Transport Model Predictions Research Articles

Bayesian Maximum Entropy Integration of Ozone Observations and Model Predictions: A National Application.

To improve ozone exposure estimates for ambient concentrations at a national scale, we introduce our novel Regionalized Air Quality Model Performance (RAMP) approach to integrate chemical transport model (CTM) predictions with the available ozone observations using the Bayesian Maximum Entropy (BME) framework. The framework models the nonlinear and nonhomoscedastic relation between air pollution observations and CTM predictions and for the first time accounts for variability in CTM model performance. A validation analysis using only noncollocated data outside of a validation radius rv was performed and the R(2) between observations and re-estimated values for two daily metrics, the daily maximum 8-h average (DM8A) and the daily 24-h average (D24A) ozone concentrations, were obtained with the OBS scenario using ozone observations only in contrast with the RAMP and a Constant Air Quality Model Performance (CAMP) scenarios. We show that, by accounting for the spatial and temporal variability in model performance, our novel RAMP approach is able to extract more information in terms of R(2) increase percentage, with over 12 times for the DM8A and over 3.5 times for the D24A ozone concentrations, from CTM predictions than the CAMP approach assuming that model performance does not change across space and time.

The impact of energy conservation in transport models on the π−/π+ multiplicity ratio in heavy-ion collisions and the symmetry energy

The charged pion multiplicity ratio in intermediate energy central heavy-ion collisions has been proposed as a suitable observable to constrain the high density dependence of the isovector part of the equation of state. A comparison of various transport model predictions with existing experimental data has led, however, to contradictory results. Using an upgraded version of the Tübingen QMD transport model, which allows the conservation of energy at a local or global level by accounting for the potential energy of hadrons in two-body collisions and leading thus to particle production threshold shifts, we demonstrate that compatible constraints for the symmetry energy stiffness can be extracted from pion multiplicity and elliptic flow observables. However, pion multiplicities and ratios are proven to be highly sensitive to the yet unknown isovector part of the in-medium Δ(1232) potential which hinders, at present, the extraction of meaningful information on the high density dependence of the symmetry energy. A solution to this problem together with the inclusion of contributions presently neglected, such as in-medium pion potentials and retardation effects, are needed for a final verdict on this topic.

Hydrodynamic and Sediment Modelling within a Macro Tidal Estuary: Port Curtis Estuary, Australia

An understanding of sediment transport processes and resultant concentration dynamics in estuaries is of great importance to engineering design awareness and the management of these environments. Predictive modelling approaches provide an opportunity to investigate and address potential system responses to nominated events, changes, or conditions of interest, often on high temporal and spatial resolution scales. In this study, a three-dimensional hydrodynamic model and wave model were validated and applied to generate forcing conditions for input into a sediment transport model for the period 7 May 2010–30 October 2010 within a macro tidal estuary, Port Curtis estuary (Australia). The hydrodynamic model was verified against surface and near-bottom current measurements. The model accurately reproduced the variations of surface and near-bottom currents at both a mid-estuary and upper-estuary location. Sediment transport model predictions were performed under varying meteorological conditions and tidal forcing over a 180-day period and were validated against turbidity data collected at six stations within Port Curtis estuary. The sediment transport model was able to predict both the magnitudes of the turbidity levels and the modulation induced by the neap and spring tides and wind-wave variations. The model-predicted (converted) turbidity levels compared favourably with the measured surface water turbidity levels at all six stations. The study results have useful practical application for Port Curtis estuary, including providing predictive capabilities to support the selection of locations for monitoring/compliance sites.

A Comparative Analysis of Turbulence Models Utilised for the Prediction of Turbulent Airflow through a Sudden Expansion

The turbulent airflow in a circular duct with sudden expansion was investigated utilizing three turbulence models. The turbulence models chosen are: the k-epsilon model, the shear stress transport model and the Reynolds-stress model. The performance of the models was investigated with respect to the flow parameter-recirculation length. The turbulent kinetic energy and velocity predictions were compared between the turbulence models and with experimental data, then interpreted on the basis of the recirculation length. From the results, the shear stress transport model predictions of recirculation length had the closest agreement with the experimental result compared to the other model. Likewise, the convergence rate for the shear stress transport model was reasonable compared to that of the Reynolds model which has the slowest convergence rate. In light of these findings, the shear stress transport model was discovered to be the most appropriate for the investigation of turbulent air flow in a circular duct with sudden expansion. Keywords: Turbulence, recirculation length, sudden expansion, Turbulence models.

