European inland shipping is facing a series of challenges over the next decades as waterways and their connected land infrastructures are exposed to risks related to climate hazard and decarbonization requirements, while demand for availability and reliability will increase. In the frame of the PLOTO project, mesoscale and microscale models are used to assess exposure of inland waterways and ports to climatic risk, under selected climatic scenarios. Starting from long-term climatic series provided by regional-scale climate models, an analysis of local exposure to climate hazards has been performed, by applying a dynamical downscaling methodology over three case-study areas in mainland Europe: Wallonia, the Budapest port, and the Lower Danube area in Romania. The analysis has led to a quantification of hazards related to drought and flood events, heavy rainfall and ice, as well as intense wind gusts over a period of 100 years. A high-resolution building-resolving Large-Eddy Simulation approach is used to obtain a comprehensive library of representative maps of wind velocity over sensitive infrastructures. At slightly larger scale, a near-real-time forecast system based on the mesoscale model MEMO has been implemented, providing hourly nowcasted fields of wind, temperature and precipitation, as well as next-day forecasts, over the three case study areas. The system makes use of measurement data from terrestrial networks and is integrated in the operational PLOTO platform coupled with a hydrological/soil module, providing real-time alerts of meteorological events. The presented approach strongly supports downscaling modelling studies provided that high-resolution local morphology data is available.

Nowadays, it is common to build wind farms in forested areas as wind-energy production is growing rapidly. However, surrounding forests change the local wind conditions drastically, and therefore, there is a need to understand the interaction between local wind conditions and forest properties. The present work aims to investigate the impact of various forest densities on the flow characteristics in the lower part of the Atmospheric Boundary-Layer (ABL). Here, Large-Eddy Simulations (LES) of wind flow over horizontally homogeneous forest canopies were carried out for four different forest densities. The selected forest cases range from extremely dense forests with a Leaf Area Index (LAI) of 10.5 to extremely sparse forests with an LAI of 0.44. The LES results reveal a strong impact of forest density on wind shear and turbulence at rotor-relevant heights. At hub height, the wind-shear exponent varies by up to 16 ≈ 2.2 - 4.4) produce up to 24

A methodology is presented for downscaling the wind projections of Euro-CORDEX in order to derive temporally and spatially correlated region-wide wind fields that can be used for assessing the wind risk for cultural heritage sites. The coarse spatial and temporal resolutions of the Euro-CORDEX projections prohibit their use as a direct input for such purposes, especially for cultural heritage assets that are spatially distributed within the Euro-CORDEX grid and dynamically respond differently to wind. To improve the temporal resolution of the Euro-CORDEX data, we leverage machine learning tools and weather station measurements, aiming to generate composite “Frankenstein” days at the locations of the weather stations that comprise 144 jigsaw pieces of actually measured 10min wind time-series that are matched together to form a continuous daily record. The “Frankenstein” days are expanded spatially to all locations where critical assets can be found by employing spatially distributed wind fields that are computed via high-fidelity computational fluid dynamics simulations and provide contemporaneous wind values at all locations of interest. This process allows generating “Frankenstein” days and wind fields with a temporal resolution of 10min and spatial resolution that allows assessing the wind risk for spatially distributed assets. As a case study, the Euro-CORDEX wind projections are downscaled for the cultural heritage village of Metsovo that is found at the Western part of Greece. Most of the buildings within this village are made of stone masonry and tiled roofs and are vulnerable to extreme wind actions as wind can cause damages e.g., on the tiled roofs thus making the buildings vulnerable to rainfall, or even lead to their partial or complete failure. Thus, the Frankenstein days and wind fields are employed for assessing the wind risk for the cultural heritage buildings of Metsovo both on an event-basis and in the long-term.

Dispersion in urban areas is difficult to simulate accurately due to, among other things, the complex interaction between the wind and topographical features. We perform a large eddy simulation on the dispersion of an inert pollutant in the city of Turku, Finland. The pollutant is released from a point source located at the top of a stack of a heating plant. Our simulations produce an irregular plume with a complex shape. The spreading of the plume appears to be influenced by buildings, trees, and terrain.

In the present work, the PALM-LES model is employed to study different indoor dispersion problems utilizing a dental treatment room as a test space. With high-resolution modeling, the structured LES solver is applied to different indoor configurations with varying ventilation conditions and room geometries. The aim is to investigate the role of enhanced mixing in indoor dispersion problems. The findings demonstrate that improved mixing lowers overall concentration levels and dilutes local concentration peaks indoors. These positive impacts can be achieved by moderate means, for example by employing a simple table fan.

