C. Garcia Sanchez
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1
MORICHI
A Dataset to Study Urban Overheating during Extreme Heat in a Hot-Summer Humid Continental Climate
This paper describes a firsthand and open dataset comprising weather data collected from four street-level stations and microscale thermal images captured by a single infrared thermal camera during an extreme heat event in late August 2024 in Pittsburgh, United States. The weather data includes air temperature, relative humidity, wind speed and direction, and rainfall, measured at a height of 2 meters above the ground. From microscale thermal images, it is possible to assess the temperatures of built-up surfaces within a street canyon on a university campus, including a road, sidewalks, and building façades. Other factors that contribute to or mitigate urban overheating, such as waste heat emissions, traffic, and vegetation, can also be analyzed using the microscale thermal images. The weather data and microscale thermal images are publicly accessible in the 4TU.ResearchData repository under the CC BY 4.0 license. A Python library was developed to extract and process the data, particularly microscale thermal images, and is publicly available via the PIP package installer.
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This paper describes a firsthand and open dataset comprising weather data collected from four street-level stations and microscale thermal images captured by a single infrared thermal camera during an extreme heat event in late August 2024 in Pittsburgh, United States. The weather data includes air temperature, relative humidity, wind speed and direction, and rainfall, measured at a height of 2 meters above the ground. From microscale thermal images, it is possible to assess the temperatures of built-up surfaces within a street canyon on a university campus, including a road, sidewalks, and building façades. Other factors that contribute to or mitigate urban overheating, such as waste heat emissions, traffic, and vegetation, can also be analyzed using the microscale thermal images. The weather data and microscale thermal images are publicly accessible in the 4TU.ResearchData repository under the CC BY 4.0 license. A Python library was developed to extract and process the data, particularly microscale thermal images, and is publicly available via the PIP package installer.
Coral reefs are vital to marine ecosystems, supporting biodiversity and driving nutrient cycling. Despite significant research on the interaction between surface waves and natural or artificial reefs, the turbulent flow dynamics within coral canopies remain poorly understood due to their intricate geometries. This study addresses this knowledge gap using a turbulence-resolving computational framework based on the volume-penalizing immersed boundary method (vIBM). Comparing the serial, staggered, and stochastic arrangements of various coral roughness types we observe that massive corals and cylinders lead to a similar hydrodynamics response and the effect of dispersive stresses can introduce a large difference when stochastic coral reefs are considered. These observations highlight the importance of better understanding the hydrodynamics of complex coral reef geometries, emphasizing the need for further studies on this aspect of coral reef hydrodynamics.
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Coral reefs are vital to marine ecosystems, supporting biodiversity and driving nutrient cycling. Despite significant research on the interaction between surface waves and natural or artificial reefs, the turbulent flow dynamics within coral canopies remain poorly understood due to their intricate geometries. This study addresses this knowledge gap using a turbulence-resolving computational framework based on the volume-penalizing immersed boundary method (vIBM). Comparing the serial, staggered, and stochastic arrangements of various coral roughness types we observe that massive corals and cylinders lead to a similar hydrodynamics response and the effect of dispersive stresses can introduce a large difference when stochastic coral reefs are considered. These observations highlight the importance of better understanding the hydrodynamics of complex coral reef geometries, emphasizing the need for further studies on this aspect of coral reef hydrodynamics.
In response to the WHO and UN's call to ensure children's right to breathe "clean"air and the challenges posed by the COVID-19 pandemic on maintaining healthy indoor air quality (IAQ), a holistic research was conducted to explore ventilation and air cleaning strategies to control the spread of infectious respiratory particles (IRPs) in school classrooms. The study follows four key steps: (1) a literature review bridging school ventilation regimes, IRP transmission, and advanced ventilation systems; (2) a field study to evaluate real-world ventilation and thermal conditions during the pandemic; (3) an experimental investigation of performance of mobile air cleaners (MACs) followed by an in-situ validation; and (4) a combined experimental and computational study to assess personalized air cleaners (PACs) as localized exhaust for IRP removal. Findings reveal that most classrooms rely on natural ventilation, often failing to meet IAQ standards, especially when fully occupied. With windows and doors kept open, ventilation rates remained inconsistent, and thermal conditions were unsatisfactory. Hence, more controllable ventilation and air cleaning approaches are needed. MACs, when appropriately selected and positioned, offer effective protection against long-range IRP transmission at room scale, while PACs are effective at mitigating localized, short-range IRP exposure, improving IAQ at an individual level.
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In response to the WHO and UN's call to ensure children's right to breathe "clean"air and the challenges posed by the COVID-19 pandemic on maintaining healthy indoor air quality (IAQ), a holistic research was conducted to explore ventilation and air cleaning strategies to control the spread of infectious respiratory particles (IRPs) in school classrooms. The study follows four key steps: (1) a literature review bridging school ventilation regimes, IRP transmission, and advanced ventilation systems; (2) a field study to evaluate real-world ventilation and thermal conditions during the pandemic; (3) an experimental investigation of performance of mobile air cleaners (MACs) followed by an in-situ validation; and (4) a combined experimental and computational study to assess personalized air cleaners (PACs) as localized exhaust for IRP removal. Findings reveal that most classrooms rely on natural ventilation, often failing to meet IAQ standards, especially when fully occupied. With windows and doors kept open, ventilation rates remained inconsistent, and thermal conditions were unsatisfactory. Hence, more controllable ventilation and air cleaning approaches are needed. MACs, when appropriately selected and positioned, offer effective protection against long-range IRP transmission at room scale, while PACs are effective at mitigating localized, short-range IRP exposure, improving IAQ at an individual level.
