing a threshold mode to test periodic characteristics and analysis by regions. Results verify the effect of urbanization on CO₂ emissions as: (1) emissions increase when threshold point 0.43 was surpassed; (2) emissions increase as residential income increases; (3) coefficients of urbanization on emissions increase initially and then decrease as a factor of increasing industry percentage in overall GDP; (4) patterns of threshold points vary geographically.     

Impacts of energy-related CO2 emissions: Evidence from under developed,developing and highly developed regions in China

A large accumulation of carbon dioxide and other greenhouse gases have caused great concern around the world. A great deal of general literature focus on the impact factors of CO₂ emissions at the national, regional and city levels. However, there is little specific guidance on regional difference in CO₂ emissions. In this paper, 30 provincial-level administrative units of China are divided into three different levels of economic development regions according to the GDP per capita from 1997 to 2012. A STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model is used to examine the impact factors on energy-related CO₂ emissions, including population, economic level, technology level, urbanization level, industrialization level and foreign trade degree. The results indicate that the effect of energy intensity is the greatest in highly developed region. Nevertheless, the impact of urbanization, industry structure and foreign trade degree in under developed region is higher than the other two regions. Population and GDP per capita have greater effect on carbon emissions in developing region than the others. Finally, differentiated measures for CO₂ reductions should be adopted according to local conditions of different regions.     

中国电力行业CO2减排潜力及其贡献因素

电力行业低碳转型是中国低碳经济转型进程中关键行业之一,如何科学分析电力行业的碳减排潜力,确定操作性强的低碳转型路线、提出有效的政策措施是中国政府亟待解决的焦点问题之一。考虑终端电力消费、低碳能源发电占比、火力发电结构、火力发电效率、线损率等因素,构建了自底向上的电力行业CO2排放核算模型,在此基础上,利用情景分析方法探索中国电力行业2015和2020年的CO2减排潜力,进一步利用对数平均权重分解法(LMDI,Logarithmic Mean weight Divisia Index method)对电力行业CO2减排影响因素的贡献度做了归因分析。结果显示,相比基准情景,在当前政策情景和低碳政策情景下,电力行业将分别带来27.0亿t和36.9亿t的CO2减排量。低碳能源发电和火力发电效率是未来对CO2减排最重要的两个贡献因素。终端电力消费量一直是促进电力行业CO2排放增长最重要的贡献因素,因此通过电力需求侧管理等手段控制电力消费量对电力行业的低碳发展至关重要。最后结合减排贡献因素分析的结果为中国电力行业低碳发展提出了相应的政策建议。     

共享社会经济路径下中国2020—2100年碳排放预测研究

碳排放和减碳经济代价研究日益受到学术界和决策者的关注，中国政府做出的关于争取在2060年前实现碳中和的表态引起了国际社会的热议。在此背景下，开展中国未来长时间序列碳排放的情景预测具有切实意义。基于可拓展的随机性环境影响评估模型（STIRPAT）评估了人口、经济和受教育程度对碳排放的影响，对比历史数据并验证了碳排放预测模型的准确性，结合共享社会经济路径（SSPs）情景的设定和模型参数，预测了5种情景下中国2020年至2100年的碳排放轨迹及经济代价。结果表明：（1）考虑碳排放达峰目标的实现，SSP3情景是中国未来发展的最佳情景，在此情景下，中国有望提前三年实现碳排放达峰目标；（2） SSP3情景可使中国年度总碳排放量和人均碳排放量处于相对其他四种情景的最低值，但需要付出累积GDP下降5.49%至8.80%的代价；（3）为完成在2060年前实现碳中和的承诺，中国政府在未来的40年需面对409.36-467.42 Gt的碳中和量；（4）2020年中国的碳排放强度将会较2005年水平下降40.52%至41.39%，2030年碳排放强度将会较2005年水平下降59.64%至60.75%。5种情境中，SSP5情景是降低碳排放强度的最佳情景，可最大程度地超额实现碳排放强度目标。未来，受经济发展、人口增长等重要因素影响，中国政府减碳压力将进一步加大。后疫情时代，考虑到能源供应的减少和高科技产业的发展，碳排放社会成本的上升将为中国创造一个使能源系统脱碳的机遇。中国应在"十四五"期间继续提升能源利用效率、升级产业结构、提倡低碳消费、实施隐含碳战略，以尽快实现碳减排目标。     

