Search

Objectives Mental health and neurocognitive conditions are important causes of hospitalization among immigrants, though patterns may vary by immigrant category, world region of origin, and time since arrival in Canada. This study uses linked administrative data to explore differences in mental health hospitalization rates between immigrants and individuals born in Canada. Methods Hospital records from the Discharge Abstract Database and the Ontario Mental Health Reporting System for 2011 to 2017 were linked to the 2016 Longitudinal Immigrant Database and to Statistics Canada’s 2011 Canadian Census Health and Environment Cohort. Age-standardized hospitalization rates for mental health–related conditions (ASHR-MHs) were derived for immigrants and the Canadian-born population. ASHR-MHs overall and for leading mental health conditions were compared between immigrants and the Canadian-born population, stratified by sex and selected immigration characteristics. Quebec hospitalization data were not available. Results Overall, immigrants had lower ASHR-MHs compared to the Canadian-born population. Mood disorders were leading causes of mental health hospitalization for both cohorts. Psychotic, substance-related, and neurocognitive disorders were also leading causes of mental health hospitalization, although there was variation in their relative importance between subgroups. Among immigrants, ASHR-MHs were higher among refugees and lower among economic immigrants, those from East Asia, and those who arrived in Canada most recently. Conclusion Differences in hospitalization rates among immigrants from various immigration streams and world regions, particularly for specific types of mental health conditions, highlight the importance of future research that incorporates both inpatient and outpatient mental health services to further understand these relationships.

Canadian immigrants from countries where the hepatitis B virus (HBV) and hepatitis C virus (HCV) are endemic may be at higher risk of liver-related disease than Canadian-born residents. This study compared HBV- and HCV-related hospitalizations in Canadian immigrants (arriving from 1980 to 2013) and long-term residents (Canadian-born population and pre-1980 immigrants) and aimed to describe the burden of disease in both groups.Based on the 2004/2005-to-2013/2014 hospital Discharge Abstract Database linked to the 1980-to-2013 Longitudinal Immigration Database, this descriptive cross-sectional study examined the distribution of HBV- and HCV-related hospitalizations, lengths of stay, comorbidities, and sequelae incurred by immigrants and long-term residents in Canada. With a linkage rate of 85%, 5,854,949 immigrants were included in the study. Proportions of HBV- and HCV-related hospitalizations attributable to immigrants were calculated.By birth country risk level, 22% of HBV-related hospital events among recent immigrants, and 20% of those related to HCV, were among people from high-risk countries. Proportionally, fewer immigrants had comorbidities than long-term residents. The top two hospital-related sequelae in both groups were cirrhosis and ascites, and liver cancer. While immigrants made up 16% of the Canadian population, they incurred 37% of HBV-related hospitalizations and 9% of HCV-related hospitalizations, giving ratios of hepatitis-related hospitalizations relative to the population share of 2.3 (95% confidence interval [CI]: 2.2 to 2.5) and 0.5 (95% CI: 0.5 to 0.6) respectively. These ratios were higher among seniors, at 4.4 (95% CI: 3.9 to 4.9) and 2.3 (95% CI: 1.9 to 2.6), respectively.Immigrants can require hospitalization for hepatitis in Canada, especially for HBV. These results may inform health screening for HBV or HCV in the Canadian immigration context.

