Construction and validation of parametric models to predict radium sorption in soils.

Elucidating the factors affecting the transfer of naturally occurring radionuclides (NOR) between environmental compartments is a key part of the assessment of ecosystem's exposure to naturally occurring radionuclide materials (NORM). For that, the sorption and desorption solid-liquid distribution coefficients (Kd) of radium (Ra) were quantified in a collection of 31 soil samples with contrasting edaphic properties under controlled conditions in laboratory batch experiments. Ra sorption was demonstrated to be moderate to high, with Kd (Ra) values ranging from 102 to 103 L kg-1. Ra sorbed was mostly irreversible, as evidenced by desorption percentages lower than 2 %. An exploratory analysis with partial least squares (PLS) regression identified the soil properties that correlated with Kd (Ra) and discarded those that were not relevant for describing Kd variability. A dataset of the sorption Kd (Ra) values and associated soil properties was built from our own data and from the literature after performing an in-depth review of similar Ra sorption studies. For the first time, Kd (Ra) parametric prediction models were constructed using univariate linear regression (ULR) and multivariate linear regression (MLR). Ra sorption in soils was mostly explained by the soil properties directly or indirectly related to the available exchange sites, such as the levels of water-soluble and exchangeable Ca and Mg as well as the pH of the contact solution. The most promising models explained around 80 % of the Kd (Ra) data variance, only needing Kd (Ca + Mg) or additional soil descriptors such as pH, Mn content, and the specific surface area. The validation of the proposed models confirmed that Kd (Ra) can be predicted with only a few soil properties that can be characterised in routine analysis. Thus, the proposed models could be used to estimate the interaction of Ra in soils in risk assessment.

Assessing sorption of fluoroquinolone antibiotics in soils from a Kd compilation based on pure organic and mineral components.

The presence of fluoroquinolone (FQ) antibiotics in soils may cause a threat to human health due to overexposure and the generation of antibiotic resistance genes. Understanding their sorption behavior in soils is important to predict subsequent FQ (bio) availability. Here, FQ sorption in pure soil organic (i.e., humic substances) and mineral (i.e., metal oxides; phyllosilicates) components is evaluated through a solid-liquid distribution coefficient (Kd (FQ)) dataset consisting of 243 entries originated from 80 different studies, to elucidate their respective contribution to the overall Kd (FQ) in bulk soils. First, different factors affecting FQ sorption and desorption in each of these soil phases are critically discussed. The strong role of pH in Kd (FQ), due to the simultaneous effect on both FQ speciation and surface charge changes, encouraged the derivation of normalized sorption coefficients for the cationic, zwitterionic and anionic FQ species in humic substances and in different phyllosilicates. Kd (FQ) in metal oxides revealed a key role of metal nature and material specific surface area due to complexation sorption mechanisms at neutral pH. Cumulative distribution functions (CDF) were applied to each dataset to establish a sorption affinity range for each phase and to derive best estimate Kd (FQ) values for those materials where normalized sorption coefficients to FQ species were unavailable. The data analysis conducted in the different soil phases set the basis for a Kd (FQ) prediction model, which combined the respective sorption affinity of each phase for FQ and phase abundance in soil to estimate Kd (FQ) in bulk soils. The model was subsequently validated with sorption data in well characterized soils compiled from the literature.

Using a batch test to derive sorption data of fluoroquinolone antibiotics in humic acids.