Panel estimation for the impacts of population-related factors on CO2 emissions: A regional analysis in China

A large accumulation of carbon dioxide emission have attracted much attention recently. The existing researches mainly focused on such impact factors of carbon dioxide emission as population, economy, technology and others. However, there is little specific guidance for the subdivision of demographic factors. This paper employed STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model to examine the impact of population size, per capita consumption, energy intensity, urbanization and aging population on CO₂ emissions by adopting panel data of 30 provinces from 1997 to 2012. Taking the climate change as a control variable, we can get the result that the population size, per capita consumption and energy intensity have strong explanatory power on CO₂ emissions in the three regions. The urbanization level has a positive influence on carbon emissions in the western region and has a negative effect in the central region, while it is not statistically significant in the eastern region. Aging population increases emissions in the eastern region, while decreases emissions in the central region and the western region.     

Economic growth,electricity consumption,urbanization and environmental degradation relationship in United Arab Emirates

The present study explores the relationship between economic growth, electricity consumption, urbanization and environmental degradation in case of United Arab Emirates (UAE). The study covers the quarter frequency data over the period of 1975–2011. We have applied the ARDL bounds testing approach to examine the long run relationship between the variables in the presence of structural breaks. The VECM Granger causality is applied to investigate the direction of causal relationship between the variables. Our empirical exercise reported the existence of cointegration among the series. Further, we found an inverted U-shaped relationship between economic growth and CO₂ emissions i.e. economic growth raises energy emissions initially and declines it after a threshold point of income per capita (EKC exists). Electricity consumption declines CO₂ emissions. The relationship between urbanization and CO₂ emissions is positive. Exports seem to improve the environmental quality by lowering CO₂ emissions. The causality analysis validates the feedback effect between CO₂ emissions and electricity consumption. Economic growth and urbanization Granger cause CO₂ emissions.     

Does energy intensity contribute to CO2 emissions? A trivariate analysis in selected African countries

The present study investigates the dynamic relationship between energy intensity and CO₂ emissions by incorporating economic growth in environment CO₂ emissions function using data of Sub Saharan African countries. For this purpose, we applied panel cointegration to examine the long run relationship between the series. We employed the VECM Granger causality to test the direction of causality amid the variables.At panel level, our results validate the existence of cointegration among the series. The long run panel results show that energy intensity has positive and statistically significant impact on CO₂ emissions. There is also positive and negative link of non-linear and linear terms of real GDP per capita with CO₂ emissions supporting the presence of environmental Kuznets curve (EKC). The causality analysis reveals the bidirectional causality between economic growth and CO₂ emissions while energy intensity Granger causes economic growth and hence CO₂ emissions, while across the individual countries, the results differ. This paper opens up new insights for policy makers to design comprehensive economic, energy and environmental policy for sustainable long run economic growth.     

Scenario Analysis and Path Selection of Low-Carbon Transformation in China Based on a Modified IPAT Model

This paper presents a forecast and analysis of population, economic development, energy consumption and CO₂ emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO₂ emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40–45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China’s low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China''s development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance.     

Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas

Urban areas consume more than 66% of the world’s energy and generate more than 70% of global greenhouse gas emissions. With the world’s population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO₂) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO₂ emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999–2008, CO₂ emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.     

