China's Building Energy Demand: Long-Term Implications from a Detailed Assessment

Journal Article · Mon Oct 01 04:00:00 EDT 2012 · Energy, 46(1):405-419

DOI:https://doi.org/10.1016/j.energy.2012.08.009· OSTI ID:1054433

Eom, Jiyong; Clarke, Leon E; Kim, Son H; Kyle, G Page; Patel, Pralit L

We present here a detailed, service-based model of China’s building energy use, nested in the GCAM (Global Change Assessment Model) integrated assessment framework. Using the model, we explore long-term pathways of China’s building energy use and identify opportunities of reducing greenhouse gas emissions. The inclusion of a structural model of building energy demands within an integrated assessment framework represents a major methodological advance. It allows for a structural understanding of the drivers of building energy consumption while simultaneously considering the other human and natural system interactions that influence changes in the global energy system and climate. We also explore a range of different scenarios to gain insights into how China’s building sector might evolve and what the implications might be for improved building energy technology and carbon policies. The analysis suggests that China’s building energy growth will not wane anytime soon, although technology improvement will put downward pressure on this growth. Also, regardless of the scenarios represented, the growth will involve the continued, rapid electrification of the buildings sector throughout the century, and this transition will be accelerated by the implementation of carbon policy.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1054433
• Report Number(s): PNNL-SA-83864; 400408000
• Journal Information: Energy, 46(1):405-419, Journal Name: Energy, 46(1):405-419
• Country of Publication: United States
• Language: English

Related Subjects

Building energy modeling
China buildings
Electrification
Integrated assessment model
Scenario Analysis