Spreading livestock manure as fertilizer on farmlands is a widespread practice. It represents the major source of heavy metal(loid)s (HM) input in agricultural soils. Since zinc (Zn) is present at high concentrations in manure, it poses special environmental concerns related to phytotoxicity, groundwater contamination, and introduction in the food chain. Therefore, investigations on the fate and behavior of manure-borne Zn, when it enters the soil environment, are necessary to predict the environmental effects. Nevertheless, long-term field studies assessing Zn speciation in the organic waste matrix, as well as within the soil after manure application, are lacking. This study was designed to fill this gap. Using SEM-EDS and XAS analysis, we reported the following new results: (i) ZnS made up 100% of the Zn speciation in the pig slurry (the highest proportion of ZnS ever observed in organic waste); and (ii) ZnS aggregates were about 1-?m diameter (the smallest particle size ever reported in pig slurry). Moreover, the pig slurry containing ZnS was spread on the soil over an 11-year period, totaling 22 applications, and the resulting Zn speciation within the amended soil was analyzed. Surprisingly, ZnS, i.e. the only species responsible for a nearly 2-fold increase in the Zn concentration within the amended soil, was not detected in this soil. Based on SEM-EDS and XAS observations, we put forward the hypothesis that Zn in the pig slurry consisted of nano-sized ZnS crystallites that further aggregated. The low stability of ZnS nanoparticles within oxic and complex environments such as the studied soil was the key explanation for the radical change in pig slurry-borne Zn speciation after long-term amendments. (Résumé d'auteur)

Spreading livestock manure as fertilizer on farmlands is a widespread practice. It represents the major source of heavy metal(loid)s (HM) input in agricultural soils. Since zinc (Zn) is present at high concentrations in manure, it poses special environmental concerns related to phytotoxicity, groundwater contamination, and introduction in the food chain. Therefore, investigations on the fate and behavior of manure-borne Zn, when it enters the soil environment, are necessary to predict the environmental effects. Nevertheless, long-term field studies assessing Zn speciation in the organic waste matrix, as well as within the soil after manure application, are lacking. This study was designed to fill this gap. Using SEM-EDS and XAS analysis, we reported the following new results: (i) ZnS made up 100% of the Zn speciation in the pig slurry (the highest proportion of ZnS ever observed in organic waste); and (ii) ZnS aggregates were about 1-μm diameter (the smallest particle size ever reported in pig slurry). Moreover, the pig slurry containing ZnS was spread on the soil over an 11-year period, totaling 22 applications, and the resulting Zn speciation within the amended soil was analyzed. Surprisingly, ZnS, i.e. the only species responsible for a nearly 2-fold increase in the Zn concentration within the amended soil, was not detected in this soil. Based on SEM-EDS and XAS observations, we put forward the hypothesis that Zn in the pig slurry consisted of nano-sized ZnS crystallites that further aggregated. The low stability of ZnS nanoparticles within oxic and complex environments such as the studied soil was the key explanation for the radical change in pig slurry-borne Zn speciation after long-term amendments.

International audience | Abstract Spreading livestock manure as fertilizer on farmlands is a widespread practice. It represents the major source of heavy metal(loid)s (HM) input in agricultural soils. Since zinc (Zn) is present at high concentrations in manure, it poses special environmental concerns related to phytotoxicity, groundwater contamination, and introduction in the food chain. Therefore, investigations on the fate and behavior of manure-borne Zn, when it enters the soil environment, are necessary to predict the environmental effects. Nevertheless, long-term field studies assessing Zn speciation in the organic waste matrix, as well as within the soil after manure application, are lacking. This study was designed to fill this gap. Using SEM-EDS and \XAS\ analysis, we reported the following new results: (i) ZnS made up 100% of the Zn speciation in the pig slurry (the highest proportion of ZnS ever observed in organic waste); and (ii) ZnS aggregates were about 1-μm diameter (the smallest particle size ever reported in pig slurry). Moreover, the pig slurry containing ZnS was spread on the soil over an 11-year period, totaling 22 applications, and the resulting Zn speciation within the amended soil was analyzed. Surprisingly, ZnS, i.e. the only species responsible for a nearly 2-fold increase in the Zn concentration within the amended soil, was not detected in this soil. Based on SEM-EDS and \XAS\ observations, we put forward the hypothesis that Zn in the pig slurry consisted of nano-sized ZnS crystallites that further aggregated. The low stability of ZnS nanoparticles within oxic and complex environments such as the studied soil was the key explanation for the radical change in pig slurry-borne Zn speciation after long-term amendments.

Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economi

Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economic conditions for developing alternative agricultural systems or targeting mitigation measures. Our integrated assessment of these scenarios combines the calculation of spatialized environmental indicators with integrated bio-economic modeling. The latter is achieved by a combined use of Soil and Water Assessment Tool (SWAT) modeling with our own purpose-built land use generator module (Generator of Land Use version 2 (GenLU2)) and an economic model developed using General Algebraic Modeling System (GAMS) for cost-effectiveness assessment. This integrated approach is applied to two embedded catchment areas (total area of 360,000 ha) within the Charente river basin (SW France). Our results show that it is possible to differentiate scenarios based on their effectiveness, represented by either evolution of pressure (agro-environmental indicators) or transport into waters (pesticide concentrations). By analyzing the implementation costs borne by farmers, it is possible to identify the most cost-effective scenarios at sub-basin and other aggregated levels (WFD hydrological entities, sensitive areas). Relevant results and indicators are fed into a specifically designed database. Data warehousing is used to provide analyses and outputs at all thematic, temporal, or spatial aggregated levels, defined by the stakeholders (type of crops, herbicides, WFD areas, years), using Spatial On-Line Analytical Processing (SOLAP) tools. The aim of this approach is to allow public policy makers to make more informed and reasoned decisions when managing sensitive areas and/or implementing mitigation measures.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]DTAM [Axe_IRSTEA]DTAM-QT2-ADAPTATION [TR2_IRSTEA]SYNERGIE | International audience | Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economic conditions for developing alternative agricultural systems or targeting mitigation measures. Our integrated assessment of these scenarios combines the calculation of spatialized environmental indicators with integrated bio-economic modeling. The latter is achieved by a combined use of Soil and Water Assessment Tool (SWAT) modeling with our own purpose-built land use generator module (Generator of Land Use version 2 (GenLU2)) and an economic model developed using General Algebraic Modeling System (GAMS) for cost-effectiveness assessment. This integrated approach is applied to two embedded catchment areas (total area of 360,000 ha) within the Charente river basin (SW France). Our results show that it is possible to differentiate scenarios based on their effectiveness, represented by either evolution of pressure (agro-environmental indicators) or transport into waters (pesticide concentrations). By analyzing the implementation costs borne by farmers, it is possible to identify the most cost-effective scenarios at sub-basin and other aggregated levels (WFD hydrological entities, sensitive areas). Relevant results and indicators are fed into a specifically designed database. Data warehousing is used to provide analyses and outputs at all thematic, temporal, or spatial aggregated levels, defined by the stakeholders (type of crops, herbicides, WFD areas, years), using Spatial On-Line Analytical Processing (SOLAP) tools. The aim of this approach is to allow public policy makers to make more informed and reasoned decisions when managing sensitive areas and/or implementing mitigation measures.

Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economic conditions for developing alternative agricultural systems or targeting mitigation measures. Our integrated assessment of these scenarios combines the calculation of spatialized environmental indicators with integrated bio-economic modeling. The latter is achieved by a combined use of Soil and Water Assessment Tool (SWAT) modeling with our own purpose-built land use generator module (Generator of Land Use version 2 (GenLU2)) and an economic model developed using General Algebraic Modeling System (GAMS) for cost-effectiveness assessment. This integrated approach is applied to two embedded catchment areas (total area of 360,000 ha) within the Charente river basin (SW France). Our results show that it is possible to differentiate scenarios based on their effectiveness, represented by either evolution of pressure (agro-environmental indicators) or transport into waters (pesticide concentrations). By analyzing the implementation costs borne by farmers, it is possible to identify the most cost-effective scenarios at sub-basin and other aggregated levels (WFD hydrological entities, sensitive areas). Relevant results and indicators are fed into a specifically designed database. Data warehousing is used to provide analyses and outputs at all thematic, temporal, or spatial aggregated levels, defined by the stakeholders (type of crops, herbicides, WFD areas, years), using Spatial On-Line Analytical Processing (SOLAP) tools. The aim of this approach is to allow public policy makers to make more informed and reasoned decisions when managing sensitive areas and/or implementing mitigation measures.

Persistent organic pollutants like organochlorine pesticides continue to contaminate large areas worldwide raising questions concerning their management. We designed and tested a method to link soil and water pollution in the watershed of the Galion River in Martinique. We first estimated the risk of soil contamination by chlordecone by referring to past use of land for banana cultivation and took 27 soil samples. We then sampled surface waters at 39 points and groundwater at 16 points. We tested three hypotheses linked to the source of chlordecone pollution at the watershed scale: (i) soils close to the river, (ii) soils close to the sampling point, (iii) throughout the sub-watershed generated at the sampling point. Graphical and statistical analysis showed that contamination of the river increased when it passed through an area with contaminated plots and decreased when it passed through area not contaminated by chlordecone. Modeling showed that the entire surface area of the watershed contributed to river pollution, suggesting that the river was mainly being contaminated by the aquifers and groundwater flows. Our method proved to be a reliable way to identify areas polluted by chlordecone at the watershed scale and should help stakeholders focus their management actions on both hot spots and the whole watershed. (Résumé d'auteur)

Persistent organic pollutants like organochlorine pesticides continue to contaminate large areas worldwide raising questions concerning their management. We designed and tested a method to link soil and water pollution in the watershed of the Galion River in Martinique. We first estimated the risk of soil contamination by chlordecone by referring to past use of land for banana cultivation and took 27 soil samples. We then sampled surface waters at 39 points and groundwater at 16 points. We tested three hypotheses linked to the source of chlordecone pollution at the watershed scale: (i) soils close to the river, (ii) soils close to the sampling point, (iii) throughout the sub-watershed generated at the sampling point. Graphical and statistical analysis showed that contamination of the river increased when it passed through an area with contaminated plots and decreased when it passed through area not contaminated by chlordecone. Modeling showed that the entire surface area of the watershed contributed to river pollution, suggesting that the river was mainly being contaminated by the aquifers and groundwater flows. Our method proved to be a reliable way to identify areas polluted by chlordecone at the watershed scale and should help stakeholders focus their management actions on both hot spots and the whole watershed.