Three Postgraduate students awarded dissertation prizes
The Department for Social Responsibility & Sustainability is delighted to announce that three students have won prizes for their Masters dissertations.
Now in its second year, the SRS Dissertation Prizes aim to highlight and recognise student research on social responsibility and sustainability themes.
A panel of academics from across the University judged the Masters entries on their contribution to furthering knowledge and/or understanding of social responsibility and/or sustainability.
Three students were awarded prizes, each receiving £150 and a £50 voucher for an ethical organisation of their choice.
The Prize Winners
Catherine Chisem, MSc Carbon Finance
Portfolio Analysis Using Water Shadow Pricing: How Valuing Water Risk Can Reduce Carbon Emissions
Water is the primary vehicle through which the effects of climate change will be felt, with a two degree scenario expected to severely decrease water resource availability for an additional 15% of the population; by 2040, 35% of the global population is expected to live in areas of high water stress. Whilst investors are now well-versed in the risks and opportunities presented by carbon emissions, there is a paucity of research into the risks posed by water stress. Few investors have attempted to value a company's exposure to water risk, and consequently even fewer have suggested the link between water risk and carbon emissions in a portfolio. This study breaks new ground by using a total economic value framework to define a company’s ‘shadow price of water’. It provides an implementable method for integrating water risk into an investment strategy, and suggests that the two targets of reducing a portfolio's carbon emissions and water risk are neither difficult to measure nor mutually exclusive.
This is a well-written dissertation on an increasingly important issue, which demonstrates strong analysis and a convincing argument.
Christopher Sipola, MSc Artificial Intelligence
Summarizing electricity usage with a neural network
This dissertation explores whether a neural network—arguably the most powerful and flexible model used in artificial intelligence today—is capable of summarizing energy usage of individual household appliances, given only the aggregate signal of a smart meter. An example of such a statistic is the total energy used by a washing machine in a day. Access to this information has been shown to encourage a decrease in energy usage. The results show that using a neural network is not only capable of predicting appliance-level summary statistics directly, but that the predictions are accurate and generalizable.
This is a well-researched dissertation on an important topic, with a very promising outcome.
Amanda Midhamre, MSc Environmental Sustainability
How can public procurement encourage new developments in Circular Economy? Opportunities and examples for the University of Edinburgh.
In Scotland alone, £10 billion per year is spent on goods and services through public procurement (Ellen MacArthur Foundation, 2013). This is a substantial amount, indicating that public procurement decisions can steer demand and stimulate innovation, including in relation to a transition towards a circular economy. However, there is little research that looks at how public organisations practically and strategically procure circular products. In order to better understand how public procurement in the context of the University of Edinburgh could reflect circular economy principles, the department for Social Responsibility and Sustainability commissioned this research as part of a work-based placement. The dissertation identifies barriers, practical examples and mechanisms for the development of circular public procurement.
This is a well-written and presented dissertation which demonstrates good background knowledge and a clear impact.
We accept entries from students who have worked with us in the past, however, entries are scored by a panel of academic judges from different disciplines to ensure impartiality.