Estimating CO2 emissions from international medical electives: a literature review and quantitative analysis
Bibliographic record
Abstract
• There is growing concern regarding the carbon footprint associated with face-to-face international electives. • Virtual electives are undertaken by students and instructors who are separated in space, where instructors can teach remotely via the internet using technology such as videoconferencing and virtual reality. These virtual electives have recently appeared as an attractive alternative with the potential to contribute to improving the sustainability of medical education and student satisfaction has so far been broadly positive based on available literature. • We performed calculations for direct round trips from the United Kingdom (UK) to the 10 most popular elective destinations for UK medical students. • Our CO2 emissions calculator produced similar emission estimates to other calculators used, and suggests that the carbon footprint of IMEs is substantial. • Future research should also evaluate alternative programmes, to assess whether or not virtual or local electives are considered to provide the same educational benefits as in-person electives. Electives are short placements during medical school lasting 2–8 weeks, serving as an opportunity to engage with different healthcare systems and cultures and to travel overseas. However, amid increasing alarm about climate change, interest in the sustainability of electives and alternative elective formats are gaining attention. A scoping review of MEDLINE, Embase, ERIC, Web of Science SCOPUS, WHO Globus Index Medicus and Scielo was conducted with double-blind screening to identify previous efforts to quantify carbon costs of electives. To quantify the carbon dioxide (CO 2 ) emissions of electives, we created an approach based on the fuel efficiency of aircraft used for long-haul travel, distances from the UK to popular elective destinations and the average occupancy rates of aeroplanes. These results were compared with results from seven existing resources: MyClimate, ICAO, Google Flights, C Level and EcoTree. The review did not identify any previous studies estimating the environmental costs of medical student electives. All of the 7,575 records revealed by the database search were excluded following full-text screening. Our estimates of the CO 2 emissions from round-trip flights from Heathrow Airport, London, UK to the 10 most popular elective destinations were: Australia: 2,995 kg/person, USA: 1,039 kg/person, New Zealand: 3,316 kg/person, Canada: 941 kg/person, India: 1,185 kg/person, South Africa: 1,705 kg/person, Malaysia: 1,867 kg/person, Tanzania: 1,322 kg/person, Ireland: 79 kg/person. This is the first study to quantify the carbon footprint of international medical electives. Our bespoke calculations, which generally agree with the results from established tools, reveal that CO 2 emissions from international travel for electives are substantial, compared to the average annual CO 2 emissions of 7,000 kg per person in the UK. This study provides evidence to motivate the design and delivery of alternative elective programmes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.034 | 0.037 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".