Organic micropollutants (OMPs) are widely detected in surface waters. So far, the removal processes of these compounds in situ in river systems are not yet totally revealed. In this study, a combined monitoring and modelling approach was applied to determine the behaviour of 1-H benzotriazole, carbamazepine, diclofenac and galaxolide in a small river system. Sewage treatment plant effluents and the receiving waters of the river Swist were monitored in 9 dry weather sampling campaigns (precipitation < 1 mm on the sampling day itself and <5 mm total precipitation two days before the sampling) during different seasons over a period of 3 years. With the results gained through monitoring, mass balances have been calculated to assess fate in the river. With the DWA Water Quality Model, OMP concentrations in the river were successfully simulated with OMP characteristics gained through literature studies. No removal was determined for 1-H benzotriazole and carbamazepine, whereas diclofenac showed removal that coincided with light intensity. Moreover, modelling based on light sensitivity of diclofenac also suggested relevant degradation at natural light conditions. These two approaches suggest removal by photodegradation. The highest removal in the river was detected for galaxolide, presumably due to volatilisation, sorption and biodegradation. Furthermore, short-term concentration variability in the river was determined, showing that daily concentration patterns are influenced by dynamics of sewage treatment plant effluent volumes and removal processes in the river.

Permeable reactive bio-barriers (Bio-PRBs) are a new and developing technique for in situ remediation of groundwater contamination. Some remediation technologies have often been impeded by insufficient understanding of contaminant transport and transformation in the subsurface environment. Therefore, advanced knowledge in contaminant transport and reactions in Bio-PRBs will be crucial to the successful practical application of this technique. A two-dimensional reaction model C1 was developed for predicting the multi-path chain kinetic reaction of 1,1,1-trichloroethane (1,1,1-TCA) in Bio-PRBs. This study demonstrates that model C1 is able to predict the 1,1,1-TCA breakthrough time and rapidly evaluate the Bio-PRBs retardation performance. The results show that microbial growth and immobilization are the key factors that affect the retardation and remediation performance of Bio-PRBs. The free growth of microorganisms had significant negative effects on hydraulic conductivity (K) in the zero-valent iron (ZVI) region of free microorganism Bio-PRBs (FM-PRBs). The total head loss in the FM-PRB was 9.0 cm, which was significantly greater than the head loss (6.5 cm) of immobilized microorganism Bio-PRBs (IM-PRBs). Compared to ZVI-PRBs and FM-PRBs, the numerical simulation results reveal that microbial immobilization significantly improves the remediation performance of IM-PRBs by 550.9% and 32.7%, respectively. The dual effect of microorganisms leads to significant differences in the 1,1,1-TCA and daughter products (1,1-dichloroethane, 1,1-dichloroethene, chloroethane and vinyl chloride) contaminant-plume evolution between FM-PRBs and IM-PRBs. In addition, model C1 can be utilized to design standard Bio-PRBs for real site of 1,1,1-TCA contanminated groundwater. To meet the safety standard of groundwater as potable water, the width of IM-PRBs needs to be increased by 24 cm. However, in FM-PRBs, the width needs to be increased by 42 cm. Therefore, IM-PRBs save costs significantly. This work has successfully used a model to optimize Bio-PRBs and to predict 1,1,1-TCA and daughter products contaminant-plume evolution in different Bio-PRBs.

