Energy Service Demand Projections and CO2 Reduction Potentials in Rural Households in 31 Chinese Provinces
Until 2012, most of China’s population lived in rural areas with markedly different patterns of household energy consumption from those in Chinese cities. The studies so far done on residential energy use in rural Chinese households have been limited to questionnaire surveys and panel data analyses....
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doaj-9a4244628d2d4c1d93b034a48a6c50942020-11-24T22:25:22ZengMDPI AGSustainability2071-10502015-11-01712158331584610.3390/su71215789su71215789Energy Service Demand Projections and CO2 Reduction Potentials in Rural Households in 31 Chinese ProvincesRui Xing0Tatsuya Hanaoka1Yuko Kanamori2Hancheng Dai3Toshihiko Masui4Center for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, JapanCenter for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, JapanCenter for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, JapanCenter for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, JapanCenter for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba, Ibaraki 305-8506, JapanUntil 2012, most of China’s population lived in rural areas with markedly different patterns of household energy consumption from those in Chinese cities. The studies so far done on residential energy use in rural Chinese households have been limited to questionnaire surveys and panel data analyses. Hardly any studies on energy demand in rural areas have considered both the climatic and economic disparities across Chinese regions. In this study we conduct a systematic analysis of the rural Chinese residential sector on a regional basis. We begin by developing a macro-model to estimate energy service demands up to 2050. Next, we apply the AIM(Asia-Pasific Integrated Model)/Enduse model, a bottom-up cost-minimization model with a detailed mitigation technology database, to estimate the mitigation potential of low-carbon technologies in rural China. Our results show that energy service demand in the rural household sector will continue to increase in regions with growing population or income conditions. However, after 2030, the rural residential energy service demand will start to decline in most Chinese regions. The impacts of efficient technologies will vary from one region to the next due to regional climatic and economic disparities. Throughout all of China, the penetration of efficient technologies can reduce CO2 emissions by 20% to 50%. Of the technologies available, efficient lighting, biomass water heaters, and efficient electronics bring the most benefit when implemented in rural households.http://www.mdpi.com/2071-1050/7/12/15789Chinarural householdShared Socioeconomic PathwaysCO2 emissionefficient technology |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rui Xing Tatsuya Hanaoka Yuko Kanamori Hancheng Dai Toshihiko Masui |
spellingShingle |
Rui Xing Tatsuya Hanaoka Yuko Kanamori Hancheng Dai Toshihiko Masui Energy Service Demand Projections and CO2 Reduction Potentials in Rural Households in 31 Chinese Provinces Sustainability China rural household Shared Socioeconomic Pathways CO2 emission efficient technology |
author_facet |
Rui Xing Tatsuya Hanaoka Yuko Kanamori Hancheng Dai Toshihiko Masui |
author_sort |
Rui Xing |
title |
Energy Service Demand Projections and CO2 Reduction Potentials in Rural Households in 31 Chinese Provinces |
title_short |
Energy Service Demand Projections and CO2 Reduction Potentials in Rural Households in 31 Chinese Provinces |
title_full |
Energy Service Demand Projections and CO2 Reduction Potentials in Rural Households in 31 Chinese Provinces |
title_fullStr |
Energy Service Demand Projections and CO2 Reduction Potentials in Rural Households in 31 Chinese Provinces |
title_full_unstemmed |
Energy Service Demand Projections and CO2 Reduction Potentials in Rural Households in 31 Chinese Provinces |
title_sort |
energy service demand projections and co2 reduction potentials in rural households in 31 chinese provinces |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2015-11-01 |
description |
Until 2012, most of China’s population lived in rural areas with markedly different patterns of household energy consumption from those in Chinese cities. The studies so far done on residential energy use in rural Chinese households have been limited to questionnaire surveys and panel data analyses. Hardly any studies on energy demand in rural areas have considered both the climatic and economic disparities across Chinese regions. In this study we conduct a systematic analysis of the rural Chinese residential sector on a regional basis. We begin by developing a macro-model to estimate energy service demands up to 2050. Next, we apply the AIM(Asia-Pasific Integrated Model)/Enduse model, a bottom-up cost-minimization model with a detailed mitigation technology database, to estimate the mitigation potential of low-carbon technologies in rural China. Our results show that energy service demand in the rural household sector will continue to increase in regions with growing population or income conditions. However, after 2030, the rural residential energy service demand will start to decline in most Chinese regions. The impacts of efficient technologies will vary from one region to the next due to regional climatic and economic disparities. Throughout all of China, the penetration of efficient technologies can reduce CO2 emissions by 20% to 50%. Of the technologies available, efficient lighting, biomass water heaters, and efficient electronics bring the most benefit when implemented in rural households. |
topic |
China rural household Shared Socioeconomic Pathways CO2 emission efficient technology |
url |
http://www.mdpi.com/2071-1050/7/12/15789 |
work_keys_str_mv |
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