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Current operational methods for predicting tree mortality from fire injury are regression-based models that only indirectly consider underlying causes and, thus, have limited generality. A better understanding of the physiological consequences of tree heating and injury are needed to develop biophysical process models that can make predictions under changing or novel conditions. As an illustration of the benefits that may arise from including physiological processes in models of fire-caused tree mortality, we develop a testable, biophysical hypothesis for explaining pervasive patterns in conifer injury and functional impairment in response to fires. We use a plume model to estimate vapor pressure deficits (D) in tree canopies during surface fires and show that D are sufficiently high to cause embolism in canopy branches. The potential implications of plume conditions and tree response are discussed.

A photochemical/dynamic ship-plume model, which can consider the ship-plume dynamics and ship-plume chemistry, simultaneously, was developed to gain a better understanding of atmospheric impact of ship emissions. The model performance was then evaluated by a comparison with the observation data measured on a NOAA WP-3D flight during the Intercontinental Transport and Chemical Transformation 2002 (ITCT 2K2) airborne field campaign. The simulation conditions and parameters, such as meteorological conditions, emission rates, and background gas and particulate species concentrations, were obtained directly and/or inferred indirectly from the ITCT 2K2 observation data. The model-predicted concentrations showed good agreement with the observed concentrations of five ambient species (NOx, NOy, ozone, HNO3, and H2SO4) at the eight plume transects by the WP-3D flight with strong correlations around the 1:1 line (0.64≤R≤0.85). In addition, a set of tests were carried out to approximate the magnitude of the reaction probability of HNO3 onto sea-salt particles in the model-observation comparison framework. These results suggest that the reaction probability of HNO3 onto sea-salt particles may be in the order of 0.05–0.1. The equivalent NOx lifetime throughout the "entire plume" was also estimated from photochemical/dynamic ship-plume modeling. The NOx lifetimes estimated throughout the entire ship plume ranged from 2.64 h to 3.76 h under stable to neutral stability conditions. The short NOx lifetime over the entire ship plume clearly shows that the ship-plume chemistry shortens the NOx lifetime considerably. Therefore, the ship-plume chemistry model should be used to model the changes in ship-plume chemical compositions and better evaluate the atmospheric impact of ocean-going ship emissions.

In fire safety engineering, rapid fire detection and suppression in large spaces are very important issue. Development of new techniques is always based on the good understanding of the basic principle of smoke movement, especially the temperature of spill plume. Aiming to this objective, this paper specifies the multi-sectional characteristics on spill plume free developing out of a wide-door cabin in a large space atrium by means of full-scale experiment, theoretical analysis and CFD modeling. First the physical development process of the spill plume is analyzed from the horizontal curved regime at the door, the near-field two-dimensional linear plume regime, through to the far-field axisymmetric plume regime. It demonstrates the coupling correlation existing between the linear virtual origin, critical transition height from linear to axisymmetric regime, the axisymmetric virtual origin and other parameters, such as the spill plume depth at the door, the mass and heat flow rate outside the cabin door, the cabin door width and height etc. The basic mathematic equations regarding each regime's centerline temperature have been obtained. The virtual origin position of linear plume regime and axisymmetric plume regime are given, the critical transition height of spill plume from the two-dimensional linear plume to axisymmetric plume regime is also proposed, and finally the double-part prediction model (MEDP) for the spill plume centerline temperature is put forward. By validation with the full-scale experiment and the large eddy CFD modeling, it shows that the proposed spill plume model is capable to well describe the centerline temperature varying characteristics of the spill plume free developing out of the cabin.

This paper reports an investigation on the scenarios of the spill plume and the resultant natural filling in a full-scale atrium mock-up due to a retail shop fire. The study includes two aspects, i.e., the full-scale experiment and the numerical simulation. A spill plume model is proposed to predict the characteristic properties of the plume development in the atrium under a retail shop fire. Furthermore, to accurately predict the shop fire in the atrium, an improved zone model is developed combining the transport lag time model and the spill plume model. Besides validating the developed model by experiments, the case is also simulated by the established zone model, i.e., CFAST code, and the computational fluid dynamics model, i.e., FDS code. By both physical and numerical experiments, the process of natural smoke filling and the temperature rise in the atrium are investigated and well understood. It is found that a typical spill plume contains three regimes, i.e., the curved section out of the retail shop door, the line plume in the near field, and the axisymmetric plume in the far field. Predictions from the proposed empirical model for the spill plume and the resultant improved zone model compare favorably with the experiments. The study indicates that the atrium becomes very dangerous due to such shop fire if no smoke control employed. The ability of mechanical exhaust system in the atrium to mitigate the hazard of a retail shop fire is investigated as well.

