Scientific research to characterize the long-term wind energy resource is plentiful. However, if the impact of wind power on the electric power system is the goal of modeling, consideration must be given to diurnal and seasonal effects, as well as the correlation of wind speed between geographical areas. This paper provides such detail by modeling these effects explicitly, enabling accurate evaluations of wind power impact on future power systems to be carried out. This is increasingly important in the context of ambitious wind energy targets driven in the U.K., for example, by the requirement for 20% of Europe's energy to be met from renewable energy sources by 2020. Both univariate and multivariate auto-regressive models are presented here and it is shown how they can be applied to geographically dispersed wind speed data. These models are applied to suitably de-trended data. The accuracy of the models is assessed both by inspection of the residuals and by assessment of the forecasting accuracy of the models. Finally, it is shown how the models can be used to synthesize wind speed and thus wind power time series with the correct seasonal, diurnal, and spatial diversity characteristics.

Summary. Background: Radon is a well-established lung carcinogen that has been extensively studied. Very high concentrations can occur in some undergro

Changes to the electricity supply industry, in particular the progress towards deregulation, have prompted an increased interest in short-term electricity demand forecasting. Trend removal has been identified as a key element in forecasting, and perhaps the area that can most benefit from the application of advanced time series analysis. A new approach to trend removal is presented based on fixed interval, or optimal, smoothing techiques. Forecasts derived in this way are compared with more conventional approaches. Preliminary results indicate the new method to be promising and deserving of further development

Objective High-quality maternity care is key to long-term improvements in population health. However, even within developed welfare systems, some mothers and babies experience poorer care and outcomes. This study aimed to explore whether women’s experiences of maternity care in Scotland differs by their physical or sociodemographic characteristics. Design Secondary analysis of the 2015 Scottish Maternity Care Experience Survey. The questionnaire was based on the Care Quality Commission English maternity survey. Setting National Health Service maternity care in Scotland. Participants The survey was distributed to 5025 women who gave birth in Scotland during February and March 2015 with 2036 respondents (41%). Main outcome measures The questionnaire explored aspects of care processes and interpersonal care experienced from the first antenatal contact (booking) to 6 weeks following the birth. The analysis investigated whether experiences were related to age, parity, deprivation, rurality, self-reported general health or presence of a health condition that limited daily activities. Analysis used mixed effect multilevel models incorporating logistic regression. Results There were associations between parity, age and deprivation with gestation at booking indicating that younger women, women from more deprived areas and multiparous women booked later. Women reporting generally poorer health were more likely to describe poorer care experiences in almost every domain including continuity, pain relief in labour, communication with staff, support and advice, involvement in decision making, confidence and trust and overall rating of care. Conclusions We found few differences in maternity care experience for women based on their physical or socioeconomic characteristics. Our findings indicate that maternity care in Scotland is generally equitable. However, the link between poorer general health after childbirth and poorer experience of maternity care is an important finding requiring further study.