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Trees play a significant role in regulating microclimates and enhancing outdoor comfort. Their effects have been widely investigated through on-site tests, wind tunnel (WT) experiments, and numerical simulations. WT experiments, known for their controlled conditions, are increasingly used to investigate the blockage effect of trees. However, the impact of this effect on experimental data is often overlooked. Therefore, we conducted numerical simulations to analyze the blockage effect of trees on airflow distributions under different wind speeds, leaf area density (LAD), drag coefficient (DC), tree canopy morphologies, and blockage ratios (BRs). By comparing the results under various conditions with the case of LAD = 0, we aim to quantify the extent of this impact. The results indicate that LAD and DC are key parameters affecting the blockage effect of trees. The cuboid model exhibits a more significant blockage effect on airflow distributions compared to the cylinder, truncated cone, and ellipsoid models. For tree canopies with low LAD and DC, the impact on airflow distribution is minimal. For the cuboid model with an LAD of 3.0 m2/m3, a DC of 0.5, and a BR of 8 %, the average airflow deviation is approximately 4.28 % compared to the case of LAD = 0. However, when the BR is in the range of 8%–12 %, the WT experimental data need to be corrected. The BR in WT experiments can be appropriately increased for other tree canopy morphologies. This study provides guidance for investigating the blockage effect of trees in WT experiments. • Numerical investigation of the blockage effect of trees on airflow distribution. • The impact of tress on airflow distribution is quantified under various conditions. • For trees with low LAD and DC, the impact on airflow distribution is minimal. • The cuboid tree canopy morphology demonstrates a more significant blockage effect. • For cuboid model with LAD of 3.0 m2/m3 and DC of 0.8, the BR should not exceed 8 %. [ABSTRACT FROM AUTHOR]

Over the past four years, five major variants of the SARS-CoV-2 virus have circulated globally, causing seven million deaths. Meanwhile, specific preventative ventilation measures were recommended to minimize exposure to the aerosol infection risk, such as opening doors, and disabling ventilation systems. Given more attention to high-rise buildings, where quite a few outbreaks have been reported, there is a notable lack of reported studies assessing preventive ventilation measures. Therefore, this study focused on practicing several ventilation measures in a 16-story high-rise building located in Montreal, Canada. A variety of inter-zonal tracer measurements, including room-to-floor and inter-floor tests, were carried out considering controlled airflow/pressure across zones. An automated data acquisition system was developed for real-time monitoring of tracer/CO 2 spatial concentrations. Findings show that enabled ventilation with opened doors reduces CO 2 concentrations by up to 82 % in nearby source locations and positively pressurized zones; however, negatively pressurized zones experience a 40 % increase in tracer exposure. With ventilation active, a corridor source leads to a higher risk of tracer exposure (up to 86 %) than the in-room source. Disabled ventilation with closed doors is a recommended ventilation measure, for corridors with infection sources, to minimize tracer transport across zones. Zones with infection sources follow the latter ventilation measure; however, ventilation with open doors offers a conditional ventilation measure if careful airflow is designed particularly at return and exhaust points within the ventilation system. This study has implications for practicing preventative ventilation measures for post-COVID-19 building practices and design considerations. • Field study conducted in 16-story building, assessing preventive ventilation measures. • Inter-zonal ventilation performance across floors was assessed by tracer measurements. • Automated real-time monitoring system measured tracer/CO 2 concentrations. • Corridor source with ventilation poses 86 % higher tracer transport than in-room source. • Ventilation affects tracer transport based on air flow pressurization across zones. [ABSTRACT FROM AUTHOR]

Global urbanization has underscored the significance of urban microclimates for human comfort, health, and building/urban energy efficiency. However, analyzing urban microclimates requires considering a complex array of outdoor parameters within computational domains at the city scale over a longer period than indoors. As a result, numerical methods like Computational Fluid Dynamics (CFD) become computationally expensive when evaluating the impact of urban microclimates. The rise of deep learning techniques has opened new opportunities for accelerating the modeling of complex nonlinear interactions and system dynamics. Recently, the Fourier Neural Operator (FNO) has been shown to be very promising in accelerating solving the Partial Differential Equations (PDEs) and modeling fluid dynamic systems. In this work, we apply the FNO network for real-time three-dimensional (3D) urban microclimate simulation. For modeling large-scale urban microclimate problems, CityFFD simulates urban microclimate features based on the semi-Lagrangian approach and fractional stepping method with the Smagorinsky large eddy simulation model. In our simulation, the 1200 sequential time steps are used as training data. We retain and analyze the data from all stages, including the spin-up period, because we wish to understand how the flow develops transiently from initial conditions, and both one-step and sequential timestep predictions are analyzed. When applied to unseen data with different wind directions, the FNO model has a 0.3% one-step prediction error and a maximum error of 5%. A real-time simulation of urban microclimates in 3D is possible with the FNO approach, which is 25 times faster than the traditional numerical solver. • Fourier neural operator (FNO) was applied to simulate 3D urban wind field. • FNO is demonstrated to learn 3-D N–S equations for reconstruction of urban microclimate. • Different instantaneous wind direction results obtained when trained only for one wind direction. • Real-time predictions achieved within 0.08 s: 25 times faster than physics-based GPU solver. • Limitations identified and FNO codes and training data available for public sharing. [ABSTRACT FROM AUTHOR]

