Characterization and optimization of long-term controlled release system for groundwater remediation: a generalized modeling approach

A well-based reactive barrier system using controlled-release KMnO4 has been recently developed as a long-term in situ treatment option for plumes of dense and non-aqueous phase liquids in groundwater. In order to take advantage of the merits of controlled release systems (CRS) in environmental remediation, the release behavior needs to be optimized for the hydrologic and environmental conditions of target treatment zone. Where release systems are expected to be operated over long times, like for the reactive barriers, it may only be practical to describe the long-term behavior numerically. We developed a numerical model capable of describing release characteristics associated with variable forms and structures of long-term CRS. Sensitivity analyses and illustrative simulations showed that the release kinetics and durations would be constrained by changes in agent solubility, bulk diffusion coefficients, or structures of the release devices. The generality of the numerical model was demonstrated through simulations for CRS with monolithic and double-layered matrices. The generalized model was then used for actual design and analyses of an encapsulated-matrix CRS, which can yield constant release kinetics for several years. A well-based reactive barrier system (4.05 x 10(3)m3) using the encapsulated-matrix CRS can release approximately 1.65 kg of active agent (here MnO4(-)) daily over the next 6.6 yr, creating prolonged reaction zone in the subsurface. The generalized model-based, target-specific approach using the long-term CRS could provide practical tool for improving the efficacy of advanced in situ remediation schemes such as in situ chemical oxidation, bioremediation, or in situ redox manipulation. Development of techniques for adjusting the bulk diffusion coefficients of the release matrices and facilitating the lateral spreading of the released agent is warranted.     

On the role of physical modelling in atmospheric and oceanic forecast

We discuss how physical modelling can be used to reproduce atmospheric or oceanic flows in the laboratory. The similarity conditions for the effects of density stratification and Earth rotation are first presented. Then examples of results obtained on the large ‘Coriolis’ platform in Grenoble are described. These include topographic wakes in a stratified fluid and gravity currents. Physical modelling is not used to get direct results of practical relevance, but rather to test numerical models on specific processes of environmental flows. Therefore it must be performed in close relationship with theory and numerical modelling, using advanced measurement and data assimilation techniques.     

Road soil retention of Pb leached from MSWI bottom ash

Municipal solid waste incinerator (MSWI) bottom ash may be used as a road construction material; it potentially contains however a sizable quantity of heavy metals, which under the effect of rainfall infiltration through the road structure can be leached out from the material and infiltrate into the underlying soil. An eco-compatibility assessment of MSWI bottom ash reuse in road construction applications necessitates examining the solubility and retention of heavy metals in road soils. This study is dedicated to Pb transfer, sorption and desorption (NEN 7341 standard test) within various soils. These experiments yield results relative to the interaction between road soils and an MSWI bottom ash leachate representative of a "fresh" product, with a high leaching potential. For the soils investigated, the sorption of lead varies between 90% and 99%. For an extraction at pH 7, Pb release is very low (<2%) for all soils, while at pH 4 leaching varies between 4% and 47%. This work shows that Pb may be fixed by some types of road soil in mostly stable forms.     

Development of a Computationally Efficient Full Human Body Finite Element Model

Introduction: A simplified and computationally efficient human body finite element model is presented. The model complements the Global Human Body Models Consortium (GHBMC) detailed 50th percentile occupant (M50-O) by providing kinematic and kinetic data with a significantly reduced run time using the same body habitus.

Methods: The simplified occupant model (M50-OS) was developed using the same source geometry as the M50-O. Though some meshed components were preserved, the total element count was reduced by remeshing, homogenizing, or in some cases omitting structures that are explicitly contained in the M50-O. Bones are included as rigid bodies, with the exception of the ribs, which are deformable but were remeshed to a coarser element density than the M50-O. Material models for all deformable components were drawn from the biomechanics literature. Kinematic joints were implemented at major articulations (shoulder, elbow, wrist, hip, knee, and ankle) with moment vs. angle relationships from the literature included for the knee and ankle. The brain of the detailed model was inserted within the skull of the simplified model, and kinematics and strain patterns are compared.

