Description and preliminary validation of the PMSS fast response parallel atmospheric flow and dispersion solver in complex built-up areas

Noxious atmospheric releases may originate from both accidents and malicious activities. They are a major concern for public authorities or first responders who may wish to have the most accurate situational awareness. Nonetheless, it is difficult to reliably and accurately model the flow, transport, and dispersion processes in large complex built-up environments in a limited amount of time and resources compatible with operational needs. The parallel version of Micro-SWIFT-SPRAY (PMSS) is an attempt to propose a physically sound and fast response modelling system applicable to complicated industrial or urban sites in case of a hazardous release. This paper presents and justifies the choice of the diagnostic flow and Lagrangian dispersion models in PMSS. Then, it documents in detail the development of the parallel algorithms used to reduce the computational time of the models. Finally, the paper emphasizes the preliminary model validation and parallel performances of PMSS based on data from both wind tunnel (Evaluation of Model Uncertainty) and in-field reduced-scale (Mock Urban Setting Test) and real-scale (Oklahoma City) experimental campaigns.     

Evaluation of the QUIC-URB fast response urban wind model for a cubical building array and wide building street canyon

This paper describes the QUIC-URB fast response urban wind modeling tool and evaluates it against wind tunnel data for a 7 × 11 cubical building array and wide building street canyon. QUIC-URB is based on the Röckle diagnostic wind modeling strategy that rapidly produces spatially resolved wind fields in urban areas and can be used to drive urban dispersion models. Röckle-type models do not solve transport equations for momentum or energy; rather, they rely heavily on empirical parameterizations and mass conservation. In the model-experiment comparisons, we test two empirical building flow parameterizations within the QUIC-URB model: our implementation of the standard Röckle (SR) algorithms and a set of modified Röckle (MR) algorithms. The MR model attempts to build on the strengths of the SR model and introduces additional physically based, but simple parameterizations that significantly improve the results in most regions of the flow for both test cases. The MR model produces vortices in front of buildings, on rooftops and within street canyons that have velocities that compare much more favorably to the experimental results. We expect that these improvements in the wind field will result in improved dispersion calculations in built environments.     

Urban Fluid Mechanics: Air Circulation and Contaminant Dispersion in Cities

Recently, many urban areas of the world have experienced rapid growth of population and industrial activity raising concerns of environmental deterioration. To meet challenges associated with such rapid urbanization, it has become necessary to implement wise strategies for environmental management and planning, addressing the exclusive demands of urban zones for maintaining environmental sustainability and functioning with minimum disruption. These strategies and related public policy must be based on state-of-the-science tools for environmental forecasting, in particular, on mathematical models that accurately incorporate physical, biological, chemical and geological processes at work on urban scales. Central to such models are the mechanics of environmental fluids (air and water) and their transport and transformation characteristics. Although much progress has been made on understanding environmental flow phenomena, a myriad of issues akin to urban flow, the transport phenomena, air and water quality and health issues (epidemiology) remain to be understood and quantified. We propose to initiate a new focus area – Urban Fluid Mechanics (UFM) – tailored to research on such issues. For optimal societal impact, UFM must delve into fundamental and applied fluid flow problems of immediate utility for the development of urban public policy and environmental regulations. Such efforts often entail the use of `whole' systems approach to environmental studies, requiring careful synthesis between crosscutting areas.In this paper, a few topics in the realm of UFM are presented, the theme being the flow and air quality in urban areas. Topics such as the scales of flow, the atmospheric boundary layer, pollutants and their transport and modeling of flow and air quality are briefly reviewed, discussed and exemplified using case studies. Identification of important flow-related issues, rigorous multidisciplinary approaches to address them and articulation of results in the context of socio-political cause calebre will be the challenges faced by UFM.     

