̽��ֱ�� of Cambridge - EMBL-EBI

Act now to prevent uncontrolled rise in carbon footprint of computational science

cjb250 — Mon, 26 Jun 2023 09:04:03 +0000

Writing in Nature Computational Science, researchers from the Department of Public Health and Primary Care at the ̽��ֱ�� of Cambridge argue that the scientific community needs to act now if it is to prevent a potentially uncontrolled rise in the carbon footprint of computational science as data science and algorithms increase in usage.

Dr Loïc Lannelongue, who is a research associate in biomedical data science and a postdoctoral associate at Jesus College, Cambridge, said: “Science has transformed our understanding of the world around us and has led to great benefits to society. But this has come with a not-insignificant – and not always well understood – impact on the environment. As scientists – as with people working in every sector – it’s important that we do what we can to reduce the carbon footprint of our work to ensure that the benefits of our discoveries are not outweighed by their environmental costs.”

Recent studies have begun to explore the environmental impacts of scientific research, with an initial focus on scientific conferences and experimental laboratories. For example, the 2019 Fall Meeting of the American Geophysical Union was estimated to emit 80,000 tons of CO2e* (tCO2e), equivalent to the average weekly emissions of the city of Edinburgh, UK. ̽��ֱ��annual carbon footprint of a typical life science laboratory has been estimated to be around 20 tCO2e.

But there is one aspect of research that often gets overlooked – and which can have a substantial environmental impact: high performance and cloud computing.

In 2020, the Information and Communication Technologies sector was estimated to have made up between 1.8% and 2.8% of global greenhouse gas emissions – more than aviation (1.9%). In addition to the environmental effects of electricity usage, manufacturing and disposal of hardware, there are also concerns around data centres’ water usage and land footprint.

Professor Michael Inouye said: “While the environmental impact of experimental ‘wet’ labs is more immediately obvious, the impact of algorithms is less clear and often underestimated. While new hardware, lower-energy data centres and more efficient high performance computing systems can help reduce their impact, the increasing ubiquity of artificial intelligence and data science more generally means their carbon footprint could grow exponentially in coming years if we don’t act now.”

To help address this issue, the team has developed GREENER (Governance, Responsibility, Estimation, Energy and embodied impacts, New collaborations, Education and Research), a set of principles to allow the computational science community to lead the way in sustainable research practices, maximising computational science’s benefit to both humanity and the environment.

Governance and Responsibility

Everyone involved in computational science has a role to play in making the field more sustainable: individual and institutional responsibility is a necessary step to ensure transparency and reduction of greenhouse gas emission.

For example, institutions themselves can be key to managing and expanding centralised data infrastructures, and in ensuring that procurement decisions take into account both the manufacturing and operational footprint of hardware purchases. IT teams in high performance computing (HPC) centres can play a key role, both in terms of training and helping scientists monitor the carbon footprint of their work. Principal Investigators can encourage their teams to think about this issue and give access to suitable training. Funding bodies can influence researchers by requiring estimates of carbon footprints to be included in funding applications.

Estimate and report the energy consumption of algorithms

Estimating and monitoring the carbon footprint of computations identifies inefficiencies and opportunities for improvement.

User-level metrics are crucial to understanding environmental impacts and promoting personal responsibility. ̽��ֱ��financial cost of running computations is often negligible, particularly in academia, and scientists may have the impression of unlimited and inconsequential computing capacity. Quantifying the carbon footprint of individual projects helps raise awareness of the true costs of research.

Tackling Energy and embodied impacts through New collaborations

Minimising carbon intensity – that is, the carbon footprint of producing electricity – is one of the most immediately impactful ways to reduce greenhouse gas emissions. This could involve relocating computations to low-carbon settings and countries, but this needs to be done with equity in mind. Carbon intensities can differ by as much as three orders of magnitude between the top and bottom performing high-income countries (from 0.10 gCO2e/kWh in Iceland to 770 gCO2e/kWh in Australia).

̽��ֱ��footprint of user devices is also a factor: one estimate found that almost three-quarters (72%) of the energy footprint of streaming a video to a laptop is from the laptop, with 23% used in transmission and a mere 5% at the data centre.

Another key consideration is data storage. ̽��ֱ��carbon footprint of storing data depends on numerous factors, but the life cycle footprint of storing one terabyte of data for a year is of the order of 10 kg CO2e. This issue is exacerbated by the duplication of such datasets in order for each institution, and sometimes each research group, to have a copy. Large (hyperscale) data centres are expected to be more energy efficient, but they may also encourage unnecessary increases in the scale of computing (the ‘rebound effect’).

Education and Research

Education is essential to raise awareness of the issues with different stakeholders. Integrating sustainability into computational training courses is a tangible first step toward reducing carbon footprints. Investing in research that will catalyse innovation in the field of environmentally sustainable computational science is a crucial role for funders and institutions to play.

Recent studies found that the most widely-used programming languages in research, such as R and Python, tend to be the least energy efficient ones, highlighting the importance of having trained Research Software Engineers within research groups to ensure that the algorithms used are efficiently implemented. There is also scope to use current tools more efficiently by better understanding and monitoring how coding choices impact carbon footprints.

Dr Lannelongue said: “Computational scientists have a real opportunity to lead the way in sustainability, but this is going to involve a change in our culture and the ways we work. There will need to more transparency, more awareness, better training and resources, and improved policies.