Abstract Air curtains have been widely used as a mean of reducing infiltration and associated energy losses through building entrances. Since quantifying the infiltration rate through the entrances is directly related to air curtain energy performance, previous studies investigated the infiltration through air curtain doors accounting for door operation, usage frequency, air supply angle and velocity etc. Limited studies have focused on the effect of the wind on air curtain performance, although wind is quite common and could interact with air curtain directly. The purpose of this study is to evaluate experimentally the performance of air curtain under different wind speeds and directions, and their interactions with air curtain jet considering different supply speeds, angles, and pressure differences across the air curtain. The experiments were mostly conducted in an atmospheric boundary layer wind tunnel in a sub-scale building model to represent the actual large-scale air curtain performance in terms of the function of dimensionless air infiltration rate versus the dimensionless pressure difference across the air curtain. The study found that air curtains could resist a certain level of wind speed but could be penetrated by high wind mostly at the lower section of the door, which may be avoided by selecting suitable air curtain speeds and angles, increase of indoor pressures, and entrance door types; the wind effect is the strongest for wind blowing straight-onto the air curtain and decreases with the inclined angles before arriving at the minimal effect at a certain angle, as defined by new wind pressure coefficients. Graphical abstract Image 1 Highlights • Wind and air curtain interactions were experimentally studied by wind tunnel tests. • Air curtain performance was characterized by dimensionless pressures and flow rates. • Air curtain can resist wind at suitable supply jet speed, angle, and door type. • The strongest wind effect is for zero-degree wind towards air curtain. • A new definition of wind pressure coefficient was used to quantify wind effect. [ABSTRACT FROM AUTHOR]

Urban Heat Island (UHI) and climate change are two critical factors affecting the energy demand of buildings. However, the previous literature often overlooked the concurrent impacts of these factors, which leads to an erroneous estimation of the current and future energy demand of buildings. To address this issue, this paper investigates the UHI and climate change and their combined impacts on the current and future cooling demands of high-rise residential buildings in the hot and humid climate of Qatar. The impacts of UHI and climate change on the climatic conditions of the Marina district of Lusail City, Qatar, are evaluated using Urban Weather Generator (UWG) and World Weather Generator (WWG) tools, respectively, for 2050 and 2080. A total of eight weather sources, two for 2020 and six for 2050 and 2080, are compared to the weather data collected from the established local weather stations in the city. Two important methods are adopted to elaborate on the combined impact of the UHI and climate change on building cooling demand. In the first method (M1), the future weather file obtained from the Open Weather Map (OM) is processed by UWG for the UHI impact analysis and then by WWG for the climate change impact analysis, while in the second method (M2), the future weather file is first processed by WWG, followed by UWG. According to the results, for the hot and humid climate of Qatar, the cooling energy consumption of the high-rise residential building increases by 19% and 33.5% for 2050 and 2080, respectively, by the first method, and by 20% and 34.4% for 2050 and 2080, respectively by the second method. Both methods yield fairly similar results on the combined impact of UHI and climate change on building cooling demand in hot and humid climates. The findings of this study highlight the importance and necessity of considering UHI and climate change impact in building energy simulations to estimate the present and future energy demand of buildings accurately. • Effect of urban microclimate and climate change on building cooling load investigated. • A case study of high-rise buildings in the Marina district of Lusail City is considered. • The current and future cooling demands of buildings are studied. • Results imply the significance of considering climate change and microclimate. [ABSTRACT FROM AUTHOR]

Building ventilation is essential during COVID-19 to reduce airborne viral transmission risks, while accurately estimating air change rates remains quite challenging. Due to the tracer gas method's assumption of uniform air mixing in a space, which is often not the case. However, the existing mixing models such as mixing factor (K) and zone distribution effectiveness (E z) are limited to decrease the uncertainty of this assumption since their reported data are subjective, rough estimates, and inconsistent across different standards (e.g., ASHRAE and AIHA). Therefore, in this study, a novel modified decay method (MDM) is developed, where a proposed uniformity index (U i) is integrated into the original decay method (ODM) to quantify the non-uniform air mixing and thereby improve the estimation of air change rates. We validated the proposed method in a real classroom using CO 2 as a tracer gas. Wherein, the spatial variations of CO 2 concentrations were measured at various locations using an automated system of a mass spectrometer with a 16-position valve. Later, the estimated air change rates using both the ODM and MDM were compared with the measured ones. It was found that the proposed U i significantly decreased the error caused by the uniform-mixing assumption of estimated air change rates using ODM from 25.6 % to 3.4 % estimated by MDM at the outlet location. Similarly, the average concentrations of 16 distributed sensors at the breathing level also showed a decrease in error from 25.0 % to 2.5 %. This study can be applied to improve ventilation performance in buildings. • A uniformity index is proposed to quantify the uniformity of tracer mixing with air. • A modified decay method is developed to improve the estimation of air change rates. • CO 2 concentrations and ventilation rates are measured to validate the developed method. • A comparison with ASHRAE zone distribution effectiveness (E z) is also presented. • The proposed uniformity index decreased the error of estimated air change rates by 22 %. [ABSTRACT FROM AUTHOR]

