Recent Data Additions to the EDC

This spreadsheet contains the results for the article, "Meeting the costs of decarbonising industry – the potential effects on prices and competitiveness (a case study of the UK)". These include projected impacts for industrial process decarbonisation (costs, fuel use, residual emissions), for key years (2030, 2040, 2050), distributed in the following ways:

• Directly allocated to industrial sector in which they occur


• Shared between sectors in proportion to the share of GVA of each supply chain


• Embodied in final products


• Embodied in final products, aggregated to consumption patterns

The source of the projections and the method to perform the distribution are described in detail in the associated article.

The Annual Gas and Electricity Consumption at Meter Level, Great Britain, 2004-2022: Secure Access study includes annual gas and electricity consumption data at an individual property level, covering England, Scotland and Wales from 2004 onwards. Both domestic and non-domestic properties are included.

Energy Systems Catapult was set up to accelerate the transformation of the UK’s energy system and ensure UK businesses and consumers capture the opportunities of clean growth. The Catapult is an independent, not-for-profit centre of excellence that bridges the gap between industry, government, academia and research. This links to the searchable interface for the public datasets.

This work benchmarks the existing UK cold chain and provides robust evidence-based data on emissions in 2020. Only emissions from refrigeration within UK borders was considered, both from refrigerant leakage and from electrical power usage. Energy consumption For energy consumption the Digest of UK Energy Statistics (DUKES) was widely used. This data is compiled by the Department for Business, Energy & Industrial Strategy (BEIS) and contains data for many years up until the current year. The United Kingdom Statistics Authority has designated these statistics as National Statistics, in accordance with the Statistics and Registration Service Act 2007 and therefore they were considered as the most accurate data available. DUKES data does not always differentiate the energy consumed by refrigeration systems in each of the cold chain sectors and therefore further analysis and assumptions were often required. Energy consumption values shown were collated per year for the years 2019/2020, unless otherwise stated. Emissions from refrigerant leakage The main GHG refrigerants are the fluorinated gases (f-gases); hydrofluorocarbons (HFCs) and hydrochlorofluorocarbons (HCFCs). According to Brown et al (Brown et al., 2021) emissions of f-gases can occur at various stages of the refrigeration equipment life-cycle: During manufacturing, During installation, Over the operational lifetime, At disposal. The most comprehensive source of information for direct emissions is the UK Greenhouse Gas Inventory. This contains national greenhouse gas emission estimates for the period 1990-2019 and is the United Kingdoms National Inventory Report (NIR) submitted to the United Nations Framework Convention on Climate Change (UNFCCC). It includes losses during manufacture/initial charging and at decommissioning as well as losses in use.

Interviews with actors concerned with local transport decarbonisation in the UK, including challenges related to finance, governance arrangements, and public support. Data were collected using a series of 54 interviews, spread equally across three case study sites: 18 Nottingham, 18 Leeds, and 18 Oxford. Of those, 12 of the Nottingham interviews, all 18 of the Leeds interviews, and 8 of the Oxford interviews are shared in this data deposit (the rest did not give permission for their data to be deposited). The interviews were designed to reveal different local perspectives on areas recent attempts to decarbonise their transport system. The initial introduction to each participant was facilitated by pre-existing professional contacts, after which subsequent participants were identified by snowballing (i.e. feedback from interview participants) in combination with criteria-specific identification (i.e. from a review of published local authority documents

Peer-to-peer (P2P) energy trading could help address grid management challenges in a decentralizing electricity system, as well as provide other social and environmental benefits. Many existing and proposed trading schemes are enabled by blockchain, a distributed ledger technology (DLT) relying on cryptographic proof of ownership rather than human intermediaries to establish energy transactions. This study used an online survey experiment (n = 2064) to investigate how consumer demand for blockchain-enabled peer-to-peer energy trading schemes in the United Kingdom varies depending on how the consumer proposition is designed and communicated. The analysis provides some evidence of a preference for schemes offering to meet a higher proportion of participants energy needs and for those operating at the city/region (as compared to national or neighbourhood) level. People were more likely to say they would participate when the scheme was framed as being run by their local council, followed by an energy supplier, community energy organization, and social media company. Anonymity was the most valued DLT characteristic and mentioning blockchains association with Bitcoin led to a substantial decrease in intended uptake. We highlight a range of important questions and implications suggested by these findings for the introduction and operation of P2P trading schemes.

We set out to study how the promise of green 5G is produced and circulated. We conducted an analysis of a UK-focused corpus of documents that represent key sites through which the promise of green 5G is produced, circulated and challenged. By the promise of green 5G we refer to an emerging, overarching, dominant expectation that 5G will produce positive environmental sustainability benefits of various kinds. We employed an analytical approach informed by the sociology of expectations and the concept of technoscientific promises. We asked: what are the particular contents of this promise (i.e. the more specific promises and expectations it is built upon), how do enactors seek to boost its legitimacy and credibility, what activities are involved in its production and circulation and what are its present-day material effects, does the promise exclude or overlook alternative options, and is it challenged? We pursued these aims and questions through a document analysis of a diverse corpus (n=260) comprised of UK newspaper articles and newswire results, and reports and webpage content from industry, standardisation bodies and research consortia.

