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ABSTRACTWind power forecasts are useful tools for power load balancing, energy trading and wind farm operations. Long range monthly‐to‐seasonal forecasting allows the prediction of departures from average weather conditions beyond traditional weather forecast timescales, months in advance. However, it has not yet been demonstrated how these forecasts can be optimally transformed to wind power. The predictable part of a seasonal forecast is for longer monthly averages, not daily averages, but to use monthly averages misses information on variability. To investigate, here a model relating average weather conditions to average wind power output was built, based on the relationship between instantaneous wind speed and power production and incorporating fluctuations in air density due to temperature and wind speed variability. Observed monthly average power output from UK stations was used to validate the model and to investigate the optimal temporal resolution for the data used to drive the model. Multiple simulations of wind power were performed based on reanalysis data, making separate simulations based on monthly, daily and sub‐daily averages, using a distribution defined by the mean across the period to incorporate information on variability. Basing the simulation on monthly averages alone is sub‐optimal: using daily average winds gives the highest correlation against observations. No improvement over this is gained by using sub‐daily averages or including temperature variability. This signifies that to transform seasonal forecasts to wind power a compromise must be made between using the daily averages with debatable skill and the more predictable monthly averages, losing information on day‐to‐day variability.

The energy consumption of the current building stock represents about 40% of the total final energy consumption in Europe. New gamification techniques may play a significant role in helping users adopt new and more energy efficient behaviours. This paper presents the advances achieved within the context of the EU-funded project EnerGAware - Energy Game for Awareness of energy efficiency in social housing communities. The main objective of the project, funded by the European Union under the Horizon2020 programme, is to reduce the energy consumption and carbon emissions in a sample of European social housing by changing the energy efficiency behaviour of the social tenants through the implementation of a serious game linked to the real energy use of the participants’ homes. Peer Reviewed

What commonalities are there in sustainable or unsustainable heating practices in five high-income, high-emitting western European countries? What preferences do a nationally representative sample of the public in these countries hold towards low-carbon options? It is imperative that climate policy researchers and practitioners grapple with the difficulty of decarbonizing heat, which remains the largest single end-use service worldwide and which accounts about half of total final energy consumption. Based on a comparative assessment of five representative national surveys in Germany (N = 2009), Italy (N = 2039), Spain (N = 2038), Sweden (N = 2023), and the United Kingdom (N = 2000), this study explores the demographics and geography of household heat decarbonisation in Europe. By analyzing our country level data as well as our combined sample of 10,109 respondents, it investigates how people conceive of the purposes of low-carbon heat, their preferences for particular forms of heat supply, and their (at times odd) practices of heat consumption and temperature settings. Grounded in its original data, the study organizes its findings inductively across the five themes of literacy (heating knowledge, awareness and control), sustainability (heating practices, dynamics and conflicts), temperature (heating satisfaction and preferences), desirability of change (low-carbon heating priorities, business models and trust), and culture (country and national variation). The study also explores intersections between these dimensions, using multivariate analysis, as well as how preferences differ according to varying types of actors as well as geography and space. The authors gratefully acknowledge support from UK Research and Innovation through the Centre for Research into Energy Demand Solutions (CREDS), grant reference number EP/R035288/1. This paper has also received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 764025.

Although future climate is predicted to have more extreme heat conditions, the available evidence on the impact of these conditions on pregnancy length is very scarce and inconclusive.We investigated the impact of maternal short-term exposure to extreme ambient heat on the length of pregnancy.This study was based on a cohort of births that occurred in a major university hospital in Barcelona during 2001-2005. Three indicators of extreme heat conditions based on 1-day exposure to an unusually high heat-humidity index were applied. Each mother was assigned the measures made by the meteorological station closest to maternal residential postcodes. A two-stage analysis was developed to quantify the change in pregnancy length after maternal exposure to extreme heat conditions adjusted for a range of covariates. The second step was repeated for lags 0 (delivery date) to 6 days.We included data from 7,585 pregnant women in our analysis. We estimated a 5-day reduction in average gestational age at delivery after an unusually high heat-humidity index on the day before delivery.Extreme heat was associated with a reduction in the average gestational age of children delivered the next day, suggesting an immediate effect of this exposure on pregnant women. Further studies are required to confirm our findings in different settings.

The environmental profile of a dielectric-based 3D Building-Integrated Concentrating Photovoltaic(BICPV) device is investigated. Several scenarios and life-cycle impact assessment methods are adopted,including the newly-developed method ReCiPe. Multiple environmental indicators are evaluated fordifferent cities: Barcelona, Seville, Paris, Marseille, London and Aberdeen. The results from the mate-rial manufacturing phase demonstrate that the PV cells and the concentrator are the components withthe highest contribution to the total impact of the BICPV, based on ReCiPe, Eco-indicator 99, USEtox,CED (cumulative energy demand), GWP (global warming potential) according to different time hori-zons (20a, 100a, 500a) and Ecological footprint. Among the studied cities, Barcelona, Marseille andSeville present the lowest GWP and CED: less than 142 g CO2.eq/kWh and less than 2.9 MJprim/kWh,based on all the studied scenarios. Moreover, by considering 30-years lifespan, Barcelona, Marseille andSeville show 0.0107–0.0111 ReCiPe Pts/kWh while London, Paris and Aberdeen present 0.0161-0.0173ReCiPe Pts/kWh. Results about greenhouse-gas-, energy-, ReCiPe-payback times and energy-return-on-investment are also presented and critically discussed. In addition, comparisons with the literature andissues for the improvement of the environmental profile of the proposed system are included. The authors would like to thank “Ministerio de Economía y Competitividad” of Spain for the funding (grant reference ENE2013-48325-R).

I formulate and estimate a model of externalities within countriesand technological interdependence across countries. I find that externalreturns to scale to physical capital within countries are 8 percent; thata 10 percent increase of total factor productivity of a country's neighborsraises its total factor productivity by 6 percent; and that a 2 percentannual growth rate of labor productivity can be explained as an endogenousresponse to an exogenous 0.2 percent annual growth rate of total factorproductivity in the steady--state.