Energy efficiency, renewables, and electrification contribute to decarbonising the operation of residential building stock in Hong Kong

Abstract

Reducing operational carbon emissions from residential buildings is crucial for achieving carbon neutrality in high-density metropolises such as Hong Kong. However, existing studies on decarbonising the building sector have mainly focused on the impact of socio-economic factors, rather than technical factors, resulting in an unclear action plan. Aiming to fill the knowledge gap on the pathway to net-zero emissions from the operation of Hong Kong’s residential buildings, this paper develops an emission prediction model integrating the Kaya identity and the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. Technical factors related to building operation, including energy use intensity, carbon emission factor and electrification rate, were incorporated into the model. The Logarithmic Mean Divisia Index (LMDI) decomposition method was then used to identify the key factors influencing the carbon emissions based on official statistics from 2000 to 2023. Finally, a total of 81 dynamic scenarios were developed within the context of Hong Kong to predict future emissions and analyse the contributions of different decarbonisation strategies. Electricity use intensity and carbon emission factor were identified as the most significant explicit influencing factors, while building electrification rate was identified as an implicit factor. Accordingly, the strategies of building energy efficiency, renewable energy use, and building electrification can respectively contribute to 48.0%, 44.5% and 7.4% of the reduction in operational carbon emissions from Hong Kong's residential building stock in 2050. The findings provide important implications for Hong Kong in formulating effective decarbonisation roadmaps for the operation of the residential building stock.