This data collection includes a User Guide and the anonymised transcripts of 30 semi-structured interviews of #60-90 minutes each, with 31 high household energy consumers, about their homes, appliances, infrastructures, vehicles, and everyday life and travel practices that generate household (domestic and travel-related) energy demand. It also includes the anonymised transcripts of 4 3-hour deliberatively workshops of ~8 public participants and 2 facilitators, one recruited from the interviewees, and the others recruited to represent different levels of domestic and travel-related energy consumption, held to discuss the validity, fairness, effectively and acceptability of four broad policy approaches to reduce (particularly high levels of) household energy consumption: Rationing; Economic (Dis)Incentives; Structural Change; and Behaviour Change

Using heat demand data for domestic buildings sourced from the UKERC Energy Data Centre's "Spatio-temporal heat demand for LSOAs in England and Wales", we have identified Lower Layer Super Output Areas (LSOAs) exhibiting a linear heat density surpassing 2900 kWh/m indicating their potential suitability for a heat network. We have integrated borehole information from the British Geological Survey (BGS) Single Onshore Borehole Index (SOBI), the average thermal conductivity of general soils and rocks, SAP 10.2 annual average temperature on the ground surface, and the average geothermal gradient for council areas in Great Britain. Employing the specific heat extraction rate methodology, and referencing MCS 022 Borehole Heat Exchanger look-up tables, we have generated comprehensive heat supply potential data from boreholes.

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This dataset relates to the modelling component of the UKERC Phase 4 Project '4.2a Investment in infrastructure'. The aim is to assess the scale of investment risks in the electricity generation sector associated with uncertainty over the pathway towards net zero. The model comprises three components:1. Input data. Based in Excel, contains the scenario assumptions on the electricity system including generation technologies, wind and solar power availability, demand profiles, interconnector and storage capacities etc.2. Modelling files based on the open-source Antares modelling framework. This requires additional free software to be able to run the model. The model calculates the hourly dispatch of all types of plant included in the system.3. Excel-based financial model, based on post-processing the output of the Antares model.Additional 1_Metadata.xls, Input_ReadMe and Outputs_ReadMe files explain the method for running each step of the modelling process. Software available at https://antares-simulator.org/. Version used 8.0.2

UKESTO showcases national energy storage innovation, describing energy storage facilities in the UK and providing data from test beds.

In 2012 the Engineering and Physical Sciences Research Council (EPSRC) funded the Energy Storage Capital Grants call, where fifteen institutions received 30m pounds of funding across five consortia for the development and testing of energy storage technologies that span application areas. The consortia leads were the University of Birmingham, Imperial College, Loughborough University, the University of Manchester, and the University of Sheffield.

In 2016 these institutions secured a 4m pound investment from EPSRC to deliver the Multi-scale Analysis for Facilities for Energy Storage (MANIFEST) project, where the UK Energy Storage Observatory is a major deliverable.

Flexible Networks for a Low Carbon Future was a Low Carbon Networks Fund innovation trial project, led by SP Energy Networks. As part of the project, network monitoring equipment was installed in eight primary (33/11kV) and over 150 secondary (11kV/415V) substations in three test areas

SP Energy Networks are pleased to provide access to the complete data set (which is hosted by the University of Strathclyde) in response to requests.

Estimated number of use cycles by temperature programme for UK domestic washing machines

This file provides a harmonised data for the UK main manufacturing industry based on the NAEI 2020 data https://naei.beis.gov.uk/data/map-large-source, which can be used for analysis and modelling.Since the original NAEI data include sites that do not fall within the definition of manufacturing industry, we created this harmonised data for ease of use. We classified the sectors into: Iron and steel, Chemicals, Cement, Food and drink, Paper, Refining, Lime, Glass, Ceramics, Other minerals, and Other industry. We also converted the 'Easting' and 'Northing' to 'Latitude' and 'Longitude'.

This is an evidence base of available literature on the impacts of offshore wind farm (OWF) developments and the outcomes for marine ecosystem services. The evidence was collated through a systematic search of global primary literature (also known as peer-reviewed or published literature) and UK grey literature regarding the impacts of OWF developments (the scope for including global grey literature was unfeasible). Grey literature refers to multiple types of report or document, and is defined as: "information produced on all levels of government, academia, business and industry in electronic and print formats not controlled by commercial publishing" i.e. where publishing is not the primary activity of the producing body(ICGL, 1997). Data was extracted from each evidence source, for each subject or marine ecosystem component that was impacted by the OWF development, the phase of development, the specific pressure and other relevant information about the wind farm or location. Expert judgement was used to map each piece of evidence for impacts on the marine environment according to CICES (Common International Classification of Ecosystem Services) or MEA (Millenium Ecosystem Assessment) and other published classification systems for ecosystem services (Ryfield et al., 2019; Hooper et al., 2020). The dataset was created to provide a central evidence base of available primary and grey literature regarding the impacts of OWF developments (for construction, operational and decommissing phases) on ecosystem service outcomes in the marine environment. The primary literature represents a global semi-systematic search, while the grey literature is restricted to a semi-systematic search for reports and documents from the UK (that also include wind farms in adjacent waters). The database provides a comprehensive list of available literature on this topic, and it enables the assessment and comparison of the evidence for enviromental impacts and ecosystem service outcomes between primary and grey literature sources. This will be critical for marine policy makers when gathering evidence for future OWF developments and advances understanding of the impacts and trade-offs associated with OWF and ecosystem services. A tool (currently in development by Plymouth Marine Laboratory) will improve accessibility of the data for this purpose. This research was funded by the UKERC Phase 4 research programme.

Annual residential heat demand data for Scotland at Lower Layer Super Output Area (LSOA) level, before and after energy efficiency measures