Characterization of forest fire smoke event near Washington, DC in summer 2013 with multi-wavelength lidar

Abstract. The multi-wavelength lidar technique was applied to the study of a smoke event near Washington, DC on 26–28 August 2013. Satellite observations combined with transport model predictions imply that the smoke plume originated mainly from Wyoming/Idaho forest fires and its transportation to Washington, DC took approximately 5 days. The NASA Goddard Space Flight Center (GSFC) multi-wavelength Mie–Raman lidar was used to measure the smoke particle intensive parameters such as extinction and backscatter Ångström exponents together with lidar ratios at 355 and 532 nm wavelengths. For interpretation of the observed vertical profiles of the backscatter Ångström exponents γβ at 355–532 and 532–1064 nm, numerical simulation was performed. The results indicate that, for fine-mode dominant aerosols, the Ångström exponents γβ(355–532) and γβ(532–1064) have essentially different dependence on the particle size and refractive index. Inversion of 3 β + 2 α lidar observations on 27–28 August provided vertical variation of the particle volume, effective radius and the real part of the refractive index through the planetary boundary layer (PBL) and the smoke layer. The particle effective radius decreased with height from approximately 0.27 μm inside the PBL to 0.15 μm in the smoke layer, which was situated above the PBL. Simultaneously the real part of the refractive index in the smoke layer increased to mR ≈ 1.5. The retrievals demonstrate also that the fine mode is predominant in the particle size distribution, and that the decrease of the effective radius with height is due to a shift of the fine mode toward smaller radii.

Azimuthal emission patterns ofK+and ofK−mesons in Ni + Ni collisions near the strangeness production threshold

Azimuthal emission patterns of $K^\pm$ mesons have been measured in Ni + Ni collisions with the FOPI spectrometer at a beam kinetic energy of 1.91 A GeV. The transverse momentum $p_{T}$ integrated directed and elliptic flow of $K^{+}$ and $K^{-}$ mesons as well as the centrality dependence of $p_{T}$ - differential directed flow of $K^{+}$ mesons are compared to the predictions of HSD and IQMD transport models. The data exhibits different propagation patterns of $K^{+}$ and $K^{-}$ mesons in the compressed and heated nuclear medium and favor the existence of a kaon-nucleon in-medium potential, repulsive for $K^{+}$ mesons and attractive for $K^{-}$ mesons.

Lessons Learned from Sediment Transport Model Predictions and Long-Term Postremoval Monitoring: Marmot Dam Removal Project on the Sandy River in Oregon

AbstractThe 14-m-tall Marmot Dam was removed during the summer of 2007, and the cofferdam protecting the working area was breached during a storm on October 19, 2007, allowing approximately 750,000 m3 of reservoir deposit to be eroded freely and released downstream to the Sandy River. Prior to the Marmot Dam removal, sediment transport models were developed to predict the transport dynamics of both gravel and sand, providing key pieces of information for stakeholders and regulatory agencies to select the most appropriate dam removal alternative. A monitoring program was implemented following dam removal that was designed to examine model predictions and assess when potential fish passage issues related to dam removal were no longer of concern. Comparisons of model predictions with field observations indicate that the model successfully predicted the erosion of the impoundment deposit, the deposition of sediment in a short reach downstream of the dam, and the lack of deposition in the majority of the Sand...

