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Wildfires have become an increasing threat for Mediterranean ecosystems, due to increasing climate change-induced wildfire activity and changing land management practices. In addition to the initial risk, wildfires can alter the soil in various ways—depending on fire severity—and cause enhanced post-fire erosion. Usually, post-fire erosion studies focus on a short time window and lack the attention for sediment dynamics at larger spatial scales. Yet, these large spatial and temporal scales are fundamental for a better understanding of long-term destructive effects of multiple recurring wildfires on post-fire erosion processes and catchment sediment dynamics. In this study the landscape evolution model LAPSUS was used to simulate erosion and deposition in the 404 km2 Águeda catchment in north-central Portugal over a 41-year (1979–2020) timespan, including eight wildfires each burning >1000 ha. To include variation in fire severity and its impact on the soil, four burn severity classes, represented by the difference normalized burn ratio (dNBR), were parameterized. Although model calibration was difficult due to lack of spatial and temporal measured data, the results show that long-term post-fire net erosion rates were significantly higher in the wildfire scenarios (5.95 ton ha−1 yr−1) compared to those of a non-wildfire scenario (0.58 ton ha−1 yr−1). Furthermore, erosion values increased with burn severity and multiple wildfires increased the overall catchment sediment build-up. Simulated erosion patterns showed great spatial variability, with large deposition and erosion rates inside streams. This variability made it difficult to identify land uses that were most sensitive for post-fire erosion, because some land uses were located in more erosion-sensitive areas (e.g. streams, gullies) or were more affected by high burn severity levels than others. Despite these limitations, LAPSUS performed well on addressing spatial sediment processes and can contribute to pre-fire management strategies, by identifying locations at risk of post-fire erosion.

International audience

The prediction of delayed strains is very important in prestressed concrete structures. Temperature and relative humidity of concrete structures are two important parameters for this prediction and, on site, are varying over time. Based on model code 2010 and superposition principle, we propose an analytical method to take into account these varying temperature and relative humidity. The coupling between delayed strain of concrete and relaxation of stress in prestressing bars are also considered. We validate the proposed method against in-situ measurement on the mockup of VeRCoRs which is a 1/3 scale mockup of a biaxially prestressed confining building. In the end, we discuss the importance of taking into account the coupling between delayed strain and relaxation of stress, the influence of varying temperature on delayed strain of concrete and also the value of Poisson's ratio of drying creep.

International audience; The SUD Provence-Alpes-Côte d'Azur Region in southern France recently redefined its objectives concerning the decarbonization of its territory and especially of its energy system as a response to guidelines specified in different national climate-energy laws and plans, which establish targets to reach a low-carbon scenario by 2050. Thus, a TIMES-SUD PACA bottom-up optimization model representing the energy sector of Région SUD was developed in order to analyze the impact that these policies might have, and to propose alternative policies that might lead the region to achieving its energy transition. The decarbonization of Région SUD presents different challenges than for the rest of France, such as risks to the electricity supply due to a non-looped electricity grid that affects the east of the region, and a high level of renewable potential, but low local energy production. The first results from the model show that with the use of available local renewable resources and a reduction in demand, decarbonization of Région SUD might be possible for some sectors, such as residential and commercial, but that the energy transition of the transport sector will require more accurate policies. NONMENCLATURE Abbreviations AHP SUD PACA's department: Alpes-de-Haute-Provence AM1 SUD PACA's department: Alpes-Maritimes high energy consumption zone AM2 SUD PACA's department: Alpes-Maritimes low energy consumption zone BDR1 SUD PACA's department: Bouches-du-Rhône high energy consumption zone BDR2 SUD PACA's department: Bouches-du-Rhône low energy consumption zone HA SUD PACA's department: Hautes-Alpes VAR1 SUD PACA's department: Var high energy consumption zone VAR2 SUD PACA's department: VAR low energy consumption zone VAUC SUD PACA's department: Vaucluse