This review outlines historical and recent research progress on the accuracy of computational fluid dynamics (CFD) simulations of urban aerodynamics and microclimates and clarifies future research directions and significant challenges for accuracy and reliability using CFD in this field. First, the development and accepted concepts of verification and validation (V&V) and uncertainty quantification (UQ) in general computer simulations and CFD are reviewed. Subsequently, progress made in V&V and UQ for urban aerodynamics and microclimate CFD simulations is described. The required or acceptable accuracy in this field has been discussed in several studies; however, challenges specific to applying CFD in this area should be recognized considering that the target phenomenon in urban aerodynamics and microclimates is complex. In addition, constructing a conceptual model is challenging and has many uncertainties. Furthermore, this field is characterized by significant spatial distributions of physical quantities, such as wind speed, temperature, and other scalar variables; thus, specific validation metrics and multilateral methods, including a conventional profile comparison, should be used. Therefore, the V&V and UQ processes should be implemented thoroughly, considering the characteristics of urban aerodynamics and microclimates. Discussions presented in this paper are of utmost importance and very timely in terms of simulation quality controls, especially during this new era of machine learning and artificial intelligence-based models that started being applied to urban aerodynamics and microclimate predictions. [ABSTRACT FROM AUTHOR]

Air curtains have been widely used to reduce infiltration through door openings and save heating/cooling energy in different types of buildings. Previous studies have found that there exist three aerodynamics conditions: optimum condition (OC), inflow break-through (IB), and outflow break-through (OB) conditions, which are important for categorizing air curtain performance subject to such key parameters including supply speed and angle, and presence of a person during an actual operation. However, few studies have focused on the effects of these parameters on air curtain performance in terms of resisting infiltration and reducing exfiltration. This research presents a parametric study of air curtain performance based on reduced-scale experiments and full-scale numerical simulations. It was found that increasing air curtain supply angle improves air curtain performance when it is operated under the OC and IB conditions but creates excessive exfiltration under the OB condition. Increasing supply speed of air curtain generally improves the air curtain performance whereas this improvement deteriorates with the increase of supply angle under the OB condition. The presence of person, either directly under or below the air curtain, almost has no effect on the infiltration/exfiltration during the OC condition. Moreover, the person in the doorway can block airflow from both directions, contributing to less infiltration under the IB condition and less exfiltration under the OB condition than without the person. This study provides valuable insights into air curtain aerodynamics performance under different operational conditions and key contributing parameters. [ABSTRACT FROM AUTHOR]

Increasing urbanization and population growth have brought attention to urban microclimates in recent years. The study on urban microclimate and its impact on the built environment is gaining momentum. A growing number of researchers have examined the relationship between human activity and the immediate surroundings to reduce adverse impacts on the environment and climate. This paper presents the latest progress in urban microclimate research on urban wind and thermal environment, covering traditional methods, including field measurements, wind tunnel modeling, and CFD simulations, as well as emerging methods, such as artificial intelligence or data-driven models. Among the publications reviewed, the topics include isothermal scenarios that neglected thermal aspects (e.g., urban wind energy, wind comfort), as well as thermal scenarios (e.g., urban heat islands and outdoor thermal comfort). In the review, it was found that CFD has been widely applied due to its well-developed nature. In addition to field measurements, new techniques (such as satellite and thermal imaging) provide valuable validation data for CFD and training data for artificial intelligence applications. In isothermal scenarios, wind tunnel modeling has been successfully applied. However, thermal scenarios present significant challenges. In addition, urban data-driven models have emerged with promising results, but systematic investigations have been limited. In this paper, we identify future research needs for urban microclimates based on an overview of recent progress. • 563 publications on urban microclimate from 2010 to 2020 were reviewed. • Research on urban microclimate increased fivefold over the past decade. • Numerical simulation is the most common approach, and data-driven models become promising. • Past findings, existing challenges, and future research needs are presented. [ABSTRACT FROM AUTHOR]

This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. The calibrated simulation model based on indoor and outdoor measured temperature for a school of interest is used to evaluate the optimization strategies. This paper aims to search for the optimum school building design under three simultaneous conflicting objective functions: (1) the minimization of overheating hours to less than 40 h as required by Building Bulletin BB101 building code by using passive mitigation measures, (2) the minimization of heating energy use to less than 15 kW/m2 according to passive house requirements and thus the reduction of greenhouse gas emissions, and (3) the minimization of artificial lighting energy use to less than the current lighting energy use by maximization of daylighting usage without exceeding acceptable glare index in classrooms. Ten building design variables are selected, which could generate approximately 300,000 solutions. The developed methodology reduced the numbers to 14,400 solutions and found seven Pareto solutions that comply with the three objectives and their constraints. High energy-efficient building envelope, appropriate window-wall ratio and window type, natural ventilation during the day, and night cooling can play a key role in achieving the objectives under current weather conditions. An additional cool roof and external overhang will be needed in the medium-term future climate, and an additional movable screen shading will be needed in the long-term future climate. • Overheating, lighting and heating energy use of the School building is optimized. • Sensitivity analysis with Genetic Algorithm methodology is developed. • Ten decision variables are evaluated to achieve the three objective functions. • Temporal changes of optimal designs for extreme current & future years are studied. • Five optimal designs with passive mitigation measures are founded. [ABSTRACT FROM AUTHOR]