Management of potato late blight could benefit from prediction of the risk posed to potato fields from external inoculum sources of Phytophthora infestans. Influx of inoculum depends on a complex interplay of population biological, atmospheric and spore survival processes, and is difficult to predict. This research aims at building tools for such prediction. BLIGHTSPACE is a spatio-temporal model (parameterized for potato late blight) that has been developed and utilized to study the progress of epidemics in individual fields and networks of fields. A quasi-Gaussian plume model was developed to provide long-range transport of spores within BLIGHTSPACE. Numerical results compared favorably with experimental data. A further submodel for the survival of spores during long-range transportation has been added. Integration of these three submodels will create an experimental arena for comparing control options for potato late blight.

Indoor aerodynamics induced by a fire in an atrium was simulated with the fire field model CC-EXACT. The package was developed from the computational fluid dynamics (CFD) model EXACT designed for studying indoor air flow induced by heating, ventilation and air-conditioning system. The results are compared with those predicted by the two-layer fire zone model FIRST. Both EXACT and FIRST are available from the Building and Fire Research Laboratory, National Institute of Standards and Technology (NIST), USA. Three different types of atria commonly found in Hong Kong of the same space volume of 2000 m3 were studied. The results of the interface height and average temperature of the hot-air layer predicted by the field model CC-EXACT were compared with those predicted by the zone model FIRST. Recommendations on selecting a suitable plume model for zone modeling are made.

The discussion by Turner and Thomson raises a number of interesting points which we feel required greater clarity, and presents certain statements which in truth are not hard and fast facts. A number of the criticisms levelled at the basin development paper of Bordy et al. (2004a) are based on Turner’s belief in a transient hypothetical plume model for the development of the main Karoo Basin during the Triassic to Early Jurassic (Turner, 1999). While space precludes a full discussion on the flaws of this model as addressed by Hancox et al. (2002), and which will be documented elsewhere, a number of the arguments that follow are equally as applicable to Turner (1999) as they are to the discussion put forward by Turner and Thomson. Turner and Thomson (1998) and Turner (1999) questioned the applicability of the reciprocal flexural model of Catuneanu et al. (1998) to the Triassic-Jurassic succession of the Karoo Basin, and highlighted the lack of reliable radiometric dates for the “upper Karoo”, as well as the lack of stratigraphic data for the upper Molteno and lower Elliot formations. It was in fact these papers and presentations that led to the initiation of the current spate of research into the Molteno and Elliot formations (Hancox, 1998a; b; 2000; Lucas and Hancox, 2001; Bordy et al. , 2004a to d 349–362), all of which have markedly increased our knowledge and understanding of this part of the Karoo Basin fill. One of Turner and Thomson’s major concerns with the flexural model is the use of the Halbich et al. (1983) dates for orogenic events in the Cape Fold Belt (CFB). Although Turner and Thomson do not provide references for their concerns with the 40Ar/39Ar system, we recognise that problems do exist with …

Following the collapse of the New York World Trade Center (WTC) towers on September 11, 2001, Local, State, and Federal agencies initiated numerous air monitoring activities to better understand the ongoing impacts of emissions from the disaster. The collapse of the World Trade Center towers and associated fires that lasted for several weeks resulted at times in a noticeable plume of material that was dispersed around the Metropolitan New York City (NYC) area. In general, the plume was only noticeable for a short period of time following September 11, and only apparent close to the World Trade Center site. A study of the estimated pathway which the plume of WTC material would likely follow was completed to support the United States Environmental Protection Agency’s 2002 initial exposure assessments. In this study, the WTC emissions were simulated using the CALMET-CALPUFF model in order to examine the general spatial and temporal dispersion patterns over NYC. This paper presents the results of the CALPUFF plume model in terms of plume dilution and location, since the exact source strength remains unknown. Independent observations of PM2.5 are used to support the general dispersion features calculated by the model. Results indicate that the simulated plume matched well with an abnormal increase (600–1000% of normal) in PM2.5 two nights after the WTC collapse as the plume rotated north to southeast, towards parts of NYC. Very little if any evidence of the plume signature was noted during a similar flow scenario a week after September 11. This leads to the conclusion that other than areas within a few kilometers from the WTC site, the PM2.5 plume was not observable over NYC’s background concentration after the first few days.

The performance of the American Meteorological Society (AMS) and U.S. Environmental Protection Agency (EPA) Regulatory Model (AERMOD) Improvement Committee’s applied air dispersion model against 17 field study databases is described. AERMOD is a steady-state plume model with significant improvements over commonly applied regulatory models. The databases are characterized, and the performance measures are described. Emphasis is placed on statistics that demonstrate the model’s abilities to reproduce the upper end of the concentration distribution. This is most important for applied regulatory modeling. The field measurements are characterized by flat and complex terrain, urban and rural conditions, and elevated and surface releases with and without building wake effects. As is indicated by comparisons of modeled and observed concentration distributions, with few exceptions AERMOD’s performance is superior to that of the other applied models tested. This is the second of two articles, with the first describing the model formulations.

The examination of aviation engine’s gas plume model according to the american model Aermod was done. The plume rise’s height was determined using Aermod program algorithm. The comparison analysis of obtained results with complex model of National Aviation University was done for different regimes of aviation engine and different values of wind speed.

All convection parameterizations in models of the atmosphere include a decision tree to decide on at least the occurrence, and often the type, of convection in a model grid volume. This decision tree is sometimes referred to as the ‘‘trigger function.’’ This study investigates the role that the decision-making processes play in the simulation of convection in the European Centre for Medium-Range Weather Forecasts global forecast model. For this purpose, a new simple parcel-ascent model based on an entraining plume model is developed to replace the currently used undilute ascent in the initial decision making. The consequences of the use of the more realistic model for the behavior of convection itself and its impact on the model climate are investigated. It is shown that there are profound changes to both the convection characteristics, and consequently, the model climate. The wider implications of the findings here for the general design of a mass-flux convection parameterization are discussed.

In this paper we address the problem of estimating the source location of an airborne biological agent in a turbulent wind field using an unmanned aircraft system (UAS) and Bayesian occupancy grid mapping. The UAS is assumed to fly at constant altitude and is capable of measuring the contaminant concentration using a biological sensor. In simulations, a turbulent wind simulator is used to propagate a plume of contaminant being released from an unknown source location. Recursive Bayesian estimation is applied to estimate the source location. An occupancy grid map gives the probability that a given grid cell contains the source. The grid is updated in response to detection events in order to guide the UAS toward the source.

Ab stract—At present, the broadcast of PM2.5 can’t be accurate to all the spot of the city. This paper discusses a new method to draw the distribution of PM2.5 of a city by using mass data provided by the monitoring stations, which can be accurate to all the spot. In order to solve the problem efficiently, we present modified Gauss plume model. In the proposed model, firstly, for the accuracy of the model, we put forward a new method to calculate the wind direction. In addition, through the geometric inversion of the wind direction, the pollution source can be found. Moreover, in order to simulate the real situation, we replace the normal distribution by chi square distribution in Gauss plume model. Finally, the whole distribution of PM2.5 of the city can be draw. The PM2.5 distribution of Beijing in 2014 March indicates the proposed model is effective and feasible.

Estimation of radioactive material transport accident risk requires modelling of the spread of airborne contamination in a plume moving downwind from a hypothetical accident site. The plume is usually specified by selecting a windspeed and atmospheric stability condition (Pasquill category) as input to a plume dispersion calculation for a specific, hypothetical accident. Because transport accident sites and associated atmospheric conditions are unknown until a real accident occurs, a plume model based on ‘average US weather’ has been made available in the RADTRAN code. Since this model does not maximise accident-risk values, critics have complained that this model is not adequately conservative. This paper presents an investigation of the accident risks, calculated with wind speeds and Pasquill categories determined for specific locations and times, along two hypothetical transport routes. Shipments at four seasons of the year and six departure times were evaluated and the risks at hypothetical ac...

Mathematical models of natural processes can be used as inversion tools to predict unobserved properties from measured quantities. Uncertainty in observations and model formulation impact on the efficacy of inverse modelling. We present a general methodology, history matching, that can be used to investigate the effect of observational and model uncertainty on inverse modelling studies. We demonstrate history matching on an integral model of volcanic plumes that is used to estimate source conditions from observations of the rise height of plumes during the eruptions of Eyjafjallajökull, Iceland, in 2010 and Grímsvötn, Iceland, in 2011. Sources of uncertainty are identified and quantified, and propagated through the integral plume model. A preliminary sensitivity analysis is performed to identify the uncertain model parameters that strongly influence model predictions. Model predictions are assessed against observations through an implausibility measure that rules out model inputs that are considered implausible given the quantified uncertainty. We demonstrate that the source mass flux at the volcano can be estimated from plume height observations, but the magmatic temperature, exit velocity and exsolved gas mass fraction cannot be accurately determined. Uncertainty in plume height observations and entrainment coefficients results in a large range of plausible values of the source mass flux. Our analysis shows that better constraints on entrainment coefficients for volcanic plumes and more precise observations of plume height are required to obtain tightly constrained estimates of the source mass flux.

Requirements for NH x models are discussed. It is very important that such models can describe the dry deposition of NH 3 close to sources well. A description is given of all processes that should be included as well as references to relevant literature. For the calculation of long-term average depositions, some of these processes must be parameterized in order to keep the cpu time within reasonable bounds. Which processes should be parameterized depends on the purpose of the model calculations. A Langrangian plume model using a Gaussian plume description or a K-model with many layers can be used to model NH x deposition to nature areas embedded in agricultural areas in northern Europe (spatial resolution 2 ). On the other hand long-range transport of NH x can be modelled with Lagrangian or Eulerian models with correction factors to calculate dry deposition of NH 3 close to the source correctly (spatial resolution of 1-layer models >50×50 km 2 ). TREND, a statistical atmospheric transport model was applied to calculate the concentrations and depositions of NH 3 and its reaction product NH 4 + aerosol to Denmark and surrounding sea areas on a 5×5 km 2 grid. The model is able to reproduce measured NH 3 and NH 4 + aerosol concentrations reasonably well, as well as NH x wet deposition. It was found that dry deposition constitutes about 66% to the NH x total deposition to the land area of Denmark. Wet deposition, however, is relatively more important at sea and constitutes 64–67% of the NH x total deposition to the Kattegat and Southern Belt sea areas.