Fluoroquinolone antibiotics (FQs) are of concern due to their disrupting effects on environmental bacterial communities. Evaluating FQ sorption by soil components is important to understand their interaction with soils and to address their environmental (bio)availability. However, data in soil organic components, especially humic acids, are scarce. Batch experiments following OECD guidelines are suitable for testing the sorption of pollutants in solid matrices. Here, we applied this methodology, with specific changes in the experimental setup, to derive sorption data and to identify the factors affecting sorption of four common FQs in seven humic acids with contrasting properties. The effect of shaking time, pH, calcium concentration in solution and dissolved organic carbon (DOC) content on the quantification of the solid-liquid distribution coefficient (Kd) of norfloxacin in three reference humic acids was evaluated. Sorption reversibility and sorption analogy of four FQs were additionally assessed in these three reference materials, whereas the effect of initial norfloxacin concentration was evaluated in the overall set of seven humic acids. Sorption was fast, strong, non-linear, irreversible and affected by changes in the pH and calcium levels in solution. The bell-shaped sorption trend at varying pH values confirmed the key role of FQ speciation in sorption and the high Kd values indicated a positive effect of soil organic matter components on FQ sorption in bulk soils at environmentally relevant pH values.•Relevant factors affecting sorption of pollutants in environmental matrices must be considered to derive Kd values with low variability and high representativeness.•In this article we modify the experimental conditions of standard batch tests to identify the factors that affect the sorption of FQs in humic acids.•The methodological approach followed can be extrapolated to the evaluation of other combinations of pollutant and environmental matrix.

Deriving parametric and probabilistic Kd values for fluoroquinolones in soils.

The evaluation of the sorption affinity of fluoroquinolone antibiotics (FQs) in soils, by means of the derivation of solid-liquid distribution coefficients (Kd), is a valuable information for assessing their environmental mobility. Aiming to develop Kd (FQ) prediction tools in soils, in the first stage of this study we constructed a Kd (FQ) sorption dataset using current literature data. Furthermore, additional sorption and desorption data for norfloxacin were obtained in seven different soils of contrasting properties. Sorption isotherms of norfloxacin were linear under the experimental conditions tested and desorption percentages increased for scenarios in which low sorption was noted. Sorption tests in the same soils were then extended to ciprofloxacin, enrofloxacin and ofloxacin and pooled in the dataset, revealing comparable Kd (FQ) values among the FQ tested after analyzing the overall dataset consisting in 312 entries of Kd (FQ). A partial least square (PLS) regression model was then developed to predict values of Kd (FQ) based on specific relevant soil properties (i.e., pH, cation exchange capacity and organic carbon and texture information), and, for the first time, FQ properties (fraction of cationic FQ species) affecting sorption. Additionally, probabilistic, Kd (FQ) best estimates in soils were derived through cumulative distribution functions (CDFs) for the overall and for partial datasets created by grouping Kd (FQ) values according to key soil properties affecting FQ sorption (i.e., pH, organic carbon content and texture information). This latter approach permitted to derive more representative Kd (FQ) best estimates for the soils to be assessed, and with a lower related variability than that derived from the overall dataset. Best estimates Kd (FQ) values were > 1000 L kg-1 for most acidic to neutral soils, suggesting strong sorption, although lower sorption and thus higher environmental mobility may be expected in scenarios with soils with alkaline pH, low OC and high sand contents. SYNOPSIS: This study aims to derive parametric and probabilistic Kd values for fluoroquinolone antibiotics in soils on the basis of a few relevant soil physicochemical properties.

The use of the IAEA MARIS database in determining the variability of sediment distribution coefficients in the marine environment and potential implications for marine dispersion modelling.

A prototype tool has been developed for deriving sediment distribution coefficients,Kd, in the marine environment by harvesting simultaneous measurements of activity concentrations of radionuclides in seawater and sediments based on the International Atomic Energy Agency's Marine Radioactivity Information System (MARIS). As a case study, theKdvariability in the Baltic Sea was investigated as this region has been extensively monitored by HELCOM since 1984 resulting in a comprehensive dataset with good spatial and temporal coverage and required ancillary parameters. The prototype tool was used to derive a dataset ofin-situapparentKd(a)values derived from measurements of seawater and sediment in quasi-equilibrium conditions from the Baltic Sea over a period of approximately 35 years. For Cs, a comprehensive analysis of the Baltic SeaKd(a)dataset was undertaken, focusing on the temporal trend ofKd(a)and comparing the results toKdvalues derived elsewhere. For Sr and Pu, for which there were fewer data records available a more rudimentary analysis was carried out. The CsKd(a)median values derived from137Cs data in this study were estimated to be 2154 l kg-1for seabed sediment and 10 000 l kg-1for suspended sediment. The value derived for seabed sediment is in good agreement with the previously recommended ocean margin CsKdvalue of 4000 l kg-1. The analysis demonstrated the important distinction in the Baltic Sea betweenKdvalues for seabed sediment and suspended sediments, which differed by an order of magnitude. The analysis also highlighted the dependence ofKdvalues on the variation in both the salinity of seawater and the type of seabed sediment. Such variability can significantly influence outcomes when modelling the behaviour of radionuclides in marine dispersion modelling.

