Lagrangian Atmospheric Dispersion Model Research Articles

The characteristics of the vertical distribution of radionuclide in free troposphere from simplified release scenarios: a case study

Dose estimation in the upper air is not studied as much as on ground level or in boundary layer. However, there is a need from stakeholders in aviation industry for a reasonable estimation of the radioactive plume impact at cruising levels. This study aims to provide a quantitative estimation of the dose and how reliable it is for dispersion processes up to seven days. A Lagrangian atmospheric dispersion model is used to estimate quantitively the vertical extension of radionuclides from simplified hypothetical radionuclide release scenarios. Sources at different latitudes are selected for simulation in a boreal winter case. Three meteorological data are examined to test the sensitivity of vertical plume distribution to driving meteorological data. The vertical distribution of air concentration of radionuclides is investigated and the associated uncertainties are analysed. It is found that the vertical extension of plumes is sensitive to meteorological data being used where vertical turbulent velocities play an important role. It is therefore necessary to address the uncertainties of air concentration or dose in the free troposphere and caution must be taken when providing the results to stakeholders.

Information Theory Solution Approach to the Air Pollution Sensor Location–Allocation Problem

Air pollution is one of the prime adverse environmental outcomes of urbanization and industrialization. The first step toward air pollution mitigation is monitoring and identifying its source(s). The deployment of a sensor array always involves a tradeoff between cost and performance. The performance of the network heavily depends on optimal deployment of the sensors. The latter is known as the location–allocation problem. Here, a new approach drawing on information theory is presented, in which air pollution levels at different locations are computed using a Lagrangian atmospheric dispersion model under various meteorological conditions. The sensors are then placed in those locations identified as the most informative. Specifically, entropy is used to quantify the locations’ informativity. This entropy method is compared to two commonly used heuristics for solving the location–allocation problem. In the first, sensors are randomly deployed; in the second, the sensors are placed according to maximal cumulative pollution levels (i.e., hot spots). Two simulated scenarios were evaluated: one containing point sources and buildings and the other containing line sources (i.e., roads). The entropy method resulted in superior sensor deployment in terms of source apportionment and dense pollution field reconstruction from the sparse sensors’ network measurements.

Modelling the size distribution of aggregated volcanic ash and implications for operational atmospheric dispersion modelling

Abstract. We have developed an aggregation scheme for use with the Lagrangian atmospheric transport and dispersion model NAME (Numerical Atmospheric Dispersion modelling Environment), which is used by the London Volcanic Ash Advisory Centre (VAAC) to provide advice and guidance on the location of volcanic ash clouds to the aviation industry. The aggregation scheme uses the fixed pivot technique to solve the Smoluchowski coagulation equations to simulate aggregation processes in an eruption column. This represents the first attempt at modelling explicitly the change in the grain size distribution (GSD) of the ash due to aggregation in a model which is used for operational response. To understand the sensitivity of the output aggregated GSD to the model parameters, we conducted a simple parametric study and scaling analysis. We find that the modelled aggregated GSD is sensitive to the density distribution and grain size distribution assigned to the non-aggregated particles at the source. Our ability to accurately forecast the long-range transport of volcanic ash clouds is, therefore, still limited by real-time information on the physical characteristics of the ash. We assess the impact of using the aggregated GSD on model simulations of the 2010 Eyjafjallajökull ash cloud and consider the implications for operational forecasting. Using the time-evolving aggregated GSD at the top of the eruption column to initialize dispersion model simulations had little impact on the modelled extent and mass loadings in the distal ash cloud. Our aggregation scheme does not account for the density of the aggregates; however, if we assume that the aggregates have the same density of single grains of equivalent size, the modelled area of the Eyjafjallajökull ash cloud with high concentrations of ash, significant for aviation, is reduced by ∼ 2 %, 24 h after the start of the release. If we assume that the aggregates have a lower density (500 kg m−3) than the single grains of which they are composed and make up 75 % of the mass in the ash cloud, the extent is 1.1 times larger.

