Estimating Space-Cooling Energy Consumption and Indoor PM_2.5 Exposure across Hong Kong Using a City-Representative Housing Stock Model

Abstract

High-quality data on building energy use and indoor pollution are critical to supporting government efforts to reduce carbon emissions and improve the population’s health. This study describes the development of a city-representative housing stock model used for estimating space-cooling energy use and indoor PM2.5 exposure across the Hong Kong housing stock. Archetypes representative of Hong Kong dwellings were developed based on geographically-referenced housing databases. Simulations of unique combinations of archetype, occupation, and environment were run using EnergyPlus, estimating the annual space-cooling energy consumption and annual average PM2.5 exposure concentrations under both non-retrofit and retrofit scenarios. Results show that modern village houses and top-floor flats in high-rise residential buildings, on average, used 19% more space-cooling energy than other archetypes. Dwellings in urban areas had lower exposure to outdoor-sourced PM2.5 and higher exposure to indoor-sourced PM2.5 compared to those in rural areas. The percentage decrease in space-cooling energy consumption caused by energy efficiency retrofits, including external wall insulation, low-e windows, and airtightening, varied significantly based on archetype. The implementation of external wall insulation in the housing stock led to an average decrease of 3.5% in indoor PM2.5 exposure, whilst airtightening and low-e windows resulted in 7.9% and 0.2% average increases in exposure, respectively.

Keywords

• building simulation
• housing stock modelling
• space-cooling energy use
• indoor PM_2.5 exposure
• building retrofit