Examining sorption of perfluoroalkyl substances (PFAS) in biochars and other carbon-rich materials.

The use of carbon-rich sorbents to remove and/or immobilize perfluoroalkyl substances (PFAS) in contaminated environmental scenarios is attracting increasing interest. The identification of key sorbent properties responsible for PFAS sorption and the development of models that can predict the distribution coefficients (Kd) for PFAS sorption in these materials are crucial in the screening of candidate materials for environmental remediation. In this study, sorption kinetics, sorption isotherms, and the effects of pH, calcium concentration and dissolved organic carbon (DOC) content on PFAS sorption were evaluated in four representative carbon-rich materials: two biochars with contrasting properties, a compost, and charcoal fines rejected by the metallurgical industry. Subsequently, the sorption of seven PFAS with numbers of fluorinated carbons ranging from 4 to 11 was evaluated in a total of ten carbon-rich materials, including activated carbons, so as to build up a Kd prediction model. The sorption of PFAS increased with greater fluorinated chain length, suggesting that hydrophobic interactions play a major role in sorption and electrostatic interactions a minor one. These results were confirmed by a principal component analysis, which revealed that the CORG/O molar ratio and the specific surface area of the material were the two main sorbent properties affecting PFAS sorption. Furthermore, the DOC content in solution had a negative effect on PFAS sorption. Using this information, a simple Kd prediction model applicable to a wide range of materials and PFAS was developed, using only a few easily-derived physicochemical properties of sorbent (CORG/O molar ratio and SSA) and PFAS (number of CF2), and was externally validated with data gathered from the literature.

Examining samarium sorption in biochars and carbon-rich materials for water remediation: batch vs. continuous-flow methods.

Samarium (Sm) sorption from aqueous solutions was evaluated in biochars (derived from castor meal (CM), eucalyptus forest residues (CE), sugarcane bagasse (SB) and green pericarp of coconut (PC)) and in other carbon-rich materials (coal fines (CF); two commercial activated charcoals (GAC, NGAC)) by applying batch and continuous-flow sorption experiments. Batch experiments revealed great Kd values, in the range of 104-105 L kg-1, and high Sm sorption percentages (>97%, except for SB) in the range of environmental representative concentrations, using as-received materials, with no further treatments. Maximum sorption capacities were derived from sorption isotherms using the Langmuir model (from 1.2 to 37 mg g-1). Continuous-flow sorption experiments permitted to obtain maximum sorption capacities by mass balance and by fitting the experimental breakthrough curves to Thomas and Yan models. CF exhibited the greatest maximum sorption capacity (40 mg g-1) besting the commercial activated charcoals, while CM was established as the best biochar (7.2 mg g-1), with similar results to NGAC (12 mg g-1) but worse than GAC (36 mg g-1). The contribution of cation exchange in Sm sorption was confirmed to be significant for most materials based on the analyses of cations leached during continuous-flow sorption experiments. Maximum sorption capacities derived from Langmuir fitting correlated well with maximum sorption capacities obtained from continuous-flow experiments. Both methods were confirmed to be suitable to determine the maximum Sm sorption capacity of the materials and then to propose the most suitable materials that can act as alternative to commercial activated charcoals.

Modelling the sorption behaviour of perfluoroalkyl carboxylates and perfluoroalkane sulfonates in soils.

A simple parametric model was developed to predict the sorption of perfluoroalkyl substances (PFASs) in soils. Initially, sorption and desorption solid-liquid distribution coefficients (Kd and Kd,des respectively) of eight PFASs (five perfluoroalkyl carboxylates, PFCAs, and three perfluoroalkane sulfonates, PFSAs) in seven soils with organic carbon (OC) content ranging from 1.6 to 41% were quantified using batch experiments. The information obtained helped to fill the gaps in a literature-based database of Kd values of PFASs, which was lacking data on soils with high OC content. The overall dataset finally comprised 435 entries. Normalized sorption coefficients for the soil OC and mineral fraction contents (KOC and KMIN respectively) were deduced for each PFAS by correlating the corresponding Kd values obtained under a wide range of experimental conditions with the fraction of organic carbon (fOC) of the soils. Furthermore, the sorption mechanisms in each phase were shown to depend mainly on PFAS chain length. The dependence of KOC and KMIN values on PFAS chain length defined the basic equations to construct the model for predicting PFAS sorption, applicable to both PFCAs and PFSAs with chain lengths ranging from 3 to 11 fluorinated carbons. The validation of the proposed model confirmed its ability to predict the Kd of PFASs based only on the soil OC and silt+clay contents and PFAS chain length. Therefore, it can be used in the first stages of a risk assessment process aiming at estimating the potential mobility of PFASs in soils after a contamination event. SYNOPSIS: This study develops a new parametric model to predict the sorption of perfluoroalkyl substances (PFASs) in soils.

An updated strategic research agenda for the integration of radioecology in the european radiation protection research.

The ALLIANCE Strategic Research Agenda (SRA) for radioecology is a living document that defines a long-term vision (20 years) of the needs for, and implementation of, research in radioecology in Europe. The initial SRA, published in 2012, included consultation with a wide range of stakeholders (Hinton et al., 2013). This revised version is an update of the research strategy for identified research challenges, and includes a strategy to maintain and develop the associated required capacities for workforce (education and training) and research infrastructures and capabilities. Beyond radioecology, this SRA update constitutes a contribution to the implementation of a Joint Roadmap for radiation protection research in Europe (CONCERT, 2019a). This roadmap, established under the H2020 European Joint Programme CONCERT, provides a common and shared vision for radiation protection research, priority areas and strategic objectives for collaboration within a European radiation protection research programme to 2030 and beyond. Considering the advances made since the first SRA, this updated version presents research challenges and priorities including identified scientific issues that, when successfully resolved, have the potential to impact substantially and strengthen the system and/or practice of the overall radiation protection (game changers) in radioecology with regard to their integration into the global vision of European research in radiation protection. An additional aim of this paper is to encourage contribution from research communities, end users, decision makers and other stakeholders in the evaluation, further advancement and accomplishment of the identified priorities.

Deriving probabilistic soil distribution coefficients (Kd). Part 3: Reducing variability of americium Kd best estimates using soil properties and chemical and geological material analogues.

The solid-liquid distribution coefficient (Kd) is a key input parameter in radioecological risk models. However, its large variability hampers its usefulness in modelling transport processes as well as its accuracy in representing soil-radionuclide interactions. To assist in the selection of Kd values and their cumulative distribution functions for study areas without site specific information, a critically reviewed dataset was developed, containing more than 5000 soil Kd entries for 83 elements and an additional 2000 entries of Kd data for 75 elements gathered from a selection of other geological materials. For the specific case of americium (Am), the dataset contained 109 entries for soils and 33 additional entries for sediment and subsoils. The analysis of the Am Kd soil dataset showed that values varied 4-orders of magnitude, and consequently the resulting Am Kd best estimate (geometric mean (GM): 4.6 × 103 L kg-1) lacked sufficient reliability. The objective of this study was to calculate cumulative distribution functions and statistically evaluate this dataset to determine if the Am Kd variability in soils could be reduced by considering various factors, including: 1) measurement methods, 2) key soil properties, 3) the use of chemical analogue data, and 4) the use of analogue data. Accounting for Am Kd experimental method (i.e., sorption vs. desorption; long-vs. short-term experiments) had little effect on reducing variability. However, accounting for key soil factors (i.e., organic matter content (OM), pH, soil texture) succeeded in reducing variability of Am Kd, especially when combining pH and OM. While previous data sets have used 20% OM content as a critical value to distinguish between mineral and organic soils, this study shows that this critical value should be reduced to 10% OM to minimize Am Kd variability. The inclusion in the dataset of Am Kd from other geological materials (e.g., gyttjas, tills, and subsoils) and Kd values from trivalent lanthanides (Ln (III)) and actinides (An (III)) (172 additional entries) did not statistically affect the Am Kd geometric means of the various pH and OM partial datasets. The larger composite dataset (> 310 entries), with both chemical analogues and geological material analogues to address data gaps, increased the statistical power for calculating Kd best estimates with lower variability, thereby enhancing their usefulness for radionuclide risk calculations.