A prognostic air pollution model (TAPM) has been used to predict meteorology and sulphur dioxide concentration in the Kwinana industrial region of Western Australia for 1997, with a view to verifying TAPM for use in environmental impact assessments and associated air pollution studies. The regulatory plume model, DISPMOD, developed for the Kwinana region has also been run using both an observationally based meteorological file (denoted DISPMOD-O) and using a TAPM-based meteorological file (denoted DISPMOD-T). TAPM predictions of the meteorology for 1997 compare well with the observed values at each of the five monitoring sites. Root mean square error and index of agreement values for temperature and winds indicate that TAPM performs well at predicting the meteorology, compared to the performance of similar models from other studies. The yearly average, 99.9 percentile, maximum and mean of the top 10 ground-level sulphur dioxide concentrations for 1997 were predicted well by all of the model runs, although DISPMOD-O and DISPMOD-T tended to overpredict extreme statistics at sites furthest from the sources. Overall, TAPM performed better than DISPMOD-O, which in turn performed better than DISPMOD-T, for all statistics considered, but we consider that all three sets of results are sufficiently accurate for regulatory applications. The mean of the top ten concentrations is generally considered to be a robust performance statistic for air pollution applications, and we show that compared to the site-averaged observed value of 95 μg m−3, TAPM predicted 94 μg m−3, DISPMOD-O predicted 111 μg m−3 and DISPMOD-T predicted 125 μg m−3. The results indicate that the prognostic meteorological and air pollution approach to regulatory modelling used by TAPM, gives comparable or better results than the current regulatory approach used in the Kwinana region (DISPMOD), and also indicates that the approach of using a currently accepted regulatory model with a prognostically determined meteorology file will be an acceptable approach for regions without meteorological observations. There is nothing in TAPM that was developed specifically for the Kwinana region, and so we feel that TAPM could be applied equally well to other regions, with similar performance. The disadvantage of TAPM is the approximately 1000 times longer CPU time required to run the model compared to models such as DISPMOD, and so we anticipate that the two approaches will complement each other for regulatory applications for the near future.

Gifford's (1959. Advances in Geophysics 6, 117–138) meandering plume model is extended to account for internal plume structure. The applicability of the model is thereby extended to include the near field of large sources and the far field. Agreement with measured root-mean-square fluctuating concentrations of scalars dispersing from elevated compact-area and line sources into surface layers with neutral stability is shown to be as good or better than that obtained with Gifford's model.

The Laxmi Ridge is the most intriguing structural feature of the northeastern Arabian sea. It is char- acterized by unusual crustal structure and anomalous gravity signature. Though the earlier geophysical examinations provide some vital information about its crustal configuration, its origin and evolution have remained unsolved. Using the available seismic information, the present 2-D together with 3-D gravity modelings of the Laxmi Ridge crust:mantle system brought out a transitional layer between the depth of 11-22 km. This anomalous layer is not confined beneath the ridge axis but found to be present in the entire eastern basin and interpreted as a massive mafic intrusion beneath the region. Thickness of this layer at the base of the crust beneath the Laxmi Ridge decreases gradually towards the north-west. However, its extension towards the southeast and ultimate connection with the Chagos-Laccadive Ridge makes the western bound- ary of the magmatic crustal accretion along the west coast of India. It is suggested that the Deccan plume head mushrooming beneath the region has modified the crust with a huge magmatic intrusion. The then spreading centre coupled with the Deccan volcanic eruption is held responsible for the present day con- figuration of the Laxmi Ridge.

As a background for other papers presented in this issue on the 1995 Southern Oxidants Study (SOS) Nashville/Middle Tennessee Field Intensive, the role of meteorology in the field study is reviewed. Descriptions of the meteorological observing systems are given, and the strategy behind the observational network is defined. The tools used in making forecasts and their use for operational decisions are described. In particular, the use in real time of a dynamic boundary layer model coupled with a Lagrangian plume model to forecast power plant and urban plumes is examined. The weather occurring during the field intensive is summarized and put into a climatological perspective. Specific attention is given to the episodes of July 1–3 and July 10–14, 1995, when some of the highest ozone values were recorded. The role of nocturnal, low-level jets observed by the boundary layer wind profiler network in dispersing urban emissions into the regional background is explored.

A population ofHimantoglossum hircinum(L.) Spreng. (lizard orchid) has been monitored since the 1940s at a site in the south-east of Great Britain. A map of the site showing the number and position of flowering plants has been produced in most summers between 1978 and 1994. The maps have been digitized on a 25×25 m scale. In the summer of 1995 the whole site was surveyed for habitat suitable for the growth of the orchid and this information was also digitized on to the 25 m grid. The spread ofH. hircinumaround the site can now be demonstrated with a program, SCATTER. Population biology parameters for SCATTER have been calculated from data from two permanent 10×10 m plots. These data were collected annually between 1987 and 1994, and give information on the size and position of allH. hircinumplants within the plots. Two dispersal models were employed and compared with SCATTER. The first was a diffusion model and the second a tilted plume model. The tilted plume model describes the expansion of the population ofH. hircinumand also the number of flowering plants in the population more satisfactorily than the diffusion model.

