POST has published 20 COVID-19 Areas of Research Interest (ARIs) for the UK Parliament. ARIs were identified using the input of over 1,000 experts. They were then ranked in order of interest to UK Parliament research and select committee staff, following internal feedback. Each ARI comes with a series of questions aiming to further break down each broad area. The ARIs focus on the impacts of the global pandemic and range from economic recovery and growth, to surveillance and data collection, long-term mental health effects, education, vaccine development, and the NHS.
Documents to download
Heat networks (314 KB, PDF)
Generating heat and hot water in buildings accounts for a large part of the UK’s greenhouse gas emissions. This is because most heat is made by burning natural gas. Emissions from heating will need to reduce to almost zero by 2050 to meet UK climate change targets. Heat networks are likely to be a part of this emissions reduction.
There are currently around 14,000 UK heat networks and half a million customers. This is low compared to some other parts of Europe and abroad. However, the UK Government has a target for heat networks to supply around a fifth of heat by 2050. To achieve this a new market framework is being created. This is needed to increase investment and put consumer protections in place for heat network customers that are currently lacking.
Key points in this briefing include:
- Heat networks can reduce CO2 emissions from buildings by using heat pumps, waste heat, geothermal heat or other sources. Most currently use natural gas.
- They could technically provide 20% of UK heat by 2050. They provide 2-3% today.
- Heat network developers have a few key considerations. These include the location of new networks and planning policy. They also include how much heat demand there will be and the design of buildings connected to the network. Costs and other commercial considerations are also key.
- On average, heat network customers are as satisfied and have equal or cheaper bills than gas and electric customers. Some customer have had bad experiences in the past.
- The UK Government expects to publish a market framework for heat networks in 2022. It will put consumer protection in place and aims to increase private investment.
POSTnotes are based on literature reviews and interviews with a range of stakeholders and are externally peer reviewed. POST would like to thank interviewees and peer reviewers for kindly giving up their time during the preparation of this briefing, including
- Asad Kwaja, AECOM
- Charlotte Owen, Association for Decentralised Energy*
- Arran Mornin, BEIS*
- Dr Corinna Abesser, British Geological Survey*
- Phil Jones, Building Low Carbon Solutions*
- Dr Meysam Qadrdam, Cardiff University*
- Dr Charlotte Adams, Durham University
- John Armstrong, formerly E.On
- Bindi Patel, formerly Heat Trust
- Chris Twinn, London Energy Transformation Initiative*
- Dr Madeleine Morris, Imperial College London (EnergyREV)*
- Clara Bagenal George, London Energy Transformation Initiative
- Matt Hindle, Energy Networks Association
- Peter Kocen, Energy Networks Association
- Matthew Lipson, Energy Systems Catapult
- Mark Sommerfeld, REA
- Samuel Stevenson, formerly REA
- Scottish Government*
- Simon Woodward, UK District Energy Association*
- Ugbana Oyet, UK Parliament
- Dr David Boardman, University of Birmingham
- Dr Jess Britton, University of Exeter*
- Dr Richard Lowes, University of Exeter*
- Prof Simon Rees, University of Leeds
- Dr Sean Jones, University of Nottingham*
- Prof Bob Critoph, University of Warwick*
- Rufus Ford, Vatenfall*
- Andrew Hirst, Womble Bond Dickinson
- Members of the POST Board
* Denotes contributors who acted as external reviewers for the POSTnote
Documents to download
Heat networks (314 KB, PDF)
Machine learning (ML, a type of artificial intelligence) is increasingly being used to support decision making in a variety of applications including recruitment and clinical diagnoses. While ML has many advantages, there are concerns that in some cases it may not be possible to explain completely how its outputs have been produced. This POSTnote gives an overview of ML and its role in decision-making. It examines the challenges of understanding how a complex ML system has reached its output, and some of the technical approaches to making ML easier to interpret. It also gives a brief overview of some of the proposed tools for making ML systems more accountable.
Over 350 experts have shared with us what they think the implications of the COVID-19 pandemic will be in the next 2 to 5 years. This work was done to inform the House of Lords COVID-19 Committee inquiry on Life beyond COVID, and is based on 366 expert responses. Areas of concern include work and employment, health and social care, research and development, society and community, the natural environment, education, arts, culture and sport, infrastructure and crime and justice.