Deriving probabilistic soil distribution coefficients (Kd). Part 2: Reducing caesium Kd uncertainty by accounting for experimental approach and soil properties.

The solid-liquid distribution coefficient (Kd) is a key input parameter in radioecological models. However, its large variability hampers its usefulness in modelling transport processes as well as its accuracy in representing soil-radionuclide interactions. For the specific case of radiocaesium, the analyses of a Cs Kd soil dataset (769 entries) showed that values varied over a five order of magnitude range, and the resulting Cs Kd best estimate (calculated as a geometric mean = 2.5 × 103 L kg-1) lacked reliability and representativity. Grouping data and creation of partial datasets based on the experimental approach (short-term (< ~1 yr) vs. long-term experiments (> ~1 yr)) and soil factors affecting Cs interaction (i.e., the ratio of the radiocaesium interception potential (RIP) to the potassium content in soil solution (Kss); organic matter content (OM) and soil texture) succeeded in reducing variability a few orders of magnitude, with Cs Kd best estimates also differing by one-two orders of magnitude depending on the type of soil and experimental approach. The statistical comparison of the Cs Kd best estimates and related cumulative distribution functions of the partial datasets revealed a relevant effect of the sorption dynamics on Cs Kd values (with long-term values systematically higher than short-term ones), and that the RIP/Kss ratio was an excellent predictor of Cs Kd for short-term scenarios, whereas the RIP parameter could be predicted on the basis of texture information. The OM threshold to distinguish between OM threshold to distinguish between Mineral and Organic soils subclasses, regarding Cs interaction was determined to be 50% and 90% OM for short- and long-term scenarios, respectively. It was then recommended to select the Cs Kd input data depending on the soils and scenarios to be assessed (e.g., short- vs. long-term; OM %) to improve the reliability and decrease the uncertainty of the radioecological models.

Deriving probabilistic soil distribution coefficients (Kd). Part 1: General approach to decreasing and describing variability and example using uranium Kd values.

A general approach is presented to derive probabilistic radionuclide distribution coefficients (Kd) in soils from a Kd dataset. The main aim was to derive informed estimates with a low inherent uncertainty by restricting the Kd value data to subsets based on key soil factors and the experimental approach used to calculate the Kd value (e.g., sorption and desorption tests). As an example, the general approach was applied to uranium (U) Kd values that are part of a critically reviewed dataset containing more than 5000 soil Kd entries for 83 elements and an additional 2000 entries of Kd data for 75 elements gathered from a selection of other, non-soil, geological materials. The overall soil U Kd dataset included 196 values spanning a range of four orders of magnitude (1-67,000 L kg-1), with additional 50 entries for other geological materials. Whereas the effect of the experimental approach could be disregarded, major factors in decreasing U Kd variability were pH and organic matter content (OM). Limitation in the number of entries made it difficult to use texture information (sand, silt, clay) to further decrease U Kd variability. The integrated combination of pH + OM permitted some soil groups to have U Kd confidence intervals as narrow as two orders of magnitude. Specifically for U Kd, data in the Mineral (< 20% OM) and Organic (≥ 20% OM) partial datasets were significantly different. Analogue data from geological materials other than soils, such as subsoil, till and gyttja (a lacustrine mud having elevated organic matter (OM) contents), were also statistically evaluated to determine whether they could be used to fill U Kd data gaps. It was shown that U Kd from subsoils and tills, but not gyttjas, could be used to enhance soil U Kd datasets. Selection of probabilistic Kd values for risk modelling can be made more reliably and with less uncertainty by using appropriate geochemical data representative of the study site to narrow the wide range of potential Kd values.

Feasibility of using low-cost, byproduct materials as sorbents to remove heavy metals from aqueous solutions.

