Urban waste heat recovery, in which low temperature heat from urban sources is recovered for use in a district heat network, has a great deal of potential in helping to achieve 2050 climate goals. For example, heat from data centres, metro systems, public sector buildings and waste water treatment plants could be used to supply 10% of Europe’s heat demand. Despite this, at present, urban waste heat recovery is not widespread and is an immature technology. Based on interviews with urban waste heat stakeholders, investors interested in green investments, and experience from demonstrator projects, a number of recommendations are made. It is suggested that policy raising awareness of waste heat recovery, encouraging investment and creating a legal framework should be implemented. It is also recommended that pilot projects should be promoted to help demonstrate technical and economic feasibility. A pilot credit facility is suggested aimed at bridging the gap between potential investors and heat recovery projects.

Approximately 1.2 EJ of energy are potentially available for recovery each year from urban heat sources in the EU. This corresponds to more than 10 percent of the EU’s total energy demand for heat and hot water. There are, however, a number of challenges to be met before urban waste heat recovery can be performed on a wide scale. This paper focuses on the non-technical issues related to urban waste heat recovery and is written on the basis of opinions gathered from stakeholders in the field. Three non-technical issues are focused upon. First, a number of important barriers to wide scale urban waste recovery are identified, and where applicable, recommendations are made regarding how to overcome these barriers. Second, important issues and challenges regarding contract design are identified and discussed. Key elements of heat supply contracts between the district heating company and the owner of the waste heat are described. Finally, the impact on business models of properties specific to urban waste heat recovery are discussed. Data were collected from two separate sources, both related to the ReUseHeat Horizon 2020 project, which addresses the application of urban waste heat recovery in existing district heating networks. First, a number of interviews with stakeholders were carried out. Second, information was collected from demonstrator sites involved in the ReUseHeat project. It was concluded that, for urban waste heat recovery to be taken up on a wide scale, there is still a large amount of work to do to overcome these major issues. This paper is novel in that key non-technical issues of urban waste heat recovery are discussed from the perspective of a large sample of actual stakeholders and practitioners in the field.

A scoring rule is a function of a probabilistic forecast and a corresponding outcome used to evaluate forecast performance. There is some debate as to which scoring rules are most appropriate for evaluating forecasts of sporting events. This paper focuses on forecasts of the outcomes of football matches. The ranked probability score (RPS) is often recommended since it is 'sensitive to distance', that is it takes into account the ordering in the outcomes (a home win is 'closer' to a draw than it is to an away win). In this paper, this reasoning is disputed on the basis that it adds nothing in terms of the usual aims of using scoring rules. A local scoring rule is one that only takes the probability placed on the outcome into consideration. Two simulation experiments are carried out to compare the performance of the RPS, which is non-local and sensitive to distance, the Brier score, which is non-local and insensitive to distance, and the Ignorance score, which is local and insensitive to distance. The Ignorance score outperforms both the RPS and the Brier score, casting doubt on the value of non-locality and sensitivity to distance as properties of scoring rules in this context.

Wild reindeer have a range that extends across the circumpolar region. In the last few decades, however, populations of wild reindeer have been on the decline. The reasons for these declines are poorly understood, but are suggested to be linked to both local and global climatic factors, disease, and human interference. Hardangervidda plateau in Norway is home to the largest wild reindeer population in Europe, and is at the southern end of its European range. This population is therefore of particular importance, particularly in the light of climate change. We investigated how weather and hunting have affected the wild reindeer population in Hardangervidda over the last two decades. Our findings suggest that the wild reindeer population in Hardangervidda is most affected by winter temperature and hunting, where colder temperatures and lower harvest rates typically result in higher growth rates. We did not find significant evidence for linear density dependence. Our results show trends across Hardangervidda, and give an indication of how region‐wide weather and hunting pressure can affect the wild reindeer population. As new data emerge, future investigations should look into the existence and nature of density dependence and the influence of other weather and human disturbance related factors.

Betting odds are generally considered to represent accurate reflections of the underlying probabilities for the outcomes of sporting events. There are, however, known to be a number of inherent biases such as the favorite-longshot bias in which outsiders are generally priced with poorer value odds than favorites. Using data from European soccer matches, this paper demonstrates the existence of another bias in which the match odds overreact to favorable and unfavorable runs of results. A statistic is defined, called the Combined Odds Distribution (COD) statistic, which measures the performance of a team relative to expectations given their odds over previous matches. Teams that overperform expectations tend to have a high COD statistic and those that underperform tend to have a low COD statistic. Using data from twenty different leagues over twelve seasons, it is shown that teams with a low COD statistic tend to be assigned more generous odds by bookmakers. This can be exploited and a sustained and robust profit can be made. It is suggested that the bias in the odds can be explained in the context of the “hot hand fallacy”, in which gamblers overestimate variation in the ability of each team over time.

Urban Waste Heat Recovery, heat recovery from low-temperature urban sources such as data centres and metro systems, has a great deal of potential in terms of meeting domestic and commercial heat demands whilst significantly reducing carbon emissions. Urban sources of heat are advantageous in that they tend to be close to areas of high heat demand and are therefore highly suitable as inputs to existing and newly constructed district heating networks. This paper has two main focuses. Firstly, the issue of efficiency in waste heat recovery is addressed with a focus on Technical, Economic, Social, and Environmental (TESE) efficiencies, which we consider should be given equal consideration. Secondly, we address the question of contractual efficiency and argue that contracts should be underpinned by mathematical modelling. We then focus on the contractual relationship between the owner of the waste heat and the district heating operator and consider the question of waste heat pricing. We suggest a profit sharing approach in which the price per unit of waste heat is allowed to vary according to important aspects such as demand and the electricity price. A demonstration of this approach is presented using a simple model of a waste heat recovery system that extracts heat from a data centre in Brunswick, Germany.