Using a sub-grid scale modeling approach to simulate the transport and fate of toxic air pollutants

Several air toxics are emitted from mobile sources on roadways and these emissions account for a significant fraction of the health risks to the population. In addition, health effect studies are now becoming more comprehensive and some account for the spatial heterogeneities of air pollutant concentration fields (as is the case near roadways). Standard models can simulate either the near-source concentration fields or the urban background, but no model can handle both spatial scales in the vicinity of roadways in a coherent and scientifically correct manner. Here, we present a model that provides such an integrated treatment by combining a grid-based air quality model of the urban background with a plume-in-grid representation of roadway emissions. The model is applied to simulate near-roadway concentrations due to emissions from a busy interstate highway in New York City. Qualitative comparisons with typical measured concentration profiles show that the model captures the observed features of toxic air pollutant concentrations near roadways.     

LES validation of urban flow,part II: eddy statistics and flow structures

Time-dependent three-dimensional numerical simulations such as large-eddy simulation (LES) play an important role in fundamental research and practical applications in meteorology and wind engineering. Whether these simulations provide a sufficiently accurate picture of the time-dependent structure of the flow, however, is often not determined in enough detail. We propose an application-specific validation procedure for LES that focuses on the time dependent nature of mechanically induced shear-layer turbulence to derive information about strengths and limitations of the model. The validation procedure is tested for LES of turbulent flow in a complex city, for which reference data from wind-tunnel experiments are available. An initial comparison of mean flow statistics and frequency distributions was presented in part I. Part II focuses on comparing eddy statistics and flow structures. Analyses of integral time scales and auto-spectral energy densities show that the tested LES reproduces the temporal characteristics of energy-dominant and flux-carrying eddies accurately. Quadrant analysis of the vertical turbulent momentum flux reveals strong similarities between instantaneous ejection-sweep patterns in the LES and the laboratory flow, also showing comparable occurrence statistics of rare but strong flux events. A further comparison of wavelet-coefficient frequency distributions and associated high-order statistics reveals a strong agreement of location-dependent intermittency patterns induced by resolved eddies in the energy-production range. The validation concept enables wide-ranging conclusions to be drawn about the skill of turbulence-resolving simulations than the traditional approach of comparing only mean flow and turbulence statistics. Based on the accuracy levels determined, it can be stated that the tested LES is sufficiently accurate for its purpose of generating realistic urban wind fields that can be used to drive simpler dispersion models.     

Large-eddy simulation of turbulent flow and dispersion over a complex urban street canyon

Turbulent flow and dispersion characteristics over a complex urban street canyon are investigated by large-eddy simulation using a modified version of the Fire Dynamics Simulator. Two kinds of subgrid scale (SGS) models, the constant coefficient Smagorinsky model and the Vreman model, are assessed. Turbulent statistics, particularly turbulent stresses and wake patterns, are compared between the two SGS models for three different wind directions. We found that while the role of the SGS model is small on average, the local or instantaneous contribution to total stress near the surface or edge of the buildings is not negligible. By yielding a smaller eddy viscosity near solid surfaces, the Vreman model appears to be more appropriate for the simulation of a flow in a complex urban street canyon. Depending on wind direction, wind fields, turbulence statistics, and dispersion patterns show very different characteristics. Particularly, tall buildings near the street canyon predominantly generate turbulence, leading to homogenization of the mean flow inside the street canyon. Furthermore, the release position of pollutants sensitively determines subsequent dispersion characteristics.     

Daytime air pollution transport mechanisms in stable atmospheres of narrow versus wide urban valleys

Transport of air pollutants emitted from urban valleys can be strongly restricted by interactions between static and dynamic factors including topographic forcing, low-level atmospheric stability related to temperature inversions, and urban heat island-induced circulations. Interplay between these processes has a complex and dynamic nature, and is determinant for the evolution of different ventilation mechanisms and the associated impacts on air quality. Here we investigate these transport mechanisms through large eddy simulations using EULAG, an established model for multiscale flows, to simulate an idealized atmospheric environment in narrow versus wide urban valleys during critical conditions for air quality (high atmospheric stability). Our results show how the ventilation of valleys depends on a dynamic (variable during the daytime) balance between interacting and sometimes competing processes related to thermally-driven slope flows, urban heat island-induced flows, and the trapping effect of atmospheric stability; and how valley width affects this balance. Particularly important is that the time-space distribution of pollutants (a passive tracer) varies greatly between both valleys despite having the same urban area and emission rates. These variations lead to pollutants being mostly concentrated in different areas of the narrow and wide valleys. We discuss the mechanisms behind these results and their potential implications for real urban valleys. Further understanding of these mechanisms is crucial for explaining the occurrence of severe air pollution episodes and informing related decision-making processes in urban valleys.

