A framework for participatory impact assessment : involving stakeholders in European policy making, a case study of land use change in Malta

A Framework for Participatory Impact Assessment is presented for use within European land use policy impact assessment. The context and rationale for the development of the Framework are outlined, both in the context of European policy making and within a project called "Sustainability Impact Assessment: Tools for Environmental, Social and Economic Effects of Multifunctional Land Use in European Regions". A detailed description of the sequence of methods that make up the Framework is provided, followed by illustrations and details of the practical application and results from a case study in Malta, where the Framework was used to carry out an impact assessment of biodiversity policies. After reporting on the reflections of the research team and valuable feedback provided by Maltese stakeholders, the Framework’s ability to enhance the quality, credibility and legitimacy of European policy impact assessment is discussed.peer-reviewe

Locals and professionals : participatory approaches to protected area management in Britain and Peru

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Ex ante impact assessment of policies affecting land use, Part B: application of the analytical framework

The use of science-based tools for impact assessment has increasingly gained focus in addressing the complexity of interactions between environment, society, and economy. For integrated assessment of policies affecting land use, an analytical framework was developed. The aim of our work was to apply the analytical framework for specific scenario cases and in combination with quantitative and qualitative application methods. The analytical framework was tested for two cases involving the ex ante impact assessment of: (1) a European Common Agricultural Policy (CAP) financial reform scenario employing a modeling approach and combined with a comprehensive indicator analysis and valuation; and (2) a regional bioenergy policy scenario, employing a fully participatory approach. The results showed that European land use in general is less sensitive to changes in the Common Agricultural Policy, but in the context of regions there can be significant impacts on the functions of land use. In general, the implementation of the analytical framework for impact assessment proved to be doable with both methods, i.e., with the quantitative modeling and with the qualitative participatory approach. A key advantage of using the system of linked quantitative models is that it makes possible the simultaneous consideration of all relevant sectors of the economy without abstaining from a great level of detail for sectors of particular interest. Other advantages lie in the incontestable character of the results. Based on neutral, existing data with a fixed set of settings and regions, an absolute comparability and reproducibility throughout Europe can be maintained. Analyzing the pros and cons of both approaches showed that they could be used complementarily rather than be seen as competing alternatives

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6 $\times$ 6 $\times$ 6 m$^3$ liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6x6x6m3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

International audienceLiquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation