A multidomain system for accounting carbon credits for individuals
Project reference: MN77
Application deadline: 10 April 2023
One of the most interesting concepts designed within the Kyoto Protocol to tackle greenhouse gas (GHG) emissions is the creation of a trading system for carbon emissions, using ‘carbon credits’. For example, the New Zealand Emissions Unit Register, and the EU Emissions Trading Scheme.
These markets have been developed for large polluters rather than individuals, but there is a revival of interest in developing personal or individual carbon credit trading systems. With current data, machine learning and simulation methods and techniques there are many more possibilities to explore the complexities of all the domains in which carbon emissions of individuals take place. This can be coupled with simulation, visualisation and gamification methods and tools to create powerful and usable systems that are more effective in inducing behavioural change and supporting climate adaptation policies.
The aim of this project will be to explore theoretical concepts and methodological approaches to create an integrated, multidomain (e.g. transport, housing, consumer patterns, finance, indirect emissions), and high-resolution carbon credit system (CCS) for individuals.
Detailed project description:
Emissions of greenhouse pollutants have been the central point of climate change policies, being the central policy measure of global treaties such as the Paris Accord (UN, n.a.). One of the most interesting concepts designed within the Kyoto Protocol to tackle greenhouse gas (GHG) emission was the creation of a trading system for carbon emissions where one carbon unit (a tonne) would be one credit and big pollutant entities (companies, countries) would have to obtain credits to emit carbon and greener ones would sell their carbon savings. Carbon markets have since the late 1990s being in place spanning from countries, for example the New Zealand Emissions Unit Register (NZG, 2008) to continents with the EU Emissions Trading Scheme (EU Commission, 2005).
These markets operate at a very aggregate level of emissions, with only large polluters (e.g. aviation companies, energy companies or individual power stations, cement producers or countries) trading credits. Individuals can indirectly participate in the systems in multiple commercial or charity schemes of offsetting their carbon emissions with operators that eventually will trade these credits in the current trading schemes. These offset schemes have been under strong scrutiny due to the difficulty of auditing its efficiency (The Guardian, n.a.) and the risk of greenwashing individual attitudes. On the other hand, the role of individual behavioural change towards more sustainable attitudes is central to any climate change adaptation policy, with communities and political discourses and media attention highlighting it.
There is a revival of interest in developing personal or individual carbon credits systems. There is some research on setting the principles and designing possible systems (Fuso Nerini et all, 2021) and some older analyses of principles and bottlenecks (Fawcett and Parag, 2010). On the policy side, there are few initiatives. For the UK contemplates this possibility since the Climate Change Act 2008, without notice of further implementation. Many of these systems are also focus on specific domains in isolation, as house energy or transport.
With current data, machine learning and simulation methods and techniques there are many more possibilities to explore the complexities of all the domains in which carbon emissions of individuals take place, and how can they be saved to create carbon credits. This can be coupled with simulation, visualisation and gamification methods and tools to create powerful and usable systems that are more effective in inducing behavioural change and supporting climate adaptation policies.
The aim of this project will be to explore theoretical concepts and methodological approaches to create an integrated, multidomain (e.g. transport, housing, consumer patterns, finance, indirect emissions), and high-resolution carbon credit system (CCS) for individuals. This will include four main components:
(1) conceptualising a new model of carbon credits, co-designed with relevant stakeholders (e.g. urban decision-makers, transport operators, consumers groups, local community groups) suitable for accounting individual emissions and savings, for different domains of human activities, that can be measured in an accurate, transparent and untransmissible way;
(2) develop a system to compile, process and visualise data to support computing accurate measures of generation and saving of carbon emissions at the individual level, to generate new, interoperable datasets that can be used by different assessment, simulation and gamification tools;
(3) develop multisystem assessment and simulation tools that can help individuals understand in detail their environmental footprint, inducing effective individual behavioural change that contributes to collective sustainability, with clear implications at both the local (neighbourhood) and the city contexts;
(4) develop a policy framework where these individual carbon credits can be used as policy tools to generate effective bottom-up approaches to more sustainable management of aggregate systems that already trade in the carbon credit markets such as transport systems or cities.
This project will make use of existing open access numerical and descriptive data about consumers behaviours (e.g., retail, finance, leisure, public services), housing characteristics and travel behaviours. The project may use area data (e.g. national censuses, deprivation) to characterise neighbourhoods and cross-analyse it with individual data, using estimation models that may be able to complement missing variables in the datasets. The project will also use pilot schemes where new types of sensors are being used to generate accurate carbon emissions, for example in public transport vehicles.
The project will be developed in collaboration with two industry partners which possess expertise in the field.
Modeshift (USA, Bulgaria) has expertise in developing data collection and management systems for public transport operators where carbon emissions are measured accurately for each travel (and not only based on generic vehicle specs). Modeshift participates in international projects and in policy initiatives (for example at the European Union level) to design new policy tools to account for individual carbon credits.
EarthChain (UK) has expertise in developing systems to account and certify carbon emissions using blockchain technology for retail, consumer goods and banking, having experience in working on improving the accuracy of the carbon footprint of supermarket and other consumer goods and in travel emissions.