     

Characteristics of clustered particles in skimming flows on a stepped spillway

Air–water flows at hydraulic structures are commonly observed and called white waters. The free-surface aeration is characterised by some intense exchanges of air and water leading to complex air–water structures including some clustering. The number and properties of clusters may provide some measure of the level of particle-turbulence and particle–particle interactions in the high-velocity air–water flows. Herein a re-analysis of air–water clusters was applied to a highly aerated free-surface flow data set (Chanson and Carosi, Exp Fluids 42:385–401, 2007). A two-dimensional cluster analysis was introduced combining a longitudinal clustering criterion based on near-wake effect and a side-by-side particle detection method. The results highlighted a significant number of clustered particles in the high-velocity free-surface flows. The number of bubble/droplet clusters per second and the percentage of clustered particles were significantly larger using the two-dimensional cluster analysis than those derived from earlier longitudinal detection techniques only. A number of large cluster structures were further detected. The results illustrated the complex interactions between entrained air and turbulent structures in skimming flow on a stepped spillway, and the cluster detection method may apply to other highly aerated free-surface flows.     

On thermally forced flows in urban street canyons

During sunny days with periods of low synoptic wind, buoyancy forces can play a critical role on the air flow, and thus on the dispersion of pollutants in the built urban environments. Earlier studies provide evidence that when a surface inside an urban street canyon is at a higher temperature than that of local ambient air, buoyancy forces can modify the mechanically-induced circulation within the canyons (i.e., gaps between buildings). The aspect ratio of the urban canyon is a critical factor in the manifestation of the buoyancy parameter. In this paper, computational fluid dynamics simulations are performed on urban street canyons with six different aspect ratios, focusing on the special case where the leeward wall is at a greater temperature than local ambient air. A non-dimensional measure of the influence of buoyancy is used to predict demarcations between the flow regimes. Simulations are performed under a range of buoyancy conditions, including beyond those of previous studies. Observations from a field experiment and a wind tunnel experiment are used to validate the results.     

A Computational Fluid Dynamics Approach for Urban Area Transport and Dispersion Modeling

A simulation tool has been developed to model the wind fields, turbulence fields, and the dispersion of Chemical, Biological, Radiological and Nuclear (CBRN) substances in urban areas on the building to city blocks scale. A Computational Fluid Dynamics (CFD) approach has been taken that naturally accounts for critical flow and dispersion processes in urban areas, such as channeling, lofting, vertical mixing and turbulence, by solving the steady-state, Reynolds-Averaged Navier–Stokes (RANS) equations. Rapid generation of high quality cityscape volume meshes is attained by a unique voxel-based model generator that directly interfaces with common Geographic Information Systems (GIS) file formats. The flow and turbulence fields are obtained by solving the steady-state RANS equations using a collocated, pressure-based approach formulated for unstructured and polyhedral mesh elements. Turbulence modeling is based upon the Renormalization Group variant of the k–ε model (k–ε RNG). Neutrally buoyant simulations are made by prescribing velocity boundary condition profiles found by a power–law relationship, while turbulence quantities boundary conditions are defined by a prescribed mixing length in conjunction with the assumption of turbulence equilibrium. Dispersion fields are computed by solving an unsteady transport equation of a dilute gas, formulated in a Eulerian framework, using the velocity and turbulence fields found from the steady-state RANS solution. In this paper the model is explained and detailed comparisons of predicted to experimentally obtained velocity, turbulence and dispersion fields are made to neutrally stable wind tunnel and hydraulic flume experiments.     

