Transitions to “low-carbon” development paths (i.e., to development paths with limited greenhouse gases emissions) are unlikely to be achievable solely via technological solutions: behavior, notably consumption patterns, will also have to evolve. However, an assumption implicit in most GHG emissions scenarios is that as income per capita converge across countries, households consumption patterns will converge as well, leading to potentially very high demand for energy, very high demand for natural resources and very high emissions. ECOPA precisely aims at examining how flexible the link between income per capita and consumption patterns is; and at drawing implications of these findings for future emissions scenarios. To do so, ECOPA maps and compares consumption patterns, and their evolution, in France, an “old” industrialized economy, and Brazil, a rapidly emerging economy. In both countries, a combination of econometric analysis of consumption data, household surveys and in-depth studies of representative goods and services is used to (i) map consumption patterns across income groups, and (ii) explore the determinants of their changes over time. Strong emphasis is put on obtaining consistent monetary and physical flows. This is necessary to analyze the energy and emissions implications of consumption patterns, but this constitutes a significant theoretical and empirical stumbling block. Finally, on the basis of the retrospective analysis, scenarios of how household consumption patterns in the two countries might evolve are built and their implications for energy and GHG emissions are computed.

Due to expectations of more ambitious GHG mitigation goals to be agreed on internationally in the future, climate policy will have to target households. Households in high-income-countries influence some 50 % of GHG emissions. Thus, targeting them in climate policies implies including emissions embedded in private consumption which so far has largely been outside the scope of current climate policies. The EU roadmap for a competitive low carbon economy calls for reducing GHG emissions by 80-95% until 2050. Thus, we apply a long-term goal of reducing household GHG emissions in the range of 50 % by 2050 compared with 1990, in which we will develop possible pathways for households to contribute to reach this goal. The HOPE project will generate new knowledge in three areas (1) the drivers behind current household emission (2) households choices to achieve imposed GHG reduction targets (3) economic costs amp; benefits as well as health co-benefits of each choice. The four study countries offer different contexts in climate policy, GHG-emission profiles and energy supply. We study a representative urban household sample in each country. The study comprises three stages: (1) A household interview survey including the assessment of the current household footprint of direct and indirect GHG emissions. (2) An on-site simulation, in which household will be guided through a GHG reduction simulation of 60 GHG saving options. For each behavioral change, the resulting savings (GHG reduction), costs and health co-benefits will be shown. (3) A semi-structured qualitative follow-up interview addressing household views on potential barriers and motivation for the measures chosen in stage 2 will be applied to a carefully chosen subsample based on the results of stages 1 and 2. Engaging with policy-makers from the start we will develop possible innovations in current climate policy regimes at EU, national and local level of governance to support households in their consumption choices.

The warming of the climate system is unequivocal and continued emission of greenhouse gases will cause further warming and changes. Islands are particularly vulnerable to Climate Change (CC) consequences but the coarse spatial resolution of available projections makes it difficult to derive valid statements for islands. Moreover, science-based information about the economic impacts of CC in marine and maritime sectors is scarce, and current economic models lack of solid non-market assesment. Policy makers must have accurate information about likely impact chains and about the costs and benefits of possible strategies to implement efficient measures. SOCLIMPACT aims at modelling downscaled CC effects and their socioeconomic impacts in European islands for 2030–2100, in the context of the EU Blue Economy sectors, and assess corresponding decarbonisation and adaptation pathways, complementing current available projections for Europe, and nourishing actual economic models with non-market assessment, by: • Developing a thorough understanding on how CC will impact the EU islands located in different regions of the world. • Contributing to the improvement of the economic valuation of climate impacts by adopting revealed and stated preference methods. • Increasing the effectiveness of the economic modelling of climate impact chains, through the implementation of an integrated methodological framework (GINFORS, GEM-E3 and non-market indicators). • Facilitating climate-related policy decision making for Blue Growth, by ranking and mapping the more appropriate mitigation and adaptation strategies. • Delivering accurate information to policy makers, practitioners and other relevant stakeholders. SOCLIMPACT addresses completely this Work Programme providing advances in the economic valuation of climate-induced impacts, and in climate and economic models, allowing downscaled projections of complex impact chains, and facilitating the resilience capacity of these vulnerable lands.

The PROSNOW project ambitions to build a demonstrator of a meteorological and climate prediction system from one week to several months ahead applied to snow management, specifically tailored to the needs of the ski industry using a co-design approach. This novel climate service holds significant potential to increase the resilience of socio-economic mountain stakeholders and supports their real-time climate change adaptation potential. PROSNOW will apply state-of-the-art knowledge relevant to the predictability of atmospheric and snow conditions, then develop products well beyond state-of-the-art operational tools. Improved anticipation capabilities at all time scales, spanning from “weather forecast” (up to 5 days typically) to “climate prediction” at the seasonal scale (up to several months), will be achieved through a seamless integration of weather and seasonal prediction products, together with snowpack models, in-situ and remotely-sensed observations and cutting-edge statistical tools in support of the decision making process. The project proposes an Alpine-wide system (France, Switzerland, Germany, Austria and Italy). It will associate research institutions for weather forecasts, climate predictions at the seasonal scale and snowpack modeling, a group of providers proposing high tech solutions for snow monitoring and management, and a relevant ensemble of eight representative resorts in the Alps. The added value of such services for ski resorts will be investigated and documented, making it possible to initiate a commercial exploitation of the service at the end of the project.