Lagrangian Dispersion Model Research Articles

A Lagrangian dispersion model with chemical reactions

A Lagrangian stochastic (single particle) model is modified in order to account for simple chemistry reactions and tested against measured wind tunnel data. These data refers to a reactive plume generated by a single point source of NO inside a turbulent grid flow doped with ozone. The comparisons were made at different distances from the emission considering all the substances involved in the experiment. The cross correlation terms between the concentrations of the different chemical compounds are neglected or parameterised. Despite this simplification the results are rather satisfactory and seem to encourage practical applications in real atmosphere.

Development and first tests of a data assimilation algorithm in a Lagrangian puff atmospheric dispersion model

The development of a Data Assimilation algorithm based on variational approach that allows estimation of source emission rate in Lagrangian particle/puff Atmospheric Dispersion Models for non-stationary (wind and source) conditions is presented. The one-dimensional tests including constant and variable in time source emission rate and wind velocity showed that methodology can be extended to take into account variable meteorological conditions. In the 2-dimensional atmospheric dispersion test cases the sensitivity of the developed method on the spatial density of the measurement network was evaluated and an optimal value for the parameter rmod (error of observations proportional to observed concentrations) was estimated.

Validation of regulatory micro-scale air quality models: modelling odour dispersion and built-up areas

Gaussian and Lagrangian model runs are evaluated in comparison to field data from the Odour Release and Odour Dispersion (OROD) project and to wind tunnel data from the Mock Urban Setting Test (MUST). Different statistical metrics are discussed. The results illustrate once again that a good model performance is strongly dependent on the model input (e.g., terrain data, roughness length). Promising results are received from a combination of the Lagrangian dispersion model LASAT with wind field simulations calculated with the CFD model MISKAM.

Locating a compact odor source using a four-channel insect electroantennogram sensor

Here we demonstrate the feasibility of using an array of live insects to detect concentrated packets of odor and infer the location of an odor source (∼15 m away) using a backward Lagrangian dispersion model based on the Langevin equation. Bayesian inference allows uncertainty to be quantified, which is useful for robotic planning. The electroantennogram (EAG) is the biopotential developed between the tissue at the tip of an insect antenna and its base, which is due to the massed response of the olfactory receptor neurons to an odor stimulus. The EAG signal can carry tens of bits per second of information with a rise time as short as 12 ms (K A Justice 2005 J. Neurophiol. 93 2233–9). Here, instrumentation including a GPS with a digital compass and an ultrasonic 2D anemometer has been integrated with an EAG odor detection scheme, allowing the location of an odor source to be estimated by collecting data at several downwind locations. Bayesian inference in conjunction with a Lagrangian dispersion model, taking into account detection errors, has been implemented resulting in an estimate of the odor source location within 0.2 m of the actual location.

Development and evaluation of GRAL-C dispersion model, a hybrid Eulerian–Lagrangian approach capturing NO–NO2–O3 chemistry

Abstract Based on two recent publications using Lagrangian dispersion models to simulate NO–NO2–O3 chemistry for industrial plumes, a similar modified approach was implemented using GRAL-C (Graz Lagrangian Model with Chemistry) and tested on two urban applications. In the hybrid dispersion model GRAL-C, the transport and turbulent diffusion of primary species such as NO and NO2 are treated in a Lagrangian framework while those of O3 are treated in an Eulerian framework. GRAL-C was employed on a one year street canyon simulation in Berlin and on a four-day simulation during a winter season in Graz, the second biggest city in Austria. In contrast to Middleton D.R., Jones A.R., Redington A.L., Thomson D.J., Sokhi R.S., Luhana L., Fisher B.E.A. (2008. Lagrangian modelling of plume chemistry for secondary pollutants in large industrial plumes. Atmospheric Environment 42, 415–427) and Alessandrini S., Ferrero E. (2008. A Lagrangian model with chemical reactions: application in real atmosphere. Proceedings of the 12th Int. Conf. on Harmonization within atmospheric dispersion modelling for regulatory purposes. Croatian Meteorological Journal, 43, ISSN: 1330-0083, 235–239) the treatment of ozone was modified in order to facilitate urban scale simulations encompassing dense road networks. For the street canyon application, modelled daily mean NOx/NO2 concentrations deviated by +0.4%/−15% from observations, while the correlations for NOx and NO2 were 0.67 and 0.76 respectively. NO2 concentrations were underestimated in summer, but were captured well for other seasons. In Graz a fair agreement for NOx and NO2 was obtained between observed and modelled values for NOx and NO2. Simulated diurnal cycles of NO2 and O3 matched observations reasonably well, although O3 was underestimated during the day. A possible explanation here might lie in the non-consideration of volatile organic compounds (VOCs) chemistry.

