The Black Sea receives increasing amounts of microplastics from rivers. In this study, we explore options to reduce future river export of microplastics to the Black Sea. We develop five scenarios with different reduction options and implement them to a Model to Assess River Inputs of pollutaNts to seA (MARINA-Global) for 107 sub-basins. Today, European rivers draining into the Black Sea export over half of the total microplastics. In 2050, Asian rivers draining into the sea will be responsible for 34–46% of microplastic pollution. Implemented advanced treatment will reduce point-source pollution. Reduced consumption or more collection of plastics will reduce 40% of microplastics in the sea by 2050. In the optimistic future, sea pollution is 84% lower than today when the abovementioned reduction options are combined. Reduction options affect the share of pollution sources. Our insights could support environmental policies for a zero pollution future of the Black Sea.

The Black Sea receives increasing amounts of microplastics from rivers. In this study, we explore options to reduce future river export of microplastics to the Black Sea. We develop five scenarios with different reduction options and implement them to a Model to Assess River Inputs of pollutaNts to seA (MARINA-Global) for 107 sub-basins. Today, European rivers draining into the Black Sea export over half of the total microplastics. In 2050, Asian rivers draining into the sea will be responsible for 34–46% of microplastic pollution. Implemented advanced treatment will reduce point-source pollution. Reduced consumption or more collection of plastics will reduce 40% of microplastics in the sea by 2050. In the optimistic future, sea pollution is 84% lower than today when the abovementioned reduction options are combined. Reduction options affect the share of pollution sources. Our insights could support environmental policies for a zero pollution future of the Black Sea.

International audience

The insecticide ¹⁴C-chlorpyrifos was found mineralized in a Tunisian soil with repeated exposure to it. From this soil, a bacterial strain was isolated that was able to grow in a minimal salt medium (MSM) supplemented with 25 mg L⁻¹ of chlorpyrifos. It was characterized as Serratia rubidaea strain ABS 10 using morphological and biochemical analyses, as well as 16S rRNA sequencing. In a liquid culture, the S. rubidaea strain ABS 10 was able to dissipate chlorpyrifos almost entirely within 48 h of incubation. Although the S. rubidaea strain ABS 10 was able to grow in an MSM supplemented with chlorpyrifos and dissipate it in a liquid culture, it was not able to mineralize ¹⁴C-chlorpyrifos. Therefore, it can be concluded that the dissipation capability of this bacteria might be attributed to its capacity to adsorb CHL. It can also be ascribed to other reasons such as the formation of biogenic non-extractable residues. In both non-sterile and sterile soil inoculated with S. rubidaea strain ABS 10, chlorpyrifos was more rapidly dissipated than in controls with DT₅₀ of 1.38 and 1.05 days, respectively.

International audience | Effect-directed analysis (EDA) aims at identifying the compound(s) responsible for toxicity in a complex environmental sample where several dozens of contaminants can be present. In this study, we used an environmental mixture extracted from the Polar Organic Chemical Integrative Sampler (POCIS) previously immersed downstream a landfill (River Ponteils, South West France), to perform an EDA approach using a microalgal bioassay based on the photosynthetic capacities of diatom (Nitzschia palea) cultures. Adverse effects on photosynthetic capacities were recorded when algae were exposed to the entire POCIS extract (> 85% inhibition at the highest concentration tested). This result was coherent with the detection of diuron and isoproturon, which were the 2 most concentrated herbicides in the extract. However, the EDA process did not allow pointing out the specific compound(s) responsible for the observed toxicity but rather suggested that multiple compounds were involved in the overall toxicity and caused mixture effects.

Effect-directed analysis (EDA) aims at identifying the compound(s) responsible for toxicity in a complex environmental sample where several dozens of contaminants can be present. In this study, we used an environmental mixture extracted from the Polar Organic Chemical Integrative Sampler (POCIS) previously immersed downstream a landfill (River Ponteils, South West France), to perform an EDA approach using a microalgal bioassay based on the photosynthetic capacities of diatom (Nitzschia palea) cultures. Adverse effects on photosynthetic capacities were recorded when algae were exposed to the entire POCIS extract (> 85% inhibition at the highest concentration tested). This result was coherent with the detection of diuron and isoproturon, which were the 2 most concentrated herbicides in the extract. However, the EDA process did not allow pointing out the specific compound(s) responsible for the observed toxicity but rather suggested that multiple compounds were involved in the overall toxicity and caused mixture effects.

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment.

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

International audience | A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, microorganisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment.

International audience | A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, microorganisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment.

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

International audience | A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, microorganisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment.