Subtropical monsoon climates, high-density and heterogeneous urban built environments, as well as coastal–mountainous geographical environments influence the development of urban heat island (UHI) effects in Hong Kong. For better weather control of in situ observations and spatial analysis of UHI effects, it is necessary to quantitatively understand the influence of weather conditions on UHI development in Hong Kong and establish weather-based UHI estimation models. Meteorological records of four urban stations, one rural reference station, and one wind reference station at an hourly interval during the period of 2002–2012 were collected from Hong Kong observatory. A frequency analysis of the mean values of multiple meteorological elements and UHI parameters in urban stations was conducted to examine the prevailing and critical weather conditions, as well as the associated UHI conditions in Hong Kong. Multiple Linear Regression (MLR) was used to estimate the daily maximum UHI intensity (UHI_max) based on a set of meteorological elements including cloud amount, wind speed, wind direction, relative humidity, and air temperature, as well as a UHI parameter of the daily maximum UHI intensity of the previous day (UHI_pre-max). The results showed that MLR-based models can explain 33% and 56% variations of the UHI_max in the summer and the whole year, respectively. The relative importance of each meteorological element on UHI development differed in the summer and annual periods, and the UHI_max tended to be intensified under high temperature conditions in the summer.

The regenerative design framework aims to ‘engage a broader range of possibilities by moving beyond the immediate building and site boundaries’. It implies that the environmental performance of buildings requires a revised definition so that it considers not only the building itself, but also its contribution beyond its own boundary, i.e. neighbourhoods. In high-density cities, outdoor spaces are culturally considered as the extension of one’s living spaces. The environmental performance of neighbourhoods is particularly important to the health and wellbeing of urban inhabitants. This paper aims to define the environmental performance of neighbourhoods in high-density urban context based on the experience acquired in previous studies in Hong Kong over the last 15 years. These studies cover a wide range of environmental issues including urban climate, outdoor thermal comfort, and daylighting design in high-density cities. Subsequent development of the assessment tools for environmental performance of neighbourhoods in Hong Kong is also presented. The framework of stakeholder engagement, as an integral part of the neighbourhood assessment tool, is discussed. This paper highlights the distinctive features of the environmental performance of neighbourhoods in high-density urban context and how it influences the professional practices in Hong Kong.

Uncertainties concerning low-impact development (LID) practices over its service life are challenges in the adoption of LID. One strategy to deal with uncertainty is to provide an adaptive framework which could be used to support decision-makers in the latter decision on investments and designs dynamically. The authors propose a Bayesian-based decision-making framework and procedure for investing in LID practices as part of an urban stormwater management strategy. In this framework, the investment could be made at various stages of the service life of the LID, and performed with deliberate decision to invest more or suspend the investment, pending the needs and observed performance, resources available, anticipated climate changes, technological advancement, and users’ needs and expectations. Variance learning (VL) and mean-variance learning (MVL) models were included in this decision tool to support handling of uncertainty and adjusting investment plans to maximize the returns while minimizing the undesirable outcomes. The authors found that a risk-neutral investor tends to harbor greater expectations while bearing a higher level of risks than risk-averse investor in the VL model. Constructed wetlands which have a higher prior mean performance are more favorable during the initial stage of LID practices. Risk-averse decision-makers, however, could choose porous pavement with stable performance in the VL model and leverage on potential technological advancement in the MVL model.