Spatiotemporal monitoring of urban CO

Air temperature is a crucial variable in urban climate and relevant to many studies, such as urban heat islands, heat waves, climate change, energy consumption, and health-related heat exposure risk studies. Previous studies used land surface temperature (LST) and inversion methods to obtain air temperature maps with spatial detail or used weather station observations and spatial interpolation to obtain air temperature maps with high temporal resolution. However, fine spatial detail and high temporal resolution have not been resolved simultaneously. Moreover, there are differences in LST and air temperature definitions, which cannot be equated. Therefore, in this study, we carried out hourly air temperature mapping at 1-km resolution over a multi-year summer period for Guangdong Province, China, employing machine learning algorithms as well as meteorological and landscape data. The meteorological data were hourly observations from 86 weather stations in Guangdong containing variables such as air temperature, relative humidity, precipitation, barometric pressure, and wind speed. The landscape data were mainly from the landscape indices calculated based on local climate zone (LCZ) maps, mapped via Google Earth Pro and Google Earth Engine. Then, we employed the random forest (RF) algorithm for the hourly air temperature mapping. The validation results showed that the hourly air temperature maps achieved good accuracy from 2008 to 2019 with a mean R2 value of 0.8001. The importance assessment of the driving factors showed that meteorological factors, especially relative humidity, make the most outstanding contribution to air temperature mapping. Simultaneously, the landscape factors also played a non-negligible role. Further analysis revealed that the maps steadily maintained high accuracy at nighttime (20:00-7:00), which is the most critical period for studying urban heat islands. In addition, the air temperature patterns showed a correlation with the landscape. Air temperatures in contiguous mountainous areas with dense trees were significantly lower than those in the plains. Moreover, there is a correlation between nighttime air temperature changes and urban morphology, and urban-rural differences exist simultaneously. Air temperatures tend to fall more slowly in the core of metropolitan areas than in the urban fringe. Overall, this study employed machine learning to reliably improve the temporal resolution of air temperature mapping with more spatial detail. Furthermore, it reveals spatially explicit air temperature patterns in and around cities at different times in a day during the summer. In addition, it provides a new valuable and advantageous dataset for relevant applications.

The creation of a psychologically friendly outdoor environment has important quality-of-life implications for urban residents who live in cities with extremely high population density, such as Hong Kong. Prospect Refuge Theory is the most widely recognized theory that explains environmental emotional influence by referring to urban planning and architecture, and it can be quantified by applying isovist indicators. We aim to (a) conduct field measurements that record dynamic psycho-physiological stress, (b) calculate isovist indicators by introducing a new indicator-isovist time difference and then analyse their effects on stress, and (c) draw on findings to provide recommendations for urban planning and design. The experiment is conducted for the first time in a high-density city where 30 participants are asked to walk a predefined route. Each participant wears a portable smart band that records skin conductance response and a global positioning system (GPS) that records geographic coordinates. The results demonstrate that (1) an open space with a visual target set at a distance is the dominant factor that creates positive emotions in Hong Kong; (2) the new indicator-isovist time difference (D1) is valuable, as it is more significantly related to stress than the isovist level; (3) the living environment and cultural differences play an important role in the final result, i.e. people in Europe prefer relatively closed spaces while people in Hong Kong feel stress when the space is highly enclosed.

Air temperature is a crucial variable of urban meteorology and is essential to many urban environments, urban climate and climate-change-related studies. However, due to the limited observational records of air temperature and the complex urban morphology and environment, it might not be easy to map the hourly air temperature with a fine resolution at the surface level within and around cities via conventional methods. Thus, this study employed machine learning (ML) algorithms and meteorological and landscape data to develop hourly air temperature mapping techniques and methods at the 1-km resolution over a multi-year warm seasons period. Guangdong Province, China was selected for the case study. Random forest algorithm was employed for the hourly air temperature mapping. The validation results showed that the hourly air temperature maps exhibit good accuracy from 2008 to 2019, with mean R

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.

Poor air quality has been a major urban environmental issue in large high-density cities all over the world, and particularly in Asia, where the multiscale complex of pollution dispersal creates a high-level spatial variability of exposure level. Investigating such multiscale complexity and fine-scale spatial variability is challenging. In this study, we aim to tackle the challenge by focusing on PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm,) which is one of the most concerning air pollutants. We use the widely adopted land use regression (LUR) modeling technique as the fundamental method to integrate air quality data, satellite data, meteorological data, and spatial data from multiple sources. Unlike most LUR and Aerosol Optical Depth (AOD)-PM2.5 studies, the modeling process was conducted independently at city and neighborhood scales. Correspondingly, predictor variables at the two scales were treated separately. At the city scale, the model developed in the present study obtains better prediction performance in the AOD-PM2.5 relationship when compared with previous studies (R2¯ from 0.72 to 0.80). At the neighborhood scale, point-based building morphological indices and road network centrality metrics were found to be fit-for-purpose indicators of PM2.5 spatial estimation. The resultant PM2.5 map was produced by combining the models from the two scales, which offers a geospatial estimation of small-scale intraurban variability.