Comparison of atmospheric modelling systems simulating the flow,turbulence and dispersion at the microscale within obstacles

Three different modelling techniques to simulate the pollutant dispersion in the atmosphere at the microscale and in presence of obstacles are evaluated and compared. The Eulerian and Lagrangian approaches are discussed, using RAMS6.0 and MicroSpray models respectively. Both prognostic and diagnostic modelling systems are considered for the meteorology as input to the Lagrangian model, their differences and performances are investigated. An experiment from the Mock Urban Setting Test field campaign observed dataset, measured within an idealized urban roughness, is used as reference for the comparison. A case in neutral conditions was chosen among the available ones. The predicted mean flow, turbulence and concentration fields are analysed on the basis of the observed data. The performances of the different modelling approaches are compared and their specific characteristics are addressed. Given the same flow and turbulence input fields, the quality of the Lagrangian particle model is found to be overall comparable to the full-Eulerian approach. The diagnostic approach for the meteorology shows a worse agreement with observations than the prognostic approach but still providing, in a much shorter simulation time, fields that are suitable and reliable for driving the dispersion model.     

Development of a rotorcraft dust-emission parameterization using a CFD model

Flights of rotorcraft over the desert floor can result in significant entrainment of particulate matter into the atmospheric boundary layer. Continuous or widespread operation can lead to local and regional impacts on visibility and air quality. To account for this pollutant source in air quality models, a parameterization scheme is needed that addresses the complex vertical distribution of dust ejected from the rotorcraft wake into the atmospheric surface layer. A method to parameterize the wind and turbulence fields and shear stress at the ground is proposed here utilizing computational fluid dynamics and a parameterized rotor model. Measurements taken from a full scale experiment of rotorcraft flight near the surface are compared to the simulation results in a qualitative manner. The simulation is shown to adequately predict the forward detachment length of the induced ground jet compared to the measured detachment lengths. However, the simulated ground vortex widths and vorticity deviate substantially from the measured values under a range of flight speeds. Results show that the method may be applicable for air quality modeling assuming slow airspeeds of the rotorcraft, with advance ratios of 0.005–0.02.     

Analytical evaluation of mesoscale fluxes and pressure field

Terrain in natural areas is never homogeneous: there may be a variety of vegetation types and patches of vegetated and unvegetated areas which can modify the mesoscale atmospheric flow. Moreover, horizontal thermal inhomogeneities in the planetary boundary layer are a well known source of mesoscale circulation systems such as land and sea breezes, mountain-valley winds, and urban heat island circulations. Since those phenomena are not resolved in regional scale numerical models, therefore an analytic procedure able to evaluate the relative importance of mesoscale and turbulent heat fluxes associated with surface thermal heterogeneities is of crucial importance in the optic of developing a parameterization of mesoscale effects generated by these heterogeneities for use in larger scale models. In the present paper we analyze how small a horizontal variation in surface heating can be and still produce a significant mesoscale circulation, how the heat and momentum fluxes associated to mesoscale flows can penetrate deeply into the mid-troposphere, and how they modify tropospheric relevant climate parameters, such as the atmospheric static stability. In addition, we evaluate the terms of the pressure gradient force, nonlinear and linear, non-hydrostatic and hydrostatic, as function of time and space scales of the mesoscale flow. The present paper is mainly a review of analytical results, the numerical comparison and verification using RAMS is in progress.     

A GIS-based approach to spatio-temporal analysis of environmental pollution in urban areas: A case study of Prague's environment extended by LIDAR data

Environmental pollution of urban areas is one of key factors that state authorities and local agencies have to consider in the decision-making process. To find a compromise among many criteria, spatial analysis extended by geostatistical methods and dynamic models has to be carried out. In this case, spatial analysis includes processing of a wide range of air, water and soil pollution data and possibly noise assessment and waste management data. Other spatial inputs consist of data from remote sensing and GPS field measurements. Integration and spatial data management are carried out within the framework of a geographic information system (GIS). From a modeling point of view, GIS is used mainly for the preprocessing and postprocessing of data to be displayed in digital map layers and visualized in 3D scenes. Moreover, for preprocessing and postprocessing, deterministic and geostatistical methods (IDW, ordinary kriging) are used for spatial interpolation; geoprocessing and raster algebra are used in multi-criteria evaluation and risk assessment methods. GIS is also used as a platform for spatio-temporal analyses or for building relationships between the GIS database and stand-alone modeling tools. A case study is presented illustrating the application of spatial analysis to the urban areas of Prague. This involved incorporating environmental data from monitoring networks and field measurements into digital map layers. Extra data inputs were used to represent the 3D concentration fields of air pollutants (ozone, NO₂) measured by differential absorption LIDAR. ArcGIS was used to provide spatial data management and analysis, extended by modeling tools developed internally in the ArcObjects environment and external modules developed with MapObjects. Ordinary kriging methods were employed to predict ozone concentrations in selected 3D locations together with estimates of variability. Higher ozone concentrations were found above crossroads with their heavy traffic than above the surrounding areas. Ozone concentrations also varied with height above the digital elevation model. Processed data, spatial analysis and models are integrated within the framework of the GIS project, providing an approach that state and local authorities can use to address environmental protection issues.     

