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

Dosage concentration and pulsing frequency affect the degradation efficiency in simulated bacterial polycyclic aromatic hydrocarbon-degrading cultures

A major source of anthropogenic polycyclic aromatic hydrocarbon (PAH) inputs into marine environments are diffuse emissions which result in low PAH concentrations in the ocean water, posing a potential threat for the affected ecosystems. However, the remediation of low-dosage PAH contaminations through microbial processes remains largely unknown. Here, we developed a process-based numerical model to simulate batch cultures receiving repeated low-dosage naphthalene pulses compared to the conventionally used one-time high-dosage. Pulsing frequency as well as dosage concentration had a large impact on the degradation efficiency. After 10 days, 99.7%, 97.2%, 86.6%, or 83.5% of the 145 mg L^-1 naphthalene was degraded when given as a one-time high-dosage or in 2, 5, or 10 repeated low-concentration dosages equally spaced throughout the experiment, respectively. If the simulation was altered, giving the system that received 10 pulses time to recover to 99.7%, pulsing patterns affected the degradation of naphthalene. When pulsing 10 days at once per day, naphthalene accumulated following each pulse and if the degradation was allowed to continue until the recovered state was reached, the incubation time was prolonged to 17 days with a generation time of 3.81 days. If a full recovery was conditional before the next pulse was added, the scenario elongated to 55 days and generation time increased to 14.15 days. This indicates that dissolution kinetics dominate biodegradation kinetics, and the biomass concentration of PAH-degrading bacteria alone is not a sufficient indicator for quantifying active biodegradation. Applying those findings to the environment, a one-time input of a high dosage is potentially degraded faster than repeated low-dosage PAH pollution and repeated low-dosage input could lead to PAH accumulation in vulnerable pristine environments. Further research on the overlooked field of chronic low-dosage PAH contamination is necessary.

Fluorescent spectroscopy paired with parallel factor analysis for quantitative monitoring of phenanthrene biodegradation and metabolite formation

Polycyclic aromatic hydrocarbons (PAHs) are a class of environmental contaminants released into the environment from both natural and anthropogenic sources that are associated with carcinogenic, mutagenic, and teratogenic health effects. Many remediation strategies for the treatment of PAH contaminated material, including bioremediation, can lead to the formation of toxic transformation products. Analytical techniques for PAHs and PAH transformation products often require extensive sample preparation including solvent extraction and concentration, chromatographic separation, and mass spectrometry to identify and quantify compounds of interest. Excitation-emission matrix (EEM) fluorescent spectroscopy paired with parallel factor analysis (PARAFAC) is an approach for analyzing PAHs that eliminates the need for extensive sample preparation and separation techniques before analysis. However, this technique has rarely been applied to monitoring PAH biotransformation and formation of PAH metabolites. The objectives of this research were to compare an established targeted analytical method to two-dimensional fluorescent spectroscopy and combined EEM-PARAFAC methods to monitor phenanthrene degradation by a bacterial pure culture, Mycobacterium Strain ELW1, identify and quantify phenanthrene transformation products, and derive kinetic constants for phenanthrene degradation and metabolite formation. Both phenanthrene and its primary transformation product, trans-9,10-dihydroxy-9,10-dihydrophenanthrene, were identified and quantified with the EEM-PARAFAC method. The value of the EEM-PARAFAC method was demonstrated in the superiority of sensitivity and accuracy of quantification to two-dimensional fluorescent spectroscopy. Quantification of targets and derivation of kinetic constants using the EEM-PARAFAC method were validated with an established gas chromatography-mass spectrometry (GC-MS) method. To the authors' knowledge, this is the first study to use an EEM-PARAFAC method to monitor, identify, and quantify both PAH biodegradation and PAH metabolite formation by a bacterial pure culture.

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.

Formation of non-extractable residues as a potentially dominant process in the fate of PAHs in soil: Insights from a combined field and modeling study on the eastern Tibetan Plateau

Whereas non-extractable residue (NER) formation is recognized as an important process affecting the ecological risk of organic contaminants in soils, it is commonly neglected in regional-scale multi-media models assessing chemical environmental fate and risk. We used a combined field and modeling study to elucidate the relative importance of NER formation to the reduction in available organic contaminants compared with fate processes commonly considered in risk assessment models (volatilization, leaching, and biodegradation). Specifically, four polycyclic aromatic hydrocarbons (PAHs), i.e., phenanthrene (Phe), pyrene (Pyr), benzo[a]pyrene (BaP), and benzo[ghi]perylene (BghiP), were spiked and measured in a one-year field pot experiment at four sites with diverse environmental conditions on the eastern Tibetan Plateau. The rate of NER formation was derived as the difference between the overall rate of decline in total-extractable PAH concentrations, obtained by fitting a biphasic first-order model to the measured concentrations, and the sum of the calculated rates of volatilization, leaching, and biodegradation. Our work shows that the total-extractable PAH concentration undergoes a rapid decline and a slow decline, with shorter overall half-lives (especially for BaP and BghiP) than those observed in earlier studies. Generally, NER formation was assessed to be the dominant contributor (64 ± 33%) to the overall decline of PAHs, followed by biodegradation (35 ± 32%); volatilization and leaching were the smallest contributors. In particular, heavier PAHs (i.e. BaP and BghiP) tend to have shorter half-lives in the rapid and the overall decline phase, indicating that the erroneous estimation of environmental fate and risks might be more pronounced for organic contaminants with a large molecular size. The trend of overall decline rates of PAHs displayed a combined effect of NER formation and biodegradation. This work indicates the need to consider NER formation as a process in multi-media models of chemical fate and risk.

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.

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.

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.

Prediction of the Formation of Biogenic Nonextractable Residues during Degradation of Environmental Chemicals from Biomass Yields

Degradation tests with radio or stable isotope labeled compounds enable the detection of the formation of nonextractable residues (NER). In PBT and vPvB assessment, remobilisable NER are considered as a potential risk while biogenic NER from incorporation of labeled carbon into microbial biomass are treated as degradation products. Relationships between yield, released CO₂ (as indicator of microbial activity and mineralization) and microbial growth can be used to estimate the formation of biogenic NER. We provide a new approach for calculation of potential substrate transformation to microbial biomass (theoretical yield) based on Gibbs free energy and microbially available electrons. We compare estimated theoretical yields of biotechnological substrates and of chemicals of environmental concern with experimentally determined yields for validation of the presented approach. A five-compartment dynamic model is applied to simulate experiments of ¹³C-labeled 2,4-D and ibuprofen turnover. The results show that bioNER increases with time, and that most bioNER originates from microbial proteins. Simulations with precalculated input data demonstrate that precalculation of yields reduces the number of fit parameters considerably, increases confidence in fitted kinetic data, and reduces the uncertainty of the simulation results.