According to Part I of this paper, it seems that ignoring the contribution from descendent cloud air in a cloud model for cumulus parameterization (CMCP), such as the spectral cumulus ensemble model in the Arakawa–Schubert parameterization, is an acceptable simplification for tropical deep convection. Since each subensemble in the spectral cumulus ensemble model is formally analogous to an entraining plume, the latter is examined using the simulated data from a cloud-resolving model (CRM). The authors first follow the analysis procedure of Warner. With the data from a nonprecipitating experiment, the authors show that the entraining-plume model cannot simultaneously predict the mean liquid water profile and cloud top height of the clouds simulated by the CRM. However, the mean properties of active elements of clouds, which are characterized by strong updrafts, can be described by an entraining plume of similar top height. With the data from a precipitating experiment, the authors examine the spec...

Observations of volcanic lightning made using a lightning mapping array during the 2010 eruption of Eyjafjallajökull allow the trajectory and growth of the volcanic plume to be determined. The lightning observations are compared with predictions of an integral model of volcanic plumes that includes descriptions of the interaction with wind and the effects of moisture. We show that the trajectory predicted by the integral model closely matches the observational data and the model well describes the growth of the plume downwind of the vent. Analysis of the lightning signals reveals information on the dominant charge structure within the volcanic plume. During the Eyjafjallajökull eruption both monopole and dipole charge structures were observed in the plume. By using the integral plume model, we propose the varying charge structure is connected to the availability of condensed water and low temperatures at high altitudes in the plume, suggesting ice formation may have contributed to the generation of a dipole charge structure via thunderstorm-style ice-based charging mechanisms, though overall this charging mechanism is believed to have had only a weak influence on the production of lightning.

Robots active olfaction based on Genetic algorithm, in order to make the robot car plume in a specific environment, can be faster and more accurate to find the odor source, through the genetic algorithm crossover and mutation operator improved, the formation of a new improved genetic algorithm. In the five assumptions, will improve the genetic algorithm is applied to the robot active olfaction study, simulation results show that the genetic algorithm with the traditional comparison, the robot car can be faster and more accurate in finding the odor plume source.

The communication aspects of Swarm-based Unmanned Aerial Systems (UAS) for surveillance and monitoring tasks have received increased attention in recent research. In this paper, we address the specific challenges of unpredictable incidents as forest fires, accidents in chemical or nuclear plants which cause potentially dangerous plumes. Therefore, we focus on the detection of chemical plume borderlines while maintaining the connectivity within the UAV team. Leveraging previously developed spatial exploration algorithms like Cooperative Repelling Walk we introduce two novel strategies to optimize the trade-off between detection-efficiency and communication constraints: the Aerosol-detecting Cooperative Repelling Walk (ADCRW) and the Distributed Dispersion Detection (DDD) Algorithm. Both algorithms are evaluated with the help of a multi-scale simulation model which includes a newly incorporated Briggs plume model. Considering the mentioned scenario the results of the performance evaluation demonstrate that the detection-efficiency of our novel algorithms is significantly improved, while at the same time connectivity goals are still met: with the new algorithms the time to detect the borderline of a plume can be reduced by 35%, while the connectivity within the swarm is about 100%.

In: The Polar Oceans and Their Role in Shaping the Global Environment: The Nansen Centennial Volume pp 237-246

The paper discusses the description of the simple model of the, so-called, steam plume, which in many cases forms during the operation of the evaporative cooling systems of the power plants, or large technological units. The model is based on semi-empirical equations that describe the behaviour of a mixture of two gases in case of the free jet stream. In the conclusion of the paper, a simple experiment is presented through which the results of the designed model shall be validated in the subsequent period.

This article proposes a new implementation scheme of multi-robot odor localization based on genetic algorithm (GA). Firstly, a simple multi-hump plume model with a maximum only is set up. Secondly, the implementation procedure of mobile robot odor localization (MROL) based on GA in the stimulated environment is presented. The simulation results validate the proposed search scheme.

We consider the phenomenon of self-focusing pattern formation of motile micro-organisms (“streamer”). The focusing mechanism is based on gyrotaxis, a physical phenomenon, and it results from the balance between viscous and gravitational moments on the organisms. Under particular circumstances such streamers are stabilized and sink, resulting in vertical transport of micro-organisms as well as horizontal heterogeneity in cell concentration. We develop a plume model for the streamer, which consists of the equations of continuity, momentum, and cell concentration. These equations are further simplified to three basic equations representing volume, momentum and concentration fluxes of the steady-state plume. Asymptotic analytical solutions for the plume are obtained. From numerical solutions we find the shape of the plume which takes the form of a vertical string with lengths ranging from 1 to 10 cm. The streamer formation can be related to algal blooms occurring in the sea and to algal cultures grown in the laboratory.