我国典型城市化石能源消费CO2排放及其影响因素比较研究

城市是化石能源消费和CO_2排放的主要区域。分析典型城市化石能源消费CO_2排放特征,明确不同城市CO_2排放动态及主要影响因素的差异,是开展城市减排行动的重要科学依据。采用IPCC推荐方法及中国的排放参数核算11个典型城市2006—2015年间化石能源消费产生的CO_2排放量。根据各城市经济发展和CO_2排放特征将之分为四类:经济高度发达城市(北京、上海、广州)、高碳排放城市(重庆、乌鲁木齐、唐山)、低排放低增长城市(哈尔滨、呼和浩特和大庆)和低排放高增长城市(贵阳、合肥),并运用对数平均迪氏指数法(Logarithmic Mean Divisia Index,即LMDI分解法)对比分析了四类城市CO_2排放量的影响因素。结果表明:(1)研究期内大部分城市CO_2排放总量有所增加,仅北京和广州呈下降趋势,工业部门CO_2排放在城市排放总量及其变化中占据主导地位;四类城市的人均CO_2排放量表现出与排放总量相似的变化趋势;CO_2排放强度整体上表现为经济高度发达城市(均值为0.88 t CO_2/万元)低排放低增长城市(均值为2.82 t CO_2/万元)低排放高增长城市(均值为3.05 t CO_2/万元)高碳排放城市(均值为6.62 t CO_2/万元)。(2)在城市CO_2排放的影响因素中,经济发展和人口规模均是4类城市CO_2排放增长的促进因素,但经济发展效应的累积贡献值大于人口规模效应;能源强度降低是4类城市CO_2排放最主要的抑制因素,且经济高度发达和高碳排放城市的抑制作用强于其他两类城市;对第三产业GDP年平均增速高于第二产业的6个城市来说,产业结构是CO_2排放的抑制因素;能源结构的变化仅对煤炭消费比重较低且降幅较大的北京和广州的CO_2排放是抑制作用,累积贡献值分别为-21.73Mt和-0.03Mt,而对其他城市,特别是高碳排放城市的CO_2排放具有明显的促进作用。     

Evaluating the reduction in green house gas emissions achieved by the implementation of the household appliance recycling in Japan

Background, Aim and Scope The Home Appliance Recycling Law (hereunder referred to as the Law) for used cathode ray tube (CRT) TVs, air conditioners, refrigerators and washing machines was enacted in April 2001 in Japan. The Law requires that retailers reclaim, and manufacturers and importers recycle such home appliances. Consumers are required to pay collection and recycling fees incurred in disposing of any of the four home appliances. Home appliances must, as a general rule, be managed in accordance with the Law. In reality, other routes exist, such as via local authorities, scrap processors, illegal dumping and exporting. At about the time the Law was enacted, the refrigerant used for air conditioners and refrigerators was replaced by more environmentally friendly substances such as isobutene. Local authorities had the responsibility of disposing of the appliances of households before the enactment of the Law. It was general practice for local authorities to dispose of home appliances in landfills after breaking them up and recovering valuable resources such as iron, copper and aluminum. Although they made efforts to recover refrigerant fluorocarbons, there were not required to do so. Materials and Methods This study analyzed the material flow resulting from the Law and other processing flows to quantify the global warming effect caused by home appliance recycling using the life cycle assessment (LCA) method. To evaluate the Law and to develop policy planning, the challenges of future efforts will be considered using time series data. For these reasons, we have assessed the Project Scenario, which corresponded to the present reality; the Baseline Scenario, which assumed that measures such as the Law were not implemented after 2000, and the Ideal Scenario, where all used products were recycled as prescribed by the Law. The environmental impacts for each scenario were estimated using value, which was obtained from multiplying the amount of reproduction and waste treatment by each inventory data. Results It is estimated that emission reductions of 4.7E+4 t CO₂e, subtracted the Project Scenario from the Baseline Scenario, were reduced for TVs in 2001 through recycling. The impact from recycling glass from cathode ray tube (CRT) televisions is significant. An improvement of 2.3E+4 t CO₂e could be anticipated by upgrading to the Ideal Scenario in 2001. It was estimated that there was a reduction of 9.2E+5 t CO₂e in 2001 for air conditioners. Although the effect of the recovery for refrigerants contributed greatly, some fluorocarbons that are still discharged have had a considerable impact on greenhouse gas emissions. Hypothetically, a reduction of 3.2E+6 t CO₂e could be anticipated with the Ideal Scenario in 2001. A reduction of 2.6E+6 t CO₂e was achieved for refrigerators in 2001. Although a further reduction can be anticipated through the Ideal Scenario, there will not be much difference with the Project Scenario by 2010. It was estimated that 3.8E+4 t CO₂e were reduced for washing machines in 2001. Only a small improvement can be expected through the Ideal Scenario. Discussion Since many assumptions were used in this study, a sensitivity analysis was carried out in order to grasp their impact. The findings of the sensitivity analysis are that the uncertainties are large, but the number of the greenhouse gas (GHG) reductions is still clear except for the difference between the Project Scenario and the Ideal Scenario for TVs. This analysis gives authenticity to the findings. Conclusions Establishing a system for liquid crystal display and plasma display panel TVs is desirable because the absolute amount of used LCD/PDP TVs will rapidly increase as the usage of CRT TVs rapidly decreases from 2007. With regard to refrigerant recovery from air conditioners, a significant decrease in GHG emissions has been recorded. There is, however, still ample room for improvement. It will be necessary to switch to refrigerants with low global warming potentials (GWPs) or work more on improving the recovery rate in the future. Alternatives and recovery of fluorocarbons from refrigerators contributed greatly to GHG reductions. The GHG emissions from refrigerator recycling will be minimal whether used refrigerator will be processed legally or not because most used refrigerators will contain natural refrigerants in the near future. The improvement for washing machines was low because it was assumed that their main constituent steel has been previously recycled, and that the plastic recycling rate will not change significantly in the future. An improvement in the recycling technology itself is required. This study was carried out on four home appliance products, and it was found that the Home Appliance Recycling Law has brought significant reductions in GHG emissions. There is also room to make GHG reductions through improving the processing methods further. Recommendations and Perspectives The impact on GHG emissions by fluorocarbons of air conditioners and refrigerators is the greatest. Adequate measures are particularly required for air conditioners that may continue to discharge GHGs in the future. ESS-Submission Editor: Dr. Lindita Bushi (lindita.bushi@ghgm.com)     

