Kowloon Peninsula Research Articles

Traffic assignment optimization to improve urban air quality with the unified finite-volume physics-informed neural network

Emissions by road transportation constitute the major contributor of air pollutants to threat the public health, especially on mega cities with high-rise buildings and growing population. A practicable and economical remedy is assigning the traffic volume judiciously, termed traffic assignment optimization (TAO). Incorporating the computational fluid dynamics (CFD), this method provides precisely optimized traffic volumes under versatile meteorological conditions. However, the high-dimensional degree of freedoms (DoF) involved in CFD hampers its further application toward the large-scale problem where a massive urban area is considered. With the more complicated urban traffic network, the larger decision variable dimension also impedes the time-efficient acquisition of the optimization results. To alleviate this curse-of-dimensionality, the current work proposes an optimization framework with the surrogate model based on the unified finite-volume physics-informed neural networks (UFV-PINN). The UFV-PINN plays the dual role as the partial differential equation (PDE) solver and the surrogate model for pollutant concentration prediction. It reduces the DoF within the PDE solution process and enables the gradient-based optimization. The current work optimizes the average CO concentration and accumulative travel time in Kowloon peninsula of Hong Kong, using the multiple-gradient descent algorithm (MGDA). This optimization framework is tested with various working conditions. Results indicate that the proposed method attain high accuracy solutions, comparable to the heuristic algorithms. This study is the first attempt to incorporate UFV-PINN into the TAO with air quality consideration. Endowed with the differentiability by UFV-PINN, the framework will facilitate the TAO to provide precise suggestions toward large-scale problems.

CIM-WV: A 2D semantic segmentation dataset of rich window view contents in high-rise, high-density Hong Kong based on photorealistic city information models

Large-scale assessment of window views is demanded for precise housing valuation and quantified evidence for improving the built environment, especially in high-rise, high-density cities. However, the absence of a semantic segmentation dataset of window views forbids an accurate pixel-level assessment. This paper presents a City Information Model (CIM)-generated Window View (CIM-WV) dataset comprising 2,000 annotated images collected in the high-rise, high-density urban areas of Hong Kong. The CIM-WV includes seven semantic labels, i.e., building, sky, vegetation, road, waterbody, vehicle, and terrain. Experimental results of training a well-known deep learning (DL) model, DeepLab V3+ , on CIM-WV, achieved a high performance (per-class Intersection over Union (IoU) ≥ 86.23%) on segmenting major landscape elements, i.e., building, sky, vegetation, and waterbody, and consistently outperformed the transfer learning on a popular real-world street view dataset, Cityscapes. The DeepLab V3+ model trained on CIM-WV was robust (mIoU ≥ 72.09%) in Hong Kong Island and Kowloon Peninsula, and enhanced the semantic segmentation accuracy of real-world and Google Earth CIM-generated window view images. The contribution of this paper is three-fold. CIM-WV is the first public CIM-generated photorealistic window view dataset with rich semantics. Secondly, comparative analysis shows a more accurate window view assessment using DL from CIM-WV than deep transfer learning from ground-level views. Last, for urban researchers and practitioners, our publicly accessible DL models trained on CIM-WV enable novel multi-source window view-based urban applications including precise real estate valuation, improvement of built environment, and window view-related urban analytics.

An Urban Built Environment Analysis Approach for Street View Images Based on Graph Convolutional Neural Networks