Seasonal variations in Pluto’s atmospheric tides

Pluto’s tenuous atmosphere exhibits remarkable seasonal change as a result of the planet’s substantial obliquity and highly eccentric orbit. Over the past two decades, occultations have revealed that the atmospheric pressure on Pluto has increased substantially, perhaps by a factor as large as 2 to 4, as the planet has moved from equinox towards solstice conditions. These data have also shown variations in the strength of the dynamical activity in the atmosphere, as revealed by the varying abundance and amplitude of spikes in the occultation light curves resulting from refractive focussing by atmospheric waves. Toigo et al. (Toigo et al. [2010]. Icarus, 208, 402–411) explored the possibility that these waves are caused by solar-induced sublimation and diurnal deposition from N2 frost patches, driven by weak vertical winds resulting from the rising and sinking gas as it is released from or deposited onto the surface. Here, we extend this model to account explicitly for seasonal variations in average insolation and for the significant damping of vertical wave propagation by kinematic viscosity and thermal diffusivity (Hubbard et al. [2009]. Icarus, 204, 284–289). Damping is extremely effective in suppressing vertical propagation of waves with vertical wavelengths of a few kilometers or less, and the dominant surviving tidal modes have characteristic vertical wavelengths λ∼10–13km. We estimate the expected strength and regional characteristics of atmospheric tides over the course of Pluto’s orbit for a variety of assumed spatial distributions of surface frost and atmospheric surface pressure. We compute the predicted strength of tide-induced wave activity based on the actual frost distribution observed on Pluto from Hubble Space Telescope (HST) observations (Stern et al. [1997]. Astron. J., 113, 827; Buie et al. [2010]. Astron. J., 139, 1128–1143), and compare the results to calculations for volatile transport models of Young (Young [2013]. Astrophys. J., 766, L22) and Hansen et al. (Hansen et al. [2015]. Icarus, 246, 183–191). We develop simple scaling rules to estimate the variation of the strength of tidal activity with surface pressure PS and solar declination δ⊙, and show that the maximum expected temperature perturbation at an atmospheric pressure of P=0.1Pa scales as dTmax∝cosδ⊙/PS. Wave activity is strongest in the near-equatorial region (latitude|ϕ|≲30°), being only weakly dependent on the detailed frost distribution. Using a 3-D time-dependent geometric optics ray-tracing code, we compute model light curves for the geometric circumstances of three high-SNR occultations (2002 August 21, 2006 June 12, and 2012 July 18), taking into account the detailed three-dimensional characteristics of the tides as different regions of the atmosphere are probed over the course of each occultation chord. We compare the strength and abundance of the scintillations in the models with those seen in the data, using both the HST frost maps and the volatile transport model predictions. The striking asymmetries in the strengths of spikes between ingress and egress seen in some events are reproduced in the tidal model simulations, due primarily to the latitudes probed during the occultation: occultations at high northern or southern latitudes uniformly have much weaker wave activity than more equatorial events. A surface pressure range of PS=1–2Pa provides the best match between models and observations. With the impending arrival of the New Horizons spacecraft at Pluto in 2015, we predict that wave activity in the upper atmosphere will be strongest at equatorial regions, and controlled in amplitude primarily by the surface pressure and damping effects, rather than by the detailed frost distribution. If Pluto’s atmosphere begins to collapse in the coming decades, we expect that future stellar occultations will provide evidence for greatly enhanced atmospheric wave activity.

A comparison between the diffusion–reaction and slow axonal transport models for predicting tau distribution along an axon

This paper developed equations describing steady-state tau distributions for three versions of the diffusion-reaction model of tau transport: a model with constant kinetic rates, a model that additionally accounts for tau diffusion along microtubules (MTs) and a model with a modulated rate of tau attachment to MTs. We demonstrated that, for the model with constant kinetic rates, the concentration of free tau in the cytoplasm was determined by a single dimensionless parameter that represents the ratio of the diffusion time (the time it takes tau to diffuse from the axon hillock to the axon tip) to the half-life of tau. We also developed a model based on the hypothesis that tau is actively transported. Analytical solutions for some special situations were obtained. The model predictions were compared with experimentally measured tau distributions in axons reported in Black et al. (1996, J. Neurosc., 16: , 3601-3619), and based on these comparisons, we discussed the performance of various models. We demonstrated the significance of modulation of the tau attachment rate to MTs in the diffusion-reaction model. On the other hand, the active transport model predictions were consistent with experimental data even with constant kinetic rates. For short axons (up to 600 μm in length) the predicted average transport velocity of tau was in the experimentally reported range for both the diffusion-reaction and active transport models, but for the active transport model the average tau velocity was larger.