Climate change and urbanization have exacerbated concerns about urban overheating, affecting thermal comfort, heat-related mortality, and urban energy consumption, especially during heat waves. Developing climate projections that reliably describe the state of the urban climate, a complex system containing microclimate phenomena on a regional and global scale, is essential for assessing overheating impacts and evaluating mitigation strategies in current and future climates. Using four essential steps for advancing our understanding of overheating and informing future studies, we review climate model projections for urban overheating impact assessments: (1) Acquisition of raw future climate data at the mesoscale through GCM-RCMs; (2) Bias correction and local reference year data generation; (3) Simulations at microscale indoors and outdoors using building performance or CFD models; (4) Evaluation of overheating based on various criteria. A methodology for selecting review articles is presented. The study highlights key future research gaps related to climate data generation, improving data reliability, and addressing climate simulation complexities indoors and outdoors. In addition, a comprehensive overheating assessment also depends upon incorporating social-economic factors into evaluations. Although we focus on urban overheating assessment, the general methodologies of future climate projections may also apply to other building performance simulations considering climate change impacts. • Accurate climate projections are imperative to evaluate urban overheating in extant and forthcoming climates. • Statistical-dynamic methods present a viable balance for high-resolution, multi-decadal urban climate analyses. • Augmenting projected data reliability via bias adjustments and reference year techniques is of great importance. • Addressing challenges in indoor and outdoor climate simulation is essential for studying future overheating. • Overheating evaluation methods should consider social-economic indices to better assess urban overheating risks. [ABSTRACT FROM AUTHOR]

Inflow boundary conditions are critical for simulating urban wind fields by CFD methods, and wind profiles within the atmospheric boundary layer are significantly affected by local atmosphere circulation and diurnal variation. The Weather Research and Forecasting (WRF) model is a powerful mesoscale weather prediction model that can be used to provide more realistic inflow boundary conditions. To investigate the potential of a combined WRF and CityFFD method (WRF-CityFFD), this study first validated the WRF and CityFFD models and then used the validated models in WRF-CityFFD to calculate the wind distribution in the Kowloon district of Hong Kong within an area of 3.5 km × 2.4 km. The wind speed data at two weather stations were used as a benchmark, and CityFFD with inflow boundary conditions from a semi-empirical method (semi-empirical-CityFFD) was also investigated for comparison. The WRF-CityFFD performed better than the semi-empirical-CityFFD in calculating wind velocities in urban microclimates. The power-law exponent for wind profiles should be carefully defined when conducting CFD simulations for complex urban layouts. Coastal areas with onshore wind conditions were more suitable for selection as inflow boundary conditions for WRF-CityFFD. • A combined WRF and CityFFD method was constructed and evaluated. • Time-varying wind profiles was incorporated for urban microclimate modelling. • WRF-CityFFD performed better than semi-empirical-CityFFD. [ABSTRACT FROM AUTHOR]

In sparsely occupied large industrial and commercial buildings, large-diameter ceiling fans1 (LDCFs) are commonly utilized for comfort cooling and destratification; however, a limited number of studies were conducted to guide the operation of these devices during the COVID-19 pandemic. This study conducted 223 parametrical computational-fluid-dynamics (CFD) simulations of LDCFs in the U.S. Department of Energy warehouse reference building to compare the impacts of fan operations, index-person, and worker-packing-line locations on airborne exposures to infectious aerosols under both summer and winter conditions. The steady-state airflow fields were modeled while transient exposures to particles of varying sizes (0.5–10 μm) were evaluated over an 8-h period. Both the airflow and aerosol models were validated by measurement data from the literature. It was found that it is preferable to create a breeze from LDCFs for increased airborne dilution into a sparsely occupied large warehouse, which is more similar to an outdoor scenario than a typical indoor scenario. Operation of fans at the highest feasible speed while maintaining thermal-comfort requirements consistently outperformed the other options in terms of airborne exposures. There is no substantial evidence that fan reversal is beneficial in the current large space of interest. Reversal flow direction to create upward flows at higher fan speeds generally reduced performance compared with downward flows, as there was less airflow through the fan blades at the same rotational speed. Reversing flow at lower fan speeds decreased airflow speeds and dilution in the space and, thus, increased whole-warehouse concentrations. • 223 parametrical CFD simulations of large-diameter ceiling fans (LDCFs) in a 3220 m2 warehouse. • 8-h transient airborne particle transmissions were modeled by a validated drift-flux model. • The breeze from LDCFs and higher fan speeds benefits airborne dilutions and depositions. • Reversing LDCFs lowers air speeds and dilutions and thus results in higher airborne concentrations. • New LDCF operation guidelines were recommended for both summer and winter operations. [ABSTRACT FROM AUTHOR]