Traditionally, research in the field of traffic safety has predominantly focused on two key areas—the identification of traffic black spots and the analysis of accident causation. However, such research heavily relies on historical accident records obtained from the traffic management department, which often suffer from missing or incomplete information. Moreover, these records typically offer limited insight into the various attributes associated with accidents, thereby posing challenges to comprehensive analyses. Furthermore, the collection and management of such data incur substantial costs. Consequently, there is a pressing need to explore how the features of the urban built environment can effectively facilitate the accurate identification and analysis of traffic black spots, enabling the formulation of effective management strategies to support urban development. In this study, we research the Kowloon Peninsula in Hong Kong, with a specific focus on road intersections as the fundamental unit of our analysis. We propose leveraging street view images as a valuable source of data, enabling us to depict the urban built environment comprehensively. Through the utilization of models such as random forest approaches, we conduct research on traffic black spot identification, attaining an impressive accuracy rate of 87%. To account for the impact of the built environment surrounding adjacent road intersections on traffic black spot identification outcomes, we adopt a node-based approach, treating road intersections as nodes and establishing spatial relationships between them as edges. The features characterizing the built environment at these road intersections serve as node attributes, facilitating the construction of a graph structure representation. By employing a graph-based convolutional neural network, we enhance the traffic black spot identification methodology, resulting in an improved accuracy rate of 90%. Furthermore, based on the distinctive attributes of the urban built environment, we analyze the underlying causes of traffic black spots. Our findings highlight the significant influence of buildings, sky conditions, green spaces, and billboards on the formation of traffic black spots. Remarkably, we observe a clear negative correlation between buildings, sky conditions, and green spaces, while billboards and human presence exhibit a distinct positive correlation.

Potential “downstream blocking” synergistic mechanism for urban warming in Kowloon Peninsula, Hong Kong

A notable environmental challenge at present is the occurrence of extreme heat events in many large cities such as Hong Kong. In this study, an idealized two-dimensional model for Kowloon is proposed to investigate the urban thermal environments in various wind conditions. The hourly weather is simulated using the Weather Research and Forecasting (WRF) model to evaluate the synergistic roles of urban heat island circulation, sea breeze and mountain slope wind in urban warming. The results highlight that certain background winds transform mountain slope winds into foehn-like winds that worsen the thermal environment in urban areas. These adverse effects are exacerbated in the presence of urban heat island circulation and sea breezes in Kowloon. This potential warming mechanism would lead to long-lasting high-temperature afternoons in urban areas, during which the region with the highest temperature experiences the lowest wind speed. A new theory termed “downstream blocking” is proposed, which clarifies how air masses descend after passing a mountain ridge when a downwind urban heat island exists. The findings can help explain the mechanisms of extreme heat events in Kowloon and provide novel perspectives for understanding the foehn-like wind effects in urbanized areas adjacent to low-altitude mountains.

Amplitude modulation of velocity fluctuations in the atmospheric flows over real urban morphology

Amplitude modulation (AM) quantifies the top-down interactions between the large-scale motions (LSMs) in the outer layer and the near-ground turbulence structures. They are important to the momentum transport and pollutant dispersion in urban atmospheric surface layers (ASLs). The dataset of large-eddy simulation over a densely built region in Kowloon Peninsula, Hong Kong, therefore, is adopted to investigate the AM of small-scale eddies by LSMs in the ASL over real urban morphology. Alike its smooth-wall counterpart, the small-scale eddies are (positively) amplitude modulated by the LSMs in most regions of the roughness sublayer (RSL). However, negative AM is unexpectedly found in the RSL on the building windward side in this study, illustrating the heterogeneity of the urban surface and the flow dynamics being affected aloft. In addition, strong sweep (u′ > 0 and w′ < 0) and ejection (u′ < 0 and w′ > 0) dominate the flows, respectively, in the positive and negative AM zones. In the positive AM zones, the large-scale sweep (uL′ > 0) leads to the surplus in the small-scale turbulence kinetic energy (TKE), while the large-scale ejection (uL′ < 0) brings a TKE deficit to the small-scale eddies. By contrast, the large-scale sweeps result in a TKE deficit to the small-scale eddies and the large-scale ejections result in a TKE surplus in the negative AM zones. These findings could help elucidate the AM over different building designs and urban morphology in cities, promoting the momentum transport and pollutant dispersion via proper city planning.

Bi-objective optimization of traffic assignment with air quality consideration via CFD-based surrogate model

Vehicular emissions form a major source to ambient air pollution, constituting the leading risk factor for public health globally. To mitigate this problem with sustainable urban mobility, the paper proposes an optimization framework to minimize the air pollutant concentrations at selected site(s), where the residents are susceptible to airborne hazards. Kowloon Peninsula, Hong Kong, is taken as the example. The on-road traffic volumes nearby are optimized to minimize the carbon monoxide (CO) concentrations as well as the accumulative travel time. The CO concentration is implicitly determined via the surrogate model (Gaussian process regression; GPR). Its dataset is established by the combination of traffic model, emission model, and computational fluid dynamics (CFD). The non-dominated sorting genetic algorithm II (NSGA-II) is adopted to solve the bi-objective optimization problem. The outcome helps advance traffic strategy with the newly proposed optimization objective, giving priorities to vulnerable recipients at selected sensitive locations. Enabling the capacity to directly evaluate the pollutant concentration, it is the first attempt to incorporate surrogate model for pollutant dispersion based on experimentally verified CFD results into traffic assignment. This framework will facilitate the transport authorities to assign the traffic volumes and address health equity issues in a more precise manner.

A Water Supply System in Kowloon Peninsula, Hong Kong in the 1890s.

A Water Supply System in Kowloon Peninsula, Hong Kong in the 1890s.

Wavelet analysis of the atmospheric flows over real urban morphology

Winds are the basic forces for atmospheric transport such as pollutant removal and pedestrian thermal comfort. The transport capability is commonly measured in terms of length and velocity scales. In this connection, the flows in the atmospheric surface layer (ASL) over the Kowloon Peninsula, Hong Kong (HK) are scrutinized by the large-eddy simulation (LES) to characterize the motion scales over real urban morphology. Apart from statistical analysis, the streamwise fluctuating velocity u′ is examined by both wavelet and energy spectrum in which a primary peak is consistently shown at streamwise wavelength 70 m ≤ λx ≤ 300 m. A secondary peak at a longer wavelength 800 m ≤ λx ≤ 3000 m, however, is unveiled by wavelet only. It denotes the existence of intermittent turbulence structures whose sizes are much larger than those of buildings. Further wavelet analysis reveals that majority energy-carrying eddies are enlarging (tens to hundreds of meters) from the roughness sublayer (RSL) to the inertial sublayer (ISL). Analogous to its smooth-wall and schematic rough-wall counterparts, the turbulence kinetic energy (TKE) over urban areas is peaked in the ISL which is carried by eddies of size 50 m ≤ λx ≤ 1000 m. The (horizontal) spatial distribution of energy-carrying eddies is further visualized to compare the crucial motion scales in the RSL and ISL. Finally, conditional sampling is used to demystify the contribution to vertical momentum flux u′w′ in terms of streamwise wavelength and quadrants. The results advance our fundamental understanding of ASL transport processes, fostering sustainable environmental policy.

The differential impacts of social deprivation and social fragmentation on suicides: A lesson from Hong Kong

IntroductionLittle research has conducted to examine the association between social deprivation and social fragmentation, overall and method-specific suicide risk, and how these associations may change over time. This study investigated the association between social deprivation and social fragmentation with overall and method-specific suicide in Hong Kong from 1999 to 2018. MethodsSuicide death data of each small tertiary planning unit (STPU) was obtained from the Census and Statistics Department of Hong Kong. Socio-economic characteristics in STPU level were obtained from Census and Bi-census. Exploratory principal component analysis was used to construct the social deprivation (SDI) and social fragmentation indices (SFI) based on the socio-economic characteristics. Bayesian hierarchical modelling was conducted to explore the association between SDI and SFI with overall and method-specific suicide over time, controlling for population density and male-to-female ratio. ResultsHigher risk of suicide was generally observed around Kowloon Peninsula and some parts in the Northern, Northwestern and Southwestern areas depending on methods. The effect of SDI and SFI on suicide risk varied by years and methods. In 2014–2018, for every 10% increase in SDI, the suicide risk for overall, jumping, hanging, and charcoal burning elevated by 22% (95%Crl = 10%–37%), 26% (95%Crl = 12%–41%), 31% (95%Crl = 14%–51%), and 21% (95%Crl = 4%–42%) respectively. ConclusionSpatial variations and effects of SDI and SFI on overall and method-specific suicide risks varied by different periods. SDI was observed to be a stronger factor in the recent years. Situations should be monitored, and interventions should be implemented and adjusted accordingly to the changes.