Differences between time-averaged and ensemble-averaged wind are studied for the case of changing wind direction. We consider a flow driven by a temporally turning pressure gradient in both an idealized case of a staggered cube array and a realistic urban environment. The repeating structure of the idealized case allows us to construct a large ensemble of 3240 members with a reasonable compute time. The results indicate that the use of plain time averaging instead of an ensemble average can severely reduce the accuracy of both the mean and variance. These errors are the largest when the averaging time is of the same order as the time scale associated with the turning. Utilizing Taylor diagrams, we show that a reasonable compromise between ensemble size and accuracy can be achieved by calculating the ensemble statistics from temporally averaged results with an averaging time that is clearly smaller than the characteristic time scale. This allows the use of reasonably-sized ensembles with 10–50 members. By applying this approach to the realistic urban geometry, we identify building wakes as the regions most severely affected by the incorrectly use of time averaging.

Modeling indoor contaminant dispersion is crucial for exposure analysis in fields like occupant safety and infection prevention. Accurate predictions necessitate appropriate computational approaches because numerical solutions to turbulent indoor flow conditions are vulnerable to modeling errors. Large-eddy simulation (LES) is a turbulence-resolving approach with the potential to describe the relevant flow physics governing indoor contaminant dispersion. This work documents a quantitative validation study of the PALM LES model against experimental indoor dispersion measurements. The experiments were conducted in a controlled chamber with a mechanical ventilation system operated at two different ventilation flow rates (2 and 5 air changes per hour). The LES results were obtained using three different resolutions (1, 1.5, and 2 cm), labeled Fine, Medium, and Coarse. The evolution of particle concentration was monitored identically in the chamber and the LES model using a multipoint measurement network. The validation analysis assessed the performance of the PALM LES model in predicting aerosol dispersion using four validation metrics. The results indicated strong performance for the fine model under both ventilation rates. Validation performance declined with reduced resolution, and the coarse model demonstrated evidently lower accuracy due to deficiencies in capturing thermal stratification effects. Sensitivity analysis revealed that the validation results were largely unaffected by changes in thermal boundary conditions. This study highlights the importance of model resolution in predicting indoor contaminant dispersion and cautions against assuming predictive capacity in thermal modeling based on dispersion modeling results.

Large-Eddy Simulation (LES) has proved to be a very suitable modelling approach for a wide variety of practical dispersion-related air quality and risk analyses applications. We will demonstrate this by presenting results from three different modelling applications labelled LEScape, Car-LES and Indoor LES employing the PALM LES model system. The first two applications, LEScape and Car-LES, are novel approaches involving dispersion problems within real urban environments. The former concerns the dispersion of hazardous releases whereas the latter deals with pollutant concentrations due to traffic emissions. The Indoor LES application, on the other hand, examines the dispersion and exposure to locally released contaminants or pathogens under indoor ventilation conditions with unprecedented resolution.

A methodology is presented for downscaling the Euro-CORDEX climatic projections in order to derive spatially and temporally correlated weather fields that can be used for risk and resilience assessment of large-scale asset portfolios or interconnected infrastructure. The temporal resolution of the Euro-CORDEX data is downscaled to a 10 min basis by employing a modified analogue-type approach that utilizes the k-NN algorithm along with measurements from weather stations. The aim is to generate composite "Frankenstein" days comprising 144 jigsaw pieces of observed 10 min timeseries that are scaled and/or shifted, and matched together to form a continuous daily record. These point-estimates, valid only at the locations of the weather stations, are expanded spatially by employing high-fidelity weather intensity measure fields that provide variable yet synchronous patterns of weather parameters at all locations of interest. As a case study, the Euro-CORDEX projections for wind, temperature, and precipitation are downscaled for the Metsovo-Panagia segment of Egnatia Odos highway in Greece, by employing high-fidelity Computational Fluid Dynamic simulations that account for the topography of the site to simulate turbulent wind flows. These are combined with measurements of two local weather stations to generate the Frankenstein timeseries and corresponding weather fields that can be used for estimating operability, recovery and direct/indirect loss statistics on an event-by-event basis for an ensemble of interconnected highway assets.

AbstractMore than 37,000 km of waterways connect hundreds of cities and industrial regions in Europe. These inland waterways play an important role in the transport of goods. The EU-funded PLOTO project aims at studying the resilience of the infrastructure of inland waterways and that of the connected land infrastructure. The main objective of the project is to ensure reliable network availability under unfavourable conditions (e.g. extreme weather, accidents, as well as other kind of hazards). PLOTO utilises high-resolution modelling data to assess climatic risk and focuses on the design of an innovative planning tool that can run ‘what if’ impact/risk/resilience assessment scenarios.

