Remediation Decisions Research Articles

Recommendations to improve wildlife exposure estimation for development of soil screening and cleanup values

An integral component in the development of media-specific values for the ecological risk assessment of chemicals is the derivation of safe levels of exposure for wildlife. Although the derivation and subsequent application of these values can be used for screening purposes, there is a need to identify the threshold for effects when making remedial decisions during site-specific assessments. Methods for evaluation of wildlife exposure are included in the US Environmental Protection Agency (USEPA) ecological soil screening levels (Eco-SSLs), registration, evaluation, authorization, and restriction of chemicals (REACH), and other risk-based soil assessment approaches. The goal of these approaches is to ensure that soil-associated contaminants do not pose a risk to wildlife that directly ingest soil, or to species that may be exposed to contaminants that persist in the food chain. These approaches incorporate broad assumptions in the exposure and effects assessments and in the risk characterization process. Consequently, thresholds for concluding risk are frequently very low with conclusions of risk possible when soil metal concentrations fall in the range of natural background. A workshop held in September, 2012 evaluated existing methods and explored recent science about factors to consider when establishing appropriate remedial goals for concentrations of metals in soils. A Foodweb Exposure Workgroup was organized to evaluate methods for quantifying exposure of wildlife to soil-associated metals through soil and food consumption and to provide recommendations for the development of ecological soil cleanup values (Eco-SCVs) that are both practical and scientifically defensible. The specific goals of this article are to review the current practices for quantifying exposure of wildlife to soil-associated contaminants via bioaccumulation and trophic transfer, to identify potential opportunities for refining and improving these exposure estimates, and finally, to make recommendations for application of these improved models to the development of site-specific remedial goals protective of wildlife. Although the focus is on metals contamination, many of the methods and tools discussed are also applicable to organic contaminants. The conclusion of this workgroup was that existing exposure estimation models are generally appropriate when fully expanded and that methods are generally available to develop more robust site-specific exposure estimates. Improved realism in site-specific wildlife Eco-SCVs could be achieved by obtaining more realistic estimates for diet composition, bioaccumulation, bioavailability and/or bioaccessibility, soil ingestion, spatial aspects of exposure, and target organ exposure. These components of wildlife exposure estimation should be developed on a site-, species-, and analyte-specific basis to the extent that the expense for their derivation is justified by the value they add to Eco-SCV development.

From sediment to tissue and tissue to sediment: An evaluation of statistical bioaccumulation models

Biota-sediment accumulation factors (BSAFs) and biota-sediment accumulation regressions (BSARs) are statistical models that may be used to estimate tissue chemical concentrations from sediment chemical concentrations or vice versa. Biota-sediment accumulation factors and BSARs are used to fill tissue concentration data gaps, set sediment preliminary remediation goals (PRGs), and make projections about the effectiveness of potential sediment cleanup projects in reducing tissue chemical concentrations. We explored field-based, benthic invertebrate biota-sediment chemical concentration relationships using data from the US Environmental Protection Agency (USEPA) Mid-Continent Ecology Division (MED) BSAF database. Approximately two thirds of the 262 relationships investigated were very poor (r(2) < 0.3 or p-value ≥ 0.05); for some of the biota-sediment relationships that did have a significant nonzero slope (p-value < 0.05), lipid-normalized tissue concentrations tended to decrease as the colocated organic carbon (OC)-normalized sediment concentration increased. Biota-sediment relationships were further evaluated for 3 of the 262 datasets. Biota-sediment accumulation factors, linear regressions, model II regressions, illustrative sediment PRGs, and confidence intervals (CIs) were calculated for each of the three examples. These examples illustrate some basic but important statistical practices that should be followed before selecting a BSAR or BSAF or relying on these simple models of biota-sediment relationships to support consequential management decisions. These practices include the following: one should not assume that the relationship between chemical concentrations in tissue and sediment is necessarily linear, one should not assume the model intercept to be zero, and one should not place too much stock on models that are heavily influenced by one or a few high chemical concentration data points. People will continue to use statistical models of field-based biota-sediment chemical concentration relationships to support sediment investigations and remedial action decisions. However, it should not be assumed that the models will be reliable. In developing and applying BSAFs and BSARs, it is essential that best practices are followed and model limitations and uncertainties are understood, acknowledged, and quantified as much as possible.