Emission scenario of non-CO2 gases from energy activities and other sources in China

This paper gives a quantitative analysis on the non-CO₂ emissions related to energy demand, energy activities and land use change of six scenarios with different development pattern in 2030 and 2050 based on IPAC emission model. The various mitigation technologies and policies are assessed to understand the corresponding non-CO₂ emission reduction effect. The research shows that the future non-CO₂ emissions of China will grow along with increasing energy demand, in which thermal power and transportation will be the major emission and mitigation sectors. During the cause of future social and economic development, the control and mitigation of non-CO₂ emissions is a problem as challenging and pressing as that of CO₂ emissions. This study indicates that the energy efficiency improvement, renewable energy, advanced nuclear power generation, fuel cell, coal-fired combined cycle, clean coal and motor vehicle emission control technologies will contribute to non-CO₂ emissions control and mitigation.

     

中国能源消费碳排放的时空特征

选择联合国政府间气候变化专门委员会(IPCC)的部门方法和8大类能源,采用1990年至2009年的中国能源统计数据,按照自下而上的思路,对我国各省区的碳排放量进行估算,并从碳排放量、碳排放强度、人均碳排放量和碳排放密指标出发,深入分析了各省区碳排放的时空特征差异。以期对国内碳排放的时空特征分析,有助于决策者和能源分析家提高节能减排政策制定的有效性。     

Emission scenario of non-CO2 gases from energy activities and other sources in China

This paper gives a quantitative analysis on the non-CO₂ emissions related to energy demand, energy activities and land use change of six scenarios with different development pattern in 2030 and 2050 based on IPAC emission model. The various mitigation technologies and policies are assessed to understand the corresponding non-CO₂ emission reduction effect. The research shows that the future non-CO₂ emissions of China will grow along with increasing energy demand, in which thermal power and transportation will be the major emission and mitigation sectors. During the cause of future social and economic development, the control and mitigation of non-CO₂ emissions is a problem as challenging and pressing as that of CO₂ emissions. This study indicates that the energy efficiency improvement, renewable energy, advanced nuclear power generation, fuel cell, coal-fired combined cycle, clean coal and motor vehicle emission control technologies will contribute to non-CO₂ emissions control and mitigation.     