This work investigates the sorption of heavy metals by low-cost, byproducts such as charcoal fines (CF), waste green sand, and rice husk ash, in order to examine the feasibility of their use as alternative filter materials for metal-contaminated waters. The sorption of Cd, Cu, Pb, and Zn was investigated in batch experiments and sorption isotherms were constructed. The three byproducts showed high metal removal efficiencies (>95%, regardless of the metal concentration tested). The highest metal sorption distribution coefficients were obtained for CF, with maximum values within the 105-106 L kg-1 range for all the target metals. The sorption isotherms were satisfactorily fitted using the Freundlich equation and a linear model, the latter only being valid for initial metal concentrations lower than 0.4 mmol L-1. Sorption reversibility was very low, with desorption yields lower than 2% and desorption distribution coefficients often higher than 106 L kg-1. The values of the sorption and desorption parameters indicated that the use of these materials, especially CF, could constitute a low-cost alternative for the remediation of contaminated waters.

LightDock: a new multi-scale approach to protein-protein docking.

Motivation: Computational prediction of protein-protein complex structure by docking can provide structural and mechanistic insights for protein interactions of biomedical interest. However, current methods struggle with difficult cases, such as those involving flexible proteins, low-affinity complexes or transient interactions. A major challenge is how to efficiently sample the structural and energetic landscape of the association at different resolution levels, given that each scoring function is often highly coupled to a specific type of search method. Thus, new methodologies capable of accommodating multi-scale conformational flexibility and scoring are strongly needed. Results: We describe here a new multi-scale protein-protein docking methodology, LightDock, capable of accommodating conformational flexibility and a variety of scoring functions at different resolution levels. Implicit use of normal modes during the search and atomic/coarse-grained combined scoring functions yielded improved predictive results with respect to state-of-the-art rigid-body docking, especially in flexible cases. Availability and implementation: The source code of the software and installation instructions are available for download at https://life.bsc.es/pid/lightdock/. Contact: juanf@bsc.es. Supplementary information: Supplementary data are available at Bioinformatics online.

Education and training in radioecology during the EU-COMET project-successes and suggestions for the future.

The 2014 Strategic Research Agenda (SRA) for Radioecology identified the key challenge in education and training (E&T) as being 'to maintain and develop a skilled workforce in Europe and world-wide, through university candidates and professionals trained within radioecology' since 'scientific research in radioecology and application of that knowledge … requires scientists and workers with adequate competence and appropriate skills.' Radioecology is a multidisciplinary science and E&T is needed by both students and professionals within research, industry and radiation protection. In order to address these needs, the EU COMET project has developed an E&T web platform and arranged a number of field courses, training courses, PhD and MSc courses, refresher courses and workshops, drawing on the COMET consortium to assemble relevant experts. In addition, COMET has been engaged in discussions with stakeholders for more long-term solutions to maintain the sustainability of radioecology E&T after the end of the project. Despite much progress in some areas, many of the challenges outlined in the 2014 SRA remain, mainly due to the lack of sustainable dedicated funding. Future plans within the ALLIANCE radioecology platform and the CONCERT-European Joint Programme for the Integration of Radiation Protection Research must urgently address this lack of sustainability if radioecological competence is to be maintained in Europe.

Dependence of samarium-soil interaction on samarium concentration: Implications for environmental risk assessment.

The sorption and desorption behaviour of samarium (Sm), an emerging contaminant, was examined in soil samples at varying Sm concentrations. The obtained sorption and desorption parameters revealed that soil possessed a high Sm retention capacity (sorption was higher than 99% and desorption lower than 2%) at low Sm concentrations, whereas at high Sm concentrations, the sorption-desorption behaviour varied among the soil samples tested. The fractionation of the Sm sorbed in soils, obtained by sequential extractions, allowed to suggest the soil properties (pH and organic matter solubility) and phases (organic matter, carbonates and clay minerals) governing the Sm-soil interaction. The sorption models constructed in the present work along with the sorption behaviour of Sm explained in terms of soil main characteristics will allow properly assessing the Sm-soil interaction depending on the contamination scenario under study. Moreover, the sorption and desorption Kd values of radiosamarium in soils were strongly correlated with those of stable Sm at low concentrations (r = 0.98); indicating that the mobility of Sm radioisotopes and, thus, the risk of radioactive Sm contamination can be predicted using data from low concentrations of stable Sm.