Trees can effectively regulate the urban microclimate, while the change of microclimate conditions in turn affect the physiological state of trees. In this paper, CFD simulations are performed by coupling canopy energy balance (CEB) model to study the effects of trees on outdoor microclimate. The results show that the tree has different effects on outdoor microclimate under different wind speeds, air conditions, solar radiation and stomatal resistance. Increasing the wind speed will weaken the cooling effect of the tree. This weakening effect can extend to a distance of about 3.2 times of the tree canopy width behind the tree when the inflow air temperature is 30 °C. However, the influence range at high wind speeds is greater than that at low wind speeds. Air temperature and relative humidity have opposite effects on the sensible and latent heat fluxes of the tree, while they both have negligible effects on the net radiation flux. The humidification effect of the tree will be weakened as the relative humidity increases. Solar radiation has a greater effect on leaf surface temperature (LST) than on air temperature. The net radiation flux is high at the top and bottom of the tree and comparatively low at the central section, which is related to the vertical distribution of leaf area density (LAD). Trees can mitigate the effects of environmental changes on the LST by regulating stomatal resistance, and the reduction of stomatal resistance leads to a greater cooling effect. • CFD study trees effect on urban microclimate under different influencing factors. • Trees have different effects on urban microclimate in different environments. • Increasing wind speed weakens cooling effect of trees under the same conditions. • Air parameters have little effect on the net radiation flux absorbed by trees. • The distribution of net radiation flux is highly correlated with leaf area density. [ABSTRACT FROM AUTHOR]

Quantifying building resilience to extreme weather conditions helps identify the capability of a building system to tolerate disturbances and recover from extreme events. The robustness of building retrofit strategies can also be evaluated through their contributions to building resilience. In this study, building thermal resilience to summertime heatwaves is defined based on the concept of resilience trapezoid. The Thermal Resilience Index (TRI) with several labeling classes (Class F to Class A+) is proposed to quantify the resilience levels with respect to the relative improvement from original indoor thermal conditions. In addition to evaluating the overall resilience of a building, the resilience of each thermal zone in the building can be quantified with the proposed TRI criteria. A quantification framework is proposed by using the Standard Effective Temperature (SET) index as the performance indicator, and the entire procedure is demonstrated with a long-term care building of five stories. Four retrofit measures and their combinations are implemented to improve the building resilience to heatwaves. The results show layered multiple strategies are necessary to improve both the overall resilience of the building and the resilience of its component thermal zones. The resilience of the building can achieve the level of Class B after the combined strategies are applied, providing an improvement of 50%–70% in the degree of resilience. The proposed TRI index and spatial distribution analysis are useful in evaluating the overall and zonal resilience of a building. • Thermal Resilience Index (TRI) - a new building resilience parameter against heatwave is proposed. • Building thermal resilience curve is shown to be a trapezoid profile based on field measurements. • TRI is proposed to label the zone-level and building-level resiliences from Class F to Class A+. • TRI is evaluated using Standard Effective Temperature (SET) index as the performance indicator. • The new TRI approach is demoed by a long-term care center by measurements and simulations. [ABSTRACT FROM AUTHOR]

Air infiltration through building entrances is one of the main sources of energy loss in modern buildings. Previous studies have shown that air curtains, when used at building entrances, can reduce infiltration-related energy loss significantly. A recent computational fluid dynamics (CFD) study proposed a new empirical model to capture air curtain door infiltration/exfiltration characteristics under varying operation conditions and pressure differences. Extending the recent CFD study, this paper presents an experimental study to verify and further investigate the flow characteristics of building entrances equipped with air curtains. A small scale chamber of 2.44 m × 2.44 m × 1.3 m (L × W × H) was constructed and used for the measurements of infiltration/exfiltration and pressure differentials, which were then used for developing the empirical model across the operating air curtain. A 2-D particle image velocimetry (PIV) system with helium filled soap bubbles as seeds was used to visualize the airflow fields captured at the doorway. Both the PIV and the measurement-based correlations were also compared to CFD simulations. The flow/pressure measurements confirmed that, for the tested pressure difference range, air curtains can significantly reduce infiltration. The PIV results confirmed the existence of multiple flow characteristics subject to pressure differences across the air curtain. The experimental results also validated the CFD modeling methods for air curtain, and verified that the empirical model of air curtain from the literature is valid in estimating infiltration through building entrances equipped with air curtains. [ABSTRACT FROM AUTHOR]

Fast and accurate simulation of outdoor airflow distribution is important for studying urban microclimate. Choosing a reasonable turbulence model and discretization scheme is not only related to the computational accuracy but also to efficiency. However, conventional CFD methods are computationally intensive and slow for unsteady problems, and thus cannot meet the demand for fast simulation of urban microclimate. In this paper, three pressure-correction schemes (i.e., NIPC, SIPC, and NSPF) for solving the N–S equation item by item are implemented in OpenFOAM, and then the differences are compared when applying different turbulence models and discretization schemes to quickly simulate the airflow distribution around a single 1:1:2 bluff body. All pressure-correction schemes can accurately predict the main airflow characteristics around the bluff body. The three schemes are about 2.5–3.5 times faster than the PISO algorithm, and they take the shortest computational time when applying RKE, followed by SQKE and RNG, while the longest computational time is required when applying SKE and LBKE. NIPC and SIPC have similar computational speeds, while NSPF is about 10–16% faster than them. The pressure-correction scheme with the first-order upwind scheme is about 6–10% faster than the second-order discretization scheme. Considering both computational accuracy and efficiency, the combination of NSPF with RNG or SQKE turbulence model and first-order upwind scheme may be a reasonable choice to quickly simulate the urban airflow distributions. • Three pressure-correction schemes are implemented in OpenFOAM to solve N–S equation. • Validation with experimental data of airflow around a single 1:1:2 bluff body. • NIPC and SIPC have similar computational speeds, while NSPF is 10–16% faster than them. • FFD method with first-order upwind scheme is 6–10% faster than second-order scheme. • Combination of NSPF with RNG or SQKE and first-order upwind scheme is optimal. [ABSTRACT FROM AUTHOR]

