From income and housing wealth inequalities to emissions inequality: carbon emissions of households in China

Yang, Zan; Wu, Shuping; Cheung, Hiu Ying

doi:10.1007/s10901-016-9510-9

Cited by 23 publications

(11 citation statements)

References 59 publications

(63 reference statements)

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“…In the current backdrop of increasing global apprehension about carbon emissions and their impact on climate change, considerable research effort has been devoted to exploring the intricate relationship between household characteristics, household consumption patterns and their environmental repercussions (Clarke-Sather et al ., 2011; Duro, 2013; Yang et al ., 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Comparing the determinants of household carbon footprints between rural and urban: evidence from China household survey data

Lv,

Liu,

Chai

2024

CAER

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PurposeUrbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.Design/methodology/approachWe employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.FindingsThe results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.Originality/valueThis paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

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Section: Literature Reviewmentioning

confidence: 99%

Comparing the determinants of household carbon footprints between rural and urban: evidence from China household survey data

Lv,

Liu,

Chai

2024

CAER

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“…The cost of changing consumption towards "greener" goods and services can be higher than paying carbon taxes (as evidenced by the cost and length of train journeys that is often higher than flights to the same destination; or green mortgages in a context where energy efficient housing remains more costly than non-energy efficient one). Furthermore, the inducement of changes in consumption behaviour is less likely to include high-income groups, which have been identified as the higher CO2 emitters (Knight et al 2017;Gore, 2015;Yang et al 2017) and are paradoxically the ones who can afford to secure and maintain their carbon-intensive consumption patterns and lifestyle by "buying" their right to pollute. As a result, the 1 st dimension of GIP can have a discriminatory impact on low-income groups if they neglect issues of income distribution.…”

Section: First Dimension Of Gip: Consumption-focused Approaches To Cl...mentioning

confidence: 99%

Three Dimensions of Green Industrial Policy in the Context of Climate Change and Sustainable Development

Anzolin

Lebdioui

2021

Eur J Dev Res

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Climate change has taken an increasingly important space in the development agenda. However, whether most countries can meet the challenge of mitigating climate change while simultaneously ensuring growth and poverty reduction remains debatable. This research contributes to the growing literature at the intersection of environment sustainability and economic/industrial development by identifying three dimensions of Green Industrial Policy (GIP), which rely on different approaches to mitigate climate change. Those three dimensions are: (i) the consumption-centred dimension; (ii) the firm-level sustainability dimension, (iii) the productionist innovation-driven dimension. This paper then applies this green industrial policy framework and examines the implications of pursuing different levels of GIP by drawing on a country case study (Ecuador). Two main findings arise from this study. Firstly, a greener consumption is necessary but can hardly be achieved without industrial policies to stimulate green manufacturing and low carbon innovation. Green industrial policy therefore has a central role to play in the structural transformation towards a low carbon future. Secondly, a holistic and complementary approach is needed across the three dimensions of green industrial policy to ensure a coherent and developmental transition towards a low carbon economy.

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“…The results showed that the properties of energy-saving buildings and better community facilities had significantly reduced the carbon emission levels of households. Residents of communities far away from public facilities tended to have a higher probability of buying cars, leading to higher traffic carbon emissions [ 15 ]. Gu found the CO 2 emission status of the energy consumption of urban households in Nanjing and its influencing factors were analyzed.…”

Section: Introductionmentioning

confidence: 99%

Influencing Factors of Direct Carbon Emissions of Households in Urban Villages in Guangzhou, China

Chen

Jiang

2022

IJERPH

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China’s household energy consumption has obvious regional differences, and rising income levels and urbanization have changed the ability of households to make energy consumption choices. In this paper, we analyze the energy consumption characteristics of urban village residents based on microlevel household survey data from urban villages in Guangzhou, China. Then, the results of modeling the material flows of per capita carbon emissions show the most dominant type of energy consumption. OLS is applied to analyze the influencing factors of carbon emissions. We find that the per capita household carbon emissions in urban villages are 722.7 kg/household.year, and the average household carbon emissions are 2820.57 kg/household.year. We also find that household characteristics, household size, household appliance numbers, and carbon emissions have a significant positive correlation, while income has no significant effect on carbon emissions. What is more, the size and age of the house have a positive impact on carbon emissions. Otherwise, the new finding is the demonstration that income is not significantly correlated with household carbon emissions, which is consistent with the characteristics of urban villages described earlier. On the basis of this study, we propose more specific recommendations regarding household energy carbon emissions in urban villages.

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From income and housing wealth inequalities to emissions inequality: carbon emissions of households in China

Abstract: The emerging notion of emissions inequality expands the idea of sustainability by incorporating economic opportunity as well as social needs and rights into environ-

Cited by 23 publications

References 59 publications

Comparing the determinants of household carbon footprints between rural and urban: evidence from China household survey data

Comparing the determinants of household carbon footprints between rural and urban: evidence from China household survey data

Three Dimensions of Green Industrial Policy in the Context of Climate Change and Sustainable Development

Influencing Factors of Direct Carbon Emissions of Households in Urban Villages in Guangzhou, China

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