The long-term multiple-point source plume model, described by Ahmad and Bouhamra was applied to describe the dispersion and predict the concentration of NH 3 . Different NH 3 emitting stacks from all chemical and petrochemical industries in the Shuaiba Industrial Area in Kuwait were represented by one superstack. The model prediction was compared with the measurements of seven monitoring stations inside and outside Shuaiba. The model gave the best concentration prediction at stations between 1 and 10 km away from the source. Measurements of the stations lying outside this range were underestimated by one order of magnitude. The model was also used to predict NH 3 concentration in Kuwait city, Kuwait International Airport and Ahmadi city where NH 3 is not monitored. The normalized mean square error (NMSE) and the weighted average fractional bias (FB) for the monthly values of sixteen months at the seven stations ranged from 0.8 to 13.3 and from −1.6 to 1.4, respectively. The mixing height ( L ) was found to have a significant effect on the model prediction up to an L value of 350 m. Beyond this value the mixing height showed no significant effect on concentration prediction.

Efficient emergency rehearse system provides both commanders and evacuation crowds with better preparation for dangerous gas diffusion accidents, which definitely causes serious social panic and huge property loss. This paper focuses on four key issues raised by such accidents in the chemical industry parks. These issues include modeling, simulation, rendering and decision making. Virtual Reality and GIS are exploited to enhance intuitive and comprehensive visual information. Google SketchUp is worked as large model resource library and used to efficiently assemble the targeted virtual environments. Simulation of dangerous gas diffusion is built based on Pasquill-Gifford model and gas properties. Puff model combined with plume model is used to generate the gas diffusion animation. And evacuation route of crowds is display through scene-GIS map. Large scale virtual environment is rendered using OSG engine. All the simulation processes are recorded in a video with time tag embedded, which enable the commanders review history scene and hence make reasonable decision instantly. The gas emergency rehearse system enable all the people involved in this system having useful information and immersive experience. The system is now integrated into a common public safety platform and running well.

Chemical and biological (CB) agent de tection and effective use of these observations in hazard assessment models are key elements of our nation’s CB defense program that seeks to ensure that Department of Defense (DoD) operations are minimally affected by a CB attack. A ccurate hazard assessments rely heavily on the source term parameters necessary to characterize the release in the transport and dispersion (T&D) simulation. Unfortunately, these source parameters are often not known and based on rudimentary assumptions. In this presentation we describe an algorithm that utilizes variational data assimilation techniques to fuse CB and meteor ological observations to char acterize agent release source parameters and provide a refi ned hazard assessment. The un derlying algorithm consists of a combination of modeling systems, including the Second order Closure Integrated PUFF model (SCIPUFF), its corresponding Source Term Estimation (STE) model, a hybrid Lagrangian-Eulerian Plume Model (LEPM), its formal adjoint, and the software infrastructure necessary to link them. SCIPUFF and its STE m odel are used to calculate a “first guess” source estimate. The LEPM and corresponding adjoint are then used to iteratively refine this release source estimate using variational data assimilation techniques. This algorithm has undergone preliminary testing using virtual “single realization” plume release data sets from the Virtual THreat Response Emulation and Analysis Testbed (VTHREAT) and data from the FUSION Field Trials 2007 (FFT07). The end-to-end prototype of this system that has been developed to illustrate its use within the United States (US) Joint E ffects Model (JEM) will be demonstrated. Keywords: Atmosphere, Chemical, Biological, Transport, Dispersion , Source, Parameter, Estimate, Variational, Adjoint

A livestock odor dispersion model (LODM) was developed to predict mean odor concentration, odor frequency, instantaneous odor concentration, and peak odor concentration from livestock operations. This model is based on the Gaussian fluctuating plume model and has the ability to consider the instantaneous concentration fluctuations and the differences between odor and traditional air pollutants. It can predict odor frequency from the routine hourly meteorological data input and deal with different types of sources and multiple sources. Also, the relationship between odor intensity and odor concentration was incorporated into the model.

[1] Firebrand spotting is one of the most vexing problems associated with wildland fires, challenging the lives and efforts of fire–fighting planners. This work is an effort to model numerically the event of firebrand spotting for the purposes of reviewing past modelling approaches and of demonstrating a more current coupled fire/atmosphere approach. A simple, two–dimensional treatment of the process of firebrand lofting is examined under the restrictive conditions typical of a classical plume modelling approach. Using this approach, the differences in trajectories of combusting and non–combusting particles are investigated. Next, firebrand spotting is examined using a coupled fire/atmosphere LES (Large Eddy Simulator) in which the processes of firebrand lofting, propagation, and deposition are connected. The behaviour of combusting and non-combusting firebrands released from a moving grassfire into three-dimensional time-varying coupled atmosphere-wildfire induced circulations is examined. When these results are compared to the results of a classical plume model for firebrand spotting, it is found that firebrand propagation in the coupled LES simulated flow is significantly different from that obtained by the two–dimensional empirically–derived plume model approach. The coupled atmosphere-wildfire LES results are explorative and need to be subjected to direct testing.