Furthering the derivation of predictive wildlife toxicity reference values for use in soil cleanup decisions

The development of media-specific ecological values for risk assessment includes the derivation of acceptable levels of exposure for terrestrial wildlife (e.g., birds, mammals, reptiles, and amphibians). Although the derivation and subsequent application of these values can be used for screening purposes, there is a need to identify toxicological effects thresholds specifically for making remedial decisions at individual contaminated sites. A workshop was held in the fall of 2012 to evaluate existing methods and recent scientific developments for refining ecological soil screening levels (Eco-SSLs) and improving the derivation of site-specific ecological soil clean-up values for metals (Eco-SCVs). This included a focused session on the development and derivation of toxicity reference values (TRVs) for terrestrial wildlife. Topics that were examined included: methods for toxicological endpoint selection, techniques for dose-response assessment, approaches for cross-species extrapolation, and tools to incorporate environmental factors (e.g., metal bioavailability and chemistry) into a reference value. The workgroup also made recommendations to risk assessors and regulators on how to incorporate site-specific wildlife life history and toxicity information into the derivation of TRVs to be used in the further development of soil cleanup levels.

A more accurate analysis of alkylated PAH and PASH and its implications in environmental forensics

The accurate measurement of polycyclic aromatic hydrocarbons (PAH), polycyclic aromatic sulfur heterocycles (PASH), and their alkylated homologues is essential at all levels of risk assessment and remedial decision-making. In the field of environmental forensics, diagnostic ratios of these compounds are used to delineate fossil fuel-based sources from one another and to assess the degree of weathering occurring on-site. Fresh and weathered coal tar and crude oil samples from different locations were analysed by gas chromatography/mass spectrometry. The same files were analysed by selected ion extraction of one-ion and two-ion signals from full-scan data and compared to a new data analysis method using spectral information from homologous isomers. Findings showed that using too few ions produced false positives and concentrations much higher than those found using the homologous isomer spectral method, which adversely affected the corresponding diagnostic ratios used by forensic scientists.

Development and Realization of Contaminated Sites Information and Remediation Decision System Based on GIS

Based on the geographic information systems and database technology, this study set up a contaminated sites information and remediation management decision-making system using Beijing sites data, which include a web portal interface and three major modules: site management, risk assessment and remediation decision. People can inter the system to browse and inquiry the information concerned, zoom in and zoom out the map, statistics and analysis the data. This system provided tools for risk assessment, remediation decision and expert review. This system will provide technical support for government departments and technical institutions.

Seasonal changes in physico-chemical parameters and nutrient load of river sediments in Ibadan City, Nigeria

Seasonal variations in ecological parameters exert a profound effect on the distribution and population density of both animal and plant species (Odum, 1971). The productivity in terms of planktonic biomass in freshwater bodies is regulated by various physico-chemical factors viz., temperature, transparency, pH, total hardness, nitrates, phosphates etc. A field study was conducted (October 2003 and March 2004) to develop a data-base on seasonal changes of physico-chemical parameters and nutrient load of the river sediment in Ibadan metropolis. Quantitative samples of sediments were collected during dry and rainy seasons from 11 stations and analyzed for various physico-chemical parameters and nutrient load. All (except dissolved oxygen) physico-chemical parameters assessed in this study were higher than the recommended standard (EPA, 2002). The nutrient load of pore water of Ibadan river system sediments during rainy and dry seasons was found in the range of: phosphate (2.23-16.2 ppm and 0.35-2.8 ppm respectively); nitrate (0.22 to 0.9 ppm and 0.47-3.3 ppm respectively); Nitrite (0.2-0.42 ppm and 0.03-0.3 ppm respectively); Total nitrogen (0.13-0.9ppm and 0.47- 3.4 ppm respectively) and sulphate (70-99.4 ppm and 26.6-120 ppm respectively). The levels of parameters downstream were significantly elevated than the corresponding levels upstream. This result suggests that the water quality of Ibadan river system is adversely affected and impaired by the discharge of domestic, agricultural and industrial wastes, which is the usual practice in Ibadan. The data generated from this study will guide potential remediation and other management decisions.