Results: The M50-OS model has 11 contacts and 354,000 elements; in contrast, the M50-O model has 447 contacts and 2.2 million elements. The model can be repositioned without requiring simulation. Thirteen validation and robustness simulations were completed. This included denuded rib compression at 7 discrete sites, 5 rigid body impacts, and one sled simulation. Denuded tests showed a good match to the experimental data of force vs. deflection slopes. The frontal rigid chest impact simulation produced a peak force and deflection within the corridor of 4.63 kN and 31.2%, respectively. Similar results vs. experimental data (peak forces of 5.19 and 8.71 kN) were found for an abdominal bar impact and lateral sled test, respectively. A lateral plate impact at 12 m/s exhibited a peak of roughly 20 kN (due to stiff foam used around the shoulder) but a more biofidelic response immediately afterward, plateauing at 9 kN at 12 ms. Results from a frontal sled simulation showed that reaction forces and kinematic trends matched experimental results well. The robustness test demonstrated that peak femur loads were nearly identical to the M50-O model. Use of the detailed model brain within the simplified model demonstrated a paradigm for using the M50-OS to leverage aspects of the M50-O. Strain patterns for the 2 models showed consistent patterns but greater strains in the detailed model, with deviations thought to be the result of slightly different kinematics between models. The M50-OS with the deformable skull and brain exhibited a run time 4.75 faster than the M50-O on the same hardware.

Conclusions: The simplified GHBMC model is intended to complement rather than replace the detailed M50-O model. It exhibited, on average, a 35-fold reduction in run time for a set of rigid impacts. The model can be used in a modular fashion with the M50-O and more broadly can be used as a platform for parametric studies or studies focused on specific body regions.     

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Objective: Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.

Methods: Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15–105 km/h longitudinal delta-Vs and belt status was adjusted for as a covariate.

Results: Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4–4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6–9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9–43.8% risk).

Conclusions: These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.     

New Methodology for an Expert-Designed Map From International Classification of Diseases (ICD) to Abbreviated Injury Scale (AIS) 3+ Severity Injury

Objective: There has been a longstanding desire for a map to convert International Classification of Diseases (ICD) injury codes to Abbreviated Injury Scale (AIS) codes to reflect the severity of those diagnoses. The Association for the Advancement of Automotive Medicine (AAAM) was tasked by European Union representatives to create a categorical map classifying diagnoses codes as serious injury (Abbreviated Injury Scale [AIS] 3+), minor/moderate injury (AIS 1/2), or indeterminate. This study's objective was to map injury-related ICD-9-CM (clinical modification) and ICD-10-CM codes to these severity categories.

Methods: Approximately 19,000 ICD codes were mapped, including injuries from the following categories: amputations, blood vessel injury, burns, crushing injury, dislocations/sprains/strains, foreign body, fractures, internal organ, nerve/spinal cord injury, intracranial, laceration, open wounds, and superficial injury/contusion. Two parallel activities were completed to create the maps: (1) An in-person expert panel and (2) an electronic survey. The panel consisted of expert users of AIS and ICD from North America, the United Kingdom, and Australia. The panel met in person for 5 days, with follow-up virtual meetings to create and revise the maps. Additional qualitative data were documented to resolve potential discrepancies in mapping. The electronic survey was completed by 95 injury coding professionals from North America, Spain, Australia, and New Zealand over 12 weeks. ICD-to-AIS maps were created for: ICD-9-CM and ICD-10-CM. Both maps indicated whether the corresponding AIS 2005/Update 2008 severity score for each ICD code was AIS 3+, 1/2, or indeterminable. Though some ICD codes could be mapped to multiple AIS codes, the maximum severity of all potentially mapped injuries determined the final severity categorization.