On concentration footprints for a tall tower in the presence of a nocturnal low-level jet

This paper reports on the location of sources contributing to a point concentration measurement in the stable boundary layer. Concentration footprints for sensors located at different heights during the night are examined using a backward-in-time Lagrangian stochastic dispersion model. Simulations of air parcel transport in a non-steady-state atmospheric boundary layer above a bare surface and a forest under different insolation suggest that sources located as far as several hundred kms away contribute to a concentration measurement made at levels as high as 500 m. The origin of the maximal contribution area shifts during the night depending on the wind direction at the sensor location, a feature most prominent in the presence of decoupling between sensor levels and surface sources. Simulations suggest that atmospheric static stability alone is not a sufficient criterion to trigger flow decoupling. The presence of the low-level jet provides vertical mixing of air parcels even for stable boundary layers with Richardson numbers higher than the critical. This finding is in agreement with earlier observations suggesting that the level of the low-level jet nose acts as a strong lid prohibiting vertical gas propagation. These findings have important implications in the interpretation of eddy-flux measurements in nocturnal conditions.

Autocorrelation function formulations and the turbulence dissipation rate: Application to dispersion models

The classical statistical diffusion theory and the binomial autocorrelation function are used to obtain a new formulation for the turbulence dissipation rate ε . The approach employs the Maclaurin series expansion of a logarithm function contained in the dispersion parameter formulation. The numerical coefficient of this new relation for ε is 100% larger than the numerical coefficient of the classical relation derived from the exponential autocorrelation function. A similar approach shows that the dispersion parameter obtained from the even exponential autocorrelation function does not result in a relation for ε and, therefore, is not suitable for application in dispersion models. In addition, a statistical comparison to experimental ground-level concentration data demonstrates that this newly derived relation for ε as well as other formulations for the turbulence dissipation rate are suitable for application in Lagrangian stochastic dispersion models. Therefore, the analysis shows that there is an uncertainty regarding the turbulence dissipation rate function form and the autocorrelation function form.

Lagrangian models of dispersion in marine environment

Turbulent dispersion can be studied successfully by using Lagrangian particle models. In general, the prediction of correct concentration fields is a complex issue when the turbulent field is inhomogeneous and non-stationary. Two classes of Lagrangian dispersion models have been considered in this work, which are based on the Wiener process and the so called “well-mixed” criterion. In order to test the performances of these models and shed light on the underlying physical processes and modeling assumptions, four different numerical models have been compared and tested by means of their long time behavior by considering several study cases concerning idealized marine environment. Furthermore, the coupling of the community model Princeton Ocean Model (POM) with the Lagrangian model LASEMOD (LAgrangian SEa MODel) is used to investigate the temporal and spatial evolution of a passive pollutant released in the vicinity of the coast in the Tyrrhenian Sea basin. The simulation shows with reasonable accuracy the time evolution of both the hydrodynamic and the concentration fields and provides a useful insight into the evaluation of the environmental impact of pollutant releases along the coast.

A set of rapid-response models for pollutant dispersion assessments in southern Spain coastal waters

Three rapid-response Lagrangian particle-tracking dispersion models have been developed for southern Spain coastal waters. The three domains cover the Gulf of Cádiz (Atlantic Ocean), the Alborán Sea (Mediterranean), and the Strait of Gibraltar with higher spatial resolution. The models are based on different hydrodynamic submodels, which are run in advance. Tides are calculated using a 2D barotropic model in the three cases. Models used to obtain the residual circulation depend on the physical oceanography of each region. Thus, two-layer models are applied to Gibraltar Strait and Alborán Sea and a 3D baroclinic model is used in the Gulf of Cádiz. Results from these models have been compared with observations to validate them and are then used by the particle-tracking models to calculate dispersion. Chemical, radioactive and oil spills may be simulated, incorporating specific processes for each kind of pollutant. Several application examples are provided.

