New research seeks to take account of the fast pace at which technology is evolving in understanding how to tackle greenhouse gas emissions.

Technology comes to life through innovation, timely investments and policy incentives

Jean-Francois Mercure

Computational models provide unparalleled insight into current and future demand for water, land and energy, and the impact these demands have on greenhouse gas (GHG) emissions and the environment. What if we could also take into account the fast pace at which new technologies are evolving? This is the aim of a new project in the Cambridge Centre for Climate Change Mitigation Research (4CMR) in the University of Cambridge’s Department of Land Economy.

Dr Jean-Francois Mercure, who leads the research, asserts that building this factor into models will help understanding of the degree to which improvements in energy-consuming technologies and their adoption can help governments reduce emissions: “Technology comes to life through innovation, timely investments and policy incentives, and so it’s important to include technology diffusion and its pace in energy modelling.

“However, this is challenging and most models today attempt to calculate cost-optimal technology roadmaps based on current technology, which is not necessarily likely to happen, and which disregard the process by which new technology regimes come to existence, but also how old technologies endure.”

Technological change occurs constantly, either following innovations in industrial systems or through evolutions of behaviours, such as in the adoption of electric cars. Earlier this year, with funding from the Engineering and Physical Sciences Research Council, Mercure began work on a computational modelling system that takes into account the profile of technology transitions in the past to project how new transitions could arise in the future.

To do so, he is collaborating with environmental scientists at the Tyndall Centre at the University of East Anglia and at the Open University, policy advisors and researchers at the UK Department for Energy and Climate Change and the Committee for Climate Change, and applied economists at Cambridge Econometrics.

Mercure believes that this will be the first time an energy–economy–environment model at the global level simultaneously considers technology diffusion in all sectors of energy use alongside natural resource constraints and the interaction between sectors.

“If the global power sector is to decarbonise by 2050 without there being significant economic costs then all countries must make a contribution to the development of renewable technologies,” he added.

“Take as an example the solar photovoltaic industry. Large investments in Germany enabled production costs of firms in China to decline significantly in recent years, which could not have occurred without such investments. Technology sectors typically face a classic vicious circle: established technologies thrive because they are established, and emerging technologies see barriers to their diffusion due to the lock-in of established technologies. This will be the case unless an emerging technology is a radical improvement over established technologies, or it benefits from strong policy support and investment. This applies to many other sectors such as mobility technologies, industry and household appliances.”

Professor Douglas Crawford-Brown, Director of 4CMR, is excited by the prospects of this new modelling: “Dr Mercure’s work sits nicely at the intersection of aggregated economic sectors and the decisions of individual investors. He is plotting an intermediate ground in which both theories of investor behaviour and empirical econometrics allow for much greater insights into energy supply and demand.”

Mercure’s recent research has focused on the global electricity sector, which currently emits 38% of global fuel combustion emissions mostly through the use of fossil fuels. The new project will extend the model to all major energy-consuming sectors, including transport, industry (e.g. steel, cement) and buildings (heating, appliances), to model different scenarios of support policies for technological change.

“We want to be able to answer questions about the impact of policy changes on global emissions. Badly coordinated roadmaps of technological change can lead to increases in GHG emissions and so it’s important to know which types of policies will incentivise efficient emissions reductions in order to avoid dangerous climate change.”


This work is licensed under a Creative Commons Licence. If you use this content on your site please link back to this page.