COVID-19 has highlighted the need for indoor risk-reduction strategies. Our aim is to provide information about the virus dispersion and attempts to reduce the infection risk. Indoor transmission was studied simulating a dining situation in a restaurant. Aerosolized Phi6 viruses were detected with several methods. The aerosol dispersion was modeled by using the Large-Eddy Simulation (LES) technique. Three risk-reduction strategies were studied: (1) augmenting ventilation with air purifiers, (2) spatial partitioning with dividers, and (3) combination of 1 and 2. In all simulations infectious viruses were detected throughout the space proving the existence long-distance aerosol transmission indoors. Experimental cumulative virus numbers and LES dispersion results were qualitatively similar. The LES results were further utilized to derive the evolution of infection probability. Air purifiers augmenting the effective ventilation rate by 65% reduced the spatially averaged infection probability by 30%–32%. This relative reduction manifests with approximately 15 min lag as aerosol dispersion only gradually reaches the purifier units. Both viral findings and LES results confirm that spatial partitioning has a negligible effect on the mean infection-probability indoors, but may affect the local levels adversely. Exploitation of high-resolution LES jointly with microbiological measurements enables an informative interpretation of the experimental results and facilitates a more complete risk assessment.

Wind information in urban areas is essential for many applications related to air pollution, urban climate and planning, safety of drone‐related operations, and assessment of urban wind energy potential. These applications require accurate wind forecasts, and obtaining this information in an urban environment is challenging as the morphology of a city varies from street to street, altering the wind flow. Remote sensing techniques such as Doppler lidars (light detection and ranging) provide a unique opportunity for wind forecast verification as they can provide both the vertical profile of the horizontal wind and the spatial variation in the horizontal domain at high resolution. In this study, the performance of numerical weather prediction (NWP) models, analysis systems, and large‐eddy simulation (LES) models have been analysed by comparing the modelled winds against Doppler lidar observations under various atmospheric conditions and from season to season, in the coastal environment of Helsinki, Finland. The long‐term mean vertical profile of the modelled horizontal wind shows good agreement with observations; the NWP model and the analysis systems selected here exhibit different strengths and weaknesses depending on the atmospheric conditions but no significant diurnal variation in performance. However, both the model and analysis systems show differences in their spatially‐averaged bias when investigating different wind directions. LES verification shows that these models can potentially provide winds down to street level, given pre‐computed scenarios of atmospheric conditions. For Helsinki, the observed winds are stronger during winter than summer, and, on average, higher wind speeds were observed at the urban site than the sub‐urban site.

After a century of rapid urbanization, the majority of the world’s population is now living within urban areas. Despite this, micro and mesoscale meteorological dynamics and processes within the urban boundary layer are not thoroughly understood. Furthermore, a major fraction of these urban areas are located in coastal regions. These urban boundary layers are characterized by a high degree of surface heterogeneity and complex dynamics associated with interactions between land and marine air masses. The broad range of relevant spatial and temporal scales associated with coastal urban boundary layer phenomena makes them notoriously difficult to model.One example of such phenomenon is the sea-breeze, observed in numerous coastal urban areas around the globe. The general sea-breeze circulation has associated spatial scales ranging from O(10 km) to O(100 km). However, it is directly influenced by surface exchanges, which have spatial scales down to O(1 m) in urban areas. By using novel multi-scale modelling methods capable of explicitly resolving all relevant scales of interactions, our aim is to study the complex balance of boundary layer processes during a realistic springtime sea-breeze case in Helsinki, Finland.The PALM model system, an open source meteorological modelling system for boundary layer flows, has implemented the capability for multi-scale two-way self-nested large-eddy simulation (LES) setups. Such setups of several self-nested LES domains are especially suited for studying problems such as the interaction between the urban surface and the sea-breeze circulation. This approach differs from the more traditional modelling approaches, where interactions at either micro or mesoscale have been parametrized or given as one-way boundary conditions, effectively preventing the possibility of studying the two-way interactions and feedbacks.We study both the mechanical and thermal influence of the urban surface on the development of the mesoscale circulation. Furthermore, we investigate how the urban surface affects the development of the internal boundary layer and subsequent convection in the lower branch of the cell, where the stable marine air mass is advected over land. This is achieved by studying the spatial scales associated with the convective turbulent structures as well as exchanges of heat and momentum in various regions of the circulation.In order to verify the simulation setup and the results obtained, we compare the results with observations from Doppler lidars, a C-band dual-polarization weather radar and an in-situ measurement network being operated in the region. We anticipate that we will gain exciting new insights into the development of a sea-breeze circulation, convective internal boundary layers and turbulent structures in coastal urban boundary layers. Furthermore, we expect to quantify the effect of the urban surface on convective boundary layer development in the region.