A 15 year record of high-frequency, in situ measurements of hydrogen at Mace Head, Ireland

Abstract. Continuous high-frequency measurements of atmospheric molecular hydrogen have been made at Mace Head atmospheric research station on the west coast of Ireland from March 1994 to December 2008. The presented data provides information on long term trends and seasonal cycles of hydrogen in background northern hemispheric air. Individual measurements have been sorted using a Lagrangian dispersion model to separate clean background air from regionally polluted European air masses and those transported from southerly latitudes. No significant trend was observed in background northern hemispheric air over the 15 year record, elevations in yearly means were accounted for from large scale biomass burning events. Seasonal cycles show the expected pattern with maxima in spring and minima in late autumn. The mean hydrogen mole fraction in baseline northern hemispheric air was found to be 500.1 ppb. Air transported from southerly latitudes showed an elevation from baseline mean of 11.0 ppb, reflecting both the latitudinal gradient of hydrogen, with higher concentrations in the Southern Hemisphere, and the photochemical source of hydrogen from low northern latitudes. European polluted air masses arriving at Mace Head showed mean elevation of 5.3 ppb from baseline air masses, reflecting hydrogen's source from primary emissions like fossil fuel combustion. Forward modelling of transport of hydrogen to Mace Head suggests that the ratio of hydrogen to carbon monoxide in primary emissions is considerably less in non-traffic sources than traffic sources.

Three-dimensional characterization of the ammonia plume from a beef cattle feedlot

In Canada approximately 45% of ammonia (NH 3) emissions are attributed to dairy and beef cattle industries. The present study focused on NH 3 emissions from a beef feedlot with a one-time capacity of 17,220 head. The aim was to improve the Canadian NH 3 emission inventories and air quality forecasting capabilities. A Cessna 207, equipped with a fast-response NH 3/NO y detector and a quadrupole aerosol mass spectrometer, was flown in a grid pattern covering an area of 8 × 8 km centered on a feedlot (800 × 800 m) at altitudes ranging from 30 to 300 m above ground. Stationary ground measurements of NH 3 concentration and turbulence parameters were made downwind of the feedlot. Three flights were conducted under varying meteorological conditions, ranging from very calm to windy with near-neutral stratification. NH 3 mixing ratios up to 100 ppbv were recorded on the calm day, up to 300 m above ground. An average feedlot NH 3 emission rate of 76 ± 4 μg m −2 s −1 (equivalent to 10.2 g head −1 h −1) was estimated. Characteristics of the measured NH 3 plume were compared to those predicted by a Lagrangian dispersion model. The spatially integrated pattern of NH 3 concentrations predicted and measured agreed but the measured was often more complex than the predicted spatial distribution. The study suggests that the export of NH 3 through advection accounted for about 90% of the emissions from the feedlot, chemical transformation was insignificant, and dry deposition accounted for the remaining 10%.

Transport of north China air pollution by midlatitude cyclones: Case study of aircraft measurements in summer 2007

Warm conveyor belts (WCBs) and frontal activity play important roles in the long‐range transport of air pollutants by lifting them from the planetary boundary layer (PBL) into the free troposphere (FT) in midlatitudes. In summer 2007, an aircraft study was carried out in northeast (NE) China in order to understand the role of midlatitude cyclones in air pollution transport in north and east China in warm seasons. During a flight on 27 June, high concentrations of ozone and related trace gases were observed, with maximum concentrations (O3 ∼ 140 ppbv, SO2 ∼ 14.6 ppbv, CO ∼ 1185 ppbv) recorded at an altitude of 2.6 km. In this paper we present a detailed analysis of this flight. The mesoscale meteorological model Weather Research and Forecasting (WRF) and a Lagrangian dispersion model called FLEXPART were used to aid the diagnostic analysis of the atmospheric dynamic structure and the understanding of the transport characteristics of regional and local air pollution. The flight took place in a region adjacent to a warm front associated with a weak cyclone in north China. The aircraft sampled both the WCB and warm air frontal zone of the cyclone. The simulations show that the observed high air pollution in the FT mostly originated from the North China Plain, especially the megacities Beijing and Tianjin. Their plumes were vented by a stagnant front, probably through, in part, topographic lifting by the mountains in the north, and then were quickly transported in the FT to the study region. Trajectory analysis and satellite data suggest that the observed air masses were further lifted by the WCB into the middle and upper troposphere and were exported from Asia toward North America and the Arctic.

