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Energy efficiency outlook in China’s urban buildings sector through 2030

Abstract This study uses bottom-up modeling framework in order to quantify potential energy savings and emission reduction impacts from the implementation of energy efficiency programs in the building sector in China. Policies considered include (1) accelerated building codes in residential and commercial buildings, (2) increased penetration of district heat metering and controls, (3) district heating efficiency improvement, (4) building energy efficiency labeling programs and (5) retrofits of existing commercial buildings. Among these programs, we found that the implementation of building codes provide by far the largest savings opportunity, leading to an overall 17% reduction in overall space heating and cooling demand relative to the baseline. Second are energy efficiency labels with 6%, followed by reductions of losses associated with district heating representing 4% reduction and finally, retrofits representing only about a 1% savings.
- Lawrence Berkeley National Laboratory United States
- Lawrence Berkeley National Laboratory United States
- University of California System United States
690, Building sector China, Energy, 330, 550, Energy demand modeling, Energy efficiency policy, Policy and administration, Affordable and Clean Energy, Clinical Research, Built Environment and Design, Urban and regional planning, Environmental and resources law, Architecture
690, Building sector China, Energy, 330, 550, Energy demand modeling, Energy efficiency policy, Policy and administration, Affordable and Clean Energy, Clinical Research, Built Environment and Design, Urban and regional planning, Environmental and resources law, Architecture
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).101 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