The Gaussian plume model is traditionally used to describe the movements of contaminants through carrier media. In two dimensions, the model is mathematically derived from a stochastic representation of sequential collisions between contaminant particles and the particles of the carrier medium. The corresponding model for three dimensions is derived by analogy. We show with a simple experimental system that this deduction by analogy is faulty.

This paper investigates the applicability of a gas-source localization method in outdoor environment. In the proposed method, a mobile robot is used to scan the area under consideration and to collect data on gas concentration and airflow velocity at various locations. The location of the gas source is estimated by applying a turbulent diffusion model of a gas plume to the data obtained by partial observation of the gas distribution in the given area. Discussion is made on the adjustment of the turbulent diffusion coefficient in the plume model to achieve successful estimation under various airflow conditions.

The Boeing Company, with collaborators, is developing an approach to an integrated precision landing and hazard avoidance (PL&HA) system that is capable of incorporating a suite of sensors to achieve terrain-relative navigation, and hazard detection and avoidance. The approach for the powered descent phase of the lander includes the sensors to provide a digital terrain map (DTM), cost map algorithms that identify the safe-landing sites from the DTM, and guidance navigation and control (GN&C) derived from the Delta Clipper (DC-X) project. A future flight demonstration of the GN&C and PL&HA technology to demonstrate precision landing could utilize the XA-0.2 lander model of Masten Space Systems. Boeing is developing a high-fidelity dynamic simulation model of the Masten XA-0.2 lander platform. Masten Space Systems has provided lander computer-aided design (CAD), mass properties data, and propulsion system models to Boeing for inclusion in this high-fidelity dynamic model. Boeing has developed a fuel-slosh model, rocket plume model, and an aerodynamic model of the XA-0.2 lander, and it will conduct wind tunnel testing to determine aerodynamic properties for the GN&C simulation. Boeing will then conduct extensive Monte Carlo simulations using this high-fidelity dynamic model to predict lander dynamic behavior during autonomous ascent, descent, and landing when controlled by Boeing GN&C adapted from the DC-X. 1 Systems Engineer, Boeing IDS, 5301 Bolsa Avenue, Huntington Beach, CA 92647/Mail Stop H012-C349, AIAA Member. 2 Flight Simulation Engineer, Boeing IDS, 5301 Bolsa Avenue, Huntington Beach, CA 92647/Mail Stop H022C328, AIAA Member. 3 Senior Manager, Flight Systems, Boeing IDS, 5301 Bolsa Avenue, Huntington Beach, CA 92647/Mail Stop H013-C328, AIAA Member. 4 Senior Manager, Advanced Technology Concepts, Boeing Research and Technology, 5301 Bolsa Avenue, Huntington Beach, CA 92647/Mail Stop H045-E408, AIAA Member. 5 Aerothermodynamics Engineer, Boeing IDS, Bolsa Avenue, Huntington Beach, CA 92647/Mail Stop H013-C322, AIAA Member. 6 Propulsion Engineer, Boeing Research and Technology, 5301 Bolsa Avenue, Huntington Beach, CA 92647/Mail Stop H045-E408, AIAA Member. 7 CFD Engineer, Boeing Research and Technology, 5301 Bolsa Avenue, Huntington Beach, CA 92647/Mail Stop H045-E408, AIAA Member. 8 Propulsion Engineer, Masten Space Systems, 1570 Sabovich St., Bldg 25, Mojave, CA 93501, AIAA Member. 9 President, Masten Space Systems, 1570 Sabovich St., Bldg 25, Mojave, CA 93501, non-member. AIAA SPACE 2009 Conference & Exposition 14 17 September 2009, Pasadena, California AIAA 2009-6571 Copyright © 2009 by The Boeing Co. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. American Institute of Aeronautics and Astronautics 2

The observed levels of high sea‐state surface‐related reverberation are modeled as scattering from plumes of microbubbles. The plume model is constrained as much as possible by existing microbubble data, particularly the average bubble content as a function of depth measured by Farmer and Vagle [J. Acoust. Soc. Am. 86, 1897–1908 (1989)]. The Chapman–Harris [J. Acoust. Soc. Am. 34, 1592–1597 (1962)] and Chapman–Scott [J. Acoust. Soc. Am. 36, 1735–1737 (1964)] experimental levels are fit with reasonable parameter choices. Frequency and grazing angle dependence are predicted by the model. Wind speed dependence is not addressed in this paper.

