Tradeoff and complementarity between energy use, transport and food choices under personal carbon trading

Direct energy consumption in the households (resulting from energy use for residences and transport choices) is responsible for the largest share of UK carbon emissions and presents a significant challenge to reducing GHG emissions. The situation is further aggravated if embedded emissions from food, especially meat products, are included in the household emission account, too (e.g. CCC 2018 suggests substantial cuts in the consumption of meat products in order to combat climate change). As such reducing emissions from household consumption is an important front in the challenge to meeting GHG emission target.

This project intends to investigate the effects of a novel policy – personal carbon trading – in order to reduce GHG emissions from the household consumption sector. In such a policy, households will be allocated carbon budgets or permits, which can then be traded amongst themselves, similar to upstream emissions trading schemes. While there has been previous studies on personal carbon trading at the direct energy, transport energy and combined transport and direct energy use level (Wadud 2011, Fawcett 2015, Wadud and Chintakayala 2018), indirect emissions from food or other household consumption has not been included in the household carbon budgets before. Yet, including meat consumption enhances the flexibility available to people in reducing emissions.

The aim of the project is to understand the potential responses of households to such a policy and their potential pathways to reduce emissions. Special focus will be on the consumers’ tradeoff between reducing emissions from in-house energy use, transportation choices and food choices. The project will have a strong quantitative modelling component. It will likely involve choice experiments and choice modelling, although traditional econometric/statistical/quantitative behavioural model or a combination of qualitative and quantitative methods (mixed methods) may also be a possibility.

Co-supervisors: Professor Stephane Hess, Dr Phani Kumar Chintakayala and Dr Hannah Ensaff. Contact Dr Zia Wadud to discuss this project further informally.