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.@en

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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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.@en

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.@en

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.@en

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.@en

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. @en

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.@en

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.@en

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.@en

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.@en

In the computational fluid dynamics simulation workflow, the geometry preparation step is often regarded as a tedious, time-consuming task. Many practitioners consider it one of the main bottlenecks in the simulation process. The more complex the geometry, the longer the necessary work, meaning this issue is amplified for urban flow simulations that cover large areas with complex building geometries. To address the issue of geometry preparation, we propose a workflow for automatically reconstructing simulation-ready 3D city models. The workflow combines 2D geographical datasets (e.g., cadastral data, topographic datasets) and aerial point cloud-based elevation data to reconstruct terrain, buildings, and imprint surface layers like water, low vegetation, and roads. Imprinted surface layers serve as different roughness surfaces for modeling the atmospheric boundary layer. Furthermore, the workflow is capable of automatically defining the influence region and domain size according to best practice guidelines. The resulting geometry aims to be error-free: without gaps, self-intersections, and non-manifold edges. The workflow was implemented into an open-source framework using modern, robust, and state-of-the-art libraries with the intent to be used for further developments. Our approach limits the geometry generation step to the order of hours (including input data retrieval and preparation), producing geometries that can be directly used for computational grid generation without additional preparation. The reconstruction done by the algorithm can last from a few seconds to a few minutes, depending on the size of the input data. We obtained and prepared the input data for our verification study in about 2 hours, while the reconstruction process lasted 1 minute. The unstructured computational meshes we created in an automatic mesh generator show satisfactory quality indicators and the subsequent numerical simulation exhibits good convergence behavior with the grid convergence index of observed variables less than 5%@en

Climate change and urbanization rates are transforming urban environments, making the use of 3D city models in computational fluid dynamics (CFD) a fundamental ingredient to evaluate urban layouts before construction. However, current geometries used in CFD simulations tend to be built by CFD experts to test specific cases, most of the times oversimplifying their designs due to lack of information or in order to reduce complexity. In this work we explore what are the effects of oversimplifying geometries by comparing wind simulations of different level of detail geometries. We use semantic 3D city models automatically built and adjust them to their suitable use in CFD. For the first test, we explore wind simulations within a troublesome section of the TUDelft campus, the passage next to the EWI building (the tallest building in our domain), where the use of 3D city model variants show how differences in geometry and surface properties affect local wind conditions. Finally we analyze what these differences in velocity magnitude could mean for practitioners in terms of pedestrian wind comfort.

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As a first step toward achieving full physics urban weather simulation capabilities within the resident-GPU large-eddy simulation (LES) FastEddy® model, we have implemented and verified/validated a method for explicit representation of building effects. Herein, we extend the immersed body force method (IBFM) from Chan and Leach (2007, https://doi.org/10.1175/2006JAMC1321.1) to (i) be scale independent and (ii) control building surface temperatures. Through a specific drag-like term in the momentum equations, the IBFM is able to enforce essentially zero velocities within the buildings, in turn resulting in a no-slip boundary condition at the building walls. In addition, we propose similar forcing terms in the energy and mass conservation equations that allow an accurate prescription of the building temperature. The extended IBFM is computationally efficient and has the potential to be coupled to building energy models. The IBFM exhibits excellent agreement with laboratory experiments of an array of staggered cubes at a grid spacing of (Formula presented.) mm, demonstrating the applicability of the method beyond the atmospheric scale. In addition, the IBFM is validated at atmospheric scale through simulations of downtown Oklahoma City ((Formula presented.) m) using data collected during the Joint Urban 2003 (JU03) field campaign. Our LES IBFM results for mean wind speed, turbulence kinetic energy, and SF₆ transport and dispersion compare well to observations and produce turbulence spectra that are in good agreement with sonic anemometer data. Statistical performance metrics for the JU03 simulations are within the range of other LES models in the literature.

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Hypoxia, a condition of low dissolved oxygen concentration, is a widespread problem in marine and freshwater ecosystems. To date, prevention and mitigation of hypoxia has centered on nutrient reduction to prevent eutrophication. However, nutrient reduction is often slow and sometimes insufficient to remedy hypoxia. We investigate the utility of a complementary strategy of pumping oxygenated surface water to depth, termed induced downwelling, as a technique to remedy hypoxia in the bottom water of marine and freshwater ecosystems. We introduce simple energy-based models and apply them to depth profiles in hypoxic estuaries, lakes, and freshwater reservoirs. Our models indicate that induced downwelling may be ~3 to 102 times more efficient than bubbling air, and 104 to 106 times more efficient than fountain aerators, at oxygenating hypoxic bottom waters. A proof-of-concept downwelling field experiment highlighted potential advantages and shortcomings. We estimate that regional-scale downwelling for continual hypoxia avoidance would require 0.4 to 4 megawatts per cubic kilometer of water (depending on local conditions), or 50 to 500 US dollars per hour per cubic kilometer of water (assuming 125 USD MWh−1 of electricity). Many potential side effects of downwelling are discussed, each of which would need to be explored and assessed before implementation. Downwelling does not replace nutrient management strategies, but under some circumstances may provide an efficient means to augment these strategies.@en

Eerder publiceerden we in Geo-Info over onze methode om 3D-data zoals nodig in geluidsimulaties automatisch te genereren uit landsdekkende gegevens zoals BAG, BGT en hoogtepunten [1]. Deze geluidsimulaties zijn gebaseerd op gestandaardiseerde rekenvoorschriften voor geluids- belasting. Ook het berekenen van de luchtkwaliteit ten gevolge van binnenstedelijk verkeer kent een Standaard Rekenmethode, beheerd door het RIVM. Deze methode is onder andere gebaseerd op de afstand tussen gebouwen en de weg en hoogtes van deze gebouwen, met andere woorden: een mooi 3D-geo informatievraagstuk. Daarom hebben we met een groep Geomatics-studenten gekeken of we deze informatie automatisch kunnen genereren, zodat de luchtverontreiniging ten gevolge van verkeer op landelijke schaal kan worden berekend.@en