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Highlights • The majority of carbon emissions derived from indirect fraction of energy consumption in Beijing. • Life expectancy is reduced in areas where a higher amount of coal is burnt for household consumption. • Socio-economic structure changes play a major role in the observed energy and emission trends. • Search of optimal solutions for energy-efficient and low carbon private will continue to be crucial. Abstract Household carbon emissions are major contributors to global emissions that is increasing recognized. In China, approximately 20 million rural populations transfer to the urban areas annually, which results in a lot of new infrastructure construction and consumer requirements. This paper quantifies the numbers and trends of urban and rural resident on energy use and carbon footprint in Beijing from 1996 to 2011 by analysis of Consumer Lifestyle Approach (CLA) and carbon footprint. It provides a better understanding of complete energy consumption and carbon emissions profile in Beijing. The results show that for the Beijing residents, when direct and indirect energy consumption and CO 2 emissions are taken into account, the total household energy consumption proportion compared to the city increases from 22.7% to 59.2%, and the total household CO 2 emissions proportion increases from 32.2% to 68.8% in the research period. In the urbanization process, total energy consumption and carbon emissions of Beijing urban residents are significantly higher than those of rural residents. However, the transformation of a rural Beijing resident into an urban Beijing resident would not create a large difference between urban and rural areas in the per-capita energy consumption and per-capita carbon footprint. Results are assessed with respect to the available scientific literature, as well as potential available technological and policy solutions. Since the implementation that different policy instruments can mitigate carbon emissions, governments are gradually combining policy measures for the same technology. The results in this paper may help promote alternative consumption strategies in household sector which could entail more reasonable resource distribution and effective reduction of both urban and rural environmental influences. [ABSTRACT FROM AUTHOR]

Along with rapid urbanization and economic development, urban household consumption has experienced a remarkable change, leading to a corresponding increase in direct and indirect carbon emissions. A systematic accounting of household carbon footprints (HCFs) in Beijing during 2002, 2007, and 2012 using a nested input-output model is presented in this paper. The results indicate that the per capita carbon footprint from urban household consumption in Beijing increased from 3054.05 kg in 2002–4611.12 kg in 2012, of which the indirect emissions were the majority. In terms of consumption structure, food, housing, transportation and communication, and education and entertainment were the four dominant sources contributing to the indirect urban HCFs in Beijing. With respect to the source, local Beijing was the largest contributor for itself materials and service provisions in 2002 and 2007, while the domestic source became the largest contributor in 2012, accounting for 55.08% of the total indirect household carbon emissions. Moreover, we also discovered that families with high income level had much higher HCFs compared to those with low income level. Given these considerations, transitions towards low-carbon household consumption are needed so as to provide equality and sustainability. • Nested input-output model is adopted to calculate household carbon footprints (HCFs). • Per capita HCFs in Beijing increased from 3054.05 kg in 2002–4611.12 kg in 2012. • Indirect emission constituted the majority of HCFs, accounting for 63.69% in 2012. • Income level has great impacts on HCFs due to energy intensive consumption pattern. [ABSTRACT FROM AUTHOR]

• Studying on dynamic ecological footprint (EF) in Jing-Jin-Ji from 1996 to 2020. • Six impact factors for driving EF is decomposed. • The EF in Jing-Jin-Ji will increase of 10% from 2015 to 2020. The ecological footprint (EF) describes the complex relationship between the eco-environment and economic development. EF dynamics can better reflect the appropriation of natural resources in various countries or regions compared with previous studies. This paper identified six dominant factors including population, per capita GDP, three major industrial added values, and energy consumption using grey correlation model for the EF changes of the Beijing-Tianjin-Hebei (Jing-Jin-Ji) region from 1996 to 2015. Then, we predicted the EF of the Jing-Jin-Ji region from 2016 to 2020 based on support vector machine model. (1) Since 1996, the EF and per capita EF of the overall Jing-Jin-Ji region have increased, of which those of Hebei Province and Tianjin increased while Beijing decreased. (2) Energy consumption dominated the EF of Jing-Jin-Ji region. The population of Beijing had a high correlation coefficient of 0.735 with the local EF, and the degree of correlation between the EF and per capita GDP was 0.812 in Hebei Province. In Tianjin, the added value of the tertiary industry was closely correlated with its EF, with a correlation coefficient of 0.741. (3) The EF of the Jing-Jin-Ji region will reach 778.30 million hectares by 2020, an increase of 10% compared with the value in 2015. Finally, suggestions for the development of industrial structure and energy consumption are listed for the sustainable development of Jing-Jin-Ji region. [ABSTRACT FROM AUTHOR]