Search

Hong Kong suffers from an intense urban heat island (UHI) effect of up to 4 °C as a result of compact urban form and highly urbanized land cover. Enhancing the cooling efficiency of urban greenery is essential for improving the microclimate in high-density cities. This paper aims to delineate design strategies for urban greenery to maximize thermal benefits and mitigate the daytime UHI effect. Two site-specific design strategies for tree planting in the urban environment are proposed. The sky view factor (SVF)-based design approach and the wind-path design approach are evaluated in the neighbourhood scale in two climate-sensitive areas with different urban morphologies. Observed data and simulation results indicated that the cooling effect of urban trees is highly associated with SVF. Air temperature reduction (a 1.5 °C reduction) is the most profound for the high SVF scenario, whereas substantial radiation shading ( T mrt reduced to 34 °C) is detected in areas with medium-low SVFs. The modelling study also showed that the cooling of air temperature and sensible heat were twice as high for vegetation arranged in wind corridors than those for leeward areas. The study demonstrated that tree planting in conjunction with proper planning is an effective measure to mitigate daytime UHI. [ABSTRACT FROM AUTHOR]

Abstract: It becomes popular to use computer simulation technique to evaluate the performance of energy utilizations in buildings. The hourly weather data as simulation input is a crucial factor for the successful energy system simulation, and obtaining an accurate set of weather data is necessary to represent the long-term typical weather conditions throughout a year. This paper introduces a stochastic approach, which is called the first order multivariate Markov chain model, to generate the annual weather data for better evaluating and sizing different energy systems. The process for generating the weather data time series from the multivariate Markov transition probability matrices is described using 15-years actual hourly weather data of Hong Kong. The ability of this new model for retaining the statistical properties of the generated weather data series is examined and compared with the current existing TMY and TRY data. The main statistical properties used for this purpose are mean value, standard deviation, maximum value, minimum value, frequency distribution probability and persistency probability of the weather data sequence. The comparison between the observed weather data and the synthetically generated ones shows that the statistical characteristics of the developed set of weather data are satisfactorily preserved and the developed set of weather data can predict and evaluate different energy systems more accurately. [Copyright &y& Elsevier]