Bioavailability of Metals in Contaminated Sediments

Bioavailability controls the transfer of metals from sediments to ecological receptors and humans. It can rarely be predicted from total metal concentrations because it is affected by metal geochemistry in sediments as well as the biochemistry, physiology, and behavior of benthic organisms. There is no single approach for including bioavailability in risk assessments because of variability in site specific conditions and the difficulty of validating methods. Acid-volatile sulfide and simultaneously extracted metals are useful in predicting bioavailability in anoxic sediments containing sulfides that react to form insoluble metal complexes. This method can be improved by adjusting for organic carbon and other ligands that also bind free metals. Site-specific desorption Kd values calculated by sequential extraction methods can be useful in predicting bioavailable metal fractions in oxic and anoxic sediments. A modified desorption distribution coefficient (Kdg) can be calculated by extraction with the digestive gut fluids of sediment feeding organisms to account for the effects of ingestion on metal release from sediments. Recently developed in situ measurement technologies can accumulate dissolved metals in a controlled fashion that may correspond with bioavailable metal fractions in sediment. Successful evaluation of bioavailability requires the selection of methods suitable for the organisms and sediment environments under consideration. A weight-of-evidence approach that incorporates multiple lines of evidence can help address uncertainties and increase the likelihood of incorporating bioavailability into remedial decisions.

Analysis of Students’ Misconception Based on Rough Set Theory

The study analyzed students’ misconception based on rough set theory and combined with interpretive structural model (ISM) to compare students’ degree of two classes. The study then has provided an effective diagnostic assessment tool for teachers. The participants were 30 fourth grade students in Central Taiwan, and the exam tools were produced by teachers for math exams. The study has proposed three methods to get common misconception of the students in class. These methods are “Deleting conditional attributes”, “Using Boolean logic to calculate discernable matrix”, and “Calculating significance of conditional attributes.” The results showed that students of Class A had common misconceptions but students of Class B had not common misconception. In addition, the remedial decision-making for these two classes of students is pointed out. While remedial decision-making of two classes corresponded to structural graph of concepts, it can be found the overall performance of the Class B was higher than Class A.

Correlations Between PANCE Performance, Physician Assistant Program Grade Point Average, and Selection Criteria

The purpose of this study was to examine correlations between first-time Physician Assistant National Certifying Exam (PANCE) scores and pass/fail status, physician assistant (PA) program didactic grade point average (GPA), and specific selection criteria. This retrospective study evaluated graduating classes from 2007, 2008, and 2009 at a single program (N = 119). There was no correlation between PANCE performance and undergraduate grade point average (GPA), science prerequisite GPA, or health care experience. There was a moderate correlation between PANCE pass/fail and where students took science prerequisites (r = 0.27, P = .003) but not with the PANCE score. PANCE scores were correlated with overall PA program GPA (r = 0.67), PA pharmacology grade (r = 0.68), and PA anatomy grade (r = 0.41) but not with PANCE pass/fail. Correlations between selection criteria and PANCE performance were limited, but further research regarding the influence of prerequisite institution type may be warranted and may improve admission decisions. PANCE scores and PA program GPA correlations may guide academic advising and remediation decisions for current students.

Optimized multi-phase sampling for soil remediation surveys

We develop an algorithm for optimizing the design of multi-phase soil remediation surveys. The locations of observations in later phases are selected to minimize the expected loss incurred from misclassification of the local contamination status of the soil. Unlike in existing multi-phase design methods, the location of multiple observations can be optimized simultaneously and the reduction in the expected loss can be forecast. Hence rational decisions can be made regarding the resources which should be allocated to further sampling. The geostatistical analysis uses a copula-based spatial model which can represent general types of variation including distributions which include extreme values. The algorithm is used to design a hypothetical second phase of a survey of soil lead contamination in Glebe, Sydney. Observations for this phase are generally dispersed on the boundaries between areas which, according to the first phase, either require or do not require remediation. The algorithm is initially used to make remediation decisions at the point scale, but we demonstrate how it can be used to inform over blocks.

Predicting topsoil heavy metal content of parcels of land: An empirical validation of customary and constrained lognormal block kriging and conditional simulations