“Cooperation, open science, and equitable access to low-carbon computing facilities will also be crucial. We need to make sure that sustainable solutions work for everyone, as they frequently have the least benefit for populations, often in low- and middle-income countries, who suffer the most from climate change.”

Professor Inouye added: “Everyone in the field – from funders to journals to institutions down to individuals – plays an important role and can, themselves, make a positive impact. We have an immense opportunity to make a change, but the clock is ticking.”

̽��ֱ��research was a collaboration with major stakeholders including Health Data Research UK, EMBL-EBI, Wellcome and UK Research and Innovation (UKRI).

*CO2e, or CO2-equivalent, summarises the global warming impacts of a range of greenhouse gases and is the standard metric for carbon footprints, although its accuracy is sometimes debated.

Reference
Lannelongue, L et al. GREENER principles for environmentally sustainable computational science. Nat Comp Sci; 26 June; DOI: 10.1038/s43588-023-00461-y

For more information on energy-related research in Cambridge, please visit Energy IRC, which brings together Cambridge’s research knowledge and expertise, in collaboration with global partners, to create solutions for a sustainable and resilient energy landscape for generations to come.

Cambridge scientists have set out principles for how computational science – which powers discoveries from unveiling the mysteries of the universe to developing treatments to fight cancer to improving our understanding of the human genome, but can have a substantial carbon footprint – can be made more environmentally sustainable.

Science has transformed our understanding of the world around us and has led to great benefits to society. But this has come with a not-insignificant – and not always well understood – impact on the environment

Loic Lannelongue

geralt

Binary world

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Ambitious project launched to map genomes of all life in British Isles

jg533 — Fri, 08 Nov 2019 00:01:00 +0000

̽��ֱ��£9.4m funding will support a collaboration of ten research institutes, museums and associated organisations to launch the first phase of sequencing all the species on the British Isles. This will see the teams collect and ‘barcode’ around 8,000 key British species of animal, plant and fungi, and deliver high-quality genomes of 2,000 species.

Exploring the genomes – the entire DNA - of these species will give an unprecedented insight into how life on Earth evolved. It will uncover new genes, proteins and metabolic pathways to help develop drugs for infectious and inherited diseases.

At a time when many species are under threat from climate change and human development, the data will also help characterise, catalogue and support conservation of global biodiversity for future generations.

“This project is the start of a transformation for biological research. It will change our relationship to the natural world by enabling us to understand life as never before,” said Professor Richard Durbin in Cambridge ̽��ֱ��’s Department of Genetics, who will lead the ̽��ֱ��’s involvement in the collaboration. “It will create a knowledge resource for others to build on, just as we’ve seen with the Human Genome Project for human health.”

From the small fraction of the Earth’s species that have been sequenced, enormous advances have been made in knowledge and biomedicine. From plants, a number of lifesaving drugs have been discovered and are now being created in the lab – such as artemisinin for malaria and taxol for cancer.

Assembling the full genetic barcode of each species from the millions of genetic fragments generated in the sequencing process will rely on the ̽��ֱ�� of Cambridge’s expertise in computational analysis.

“Genome assembly is like doing a very complicated jigsaw puzzle. ̽��ֱ��genome revolution is all about information, and our ability to put the sequencing data together is based on cutting-edge computing techniques,” said Dr Shane McCarthy at the ̽��ֱ�� of Cambridge, who will work on the project with Professor Durbin.

̽��ֱ��project will identify and collect specimens that will include plants from the Cambridge ̽��ֱ�� Botanic Garden. It will set up new pipelines and workflows to process large numbers of species through DNA preparation, sequencing, assembly, gene finding and annotation. New methods will be developed for high-throughput and high-quality assembly of genomes and their annotation, and data will be shared openly through existing data sharing archives and project specific portals.

̽��ֱ��10 institutes involved in the project are:

• ̽��ֱ�� of Cambridge
• Earlham Institute (EI)
• ̽��ֱ�� of Edinburgh
• EMBL’s-European Bioinformatics Institute (EMBL-EBI)
• ̽��ֱ��Marine Biological Association (Plymouth)
• Natural History Museum
• Royal Botanic Gardens Kew
• Royal Botanic Garden Edinburgh
• ̽��ֱ�� of Oxford
• Wellcome Sanger Institute

̽��ֱ��consortium ultimately aims to sequence the genetic code of 60,000 species that live in the British Isles. Its work will act as a launchpad for a larger ambition to sequence all species on Earth, as part of the Earth Biogenome Project.

Dr Michael Dunn, Head of Genetics and Molecular Sciences at Wellcome, said, “ ̽��ֱ��mission to sequence all life on the British Isles is ambitious, but by bringing together this diverse group of organisations we believe that we have the right team to achieve it. We’ll gain new insights into nature that will help develop new treatments for infectious diseases, identify drugs to slow ageing, generate new approaches to feeding the world and create new bio-materials.”

Adapted from a press release by Wellcome.

An unprecedented insight into the diverse range of species on the British Isles will be made possible by Wellcome funding to the Darwin Tree of Life project.

This project is the start of a transformation for biological research.

Richard Durbin

Jim Haseloff

Liverwort (Pellia epiphylla)

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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