Raw earth is the main material used in traditional architecture in Southwest rural China because it is inexpensive, accessible and exhibits remarkable thermal performance. However, local residents stopped implementing traditional rammed earth building technology because of several limitations. An innovative rammed earth construction approach suitable for Southwest rural China has been developed by One University One Village (1U1V) Team. The “local material, local technology, local labour” principle and the “high-science-low-technology” strategy has been used to improve the safety, quality and dignity of the living environment without adding substantial environmental load (negative aspects of environmental impact). The Terra Centre has been built in Kunming as the working base to research, promote, train and knowledge transfer. This holistic strategy creatively mended the long-term environmental, economic, and social sustainable development of poor rural areas and contributed to the local endogenous development significantly. It also responds to multiple targets of the 17 Sustainable Development Goals (SDGs).

As Canadian immigration levels increase, knowledge concerning immigrant health becomes increasingly important for health system policy and planning. This study compares the rate of all-cause hospitalization among immigrants with that of their Canadian-born counterparts.Using records from the Discharge Abstract Database (2004/2005 to 2016/2017) and the Ontario Mental Health Reporting System (2006/2007 to 2017/2018) linked to the 2016 Longitudinal Immigration Database, this study compared the age-standardized hospitalization rates (ASHRs) among immigrants with those of the Canadian-born population; the latter were obtained from a linkage based on the 2011 National Household Survey. Comparisons were made at the International Classification of Diseases chapter level by immigrant landing year, admission category and world region of birth. Quebec data were not available.Overall, ASHRs among immigrants were lower than for the Canadian-born population. Immigrants in the economic class had the lowest ASHR, followed by those in the family class and among refugees. After pregnancy was excluded, leading hospitalization causes were similar for immigrants and the Canadian-born population, where top causes included digestive system and circulatory diseases, injuries, and cancer. In male and female immigrants, the ASHRs were lowest among those from East Asia. By landing year, males arriving earlier had the highest ASHR compared with the most recent arrivals. When pregnancy was excluded and while the differential in ASHRs among females by landing year remained, the magnitude was smaller.These results corroborate those from previous studies suggesting a healthy immigrant effect, but also reveal heterogeneity in ASHRs within the immigrant population. They provide a baseline for comparison of health status between populations, which enables further monitoring and informs health-system policy and planning.

Climate warming, rapid economic development, and urbanisation in (sub)tropical regions lead to increasing electricity demand for building air-conditioning that could jeopardise the efforts of decarbonisation required to meet the climate change mitigation goals. This study investigates two strategies to reduce building energy consumption due to air-conditioning: 1) the bottom-up adoption of an Adaptive Thermal Comfort (ATC)-based cooling setpoint temperature and 2) the top-down implementation of efficient District Cooling Systems (DCS). The subtropical high-density city of Hong Kong is chosen for case study since detailed data on the city's current and realistic future urban form and function are available. Numerical simulations representing the feedback between urban climate and building energy consumption are conducted by employing a mesoscale atmospheric model coupled to an urban climate and building energy model for a scenario of future (mid-21st century) Hong Kong. A prolonged high temperature event representative of future extreme conditions is simulated, during which the ATC and DCS strategies reduce building cooling energy consumption by 9.7% and 5.9%, respectively. The ATC has almost no effect on the local meteorological conditions, whereas the DCS reduces daytime sensible heat flux by up to 600 W/m