While the worst COVID-19 pandemic is past us and everything has almost returned to normal, we should act on the lessons learned and prepare for a future pandemic. Public places of large social gatherings like cafes, bars, and restaurants might be the most vulnerable indoor environments because the occupants face each other in combination with poor ventilation. However, little research has been done to study such a social setting. As an initial experimental study, a respiring manikin setup is developed to mimic face-to-face conversations between two occupants. This setup can mimic and visualize speech-like particle-laden flow in different environmental conditions. It has the potential to quantify the illuminated flow field for correlation with numerical simulations and be used with infectious viruses for virology studies in the context of airborne transmission.
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While the worst COVID-19 pandemic is past us and everything has almost returned to normal, we should act on the lessons learned and prepare for a future pandemic. Public places of large social gatherings like cafes, bars, and restaurants might be the most vulnerable indoor environments because the occupants face each other in combination with poor ventilation. However, little research has been done to study such a social setting. As an initial experimental study, a respiring manikin setup is developed to mimic face-to-face conversations between two occupants. This setup can mimic and visualize speech-like particle-laden flow in different environmental conditions. It has the potential to quantify the illuminated flow field for correlation with numerical simulations and be used with infectious viruses for virology studies in the context of airborne transmission.
Wind flow predictions in realistic urban areas are sensitive to a wide range of governing parameters such as building resolution, wind incidence, urban morphology, and underlying topography, to name a few. In this study, we systematically study the impact of the geometric level of detail (LoD) of the urban built environment using a Reynolds Averaged Navier–Stokes (RANS) computational framework specifically tailored for urban air mobility. Using a wind-incidence angular resolution of 1 ◦ , we simulated a total of 1440 simulations for two distinct urban areas and developed a probabilistic risk metric ([...]) based on velocity and turbulence fields that allow us to compare the impact of LoD 1.2 (lower geometric detail) and LoD 2.2 (higher geometric detail). Comparing the wind-rose weighted average velocity and the risk map, we found that LoD 2.2 provides a more conservative prediction for high-risk areas than LoD 1.2, suggesting the need to adopt higher geometric details when applicable. Our results present a cautionary view on the impact of LoD and how automatic reconstruction can further the efficiency of current wind engineering practices.
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Wind flow predictions in realistic urban areas are sensitive to a wide range of governing parameters such as building resolution, wind incidence, urban morphology, and underlying topography, to name a few. In this study, we systematically study the impact of the geometric level of detail (LoD) of the urban built environment using a Reynolds Averaged Navier–Stokes (RANS) computational framework specifically tailored for urban air mobility. Using a wind-incidence angular resolution of 1 ◦ , we simulated a total of 1440 simulations for two distinct urban areas and developed a probabilistic risk metric ([...]) based on velocity and turbulence fields that allow us to compare the impact of LoD 1.2 (lower geometric detail) and LoD 2.2 (higher geometric detail). Comparing the wind-rose weighted average velocity and the risk map, we found that LoD 2.2 provides a more conservative prediction for high-risk areas than LoD 1.2, suggesting the need to adopt higher geometric details when applicable. Our results present a cautionary view on the impact of LoD and how automatic reconstruction can further the efficiency of current wind engineering practices.
The interaction of oscillatory wave motion with morphologically complex coral reefs showcases a wide range of consequential hydrodynamic responses within the canopy. While a large body of literature has explored the interaction of morphologically simple coral reefs, the in-canopy flow dynamics in complex coral reefs are poorly understood. This study used a synthetically generated coral reef over flat topography with varying reef height and frontal and planform density to understand the in-canopy turbulence dynamics. Using a turbulence-resolving computational framework, we found that most of the turbulent kinetic energy dissipation is confined to a region below the top of the reef and above the Stokes boundary layer. The results also suggest that most of the vertical Reynolds stress peaks within this region positively contribute to the down-gradient momentum flux during the wave cycle. These findings shed light on the physical relationships between in-canopy flow and morphologically complex coral reefs, thereby motivating a further need to explore the hydrodynamics of such flows using a scale-resolving computational framework.
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The interaction of oscillatory wave motion with morphologically complex coral reefs showcases a wide range of consequential hydrodynamic responses within the canopy. While a large body of literature has explored the interaction of morphologically simple coral reefs, the in-canopy flow dynamics in complex coral reefs are poorly understood. This study used a synthetically generated coral reef over flat topography with varying reef height and frontal and planform density to understand the in-canopy turbulence dynamics. Using a turbulence-resolving computational framework, we found that most of the turbulent kinetic energy dissipation is confined to a region below the top of the reef and above the Stokes boundary layer. The results also suggest that most of the vertical Reynolds stress peaks within this region positively contribute to the down-gradient momentum flux during the wave cycle. These findings shed light on the physical relationships between in-canopy flow and morphologically complex coral reefs, thereby motivating a further need to explore the hydrodynamics of such flows using a scale-resolving computational framework.
