| Author: | Jia, Siqi |
| Title: | Multiscale evaluation of thermal environment in Hong Kong and strategies for improving urban thermal environment and walkability |
| Advisors: | Wang, Yuhong (CEE) |
| Degree: | Ph.D. |
| Year: | 2023 |
| Subject: | Urban heat island -- China -- Hong Kong Urban climatology -- China -- Hong Kong Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Civil and Environmental Engineering |
| Pages: | xxi, 229 pages : color illustrations |
| Language: | English |
| Abstract: | A remarkable phenomenon in modern cities is the urban heat island (UHI) effect, a term used to describe higher temperatures in cities compared to surrounding rural areas. UHI not only acts as a trap for heat and atmospheric pollutants, it also deteriorates the conditions of living environments and increases energy consumption. Consequently, UHI affects the health, leisure activities, and well-being of urban dwellers. Due to the increasing UHI effect in cities and its serious consequences, there is an urgent need to better understand the causes, magnitude, and patterns of the UHI and develop effective mitigation strategies. However, the assessment of the urban thermal environment, UHI effect, and their impacts on urban residents are currently not satisfactory due to insufficient modeling methods and modeling tools. In addition, strategies to mitigate the UHI effects are not rigorously scrutinized. A multiscale evaluation of the thermal environment in the subtropical city of Hong Kong is conducted in this study, and some data from Singapore is also used to assist the evaluation at the micro-scale. Strategies for improving urban thermal environment and walkability are assessed. The main objectives of this study include: (1) to evaluate the UHI effect and urban thermal environment at multiple scales (macro-scale, meso-scale, and micro-scale); (2) to investigate the effect of urban thermal environment on pedestrians' thermal comfort and walking behaviors; (3) to assess the effectiveness of heat mitigation strategies on microclimate, thermal comfort, and walkability. The data used in this study can be divided into two categories, namely onsite data and satellite data. Onsite data collection includes meteorological surveys, interviews, and video recordings. A total of 42 weather stations managed by the Hong Kong Observatory and 28 weather stations by the National University of Singapore were used for obtaining long-term meteorological data, and mobile weather stations and net radiometers were used to obtain data not covered by those weather stations. A total of 337 pedestrians were interviewed to investigate their thermal perceptions and walking speed, along with the simultaneous collection of site-specific climatic data. For satellite data, large-scale and continuous land surface temperature (LST) and land use /land cover (LULC) data were retrieved from cloud-free satellite images. At the macro-scale, the patterns of LST and LULC in the entire territory of Hong Kong and the seasonal variations of the relationships between them were studied. Both the ordinary least squared (OLS) model and the geographically weighted regression (GWR) model were applied. The results indicate that LST is significantly affected by LULC types. The adjusted coefficient of determination (R²) values of the GWR models are much higher than those of the corresponding OLS models in all seasons. At the meso-scale, the pixel-level LST (100 m × 100 m) in two representative regions of Hong Kong was predicted using 25 biophysical and morphological predictors. Results demonstrate that the hybrid model combining GWR and deep neural network (DNN) performs the best among all evaluated models in terms of model fitness and prediction error. The coefficient of determination (R²) of the hybrid model ranges from 0.651 to 0.910 and the mean squared error (MSE) ranges from 0.260 to 1.017 among all datasets. At the micro-scale, the performance of five commonly used methods in the prediction of the mean radiant temperature (Tmrt) of each location in complex urban environments was compared. A total number of 670 observations across 14 typical areas in Hong Kong were collected using net radiometers as the reference. The Singapore dataset consisting of hourly meteorological data among 28 measurement stations over a two-year period was used for model validation. The DNN model yields the highest accuracy among all evaluated models with the R² of 0.878. For the second objective, the relationships between urban thermal environment, human thermal perception, and walking speed were analyzed exploratively and quantitatively using different predictive methods. Four sites in the shaded and open environments in Hong Kong were used to conduct field studies. It is found that pedestrian's walking speed decreases steeply when pedestrians experience thermal discomfort. Pedestrians' average thermal sensation and thermal comfort can be well characterized by linear models by using universal thermal indices as independent variables, and their walking speeds are well predicted by the polynomial regression model (R²=0.719), artificial neural network (R²=0.907), and DNN models (R²=0.931). The findings clearly reveal the quantitative relationships between urban thermal environment and pedestrian's thermal perception and walking behaviors. Finally, the effectiveness of typical heat mitigation strategies on microclimate, thermal comfort, and walkability was evaluated. The evaluated approaches include solar reflective 'cool pavements', vegetative 'extensive/intensive green roofs', 'green façades', 'street trees', and 'permeable pavements'. A typical high-density urban area located in the Yuen Long district of Hong Kong is used to evaluate the effects of common heat mitigation strategies. Thermal environment was simulated using a microclimatic computational fluid dynamic (CFD) model - ENVI-met. Pedestrian's walking behaviors were simulated using agent-based modeling (ABM). Among all the heat mitigation strategies, adding street trees is found to be the key strategy to reduce mean radiant temperature, improve outdoor thermal comfort, and facilitate city walkability. The methods and findings are expected to help identify the most effective UHI mitigation strategies and improve urban planning and design. |
| Rights: | All rights reserved |
| Access: | open access |
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