International audience; The SUD Provence-Alpes-Côte d'Azur Region in southern France recently redefined its objectives concerning the decarbonization of its territory and especially of its energy system. This was a response to guidelines specified in different climate-energy laws and plans, which establish both national targets for greenhouse gases, energy production, and air quality, and strategies to reach a low-carbon scenario in 2050. In addition, the NOTRe law gives the French regions the necessary competences to develop their own energy system and policies related to other climate topics. Thus, a TIMES-SUD PACA bottom-up optimization model representing the electricity sector of the Région SUD was developed in order to analyze the impact that these policies might have on the decarbonization of the electricity sector. This decarbonization presents specific challenges compared to the rest of France, such as risks for electricity supply due to a non-looped electricity grid (a situation qualified as an electricity peninsula) that affects the east of the region, and a high level of renewable potential, but a low local energy production. First results from the model show that decarbonization of the Région SUD electricity sector is possible involving the use of local available renewable resources.

With growing concerns about climate change, countries are increasing efforts to reduce dependency on fossil energy sources, the major source of C O 2 , by replacing them with cleaner energy sources including bioenergy. In this context, the global bioenergy market has grown massively during the last few decades. In addition, under the aegis of the United Nations Framework Convention on Climate Change (UNFCCC) and the Paris Agreement, 162 countries have already submitted their intended nationally determined contributions (INDCs) to mitigate climate change, including greenhouse gas emissions pledges and action plans. Hence, the effect of these GHG restrictions on the bioenergy sector in the new expected global decarbonized energy system needs to be addressed. In this study, we estimate what role the international climate agreement could play in bioenergy sector expansion using the bottom-up energy system optimization model, TIAM-FR, a TIMES family model from ETSAP/IEA. As results, GHG restrictions promoted global bioenergy supply over the time horizon 2010–2050. In 2050, global biomass supply reaches 131–138 EJ under these climate scenarios, which is more than double biomass supply in the BAU scenario (60 EJ). In final bioenergy consumption, in 2050, only 3–5 EJ is consumed as biofuel in transport sector while 60 EJ of biomass is consumed for different uses in other sectors and more than 40% of total supplied biomass produces heat and electricity.

Seit Beginn der industriellen Revolution im 18. Jahrhundert ist der Wohlstand und die wirtschaftliche Entwicklung fast aller Länder der Erde maßgeblich an die Nutzung fossiler Brennstoffe wie Öl, Kohle oder Gas gekoppelt. Bei deren Verbrennung werden jedoch Treibhausgase wie z.B. Kohlenstoffdioxid (CO2) freigesetzt, die wiederum den anthropogenen Klimawandel forcieren. Da sich CO2 nahezu gleichmäßig in der Atmosphäre verteilt, muss auch die nachhaltige Reduktion im Rahmen einer globalen Klimaschutzstrategie angegangen werden. Dem Elektrizitäts- und Wärmesektor kommt dabei eine tragende Rolle zu, da diesem Sektor ungefähr 50% der weltweiten CO2-Emissionen zuzuschreiben sind. Weitgehende CO2-Minderungsverpflichtungen bedingen jedoch deutliche Veränderungen innerhalb dieses Sektors und haben mittel- und langfristig einen kompletten Strukturwechsel (z.B. Zuwachs Erneuerbarer Energien, Nutzung von Speichertechnologien etc.) zur Folge. Eine Technologie, die beim Übergang zu einem 100% erneuerbaren Stromsektor helfen kann, ist die sogenannte Carbon Capture and Storage Technologie - kurz CCS. Dabei wird in Kohle- oder Gaskraftwerken das im Abgas enthaltene CO2 größtenteils abgeschieden, transportiert und letztendlich in unterirdischen Speichern endgelagert. Insbesondere rasant wachsende Volkswirtschaften wie China und Indien können damit bei der Stromerzeugung auf heimische und billige Brennstoffe wie Steinkohle zurückgreifen und trotzdem Emissionen in diesem Sektor signifikant reduzieren. Vor diesem Hintergrund werden in der vorliegenden Arbeit zunächst der aktuelle Wissensstand zur globalen Erwärmung dargestellt und erforderliche Klimaschutzstrategien zur Eindämmung diskutiert. Eine mögliche Nutzung der CCS-Technologie wird sowohl von den globalen Klimaschutzzielen und –strategien als auch von den jeweiligen nationalen bzw. supranationalen Energie- und Klimaschutzpolitiken beeinflusst. Darauf aufbauend wird die mögliche globale Diffusion der CCS-Technologie im Spannungsfeld von CO2-Reduktionspfaden, etablierten Kraftwerkstechnologien und Erneuerbaren Energien untersucht. Dabei wird ein zweiteiliger Modellansatz verfolgt. Es wird zum einen auf globaler Ebene (bis zum Jahr 2100) im Rahmen von verschiedenen Szenarien modelliert, ob CCS eine wirtschaftliche Technologieoption zur Erreichung ambitionierter Klimaschutzziele darstellt. Zum anderen wird eine mögliche Diffusion der CCS-Technologie auf nationaler Ebene in Deutschland modelliert (bis zum Jahr 2050). Über diesen Ansatz wird herausgearbeitet, wie sich die zur Eindämmung notwendigen CO2-Reduktionen auf den Erzeugungsmix eines speziellen Landes auswirken. Dissertation, Universität Duisburg-Essen, 2017

