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January 22nd, 2025
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University of St Andrews
neuroscience
biorxiv

Doctoral Students as Carbon Accountants: Calculating Carbon Costs of a PhD in Neuroscience

Smith, W. V.Open in Google Scholar•Bebbington, A.Open in Google Scholar•Sircar, R.Open in Google Scholar•Pulver, S. R.Open in Google Scholar

PhD students are drivers of innovation in research; however, the carbon intensity of PhD work is often unclear, especially in specialised STEM disciplines. Empowering PhD students to engage in carbon accounting could provide a powerful force for decarbonization in key areas of production and consumption in research communities. Here, we present a comprehensive life-cycle assessment for PhD work in a cellular neuroscience laboratory as part of a larger strategic effort to encourage PhD students to engage in carbon accounting. We measured Scope 1 emissions associated with anaesthetising animals and research-related travel. We then used regional conversion data openly reported by the UK National Grid through the Carbon Intensity API to accurately document time-specific Scope 2 emissions associated with neuroscience research activities, including widely used techniques like calcium imaging, electrophysiology, and optogenetics. Finally, we estimated Scope 3 Emissions associated with procuring particular equipment and consumables using UK GOV 2024 reported conversion factors. Over 1 year, we accounted for 1.56 kg of direct carbon dioxide emissions (CO2), < 1942 kg carbon dioxide equivalent (CO2e) emissions associated with ground and air travel using radiative factor, 3.56 kg CO2e directly underpinning research activities, and 10.99 kg CO2e underlying indirect costs of laboratory facilities. Procurement of a subset of laboratory supplies were estimated to be in the range of < 543 kg CO2e. We discuss challenges of accurately estimating carbon footprints across disciplines in the UK and beyond. Here, we propose a common framework for including carbon life cycle analyses in Carbon Appendices to PhD theses and other publications. Overall, this work demonstrates how PhD students can measure the carbon footprint of their work and catalyse community-led efforts to decarbonize research that are efficient, targeted, and accurate.

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