The impact of household consumption on energy use and CO2 emissions in China

Feng, Zhuo; Zou, Le–Le; Wei, Yi‐Ming

doi:10.1016/j.energy.2010.09.049

Cited by 257 publications

(104 citation statements)

References 18 publications

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“…Households are responsible for a significant portion of the CO2 emissions due to use of fossil fuels for space and hot water heating, transportation, and electricity [12][13][14]. Households consume energy in two ways: direct (space heating, lighting, vehicle fuel, etc.)…”

Section: Introductionmentioning

confidence: 99%

Determining residential energy consumption-based CO₂ emissions and examining the factors affecting the variation in Ankara, Turkey

et al. 2017

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Abstract. Energy demand of Turkey has been showing a remarkable increase in the last two decades due to rapid increase in population and changes in consumption trends. In parallel to the increase in energy demand, the CO2 emissions in Turkey are also increasing dramatically due to high usage of fossil fuels. CO2 emissions from the residential sector covers almost one fourth of the total sectoral emissions. In this study, CO2 emissions from the residential sector are estimated, and the factors affecting the emission levels are determined for the residential sector in Ankara, Turkey. In this study, detailed surveys are conducted to more than 400 households in Ankara. Using the information gathered from the surveys, the CO2 emissions associated with energy consumption of the households are calculated using the methodology outlined at IPCC. The statistical analyses are carried out using household income, dwelling characteristics, and household economic and demographic data to determine the factors causing the variation in emission levels among the households. The results of the study present that the main factors impacting the amount of total energy consumption and associated CO2 emissions are household income, dwelling construction year, age, education level of the household, and net footage of the dwelling.

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Section: Introductionmentioning

confidence: 99%

Determining residential energy consumption-based CO₂ emissions and examining the factors affecting the variation in Ankara, Turkey

et al. 2017

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“…Most of them focused on family income's influence on residential energy and electricity consumption [1][2][3][4][5][6][7][8][9][10][11][12]. The results of these studies suggested that family income was the major influencing factor of household energy consumption.…”

Section: （%）mentioning

confidence: 99%

“…Families with different incomes have different energy consumption situations. Feng et al and Niu et al [4,8]studied the influencing factors of energy consumption of urban and rural residents in China. Their findings showed that household energy consumption of high-income families was more than that of low-income families and the direct energy consumption of urban residents was more than that of rural residents.…”

Section: （%）mentioning

confidence: 99%

“…90% of them raised the first ladder standard. However, the first ladder standard is unreasonable and requires adjustment for 4 Calculated with the data originated from "China Statistical Yearbook" the actual situation of different regions. Besides, the government should guide residents' electricity consumption behaviors through rewards for saving electricity, regulations and policies.…”

Section: Decomposition Of Income Effect and Population Structure Effectmentioning

confidence: 99%

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Income, Consumption Tendency and Per Capital Electricity Consumption in the Age of China' Urbanization

Wen¹,

Chong-huai²,

Yao³

et al. 2017

Proceedings of the 3rd 2017 International Conference on Sustainable Development (ICSD 2017)

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Abstract. The rapid development of urbanization in China is coupled with the increase in per capital electricity consumption. This study focuses on the impacts of residents' income change and consumption tendency change on per capital electricity consumption in the process of urbanization in China. In this paper, LMDI method is used to analyze each factor's impact on per capital electricity consumption in the process of urbanization in China. The results show that income effect is the major determinant of per capital electricity consumption which is followed by population structure effect and electricity consumption effect; income effect in the urban regions is more than that in the rural regions; electricity consumption tendency effect in the rural regions is more than that in the urban regions.

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“…Additionally, the national comparison at the product level indicated that country characteristics (such as energy supply, population density, and the availability of district heating) influence variations in household CO 2 emissions between and within countries (Kerkhof et al 2009). Feng et al (2011) used a gray model to compare the relationship between energy consumption, consumption expenditure, and CO 2 emissions for different lifestyles, which showed that direct energy consumption was diverse for urban households and simple for rural households in China. Büchs and Schnepf (2013) investigated how household characteristics such as income, household size, education, gender, unemployment, and rural or urban location were associated with all types of emissions.…”

Section: Introductionmentioning

confidence: 99%

A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China

Qin

Liu

et al. 2015

Environ Sci Pollut Res

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Given the large expenditures by households on goods and services that contribute a large proportion of global CO 2 emissions, increasing attention has been paid to household CO 2 emissions (HCEs). However, compared with industrial CO 2 emissions, efforts devoted to mitigating HCEs are relatively small. A good understanding of the effects of some driving factors (i.e., urbanization rate, per capita GDP, per capita income/disposable income, Engel coefficient, new energy ratio, carbon intensity, and household size) is urgently needed prior to considering policies for reducing HCEs. Given this, in the study, the direct and indirect per capita HCEs were quantified in rural and urban areas of China over the period 2000-2012. Correlation analysis and gray correlation analysis were initially used to identify the prime drivers of per capita HCEs. Our results showed that per capita income/disposable income, per capita GDP, urbanization rate, and household size were the most significantly correlated with per capita HCEs in rural areas. Moreover, the conjoint effects of the potential driving factors on per capita HCEs were determined by performing principal component regression analysis for all cases. Based on the combined analysis strategies, alternative polices were also examined for controlling and mitigating HCEs growth in China.

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The impact of household consumption on energy use and CO2 emissions in China

Cited by 257 publications

References 18 publications

Determining residential energy consumption-based CO₂ emissions and examining the factors affecting the variation in Ankara, Turkey

Determining residential energy consumption-based CO₂ emissions and examining the factors affecting the variation in Ankara, Turkey

Income, Consumption Tendency and Per Capital Electricity Consumption in the Age of China' Urbanization

A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China

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The impact of household consumption on energy use and CO2 emissions in China

Cited by 257 publications

References 18 publications

Determining residential energy consumption-based CO2 emissions and examining the factors affecting the variation in Ankara, Turkey

Determining residential energy consumption-based CO2 emissions and examining the factors affecting the variation in Ankara, Turkey

Income, Consumption Tendency and Per Capital Electricity Consumption in the Age of China' Urbanization

A hybrid study of multiple contributors to per capita household CO2 emissions (HCEs) in China

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Product

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Determining residential energy consumption-based CO₂ emissions and examining the factors affecting the variation in Ankara, Turkey

Determining residential energy consumption-based CO₂ emissions and examining the factors affecting the variation in Ankara, Turkey