A model to simulate long-term beach-dune evolution due to interacting longshore and cross-shore sediment transport processes is developed and tested. The work builds on a cross-shore model (CSM) previously developed at Lund University and includes changes to the equations describing aeolian transport and morphological evolution. The modifications are mainly based on existing conceptual geomorphological models which are translated into a numerical model, dealing with aeolian transport rates, transport limiting factors, and dune evolution under positive, negative, or stable beach sediment budgets. CSM is tested against a seven year data set of morphological evolution and sedimentgrain-size samples from Ängelholm Beach, Sweden. Results show a satisfactory fit between the simulated and observed evolution, although not all processes could be validated due to the limited temporal extent of the data set.

International audience; In this paper we demonstrate the role of electricity storage for the integration of high shares of Variable Renewable Energy Sources (VRES 3) in the long-term evolution of the power system. For this a new electricity module is developed in POLES (Prospective Outlook on Long-term Energy Systems). It now takes into account the impacts of VRES on the European power system. The power system operation relies on EUCAD (European Unit Commitment And Dispatch), which includes daily storage and other inter-temporal constraints. The innovative aspect of our work is the direct coupling between POLES and EUCAD, thus combining a long-term simulation horizon and a short-term approach for the power system operation. The storage technologies represented are pumped-hydro storage, lithium-ion batteries, adiabatic Compressed Air Energy Storage (a-CAES) and electric vehicles (charging optimisation and vehicle-to-grid). Demand response and European grid interconnections are also represented, in order to include to some extent these flexibility options. 2 Disclaimer: The views expressed are purely those of the writer and may not in any circumstances be regarded as stating an official position of the European Commission. 3 Abbreviations: a-CAES: adiabatic Compressed Air Energy Storage CCS: Carbon Capture and Storage

Objectives A short-term and long-term cost-effectiveness analysis (CEA) of two pedometer-based walking interventions compared with usual care. Design (A) Short-term CEA: parallel three-arm cluster randomised trial randomised by household. (B) Long-term CEA: Markov decision model. Setting Seven primary care practices in South London, UK. Participants (A) Short-term CEA: 1023 people (922 households) aged 45–75 years without physical activity (PA) contraindications. (b) Long-term CEA: a cohort of 100 000 people aged 59–88 years. Interventions Pedometers, 12-week walking programmes and PA diaries delivered by post or through three PA consultations with practice nurses. Primary and secondary outcome measures Accelerometer-measured change (baseline to 12 months) in average daily step count and time in 10 min bouts of moderate to vigorous PA (MVPA), and EQ-5D-5L quality-adjusted life-years (QALY). Methods Resource use costs (£2013/2014) from a National Health Service perspective, presented as incremental cost-effectiveness ratios for each outcome over a 1-year and lifetime horizon, with cost-effectiveness acceptability curves and willingness to pay per QALY. Deterministic and probabilistic sensitivity analyses evaluate uncertainty. Results (A) Short-term CEA: At 12 months, incremental cost was £3.61 (£109)/min in ≥10 min MVPA bouts for nurse support compared with control (postal group). At £20 000/QALY, the postal group had a 50% chance of being cost saving compared with control. (B) Long-term CEA: The postal group had more QALYs (+759 QALYs, 95% CI 400 to 1247) and lower costs (−£11 million, 95% CI −12 to −10) than control and nurse groups, resulting in an incremental net monetary benefit of £26 million per 100 000 population. Results were sensitive to reporting serious adverse events, excluding health service use, and including all participant costs. Conclusions Postal delivery of a pedometer intervention in primary care is cost-effective long term and has a 50% chance of being cost-effective, through resource savings, within 1 year. Further research should ascertain maintenance of the higher levels of PA, and its impact on quality of life and health service use., This research was supported by the Health Technology Assessment (HTA) Programme, National Institute for Health Research (project number HTA 10/32/02 ISRCTN42122561).