Flow probe of symmetry energy in relativistic heavy-ion reactions

Flow observables in heavy-ion reactions at incident energies up to about 1 GeV per nucleon have been shown to be very useful for investigating the reaction dynamics and for determining the parameters of reaction models based on transport theory. In particular, the elliptic flow in collisions of neutron-rich heavy-ion systems emerges as an observable sensitive to the strength of the symmetry energy at supra-saturation densities. The comparison of ratios or differences of neutron and proton flows or neutron and hydrogen flows with predictions of transport models favors an approximately linear density dependence, consistent with ab-initio nuclear-matter theories. Extensive parameter searches have shown that the model dependence is comparable to the uncertainties of existing experimental data. Comprehensive new flow data of high accuracy, partly also through providing stronger constraints on model parameters, can thus be expected to improve our knowledge of the equation of state of asymmetric nuclear matter.

Complex step-based low-rank extended Kalman filtering for state-parameter estimation in subsurface transport models

Summary The accuracy of groundwater flow and transport model predictions highly depends on our knowledge of subsurface physical parameters. Assimilation of contaminant concentration data from shallow dug wells could help improving model behavior, eventually resulting in better forecasts. In this paper, we propose a joint state-parameter estimation scheme which efficiently integrates a low-rank extended Kalman filtering technique, namely the Singular Evolutive Extended Kalman (SEEK) filter, with the prominent complex-step method (CSM). The SEEK filter avoids the prohibitive computational burden of the Extended Kalman filter by updating the forecast along the directions of error growth only, called filter correction directions. CSM is used within the SEEK filter to efficiently compute model derivatives with respect to the state and parameters along the filter correction directions. CSM is derived using complex Taylor expansion and is second order accurate. It is proven to guarantee accurate gradient computations with zero numerical round-off errors, but requires complexifying the numerical code. We perform twin-experiments to test the performance of the CSM-based SEEK for estimating the state and parameters of a subsurface contaminant transport model. We compare the efficiency and the accuracy of the proposed scheme with two standard finite difference-based SEEK filters as well as with the ensemble Kalman filter (EnKF). Assimilation results suggest that the use of the CSM in the context of the SEEK filter may provide up to 80% more accurate solutions when compared to standard finite difference schemes and is competitive with the EnKF, even providing more accurate results in certain situations. We analyze the results based on two different observation strategies. We also discuss the complexification of the numerical code and show that this could be efficiently implemented in the context of subsurface flow models.

Anisokinetic Shrouded Nozzle System for Constant Low-Flow Rate Aerosol Sampling from Turbulent Duct Flow

An anisokinetic shrouded nozzle system was designed for sampling particles at a constant low flow rate from a ventilation duct to an aerodynamic particle sizer (APS). Shrouded anisokinetic nozzles are a means for sampling from a moving airstream with higher particle transmission than with unshrouded isokinetic nozzles. This shrouded nozzle sampling system was evaluated in an experimental ventilation duct system. Aspiration and transport efficiency measurements were made for five particle sizes in the range 1–13 μm at each of three duct air speeds in the range 2.2–8.8 m/s. Under these conditions, the shrouded nozzle system showed improved performance compared to buttonhook isokinetic nozzles, especially for larger particles and higher air speeds. Measured transmission efficiencies through the shrouded nozzle sampling system were generally higher and more reliably predictable than those through buttonhook isokinetic nozzles. Model predictions of transport and aspiration efficiencies of the shrouded nozzle s...

