• Energy Research

To estimate household emissions from a consumption-perspective, national accounts are typically disaggregated to a sub-national level using household expenditure data. While limitations around using expenditure data are frequently discussed, differences in emission estimates generated from seemingly comparable expenditure microdata are not well-known. We compare UK neighbourhood greenhouse gas emission estimates derived from three such microdatasets: the Output Area Classification, the Living Costs and Food Survey, and a dataset produced by the credit reference agency TransUnion. Findings indicate moderate similarity between emission estimates from all datasets, even at detailed product and spatial levels; importantly, similarity increases for higher-emission products. Nevertheless, levels of similarity vary by products and geographies, highlighting the impact microdata selection can have on emission estimates. We focus our discussion on how uncertainty from microdata selection can be reduced in other UK and international contexts by selecting data based on the data generation process, the level of disaggregation needed, physical unit availability and research implications.

This editorial is the introduction to a special issue of Economics Systems Research on the topic of intercomparison of multi-regional input–output (MRIO) databases and analyses. It explains the rationale for dedicating an issue of this journal to this area of research. Then the six papers chosen for this issue are introduced. This is followed by a concluding section outlining future directions for developers and users of MRIO databases.

In the sociological tradition, markets are understood to be constituted of social relations: relations of trust, friendship, power and dependence, which have moral and emotional qualities. In this paper, we explore how people in energy poor households construct the energy market and its impact on energy policy. Drawing on secondary analysis of a large collection of qualitative interviews on the lived experience of energy poverty carried out from 2003 to 2018 (n = 197 interviews and 20 selected), and the results of an OFGEM quantitative survey on consumer engagement released in 2018, we document the experience of the energy poor as actors in the British retail energy market. We uncover a number of challenges and opportunities facing energy poor participants in the market: having access to good quality information about suppliers, energy tariffs and grants, and having the skills and resources to act on this is important, without these it can be difficult for people to take action. In explaining people’s engagement with the market, we draw on the concept of ‘socio-economic attachments’, showing how a supportive network of family and friends, and people’s trust of and resulting loyalty to their energy supplier mediate their engagement. These findings lead us to relational explanations of the retail energy market, with related policy recommendations: if we are to aim for people to act ‘rationally’, they will need support to navigate the market from intermediaries.

Datasets for Nature Energy journal article 'Estimation of global final stage energy-return-on-investment for fossil fuels with comparison to renewable energy sources'. The dataset contains the three concordance matrices (A,B,C) in a single Excel File used in the EXIOBASE-based EROI calculations.

Climate change threatens to undermine the past 50 years of gains in public health. In response, the National Health Service (NHS) in England has been working since 2008 to quantify and reduce its carbon footprint. This Article presents the latest update to its greenhouse gas accounting, identifying interventions for mitigation efforts and describing an approach applicable to other health systems across the world.A hybrid model was used to quantify emissions within Scopes 1, 2, and 3 of the Greenhouse Gas Protocol, as well as patient and visitor travel emissions, from 1990 to 2019. This approach complements the broad coverage of top-down economic modelling with the high accuracy of bottom-up data wherever available. Available data were backcasted or forecasted to cover all years. To enable the identification of measures to reduce carbon emissions, results were disaggregated by organisation type.In 2019, the health service's emissions totalled 25 megatonnes of carbon dioxide equivalent, a reduction of 26% since 1990, and a decrease of 64% in the emissions per inpatient finished admission episode. Of the 2019 footprint, 62% came from the supply chain, 24% from the direct delivery of care, 10% from staff commute and patient and visitor travel, and 4% from private health and care services commissioned by the NHS.This work represents the longest and most comprehensive accounting of national health-care emissions globally, and underscores the importance of incorporating bottom-up data to improve the accuracy of top-down modelling and enabling detailed monitoring of progress as health systems act to reduce emissions.Wellcome Trust.

Under many scenarios, fossil fuels are projected to remain the dominant energy source until at least 2050. However, harder-to-reach fossil fuels require more energy to extract and, hence, are coming at an increasing ‘energy cost’. Associated declines in fossil fuel energy-return-on-investment ratios at first appear of little concern, given that published estimates for oil, coal and gas are typically above 25:1. However, such ratios are measured at the primary energy stage and should instead be estimated at the final stage where energy enters the economy (for example, electricity and petrol). Here, we calculate global time series (1995–2011) energy-return-on-investment ratios for fossil fuels at both primary and final energy stages. We concur with common primary-stage estimates (~30:1), but find very low ratios at the final stage: around 6:1 and declining. This implies that fossil fuel energy-return-on-investment ratios may be much closer to those of renewables than previously expected and that they could decline precipitously in the near future.

Correction to: Nature Energy https://doi.org/10.1038/s41560-020-0579-8, published online 16 March 2020.