Soil contamination by heavy metals is an important problem in many countries. As a first step in mitigating the related health risks, one has to delineate zones where metal concentrations exceed tolerable levels. Predictions of metal concentrations are usually required for blocks because remediation or regulatory decisions are imposed for entire parcels. Parcel areas typically exceed the observation support, but are smaller than the survey domain. Mapping soil pollution involves therefore a local change of support. Using data from an extensive survey of heavy metals in the soils around a metal smelter, we validate in this study geostatistical block predictions with measured heavy metal concentrations that were representative for the mean metal content on 53 parcels with areas of 500–5500m2. Block predictions were computed by conditional simulations (CS) and several variants of lognormal universal (LUK), constrained (LCK) and covariance-matching constrained (LCMCK) block kriging from observations with quasi-point support (2–100m2). Lognormal block kriging predictions were either computed based on the assumption that both observations and block means are lognormally distributed or by averaging lognormal point kriging predictions. Target quantities were the block means of metal content in 0–20cm depth and exceedance of regulatory thresholds by these means. CS gave the most precise predictions, both of block means and of threshold exceedance. However, the advantage was not pronounced: LUK, although slightly negatively biased, predicted block means nearly as well and was not much worse than LCK, LCMCK or CS when predicting threshold exceedance. LCK was partly positively biased (in particular when averaging lognormal constrained point kriging predictions) and was clearly less precise than LUK and CS when predicting block means. All four methods predicted threshold exceedance with good success as judged by the areas under Receiver Operating Characteristic curves (0.78–0.92). The good performance of LUK was rather surprising because nonlinear transforms of customary block kriging predictions are commonly known to be biased because kriging predictions are smoother than the target quantities. The relative success of LUK must be attributed to dense soil sampling around the validation parcels that dominantly lay in the severely contaminated part of the survey domain where a lot of soil samples had been taken. When sampling is dense the smoothing bias of block kriging does not matter much. In this situation, we can expect only limited gains in the precision of predictions by more sophisticated methods such as CS and LCK.

Dyke leakage localization and hydraulic permeability estimation through self-potential and hydro-acoustic measurements: Self-potential ‘abacus’ diagram for hydraulic permeability estimation and uncertainty computation

Abstract In the present study, we propose the combination of two geophysical techniques, which we have applied to a dyke located in southeastern France that has a visible downstream flood area: the self-potential (SP) and hydro-acoustic methods. These methods are sensitive to two different types of signals: electric signals and water–soil pressure disturbances, respectively. The advantages of the SP technique lie in the high rate of data acquisition, which allows assessment of long dykes, and direct diagnosis in terms of leakage area delimitation and quantification. Coupled with punctual hydro-acoustic cartography, a leakage position can be precisely located, therefore allowing specific remediation decisions with regard to the results of the geophysical investigation. Here, the precise localization of leakage from an earth dyke has been identified using SP and hydro-acoustic signals, with the permeability of the preferential fluid flow area estimated by forward SP modeling. Moreover, we propose a general ‘abacus’ diagram for the estimation of hydraulic permeability of dyke leakage according to the magnitude of over water SP anomalies and the associated uncertainty.

Evaluation of a sustainable remediation option: Beneficial reuse of petroleum-contaminated sediment as an energy source

The characteristics of petroleum-contaminated sediment (PCS) have been evaluated to assess whether the practice of its beneficial reuse as a sole or supplemental energy source is sustainable relative to other sediment remediation options such as monitored natural recovery (MNR), capping, or off-site disposal. Some of these remediation options for PCS are energy-intensive and/or require land utilization. The energy and compositional analysis results indicate a low carbon content (15–17%(wt)) and corresponding low energy values of 5,200 kJ/kg (2,200 Btu/lb) to 5,600 kJ/kg (2,400 Btu/lb). However, given other decision-making criteria, the sediment may contain enough value to be added as a supplemental fuel given that it is normally considered a waste product and is readily available. The thermogravimetric profiles obtained under both combustion and pyrolytic conditions showed that the sulfur contents were comparable to typical low sulfur bituminous or lignite coals found in the United States, and most of the volatiles could be vaporized below 750°C. The heavy metal concentrations determined before and after combustion of the PCS indicated that further engineering controls may be required for mercury, arsenic, and lead. Due to the potential for reduction of public health and environmental threats, potential economic savings, and conservation of natural resources (petroleum and land), removal of PCS by dredging and beneficial reuse as a supplemental fuel clearly has merit to be considered as a sustainable remediation option. Implications: This study will provide a logical evaluation process to determine whether petroleum-contaminated sediment can be reused as an energy source. The energy and emissions values were determined and evaluated whether the sediment could be combusted for viable and sustainable use, considering several factors pertinent to evaluate in the remediation decision process. Various analysis methods were employed to determine elemental compositions, heating values, thermal and emission characteristics. This evaluation process may be used as a general methodology for the determination of petroleum-contaminated sediment as a supplemental fuel that may have merit to be considered as a sustainable remediation option.

