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The estimation of the vertical components of built-up areas from free Digital Elevation Model (DEM) global data filtered by multi-scale convolutional, morphological and textural transforms are generalized at the spatial resolution of 250 meters using linear least-squares regression techniques. Six test cases were selected: Hong Kong, London, New York, San Francisco, Sao Paulo, and Toronto. Five global DEM and two DEM composites are evaluated in terms of 60 combinations of linear, morphological and textural filtering and different generalization techniques. Four generalized vertical components estimates of built-up areas are introduced: the Average Gross Building Height (AGBH), the Average Net Building Height (ANBH), the Standard Deviation of Gross Building Height (SGBH), and the Standard Deviation of Net Building Height (SNBH). The study shows that the best estimation of the net GVC of built-up areas given by the ANBH and SNBH, always contains a greater error than their corresponding gross GVC estimation given by the AGBH and SGBH, both in terms of mean and standard deviation. Among the sources evaluated in this study, the best DEM source for estimating the GVC of built-up areas with univariate linear regression techniques is a composite of the 1-arcsec Shuttle Radar Topography Mission (SRTM30) and the Advanced Land Observing Satellite (ALOS) World 3D–30 m (AW3D30) using the union operator (CMP_SRTM30-AW3D30_U). A multivariate linear model was developed using 16 satellite features extracted from the CMP_SRTM30-AW3D30_U enriched by other land cover sources, to estimate the gross GVC. A RMSE of 2.40 m and 3.25 m was obtained for the AGBH and the SGBH, respectively. A similar multivariate linear model was developed to estimate the net GVC. A RMSE of 6.63 m and 4.38 m was obtained for the ANBH and the SNBH, respectively. The main limiting factors on the use of the available global DEMs for estimating the GVC of built-up areas are two. First, the horizontal resolution of these sources (circa 30 and 90 meters) corresponds to a sampling size that is larger than the expected average horizontal size of built-up structures as detected from nadir-angle Earth Observation (EO) data, producing more reliable estimates for gross vertical components than for net vertical component of built-up areas. Second, post-production processing targeting Digital Terrain Model specifications may purposely filter out the information on the vertical component of built-up areas that are contained in the global DEMs. Under the limitations of the study presented here, these results show a potential for using global DEM sources in order to derive statistically generalized parameters describing the vertical characteristics of built-up areas, at the scale of 250x250 meters. However, estimates need to be evaluated in terms of the specific requirements of target applications such as spatial population modelling, urban morphology, climate studies and so on.

Local climate zone (LCZ) maps that describe the urban surface structure and cover with consistency and comparability across cities are gaining applications in studies of urban heat waves, sustainable urbanization and urban energy balance. Following the standard World Urban Database and Access Portal Tools (WUDAPT) method, we generated LCZ maps for over 20 individual cities and 3 major economic regions in China. Based on the confusion matrices constructed by manual comparison between the predicted classes and ground truths, we highlight the following: (1) notable variation in overall accuracies (i.e., 60%–89%) among cities were observed, which was mainly due to class incompleteness and distinct proportions of natural landscapes; (2) building classes in selected cities were poorly classified in general, with a mean accuracy of 48%; (3) the sparsely built class (i.e., LCZ 9), which is rare in the selected Chinese cities, had the lowest classification accuracy (32% on average), and the class of low plants had the widest accuracy range. The findings indicate that the standard WUDAPT method alone is insufficient for generating LCZ products that demonstrate practical value, especially for built-up areas in China, and the misclassification is largely caused by the lack of building height data. This result is confirmed by a refinement test, in which the urban DEM retrieved from Sentinel-1 data with radar interferometry technique was used. The study shows a detailed and comprehensive assessment of applying the WUDAPT method in China and a feasible refinement strategy to improve the classification accuracy, especially for the built-up types of LCZ. The study could serve as a useful reference for generating quality-ensured LCZ maps. This study also examines and explores the relationship between socio-economic status and LCZ products, which is essential for further implementations.