GenSDF
An MPI-Fortran based signed-distance-field generator for computational fluid dynamics applications
This paper presents a highly efficient signed-distance field (SDF) generator designed specifically for computational fluid dynamics (CFD) workflows. Our approach integrates the Message Passing Interface (MPI) for parallel computing with the performance benefits of modern Fortran, enabling efficient and scalable signed distance field (SDF) computations for complex geometries. The algorithm focuses on localized distance calculations to minimize computational overhead, ensuring efficiency across multiple processors. An adjustable stencil width allows users to balance computational cost with the desired level of accuracy in the distance approximation. Additionally, GenSDF supports the widely used Wavefront OBJ format, utilizing its encoded outward normal information to achieve accurate boundary definitions. Performance benchmarks demonstrate the tool's ability to handle large-scale 3D models (∼O(10
7) triangulation faces) and computational grid points ∼O(10
9) with high fidelity and reduced computational demands. This makes it a practical and effective solution for CFD applications that require fast, reliable distance field computations while accommodating diverse geometric complexities.
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This paper presents a highly efficient signed-distance field (SDF) generator designed specifically for computational fluid dynamics (CFD) workflows. Our approach integrates the Message Passing Interface (MPI) for parallel computing with the performance benefits of modern Fortran, enabling efficient and scalable signed distance field (SDF) computations for complex geometries. The algorithm focuses on localized distance calculations to minimize computational overhead, ensuring efficiency across multiple processors. An adjustable stencil width allows users to balance computational cost with the desired level of accuracy in the distance approximation. Additionally, GenSDF supports the widely used Wavefront OBJ format, utilizing its encoded outward normal information to achieve accurate boundary definitions. Performance benchmarks demonstrate the tool's ability to handle large-scale 3D models (∼O(10 7) triangulation faces) and computational grid points ∼O(10 9) with high fidelity and reduced computational demands. This makes it a practical and effective solution for CFD applications that require fast, reliable distance field computations while accommodating diverse geometric complexities.
Fake it till you make it
Synthetic turbulence to achieve swift converged turbulence statistics in a pressure-driven channel flow
In this study, we introduced a simple yet innovative application: the isotropic synthetic turbulence field generator (iSTFG), based on the synthetic turbulent inflow generator. The iSTFG leverages the homogeneity in the streamwise direction for channel flows and triggers turbulence to achieve statistically stationary flow conditions faster than standard community-used strategies. We compare this new method with two other well-established methods: linear and log-law profiles superposed with random noise and descending counter-rotating vortices. We find that iSTFG provides a computationally cheap and effective way to reduce simulation spin-up costs/time/emissions to achieve statistically stationary flow conditions when a precursor turbulent initial condition is unavailable. At a one-time cost between 1-10 Central Processing Unit (CPU) hour(s) to generate the synthetic turbulent initial condition based on the target friction Reynolds numbers (1 CPU hour - Reτ=500, 7 CPU hours - Reτ=2000), the flow achieves statistically stationary turbulent flow (SSTF) state within three eddy turnovers for all the parameters of interest in wall-bounded pressure-driven channel flow simulations when compared to other alternatives that can take more than ten eddy turnovers resulting in substantial savings in the computational cost. We also demonstrate that the transition and convergence to an SSTF state using conventional methods are sensitive to the computational domain size, while iSTFG is agnostic to the domain size. Furthermore, we explored the sensitivity of the iSTFG method to the non-dimensional integral length scale parameter and mismatch in reference and target input data to find iSTFG robust in such scenarios.
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In this study, we introduced a simple yet innovative application: the isotropic synthetic turbulence field generator (iSTFG), based on the synthetic turbulent inflow generator. The iSTFG leverages the homogeneity in the streamwise direction for channel flows and triggers turbulence to achieve statistically stationary flow conditions faster than standard community-used strategies. We compare this new method with two other well-established methods: linear and log-law profiles superposed with random noise and descending counter-rotating vortices. We find that iSTFG provides a computationally cheap and effective way to reduce simulation spin-up costs/time/emissions to achieve statistically stationary flow conditions when a precursor turbulent initial condition is unavailable. At a one-time cost between 1-10 Central Processing Unit (CPU) hour(s) to generate the synthetic turbulent initial condition based on the target friction Reynolds numbers (1 CPU hour - Reτ=500, 7 CPU hours - Reτ=2000), the flow achieves statistically stationary turbulent flow (SSTF) state within three eddy turnovers for all the parameters of interest in wall-bounded pressure-driven channel flow simulations when compared to other alternatives that can take more than ten eddy turnovers resulting in substantial savings in the computational cost. We also demonstrate that the transition and convergence to an SSTF state using conventional methods are sensitive to the computational domain size, while iSTFG is agnostic to the domain size. Furthermore, we explored the sensitivity of the iSTFG method to the non-dimensional integral length scale parameter and mismatch in reference and target input data to find iSTFG robust in such scenarios.
