Evaluation of semi-mechanistic models to predict soil to grass transfer factor of 137Cs based on long term observations in French pastures.

The aim of this study was to evaluate and improve the accuracy of the semi-mechanistic models used in regulatory exposure assessment tools, to describe the transfer factors of 137Cs from pasture soils to grass observed in different grazing areas of France between 2004 and 2017. This involved a preliminary parameterization step of the dynamic factor describing the ageing of radiocesium in the root zone using a Bayesian approach. A data set with mid-term (10 years about) and long term (more than 20 years) field and literature data from 4 European countries was used. A double kinetics of the bioavailability decay was evidenced with two half-life periods equal to 0.46 ± 0.11 yr and 9.57 ± 1.12 yr for the fast and slow declining rates respectively. We, then, tested a few existing alternative models proposed in literature. The comparison with field data showed that these models always underestimated the observations by one to two orders of magnitude, suggesting that the solid-liquid partition coefficient (Kd) was overestimated by models. The results suggest that semi mechanistic models might fail in the long-term prediction of the radionuclide transfer from soil-to-plant in the food chain. They highlight the need to calculate Kd using easily exchangeable 137Cs (i.e. labile fraction) rather than total soil 137Cs.

Long term decrease of 137Cs bioavailability in French pastures: Results from 25 years of monitoring.

Long term radioactivity monitoring programs contribute to the understanding of the behavior of radionuclides in the environment. This work aims to investigate the long term behavior of Cesium-137 in pasture ecosystem (root soil, grass and cow's milk) by using of more than twenty five years monitoring data collected at ten of French pasture sites contaminated by atmospheric fallouts from Chernobyl and nuclear atmospheric tests. We estimated with a simple exponential model the long term effective half-lives of radiocesium in root soil, grass vegetation and cow's milk along with their associated uncertainties. The average values of the effective half-lives over all the investigated sites were determined as 17, 11 and 9 years for soil, grass and milk respectively. Those values compare favorably to those estimated in previous studies in literature. These findings further enable us to quantify the decrease of 137Cs bioavailability which ranges from 0.008 to 0.044 year-1 with an average value of 0.026 year-1 (i.e. effective half lives ranging from 16 to 87 years with an average value of 26 years in soil).

Environmental availability of sulfamethoxazole and its acetylated metabolite added to soils via sludge compost or bovine manure.

The fate of antibiotics and their metabolites in soils after application of organic waste depends on their environmental availability, which depends on the quality and biodegradability of the added exogenous organic matter (EOM). This study aimed at better understanding the fate of sulfamethoxazole (SMX) and N-acetyl-sulfamethoxazole (AcSMX) metabolite added to soils via sludge compost or cow manure application, during a 28-day incubation. Experimental results obtained for mineralized, extractable, and non-extractable fractions as well as EOM mineralization were used to couple SMX and AcSMX dynamics to the EOM evolution using the COP-Soil model. According to various mechanisms of extraction, CaCl2, EDTA and cyclodextrin solutions extracted contrasted available fractions (31-96% on day 0), resulting in different sets of parameter values in the model. CaCl2 extraction was the best method to assess the sulfonamide availability, leading to low relative root mean squared errors and best simulations of SMX and AcSMX dynamics. The decrease of SMX and AcSMX availability over time went with the formation of non-extractable residues, mostly of physicochemical origin. Using the COP-Soil model, the co-metabolism was assumed to be responsible for the formation of biogenic non-extractable residues and the low mineralization of SMX and AcSMX.

Modelling the fate of PAH added with composts in amended soil according to the origin of the exogenous organic matter.

A new model that was able to simulate the behaviours of polycyclic aromatic hydrocarbons (PAH) during composting and after the addition of the composts to agricultural soil is presented here. This model associates modules that describe the physical, biological and biochemical processes involved in PAH dynamics in soils, along with a module describing the compost degradation resulting in PAH release. The model was calibrated from laboratory incubations using three 14C-PAHs, phenanthrene, fluoranthene and benzo(a)pyrene, and three different composts consisting of two mature and one non-mature composts. First, the labelled PAHs were added to the compost over 28days, and spiked composts were then added to the soil over 55days. The model calculates the proportion of biogenic and physically bound residues in the non-extractable compartment of PAHs at the end of the compost incubation to feed the initial conditions of the model for soil amended with composts. For most of the treatments, a single parameter set enabled to simulate the observed dynamics of PAHs adequately for all the amended soil treatments using a Bayesian approach. However, for fluoranthene, different parameters that were able to simulate the growth of a specific microbial biomass had to be considered for mature compost. Processes that occurred before the compost application to the soil strongly influenced the fate of PAHs in the soil. Our results showed that the PAH dissipation during compost incubation was higher in mature composts because of the higher specific microbial activity, while the PAH dissipation in amended soil was higher in the non-mature compost because of the higher availability of PAHs and the higher co-metabolic microbial activity.

In situ long-term modeling of phenanthrene dynamics in an aged contaminated soil using the VSOIL platform.

Management and remediation actions of polycyclic aromatic hydrocarbons (PAH) contaminated sites require an accurate knowledge of the dynamics of these chemicals in situ under real conditions. Here we developed, under the Virtual Soil Platform, a global model for PAH that describes the principal physical and biological processes controlling the dynamics of PAH in soil under real climatic conditions. The model was applied first to simulate the observed dynamics of phenanthrene in situ field experimental plots of industrial contaminated soil. In a second step, different long-term scenarios of climate change or bioavailability increase were applied. Our results show that the model can adequately predict the fate of phenanthrene and can contribute to clarify some of unexplored aspects regarding the behavior of phenanthrene in soil like its degradation mechanism and stabilization. Tested prospective scenarios showed that bioavailability increase (through the addition of solvent or surfactants) resulted in significant increase in substrate transfer rate, hence reducing remediation time. Regarding climate change effect, the model indicated that phenanthrene concentration decreased by 54% during 40years with a natural attenuation and both scenarios chosen for climatic boundaries provided very similar results.

Using a Bayesian approach to improve and calibrate a dynamic model of polycyclic aromatic hydrocarbons degradation in an industrial contaminated soil.

A novel kinetics model that describes the dynamics of polycyclic aromatic hydrocarbons (PAHs) in contaminated soils is presented. The model includes two typical biodegradation pathways: the co-metabolic pathway using pseudo first order kinetics and the specific biodegradation pathway modeled using Monod kinetics. The sorption of PAHs to the solid soil occurs through bi-phasic fist order kinetics, and two types of non-extractible bounded residues are considered: the biogenic and the physically sequestrated into soil matrix. The PAH model was developed in Matlab, parameterized and tested successfully on batch experimental data using a Bayesian approach (DREAM). Preliminary results led to significant model simplifications. They also highlighted that the specific biodegradation pathway was the most efficient at explaining experimental data, as would be expected for an old industrial contaminated soil. Global analysis of sensitivity showed that the amount of PAHs ultimately degraded was mostly governed by physicochemical interactions rather than by biological activity.

Speciation study in the sulfamethoxazole-copper-pH-soil system: implications for retention prediction.

Sulfamethoxazole (SMX) is a persistent sulfonamide antibiotic drug used in the veterinary and human medical sectors and is widely detected in natural waters. To better understand the reactive transport of this antibiotic in soil, the speciation of the SMX-Cu(II)-H(+) system in solution and the combined sorption of these components in a natural vineyard soil were investigated by acid-base titrimetry and infrared spectroscopy. Cu(II) is considered to represent a strongly complexing trace element cation (such as Cd(2+), Zn(2+), Pb(2+), Ni(2+), etc.) in comparison to more prevalent but more weakly binding cations (such as Ca(2+) and Mg(2+)). Titrimetric studies showed that, relative to other antibiotics, such as tetracycline, SMX is a weak copper chelating agent and a weak soil sorbent at the soil pH (pH6). However, the sorption of SMX in soil increases strongly (by a factor of 6) in the presence of copper. This finding strongly supports the hypothetical formation of ternary SMX-Cu-soil complexes, especially considering that copper is dominantly sorbed in a state at pH6. The data were successfully modelled with PhreeqC assuming the existence of binary and ternary surface complexes in equilibrium with aqueous Cu, SMX and Cu-SMX complexes. It is thought that other strongly complexing cations present on the surface of reactive organic and mineral soil phases, such as Cd(II), Ni(II), Zn(II), Pb(II), Fe(II/III), Mn(II/IV) and Al(III), affect the solid/solution partitioning of SMX. This study thus suggests that surface-adsorbed cations significantly increase the sorption of SMX.