Влияние отдельных нормативно-правовых актов материкового Китая на политическую ситуацию в Гонконге

The article's purpose is to assess the response actions taken by the British Empire and the current Chinese government to stop the Hong Kong protests, as well as to identify the "inherited" reasons that contribute to the persistence of protest activity. The author hypothesizes that the difference in the British Empire (before 1997) and the Chinese reactionary actions on public unrest formed the prerequisites for the continuation of protest activity in the region. Comparative, retrospective and normative scientific research methods were used in the article. The author analyzed the British and Chinese reactionary measures to the political demands of the Kowloon Peninsula residents, and also reviewed the law "On National Security in Hong Kong" adopted by mainland China. As a result, he came to the conclusion that the political concessions made by the British Empire during the long colonial period in Hong Kong could have formed among its inhabitants the conviction of the large-scale protests necessity to achieve their political demands. In turn, the current Chinese authorities' actions contradict Hong Kong people's beliefs and cause the rejection of "socialism with Chinese specifics". The article's theoretical significance lies in the identification of Hong Kong resident's specific behavioral attitudes "inherited" from English citizenship, which are one of the reasons for regular protests in the region.

The effect of background wind on summertime daily maximum air temperature in Kowloon, Hong Kong

The increased intensity of extreme weather events (e.g., heatwaves) that is predicted to occur due to global climate change could significantly impact human health, biodiversity, and infrastructure integrity in cities. As one of the most densely constructed cities in the world, Hong Kong has been experiencing increasingly intense heatwaves in recent years. However, the city presents a challenging site for studying urban climate due to its complex topography. Using observed weather data for clear summer (June to August) days from 2000 to 2020, we examine the relationship between background wind and daily maximum temperature in Kowloon, Hong Kong, and investigate how this relationship is affected by geographical location, land cover, and topography. We reveal the distribution of near-surface wind fields under calm weather conditions, which provides a basis for the analysis of relationship between background wind and maximum temperature in urban areas under windy conditions. We find that the maximum surface air temperature in coastal regions is significantly influenced by the background wind direction. For weather stations located in the Kowloon Peninsula, a larger background wind speed is associated with a faster increase in daily maximum temperature when the background temperature rises. We find that the mountain warming effect is influential in areas at the foot of a mountain, even though the maximum terrain height is only approximately 500 m a.s.l. These findings on the daily maximum temperature behavior under different background wind conditions provide a possible way to predict extreme high-temperature patterns in different regions of Hong Kong.

Statistical analysis of the organized turbulence structure in the inertial and roughness sublayers over real urban area by building-resolved large-eddy simulation

Dynamics and organized turbulence structure in the atmospheric boundary layer (ABL) over a real urban area, Mong Kok neighborhood in Kowloon Peninsula, Hong Kong, is investigated using the large-eddy simulation (LES) to enrich the transport mechanism. The urban morphology is explicitly resolved and the LES results are validated by wind tunnel measurements. Wind speed <u‾>/U∞ profiles manifest the inflections and zero-plane displacement d for 2 to 3 times the average building height Have, signifying higher blockage (stronger shear) than idealized geometries. The enhanced mixing induced by real urban morphology leads to faster, more uniform flows in the roughness sublayer (RSL) than those extrapolated from the inertial sublayer (ISL) by the conventional logarithmic law-of-the-wall (log-law). Higher-order moments signify that RSLs and ISLs feature, respectively, tiny, accelerating, spurlike downdraft (skewness Su > 0 and Sw < 0) and frequent, decelerating, bulky updraft (Su < 0 and Sw > 0). Besides, quadrant analysis shows that RSL ejection Q2 (u" < 0 and w" > 0) occurs more frequently (but contributes less to momentum flux <u"w">) than does sweep Q4 (u" > 0 and w" < 0). Conditional sampling further demonstrates that RSL (ISL) consists of majority large-scale Q4 (Q2) and small-scale Q2 (Q4). Comparing both the occurrence Ti,η of and contribution Si,η from Q2 and Q4 contrasts their roles in the transport process. The motion scale η (around 4 times of the average momentum flux) differentiates the dominance between Q2 and Q4 over a real, dense city, improving the fundamental understanding. (250 words)