Conference paper
(2024)
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M. Martin, M. Ignatius, M. Berges, J. Lim, Y. Lu, R. Xu, J. Stoter, C. Garcia Sanchez, N.H. Wong
This paper suggests a method to simulate interactions between buildings and their outdoor conditions at the city-scale using a coupled scheme whose physical parameters are entirely assessed from data of the indoor and outdoor built environment. The coupled scheme consists of a reduced order building energy model and a single layer urban canopy model. In a previous study, it was proven that physical parameters of a single layer urban canopy model can be assessed using measurements of the outdoor temperature and humidity in a street canyon. For the coupled scheme to be fully data driven, the next step is to demonstrate that the reduced order building energy model can estimate the cooling consumption and exterior wall surface temperature in good agreement with measurements or simulated data after being trained using machine learning. Indeed, results show that a multi objective genetic algorithm can find values for physical parameters of the reduced order building energy model. Estimates of the cooling consumption and exterior wall surface temperature provided by the trained model achieve a CV-RMSE below 10% and a RMSE lower than 2.5 Kelvin, respectively, with respect to data generated from EnergyPlus. The last step towards a full data driven coupled scheme for city-scale simulations would be to iteratively train the reduce order building energy model with the single layer urban canopy model and show the convergence and accuracy of their respective outputs.
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This paper suggests a method to simulate interactions between buildings and their outdoor conditions at the city-scale using a coupled scheme whose physical parameters are entirely assessed from data of the indoor and outdoor built environment. The coupled scheme consists of a reduced order building energy model and a single layer urban canopy model. In a previous study, it was proven that physical parameters of a single layer urban canopy model can be assessed using measurements of the outdoor temperature and humidity in a street canyon. For the coupled scheme to be fully data driven, the next step is to demonstrate that the reduced order building energy model can estimate the cooling consumption and exterior wall surface temperature in good agreement with measurements or simulated data after being trained using machine learning. Indeed, results show that a multi objective genetic algorithm can find values for physical parameters of the reduced order building energy model. Estimates of the cooling consumption and exterior wall surface temperature provided by the trained model achieve a CV-RMSE below 10% and a RMSE lower than 2.5 Kelvin, respectively, with respect to data generated from EnergyPlus. The last step towards a full data driven coupled scheme for city-scale simulations would be to iteratively train the reduce order building energy model with the single layer urban canopy model and show the convergence and accuracy of their respective outputs.
Due to lack of information and long geometry generation times, tree geometries are usually oversimplified or even ignored in Computational Fluid Dynamic (CFD) simulations that predict wind and pollutant dispersion in urban areas. Nevertheless, trees are known to impact local wind patterns and air quality levels. Thus, in this paper we explore the effects that tree models automatically reconstructed at diverse Level of Detail (LoD) (1, 2 and 3) have in numerical wind predictions. We address this by comparing the non-dimensional velocity magnitude differences between simulations with multiple tree LoDs. To further understand these differences in changing environmental contexts we use three morphologies: an isolated tree, an idealized street, canyon, and a real urban geometry from Rotterdam, The Netherlands The numerical results show that the velocity magnitude differences between the cases with LoD1 tree models and those with LoD2 tree models can be over 1.0 m/s while the differences between LoD2 and LoD3 cases are rather limited, usually lower than 0.2 m/s. Consequently, through this study we highlight the importance of using tree models in LoD2 or LoD3 at least for CFD simulations of wind flows in urban areas. To further support this conclusion we also analyze the impact of changing wind directions and tree Leaf Area Density (LAD) values in the impact of tree LoDs on wind. The differences found in this work linked to the level of realism in your tree models can support future studies where researchers want to make an informed choice.
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Due to lack of information and long geometry generation times, tree geometries are usually oversimplified or even ignored in Computational Fluid Dynamic (CFD) simulations that predict wind and pollutant dispersion in urban areas. Nevertheless, trees are known to impact local wind patterns and air quality levels. Thus, in this paper we explore the effects that tree models automatically reconstructed at diverse Level of Detail (LoD) (1, 2 and 3) have in numerical wind predictions. We address this by comparing the non-dimensional velocity magnitude differences between simulations with multiple tree LoDs. To further understand these differences in changing environmental contexts we use three morphologies: an isolated tree, an idealized street, canyon, and a real urban geometry from Rotterdam, The Netherlands The numerical results show that the velocity magnitude differences between the cases with LoD1 tree models and those with LoD2 tree models can be over 1.0 m/s while the differences between LoD2 and LoD3 cases are rather limited, usually lower than 0.2 m/s. Consequently, through this study we highlight the importance of using tree models in LoD2 or LoD3 at least for CFD simulations of wind flows in urban areas. To further support this conclusion we also analyze the impact of changing wind directions and tree Leaf Area Density (LAD) values in the impact of tree LoDs on wind. The differences found in this work linked to the level of realism in your tree models can support future studies where researchers want to make an informed choice.
Reconstructing urban scenarios for computational fluid dynamics simulations typically requires significant manual effort, especially when higher geometrical details are required. To address this issue, we present a workflow to automatically reconstruct buildings in three levels of detail (LoDs): LoD1.2, LoD1.3, and LoD2.2, tailored to urban microscale simulations. The workflow uses a combination of building footprints and a point cloud to segment roof planes, create partitions, optimise planes, and finally assemble roof planes into 3D building models. Reconstructed buildings are seamlessly integrated into the terrain together with different surface layers such as water, low vegetation, and paved surfaces. Apart from three general LoDs, building footprints can be simplified as a part of the 2D generalisation; additionally, smaller surfaces such as chimneys and ventilation shafts can be removed using a graph-cut optimisation. The integrated geometry validator can report on validity of building models, such as watertightness, manifoldness, or occurrences of self-intersections. In the case of invalid geometries, we can generate an approximation: geometry repair the with alpha wrapping algorithm, or reconstruction in lower LoD. We tested our implementation on two different real-world datasets — one in The Netherlands, and another one in the USA. The results showed that 95% (Dutch dataset) and 90% (US dataset) buildings were valid according to the ISO 19107 standard. Generated grids showed satisfactory quality as we observed monotonous convergence in simulations with grid convergence indices up to 3.8% for pressure and velocity variables. These results indicate that the workflow is suitable for typical urban microscale simulations.