Employing turbulent and meandering time scales to modeling the contaminants enhanced horizontal dispersion

A Lagrangian stochastic particle dispersion model composed of two coupled Langevin equations, employing a new transport parameterization is used to study the meandering enhanced dispersion in a low wind speed stable atmospheric boundary layer (ABL). The meandering parameterization introduced into the Lagrangian stochastic dispersion model is expressed in terms of a characteristic phenomenological meandering period and of the horizontal local turbulent time scales associated with a fully developed turbulence. The results of this new method are shown to agree with the field observations of Idaho experiments and also with other different meandering dispersion models. The major advance shown throughout this paper is as it follows: For air quality modeling it is highly necessary to include a parameterization that allows a correct description of the dispersion caused by the low-frequency horizontal wind oscillations.

Sensitivity of modelled sulphate and nitrate aerosol to cloud, pH and ammonia emissions

A Lagrangian dispersion model has been used to predict daily sulphate aerosol in 2006 at five UK rural measurement sites and hourly nitrate aerosol in April 2003 at Harwell (UK). The sensitivity of aqueous phase sulphate production to the meteorological input has been investigated. Large differences were found between cloud fraction and cloud liquid water output from the regional and mesoscale Met Office Unified Model. The impact on the sulphate aerosol was relatively small, with the mesoscale meteorology giving better results. Sulphate aerosol production in the aqueous phase was found to be very sensitive to modelled cloud pH. As the cloud becomes acidic sulphate production is greatly limited, conversely if the cloud is basic large amounts of sulphate aerosol are produced. A fixed model pH of 5.8 was found to produce better results than allowing the model to calculate pH which resulted in large over-predictions of measured sulphate aerosol in some episodes. Nitrate aerosol was not sensitive to cloud variables or pH, but showed a slight increase with 30% more ammonia emissions, and a slight decrease with 30% less ammonia. Sulphate production in model runs with fixed pH was not sensitive to changing ammonia emissions, however the sulphate production with modelled pH was very sensitive to plus or minus 30% ammonia. This work suggests that good modelling of ammonia is essential to correct estimation of aqueous phase sulphate aerosol if cloud pH is modelled. It is concluded that modelling to estimate the effect of reduced ammonia emission scenarios on future ambient aerosol levels should also take into account the neutralising effect of ammonia in cloud and hence the effect on aqueous phase production of sulphate.

Selected results of a model validation exercise

Abstract. The concentration fields calculated with three Gaussian models and one Lagrangian dispersion model are validated against a set of SF6 concentration data provided by the German environmental programme BWPLUS. The source was a pig fattening unit in fairly flat terrain. The results reveal that, in flat terrain with steady undisturbed flow, the use of Gauss models is still justified, whereas Lagrangian models should be used whenever the flow is modified by obstacles or topography.

Predicting Outcrossing in Maize Hybrid Seed Production

Controlling pollination of the female inbred is critical to achieve maximum kernel set and high levels of genetic purity in maize (Zea mays L.) hybrid seed production. Although kernel set associated with inbred flowering dynamics is fairly predictable, it has not been possible to predict the level of outcrossing resulting from adventitious pollen entering the seed field. Our objective was to combine our kernel set model with a new Lagrangian pollen dispersal model to determine whether outcrossing could be simulated from flowering dynamics and estimates of pollen drift. This study was conducted in a commercial seed production field in which male and female planting dates were varied to provide a range of flowering synchronies and risk for outcrossing. Kernel production varied from 13.4 × 106 to 24.5 × 106 kernels ha−1. Outcrossing at field locations 100 to 170 m from an adventitious pollen source varied from 1.4 to 18% as determined by allelic variation at 13 loci. The kernel set model accurately simulated variation in kernel production (R2 = 0.83; RMSE = 0.3 × 106) when silk receptivity was limited to 4 d. Percentage outcrossing due to adventitious pollen also was accurately simulated (R2 = 0.78; RMSE = 0.8) for wind conditions and plant development patterns typically encountered in maize hybrid seed production. The combined kernel set and pollen dispersal models provide a novel and robust approach for defining management strategies to optimize kernel production and genetic purity.

