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This paper provides a background review of models predicting occupancy, occupancy-sensing control and manual environmental control, and outlines their current addition to whole building energy simulation, in particular ESP-r. It deals with how occupancy-related input data models are defined and used in whole-building energy simulation., The CIB Conference 2004: 02 May 2004, Toronto, Ontario

A web-based, non-expert daylighting analysis tool has been developed to support daylighting-related design decisions in peripheral private offices during an early design stage (http:buildwiz.com). The tool offers a comparative, reliable, and fast analysis of the annual amount of daylight in the offices (daylight factor and daylight autonomy) and the lighting energy performance of automated lighting controls (occupancy sensors, photocells) compared to standard on/off switches. Blinds are either manually or automatically controlled. During a simulation run, pre-calculated, RADIANCE-based daylight coefficients for over 600 office designs are coupled with weather data from 285 sites in North America to yield annual daylight illuminance profiles. The annual electric lighting energy use is subsequently predicted via a model that mimics occupancy and manual lighting and blinds control in private offices. A simulation run takes between 30 seconds to 3 minutes and yields a detailed report of the annual daylight availability and lighting energy use in the investigated office., Buildings Simulation 2003, 1 September 2003, Eindhoven, the Netherlands

Being overconfident when estimating scores for an upcoming exam is a widespread phenomenon in higher education and presents threats to self-regulated learning and academic performance. The present study sought to investigate how overconfidence and poor monitoring accuracy vary over the length of a college course, and how an intervention consisting of (1) a monitoring exercise and (2) a monitoring and regulation strategy, improves students’ monitoring accuracy and academic performance. Moreover, we investigated how personality factors (i.e., grandiose and vulnerable narcissism, optimism) influence monitoring accuracy. We found that the monitoring and regulation strategy positively influenced monitoring accuracy and exam scores, whereas the monitoring exercise that confronted students with their overconfidence protected students against overconfidence in the second exam score prediction but did not affect exam score. The results further revealed that exam score predictions lowered from the start to the end of the course for both poor and high performing students, but still leaving poor performers overconfident and high performers underconfident. Topic knowledge gained in the course did not wash out the dunning kruger effect, and results indicate that poor and high performers use different cues when predicting exam scores. Both grandiose and vulnerable narcissism contributed to overconfidence on exam score predictions but not on the monitoring exercise. These findings underline the potential of the monitoring and regulation strategy intervention and ask for upscaling it to include measurements of self-regulated learning activities.

The World Health Organization's Health Economic Assessment Tool (HEAT) for walking and cycling is a user-friendly web-based tool to assess the health impacts of active travel. HEAT, developed over 10 years ago, has been used by researchers, planners and policymakers alike in appraisals of walking and cycling policies at both national and more local scales. HEAT has undergone regular upgrades adopting the latest scientific evidence. This article presents the most recent upgrades of the tool. The health impacts of walking and/or cycling in a specified population are quantified in terms of premature deaths avoided (or caused). In addition to the calculation of benefits derived from physical activity, HEAT was recently expanded to include assessments of the burden associated with air pollution exposure and crash risks while walking or cycling. Further, the impacts on carbon emissions from mode shifts to active travel modes can now be assessed. The monetization of impacts using Value of Statistical Life and Social Costs of Carbon now uses country-specific values. As active travel inherently results in often substantial health benefits as well as not always negligible risks, assessments of active travel behavior or policies are incomplete without considering health implications. The recent developments of HEAT make it easier than ever to obtain ballpark estimates of health impacts and carbon emissions related to walking and cycling.

There is evidence that many individuals make sub-optimal investment decisions when the benefits and costs associated with that decision are distributed over time. One example is the decision to adopt new electrical appliances, with the benefits of choosing a more energy efficient device materializing only in the future. This paper analyses the impact of the level of an individual’s energy-related investment literacy on the adoption of energy-efficient appliances. Moreover, the empirical analysis explores the impact of decision support tools such as educational slides on the probability that individuals identify the appliance with the lowest lifetime cost, which is ideally also the most energy-efficient appliance. To test the influence of these decision support tools, we developed an online randomized controlled trial and implemented it on two independently chosen samples of the Swiss population. One treatment offers a short education program on how to calculate the lifetime cost of an appliance – via a set of information slides. The second intervention provides access to an online calculator that supports the investment decision-making of the individual. Results across the two samples are encouraging. We find that i) pre-treatment energy and investment literacy positively impact on the probability of identifying the appliance with the lowest lifetime cost; ii) the reinforcement of energy-related investment literacy increases the rate at which individuals identify the appliance with the lowest lifetime cost; and iii) while both interventions are effective in increasing the chances that an appliance with the lower lifetime cost is chosen, the online calculator turned out to be more effective than the educational program. Public policy implications are discussed.

Since seafood is a significant source of nutrients with known health benefits, its consumption is promoted as a healthy food choice. However, seafood can also contain potentially hazardous environmental pollutants. In the context of the ECsafeSEAFOOD FP7 project, FishChoice (www.fishchoice.eu) was developed as a communication tool to help to the consumers to take the most appropriate decisions on their seafood consumption habits. FishChoice relies on scientific information that allows calculating, on an individual basis, intakes of nutrients and pollutants derived from seafood consumption. In the framework of the EU-H2020 funded SEAFOODTOMORROW project, an optimized version of the online tool has been released. FishChoice is available in 25 EU languages with a customized list of seafood species per EU country, considering specific (national) consumption habits. The list of nutrients has been extended according to the latest EFSA recommendations, while pollutants data incorporate results from recent studies. The sustainability of seafood consumption has been also implemented, providing recommendations to help preserve the marine environment. Finally, FishChoice is suitable not only for consumers, but also health professionals, schools and academia, as well as the industrial sector and public health providers.