Outdoor thermal comfort studies have proved that urban design has a great influence on pedestrians’ thermal comfort and that its assessment helps one to understand the quality and usage of the pedestrian environment. However, the majority of outdoor thermal comfort studies perceive pedestrian thermal comfort as “static”. The dynamic multiple uses of urban spaces and the highly inhomogeneous urban morphology in high-density cities of the tropics are seldom considered, which leads to a lack of understanding about how pedestrians respond to the changes of the outdoor environment. This study contributes to the understanding of the dynamic thermal comfort using a longitudinal survey that was conducted to obtain information about how thermal sensation changes throughout the walking route and how it is affected by micro-meteorological conditions and the urban geometry. The large variations in micro-meteorological conditions throughout the walking routes are predominantly influenced by the urban geometry. Additionally, the spatial pattern of thermal sensation varies based on the weather conditions, emphasizing the need to account for such variations in the assessment of pedestrian thermal comfort. The results also show that thermal sensation was associated with participants’ short-term thermal experience (2–3 min) and that the urban geometry plays an important role in the time-lag effect of meteorological variables on thermal sensation. The findings of this study contribute to improving urban geometry design in order to mitigate the thermal discomfort and create a better pedestrian environment in high-density cities.

Urban heat islands (UHIs), usually defined as temperature differences between urban areas and their surrounding rural areas, are one of the most significant anthropogenic modifications to the Earth’s climate. This study applies the extreme value theory to model and detect trends in extreme UHI events in Hong Kong, which have rarely been documented. Extreme UHI events are defined as UHIs with intensity higher than a specific threshold, 4.8 for summer and 7.8 °C for winter. Statistical modeling based on extreme value theory is found to permit realistic modeling of these extreme events. Trends of extreme UHI intensity, frequency, and duration are introduced through changes in parameters of generalized Pareto, Poisson, and geometric distributions, respectively. During the 27-year study period, none of the quantities in winter analyzed in this study increased significantly. The annual mean summertime daily maximum UHI intensities, which are samples from a Gaussian distribution, show an increasing but nonsignificant linear trend. However, the intensity of extreme UHI events in summer is increasing significantly, which implies that the risk of mortality and heat-related diseases due to heat stress at night (when the daily maximum UHI occurs) in summer is also increasing. The warming climate has threatened and will continue to threaten inhabitants of this subtropical high-density city. Strategies for adaptation to and mitigation of climate change, such as adding greenery and planning a city with good natural ventilation, are needed.

Doppler wind LiDAR (Light Detection And Ranging) makes use of the principle of optical Doppler shift between the reference and backscattered radiations to measure radial velocities at distances up to several kilometers above the ground. Such instruments promise some advantages, including its large scan volume, movability and provision of 3-dimensional wind measurements, as well as its relatively higher temporal and spatial resolution comparing with other measurement devices. In recent decades, Doppler LiDARs developed by scientific institutes and commercial companies have been well adopted in several real-life applications. Doppler LiDARs are installed in about a dozen airports to study aircraft-induced vortices and detect wind shears. In the wind energy industry, the Doppler LiDAR technique provides a promising alternative to in-situ techniques in wind energy assessment, turbine wake analysis and turbine control. Doppler LiDARs have also been applied in meteorological studies, such as observing boundary layers and tracking tropical cyclones. These applications demonstrate the capability of Doppler LiDARs for measuring backscatter coefficients and wind profiles. In addition, Doppler LiDAR measurements show considerable potential for validating and improving numerical models. It is expected that future development of the Doppler LiDAR technique and data processing algorithms will provide accurate measurements with high spatial and temporal resolutions under different environmental conditions.

Refugees often face increased risks of poor perinatal health outcomes compared to native-born individuals and non-refugee immigrants. However, limited research has explored how birth outcomes vary across refugee subgroups in Canada, especially compared to economic immigrants and among refugee groups themselves. This study aimed to (1) compare the risk of preterm birth (PTB), small-for-gestational-age (SGA), large-for-gestational-age (LGA), stillbirth, and infant mortality between refugee subgroups and economic immigrants, and (2) examine differences among Government-Assisted Refugees (GARs), Privately Sponsored Refugees (PSRs), and In-Canada Refugees (ICRs). This population-based study used data from the Migrant Maternal and Infant Morbidity and Mortality (MIMMM) dataset, including 706,620 singleton births from 2000 to 2017. Generalized estimating equation models calculated adjusted risk ratios (aRRs) for birth outcomes, accounting for maternal and immigration-related factors. All refugee subgroups had higher PTB (6.26-6.41 per 100 births) and LGA rates (8.65-9.17 per 100 births) but lower SGA rates (9.53-10.40 per 100 births) compared to economic immigrants (PTB: 5.95, LGA: 7.36, SGA: 10.96). After adjustment, GARs maintained higher PTB risks, and all refugee subgroups had lower SGA and higher LGA risks than economic immigrants. Within refugee subgroups, ICRs had higher SGA risks (aRR = 1.09; 95% CI: 1.04-1.14) than GARs, and PSRs (aRR = 1.22; 95% CI: 1.04-1.44) and ICRs (aRR = 1.28; 95% CI: 1.07-1.52) had higher stillbirth risks than GARs. Refugee women in Canada have higher risks of PTB and LGA births compared to economic immigrants. ICRs had higher risks of SGA births and stillbirths than other refugee subgroups but lower risks of SGA and stillbirths compared to economic immigrants. These disparities are partly explained by maternal and immigration-related factors. Further research is needed to better understand these factors and inform policies aimed at reducing health disparities among immigrant populations in Canada.