Testing Lagrangian atmospheric dispersion modelling to monitor CO 2 and CH 4 leakage from geosequestration

We assess the performance of an inverse Lagrangian dispersion technique for its suitability to quantify leakages from geological storage of CO 2. We find the technique is accurate ( 〈 Q bLS / Q 〉 = 0.99 , σ = 0.29 ) when strict meteorological filtering is applied to ensure that Monin–Obukhov Similarity Theory is valid for the periods analysed and when downwind enrichments in tracer gas concentration are 1% or more above background concentration. Because of their respective baseline atmospheric concentrations, this enrichment criterion is less onerous for CH 4 than for CO 2. Therefore for geologically sequestered gas reservoirs with a significant CH 4 component, monitoring CH 4 as a surrogate for CO 2 leakage could be as much as 10 times more sensitive than monitoring CO 2 alone. Additional recommendations for designing a robust atmospheric monitoring strategy for geosequestration include: continuous concentration data; exact inter-calibration of up- and downwind concentration measurements; use of an array of point concentration sensors to maximise the use of spatial information about the leakage plume; and precise isotope ratio measurement to confirm the source of any concentration elevations detected.

A simple model for simulation of insect pheromone dispersion within forest canopies

Synthetic pheromones and other behavioral chemicals are used by land managers to prevent insect-caused tree mortality or crop failure in forest and agricultural systems. Currently, no method exists to continuously measure pheromone concentration or movement in real-time. To improve our understanding of pheromone fate and transport under different forest canopies, results from a set of surrogate pheromone (sulfur hexafluoride tracer) experimental trials were used to evaluate a simple, instantaneous, three-dimensional Lagrangian dispersion model. The model was designed to predict both instantaneous and time-averaged pheromone concentrations. Overall, the results from the model show simulated time-averaged arc maximum concentrations within a factor of two of the observed data. The model correctly matched the sharp peaks and narrow widths of the meandering plumes observed in the instantaneous data, however the magnitude of the instantaneous peaks was often under-estimated. This model and evaluation provide the basis for a tool that can be used to guide deployment of synthetic pheromones or other semiochemicals for monitoring, mass trapping, or disruption of mating or aggregation.

The Turbulent Lagrangian Time Scale in Forest Canopies Constrained by Fluxes, Concentrations and Source Distributions

One-dimensional Lagrangian dispersion models, frequently used to relate in-canopy source/sink distributions of energy, water and trace gases to vertical concentration profiles, require estimates of the standard deviation of the vertical wind speed, which can be measured, and the Lagrangian time scale, T L , which cannot. In this work we use non-linear parameter estimation to determine the vertical profile of the Lagrangian time scale that simultaneously optimises agreement between modelled and measured vertical profiles of temperature, water vapour and carbon dioxide concentrations within a 40-m tall temperate Eucalyptus forest in south-eastern Australia. Modelled temperature and concentration profiles are generated using Lagrangian dispersion theory combined with source/sink distributions of sensible heat, water vapour and CO2. These distributions are derived from a multilayer Soil-Vegetation-Atmospheric-Transfer model subject to multiple constraints: (1) daytime eddy flux measurements of sensible heat, latent heat, and CO2 above the canopy, (2) in-canopy lidar measurements of leaf area density distribution, and (3) chamber measurements of CO2 ground fluxes. The resulting estimate of Lagrangian time scale within the canopy under near-neutral conditions is about 1.7 times higher than previous estimates and decreases towards zero at the ground. It represents an advance over previous estimates of T L , which are largely unconstrained by measurements.

SAGA: a decision support system for air pollution management around a coal-fired power plant

Air quality models are currently feasible approaches to prevent air pollution episodes. From one of the first source-oriented modelling approaches for air pollution forecasting (Souto et al., 1994, 1996, 1998), a new decision support system for air quality management, SAGA, was developed to provide support to As Pontes Power Plant (APPP) staff. SAGA can provide air pollution forecasts and manage meteorological and air quality measurements. Power plant decisions are supported by the results of a non-hydrostatic meteorological model (ARPS, Xue et al., 2001) to produce Meteorological Forecasts (MFs), and to be coupled to different Lagrangian dispersion models.