A multitower measurement network estimate of California's methane emissions

AbstractWe present an analysis of methane (CH4) emissions using atmospheric observations from five sites in California's Central Valley across different seasons (September 2010 to June 2011). CH4 emissions for spatial regions and source sectors are estimated by comparing measured CH4 mixing ratios with transport model (Weather Research and Forecasting and Stochastic Time‐Inverted Lagrangian Transport) predictions based on two 0.1° CH4 (seasonally varying “California‐specific” (California Greenhouse Gas Emission Measurements, CALGEM) and a static global (Emission Database for Global Atmospheric Research, release version 42, EDGAR42)) prior emission models. Region‐specific Bayesian analyses indicate that for California's Central Valley, the CALGEM‐ and EDGAR42‐based inversions provide consistent annual total CH4 emissions (32.87 ± 2.09 versus 31.60 ± 2.17 Tg CO2eq yr−1; 68% confidence interval (CI), assuming uncorrelated errors between regions). Summing across all regions of California, optimized CH4 emissions are only marginally consistent between CALGEM‐ and EDGAR42‐based inversions (48.35 ± 6.47 versus 64.97 ± 11.85 Tg CO2eq), because emissions from coastal urban regions (where landfill and natural gas emissions are much higher in EDGAR than CALGEM) are not strongly constrained by the measurements. Combining our results with those from a recent study of the South Coast Air Basin narrows the range of estimates to 43–57 Tg CO2eq yr−1 (1.3–1.8 times higher than the current state inventory). These results suggest that the combination of rural and urban measurements will be necessary to verify future changes in California's total CH4 emissions.

Diurnal tracking of anthropogenic CO<sub>2</sub> emissions in the Los Angeles basin megacity during spring 2010

Abstract. Attributing observed CO2 variations to human or natural cause is critical to deducing and tracking emissions from observations. We have used in situ CO2, CO, and planetary boundary layer height (PBLH) measurements recorded during the CalNex-LA (CARB et al., 2008) ground campaign of 15 May–15 June 2010, in Pasadena, CA, to deduce the diurnally varying anthropogenic component of observed CO2 in the megacity of Los Angeles (LA). This affordable and simple technique, validated by carbon isotope observations and WRF-STILT (Weather Research and Forecasting model – Stochastic Time-Inverted Lagrangian Transport model) predictions, is shown to robustly attribute observed CO2 variation to anthropogenic or biogenic origin over the entire diurnal cycle. During CalNex-LA, local fossil fuel combustion contributed up to ~50% of the observed CO2 enhancement overnight, and ~100% of the enhancement near midday. This suggests that sufficiently accurate total column CO2 observations recorded near midday, such as those from the GOSAT or OCO-2 satellites, can potentially be used to track anthropogenic emissions from the LA megacity.

Erosion source discrimination in a rural Australian catchment using compound‐specific isotope analysis (CSIA)

AbstractCompound‐specific isotope analysis (CSIA) has been used to assess the ability of δ13C signatures of fatty acid compounds to discriminate erosion sources in a rural Australian catchment. The study focussed on a high flow event (10‐year recurrence interval) which occurred in the Logan–Albert catchment in January 2008, and augmented a previous sediment tracing study using fallout radionuclides and major/minor element geochemistry. It is found that surface soil from forest, pasture and cultivated land uses are well discriminated using CSIA. Furthermore, sub‐surface soil sources associated with channel bank erosion and exposed subsoils (gullies and hillslope scalds) occurring specifically in the mid‐western Logan catchment could also be discriminated. Selected fatty acid and bulk carbon δ13C data were used in the IsoSource mixing model to determine erosion sources contributing sediment. The results were compared with results obtained using other sediment tracers. For the lower Logan River, the CSIA tracing results are consistent with fallout radionuclide and element geochemistry tracing, with channel bank erosion being confirmed as the major sediment source. Moreover, CSIA has quantified the significant contribution of exposed subsoils originating on hillslopes and drainage lines from the mid‐western region of the Logan catchment. In the Albert River catchment, about 40% of sediment comes from forest land use, although more than half of this may come from sub‐surface sources. These results have demonstrated that CSIA has the potential to significantly enhance the ability of sediment tracing studies to determine the extent that different land uses and erosion processes are contributing eroded soil to rivers, allowing an assessment of soil erosion and transport model predictions. Copyright © 2012 John Wiley & Sons, Ltd.