This research was supported by the Chair Modeling for sustainable development, driven by MINES ParisTech, Ecole des Ponts ParisTech and AgroParisTech, supported by ADEME, EDF, GRTgaz, and SCHNEIDER ELECTRIC and the French Ministry of Ecology, Sustainable Development and Energy.; A sustainable energy future requires a wide range of different mitigation options that can reduce the CO2 emissions. Particularly, renewables and carbon capture and storage appear as preferred or more largely evocated options. The aim of this study is to analyze alternative development paths of the energy system investigating different constraints on the use of CCS and BECCS, under climate policy context, and using the global multiregional optimization model, TIAM-FR. The analyze also focuses on the increasing pressure involved by the development of carbon capture technologies (fossil and biomass) on the water resources. Water and energy are indeed inextricably linked and interdependent sectors. Water requirements of existing and emerging technologies (such as carbon capture technologies) are so necessary to completely assess the water impacts of a developing decarbonizing economy.

The current development of wind and solar power sources calls for an improvement of longtermenergy models. Indeed, high shares of variable wind and solar productions have shortandlong-term impacts on the power system, requiring the development of flexibility options:fast-reacting power plants, demand response, grid enhancement or electricity storage. Ourfirst main contribution is the modelling of electricity storage and grid expansion in the POLESmodel (Prospective Outlook on Long-term Energy Systems). We set up new investmentmechanisms, where storage development is based on several combined economic values.After categorising the long-term energy models and the power sector modelling tools in acommon typology, we showed the need for a better integration of both approaches.Therefore, the second major contribution of our work is the yearly coupling of POLES to ashort-term optimisation of the power sector operation, with the European Unit CommitmentAnd Dispatch model (EUCAD). The two-way data exchange allows the long-term coherentscenarios of POLES to be directly backed by the short-term technical detail of EUCAD. Ourresults forecast a strong and rather quick development of the cheapest flexibility options: gridinterconnections, pumped hydro storage and demand response programs, including electricvehicle charging optimisation and vehicle-to-grid storage. The more expensive batterystorage presumably finds enough system value in the second half of the century. A sensitivityanalysis shows that improving the fixed costs of batteries impacts more the investments thanimproving their efficiency. We also show the explicit dependency between storage andvariable renewable energy sources., Le développement des énergies renouvelables éolienne et solaire implique de repenser les modèles à long terme du système énergétique. En effet, les impacts à court et long terme des productions intermittentes éolienne et solaire sur le système électrique entraînent un besoin de flexibilité : centrales de production très réactives, gestion de la demande,amélioration du réseau électrique ou stockage d’électricité. Le premier apport majeur à l’état de l’art est l’ajout du stockage d’électricité et du réseau électrique européen dans le modèle POLES (Prospective Outlook on Long-term Energy Systems). Un nouveau mécanisme d’investissement a été développé, mieux adapté aux enjeux des renouvelables ; il inclut plusieurs valeurs économiques du stockage. D’autre part, une nouvelle typologie applicable à la fois aux modèles de prospective énergétique et aux outils détaillés du secteur électrique,a montré l’intérêt de rassembler ces deux approches. Ainsi, la deuxième contribution principale est le couplage annuel de POLES à un modèle d’opération du système électrique,EUCAD (European Unit Commitment And Dispatch), qui optimise l’allocation technico économique des centrales européennes de production et de stockage. Les échanges bidirectionnels d’informations permettent de bénéficier à la fois de la cohérence à long terme des scénarios économiques de POLES et du détail technique d’EUCAD. Un scénario conservateur prévoit un développement rapide des options de flexibilité les moins chères :interconnexions, stockage hydraulique et gestion de la demande – que ce soit par des effacements de consommation ou par l’optimisation de la charge et décharge des batteries de véhicules électriques. Les batteries stationnaires, plus chères, sont développées en seconde partie de siècle. Leur développement pourrait être accéléré par une réduction des coûts fixes du stockage plus efficace qu’une amélioration du rendement. Les liens explicites entre renouvelables intermittents et stockage d’électricité ressortent aussi des résultats.

Asian countries have sharply increased their energy consumption due to economic growth, inducing extremely high dependency on fossil energy, ranking them among the world's highest CO2 emitters. Hence, the current focus in these countries is on using bioenergy to diversify the energy mix and mitigate climate change. In this study, we estimated the evolution of bioenergy deployment through current energy and climate policies using a bottom-up energy system optimisation model. The results indicate that a carbon tax system would derive the greatest bioenergy consumption by 2030. Current INDCs targets appear insufficient to promote bioenergy development without renewable energy targets and biofuel blending mandates. [Received: January 14, 2016; Accepted: July 24, 2016]

International audience; An increasing body of literature assesses the attainability of stringent CO2 mitigation targets (e.g. van Vuuren et al., 2007), depending on a wide range of different reduction options, and the technology 'readiness' of advanced technologies, in particular the industrial scale of carbon capture and storage (CCS)and the combination of bio-energy, carbon capture and geologic storage (BECCS). Introducing CCS to abate emissions appears more and more as incontrovertible to reduce future CO2 emissions in line with the consensual limit of 2°C temperature increase (IPCC, 2007b). This all the more if we consider that fossil fuels will remain the dominant sources of energy over the next decades and that, as a result, CO2 emissions will drastically increase to reach unsustainable levels. Furthermore, among the technological options to mitigate CO2 emissions, BECCS is gaining increasing attention, as this alternative offers a unique opportunity for a net carbon removal from the atmosphere while fulfilling energy needs (Herzog et al., 2005;Azaret al., 2006;van Vuuren et al., 2007; Katofsky et al., 2010).

International audience; The aim of this work is to develop a predictive control algorithm to improve the productivity of an ultrafiltration pilot plant producing drinking water from surface raw water. The objective is to avoid irreversible fouling, that means to get a constant quality of the membrane after backwash and at the same time to optimise the productivity of the process. This control strategy is based on a model able to predict long-term performances of the ultrafiltration pilot plant. This model consists in two interconnected recurrent neural networks coupled with the Darcy's law. The parameters taken into account are water quality parameters, operating conditions during filtration time and during the backwash procedure. The model allows predicting satisfactorily the filtration performances of the experimental pilot plant obtained for different water quality and changing operating conditions, during several hundred filtration cycles.

International audience; The aim of this study was to develop a neural network model to predict the productivity of an ultrafiltration pilot plant, treating surface water to produce drinking water and operated with sequential backwashes. The model had to predict long-term performances of the pilot plant, it means to consider both reversible and irreversible fouling. The model had also to take into account a minimum number of parameters. On site experiments were performed to constitute the learning and validation databases. The developed model consists in two interconnected recurrent neural networks. It allows predicting satisfactorily the filtration performances of the experimental pilot plant for different resource water quality and changing operating conditions.

Available on: http://www.iiis.org/CDs2011/CD2011SCI/EEEP_2011/PapersPdf/JA513YT.pdf; This paper analyzes technological options to mitigate CO2 emissions and reach the 2°C objective expressed to UNFCCC since COP15, through global and regional climate objectives. The first aim of this paper is evaluate the impact on global CO2 mitigation possibilities according to carbon constraints scenarios and the level of development of different regions An important result consists in the necessary participation of developing countries in the international climate policy. The second main aim of the study is to study the evolution of the energy system for developed and developing countries. While CCS technologies deployment appears as a necessary solution for fast developing countries (especially China), developing countries (and in a lower manner developed countries) need to invest in renewable energies. But in both cases, countries face economical aspects of their energy transition, such as costs, large scale deployment, traditional energy sector core activities and objectives.