Few quantitative studies have used national-level data to examine access to mental health consultation (MHC) by immigrants in Canada, and even fewer studies investigate MHCs using the following variables: immigrant admission category, duration in Canada since landing and world source regions. This study examines MHCs by immigrants and refugees-compared with those of Canadian-born respondents-while controlling for self-reported mental health (SRMH) and immigrant characteristics, using a population-based survey linked to immigrant landing information. This study, which is based on a linked database, allows for much richer insight into immigrant populations than most previous studies.Based on data from four cycles (2011 to 2014) of the Canadian Community Health Survey linked to data from the Longitudinal Immigration Database, the odds ratios of having had MHCs are compared between the Canadian-born population and immigrants by immigration dimensions, while controlling for SRMH. Results are hierarchically adjusted for age, sex, socioeconomic factors and sense of belonging.After the above-mentioned factors were controlled for, immigrants were much less likely than Canadian-born respondents to access MHCs. Specifically, compared with the Canadian-born population that had high levels of SRMH, immigrants with high levels of SRMH were statistically less likely to have had an MHC (odds ratio [OR]=0.5, 95% confidence interval [CI] from 0.4 to 0.5), while those with low SRMH levels were more likely to report an MHC (OR=4.8, 95% CI from 4.5 to 5.1, for the Canadian-born population but OR=1.8, 95% CI from 1.5 to 2.1, for immigrants). Most Asian immigrants with low SRMH levels were only as likely to report MHCs as Canadian-born respondents with high SRMH levels. Refugees with low SRMH levels also had only a slightly elevated MHC level (OR=1.6, 95% CI from 1.1 to 2.3) compared with Canadian-born individuals with high SRMH levels. Overall, refugees were not more likely than immigrants of other admission categories to report having had an MHC, even though previous findings have shown that refugees report low levels of SRMH.This study provides new evidence on the differences in access to MHC between Canadian-born individuals and immigrants by various characteristics, while controlling for SRMH. Results probably reflect the structural or cultural barriers to MHC and point to a possible pathway to either maintain or improve mental health among immigrants.

The continuous rise in the immigrant population in Canada makes it increasingly important to monitor immigrant settlement outcome, including that of health. This paper reviews the immigrant health data development based on the wealth of information captured by different waves of population-based datasets, many of which housed at Statistics Canada, to conduct increasingly innovative studies of immigrant health in Canada. Particular attention was devoted to data linkages of administrative and survey databases made possible by recent technological and methodological advancements, especially those that involve the immigrant landing files with information on immigrant categories.

In face of the warming climate, proper building designs are necessary to combat the ever-increasing energy demands, especially in high-density built environments. Shading is a common practice in subtropical cities owing to its effectiveness and feasibility. However, window shading alone is insufficient for achieving a satisfying energy performance and may often be a compromise to the visual comfort of occupants. In contrast, shading opaque facades has a great potential for energy saving with more design flexibility. This study proposes the adoption of shading devices on opaque facades and evaluates their energy saving potentials under near-extreme summer conditions by conducting building energy simulations. The length, the number, and the angle of tilt of shading panels are varied to explore the effects of different shading panel configurations for typical public rental housing buildings in Hong Kong. Optimal configurations that give maximum energy savings with the smallest total area of shading panels are found for different angles of tilt. Results show an energy saving potential up to 8.0% when shading panels are applied to flats with westward-facing facades. The energy saving coefficients within the optimal zones are also provided to guide the design of facade shading features in different urban contexts.

To improve outdoor thermal environment and reduce indoor energy use, passive techniques including facade greenery have been suggested. In high-density cities like Hong Kong, buildings’ surface area is much greater than the roof and ground surface areas combined, offering a huge vertical surface platform for greening. However, scientific evidence to assert the thermal benefit from this greening option especially at neighborhood scale is still very few. Therefore, this study was designed to provide such evidence using results from validated ENVI-met model simulation. Thereafter, parametric study was conducted to investigate the quantity and location of facade greening required for potential air cooling and thermal comfort improvement of a neighborhood of varying densities. Model validation results revealed an acceptable modelling of facade surface temperature, air temperature, relative humidity and wall-emitted long-wave fluxes. From the parametric study, we found that 30–50% of facades in the high-density urban setting of Hong Kong must be greened to potentially cause ∼1 °C reduction in both daytime and nighttime air temperature while the same could help improve daytime pedestrian thermal comfort by at least one thermal class. We also established that higher greened facade ratio will be required to obtain similar thermal benefits in low and medium density urban settings. Also, realized benefits at pedestrians’ height can be enhanced when the vertical greening facilities are placed along podium than tower heights. Lastly, practicable urban planning recommendations were presented for the attention of urban planners and landscape architects.