Evaluation of chemical transport model predictions of primary organic aerosol for air masses classified by particle component-based factor analysis

Abstract. Observations from the 2007 Border Air Quality and Meteorology Study (BAQS-Met 2007) in Southern Ontario, Canada, were used to evaluate predictions of primary organic aerosol (POA) and two other carbonaceous species, black carbon (BC) and carbon monoxide (CO), made for this summertime period by Environment Canada's AURAMS regional chemical transport model. Particle component-based factor analysis was applied to aerosol mass spectrometer measurements made at one urban site (Windsor, ON) and two rural sites (Harrow and Bear Creek, ON) to derive hydrocarbon-like organic aerosol (HOA) factors. A novel diagnostic model evaluation was performed by investigating model POA bias as a function of HOA mass concentration and indicator ratios (e.g. BC/HOA). Eight case studies were selected based on factor analysis and back trajectories to help classify model bias for certain POA source types. By considering model POA bias in relation to co-located BC and CO biases, a plausible story is developed that explains the model biases for all three species. At the rural sites, daytime mean PM1 POA mass concentrations were under-predicted compared to observed HOA concentrations. POA under-predictions were accentuated when the transport arriving at the rural sites was from the Detroit/Windsor urban complex and for short-term periods of biomass burning influence. Interestingly, the daytime CO concentrations were only slightly under-predicted at both rural sites, whereas CO was over-predicted at the urban Windsor site with a normalized mean bias of 134%, while good agreement was observed at Windsor for the comparison of daytime PM1 POA and HOA mean values, 1.1 μg m−3 and 1.2 μg m−3, respectively. Biases in model POA predictions also trended from positive to negative with increasing HOA values. Periods of POA over-prediction were most evident at the urban site on calm nights due to an overly-stable model surface layer. This model behaviour can be explained by a combination of model under-estimation of vertical mixing at the urban location, under-representation of PM emissions for on-road traffic exhaust along major urban roads and highways, and a more structured allocation of area POA sources such as food cooking and dust emissions to urban locations. A downward trend in POA bias was also observed at the urban site as a function of the BC/HOA indicator ratio, suggesting a possible association of POA under-prediction with under-representation of diesel combustion sources. An investigation of the emission inventories for the province of Ontario and the nearby US state of Indiana also suggested that the top POA area emission sources (food cooking, organic-bound to dust, waste disposal burning) dominated over mobile and point sources, again consistent with a mobile under-estimation. We conclude that more effort should be placed at reducing uncertainties in the treatment of several large POA emission sources, in particular food cooking, fugitive dust, waste disposal burning, and on-road traffic sources, and especially their spatial surrogates and temporal profiles. This includes using higher spatial resolution model grids to better resolve the urban road network and urban food cooking locations. We also recommend that additional sources of urban-scale vertical mixing in the model, such as a stronger urban heat island effect and vehicle-induced turbulence, would help model predictions at urban locations, especially at night time.

Seasonal variations in N2O emissions from central California

We estimate nitrous oxide (N2O) emissions from Central California for the period of December 2007 through November 2009 by comparing N2O mixing ratios measured at a tall tower (Walnut Grove, WGC) with transport model predictions based on two global a priori N2O emission models (EDGAR32 and EDGAR42). Atmospheric particle trajectories and surface footprints are computed using the Weather Research and Forecasting (WRF) and Stochastic Time‐Inverted Lagrangian Transport (STILT) models. Regression analyses show that the slopes of predicted on measured N2O from both emission models are low, suggesting that actual N2O emissions are significantly higher than the EDGAR inventories for all seasons. Bayesian inverse analyses of regional N2O emissions show that posterior annual N2O emissions are larger than both EDGAR inventories by factors of 2.0 ± 0.4 (EDGAR32) and 2.1 ± 0.4 (EDGAR42) with seasonal variation ranging from 1.6 ± 0.3 to 2.5 ± 0.4 for an influence region of Central California within approximately 150 km of the tower. These results suggest that if the spatial distribution of N2O emissions in California follows the EDGAR emission models, then actual emissions are 2.7 ± 0.5 times greater than the current California emission inventory, and total N2O emissions account for 8.1 ± 1.4% of total greenhouse gas emissions from California.

