2015
DOI: 10.3390/en80910537
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A Comparison of Household Carbon Emission Patterns of Urban and Rural China over the 17 Year Period (1995–2011)

Abstract: Abstract:The household sector consumes a large amount of goods and services and is therefore a major source of global carbon emissions. This study aims to analyze per person household carbon emission (HCEs) patterns of urban and rural China over the period from 1995 to 2011. Annual macroeconomic data for the study were obtained from authentic Chinese government sources. Direct HCE estimates for each fossil fuel were obtained using the IPCC's reference approach, and indirect HCEs were calculated by input-output… Show more

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Cited by 36 publications
(21 citation statements)
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“…Along with the increasingly serious environmental pollution and scarce resources, people have paid more and more attention to energy conservation and emissions reduction [1,2]. A heat pump (HP) can use some amount of external power to move thermal energy from a heat source (air, wastewater, ground, underground water, etc.)…”
Section: Introductionmentioning
confidence: 99%
“…Along with the increasingly serious environmental pollution and scarce resources, people have paid more and more attention to energy conservation and emissions reduction [1,2]. A heat pump (HP) can use some amount of external power to move thermal energy from a heat source (air, wastewater, ground, underground water, etc.)…”
Section: Introductionmentioning
confidence: 99%
“…PHCEs in our study and other studies are compared in Table 3. PHCEs in Beijing, Tianjin, Shanghai, and Chongqing were larger than the national average household footprint shown by Wiedenhofer et al [65], Fan et al [66], and Qu et al [67], but much smaller than the U.S. [68] and European countries [18,69,70]. Compared to the results of Tian et al [71] and Fry et al [72], Beijing's total PHCEs in our results were 31.56% and 29.02% smaller, respectively, due to different research methods and data sources.…”
Section: Urban and Rural Total Hces And Phcesmentioning
confidence: 69%
“…Two variables were chosen to represent urbanization and population density, which in previous studies have been shown to influence PHCEs [8][9][10][11]. Population per km 2 (PD) was chosen to represent the average population density of a province.…”
Section: Spatial Panel Data Modelsmentioning
confidence: 99%
“…For example, Sichuan has a relatively high population density, while it has a moderate rate of urbanization. A final demographic variable that has been shown to influence PHCEs is average household size (HS) [8][9][10][11]. Per capita income (PI) was chosen as a metric of economic affluence [21], since personal income is likely to have the most direct impact on PHCEs, relative to other measures such as per capita GDP.…”
Section: Spatial Panel Data Modelsmentioning
confidence: 99%
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