The carbon footprint of hospital diagnostic imaging in Australia

Scott McAlister1, Forbes McGain2, Matilde Petersen3

  • 1The Centre for Health Policy, The University of Melbourne, Australia, Wiser Healthcare and Faculty of Medicine and Health, The University of Sydney, Australia, and Department of Critical Care, The University of Melbourne, Grattan St, Parkville, VIC 3010, Australia.

Insights

Diagnostic imaging contributes significantly to healthcare

Area of Science:

  • Environmental Science
  • Healthcare Sustainability
  • Medical Imaging Technology

Background:

  • Diagnostic imaging and pathology testing account for 9% of healthcare's carbon footprint.
  • The carbon footprint of pathology testing is known, but the environmental impact of common imaging modalities was previously unclear.

Purpose of the Study:

  • To quantify the carbon footprint of five common diagnostic imaging modalities.
  • To compare the greenhouse gas emissions of different imaging techniques using life cycle assessment.

Main Methods:

  • A prospective life cycle assessment was conducted at two Australian health services.
  • Five imaging modalities were evaluated: chest X-ray (CXR), mobile chest X-ray (MCXR), computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US).
  • Both attributional and consequential life cycle assessment methods were used, considering scanner electricity, consumables, and waste.

Main Results:

  • Mean emissions varied significantly: MRI (17.5 kg CO2e/scan), CT (9.2 kg CO2e/scan), CXR (0.8 kg CO2e/scan), MCXR (0.5 kg CO2e/scan), and US (0.5 kg CO2e/scan).
  • Standby energy use contributed substantially to emissions.
  • Consequential analysis, excluding standby power, showed lower impacts: MRI (1.1 kg CO2e/scan), CT (1.1 kg CO2e/scan), CXR (0.6 kg CO2e/scan), MCXR (0.1 kg CO2e/scan), and US (0.1 kg CO2e/scan).

Conclusions:

  • Clinicians can reduce imaging's carbon footprint by minimizing unnecessary scans and choosing lower-impact modalities (X-ray, US) over higher-impact ones (MRI, CT) when appropriate.
  • Reducing scanner standby time by turning off equipment and increasing scanner utilization rates can significantly lower per-scan emissions and improve resource efficiency.
Abstract

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