Composting has been demonstrated to be effective in degrading organic pollutants (OP) whose behaviour depends on the composting conditions, the microbial populations activated and interactions with organic matters. The fate of OP during composting involves complex mechanisms and models can be helpful tools for educational and scientific purposes, as well as for industrialists who want to optimise the composting process for OP elimination. A COP-Compost model, which couples an organic carbon (OC) module and an organic pollutant (OP) module and which simulates the changes of organic matter, organic pollutants and the microbial activities during the composting process, has been proposed and calibrated for a first set of OP in a previous study. The objectives of the present work were (1) to introduce the COP-Compost model from its convenient interface to a potential panel of users, (2) to show the variety of OP that could be simulated, including the possibility of choosing between degradation through co-metabolism or specific metabolism and (3) to show the effect of the initial characteristics of organic matter quality and its microbial biomass on the simulated results of the OP dynamic. In the model, we assumed that the pollutants can be adsorbed on organic matter according to the biochemical quality of the OC and that the microorganisms can degrade the pollutants at the same time as they degrade OC (by co-metabolism). A composting experiment describing two different 14C-labelled organic pollutants, simazine and pyrene, were chosen from the literature because the four OP fractions simulated in the model were measured during the study (the mineralised, soluble, sorbed and non-extractable fractions). Except for the mineralised fraction of simazine, a good agreement was achieved between the simulated and experimental results describing the evolution of the different organic fractions. For simazine, a specific biomass had to be added. To assess the relative importance of organic matter dynamics on the organic pollutants’ behaviour, a sensitivity analysis was conducted. The sensitivity analysis demonstrated that the parameters associated with organic matter dynamics and its initial microbial biomass greatly influenced the evolution of all the OP fractions, although the initial biochemical quality of the OC did not have a significant impact on the OP evolution

International audience | The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO). STICS-MACRO has the advantage of being able to simulate pesticides fate in complex cropping systems and to consider some agricultural practices such as fertilization, mulch, or crop residues management, which cannot be accounted for with MACRO. The performance of STICS-MACRO was tested, without calibration, from measurements done in two French experimental sites with contrasted soil and climate properties. The prediction of water percolation and pesticides concentrations with STICS-MACRO was satisfactory, but it varied with the pedoclimatic context. The performance of STICS-MACRO was shown to be similar or better than that of MACRO. The improvement of the simulation of crop growth allowed better estimate of crop transpiration therefore of water balance. It also allowed better estimate of pesticide interception by the crop which was found to be crucial for the prediction of pesticides concentrations in water. STICS-MACRO is a new promising tool to improve the assessment of the environmental risks of pesticides used in cropping systems.

[Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]TED | International audience | The nitrifying/denitrifying activated sludge process removes several micropollutants from wastewater by sorption onto sludge and/or biodegradation. The objective of this paper is to propose and evaluate a lab-scale experimental strategy for the determination of partition coefficient and biodegradation constant for micropollutant with an objective of modelling their removal. Four pharmaceutical compounds (ibuprofen, atenolol, diclofenac and fluoxetine) covering a wide hydrophobicity range (log Kow from 0.16 to 4.51) were chosen. Dissolved and particulate concentrations were monitored for 4 days, inside two reactors working under aerobic and anoxic conditions, and under different substrate feed conditions (biodegradable carbon and nitrogen). We determined the mechanisms responsible for the removal of the target compounds: (i) ibuprofen was biodegraded, mainly under aerobic conditions by cometabolism with biodegradable carbon, whereas anoxic conditions suppressed biodegradation; (ii) atenolol was biodegraded under both aerobic and anoxic conditions (with a higher biodegradation rate under aerobic conditions), and cometabolism with biodegradable carbon was the main mechanism; (iii) diclofenac and fluoxetine were removed by sorption only. Finally, the abilities of our strategy were evaluated by testing the suitability of the parameters for simulating effluent concentrations and removal efficiency at a full-scale plant.