Method of Source Identification Following an Accidental Release at an Unknown Location Using a Lagrangian Atmospheric Dispersion Model

A computationally efficient source inversion algorithm was developed and applied with the Lagrangian atmospheric dispersion model DIPCOT. In the process of source location estimation by minimizing a correlation-based cost function, the algorithm uses only the values of the time-integrated concentrations at the monitoring stations instead of all of the individual measurements in the full concentration-time series, resulting in a significant reduction in the number of integrations of the backward transport equations. Following the source location estimation the release start time, duration and emission rate are assessed. The developed algorithm was verified for the conditions of the ETEX-I (European Tracer Experiment—1st release). Using time-integrated measurements from all available stations, the distance between the estimated and true source location was 108 km. The estimated start time of the release was only about 1 h different from the true value, within the possible accuracy of estimate of this parameter. The estimated release duration was 21 h (the true value was 12 h). The estimated release rate was 4.28 g/s (the true value was 7.95 g/s). The estimated released mass almost perfectly fitted the true released mass (323.6 vs. 343.4 kg). It thus could be concluded that the developed algorithm is suitable for further integration in real-time decision support systems.

Radiological dose assessment due to hypothetical nuclear power plant operation in Mersing, Johor, Malaysia

Malaysia has considered for some time to adopt nuclear power to cater to the increasing demand of electricity following other developed Asian countries such as Japan, Korea, and China. In implementing a nuclear power plant, strict regulations and guidelines by the International Atomic Energy Agency (IAEA) and International Commission on Radiological Protection (ICRP) must be fulfilled before any construction license is given for a new nuclear power program. One of the assessments include the estimation of potential radiological risks to both humans and environment from routine and accidental release of radioactive effluent from the nuclear power plant (NPP). In this work, simulations of radionuclide dispersion from a hypothetical NPP site in Mersing, Johor will be presented. The simulation was performed based on the Lagrangian atmospheric dispersion model using the HYSPLIT software. The radioactive effluent release rate was approximated to the value found in the Fukushima Dai-ichi accident in 2011. Meteorological data of 2017 were utilized in this study. Simulation results showed that the dispersion of radioactive effluent from the hypothetical NPP can potentially affect areas around Johor Bahru district, Singapore, and even some areas in Indonesia.

Comparison of simulated radioactive atmospheric releases to citizen science observations for the Fukushima nuclear accident

Citizen science data from the Safecast project were shown to provide a reliable estimation of the spatial distribution of concentrations of elevated radiation levels around Fukushima when compared to government data. A comparison is presented between the HYSPLIT Lagrangian atmospheric transport and dispersion (T&D) model and a reflected Gaussian model to both government and Safecast contributed measurements. The advantage of contributed data with respect to the government data is that they are collected over a long period of time and have a larger spatial coverage.First, the Safecast contributed measurements are compared to aerial surveys completed by the Department of Energy (DOE) and the National Nuclear Security Administration (NNSA). Then the HYSPLIT T&D model is run to simulate the nuclear release using high resolution terrain and meteorological data. A Gaussian dispersion model is also run for comparison using meteorological data observed at the time of the accident. The results of both models and observed data are decay corrected to December 2016 in order to use a larger quantity of contributed measurements in the comparison.The comparison of areas of elevated radiation shows that the citizen science observations align with the prediction of models representing dynamic behavior of radionuclides dispersed in the environment. This paper shows that citizen science data can be used to validate and potentially better calibrate atmospheric T&D models.

An inverse method to estimate emission rates based on nonlinear least-squares-based ensemble four-dimensional variational data assimilation with local air concentration measurements

An inverse source estimation method is proposed to reconstruct emission rates using local air concentration sampling data. It involves the nonlinear least squares-based ensemble four-dimensional variational data assimilation (NLS-4DVar) algorithm and a transfer coefficient matrix (TCM) created using FLEXPART, a Lagrangian atmospheric dispersion model. The method was tested by twin experiments and experiments with actual Cs-137 concentrations measured around the Fukushima Daiichi Nuclear Power Plant (FDNPP). Emission rates can be reconstructed sequentially with the progression of a nuclear accident, which is important in the response to a nuclear emergency. With pseudo observations generated continuously, most of the emission rates were estimated accurately, except under conditions when the wind blew off land toward the sea and at extremely slow wind speeds near the FDNPP. Because of the long duration of accidents and variability in meteorological fields, monitoring networks composed of land stations only in a local area are unable to provide enough information to support an emergency response. The errors in the estimation compared to the real observations from the FDNPP nuclear accident stemmed from a shortage of observations, lack of data control, and an inadequate atmospheric dispersion model without improvement and appropriate meteorological data. The proposed method should be developed further to meet the requirements of a nuclear emergency response.