Identifying the optimal travel path based on shading effect at pedestrian level in cool and hot climates

As shading affects thermal environments and intentions of outdoor activities, studying shaded areas is necessary to increase pedestrian travel choice. This study provided a new insight by calculating the shading length based on LiDAR data and then identifying the optimal pathway for demonstrating the shading effects at different times in summer and winter. The Kowloon Peninsula of Hong Kong was selected as the study area. Results revealed that streets oriented N-S and NE-SW before and at noon and N-S and E-W after noon are beneficial for strong shading effects in summer, and streets oriented NE-SW and NW-SE during 8:00–10:00 and 14:00–16:00 and streets oriented N-S and NW-SE at 12:00 are suitable for travel with intense solar radiation in winter. The area percentages of overlapping areas of pathways oriented E-W and N-S at different times in summer and winter demonstrated what times pedestrians can choose to go through the overlapping pathways (e.g. pathways oriented E-W during 8:00–10:00 and during 14:00–16:00) or stay in the overlapping open spaces. The more overlapping pathways based on the random points were found at different times in winter than summer. The study reflects when and in which public spaces individuals can walk or perform outdoor activities.

Assessing economic, social and environmental impacts on housing prices in Hong Kong: a time-series study of 2006, 2011 and 2016.

Given Hong Kong’s unique high-density urban environment and limited land resources, more and more general public has been concerned about the living quality. Based on three waves of census data (2006, 2011 and 2016), combined with our spatial–temporal urban environmental database consisting of three local datasets of urban climate and air quality, this paper assesses the impacts of social, economic and environmental factors on the logarithm of housing prices in Hong Kong through linear regression analysis. Specifically, both supply- and demand-side economic factors have significant impacts on housing prices. Demographic factors are not as significant as expected in affecting housing prices. Transportation factors have more significant effects in the short run than in the long run. Environmental factors, including the number of hot night hours, Annual Air Quality Index (AAQI) of nitrogen dioxide (NO2) and particulates with particle sizes less than 10 microns (PM10), significantly affect housing prices over time. The results have important implications: current policy instruments to prevent housing price escalation are focused on increasing property tax or land supply (economic factors), while little attention is paid to social or environmental factors, which are geographically heterogeneous. Our findings suggest that housing provision in the New Territories may be a feasible solution to alleviate the housing crisis as its demographic pattern, transportation connectivity and air quality are significantly different from Hong Kong Island or Kowloon Peninsula. In regard to urban environmental problems brought by the high-density development in Hong Kong despite land-use saving, intensified urban infrastructure and promotion of public transportation, our study contributes to the understanding of its housing price dynamics from a more holistic perspective by comparing the impacts of economic, social and environmental factors.

High-resolution mesoscale simulation of the microclimatic effects of urban development in the past, present, and future Hong Kong

Anthropogenic modification of the natural environment has caused significant impacts on the local atmosphere and far-reaching changes to the global climate. Taking Hong Kong as a case study, high-resolution (250 m) mesoscale simulations are conducted using Meso-NH coupled with the multi-layer Town Energy Balance to investigate the effects of past (early 1960s), present (2018), and future (late 2040s) urban developments on the city's surface energy balance, heat island, boundary layer structure, and heat stress during a prolonged heatwave event. Overall, horizontal and vertical urban expansion has caused the urban areas to become warmer, drier, less ventilated, and more susceptible to hot nights. The dense built-up urban core in the Kowloon peninsula is also found to deepen the urban boundary layer and enhance the coastal urban heat island circulation. Reclaimed land exhibits the largest differences in 2-m air temperature relative to a no urban scenario due to the drastic change in surface thermal properties. Areas downwind of the planned artificial islands in East Lantau are expected to experience warmer and calmer conditions due to the altered wind field. Study findings raise awareness regarding the increasingly long durations of strong heat stress in urban areas and the need for heat stress mitigation.