Contradictory findings are reported in the literature showing that high energy-efficient buildings have either higher or lower overheating risks compared to old buildings. A methodology is developed using the Global and Local Sensitivity Analysis to quantify the contribution and correlation of individual building envelope parameter to the change in indoor operative temperature. This methodology is applied to an archetype Canadian detached house as a case study to evaluate its overheating risk. The building envelope thermal characteristics studied represent houses built in different periods from 1950 to high energy-efficient buildings in Montreal under different weather generations: typical historical (1961–1990), recent observational (2016), and typical future years 2030 (2026–2045) and 2090 (2080–2099) generated based on RCP-4.5 and 8.5 scenarios. The results showed that the high energy-efficient buildings can be more resilient to climate change than old buildings if adequate ventilation is provided, where the decrease of window and wall U-value, and SHGC all contribute to the decrease in indoor temperature. While without adequate ventilation, the overheating risk in high-energy-efficient buildings can be higher than old buildings, where decreasing wall and window U-values and infiltration rate has a greater contribution to the increase of indoor temperature, while decreasing window SHGC has a lower contribution to the decrease in indoor temperature compared to the case with adequate ventilation. The results also showed that natural ventilation in the high energy-efficient buildings is sufficient to reduce the overheating risk under the current climate but will require additional interior and exterior shading under future climates. • Methodology is developed to find contribution of each BEP to indoor temperature. • HEEBs have lower overheating risks than OBs with adequate ventilation. • Ventilation rate threshold that makes HEEBs perform better than OBs is determined. • Effective mitigation measures are evaluated under recent and future climates. • With adequate ventilation and solar control, HEEBs can be more resilient than OBs. [ABSTRACT FROM AUTHOR]

The world has faced tremendous challenges during the COVID-19 pandemic since 2020, and effective clean air strategies that mitigate infectious risks indoors have become more essential. In this study, a novel approach based on the Wells-Riley model applied to a multizone building was proposed to simulate exposure to infectious doses in terms of " quanta ". This modeling approach quantifies the relative benefits of different risk mitigation strategies so that their effectiveness could be compared. A case study for the US Department of Energy large office prototype building was conducted to illustrate the approach. The infectious risk propagation from the infection source throughout the building was evaluated. Different mitigation strategies were implemented, including increasing outdoor air ventilation rates and adding air-cleaning devices such as Minimum Efficiency Reporting Value (MERV) filters and portable air cleaners (PACs) with HEPA filters in-room/in-duct germicidal ultraviolet (GUV) lights, layering with wearing masks. Results showed that to keep the risk of the infection propagating low the best strategy without universal masking was the operation of in-room GUV or a large industrial-sized PAC; whereas with masking all strategies were acceptable. This study contributes to a better understanding of the airborne transmission risks in multizone, mechanically ventilated buildings and how to reduce infection risk from a public health perspective of different mitigation strategies. • A new method was developed for simulating SARS-CoV-2 airborne quanta transmission in multizone buildings using CONTAM. • Whole-building exposure risk was modeled for a large office building , considering dynamic zone pressures and ambient conditions. • System level mitigation was more effective to reduce overall building risk when the location of the infected individual was unknown. • In-room mitigation reduced local transmission risk more effectively when the individual was in the same zone. [ABSTRACT FROM AUTHOR]

Climate change has led to prolonged, more frequent, intense, and severe extreme weather events, such as summertime heatwaves, creating many challenges on the economy and society and human health and energy resources. For example, the 2010 and 2018 heatwave in Quebec, Canada, resulted in about 280 and 93 heat-related deaths, and there were around 500 fatalities due to overheated indoor environments in 2021 around entire Canada. Therefore, it is imperative to understand and evaluate the overheating conditions in buildings, for which selecting suitable future reference weather data under climate change is one of the first critical steps. This study evaluated a reference year selection method in terms of typical and extreme reference years based on future climate datasets to assess both outdoor and indoor overheating in the future. The future climate data were collected from the Coordinated Regional Downscaling Experiment (CORDEX) program. Three Canadian cities (Montreal, Toronto, Vancouver) were selected for the overheating evaluation during three selected periods (2001–2020, 2041–2060, 2081–2100). The CORDEX climate projections were first bias-corrected by the multivariate quantile mapping correction method with the observational data. Then, the typical and extreme reference year data were generated as well as climate data from the design summer year for comparison. The performance of the reference year selection method was evaluated by comparing the maximum, minimum, and average overheating hours for the 20-years data of each period. This study demonstrates that the multivariate quantile mapping bias correction method can improve the reliability of future climate data making it one of the most important steps for any future weather projection study. Besides, the reference year selection method could efficiently capture maximum and minimum monthly overheating hours providing the upper and lower boundary of possible outdoor and indoor overheating conditions.. In contrast, neither the severest nor the typical monthly outdoor and indoor overheating conditions could be predicted by the design summer year method. Finally, owing to the effects of climate change, average monthly overheating hours normally increase by around one time (from 50% to 150%) until the mid-term future (2041–2060) and by around two to three times (even up to nine times for some scenarios) during the long-term future (2081–2100). [ABSTRACT FROM AUTHOR]