Assessing the efficacy over time of the addition of industrial by-products to remediate contaminated soils at a pilot-plant scale.

The effect of the addition of industrial by-products (gypsum and calcite) on the leaching of As and metals (Cu, Zn, Ni, Pb and Cd) in a soil contaminated by pyritic minerals was monitored over a period of 6 months at a two-pit pilot plant. The contaminated soil was placed in one pit (non-remediated soil), whereas a mixture of the contaminated soil (80% w/w) with gypsum (10% w/w) and calcite (10% w/w) was placed in the other pit (remediated soil). Soil samples and leachates of the two pits were collected at different times. Moreover, the leaching pattern of major and trace elements in the soil samples was assessed at laboratory level through the application of the pHstat leaching test. Addition of the by-products led to an increase in initial soil pH from around 2.0 to 7.5, and it also provoked that the concentration of trace elements in soil extracts obtained from the pHstat leaching test decreased to values lower than quantification limits of inductively coupled plasma optical emission spectrometry and lower than the hazardous waste threshold for soil management. The trace element concentration in the pilot-plant leachates decreased over time in the non-remediated soil, probably due to the formation of more insoluble secondary minerals containing sulphur, but especially decreased in pit of the remediated soil, in agreement with laboratory data. The pH in the remediated soil remained constant over the 6-month period, and the X-ray diffraction analyses confirmed that the phases did not vary over time, thus indicating the efficacy of the addition of the by-products. This finding suggests that soil remediation may be a feasible option for the re-use of non-hazardous industrial by-products.

Sorption of perfluoroalkyl substances in sewage sludge.

The sorption behaviour of three perfluoroalkyl substances (PFASs) (perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA) and perfluorobutanesulfonic acid (PFBS)) was studied in sewage sludge samples. Sorption isotherms were obtained by varying initial concentrations of PFOS, PFOA and PFBS. The maximum values of the sorption solid-liquid distribution coefficients (Kd,max) varied by almost two orders of magnitude among the target PFASs: 140-281 mL g(-1) for PFOS, 30-54 mL g(-1) for PFOA and 9-18 mL g(-1) for PFBS. Freundlich and linear fittings were appropriate for describing the sorption behaviour of PFASs in the sludge samples, and the derived KF and Kd,linear parameters correlated well. The hydrophobicity of the PFASs was the key parameter that influenced their sorption in sewage sludge. Sorption parameters and log(KOW) were correlated, and for PFOS (the most hydrophobic compound), pH and Ca + Mg status of the sludge controlled the variation in the sorption parameter values. Sorption reversibility was also tested from desorption isotherms, which were also linear. Desorption parameters were systematically higher than the corresponding sorption parameters (up to sixfold higher), thus indicating a significant degree of irreversible sorption, which decreased in the sequence PFOS > PFOA > PFBS.

[Experience with pulse carbon monoxide oximetry for prehospital assessment of patients exposed to smoke from fires in closed spaces in Catalonia]. / Experiencia del uso del pulsicooxímetro en la evaluación prehospitalaria de las víctimas expuestas al humo de incendios en ambientes cerrados en Cataluña.