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Reconstructing urban scenarios for computational fluid dynamics simulations typically requires significant manual effort, especially when higher geometrical details are required. To address this issue, we present a workflow to automatically reconstruct buildings in three levels of detail (LoDs): LoD1.2, LoD1.3, and LoD2.2, tailored to urban microscale simulations. The workflow uses a combination of building footprints and a point cloud to segment roof planes, create partitions, optimise planes, and finally assemble roof planes into 3D building models. Reconstructed buildings are seamlessly integrated into the terrain together with different surface layers such as water, low vegetation, and paved surfaces. Apart from three general LoDs, building footprints can be simplified as a part of the 2D generalisation; additionally, smaller surfaces such as chimneys and ventilation shafts can be removed using a graph-cut optimisation. The integrated geometry validator can report on validity of building models, such as watertightness, manifoldness, or occurrences of self-intersections. In the case of invalid geometries, we can generate an approximation: geometry repair the with alpha wrapping algorithm, or reconstruction in lower LoD. We tested our implementation on two different real-world datasets — one in The Netherlands, and another one in the USA. The results showed that 95% (Dutch dataset) and 90% (US dataset) buildings were valid according to the ISO 19107 standard. Generated grids showed satisfactory quality as we observed monotonous convergence in simulations with grid convergence indices up to 3.8% for pressure and velocity variables. These results indicate that the workflow is suitable for typical urban microscale simulations.
This paper describes a data driven urban canopy model that can be coupled with detailed building energy models. The data driven model is used to assess the outdoor air temperature and humidity in a street canyon considering as inputs weather conditions at the atmospheric layer, the surface temperature of surrounding building facades and the street, and the heat released from the use of air-conditioning. Predictions made by the model were tested using measurements of the outdoor air temperature and humidity collected between April and August 2019 in Singapore. Results show that the model estimates the outdoor air temperature with a similar accuracy than others that were validated using the same input and test data, while providing estimates with a higher temporal resolution and considering urban morphology with a higher fidelity. They also demonstrate that the model can predict the impact of waste heat releases and cool pavement on the outdoor air temperature and building energy consumption. In the future, vegetation could be considered as an input of the model if the land surface temperature is measured using an infrared thermal camera. Another improvement would be to define weather conditions at the atmospheric layer from rooftop measurements or a climate model.
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This paper describes a data driven urban canopy model that can be coupled with detailed building energy models. The data driven model is used to assess the outdoor air temperature and humidity in a street canyon considering as inputs weather conditions at the atmospheric layer, the surface temperature of surrounding building facades and the street, and the heat released from the use of air-conditioning. Predictions made by the model were tested using measurements of the outdoor air temperature and humidity collected between April and August 2019 in Singapore. Results show that the model estimates the outdoor air temperature with a similar accuracy than others that were validated using the same input and test data, while providing estimates with a higher temporal resolution and considering urban morphology with a higher fidelity. They also demonstrate that the model can predict the impact of waste heat releases and cool pavement on the outdoor air temperature and building energy consumption. In the future, vegetation could be considered as an input of the model if the land surface temperature is measured using an infrared thermal camera. Another improvement would be to define weather conditions at the atmospheric layer from rooftop measurements or a climate model.
Urban building energy modelling aims at studying different approaches to estimate the energy consumed by buildings. However, most urban building energy models introduced in the literature ignore the impact that buildings have on their outdoor conditions, and inversely. Therefore, the paper determines whether interactions between buildings and outdoor conditions affects simulations performed using an urban building energy model, in particular during their calibration. Results suggest that interactions between buildings and their outdoor conditions affect the sensitivity of outcomes provided by an urban building energy model towards uncertain parameters and the probability to calibrate the model in accordance to some standards.
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Urban building energy modelling aims at studying different approaches to estimate the energy consumed by buildings. However, most urban building energy models introduced in the literature ignore the impact that buildings have on their outdoor conditions, and inversely. Therefore, the paper determines whether interactions between buildings and outdoor conditions affects simulations performed using an urban building energy model, in particular during their calibration. Results suggest that interactions between buildings and their outdoor conditions affect the sensitivity of outcomes provided by an urban building energy model towards uncertain parameters and the probability to calibrate the model in accordance to some standards.
As mandatory masking and social distancing measures decrease post-COVID-19, the risk of airborne pathogen transmission in crowded indoor spaces remains a significant public health concern. The pandemic highlighted the critical role of indoor air quality and ventilation in mitigating the spread of infectious diseases, underscoring the urgent need to improve our understanding and prediction of indoor airflow to minimise airborne transmission. In this review, studies on airborne transmission in indoor settings were systematically reviewed to identify research gaps and recommend changes in approach. The analysis is categorised into indoor airflow, dynamics of infectious respiratory particles (IRPs), and investigation methodologies. Findings reveal that almost 40% of the reviewed literature does not specify the type of indoor setting, with only 3% focusing on restaurant environments. Additionally, indoor air conditions are typically assumed to be constant, and respiratory activities are often limited to coughing and breathing. The review identifies the challenge of replicating the complex behaviour of IRPs in experiments and the computational expense of predicting turbulent indoor flows. Recommendations for future research include: i) focusing on social settings like restaurants, ii) considering varying air temperatures and humidity, iii) examining speech-related respiratory flows, and iv) employing visual and accurate tools to investigate particle-laden airflow. These insights aim to enhance public health guidelines and building designs to reduce the risk of airborne diseases.