From science to policy—a geostatistical approach to identifying potential areas for cetacean conservation: a case study of bottlenose dolphins in the Pelagos sanctuary (Mediterranean Sea)

Cetaceans are top-level predators that serve as sentinels of the health and status of lower trophic levels in the marine ecosystem. For this reason they attract significant attention in marine conservation planning and often have been used to promote designation of reserve areas in many countries (e.g., Ligurian Sea, Moray Firth, Hawaiian Islands, The Gully, Wadden Sea, Banks Peninsula, and Golfo San José). Many policies are designed to protect cetaceans. For example, the Habitat Directive requires member states to select, designate, and protect sites that support certain natural habitats or species, such as the bottlenose dolphin, as Special Areas of Conservation (SACs) that aim to create a network of protected areas across the European Union known as Natura 2000. The boundaries of protected areas for cetacean species must be defined for management purposes. In recent years, many techniques have been developed to define the distribution of cetaceans in relation to habitat preferences. Although these models can provide an understanding of the ecological processes that determine species distribution, their application requires prior knowledge of the variables that should be included in the model, the interactions among these variables, and their effects on species distribution. Thus, the lack of available data in understudied areas precludes the application of these types of models. As an alternative, we describe a geostatistical approach to identifying areas that potentially should be designated as marine protected areas for cetaceans. We illustrate the application of the kriging algorithm to the bottlenose dolphin population that resides in the northwestern Mediterranean Sea. The data derived from a 7-year survey were used. The encounter rate is the only variable required for this method, making it very easy to apply. The resulting georeferenced and high resolution map includes areas most visited by bottlenose dolphins, which are called core areas. Core areas are helpful for establishing the boundaries of marine reserves for the protection of the species. The approach described herein is accurate, precise, unbiased, replicable to all highly mobile species and easy to understand by both researchers and policy makers.     

A building-based data capture and data mining technique for air quality assessment

Recently, a building-based air quality model system which can predict air quality in front of individual buildings along both sides of a road has been developed. Using the Macau Peninsula as a case study, this paper shows the advantages of building-based model system in data capture and data mining. Compared with the traditional grid-based model systems with input/output spatial resolutions of 1–2 km, the building-based approach can extract the street configuration and traffic data building by building and therefore, can capture the complex spatial variation of traffic emission, urban geometry, and air pollution. The non-homogeneous distribution of air pollution in the Macau Peninsula was modeled in a high-spatial resolution of 319 receptors·km^-2. The spatial relationship among air quality, traffic flow, and urban geometry in the historic urban area is investigated. The study shows that the building-based approach may open an innovative methodology in data mining of urban spatial data for environmental assessment. The results are particularly useful to urban planners when they need to consider the influences of urban form on street environment.     