International audience | Preservation of biodiversity and ecosystem services is critical for sustainable development and human well-being. However, an unprecedented erosion of biodiversity is observed and the use of plant protection products (PPP) has been identified as one of its main causes. In this context, at the request of the French Ministries responsible for the Environment, for Agriculture and for Research, a panel of 46 scientific experts ran a nearly 2-year-long (2020-2022) collective scientific assessment (CSA) of international scientific knowledge relating to the impacts of PPP on biodiversity and ecosystem services. The scope of this CSA covered the terrestrial, atmospheric, freshwater, and marine environments (with the exception of groundwater) in their continuity from the site of PPP application to the ocean, in France and French overseas territories, based on international knowledge produced on or transposable to this type of context (climate, PPP used, biodiversity present, etc.). Here, we provide a brief summary of the CSA's main conclusions, which were drawn from about 4500 international publications. Our analysis finds that PPP contaminate all environmental matrices, including biota, and cause direct and indirect ecotoxicological effects that unequivocally contribute to the decline of certain biological groups and alter certain ecosystem functions and services. Levers for action to limit PPP-driven pollution and effects on environmental compartments include local measures from plot to landscape scales and regulatory improvements. However, there are still significant gaps in knowledge regarding environmental contamination by PPPs and its effect on biodiversity and ecosystem functions and services. Perspectives and research needs are proposed to address these gaps.

Fate and effect of pollutants in rivers: from analysis to modeling

Air pollution is a major global concern in urban areas and it is considered the greatest environmental risk to health. Nature-based solutions (NBS) can help improve air quality and reduce the urban heat island effect. The impacts of urban vegetation on air quality and ambient temperature depend on many factors, such as vegetation type, location, pollutants, climate conditions and topography. Therefore, the implementation of NBS needs to be tailored for each city. Within the context of the H2020 UNaLab project, the main objective of this work is to assess the potential of NBS to improve air quality across three European cities with different climates: (i) Eindhoven, The Netherlands; (ii) Tampere, Finland; and (iii) Genova, Italy. The WRF-CHEM model was applied for the hottest week in a present climate reference year. The baseline case (without NBS) and two NBS scenarios were simulated for each city. These scenarios (green roofs and green parks) were implemented in the model by modifying the land-use type and the emissions of the model grid cells. According to the model results, the city that least benefited from NBS was Tampere with an average reduction of 5% in surface temperature, and 1% in nitrogen dioxide (NO2) and ozone (O3) concentrations. Temperature-wise Genova and Eindhoven had similar results, approximately 6% reduction, while Genova showed the largest improvement in NO2 (12%). These results indicate that NBS are more effective in high temperature and high air pollution cities, such as Genova. Moreover, this study reinforces the importance of studying case-specific solutions, considering environmental characteristics and challenges.

A new mercury (Hg) evasion model for the Adriatic Sea was developed accounting for the ocean mixed layer depth in order to decrease Hg depletion at the surface. Previously modelled airborne Hg species and measured Hg in the ocean were used. Simulations were run using one- and two-way coupled atmosphere-ocean models. Discrepancies in evasion between the applied coupling schemes were shown to be insignificant. The model was evaluated by applying various wind parameterisations and diffusive coefficient formulae. Relatively high discrepancies among the applied methods were observed. The results of a shorter simulation were extrapolated over a one-year period by applying a measurement-based adaptation. We obtained good agreement with previously published data on Hg evasion in the entire Mediterranean area, thus confirming the suitability of the new model for Hg evasion simulations. Model computations performed for the Adriatic Sea resulted in levels of evasion approximately two times lower than previously estimated.

Marine debris' transboundary nature and new strategies to identify sources and sinks in coastal areas were investigated along the Paranaguá estuarine gradient (southern Brazil), through integration of hydrodynamic modelling, ground truthing estimates and regressive vector analysis. The simulated release of virtual particles in different parts of the inner estuary suggests a residence time shorter than 5days before being exported through the estuary mouth (intermediate compartment) to the open ocean. Stranded litter supported this pathway, with beaches in the internal compartment presenting proportionally more items from domestic sources, while fragmented items with unknown sources were proportionally more abundant in the oceanic beaches. Regressive vector analysis reinforced the inner estuarine origin of the stranded litter in both estuarine and oceanic beaches. These results support the applicability of simple hydrodynamic models to address marine debris' transboundary issues in the land-sea transition zone, thus supporting an ecosystem transboundary (and not territorial) management approach.