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As mandatory masking and social distancing measures decrease post-COVID-19, the risk of airborne pathogen transmission in crowded indoor spaces remains a significant public health concern. The pandemic highlighted the critical role of indoor air quality and ventilation in mitigating the spread of infectious diseases, underscoring the urgent need to improve our understanding and prediction of indoor airflow to minimise airborne transmission. In this review, studies on airborne transmission in indoor settings were systematically reviewed to identify research gaps and recommend changes in approach. The analysis is categorised into indoor airflow, dynamics of infectious respiratory particles (IRPs), and investigation methodologies. Findings reveal that almost 40% of the reviewed literature does not specify the type of indoor setting, with only 3% focusing on restaurant environments. Additionally, indoor air conditions are typically assumed to be constant, and respiratory activities are often limited to coughing and breathing. The review identifies the challenge of replicating the complex behaviour of IRPs in experiments and the computational expense of predicting turbulent indoor flows. Recommendations for future research include: i) focusing on social settings like restaurants, ii) considering varying air temperatures and humidity, iii) examining speech-related respiratory flows, and iv) employing visual and accurate tools to investigate particle-laden airflow. These insights aim to enhance public health guidelines and building designs to reduce the risk of airborne diseases.
During the COVID-19 pandemic, the importance of ventilation for ensuring occupants’ health was widely stressed, especially for densely occupied places such as schools (Ding et al, 2022). Correspondingly, new protocols of ventilation were implemented in school buildings among many countries and regions. In the Netherlands, school classrooms were first required to keep the windows and doors open, and later after a national lockdown more stringent measures such as reducing student occupancy were introduced. Previous studies have already shown that the ventilation in a large portion of school classrooms did not meet the requirement (National Ventilation Coordination Team, 2020). However, what are the actual effects of the COVID-19 measures on ventilation in school classrooms remains unclear.
This study aims to investigate 1) the ventilation sufficiency, and 2) the ventilation-related effects of temporary pandemic control and prevention measures in school classrooms under the COVID-19 pandemic.
...
During the COVID-19 pandemic, the importance of ventilation for ensuring occupants’ health was widely stressed, especially for densely occupied places such as schools (Ding et al, 2022). Correspondingly, new protocols of ventilation were implemented in school buildings among many countries and regions. In the Netherlands, school classrooms were first required to keep the windows and doors open, and later after a national lockdown more stringent measures such as reducing student occupancy were introduced. Previous studies have already shown that the ventilation in a large portion of school classrooms did not meet the requirement (National Ventilation Coordination Team, 2020). However, what are the actual effects of the COVID-19 measures on ventilation in school classrooms remains unclear.
This study aims to investigate 1) the ventilation sufficiency, and 2) the ventilation-related effects of temporary pandemic control and prevention measures in school classrooms under the COVID-19 pandemic.
Using Landsat land surface temperature as a proxy for air temperature in urban settings
Experiments in the Netherlands
Understanding the UHI effect in any city requires high-resolution temperature data. This data is often difficult to obtain as cities usually have only a few ground sensors, leaving large data gaps. To fill these gaps, we compare Landsat-derived land surface temperature (LST) with air temperature (Tair) measurements from urban weather stations in the two largest cities in the Netherlands. Previous studies of this kind have often been limited due to a few main factors: low spatial resolution, limited weather station data and small sample sizes (Chung et al., 2020, Mutiibwa, 2015; Sheng 2017; Xiong, 2017; Yang, 2020). As a result, findings have been inconsistent, albeit mostly promising. Addressing these issues and adding to Burnett and Chen’s (2021) extensive comparison on a regional scale in Ontario, Canada, we present a reproducible, code-based approach focusing on cities. Using 149 Landsat scenes and data from 33 urban weather stations in the Netherlands (24 in Amsterdam, 9 in Rotterdam) between 2013-2022, 1700 comparison points across all European seasons are established.
We find that there is a strong positive and significant linear relationship between LST and Tair across the dataset (r = .89). OLS regression results indicate 80% of the Tair variation can be explained by the LST, with Tair increasing by 0.62°C for every 1°C increase in LST. Analyses were repeated to account for seasonality, each station's local climate zone (Stewart and Oke, 2012) as well as mean absolute error and root mean square error to interrogate the discrepancy, all of which will be highlighted in the presentation. Overall, our evidence suggests that LST can indeed be a suitable proxy for Tair and could consequently form an additional decision-making layer to assist climate monitoring and urban planning in the Netherlands as well as similar climates.
...