Source apportionment of speciated PM10 in the United Kingdom in 2008: Episodes and annual averages

The Lagrangian atmospheric dispersion model NAME (Numerical Atmospheric-dispersion Modelling Environment), has been used to simulate the formation and transport of PM10 over North-West Europe in 2008. The model has been evaluated against UK measurement data and been shown to adequately represent the observed PM10 at rural and urban sites on a daily basis. The Lagrangian nature of the model allows information on the origin of pollutants (and hence their secondary products) to be retained to allow attribution of pollutants at receptor sites back to their sources. This source apportionment technique has been employed to determine whether the different components of the modelled PM10 have originated from UK, shipping, European (excluding the UK) or background sources. For the first time this has been done to evaluate the composition during periods of elevated PM10 as well as the annual average composition. The episode data were determined by selecting the model data for each hour when the corresponding measurement data was >50 μg/m3. All the modelled sites show an increase in European pollution contribution and a decrease in the background contribution in the episode case compared to the annual average. The European contribution is greatest in southern and eastern parts of the UK and decreases moving northwards and westwards. Analysis of the speciated attribution data over the selected sites reveals that for 2008, as an annual average, the top three contributors to total PM10 are UK primary PM10 (17–25%), UK origin nitrate aerosol (18–21%) and background PM10 (11–16%). Under episode conditions the top three contributors to modelled PM10 are UK origin nitrate aerosol (12–33%), European origin nitrate aerosol (11–19%) and UK primary PM10 (12–18%).

Measurement of ammonia emissions from temperate and sub-polar seabird colonies

The chemical breakdown of marine derived reactive nitrogen transported to the land as seabird guano represents a significant source of ammonia (NH3) in areas far from other NH3 sources. Measurements made at tropical and temperate seabird colonies indicate substantial NH3 emissions, with emission rates larger than many anthropogenic point sources. However, several studies indicate that thermodynamic processes limit the amount of NH3 emitted from guano, suggesting that the percentage of guano volatilizing as NH3 may be considerably lower in colder climates. This study undertook high resolution temporal ammonia measurements in the field and coupled results with modelling to estimate NH3 emissions at a temperate puffin colony and two sub-polar penguin colonies (Signy Island, South Orkney Islands and Bird Island, South Georgia) during the breeding season. These emission rates are then compared with NH3 volatilization rates from other climates. Ammonia emissions were calculated using a Lagrangian atmospheric dispersion model, resulting in mean emissions of 5 μg m−2 s−1 at the Isle of May, 12 μg m−2 s−1 at Signy Island and 9 μg m−2 s−1 at Bird Island. The estimated percentage of total guano nitrogen volatilized was 5% on the Isle of May, 3% on Signy and 2% on Bird Island. These values are much smaller than the percentage of guano nitrogen volatilized in tropical contexts (31–65%). The study confirmed temperature, wind speed and water availability have a significant influence on the magnitude of NH3 emissions, which has implications for reactive nitrogen in both modern remote regions and pre-industrial atmospheric composition and ecosystem interactions.

Global Lagrangian Atmospheric Dispersion Model

The Global Lagrangian Atmospheric Dispersion Model (GLADIM) is described. GLADIM is based on the global trajectory model, which had been developed earlier and uses fields of weather parameters from different atmospheric reanalysis centers for calculations of trajectories of air mass that include trace gases. GLADIM includes the parameterization of turbulent diffusion and allows the forward calculation of concentrations of atmospheric tracers at nodes of a global regular grid when a source is specified. Thus, GLADIM can be used for the forward simulation of pollutant propagation (volcanic ash, radionuclides, and so on). Working in the reverse direction, GLADIM allows the detection of remote sources that mainly contribute to the tracer concentration at an observation point. This property of Lagrangian models is widely used for data analysis and the reverse modeling of emission sources of a pollutant specified. In this work we describe the model and some results of its validation through a comparison with results of a similar model and observation data.