Abstract: Data assimilation is widely used in weather forecasting and other complex forecasting problems such as hydrology, meteorology, and fire dynamics. Among various data assimilation methods, the Ensemble Kalman Filter (EnKF) is one of the best solutions to large-scale nonlinear problems while the computational cost is relatively less intense than other forecasting methods. In this paper, a new application of EnKF to forecast indoor contaminant concentrations is presented. The first part of the paper introduces the fundamental theories of data assimilation. The second part is a case study of forecasting the concentrations of a tracer gas in a multi-zone manufactured house by using a mass balance model with an EnKF. The benefits of EnKF and several important parameters for EnKF were discussed including numbers of ensemble members and observations, time step of observations, and forecasting lead time. The EnKF method presented is one of the first studies applied to the indoor environment field. It was shown that by using EnKF, the predictability of the simple indoor air model for the multi-zone space was improved significantly. [Copyright &y& Elsevier]

Abstract: Many contaminants in the living space of a house, such as carbon monoxide, benzene, toluene, and ethylbenzene, originate from attached garage. As more airtight and energy-efficient houses are designed and constructed, these contaminants may be retained in indoor air for a longer period of time, jeopardizing the occupants'' health. In this study, CONTAM, a multi-zone model, is employed to analyze the effect of garage-house interface on the contaminant transport from an attached garage to the living space. Parametric studies of two buildings are carried out to investigate the effect of ventilation on the transport of contaminant from the garage to living space, based on experimental data of five Effective Leakage Area (ELA) of a typical garage-house interface. The results show high concentration of indoor pollutants for typical leaky garage-house interface. Parametric simulations also indicate that the improper design of mechanical exhaust systems can cause higher infiltration of contaminants from the garage to the house, resulting in higher indoor air pollution concentration. [Copyright &y& Elsevier]

With the increased severity, intensity, and frequency of "heatwaves" due to climate change, it has become imperative to study the overheating risks in existing buildings. To do so, a building simulation model needs to be calibrated based on measured indoor temperatures under the current weather conditions. This paper presents a robust automated methodology that can calibrate a building simulation model based on the indoor hourly temperature in multiple rooms simultaneously with high accuracy. This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant parameters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. Maximum Absolute Difference (MAD), a new metric, that calculates the maximum absolute difference between simulated and measured hourly indoor temperatures, Root Mean Square Error (RMSE), Normalized Mean Bias Error (NMBE) were used as the evaluation criteria. Another new metric is introduced, 1 °C Percentage Error criterion that calculates the percentage of the number of hours with an error over 1 °C during the calibration period, to select the best solutions from the Pareto Front solutions. 0.5 °C Percentage Error criterion is also used for the level of accuracy the model can achieve. It was found that the calibrated model achieved these metrics with RMSE of 0.3 °C, and MAD of 0.8 °C, and 85% of data points with an error less than 0.5 °C for a school building case. • Robust methodology for calibrating E+ model based on indoor hourly temperature. • Multi-Objective Genetic Algorithm for calibration multi-room simultaneously. • Variance-based sensitivity method for determining the significant parameters. • New evaluation and selection criteria for finding the optimal calibrated model. • High calibration accuracy achieved for a Canadian existing school building. [ABSTRACT FROM AUTHOR]

Urban microclimate analysis is often associated with computational fluid dynamics simulations of urban aerodynamics and thermal conditions, air quality, heat island, humidity, and rain at a building level. Conventional microclimate analyses are often limited by the size of the simulation domain, turbulence models, and sparse digital urban data available. This study introduces CityFFD with its supporting web portal of digital cities for large-scale urban simulation problems. A few novel algorithms, including backward and forward sweep interpolation schemes, time-adaptive technique, and the 2nd-order temporal scheme, were implemented to enhance the computing speed and accuracy of the model. Parallel computing on graphics processing units (GPU) speeds up the simulation. CityFFD is equipped with a large eddy simulation method to capture the turbulence behavior in the urban roughness sublayer. This paper reports the structure of CityFFD, and a group of benchmark cases, including airflow around buildings, natural ventilation, and thermal stratifications around building blocks in an actual urban area, and CityFFD is shown to predict acceptable results of the urban scale wind speeds, temperatures, and flow patterns. This study demonstrates a new approach to modeling urban microclimate by CFD simulations on GPUs. • A new urban microclimate model with a multi-scale simulation portal is presented. • The new model runs on GPUs and OpenMP with unconditional stability. • The web portal enables interactive and real-time data integration for cities. • The new model was validated by benchmark cases including actual urban community. [ABSTRACT FROM AUTHOR]