Dealing With Uncertainty When Assessing Fish Passage Through Culvert Road Crossings

Assessing the passage of aquatic organisms through culvert road crossings has become increasingly common in efforts to restore stream habitat. Several federal and state agencies and local stakeholders have adopted assessment approaches based on literature-derived criteria for culvert impassability. However, criteria differ and are typically specific to larger-bodied fishes. In an analysis to prioritize culverts for remediation to benefit imperiled, small-bodied fishes in the Upper Coosa River system in the southeastern United States, we assessed the sensitivity of prioritization to the use of differing but plausible criteria for culvert impassability. Using measurements at 256 road crossings, we assessed culvert impassability using four alternative criteria sets represented in Bayesian belief networks. Two criteria sets scored culverts as either passable or impassable based on alternative thresholds of culvert characteristics (outlet elevation, baseflow water velocity). Two additional criteria sets incorporated uncertainty concerning ability of small-bodied fishes to pass through culverts and estimated a probability of culvert impassability. To prioritize culverts for remediation, we combined estimated culvert impassability with culvert position in the stream network relative to other barriers to compute prospective gain in connected stream habitat for the target fish species. Although four culverts ranked highly for remediation regardless of which criteria were used to assess impassability, other culverts differed widely in priority depending on criteria. Our results emphasize the value of explicitly incorporating uncertainty into criteria underlying remediation decisions. Comparing outcomes among alternative, plausible criteria may also help to identify research most needed to narrow management uncertainty.

Relative contribution of DNAPL dissolution and matrix diffusion to the long-term persistence of chlorinated solvent source zones

The relative contribution of dense non-aqueous phase liquid (DNAPL) dissolution versus matrix diffusion processes to the longevity of chlorinated source zones was investigated. Matrix diffusion is being increasingly recognized as an important non-DNAPL component of source behavior over time, and understanding the persistence of contaminants that have diffused into lower permeability units can impact remedial decision-making. In this study, a hypothetical DNAPL source zone architecture consisting of several different sized pools and fingers originally developed by Anderson et al. (1992) was adapted to include defined low permeability layers. A coupled dissolution–diffusion model was developed to allow diffusion into these layers while in contact with DNAPL, followed by diffusion out of these same layers after complete DNAPL dissolution. This exercise was performed for releases of equivalent masses (675kg) of three different compounds, including chlorinated solvents with solubilities ranging from low (tetrachloroethene (PCE)), moderate (trichloroethene (TCE)) to high (dichloromethane (DCM)). The results of this simple modeling exercise demonstrate that matrix diffusion can be a critical component of source zone longevity and may represent a longer-term contributor to source longevity (i.e., longer time maintaining concentrations above MCLs) than DNAPL dissolution alone at many sites. For the hypothetical TCE release, the simulation indicated that dissolution of DNAPL would take approximately 38years, while the back diffusion from low permeability zones could maintain the source for an additional 83years. This effect was even more dramatic for the higher solubility DCM (97% of longevity due to matrix diffusion), while the lower solubility PCE showed a more equal contribution from DNAPL dissolution vs. matrix diffusion. Several methods were used to describe the resulting source attenuation curves, including a first-order decay model which showed that half-life of mass discharge from the matrix-diffusion dominated phase is in the range of 13 to 29years for TCE. Because the mass discharge rate shifts significantly over time once DNAPL dissolution is complete, a Power-Law model was shown to be useful, especially at later stages when matrix diffusion dominates. An assessment of mass distribution showed that while relatively small percentages of the initial source mass diffused into the low permeability compartment, this mass was sufficient to sustain concentrations above drinking water standards for decades. These data show that relatively typical conditions (e.g., 50-year-old release, moderate to high solubility contaminant) are consistent with late stage sources, where mass in low permeability matrices serves as the primary source, and fit the conceptual model that mass in low permeability zones is important when evaluating source longevity.

Bioremediation of Pb-Contaminated Soil Based on Microbially Induced Calcite Precipitation

To remediate lead (Pb)-contaminated soils, it is proposed that microbially induced calcite precipitation (MICP) would provide the best alternative to other remediation technologies. In this study, Pb bioremediation in soils was investigated using the calcite-precipitating bacterium Kocuria flava. Results indicate that the Pb is primarily associated with the carbonate fraction in bioremediated soil samples. The bioavailability of Pb in contaminated soil was reduced so that the potential stress of Pb was alleviated. This research provides insight into the geochemistry occurring in the MICP-based Pb-remediated soils, which will help in remediation decisions.