Ocean versus atmosphere control on western European wintertime temperature variability

Using a novel Lagrangian approach, we assess the relative roles of the atmosphere and ocean in setting interannual variability in western European wintertime temperatures. We compute sensible and latent heat fluxes along atmospheric particle trajectories backtracked in time from four western European cities, using a Lagrangian atmospheric dispersion model driven with meteorological reanalysis data. The material time rate of change in potential temperature and the surface turbulent fluxes computed along the trajectory show a high degree of correlation, revealing a dominant control of ocean–atmosphere heat and moisture exchange in setting heat flux variability for atmospheric particles en route to western Europe. We conduct six idealised simulations in which one or more aspects of the climate system is held constant at climatological values and these idealised simulations are compared with a control simulation, in which all components of the climate system vary realistically. The results from these idealised simulations suggest that knowledge of atmospheric pathways is essential for reconstructing the interannual variability in heat flux and western European wintertime temperature, and that variability in these trajectories alone is sufficient to explain at least half of the internannual flux variability. Our idealised simulations also expose an important role for sea surface temperature in setting decadal scale variability of air–sea heat fluxes along the Lagrangian pathways. These results are consistent with previous studies showing that air–sea heat flux variability is driven by the atmosphere on interannual time scales over much of the North Atlantic, whereas the SST plays a leading role on longer time scales. Of particular interest is that the atmospheric control holds for the integrated fluxes along 10-day back trajectories from western Europe on an interannual time scale, despite that many of these trajectories pass over the Gulf Stream and its North Atlantic Current extension, regions where ocean dynamics influence air–sea heat exchange even on a very short time scale.

Analysis of UK and European NOx and VOC emission scenarios in the Defra model intercomparison exercise

Simple emission scenarios have been implemented in eight United Kingdom air quality models with the aim of assessing how these models compared when addressing whether photochemical ozone formation in southern England was NOx- or VOC-sensitive and whether ozone precursor sources in the UK or in the Rest of Europe (RoE) were the most important during July 2006. The suite of models included three Eulerian-grid models (three implementations of one of these models), a Lagrangian atmospheric dispersion model and two moving box air parcel models. The assignments as to NOx- or VOC-sensitive and to UK- versus RoE-dominant, turned out to be highly variable and often contradictory between the individual models. However, when the assignments were filtered by model performance on each day, many of the contradictions could be eliminated. Nevertheless, no one model was found to be the 'best' model on all days, indicating that no single air quality model could currently be relied upon to inform policymakers robustly in terms of NOx- versus VOC-sensitivity and UK- versus RoE-dominance on each day. It is important to maintain a diversity in model approaches.

Measurement of ammonia emissions from tropical seabird colonies

The excreta (guano) of seabirds at their breeding colonies represents a notable source of ammonia (NH3) emission to the atmosphere, with effects on surrounding ecosystems through nitrogen compounds being thereby transported from sea to land. Previous measurements in temperate UK conditions quantified emission hotspots and allowed preliminary global upscaling. However, thermodynamic processes and water availability limit NH3 formation from guano, which suggests that the proportion of excreted nitrogen that volatilizes as NH3 may potentially be higher at tropical seabird colonies than similar colonies in temperate or sub-polar regions. To investigate such differences, we measured NH3 concentrations and environmental conditions at two tropical seabird colonies during the breeding season: a colony of 20,000 tern spp. and noddies on Michaelmas Cay, Great Barrier Reef, and a colony of 200,000 Sooty terns on Ascension Island, Atlantic Ocean. At both sites time-integrated NH3 concentrations and meteorological parameters were measured. In addition, at Ascension Island, semi-continuous hourly NH3 concentrations and micrometeorological parameters were measured throughout the campaign. Ammonia emissions, quantified using a backwards Lagrangian atmospheric dispersion model, were estimated at 21.8 μg m−2 s−1 and 18.9 μg m−2 s−1 from Michaelmas Cay and Ascension Island, respectively. High temporal resolution NH3 data at Ascension Island estimated peak hourly emissions up to 377 μg NH3 m2 s−1. The estimated percentage fraction of total guano nitrogen volatilized was 67% at Michaelmas Cay and 32% at Ascension Island, with the larger value at the former site attributed to higher water availability. These values are much larger than published data for sub-polar locations, pointing to a substantial climatic dependence on emission of atmospheric NH3 from seabird colonies.

