Modelling Cooling Energy Consumption and Indoor PM2.5 Exposure of Hong Kong Dwellings


Student thesis: Doctoral Thesis

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Award date2 Jan 2020


The Hong Kong Government has unveiled ambitious programmes that seek significant improvement to the energy efficiency and indoor air quality of the housing stock. Understanding the details of energy consumption and indoor air quality of dwellings is critical to supporting the implementation of these programmes. This thesis describes how modelling can be used to reliably predict cooling energy consumption and indoor PM2.5 exposure of Hong Kong dwellings, and how factors such as external environment, occupant behaviour, dwelling characteristics, ventilation and shading impact the model results.

This thesis consists of three parts. The first part is devoted to the improvement of the model inputs for external environmental conditions and occupants’ window opening behaviour. A Typical Meteorological Year plus Air Pollution (TMY+AP) file was generated using Hong Kong’s weather and outdoor PM2.5 data, for use in a combined analysis of cooling energy consumption and indoor PM2.5 exposure in dwellings. In addition, this thesis examined the robustness of six existing behavioural models in predicting window-use patterns in Hong Kong dwellings, along with an analysis of the impact of behavioural models on the accuracy of indoor temperature (which impacts on cooling energy consumption) and indoor PM2.5 concentration prediction. Results show that the use of a TMY+AP file or a robust behavioural model of window opening improves the predictions about dwelling cooling energy consumption and domestic indoor PM2.5 exposure, relative to the conventional modelling approaches.

The second part of the thesis deals with the cooling-energy and indoor-PM2.5-exposure impacts of implementing energy efficiency measures in dwellings, including ventilation through open windows, window shading with interior roller blinds and energy recovery ventilation using energy recovery ventilators (ERV). Cooling energy consumption and indoor PM2.5 exposure of typical Hong Kong high-rise residential flats were modelled under different window and roller blind control strategies. Results show that flats with controlled windows and roller blinds are predicted to have cooling energy consumption up to 55% lower than those with windows closed and roller blinds open, while meeting the World Health Organisation (WHO) standard for PM2.5 exposure. In addition, dwelling cooling energy consumption and domestic indoor PM2.5 exposure associated with different control strategies for the ERV were quantified using computer modelling and monetised using per-occupant cost functions. Results show that the ERV, if operated properly, can help to reduce indoor PM2.5 exposure whilst conserving cooling energy. The most cost-effective constant-flow strategy for the ERV costs an occupant approximately HK$ 3507 over the course of a year. Varying the ventilation rate of the ERV as a function of outdoor conditions further reduces the combined energy and exposure cost compared with operating the ERV at the most cost-effective ventilation rate.

The third part of the thesis describes the development of a city-level model that allows for the predictions of cooling energy consumption and indoor PM2.5 exposure across Hong Kong dwellings, and the analysis of the impacts energy efficiency adaptations in the housing stock (including fabric insulation, low-e coating, airtightening, natural ventilation through windows, window shading and energy recovery ventilation) have on residential cooling energy consumption and population exposure to domestic indoor PM2.5. Dwelling archetypes broadly representative of the Hong Kong housing stock were developed based on geographically-referenced housing stock databases. Simulations were carried out for unique combinations of dwelling archetype, fabric, occupation and environment. Results indicate that modern village houses and top-floor flats in high-rise residential buildings, particularly those in Sham Shui Po and Wan Chai, are more prone to high cooling energy costs. Dwellings in urban areas generally have lower exposure to outdoor sourced PM2.5 and higher exposure to indoor sourced PM2.5 compared with those in rural areas, driven largely by the dominant dwelling archetypes. The cooling-energy and indoor-PM2.5-exposure impacts of implementing energy efficiency measures in dwellings are predicted to vary according to dwelling archetype.