Indoor air quality (IAQ) is an important aspect of maintaining human health and well-being, particularly since people spend most of their time indoors. Carpets, with their large surface area and dense fibre piles, have the potential to significantly impact IAQ by emitting and absorbing volatile organic compounds (VOC) from building materials and human activities. The cleaning effect of wool carpets regarding the sorption of odours from two sources of pollution: hardboard and sweaty underwear (as a proxy for bio-effluents), was investigated with an untrained panel of subjects assessing the odour intensity and the acceptability. Tests were performed in three different test environments, including a sniffing table, CLIMPAQs, and full-scale test chambers. The outcome showed that wool carpets can potentially clean the air of odours in small-scale environments, where the wool carpet covers the floor and walls of the test environment, and the odour sources are in contact with the wool carpet. However, the results were less conclusive in on scale scenarios where wool carpets only covered the floor. Overall, wool carpets have the potential to ad(b)sorb odorous emissions, but only when these emissions are near the wool carpet, and thus can have the opportunity to be ad(b)sorbed.@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 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

Noise simulations are an important part of noise studies that investigate the impact of noise sources on the environment. In noise simulation, noise levels at receiver points are calculated based on the noise propagation paths between the receiver and source points. These paths are derived from the height of the terrain. In current calculation approaches implemented in noise simulation software, 3D polylines are used as input to describe the height of the terrain. These 3D polylines are semi-automatically generated to meet the highly demanding computing performance of simulation software. In addition, previous research showed that the reconstruction of appropriate height lines as used in noise simulation is very difficult to automate, if not impossible As a solution, this research investigates how noise propagation paths between receiver and source points can directly be generated from a Triangulate Irregular Network (TIN) without creating the height lines. This would allow us to use the automatically generated TIN as input for noise simulation instead of the height lines. In addition, a TIN enables better control of the quality of the data than height lines do. This study uses the 3D noise modeling guidelines of Common Noise Assessment Methods in Europe (CNOSSOS-EU). Algorithms have been developed and implemented in a prototype to generate and validate the paths between receiver and source points using a TIN that includes the buildings as well as the noise absorption properties of the terrain. The prototype is successfully tested on two scenarios from the Netherlands. Since CNOSSOS-EU guidelines were used, the prototype is applicable to the entire European Union and can be the first step in improving the automation of 3D noise modeling using currently available techniques and data.@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

Municipalities invest a lot of time and person-hours into manual building permit checks. With the increase in computational power and the use of Building Information Models (BIM) in the building design life cycle, several municipalities are investing in automating these checks using BIM and geo-data sets. However, few examples exist of tools effectively using geo-information with BIM. In order to address this gap, a project was developed with the municipality of Rotterdam (NL). In a previous phase, a tool was implemented, able to analyse the BIM data to extract the needed information for a few representative regulations. In order to extend and improve the previously developed tool, a web-based interface is now implemented and geo-data sets are integrated to the process allowing more powerful GeoBIM analysis. Three checks using both BIM and GIS data were implemented and tested: (i) The parcel limit check evaluates if the building's footprint derived from BIM falls within the parcel limit provided from the municipalities' parcel data sets. (ii) The height check evaluates the maximum building's relative height to the road's height. Finally, (iii) the road overhang check detects neighbouring roads to the parcel and evaluates the admissible overhang over that road. This paper presents these developments, including the type of input data that is needed for the checks, the tools for the three new GeoBIM checks (parcel limit check, height check, road overhang check) and the implementation in the web-based tool.

@en