OBJECTIVES: To describe the clinical characteristics of fire smoke inhalation victims and carboxyhemoglobin values (Sp- CO) recorded with a portable pulse carbon monoxide (CO) oximeter at rescue sites in Catalonia. To assess the contribution of SpCO information to decision-making during emergency transfers. MATERIAL AND METHODS: Retrospective observational study. We included records for patients exposed to smoke in closed spaces at fires. The patients had been attended by the Catalan Emergency Medical Group (GEM) from January 2010 to December 2012. A logistic regression model included the following independent variables: sex, age, smoking status, known medical history, signs and symptoms of intoxication, burns, SpCO, and oxygen saturation. The dependent variable was the decision to transfer the patient to a hospital. RESULTS: The GEM attended 331 victims; 6 died at the scene of the fire and 43.8 % (135/308) were transferred to a hospital. The cohort included 178 men (57.8% of 308), and 73.0% were between the ages of 18 and 65 years (216/296). SpCO levels were over 10% in 11.4% (35/308); the mean SpCO was 4.33% (95% CI, 3.65%-5.12%). The regression model identified the following variables associated with the decision to transfer the patient to a hospital: presence of burns (P=.014), signs (P<.001) and symptoms (P=.011) of intoxication, and SpCO value (P<.001). The odds ratio for SpCO SOH 10% was 12.59 (95% CI, 4.32-36.69) in relation to transfer to a hospital. CONCLUSION: Pulse CO-oximetry contributed to the prehospital emergency care of these patients by influencing the decision to transfer the patient to a hospital.

OBJETIVO: El estudio describe las características clínicas y los valores de carboxihemoglobina por pulsicooximetría portátil (SpCO) in situ que presentaron víctimas de incendios y valora su aporte en la decisión de traslado hospitalario. METODO: Estudio observacional retrospectivo. Se incluyeron víctimas expuestas a humo de incendios en ambientes cerrados que recibieron asistencia prehospitalaria por el Grup d'Emergències Mèdiques (GEM) desde enero del 2010 a diciembre 2012. Se construyó un modelo explicativo de regresión logística con las variables independientes: sexo, edad, hábito tabáquico, antecedentes patológicos, síntomas y signos de intoxicación, presencia de quemaduras, valor de SpCO y saturación de oxígeno. La variable respuesta fue la decisión de traslado hospitalario. RESULTADOS: Se atendieron a 331 de víctimas, seis de ellas fallecieron in situ. El 43,8% (135/308) fueron trasladadas a un hospital. El 57,8% (178/308) eran hombres, con edades comprendidas entre 18 y 65 años el 73,0% (216/296). El 11,4% (35/308) presentó valores de SpCO SOH 10%, y la media global fue de 4,33% (IC95% 3,65-5,12). Las variables del modelo multivariante que mostraron asociación con la decisión de traslado hospitalario fueron: presencia de quemaduras (p = 0,014), signos (p < 0,001) y síntomas (p = 0,011) de intoxicación y los valores de SpCO (p < 0,001). En el caso de valores de SpCO SOH 10%, la OR para traslado hospitalario fue 12,59 (IC 95% 4,32-36,69). CONCLUSIONES: El uso del pulsicooxímetro en la asistencia prehospitalaria aportó un valor añadido independiente para la toma de decisión de traslado hospitalario.

Sorption behaviour of perfluoroalkyl substances in soils.

The sorption behaviour of three perfluoroalkyl substances (PFASs), perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA) and perfluorobutane sulfonic acid (PFBS), was studied in six soils with contrasting characteristics, especially in the organic carbon content. Sorption isotherms were obtained by equilibrating the soil samples with 0.01 mol L(-1) CaCl2 solutions spiked with increasing concentrations of the target PFAS. The sorption reversibility of PFASs was also tested for some of the samples. Liquid chromatography coupled to tandem mass spectrometry was used to quantify the target PFASs in the solutions. Both the Freundlich and linear models were appropriate to describe the sorption behaviour of PFASs in soils, and enabled us to derive solid-liquid distribution coefficients (Kd) for each compound in each soil. Kd values increased from 19 to 295 mL g(-1) for PFOS, from 2.2 to 38 mL g(-1) for PFOA and from 0.4 to 6.8 mL g(-1) for PFBS, and were positively correlated with the organic carbon content of the soil. KOC values obtained from the correlations were 710, 96 and 17 mL g(-1) for PFOS, PFOA and PFBS, respectively. Whereas Kd values decreased in the sequence PFOS>PFOA>PFBS, desorption yields were lower than 13% for PFOS, from 24 to 58% for PFOA, and from 32 to 60% for PFBS. This shows that the physicochemical characteristics of PFASs, basically their hydrophobicity, controlled their sorption behaviour in soils, with PFOS being the most irreversibly sorbed PFAS.