Turbulent flows over real heterogeneous urban surfaces: Wind tunnel experiments and Reynolds-averaged Navier-Stokes simulations

Wind tunnel experiment and steady-state Reynolds-averaged Navier-Stokes (RANS) approaches are used to examine the urban boundary layer (UBL) development above Kowloon Peninsula, Hong Kong Special Administrative Region (HKSAR). The detailed urban morphology is resolved by computational fluid dynamics (CFD) and is fabricated by 3D-printing (reduced scale) for wind tunnel experiments. Different from the majority existing results based on idealized, homogeneous urban geometries, it was found that the wind and turbulence in the UBL over downtown Kowloon are characterized by the wake behind several high-rise buildings. In particular, local maxima of turbulence kinetic energy (TKE) and shear stress are found at the roof level of those high-rise buildings. In the downstream region where the flows are already adjusted to the urban surfaces, the urban roughness sublayer (URSL) can be further divided into two layers based on the structures of the mixing length lm, effective drag Dx and dispersive stress. In the lower URSL (z ≤ 100 m), lm is rather uniform, and the Reynolds stress and dispersive stress are comparable. In the upper URSL (100 m ≤ z ≤ 300 m), on the contrary, lm is peaked at the mid-height and the magnitude of dispersive stress is smaller than that of the Reynolds stress (< 30%). The effective drag Dx is negligible in the upper URSL.

Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures

AbstractThe surface urban heat island intensity (SUHII) when using nadir‐viewing radiometric and complete surface temperature (Tr and Tc) was evaluated. The urban areas of the Kowloon peninsula and Hong Kong Island were selected and four daytime Landsat TM images and two nighttime ASTER images were collected to retrieve Tr and then model Tc based on a semi‐empirical model. SUHIIs were estimated using both the retrieved Tr and modelled Tc. High spatial resolution (HR) airborne thermal images (0.2 m) observed at 12:10 noon on Oct 24, 2017 were used to retrieve Tc directly. Results based on HR data and satellite data were consistent and indicated that the geometry of the built‐up space had a larger impact on SUHII when using Tc (SUHIIc) than Tr (SUHIIr). During daytime SUHIIc decreased while SUHIIr showed a very slight increase with building density. Both SUHIIc and SUHIIr decreased with higher building height but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr decreased with increasing building height variance and increased with increasing sky view factor (SVF). The rate of decrease with building height variance for SUHIIc was larger than SUHIIr. The rate of increase of SUHIIc with SVF was higher than SUHIIr. During nighttime, geometry effects on SUHIIc and SUHIIr were different from daytime. Both SUHIIc and SUHIIr increased with building density, while the rate of increase of SUHIIc with building density, as well as with building height, was much higher than SUHIIr. Both SUHIIc and SUHIIr decreased with SVF, but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr initially increased with building height variance and then remained approximately constant. We also evaluated the UHI intensity: SUHIIc was much closer to UHII than SUHIIr. Overall, building geometry had larger impact on SUHIIc than on SUHIIr, that is, SUHIIc is more representative of urban climate than SUHIIr.

Roughness sublayer flows over real urban morphology: A wind tunnel study

Atmospheric surface layer (ASL) consists of the inertial sublayer (ISL) and the roughness sublayer (RSL) with different dynamics. This study characterizes the ASL flows over real urban morphology using wind tunnel experiments. The building models of downtown Kowloon Peninsula, Hong Kong are fabricated by 3D printing. The vertical profiles (3 × 45 numbers) on three vertical planes in the streamwise direction are selected for velocity measurements by constant-temperature (CT) hot-wire anemometry (HWA). There exist noticeable variations of mean wind speed u‾, fluctuating velocities u’’ and w’’ together with vertical momentum flux u’’w’’ in the ISL and RSL over urban areas. On the plane with maximum drag coefficient Cd (25% higher than that on the other two), the RSL is thicker by 10% in which the winds evolve in response to individual buildings. A new analytical solution is derived to improve the prediction of ASL mean wind speeds whose root-mean-square error (RMSE) is reduced by 10 times. Its key variable, the RSL constant, converges asymptotically μ = 1.7 for urban setting. Unlike the ISL, turbulence statistics show that the RSL velocities are positively skewed (Su > 0) with high kurtosis (Ku > 3). The occurrence of ejection Q2 (detrainment; 32%–37%) is more frequent than sweep Q4 (entrainment; 30%–32%). Whereas, high-speed Q4 contributes most (0.2u’’w’’ to 0.4u’’w’’) to the RSL vertical momentum flux among the four quadrants. It is thus suggested that fresh air entry is driven by spurlike downdrafts while street-level aged air is removed by massive uprising current.