A concise review of ecological risk assessment for urban ecosystem application associated with rapid urbanization processes

ABSTRACT

Urban ecological risk (UER) caused by rapid urbanization means potential threat to urban ecosystem structure, pattern and services. The scales of ecological risk assessment (ERA) have been expanded from individual organisms to watersheds and regions. The types of stressor range from chemical to physical, biological and natural events. However, the application of ERA in urban ecosystems is relatively new. Here, we summarize the progress of urban ERA and propose an explicit framework to illumine future ERA based on UER identification, analysis, characterization, modeling, projection and early warning and management. The summary includes six urban ERA-relevant methods: weight-of-evidence (WoE), procedure for ecological tiered assessment of risks (PETAR), relative risk model (RRM), multimedia, multi-pathway, multi-receptor risk assessment (3MRA), landscape analysis and ecological models. Furthermore, we review critical cases of urban ERA in landscape ecology, soil, air, water and solid waste. Based on the Internet of Things (IoT) and cloud computing, an urban ERA management platform integrates various urban ERA methodologies that can be developed to provide better implementation strategies of UER for urban ecosystem managers and stakeholders. We develop a conceptual model of urban ERA based on the urban characteristics in China. The future applications of urban ERA include uncertainty analysis using Monte Carlo techniques on the basis of geospatial techniques and comprehensive urban ERA using nonlinear models or process models.     

The importance of spatial autocorrelation,extent and resolution in predicting forest bird occurrence

Concerns about declines in forest biodiversity underscore the need for accurate estimates of the distribution and abundance of organisms at large scales and at resolutions that are fine enough to be appropriate for management. This paper addresses three major objectives: (i) to determine whether the resolution of typical air photo-derived forest inventory is sufficient for the accurate prediction of site occupancy by forest birds. We compared prediction success of habitat models using air photo variables to models with variables derived from finer resolution, ground-sampled vegetation plots. (ii) To test whether incorporating spatial autocorrelation into habitat models via autologistic regression increases prediction success. (iii) To determine whether landscape structure is an important factor in predicting bird distribution in forest-dominated landscapes. Models were tested locally (Greater Fundy Ecosystem [GFE]) using cross-validation, and regionally using an independent data set from an area located ca. 250 km to the northwest (Riley Brook [RB]). We found significant positive spatial autocorrelation in the residuals of at least one habitat model for 76% (16/21) of species examined. In these cases, the logistic regression assumption of spatially independent errors was violated. Logistic models that ignored spatial autocorrelation tended to overestimate habitat effects. Though overall prediction success was higher for autologistic models than logistic models in the GFE, the difference was only significantly improved for one species. Further, the inclusion of spatial covariates did little to improve model performance in the geographically discrete study area. For 62% (13/21) of species examined, landscape variables were significant predictors of forest bird occurrence even after statistically controlling for stand-level variability. However, broad spatial extents explained less variation than local factors. In the GFE, 76% (16/21) of air photo and 81% (17/21) of ground plot models were accurate enough to be of practical utility (AUC > 0.7). When applied to RB, both model types performed effectively for 55% (11/20) of the species examined. We did not detect an overall difference in prediction success between air photo and ground plot models in either study area. We conclude that air photo data are as effective as fine resolution vegetation data for predicting site occupancy for the majority of species in this study. These models will be of use to forest managers who are interested in mapping species distributions under various timber harvest scenarios, and to protected areas planners attempting to optimize reserve function.     

Air pollutant levels are 12 times higher than guidelines in Varanasi,India. Sources and transfer

Air quality in an urban atmosphere is regulated by both local and distant emission sources. For air quality management in urban areas, identification of sources and their relationships with local meteorology and air pollutants are essential. The critical condition of air quality in Indo-Gangetic plain is well known, but lack of data on both local and distant emission sources limits the scope of improving air quality in this region. Concentrations of particulate matter of size lower than 10 μm (PM₁₀) were assessed in the highly urbanized Varanasi city situated in middle Indo-Gangetic plain of India from 2014 to 2017, to identify the distant air pollution sources based on trajectory statistical models and local sources by conditional bivariate probability function. Modifying effects of meteorology and air pollutants on PM₁₀ were also explored. Mean PM₁₀ concentration for the study period was 244.8 ± 135.8 μg m^?3, which was 12 times higher than the WHO annual guideline. Several distinct sources of traffic as the major source of PM₁₀ were identified in the city. Trajectory statistical models like cluster analysis, potential source contribution function and concentration-weighted trajectory showed significant contributions from north-west and eastern directions in the transport of polluted air masses to the city. Dew point, wind speed, temperature and ventilation coefficient are the major factors in PM₁₀ formation and dispersion.