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Air gasification of Solid Recovered Fuels (SRF) from wood, tire, plastics and sewage sludge has been performed in a pilot fixed bed reactor. As wastes contain pollutants precursors, it is of great interest regarding technical and environmental aspects to study their behavior in air gasification. Five fuels have been studied: Poplar, SRF wood, and three different mixtures of SRF wood and 20% of either tire (mix A), or plastics (mix B) or sewage sludge (mix C). After confirming their capacity of substituting raw wood in order to produce synthetic gas (syngas), emissions analyses have been performed on syngas, condensable matter and remaining char. A focus on sulfur, nitrogen and heavy metals brought to light differences and similarities between different SRF and raw wood. Proceedings of the 26th European Biomass Conference and Exhibition, 14-17 May 2018, Copenhagen, Denmark, pp. 478-485

Air gasification of Solid Recovered Fuels (SRF) from wood, tire, plastics and sewage sludge has been performed in a pilot fixed bed reactor. As wastes contain pollutants precursors, it is of great interest regarding technical and environmental aspects to study their behavior in air gasification. Five fuels have been studied: Poplar, SRF wood, and three different mixtures of SRF wood and 20% of either tire (mix A), or plastics (mix B) or sewage sludge (mix C). After confirming their capacity of substituting raw wood in order to produce synthetic gas (syngas), emissions analyses have been performed on syngas, condensable matter and remaining char. A focus on sulfur, nitrogen and heavy metals brought to light differences and similarities between different SRF and raw wood. Proceedings of the 26th European Biomass Conference and Exhibition, 14-17 May 2018, Copenhagen, Denmark, pp. 478-485

AbstractPeatlands cover only 3–4% of the Earth’s surface, but they store nearly 30% of global soil carbon stock. This significant carbon store is under threat as peatlands continue to be degraded at alarming rates around the world. It has prompted countries worldwide to establish regulations to conserve and reduce emissions from this carbon rich ecosystem. For example, the EU has implemented new rules that mandate sustainable management of peatlands, critical to reaching the goal of carbon neutrality by 2050. However, a lack of information on the extent and condition of peatlands has hindered the development of national policies and restoration efforts. This paper reviews the current state of knowledge on mapping and monitoring peatlands from field sites to the globe and identifies areas where further research is needed. It presents an overview of the different methodologies used to map peatlands in nine countries, which vary in definition of peat soil and peatland, mapping coverage, and mapping detail. Whereas mapping peatlands across the world with only one approach is hardly possible, the paper highlights the need for more consistent approaches within regions having comparable peatland types and climates to inform their protection and urgent restoration. The review further summarises various approaches used for monitoring peatland conditions and functions. These include monitoring at the plot scale for degree of humification and stoichiometric ratio, and proximal sensing such as gamma radiometrics and electromagnetic induction at the field to landscape scale for mapping peat thickness and identifying hotspots for greenhouse gas (GHG) emissions. Remote sensing techniques with passive and active sensors at regional to national scale can help in monitoring subsidence rate, water table, peat moisture, landslides, and GHG emissions. Although the use of water table depth as a proxy for interannual GHG emissions from peatlands has been well established, there is no single remote sensing method or data product yet that has been verified beyond local or regional scales. Broader land-use change and fire monitoring at a global scale may further assist national GHG inventory reporting. Monitoring of peatland conditions to evaluate the success of individual restoration schemes still requires field work to assess local proxies combined with remote sensing and modeling. Long-term monitoring is necessary to draw valid conclusions on revegetation outcomes and associated GHG emissions in rewetted peatlands, as their dynamics are not fully understood at the site level. Monitoring vegetation development and hydrology of restored peatlands is needed as a proxy to assess the return of water and changes in nutrient cycling and biodiversity.

AbstractPeatlands cover only 3–4% of the Earth’s surface, but they store nearly 30% of global soil carbon stock. This significant carbon store is under threat as peatlands continue to be degraded at alarming rates around the world. It has prompted countries worldwide to establish regulations to conserve and reduce emissions from this carbon rich ecosystem. For example, the EU has implemented new rules that mandate sustainable management of peatlands, critical to reaching the goal of carbon neutrality by 2050. However, a lack of information on the extent and condition of peatlands has hindered the development of national policies and restoration efforts. This paper reviews the current state of knowledge on mapping and monitoring peatlands from field sites to the globe and identifies areas where further research is needed. It presents an overview of the different methodologies used to map peatlands in nine countries, which vary in definition of peat soil and peatland, mapping coverage, and mapping detail. Whereas mapping peatlands across the world with only one approach is hardly possible, the paper highlights the need for more consistent approaches within regions having comparable peatland types and climates to inform their protection and urgent restoration. The review further summarises various approaches used for monitoring peatland conditions and functions. These include monitoring at the plot scale for degree of humification and stoichiometric ratio, and proximal sensing such as gamma radiometrics and electromagnetic induction at the field to landscape scale for mapping peat thickness and identifying hotspots for greenhouse gas (GHG) emissions. Remote sensing techniques with passive and active sensors at regional to national scale can help in monitoring subsidence rate, water table, peat moisture, landslides, and GHG emissions. Although the use of water table depth as a proxy for interannual GHG emissions from peatlands has been well established, there is no single remote sensing method or data product yet that has been verified beyond local or regional scales. Broader land-use change and fire monitoring at a global scale may further assist national GHG inventory reporting. Monitoring of peatland conditions to evaluate the success of individual restoration schemes still requires field work to assess local proxies combined with remote sensing and modeling. Long-term monitoring is necessary to draw valid conclusions on revegetation outcomes and associated GHG emissions in rewetted peatlands, as their dynamics are not fully understood at the site level. Monitoring vegetation development and hydrology of restored peatlands is needed as a proxy to assess the return of water and changes in nutrient cycling and biodiversity.

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.