Source reconstruction of airborne toxics based on acute health effects information

Airborne transmission of biological agents within the indoor built environment: a multidisciplinary review

The nature and airborne dispersion of the underestimated biological agents, monitoring, analysis and transmission among the human occupants into building environment is a major challenge of today. Those agents play a crucial role in ensuring comfortable, healthy and risk-free conditions into indoor working and leaving spaces. It is known that ventilation systems influence strongly the transmission of indoor air pollutants, with scarce information although to have been reported for biological agents until 2019. The biological agents' source release and the trajectory of airborne transmission are both important in terms of optimising the design of the heating, ventilation and air conditioning systems of the future. In addition, modelling via computational fluid dynamics (CFD) will become a more valuable tool in foreseeing risks and tackle hazards when pollutants and biological agents released into closed spaces. Promising results on the prediction of their dispersion routes and concentration levels, as well as the selection of the appropriate ventilation strategy, provide crucial information on risk minimisation of the airborne transmission among humans. Under this context, the present multidisciplinary review considers four interrelated aspects of the dispersion of biological agents in closed spaces, (a) the nature and airborne transmission route of the examined agents, (b) the biological origin and health effects of the major microbial pathogens on the human respiratory system, (c) the role of heating, ventilation and air-conditioning systems in the airborne transmission and (d) the associated computer modelling approaches. This adopted methodology allows the discussion of the existing findings, on-going research, identification of the main research gaps and future directions from a multidisciplinary point of view which will be helpful for substantial innovations in the field.

Impact of Weak Signals on the Digitalization of Risk Analysis in Process Safety Operational Environments

Weak signals in risk analysis digitalization are of great importance for preventing major accidents in risk analysis in the process industry, especially for process operations and production. However, some of the negative impacts are incorrect operational risk identification, significant inventory carrying costs, disruption of risk frequency, and risk consequence analysis, all of which will signal inaccurate information about unforeseen and current dangers in process facilities and operational environments. While the positive impacts are viewed as an early warning system that provides information on operational risk system status, the identification of potential risk weaknesses in process facilities, indicators of a transition or an emerging problem that may become significant in the future, highlighting future assumptions, challenge our views of the future and expand the selection of a processing facility. Lastly, weak signal identification in the digitalization of risk analysis can provide relevant information in supporting, assessing and analyzing the risks associated with the operation, in order to design a technical system and estimate the industry’s level of accident risk, as well as the possible control of a system. The present research will provide valuable information to the process industry on how to protect their operational facilities and increase process safety by providing information on weak safety risk monitoring systems in operations, strengthening the processes of the operational area.

Concept and demonstration of a fully coupled and dynamic exposure-response methodology for crowd evacuation numerical modelling in airborne-toxic environments

Evacuation simulation plays an indispensable role when planning for emergencies and evaluating the consequences of disasters related to airborne toxics. Various attempts have been made to improve simulation of evacuation in toxic environments and to account for the varying concentration levels and the dynamic exposure. However, most studies neglect the reverse effect, how the exposure and dosage levels affect the physical and psychological state of an evacuee and consequently the evacuation path and process. In this work, a fully coupled exposure-response-evacuation and agent based algorithm is proposed, focusing on the H₂S airborne toxic. Accordingly, the dynamically estimated exposure of the evacuee affects, non-linearly, the evacuation speed and thus the overall evacuation. This coupling is challenging and thus it depends on the available epidemiological and toxicological data. Nevertheless, the diversity and advantages of the algorithm is successfully demonstrated over three case studies including single- and multi-agent in straight-path and building evacuation scenarios. For example, the building evacuation time increased by more than 50% by inclusion of the aforementioned coupling. In conclusion, herein, a gap on the evacuation modelling is addressed by a fully coupled methodology that could be easily adapted by safety engineers and further improved by researchers as more data become available.

Implicit Definition of Flow Patterns in Street Canyons—Recirculation Zone—Using Exploratory Quantitative and Qualitative Methods

Air pollution is a major health hazard for the population that increasingly lives in cities. Street-scale Air Quality Models (AQMs) are a cheap and efficient way to study air pollution and possibly provide solutions. Having to include all the complex phenomena of wind flow between buildings, AQMs employ several parameterisations, one of which is the recirculation zone. Goal of this study is to derive an implicit or explicit definition for the recirculation zone from the flow in street canyons using computational fluid dynamics (CFD). Therefore, a CFD-Large Eddy Simulation model was employed to investigate street canyons with height to width ratio from 1 to 0.20 under perpendicular wind direction. The developed dataset was analyzed with traditional methods (vortex visualization criteria and pollutant dispersion fields), as well as clustering methods (machine learning). Combining the above analyses, it was possible to extract qualitative features that agree well with literature but most importantly to develop quantitative expressions that describe their topology. The extracted features’ topology depends strongly on the street canyon dimensions and not surprisingly is independent of the wind velocity. The developed expressions describe areas with common flow characteristics inside the canyon and thus they can be characterised as an implicit definition for the recirculation zone. Furthermore, the presented methodology can be further applied to cover more parameters such us oblique wind direction and heated-facades and more methods for data analysis.

Qualitative and Quantitative Investigation of Multiple Large Eddy Simulation Aspects for Pollutant Dispersion in Street Canyons Using OpenFOAM

Air pollution is probably the single largest environment risk to health and urban streets are the localized, relevant hotspots. Numerous studies reviewed the state-of-the-art models, proposed best-practice guidelines and explored, using various software, how different approaches (e.g., Reynolds-averaged Navier–Stokes (RANS), large eddy simulations (LES)) inter-compare. Open source tools are continuously attracting interest but lack of similar, extensive and comprehensive investigations. At the same time, their configuration varies significantly among the related studies leading to non-reproducible results. Therefore, the typical quasi-2D street canyon geometry was selected to employ the well-known open-source software OpenFOAM and to investigate and validate the main parameters affecting LES transient simulation of a pollutant dispersion. In brief, domain height slightly affected street level concentration but source height had a major impact. All sub-grid scale models predicted the velocity profiles adequately, but the k-equation SGS model best-resolved pollutant dispersion. Finally, an easily reproducible LES configuration is proposed that provided a satisfactory compromise between computational demands and accuracy.