Validation of a Lagrangian atmospheric dispersion model against middle-range scale measurements of 85Kr concentration in Japan

The Lagrangian atmospheric dispersion model of the computer-based nuclear emergency response system WSPEEDI-II was validated with the measured 85Kr concentrations in tens-of- to hundreds-of-km (middle-range) scale area by conducting dispersion simulations using the release rate from the nuclear fuel reprocessing plant in Rokkasho, Japan. The calculated weekly concentrations of 85Kr in two simulation cases during April and September in 2008 agreed with the measurements within a factor of two at the sampling sites 170 to 2000 km away from the plant. However, the sensitivity analysis of horizontal grid resolution of the meteorological model ranging from 2 to 54 km showed that the calculated results had the dependency on the grid resolution, i.e., the calculated concentrations became low compared with the results with the grid resolution of 54 km as the grid resolution became high. An empirical modification of the horizontal diffusion parameter used for long-range dispersions by WSPEEDI-II was attempted based on the sensitivity analysis to reduce the redundant diffusion effect in dispersion simulations with relatively high grid resolution. The modified horizontal diffusion parameter contributed to reduce the dependency of calculated concentrations on the horizontal grid resolution.

Parallelisation of the Lagrangian atmospheric dispersion model NAME

The NAME Atmospheric Dispersion Model is a Lagrangian particle model used by the Met Office to predict the propagation and spread of pollutants in the atmosphere. The model is routinely used in emergency response applications, where it is important to obtain results as quickly as possible. This requirement for a short runtime and the increase in core number of commonly available CPUs, such as the Intel Xeon series, has motivated the parallelisation of NAME in the OpenMP shared memory framework. In this work we describe the implementation of this parallelisation strategy in NAME and discuss the performance of the model for different setups. Due to the independence of the model particles, the parallelisation of the main compute intensive loops is relatively straightforward. The random number generator for modelling sub-grid scale turbulent motion needs to be adapted to ensure that different particles use independent sets of random numbers. We find that on Intel Xeon X5680 CPUs the model shows very good strong scaling up to 12 cores in a realistic emergency response application for predicting the dispersion of volcanic ash in the North Atlantic airspace. We implemented a mechanism for asynchronous reading of meteorological data from disk and demonstrate how this can reduce the runtime if disk access plays a significant role in a model run. To explore the performance on different chip architectures we also ported the part of the code which is used for calculating the gamma dose from a cloud of radioactive particles to a graphics processing unit (GPU) using CUDA-C. We were able to demonstrate a significant speedup of around one order of magnitude relative to the serial CPU version.

Modelling secondary organic aerosol in the United Kingdom

The Lagrangian atmospheric dispersion model, NAME, has been used to model the formation and transport of anthropogenic and biogenic secondary organic aerosol (SOA) over North-West Europe in 2008. The model has been tested against daily organic carbon measurements at Harwell, a rural site in southern UK, where it was able to represent adequately the observed values in summer, with some under-prediction in winter. The model has been used to look at the contribution of SOA to total measured PM10 at four selected UK sites. The site with the greatest contribution (32%) of SOA to PM10 was Auchencorth, a rural site in Scotland and least (9%) at London Bloomsbury. The biogenic SOA (BSOA) dominated over the anthropogenic SOA (ASOA) in the UK and showed a strong seasonal cycle peaking in the summer. There was also a slight summer increase in ASOA. The model has been employed to provide source attribution between UK sources and sources in the rest of Europe. The contribution from Europe was generally small but varied considerably due to meteorology. The UK component showed a seasonal cycle, peaking in the summer months. On an annual basis, considering the four measurement sites, the percentage of SOA arriving from outside the UK was least at Auchencorth (9.8%) and most at London (28.4%). Total modelled SOA had a maximum contribution of 2–3 μg m−3 as a monthly average. (It should be noted that in addition there will be a small contribution from background SOA to these figures.) Emission sensitivity studies revealed that the response of ASOA was highly non-linear, showing both positive and negative responses to a 30% reduction in all man-made NOx sources and the response was greater than 1:1 to a 30% reduction in all man-made VOC sources. BSOA showed only a small negative response to a 30% NOx reduction and no change to a 30% VOC reduction.