Summarization: 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. Presented on

People's subjective response to any thermal environment is commonly investigated by using rating scales describing the degree of thermal sensation, comfort, and acceptability. Subsequent analyses of results collected in this way rely on the assumption that specific distances between verbal anchors placed on the scale exist and that relationships between verbal anchors from different dimensions that are assessed (e.g. thermal sensation and comfort) do not change. Another inherent assumption is that such scales are independent of the context in which they are used (climate zone, season, etc.). Despite their use worldwide, there is indication that contextual differences influence the way the scales are perceived and therefore question the reliability of the scales’ interpretation. To address this issue, a large international collaborative questionnaire study was conducted in 26 countries, using 21 different languages, which led to a dataset of 8225 questionnaires. Results, analysed by means of robust statistical techniques, revealed that only a subset of the responses are in accordance with the mentioned assumptions. Significant differences appeared between groups of participants in their perception of the scales, both in relation to distances of the anchors and relationships between scales. It was also found that respondents’ interpretations of scales changed with contextual factors, such as climate, season, and language. These findings highlight the need to carefully consider context-dependent factors in interpreting and reporting results from thermal comfort studies or post-occupancy evaluations, as well as to revisit the use of rating scales and the analysis methods used in thermal comfort studies to improve their reliability.My individual contribution: Runa T. Hellwig: Conceptualization, Methodology, Visualization, Writing - Original Draft \ my contribution like all authors Investigation, Writing - Review & Editing, ResourcesInvestigation, Writing - Review & Editing, ResourcesRuna T. Hellwig: Conceptualization,Methodology, Visualization, Writing - Original DraftRuna T. Hellwig: Conceptualization,Methodology, Visualization, Writing - Original DraftRuna T. Hellwig: Conceptualization,Methodology, Visualization, Writing - Original DraftAuthor statementAll authors: Investigation, Writing - Review & Editing, Resources Marcel Schweiker: Conceptualization,Methodology, Visualization, Formal analysis, Writing - Original Draft Rucha Amin: Conceptualization,Methodology Susanne Becker: Conceptualization, Methodology, Writing - Original Draft Joon-Ho Choi:Conceptualization, Methodology Chungyoon Chun: Conceptualization, Methodology Lyrian Daniel:Writing - Original Draft Renata De Vecchi: Writing - Original Draft Stephanie Gauthier:Conceptualization, Methodology, Writing - Original Draft Runa T. Hellwig: Conceptualization,Methodology, Visualization, Writing - Original Draft Gesche M Huebner: Conceptualization,Methodology, Writing - Original Draft Jungsoo Kim: Conceptualization, Methodology Jakub Kolarik:Writing - Original Draft M.C. Jeffrey Lee: Conceptualization, Methodology Karin Schakib-Ekbatan:Conceptualization, Methodology Despoina Teli: Conceptualization, Methodology Conrad Voelker:Writing - Original Draft

Thermal discomfort is one of the main triggers for occupants’ interactions with components of the built environment such as adjustments of thermostats and/or opening windows and strongly related to the energy use in buildings. Understanding causes for thermal (dis-)comfort is crucial for design and operation of any type of building. The assessment of human thermal perception through rating scales, for example in post-occupancy studies, has been applied for several decades; however, long-existing assumptions related to these rating scales had been questioned by several researchers. The aim of this study was to gain deeper knowledge on contextual influences on the interpretation of thermal perception scales and their verbal anchors by survey participants. A questionnaire was designed and consequently applied in 21 language versions. These surveys were conducted in 57 cities in 30 countries resulting in a dataset containing responses from 8225 participants. The database offers potential for further analysis in the areas of building design and operation, psycho-physical relationships between human perception and the built environment, and linguistic analyses., Measurement(s)Natural Language • Demographics • humidity • response to temperature stimulus • temperature of air • geographic location • room temperature ambient airTechnology Type(s)Survey • sensorSample Characteristic - OrganismHomo sapiensSample Characteristic - EnvironmentbuildingSample Characteristic - LocationOman • Kingdom of Spain • Ecuador • Chile • Malaysia • Iraq • Poland • Nigeria • Iran • Italy • United States of America • Germany • Brazil • Jordan • Kingdom of the Netherlands • Greece • Sweden • Kingdom of Denmark • India • Sri Lanka • Uganda • South Korea • Republic of China • United Arab Emirates • Australia • French Republic • United Kingdom • Japan • Indonesia • China Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9805289