First order approximations of the rates of emission of isoprene and α-pinene are made for the region around London. Isoprene is found to be the dominant biogenic non-methane hydrocarbon species by mass in the region. Chemical degradation schemes for isoprene and α-pinene are added to an existing urban plume model which has previously been applied to London. The influence of each hydrocarbon is investigated by comparing model runs which include biogenic chemistry to a base case scenario. Oveerall, the effect is small: ozone levels in the plume are increased by the addition of the new schemes by up to 88 ppb. A model run with biogenic hydrocarbon and NO x emissions only demonstrates the VOC-limited behaviour of the urbans plume. Conversely, removall of anthropenic VOC emissions from the rural/suburban model results in a decrease of only 5 ppb in ozone production over one day. The reason for this difference in behaviour is the different NMHC/NO x ratios within and outside the urban plume. The inclusion of biogenic NMHC chemistry in the model results in a negligible change to the calculated ‘urban ozone effect’ defined as as the difference between ozone concentrations within and outsside of the plume. Substantial enhancement to present biogenic NMHC database are required if our understanding of urban plume chemistry is to be made more accurate.

A three-dimensional plume model is applied to the transport of pollutants in the lower atmosphere. The model contains parameterizations for the vertical and horizontal diffusion coefficients based on the turbulent energy equation. While this parameterization works well for stable and neutral conditions it is expectedly inadequate for convective conditions. An empirical extension containing the influence of strong ambient convection on updraft and downdraft of the plume improves comparisons with field data from tall stacks.

This paper explores the developing of a graphical simulation environment for multiple chemical plume tracing and source identification. A number of classes, including a graphical display class, make up the simulation program. Because the intent is to capture and simulate real life scenarios, the program simulates significant variation of fluid flow velocity and orientation, the significant intermittency between advection fluid flow, chemical filaments, and significant meander of chemical plumes to challenge a chemical plume tracing strategy. Thus, the advection fluid flow model class, plume model classes, sensor classes, plume tracing strategy classes, and vehicle model classes were created to bring this challenge alive in a measurable, three dimensional model. The outcome is highly promising, in that it can efficiently evaluate strategies for tracing multiple plumes, identifying their sources, and can do so even in three-dimensions.

We have developed a new approach for detecting and tracking chemical or biological plumes in distributed sensor networks, with the objective of solving the inverse location problem. The canonical plume tracking problem suffers from the challenge of a large state space, and we seek reduced dimensionality using information theoretic and stochastic methods. Working with an airborne plume we model a plume using multiple hypothesis tracking (MHT) techniques as opposed to transport based methods rooted in solutions to differential equations. The simple plume model attributes include: diffusion constant, wind direction, and wind magnitude. The location of the plume prior to current observations is calculated statistically with the use of an estimator-based joint probability. The main contribution of this work is the predictor model - a required step of the MHT algorithm. A customized predictor for plumes (as opposed to Kalman filtering) allows the MHT-like algorithm to treat the plume tracking problem as the extreme instance of the multi-target tacking (MTT) problem. The central question: how can a MHT-like method be implemented for plumes in a sensor network of simple sensors capable of rudimentary binary detection, wind speed, and wind direction. The predictor must handle the problem of data association for plume observations. The context for this work is the development of multiple competing models which is correlated to incoming observations in real time. The models run in a generic multi-purpose framework called PQS (process query system). Simulations were performed demonstrating the viability of the MHT approach with the use of a customized predictor for plume target tracking

In l99l, US Army personnel were potentially exposed to chemical warfare agents following the demolition of the Khamisiyah ammunition depot in Iraq. We conducted three related investigations concerning morbidity and mortality. First, we analyzed data from 5,555 Army veteran respondents to the VA's 1995 National Health Survey of Gulf War Era Veterans and their Families to study the association between potential exposure to chemical agents and self-reported morbidity. Potential exposure status was determined from Department of Defense (DoD) data known as the 2000 plume model. Second, we resurveyed a sample of roughly 1,200 respondents to the original survey to obtain self-reported morbidity after some of these original respondents had been notified by DoD of possible exposure to chemical agents. Comparing pre- and post-notification morbidity allowed us to study the association of notification and morbidity. Neither possible exposure nor notification of possible exposure were unduly associated with morbidity. Third, we examined the association between mortality among some 351,000 deployed Army veterans and potential exposure. We found a roughly two-fold excess of deaths due to brain cancer in the exposed group, representing an excess of 12 deaths in roughly 100,000 subjects in a 10-year period. The results of our research were published in three papers in two peer-reviewed journals.

The peak activities of continental flood basalts are currently considered as huge and brief (∼1 m.y.) magmatic events, with strong implications for geodynamics and biotic turnover. New 4 0 Ar/ 3 9 Ar dates on the Karoo flood basalts (southern Africa) show a longer duration of magmatism (∼8 m.y., with 6 m.y. for the main volume) with an apparent south-to-north migration, along with briefer distinctive pulses inside the province. This suggests that the Karoo province does not fit the general plume model invoked for most continental flood basalts (including the Karoo) and may explain the absence of a major contemporaneous mass extinction.

LIDAR images of a plume over a forest canopy are analyzed to estimate instantaneous vertical dispersion, and vertical meander of the plume centerline. Turbulence parameters calculated from the LIDAR images are compared with parameters derived from sonic anemometer data collected near the plume release point. It is argued that analysis of lidar images of spray plumes is an accurate and efficient way to estimate turbulence parameters for spray transport models in cases when installation of fast-response, in-situ, measurements are not practical.