Validation of Real Time Dispersion of Tritium over the Western Mediterranean Basin in Different Assessments

Real time Tritium concentrations in air coming from an ITER-like reactor as source were coupled the European Centre Medium Range Weather Forecast (ECMWF) numerical model with the lagrangian atmospheric dispersion model FLEXPART. This tool ECMWF/FLEXPART was analyzed in normal operating conditions in the Western Mediterranean Basin during 45 days at summer 2010. From comparison with NORMTRI plumes over Western Mediterranean Basin the real time results have demonstrated an overestimation of the corresponding climatologically sequence Tritium concentrations in air outputs, at several distances from the reactor. For these purpose two clouds development patterns were established. The first one was following a cyclonic circulation over the Mediterranean Sea and the second one was based in the cloud delivered over the Interior of the Iberian Peninsula by another stabilized circulation corresponding to a High. One of the important remaining activities defined then, was the tool qualification. The aim of this paper is to present the ECMWF/FLEXPART products confronted with Tritium concentration in air data. For this purpose a database to develop and validate ECMWF/FLEXPART tritium in both assessments has been selected from a NORMTRI run. Similarities and differences, underestimation and overestimation with NORMTRI will allowfor refinement in some features of ECMWF/FLEXPART.

Radiation source rate estimation through data assimilation of gamma dose rate measurements for operational nuclear emergency response systems

This paper presents an evaluation of an innovative data assimilation method that has been recently developed in NCSR Demokritos for estimating an unknown emission rate of radionuclides in the atmosphere, with real-scale experimental data. The efficient algorithm is based on the assimilation of gamma dose rate measured data in the Lagrangian atmospheric dispersion model DIPCOT and uses variational principles. The DIPCOT model is used in the framework of the nuclear emergency response system (ERS) RODOS. The evaluation is performed by computational simulations of dispersion of Ar-41 that was emitted routinely by the Australian Nuclear Science and Technology Organisation’s (ANSTO) previous research reactor, HIFAR, located in Sydney, Australia. In this paper the algorithm is evaluated against a more complicated case than the others used in previous studies: There was only one monitoring station available each day and the site topography is characterised as moderately complex. Overall the estimated release rate approaches the real one to a very satisfactory degree as revealed by the statistical indicators of errors.

Consequences of Different Meteorological Scenarios in the Environmental Impact Assessment of Tritium Release

The environmental impact of systems managing large (kg) tritium amount represents a public scrutiny issue for the next coming fusion facilities as ITER and DEMO. Furthermore, potentially new dose limits imposed by international regulations (ICRP) shall impact next coming devices designs and the overall costs of fusion technology deployment. Refined environmental tritium dose impact assessment schemes are then overwhelming. Detailed assessments can be procured from the knowledge of the real boundary conditions of the primary tritium discharge phase into atmosphere (low levels) and into soils. Lagrangian dispersion models using real-time meteorological and topographic data provide a strong refinement. Advance simulation tools are being developed in this sense. The tool integrates a numerical model output records from European Centre for Medium range Weather Forecast (ECMWF) with a lagrangian atmospheric dispersion model (FLEXPART). The composite model ECMWF/FLEXTRA results can be coupled with tritium dose secondary phase pathway assessment tools. Nominal tritium discharge operational reference and selected incidental ITER-like plant systems tritium form source terms have been assumed. The real-time daily data and mesh-refined records together with lagrangian dispersion model approach provide accurate results for doses to population by inhalation or ingestion in the secondary phase.

Emission rate estimation through data assimilation of gamma dose measurements in a Lagrangian atmospheric dispersion model

This paper presents an efficient algorithm for estimating the unknown emission rate of radionuclides in the atmosphere following a nuclear accident. The algorithm is based on assimilation of gamma dose rate measured data in a Lagrangian atmospheric dispersion model. Such models are used in the framework of nuclear emergency response systems (ERSs). It is shown that the algorithm is applicable in both deterministic and stochastic modes of operation of the dispersion model. The method is evaluated by computational simulations of a 3-d field experiment on atmospheric dispersion of ⁴¹Ar emitted routinely from a research reactor. Available measurements of fluence rate (photons flux) in air are assimilated in the Lagrangian dispersion model DIPCOT and the ⁴¹Ar emission rate is estimated. The statistical analysis shows that the model-calculated emission rates agree well with the real ones. In addition the model-predicted fluence rates at the locations of the sensors, which were not used in the data assimilation procedure are in better agreement with the measurements. The first evaluation results of the method presented in this study show that the method performs satisfactorily and therefore it is applicable in nuclear ERSs provided that more comprehensive validation studies will be performed.