Cost Optimization of DNAPL Remediation at Dover Air Force Base Site

This study investigates stochastic optimization of dense nonaqueous phase liquid (DNAPL) remediation design at Dover Air Force Base Area 5 using emulsified vegetable oil (EVO) injection. The Stochastic Cost Optimization Toolkit (SCOToolkit) is used for the study, which couples semianalytical DNAPL source depletion and transport models with parameter estimation, error propagation, and stochastic optimization modules that can consider multiple sources and remediation strategies. Model parameters are calibrated to field data conditions on prior estimates of parameters and their uncertainty. Monte Carlo simulations are then performed to identify optimal remediation decisions that minimize the expected net present value (NPV) cleanup cost while maintaining concentrations at compliance wells under the maximum contaminant level (MCL). The results show that annual operating costs could be reduced by approximately 50% by implementing the identified optimal remediation strategy. We also show that recalibration and reoptimization after 50 years using additional monitoring data could lead to a further 60% reduction in annual operating cost increases the reliability of the proposed remediation actions.

Review of ecological‐based risk management approaches used at five Army Superfund sites

Factors used in environmental remedial decision making concerning ecological risk are not well understood or necessarily consistent. Recent Records of Decision (RODs) for Army CERCLA sites were reviewed to select case studies where remedial management occurred in response to ecological risks. Thirty-four Army RODs were evaluated representing decisions promulgated between 1996 and 2004. Five were selected based on assessments that remedial actions were clearly linked to concern for ecological receptors. The Ecological Risk Assessment (ERA) approach and the subsequent risk management process were reviewed for each site. The case studies demonstrated that the ERA findings, as well as critical management decisions regarding interpretation of identified ecological risks, were determinants of remedial action objectives. Decisions regarding the selection of remedial alternatives were based on a set of criteria prescribed by Superfund requirements and guidance. Remedial alternative evaluations require protection of human health and the environment, but protective conditions were determined using different methods at each site. Examining the remedial management process for the 5 case study sites revealed that uncertainty in the risk assessment and decisions regarding appropriate spatial scales for both risk assessment and remediation were important factors influencing remedial action decisions. The case reviews also revealed that levels of documentation were variable from site to site. In the future, more detailed documentation of decision criteria and the development of criteria that consider the resilience of the site will result in more technically defensible ecological risk management.

Bioremediation of hydrocarbons contaminated waters and soils: monitoring by luminescent bacteria test

Bioremediation has proven successful in numerous applications to petroleum hydrocarbons or chlorinated aromatic hydrocarbons contaminated soils. There is increasing interest in application of biotoxicity tests for ecological assessment and for supporting management decisions for remediation. Luminescent assays, light-emitting bacteria in particular, can be a suitable tool for environmental analysis, and in vivo luminescence is a rapid and precise indicator of the toxic effects of xenobiotic on micro-organisms. In this study, three different strains of marine bioluminescent bacteria have been employed to follow the changes in biotoxicity occurring during the laboratory scale bioremediation of water and soil samples contaminated by hydrocarbons and collected at an industrial area. The degradation was made by hydrocarbons degrading bacteria, both of commercial sources and isolated from polluted water and soils. The samples were treated for 45 days. The toxicity of the samples, before and after the bioremediation, was determined directly on water samples or on the extracts of soil samples. The yield of extraction by different solvents (acetone, dioxane, ethanol and dichloromethane) was evaluated by the bioluminescent test. The measurements were carried out using a microplate format both for short time of contact (60 minutes, acute toxicity) and for longer time intervals (24 hours, chronic toxicity). The results have been expressed as percentage of inhibition with respect to the blank emission (100% emission). Original and treated samples have been analysed by gas chromatography to assess the hydrocarbons (C > 12 and Poly Chlorinated Biphenyls, PCB) content. The autochthonous bacteria isolated from polluted samples proved less effective, due to the short time for selection in remediation activity with respect to the commercial ones, but their capacity to degrade long chain hydrocarbons was satisfactory. The presented laboratory study can be applied also in case of on-field conditions.

Environmental risk management for radiological accidents: Integrating risk assessment and decision analysis for remediation at different spatial scales

The consequences of the Tohuku earthquake and subsequent tsunami in March 2011 caused a loss of power at the Fukushima Daiichi nuclear power plant, in Japan, and led to the release of radioactive materials into the environment. Although the full extent of the contamination is not currently known, the highly complex nature of the environmental contamination (radionuclides in water, soil, and agricultural produce) typical of nuclear accidents requires a detailed geospatial analysis of information with the ability to extrapolate across different scales with applications to risk assessment models and decision making support. This article briefly summarizes the approach used to inform risk-based land management and remediation decision making after the Chernobyl, Soviet Ukraine, accident in 1986.