Seasonal variation of CH4 emissions from central California

We estimate seasonal variations in methane (CH4) emissions from central California from December 2007 through November 2008 by comparing CH4 mixing ratios measured at a tall tower with transport model predictions based on a global 1° a priori CH4emissions map (EDGAR32) and a 10 km seasonally varying California‐specific map, calibrated to statewide by CH4emission totals. Atmospheric particle trajectories and surface footprints are computed using the Weather Research and Forecasting and Stochastic Time‐Inverted Lagrangian Transport models. Uncertainties due to wind velocity and boundary layer mixing depth are evaluated using measurements from radar wind profilers. CH4signals calculated using the EDGAR32 emission model are larger than those based on the California‐specific model and in better agreement with measurements. However, Bayesian inverse analyses using the California‐specific and EDGAR32 maps yield comparable annually averaged posterior CH4emissions totaling 1.55 ± 0.24 times and 1.84 ± 0.27 times larger than the California‐specific prior emissions, respectively, for a region of central California within approximately 150 km of the tower. If these results are applicable across California, state total CH4 emissions would account for approximately 9% of state total greenhouse gas emissions. Spatial resolution of emissions within the region near the tower reveal seasonality expected from several biogenic sources, but correlations in the posterior errors on emissions from both prior models indicate that the tower footprints do not resolve spatial structure of emissions. This suggests that including additional towers in a measurement network will improve the regional specificity of the posterior estimates.

ELLIPTIC FLOW AND THE SYMMETRY ENERGY AT SUPRA-SATURATION DENSITY

The elliptic flow in collisions of neutron-rich heavy-ion systems at intermediate energies emerges as an observable sensitive to the strength of the symmetry energy at supra-saturation densities. First results obtained by comparing ratios or differences of neutron and hydrogen flows with predictions of transport models favor a moderately soft to linear density dependence, consistent with ab initio nuclear-matter theories. Comprehensive data sets of high accuracy can be expected to improve our knowledge of the equation of state of asymmetric nuclear matter.

In Situ Chromium(VI) Reduction Using Iron(II) Solutions: Modeling Dynamic Geochemical Gradients

Previous experiments were conducted using Atlantic Coastal Plain soils and subsurface sediments to evaluate the effectiveness of Fe(II) solutions (FeCl2 or FeSO4) as an in situ means of remediating Cr(VI) contamination. Although Fe(II) was effective in reducing Cr(VI), the subsequent precipitation of Cr(III) was inhibited by the decrease in pH accompanying hydrolysis of Fe(III) and Cr(III). Including acetate buffer (pH 5.6) enhanced Cr(III) precipitation in batch equilibrium experiments, but added SO42− and acetate enhanced Cr(VI) mobility. Reactive transport modeling based on available data and constants derived from the literature was used to describe the dynamic geochemical gradients associated with advective–dispersive conditions encountered during the application of such a remediation strategy. Two mechanisms of Cr partitioning were simulated: (i) Cr(VI) (CrO42−) sorption to and competition with SO42− for weak binding sites associated with Fe oxides using the diffuse double layer model based on surface protonation and complexation constants derived from the literature, with reactive site densities derived from batch data; and (ii) Cr(III) precipitation in the form of a mixed Cr(III)–Fe(III) hydroxide. Adjusting for only two optimized parameters, apparent site density and solubility, the transport model predictions were qualitatively consistent with observed Cr(VI) behavior during both the contamination and remediation phases, including the enhanced migration of Cr(VI) induced by SO42− competition and the continued migration of Cr(III) associated with acidification induced by oxidation of nonbuffered Fe(II) treatments. Discrepancies between experimental results and model simulations can be attributed to the kinetics of both sorption and redox processes.