Results: The in-person panel consisted of 13 experts, with 11 Certified AIS specialists (CAISS) with a median of 8 years and an average of 15 years of coding experience. Consensus was reached for AIS severity categorization for all injury-related ICD codes. There were 95 survey respondents, with a median of 8 years of injury coding experience. Approximately 15 survey responses were collected per ICD code. Results from the 2 activities were compared, and any discrepancies were resolved using additional qualitative and quantitative data from the in-person panel and survey results, respectively.

Conclusions: Robust maps of ICD-9-CM and ICD-10-CM injury codes to AIS severity categories (3+ versus <3) were successfully created from an in-person panel discussion and electronic survey. These maps provide a link between the common ICD diagnostic lexicons and the AIS severity coding system and are of value to injury researchers, public health scientists, and epidemiologists using large databases without available AIS coding.     

The Influence of Varying Algal Biomass On Contaminant Exposure in Benthic-Planktonic Mesocosms: Copper (Ii)

A series of mesocosms was exposed to a suite of light treatments and nutrient enrichment in order to generate algal communities of varying biomass. the influence of this biomass on the speciation of copper (II) was studied. Distribution coefficients (_Kd,Lkg-1) were relatively high (log_Kd = 5 to 7), indicative of robust trace metal sequestration, and were likely controlled by the particulate organic carbon content (foc). Differences in _Kd over time and among treatments were significant, as was the relationship between _Kd and foc. Fluorescence quenching was used to determine binding capacities (_Lt, M) and their associated binding constants (_Kcond,M^-1) in order to model the solid phase copper speciation. the _Kcond ranged between 2.1 and 5.2 × 10¹²M^-1, indicating a very strong copper-ligand complex, and was higher in mesocosms that received more light. the light _Lt increased over time, dramatically after the nutrient enrichment, but did not vary systematically among light treatments. _Lt ranged from 7.2 × 10- 7 to 4.9 × 10- 5 M. the large magnitudes of _Kd, _Kcond and _Lt ensured that greater than 97% of total copper in the mesocosms was complexed by organic matter. the total copper concentration ([Cu]_T, M) needed to reach a target dissolved copper concentration of 10^-12.5 M (pCu = 12.5) was determined for each mesocosm over time. [Cu]_T was between 8.02 × 10^-5 and 3.41 × 10^-2 M, and increased over time. the [Cu]_T normalized to the target pCu (Effective Dose Ratio, EDR) increased directly with increases in algal biomass, indicating a direct link between system productivity and copper exposure. Approximately 45% of the variance in EDR was explained by variance in total biomass, while the residual variance in EDR was due likely to differences in the strengths of particle associations and magnitude of binding capacities.     

Influence of Baltimore's Urban Atmosphere on Organic Contaminants over the Northern Chesapeake Bay

ABSTRACT

Air and precipitation samples were collected along an urban to over-water to rural transect across the northern Chesapeake Bay as a preliminary investigation into the spatial extent of elevated atmospheric concentrations of urban-derived persistent organic pollutants. Air samples were collected daily from June 3–9, 1996, along the transect as part of the Atmospheric Exchange over Lakes and Oceans project. Total (gas + particle bound) atmospheric polycy-clic aromatic hydrocarbon concentrations [∑-PAH] ranged from 0.4 to 114 ng/m³, and gas phase polychlorinated bi-phenyl concentrations [∑-PCB] ranged from 0.02 to 3.4 ng/m³. Strong concentration gradients were found for both PAHs and PCBs, with the highest concentrations in the city and the lowest at the downwind rural site. Gas and particle bound PAHs varied independently in the city, possibly due to strong but geographically separated emission sources. A precipitation event collected during westerly winds contained fourfold higher ∑-PAH and twelvefold higher ∑-PCB concentrations at the over-water site than at the rural background location, further indicating that the urban plume extends from Baltimore, MD, over the northern Chesapeake Bay over a spatial scale of approximately 30 km.