Fine-scale mapping of an evidence-based heat health risk index for high-density cities: Hong Kong as a case study

The most recent extreme heat recorded in Europe re-alerts the world to the threat of heat stress. Future extreme heat events are reported to be more frequent, long-lasting, and intense. The intense exposure to hot temperatures can cause an excess of heat-related deaths, leading to an increasing risk of heat-related health. In reducing Heat Health Risk (HHR), the use of fine-scale evidence-based mapping of heat-related health risk index (HHRI) and its underlying contributors is essential for policy-making and site-specific action plans. However, its use is still considered to be at an early stage, especially in high-density cities like Hong Kong. This study conducted a spatially explicit assessment of HHR in Hong Kong and constructed a HHRI based on indicators categorized through Principle Component Analysis (PCA) into four meaningful components representing social/language, social isolation, socioeconomic, and urbanization/environmental risks. The applicability of the index was validated against heat-related mortality data at the community level. The community-level maps of HHRI and its subcomponents revealed that portions of Kowloon Peninsula had always suffered exceptionally high HHR ten years ago and after, but the hot spots and problematic communities experienced displacement and the dominant underlying factors of their HHR also varied. Results also showed that HHRI correlated fairly well with the heat-related deaths ratio (R2 = 0.60) at the community level for most of Hong Kong (62.33% of all communities that contain 81.69% of total population). Our analysis results helped generate an evidence-based index to assess HHR in high-density cities like Hong Kong and provided fine-scale maps of the index and its subcomponents, with the aim of benefiting site-specific policy making and optimizing the existing action plans.

Increasing incidence of oral cancer in Hong Kong-Who, where…and why?

Oral squamous cell carcinoma (SCC) is a lethal and deforming disease of rising incidence and global significance; 600000 new cases are seen each year, including 40000 in China. Despite advances in management, 50% of patients die within 5years of diagnosis. Cancer is the leading cause of death in Hong Kong, with the Hong Kong Cancer Registry (HKCR) confirming a 2% increase in new cases each year, and oral SCC the tenth leading cause of cancer death in males. Strategies to improve clinical outcome require identification and early intervention in the "high-risk" population. Unfortunately, demographic information is limited in HKCR making it difficult to undertake accurate population-based studies. This study aimed to profile contemporaneous demographics of oral cancer within the Hong Kong population. Following local ethical approval, the Hong Kong Hospital Authority (HA) database was accessed to identify new cases of oral SCC diagnosed and treated during an 18-year period (January 2000 to December 2017). A total of 6706 oral cavity SCC cases were identified: 4291 male and 2415 female patients (with a mean age of 64.14years). A trend for increasing number of cases each year was seen, with most patients presenting to hospitals on the Kowloon Peninsula and Hong Kong Island. The tongue was the most commonly affected oral site in 3168 patients, with tonsil (863), buccal mucosa (539) and floor of mouth (409) less common. Mean survival time between initial diagnosis and death was 1.95years; patients with hard palate and oropharyngeal SCC survived the shortest period, whilst labio-buccal and vestibular cases exhibited significantly longer survival (P<0.0001). Whilst useful HA data are available regarding age, sex, site and outcome, there is a need for further improvement in demographic profiling to characterise the "high-risk" oral cancer population in Hong Kong and to facilitate targeted early therapeutic intervention.