High-resolution large-eddy simulation (LES) is exploited to study indoor air turbulence and its effect on the dispersion of respiratory virus-laden aerosols and subsequent transmission risks. The LES modeling is carried out with unprecedented accuracy and subsequent analysis with novel mathematical robustness. To substantiate the physical relevance of the LES model under realistic ventilation conditions, a set of experimental aerosol concentration measurements are carried out, and their results are used to successfully validate the LES model results. The obtained LES dispersion results are subjected to pathogen exposure and infection probability analysis in accordance with the Wells-Riley model, which is here mathematically extended to rely on LES-based space- and time-dependent concentration fields. The methodology is applied to assess two dissimilar approaches to reduce transmission risks: a strategy to augment the indoor ventilation capacity with portable air purifiers and a strategy to utilize partitioning by exploiting portable space dividers. The LES results show that use of air purifiers leads to greater reduction in absolute risks compared to the analytical Wells-Riley model, which fails to predict the original risk level. However, the two models do agree on the relative risk reduction. The spatial partitioning strategy is demonstrated to have an undesirable effect when employed without other measures, but may yield desirable outcomes with targeted air purifier units. The study highlights the importance of employing accurate indoor turbulence modeling when evaluating different risk-reduction strategies.

This work aims at investigating the effects of forest heterogeneity on a wind-turbine wake under a neutrally stratified condition. Three types of forests, homogeneous (idealized), a real forest having natural heterogeneity, and an idealized forest having a strong heterogeneity, are considered in this study. For each type, three forest densities with Leaf Area Index (LAI) values of 0.42,1.7, and 4.25 are investigated. The data of the homogeneous forest are estimated from a dense forest site located in Ryningsnäs, Sweden, while the real forest data are obtained using an aerial LiDAR scan over a site located in Pihtipudas, about 140 km north of Jyväskylä, Finland. The idealized forest is made up of small forest patches to represent a strong heterogeneous forest. The turbine definition used to model the wake is the NREL 5 MW reference wind turbine, which is modeled in the numerical simulations by the Actuator Line Model (ALM) approach. The numerical simulations are implemented with OpenFOAM based on the Unsteady Reynolds Averaged Navier–Stokes (U-RANS) approach. The results highlight the effects of forest heterogeneity levels with different densities on the wake formation and recovery of a stand-alone wind-turbine wake. It is observed that the homogeneous forests have higher turbulent kinetic energy (TKE) compared to the real forests for an LAI value less than approximately 2, while forests with an LAI value above 2 show a higher TKE in the real forest than in the homogeneous and the strong heterogeneous (patched) forest. Technically, the deficits in the wake region are more pronounced in the strong heterogeneous forests than in other forest cases.

The flow-off process of de-/anti-icing fluid on a flat plate subjected to an accelerating airflow was studied both experimentally and using computational fluid dynamics (CFD) simulations. The effect of fluid viscosity on the fluid flow-off was examined experimentally in a wind tunnel. Two models with different chords (0.6 and 1.8 m) were experimented with. Type I fluid with different viscosities and Type IV fluids were tested. The CFD simulations considered only 0.6 m plate model. The effect of viscosity alteration causes an ensemble of consequences, which together caused a delay and decrease in the initial flow-off rate. These are the alterations in the wind tunnel speed for wave onset, in the wave speeds and in the flow-off process at the trailing edge. The CFD simulations supported most of the reasoning for fluid viscosity effects on fluid flow-off. However, the effect of viscosity was considerably exaggerated in simulations. Based on a simplified relation between air velocity and fluid flow-off rate, a scaling model for wind tunnel tests was created. A dimensionless parameter was found to scale the model dimensions and to consider the wind tunnel speed sequence.

Large-eddy simulation (LES) provides a physically sound approach to study complex turbulent processes within the atmospheric boundary layer including urban boundary layer flows. However, such flow problems often involve a large separation of turbulent scales, requiring a large computational domain and very high grid resolution near the surface features, leading to prohibitive computational costs. To overcome this problem, an online LES–LES nesting scheme is implemented into the PALM model system 6.0. The hereby documented and evaluated nesting method is capable of supporting multiple child domains, which can be nested within their parent domain either in a parallel or recursively cascading configuration. The nesting system is evaluated by first simulating a purely convective boundary layer flow system and then three different neutrally stratified flow scenarios with increasing order of topographic complexity. The results of the nested runs are compared with corresponding non-nested high- and low-resolution results. The results reveal that the solution accuracy within the high-resolution nest domain is clearly improved as the solutions approach the non-nested high-resolution reference results. In obstacle-resolving LES, the two-way coupling becomes problematic as anterpolation introduces a regional discrepancy within the obstacle canopy of the parent domain. This is remedied by introducing canopy-restricted anterpolation where the operation is only performed above the obstacle canopy. The test simulations make evident that this approach is the most suitable coupling strategy for obstacle-resolving LES. The performed simulations testify that nesting can reduce the CPU time up to 80 % compared to the fine-resolution reference runs, while the computational overhead from the nesting operations remained below 16 % for the two-way coupling approach and significantly less for the one-way alternative.