Understanding the UHI effect in any city requires high-resolution temperature data. This data is often difficult to obtain as cities usually have only a few ground sensors, leaving large data gaps. To fill these gaps, we compare Landsat-derived land surface temperature (LST) with air temperature (Tair) measurements from urban weather stations in the two largest cities in the Netherlands. Previous studies of this kind have often been limited due to a few main factors: low spatial resolution, limited weather station data and small sample sizes (Chung et al., 2020, Mutiibwa, 2015; Sheng 2017; Xiong, 2017; Yang, 2020). As a result, findings have been inconsistent, albeit mostly promising. Addressing these issues and adding to Burnett and Chen’s (2021) extensive comparison on a regional scale in Ontario, Canada, we present a reproducible, code-based approach focusing on cities. Using 149 Landsat scenes and data from 33 urban weather stations in the Netherlands (24 in Amsterdam, 9 in Rotterdam) between 2013-2022, 1700 comparison points across all European seasons are established.
We find that there is a strong positive and significant linear relationship between LST and Tair across the dataset (r = .89). OLS regression results indicate 80% of the Tair variation can be explained by the LST, with Tair increasing by 0.62°C for every 1°C increase in LST. Analyses were repeated to account for seasonality, each station's local climate zone (Stewart and Oke, 2012) as well as mean absolute error and root mean square error to interrogate the discrepancy, all of which will be highlighted in the presentation. Overall, our evidence suggests that LST can indeed be a suitable proxy for Tair and could consequently form an additional decision-making layer to assist climate monitoring and urban planning in the Netherlands as well as similar climates.
The corona pandemic accelerated a lot of studies about aerosol dispersion and different aerosol-generating tasks ranging in intensity from sneezing to breathing. Both measurements and numerical simulations were used to understand the behaviour of aerosols. For numerical simulations, Computational Fluid Dynamic (CFD) simulations were used; however, the set-up of cases varied between studies. Different solvers, methods, turbulence models and steadiness are used depending on the scope and aim of each study. The aim of this study is to compare different set-ups and solvers and validate them against measurements conducted in the Senselab at the Delft University of Technology. The purpose is to find the best approach that balances between accuracy and computational cost to use afterwards in ventilation design decision-making. Consequently, we set up several numerical cases with different levels of complexities (e.g.: eulerian-eulerian to eulerian-lagrangian, including/excluding temperature and relative humidity, steady/unsteady). We then compare those cases to the experiments of a breathing manikin in the Senselab. The performance of each case is determined depending on how well it predicts aerosol dispersion and the run time cost.
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The corona pandemic accelerated a lot of studies about aerosol dispersion and different aerosol-generating tasks ranging in intensity from sneezing to breathing. Both measurements and numerical simulations were used to understand the behaviour of aerosols. For numerical simulations, Computational Fluid Dynamic (CFD) simulations were used; however, the set-up of cases varied between studies. Different solvers, methods, turbulence models and steadiness are used depending on the scope and aim of each study. The aim of this study is to compare different set-ups and solvers and validate them against measurements conducted in the Senselab at the Delft University of Technology. The purpose is to find the best approach that balances between accuracy and computational cost to use afterwards in ventilation design decision-making. Consequently, we set up several numerical cases with different levels of complexities (e.g.: eulerian-eulerian to eulerian-lagrangian, including/excluding temperature and relative humidity, steady/unsteady). We then compare those cases to the experiments of a breathing manikin in the Senselab. The performance of each case is determined depending on how well it predicts aerosol dispersion and the run time cost.
The corona pandemic underlined a lack of Indoor Air Quality (IAQ) and
ventilation. Consequently, to limit the spread of the virus, researchers explored several indicators that, through different approaches, assess IAQ and ventilation performance in indoor spaces. This paper gives an overview of those indicators and assessment methods used to evaluate IAQ and ventilation regimes focusing specifically on airborne pathogens. This review considers studies from before and during the COVID-19 pandemic. The indicators found fit into three categories: dose, building, and occupant-related indicators. Studies exploring assessment methods found in this review are grouped according to their themes: aerosol dispersion, ventilation, infection risk, design parameters, and human behaviour. The review showed a need for a holistic definition for IAQ indicators that includes all indicators and a holistic approach of studying IAQ including all five themes.
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The corona pandemic underlined a lack of Indoor Air Quality (IAQ) and
ventilation. Consequently, to limit the spread of the virus, researchers explored several indicators that, through different approaches, assess IAQ and ventilation performance in indoor spaces. This paper gives an overview of those indicators and assessment methods used to evaluate IAQ and ventilation regimes focusing specifically on airborne pathogens. This review considers studies from before and during the COVID-19 pandemic. The indicators found fit into three categories: dose, building, and occupant-related indicators. Studies exploring assessment methods found in this review are grouped according to their themes: aerosol dispersion, ventilation, infection risk, design parameters, and human behaviour. The review showed a need for a holistic definition for IAQ indicators that includes all indicators and a holistic approach of studying IAQ including all five themes.
