Modeling energy intensity of residential space heating

Jin, Gong; Wu, Shimei; Hu, Jingqiu; Wei, Chu

doi:10.1007/s12053-018-9704-y

Cited by 8 publications

(2 citation statements)

References 35 publications

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“…Based on the report of the Asia-Pacific Energy Research Centre [33], when the outdoor temperature is below 18 • C, the indoor temperature needs to be raised to 18 • C by heating. In the same way, when the outdoor temperature is higher than 26 • C, it is necessary to cool the indoor temperature to 26 • C. Consistent with some previous studies [24,33,34], we use 18 • C and 26 • C as the criteria for calculating HDDS and CDD. We note that various criteria are used in calculating degree days in different countries; however, for the sake of comparison, we uniformly adopt the Chinese criteria here.…”

Section: Data Sources and Calculationmentioning

confidence: 79%

Exploring the Changing Gap of Residential Energy Consumption per Capita in China and the Netherlands: A Comparative Analysis of Driving Forces

2020

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This paper brings out some remarkable differences between China as a developing country experiencing high economic growth and the Netherlands as a developed country by examining the driving forces behind the evolution of residential energy consumption per capita (RECpc) in the two countries in the period from 2001 to 2015. The components we analysed are income, energy-intensity, weather and energy-mix effects. The most remarkable result is the changing effect of energy intensity in China: during 2001–2007 energy intensity increased, and decreased afterward. The changes reflected changes in material circumstances: the shift to relative energy intensive goods and of saturation of energy demand for heating and cooling. In the Netherlands, the declining energy intensity, warmer winters and the more diversified energy mix decreased RECpc by 511.39, 58.81 and 1.08 kgce, respectively. Although the income growth both increased RECpc in the two countries, the relatively high-speed increasing income in China narrowed the RECpc gap between the two countries. This study implies that the opposite changes in RECpc in developing and developed countries are due to the different development stages reached by the countries. Policy suggestions are being offered to deal with the different circumstances, as revealed through this study.

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Section: Data Sources and Calculationmentioning

confidence: 79%

Exploring the Changing Gap of Residential Energy Consumption per Capita in China and the Netherlands: A Comparative Analysis of Driving Forces

2020

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“…Guo [47] demonstrates that differences in geographic location and climate zone will affect energy consumption patterns through heating and cooling demands. In addition, Wu [48] illustrates the heating energy consumption of rural households in the north is higher than that in the south.…”

Section: Energy Structurementioning

confidence: 99%

Direct and Indirect Carbon Emission from Household Consumption Based on LMDI and SDA Model: A Decomposition and Comparison Analysis

et al. 2022

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Household consumption has become an important field of carbon dioxide emissions. Urban–rural disparity in the household carbon emissions (HCEs) of residents and their influencing factors are relevant to HCE reduction. Taking Fujian as the study area, the LMDI and SDA models were used to analyze the effects of influencing factors for the direct household carbon emissions (DHCEs) and indirect carbon emissions (IHCEs) of urban and rural residents from 2006 to 2018. The HCEs continue to rise, approximately 65% from the IHCEs in 2017, and urban areas occupied 67% in 2018. The gap between urban and rural per capita HCEs is narrowing. In 2017, approximately 75% of urban per capita HCEs came from the IHCEs, while the per capita DHCEs’ occupation exceeded the IHCEs in rural areas. Per capita consumption expenditure has the largest positive effect on the DHCEs and IHCEs in urban and rural areas. With the urbanization process, the inhibition effect of rural DHCEs is larger than the positive effect of the urban DHCEs, while the positive impact on urban areas is more substantial than on rural areas in the IHCEs. Combined with regional differences, urban and rural areas should take “common but differentiated” emission reduction responsibilities.

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How does income level impact residential-building heating energy consumption? Micro-level evidence from household surveys

Huo

Cai

Zhang

et al. 2021

Environmental Impact Assessment Review

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Modeling energy intensity of residential space heating

Cited by 8 publications

References 35 publications

Exploring the Changing Gap of Residential Energy Consumption per Capita in China and the Netherlands: A Comparative Analysis of Driving Forces

Exploring the Changing Gap of Residential Energy Consumption per Capita in China and the Netherlands: A Comparative Analysis of Driving Forces

Direct and Indirect Carbon Emission from Household Consumption Based on LMDI and SDA Model: A Decomposition and Comparison Analysis

How does income level impact residential-building heating energy consumption? Micro-level evidence from household surveys

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