Table of contents

Research has shown that, even though the conditions seem to comply with current standards for indoor environmental quality (IEQ) based on single-dose response relationships, staying indoors is not good for our health. In the last three decades, many studies all over the world have been performed to identify and solve health and comfort problems of occupants. In our current standards, IEQ is still described with quantitative dose-related indicators, expressed in number and/or ranges of numbers for each of the factors (indoor air, lighting, acoustics and thermal aspects). Individual differences in needs and preferences of occupants (over time) are not accounted for. Other stressors and factors, whether of psychological, physiological, personal, social or environmental nature, are rarely considered. Interactions of stressors and effects at and between human and environment level are ignored. The focus is on preventing negative effects: positive effects are usually not considered. There is a need for an integrated analysis approach for assessing indoor environmental quality, which takes account of the combined effects of positive and negative stress factors in buildings on people (patterns), interactions, as well as the (dynamic) preferences and needs of occupants (profiles) and dynamics of the environment.

Natural ventilation in buildings can increase thermal comfort and reduce air-conditioning use. However, it is very challenging today to accurately determine the natural ventilation rate through a building. This paper outlines a method to calculate the wind distribution around a building site from information obtained at a meteorological station miles away. This paper also discusses the influence of surrounding buildings on the wind flow around a target building at the site, and presents various geometrical models. In addition, the use of hour-by-hour wind velocity typically available from a meteorological station may give rise to some errors because of the large time step. A correlation method can be employed to convert the hour-by-hour wind velocity to minute-by-minute velocity. One can then use CFD to calculate the airflow around the building and wind-driven cross ventilation through an apartment simultaneously. However, prediction of single-sided natural ventilation is difficult because of the bi-directional flow at the room opening and the complex flow around buildings. This paper presents an empirical model that can predict the mean and fluctuating ventilation rates due to the pulsating flow and eddy penetration of wind-driven single-sided ventilation in buildings with three types of windows. One must use the correct strategy in a building in order to achieve the maximum benefits of natural ventilation.

The present article aims to analyse and discuss the quantitative and qualitative impact of ambient and urban overheating in the built environment and in particular : on the peak electricity demand, the cooling and heating energy demand of buildings, the electricity consumption during the hot period, the energy impact on the electricity generation and supply systems and the transmission networks, the direct and indirect effects on outdoor air environmental quality as well as the energy and environmental impact on low income and vulnerable population. The existing literature on the topic, more than 250 published articles, has been analysed, classified and discussed. All results and conclusion are tabulated.

Indoor air pollution has become a broad problem due to various indoor or outdoor pollutant sources and limited ventilation. A performance-based approach, which is built upon accurate modelling and simulation of indoor air pollutant characteristics, has obvious advantages over the prescription-based method to achieve better indoor environment. Moreover, the simulation could play a key role in actively preventing indoor air pollution from happening in the first place. In this study, a mechanistic air quality simulation tool was introduced. To verify the reliability of simulation results, two actual field cases with different levels of complexity and time duration were discussed. One was performed in a full-scale experimental room with a single formaldehyde source of a medium density board, in which indoor formaldehyde concentrations varied naturally. Long-term (more than three years) comparison between the simulation results and measurement were conducted. Another occurred during the decoration process in an actual apartment. The formaldehyde concentration levels were well predicted at the design stage and later verified by the field data. Nevertheless, a lot more efforts are required to make indoor air quality (IAQ) simulation tools readily useful in actual engineering applications.