The COVID-19 pandemic highlighted the importance of indoor air quality (IAQ) and ventilation, which researchers have been warning about for years. During the pandemic, researchers studied several indicators using different approaches to assess IAQ and diverse ventilation systems in indoor spaces. To provide an overview of these indicators and approaches in the case of airborne transmission through aerosols, we conducted a literature review, which covered studies both from before and during the COVID-19 pandemic. We searched online databases for six concepts: aerosol dispersion, ventilation, air quality, schools or offices, indicators, and assessment approaches. The indicators found in the literature can be divided into three categories: dose-, building-, and occupant-related indicators. These indicators can be measured in real physical spaces, in a controlled laboratory, or modeled and analyzed using numerical approaches. Rather than organizing this paper according to these approaches, the assessment methods used are grouped according to the following themes they cover: aerosol dispersion, ventilation, infection risk, design parameters, and human behavior. The first finding of the review is that dose-related indicators are the predominant indicators used in the selected studies, whereas building- and occupant-related indicators are only used in specific studies. Moreover, for a better understanding of airborne transmission, there is a need for a more holistic definition of IAQ indicators. The second finding is that although different design assessment tools and setups are presented in the literature, an optimization tool for a room’s design parameters seems to be missing. Finally, to efficiently limit aerosol dispersion in indoor spaces, better coordination between different fields is needed.
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The COVID-19 pandemic highlighted the importance of indoor air quality (IAQ) and ventilation, which researchers have been warning about for years. During the pandemic, researchers studied several indicators using different approaches to assess IAQ and diverse ventilation systems in indoor spaces. To provide an overview of these indicators and approaches in the case of airborne transmission through aerosols, we conducted a literature review, which covered studies both from before and during the COVID-19 pandemic. We searched online databases for six concepts: aerosol dispersion, ventilation, air quality, schools or offices, indicators, and assessment approaches. The indicators found in the literature can be divided into three categories: dose-, building-, and occupant-related indicators. These indicators can be measured in real physical spaces, in a controlled laboratory, or modeled and analyzed using numerical approaches. Rather than organizing this paper according to these approaches, the assessment methods used are grouped according to the following themes they cover: aerosol dispersion, ventilation, infection risk, design parameters, and human behavior. The first finding of the review is that dose-related indicators are the predominant indicators used in the selected studies, whereas building- and occupant-related indicators are only used in specific studies. Moreover, for a better understanding of airborne transmission, there is a need for a more holistic definition of IAQ indicators. The second finding is that although different design assessment tools and setups are presented in the literature, an optimization tool for a room’s design parameters seems to be missing. Finally, to efficiently limit aerosol dispersion in indoor spaces, better coordination between different fields is needed.
Ventilation and thermal conditions in secondary schools in the Netherlands
Effects of COVID-19 pandemic control and prevention measures
Journal article
(2023)
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Er Ding, D. Zhang, A.B. Hamida, C. Garcia Sanchez, Lotte Jonker, Annemarijn R. de Boer, Patricia C.J.L. Bruijning, Kimberly J. Linde, Inge M. Wouters, P.M. Bluyssen
During the COVID-19 pandemic, the importance of ventilation was widely stressed and new protocols of ventilation were implemented in school buildings worldwide. In the Netherlands, schools were recommended to keep the windows and doors open, and after a national lockdown more stringent measures such as reduction of occupancy were introduced. In this study, the actual effects of such measures on ventilation and thermal conditions were investigated in 31 classrooms of 11 Dutch secondary schools, by monitoring the indoor and outdoorCO2 concentration and air temperature, both before and after the lockdown. Ventilation rates were calculated using the steady-state method. Pre-lockdown, with an average occupancy of 17 students, in 42% of the classrooms the CO2 concentration exceeded the upper limit of the Dutch national guidelines (800 ppm above outdoors),while 13% had a ventilation rate per person (VRp) lower than the minimum requirement (6 l/s/p). Post lockdown, the indoor CO2 concentration decreased significantly while for ventilation rates significant increase was only found in VRp, mainly caused by the decrease in occupancy (average 10 students). The total ventilation rate per classrooms, mainly induced by opening windows and doors, did not change significantly. Meanwhile, according to the Dutch national guidelines, thermal conditions in the classrooms were not satisfying, both pre and post-lockdown. While opening windows and doors cannot achieve the required indoor environmental quality at all times, reducing occupancy might not be feasible for immediate implementation. Hence, more controllable and flexible ways for improving indoor air quality and thermal comfort in classrooms are needed.
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During the COVID-19 pandemic, the importance of ventilation was widely stressed and new protocols of ventilation were implemented in school buildings worldwide. In the Netherlands, schools were recommended to keep the windows and doors open, and after a national lockdown more stringent measures such as reduction of occupancy were introduced. In this study, the actual effects of such measures on ventilation and thermal conditions were investigated in 31 classrooms of 11 Dutch secondary schools, by monitoring the indoor and outdoorCO2 concentration and air temperature, both before and after the lockdown. Ventilation rates were calculated using the steady-state method. Pre-lockdown, with an average occupancy of 17 students, in 42% of the classrooms the CO2 concentration exceeded the upper limit of the Dutch national guidelines (800 ppm above outdoors),while 13% had a ventilation rate per person (VRp) lower than the minimum requirement (6 l/s/p). Post lockdown, the indoor CO2 concentration decreased significantly while for ventilation rates significant increase was only found in VRp, mainly caused by the decrease in occupancy (average 10 students). The total ventilation rate per classrooms, mainly induced by opening windows and doors, did not change significantly. Meanwhile, according to the Dutch national guidelines, thermal conditions in the classrooms were not satisfying, both pre and post-lockdown. While opening windows and doors cannot achieve the required indoor environmental quality at all times, reducing occupancy might not be feasible for immediate implementation. Hence, more controllable and flexible ways for improving indoor air quality and thermal comfort in classrooms are needed.