As a consequence of global warming and rapid urbanization around the globe, the magnitudes and frequencies of extreme heat events (EHEs) are increasing and this trend is expected to continue into the future. In this study, the added benefit of modelling climate at convection-permitting spatial resolutions (grid spacing <4 km) is considered for a set of exterior climate and interior building simulations during EHEs in the urban areas of Ottawa and Montreal, Canada over the summer of 2018. The climate is modelled at two spatial resolutions: i) 25 km – typically considered for regional-scale climate modelling; and ii) 1 km. The results derived from modelling at each of these resolutions is compared in respect to their adequacy in predicting different measures of overheating outdoors as well as those within a typical single-detached home. The results clearly demonstrate that simulations undertaken at a 1 km resolution permit more accurately calculate the magnitude of overheating, whereas simulations completed at a 25 km resolution lead to an underestimation of overheating in about 95% of the urban grids within either of these two cities. These results suggest the necessity of using convection-permitting climate simulations for overheating assessments over the urban scale. • Urban climate of Ottawa and Montreal is simulated at 1 and 25 km spatial resolutions. • Added value of convection-permitting model in overheating studies is demonstrated. • Simulations at a high-resolution are found more accurate in simulating urban temperatures and wind. • Use of regional climate simulations leads to underestimation of overheating. [ABSTRACT FROM AUTHOR]

Abstract: Multizone airflow network models assume that in a zone air temperature and contaminant concentrations are uniform, and air momentum effects are neglected. These assumptions could cause errors for airflow with strong buoyancy, large contaminant concentration gradient, or strong momentum. This study has found the correlations of the errors and some dimensionless air parameters. The assumption of uniform air temperature is acceptable when the dimensionless temperature gradient is smaller than 0.03. The assumption of uniform contaminant concentration is valid if the corresponding Archimedes number for the source zone is greater than 400. The assumption of neglecting air momentum effect is reasonable when the jet momentum effect is dissipated before reaching an opening in downstream. [Copyright &y& Elsevier]

• WRF was integrated with a new urban microclimate model for multi-day simulations. • Studied impacts of street aspect ratios and anthropogenic regimes on temperatures. • Studied urban microclimate impacts on urban temperatures during actual heatwaves. • Both WRF and CityFFD were validated by literature data and actual heatwave data. Urban atmospheric flow is characterized by meteorological processes and street-scale perturbations of microclimate wind velocity and air temperature distributions. The Weather Research and Forecasting model (WRF) is applied to investigate the effects of meteorological processes on temperature distribution over the Greater Montreal Area during the 2017 heatwave. The single-layer Urban Canopy Model is coupled with the WRF to estimate the heat fluxes from the canopy to the atmosphere. The mesoscale simulation results provide the boundary conditions for a new city-scale microclimate LES model, CityFFD. This study first validated the WRF model through multiple weather station measurements and the CityFFD model through the literature data, then investigated the impacts of three canyon aspect ratios and three anthropogenic heat regimes, i.e., surface temperature differences, on the boundary conditions setups. The strong anthropogenic heat assumption was applied to modeling the 2017 heatwave for three consecutive days using the integrated model. The transient results show that a difference of ∼4 m/s wind speed could result in a spatial temperature variation of up to 4 °C for the area under consideration. This study shows the importance of microclimate simulations for regional climate models when studying urban heatwaves. [ABSTRACT FROM AUTHOR]

Many urban and building microclimate problems are featured with a big computational domain and a large number of computing grids, so a fast and accurate solution by computation fluid dynamics (CFD) remains a challenge. The simulations are often only steady-state and, if there exists a transient model, the solution is often limited for a short period. For these computationally expensive simulations, large timesteps and coarse meshes (LTCM) seem preferable among users with limited computing resources, whereas many existing CFD models may not perform well for LTCM problems. This study developed a new fast fluid dynamics (FFD) model based on the semi-Lagrangian approach with high-order temporal and spatial schemes designed for LTCM problems. For large timesteps, a 2nd-order temporal scheme estimates the characteristic curve of each fluid's particle by accounting for the acceleration of the flow field. For coarse meshes, a 4th-order spatial scheme applies a backward-forward sweep technique for better accuracy in space. The performance of the proposed method is verified and validated by five benchmark cases, including a pure advection problem, forced convection in a single room, transient wind flow around a cylinder, airflow around a group of low-rise buildings, and airflow around a high-rise building. Then, we demonstrated the model for the study of the urban wind flows in a city downtown area with 2500 buildings and 35 million grids. As one of the first studies of applying FFD to urban aerodynamics, this study shows its strong potential for solving big transient problems with large timesteps and coarse meshes. • New FFD solver with high-order spatial and temporal schemes for urban airflows. • 2nd-order temporal scheme is shown suitable for large time steps. • 4th-order spatial scheme is shown efficient for coarse meshes. • City simulation with 35 million grids and 2500 buildings only took 2 h. [ABSTRACT FROM AUTHOR]