ABSTRACTBackgroundMost studies of disparities in birth and postnatal outcomes by parental birthplace combine all immigrants into a single group. We sought to evaluate heterogeneity among immigrants in Canada by comparing birth and postnatal outcomes across different immigration categories. MethodsWe conducted a population-based retrospective study using Statistics Canada data on live births and stillbirths (1993–2017) and infant deaths (1993–2018), linked to parental immigration data (1960–2017). We classified birthing parents as born in Canada, economic-class immigrants, family-class immigrants, or refugees, and evaluated differences in preterm births, small-for-gestational-age (SGA) and large-for-gestational-age (LGA) births, stillbirths, and infant deaths among singleton births by group. ResultsAmong 7 980 650 births, 1 715 050 (21.5%) were to immigrants, including 632 760 (36.9%) in the economic class, 853 540 (49.8%) in the family class, and 228 740 (13.4%) refugees. Compared with infants of Canadian-born birthing parents, infants of each of the 3 immigrant groups had higher risk of preterm birth, SGA birth, and stillbirth, but lower risk of LGA birth and neonatal death. Compared with infants of economic-class immigrants, infants of refugees had higher risk of early preterm birth (0.9% v. 0.8%, adjusted risk ratio [RR] 1.08, 95% confidence interval [CI] 1.01–1.15) and LGA birth (9.2% v. 7.5%, adjusted RR 1.12, 95% CI 1.10–1.15), but lower risk of SGA birth (10.2% v. 11.0%, adjusted RR 0.92, 95% CI 0.90–0.94), while infants of family-class immigrants had higher risk of SGA birth (12.2% v. 11.0%, adjusted RR 1.01, 95% CI 1.00–1.02). Risk of stillbirth, neonatal death, and overall infant death did not differ significantly among immigrant groups. InterpretationHeterogeneity exists in outcomes of infants born to immigrants to Canada across immigration categories. These results highlight the importance of disaggregating immigrant populations in studies of health disparities.

Prior studies from around the world have indicated that very high temperatures tend to increase summertime mortality. However possible effect modification by urban micro heat islands has only been examined by a few studies in North America and Europe. This study examined whether daily mortality in micro heat island areas of Hong Kong was more sensitive to short term changes in meteorological conditions than in other areas. An urban heat island index (UHII) was calculated for each of Hong Kong's 248 geographical tertiary planning units (TPU). Daily counts of all natural deaths among Hong Kong residents were stratified according to whether the place of residence of the decedent was in a TPU with high (above the median) or low UHII. Poisson Generalized Additive Models (GAMs) were used to estimate the association between meteorological variables and mortality while adjusting for trend, seasonality, pollutants and flu epidemics. Analyses were restricted to the hot season (June-September). Mean temperatures (lags 0-4) above 29 °C and low mean wind speeds (lags 0-4) were significantly associated with higher daily mortality and these associations were stronger in areas with high UHII. A 1 °C rise above 29 °C was associated with a 4.1% (95% confidence interval (CI): 0.7%, 7.6%) increase in natural mortality in areas with high UHII but only a 0.7% (95% CI: -2.4%, 3.9%) increase in low UHII areas. Lower mean wind speeds (5(th) percentile vs. 95(th) percentile) were associated with a 5.7% (95% CI: 2.7, 8.9) mortality increase in high UHII areas vs. a -0.3% (95% CI: -3.2%, 2.6%) change in low UHII areas. The results suggest that urban micro heat islands exacerbate the negative health consequences of high temperatures and low wind speeds. Urban planning measures designed to mitigate heat island effects may lessen the health effects of unfavorable summertime meteorological conditions.

Urban greenery is a natural solution to cool cities and provide comfort, clean air and significant social, health and economic benefits. This paper aims to present the latest progress on the field of greenery urban mitigation techniques including aspects related to the theoretical and experimental assessment of the greenery cooling potential, the impact on urban vegetation on energy, health and comfort and the acquired knowledge on the best integration of the various types of greenery in the urban frame. Also to present the recent knowledge on the impact of climate change on the cooling performance of urban vegetation and investigate and analyse possible technological solutions to face the impact of high ambient temperatures.