Recent advances in numerical tools and data for the study of urban microclimates have helped to evaluate countermeasures for urban heat in heterogeneous and high-rise cities such as Hong Kong. Thus, two ventilation strategy designs, point ('oases') and linear ('corridors') features, were numerically simulated during a typical heatwave using the multi-layer coupled MesoNH-SURFEX-TEB mesoscale atmospheric model. These strategies proved to be effective at night with respect to thermal comfort but caused a localised increase in heat stress during the day in the ventilated areas, which were less shaded. There was no significant deterioration in the wind performance around the developments that were redesigned to accommodate the displaced population due to the construction of the ventilation features; however, an improvement was observed in thermal comfort during the daytime. The simulated impacts were relatively localised, suggesting the importance of increasing porosity across the entire urban fabric. The corridors, especially when built along the axis of the prevailing winds, exhibited better ventilation at the pedestrian level than the oases. Nevertheless, the oases remain interesting features in the context of progressive urban ventilation planning that involve the implementation of isolated, connected, and eventually a network of features to provide benefits at the megalopolis scale.

Microclimate knowledge has been intensively integrated into urban planning and design to improve the buildings’ energy performance and outdoor thermal comfort. To assess the climatic mitigation strategies, numerical modeling is gaining higher relevance. ENVI-met, a microclimate model to simulate the complex surface-vegetation-atmosphere interactions in the built environment, is receiving increasing popularity. This study aims to systematically evaluate the thermal-radiative performance of the ENVI-met model based on its recent updates. First, a field measurement was conducted in a subtropical city. Thermal-radiative parameters were collected besides three green infrastructure (GI) typologies (i.e., green roof, green wall, ground tree) and three corresponding reference sites. Second, sensitivity tests were conducted for the inputs and settings of ENVI-met model, including new radiation module IVS (Indexed View Sphere), meteorological boundary conditions, materials settings, and output intervals. Third, the thermal-radiative performance of ENVI-met was compared among the six measurement sites, three output intervals, and nine microclimate variables, based on four evaluation metrics. The results showed that 1) recent updates of ENVI-met can improve the estimation accuracy, especially with IVS on, radiation forcing, and localized materials settings; 2) ENVI-met was capable of simulating the thermal-radiative performance of three GI typologies simultaneously; 3) mobile measurement can be used for ENVI-met validation, and 4) model evaluation results were sensitive to the metrics. Overall, this study emphasized proper validation for ENVI-met before applications, when full forcing and localized settings are essential. The strengths and limitations of ENVI-met were discussed and implications were provided for model developers and users.

Estimating the spatiotemporal variability of ground-level PM2.5 is essential to urban air quality management and human exposure assessments. However, it is difficult in a high-density and highly heterogeneous urban context as ground-level monitoring stations are most likely sparsely distributed. Satellite-derived Aerosol Optical Depth (AOD) observation has made it possible to overcome such difficulty due to its advantage of spatial coverage. In this study, we improve the AOD-PM2.5 correlations by combining land use regression (LUR) modelling and incorporating microscale geographic predictors and atmospheric sounding indices in Hong Kong. The spatiotemporal variations of ground-level PM2.5 over Hong Kong were estimated using MODerate resolution Imaging Spectroradiometer (MODIS) AOD remote sensing images for the period of 2003–2015. An extensive LUR variable database containing 294 variables was adopted to develop AOD-LUR models by seasons. Compared to the baseline models (fixed effect models include only basic weather parameters), the prediction performance of all annual and seasonal AOD-LUR fixed effect models were significantly enhanced with approximately 20–30% increases in the model adjusted R2. On top of that, a mixed effect model covers time-dependent random effects and a group of geographically and temporally weighted regression (GTWR) models were also developed to further improve the model performance. As the results, compared to the uncalibrated AOD-PM2.5 spatiotemporal correlation (adjusted R2 = 0.07, annual fixed effect AOD-only model), the calibrated AOD-PM2.5 correlation (the GTWR piecewise model) has a significantly improved model fitting adjusted R2 of 0.72 (LOOCV adjusted R2 of 0.65) and thus becomes a ready reference for spatiotemporal PM2.5 estimation.