a b s t r a c tDoes the association between household characteristics and household CO 2 emissions differ for areas such as home energy, transport and indirect emissions? This question is policy relevant because distributional implications of mitigation policies may vary depending on the area of emissions that is targeted if specific types of households are likely to have higher emissions in some areas than in others. So far, this issue has not been examined in depth in the literature on household CO 2 emissions. Using a representative UK expenditure survey, this paper compares how household characteristics like income, household size, education, gender, worklessness and rural or urban location differ in their association with all three areas as well as total emissions. We find that these associations vary considerably across emission domains. In particular, whilst all types of emissions rise with income, low income, workless and elderly households are more likely to have high emissions from home energy than from other domains, suggesting that they may be less affected by carbon taxes on transport or total emissions. This demonstrates that fairness implications related to mitigation policies need to be examined for separate emission domains.

This is a repository copy of Provisioning systems for a good life within planetary boundaries.

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Climate change scholars generally urge that CO 2 emissions need to be cut rapidly if we are to avoid dangerous risks of climate change. However, climate change mitigation policies are widely perceived to have regressive effects -that is, putting a higher financial burden as a proportion of household income on poor than on rich households. This is one of several major barriers to the adoption of effective mitigation policies. They would also have considerable social justice implications requiring significant welfare state responses. We assess the claim that climate change policies have regressive effects by comparing different types of mitigation policies. We will argue that many of these are indeed likely to have regressive distributional implications but that there are several policy options to counteract regressive effects.

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