A dynamic analysis of air pollution emissions in China: Evidence from nonparametric additive regression models

PM_2.5 emissions not only have serious adverse health effects, but also impede transportation activities, especially in air and highway transport. As a result, PM_2.5 emissions have become a public policy concern in China in recent years. Currently, the vast majority of existing researches on PM_2.5 are based on natural science perspective. Very few economic studies on the subject have been conducted with linear models. This paper adopts provincial panel data from 2001 to 2012, and uses the STIRPAT model and nonparametric additive regression models to examine the key driving forces of PM_2.5 emissions in China. The results show that the nonlinear effect of economic growth on PM_2.5 emissions is consistent with the Environmental Kuznets Curve (EKC) hypothesis. The nonlinear impact of urbanization exhibits an inverted “U-shaped” pattern due to the rapid development of urban real estate in the early stages and the strengthening of environmental protection measures in the latter stage. Coal consumption follows an inverted “U-shaped” relationship with PM_2.5 emissions owing to massive coal consumption at the beginning and efforts to optimize the energy structure as well as technological progress in clean energy in the latter stages. The nonlinear inverted “U-shaped” impact of private vehicles may be due to the different roles of scale, structural and technical effects at different stages. However, energy efficiency improvement follows a positive “U-shaped” pattern in relation to PM_2.5 emissions because of differences in the scale of the economy and the speed of technological progress at different times. As a result, the differential dynamic effects of the driving forces of PM_2.5 emissions at different times should be taken into consideration when initiating policies to reduce PM_2.5 emissions in China.     

CO2 emissions from the Chinese cement sector: Analysis from both the supply and demand sides

China is the largest producer and consumer of cement worldwide, and cement production entails the release of substantial carbon dioxide (CO₂) emissions. As the cement sector is a crucial sector of the Chinese economy, understanding the role of supply‐ and demand‐side factors may help accelerate efforts to mitigate CO₂ emissions. However, few studies have analyzed the critical factors affecting CO₂ emissions in the sector based on a combined supply‐ and demand‐side perspective. In this study, we developed an integrated framework that included eleven indicators covering both the supply and demand sides. Results revealed that improving cement production technology cannot offset CO₂ emissions from the growth in demand for cement. Improving technology on the supply side would considerably reduce CO₂ emissions from Chinese cement production; nevertheless, the combination of rapid urbanization, GDP growth, and an ultra‐high fixed capital formation ratio on the demand side increased CO₂ emissions nearly 25‐fold from 1990 to 2015. Notably, some demand‐side factors also had an effect that reduced CO₂ emissions. The in‐use stock per unit of fixed capital formation and output per in‐use stock reduced CO₂ emissions by 332 million metric tons, which is comparable to the contribution of technological progress. Based on these results, we examine why these demand‐side factors substantially influence CO₂ emissions in the Chinese cement sector, and we provide recommendations for policy‐makers on carbon‐reduction measures in this CO₂‐intensive sector.     

Urban Household Carbon Emission and Contributing Factors in the Yangtze River Delta,China

Carbon reduction at the household level is an integral part of carbon mitigation. This study analyses the characteristics, effects, contributing factors and policies for urban household carbon emissions in the Yangtze River Delta of China. Primary data was collected through structured questionnaire surveys in three cities in the region – Nanjing, Ningbo, and Changzhou in 2011. The survey data was first used to estimate the magnitude of household carbon emissions in different urban contexts. It then examined how, and to what extent, each set of demographic, economic, behavioral/cognitive and spatial factors influence carbon emissions at the household level. The average of urban household carbon emissions in the region was estimated to be 5.96 tonnes CO₂ in 2010. Energy consumption, daily commuting, garbage disposal and long-distance travel accounted for 51.2%, 21.3%, 16.0% and 11.5% of the total emission, respectively. Regulating rapidly growing car-holdings of urban households, stabilizing population growth, and transiting residents’ low-carbon awareness to household behavior in energy saving and other spheres of consumption in the context of rapid population aging and the growing middle income class are suggested as critical measures for carbon mitigation among urban households in the Yangtze River Delta.