The Carbon Footprint of Radiation Oncology on Climate Change: A Model in Early-Stage Breast Cancer

Purpose/Objective(s)

Tipping points in climate change are imminent and with them heightened urgency to identify drivers of carbon (CO₂) emissions. In healthcare, little is known of the influence oncology systems have on the environment. We sought to develop a model that evaluates CO₂ emissions produced due to radiation therapy (RT), incorporating contributions from treatment commute and radiation delivery/fractionation (fx) in early-stage breast cancer (ESBC) patients.

Materials/Methods

To model CO₂ emissions generated per patient at completion of RT for ESBC, we identified key emission-altering variables impacting commute and RT delivery (Table 1). CO₂ emissions from commute were modeled by: 1) average distance to a hospital from rural, suburban, and urban community settings using government data and 2) CO2 release per mile by vehicle type (gas car, electric car, and public transport) per EPA data. CO₂ emissions from RT delivery were modeled by: 1) linear accelerator (LINAC) beam-on power per manufacturing data; 2) beam-on time, estimated by average time for 5 patients receiving moderate hypofx (42.4Gy/16fx) and 5 ultra-hypofx (26Gy/5fx) RT; and 3) LINAC energy source (Es) comparing high CO2 emitting (coal: 820 gCO2/kWh) to low CO2 emitting (nuclear: 12 gCO2/kWh) energy plants per IPCC data. Contributions from commute and RT delivery variables were multiplied by the total fx course, comparing moderate vs ultra-hypofx 3D RT schedules. C02 emission analyses between variables were performed using t-test comparisons.

Results

CO₂ emissions produced from a patient's commute to RT were associated with a 6.5-fold increase (8484 vs 1302 gCO₂) when traveling from a rural area by gas car (least efficient) compared to an urban area via public (metro) transportation (most efficient). During treatment, CO₂ emissions varied by RT fx course and LINAC Es. There was a 4.12-fold increase in CO2 emissions with moderate vs ultra-hypofx RT regimens (150 vs 36 kgCO2, p<0.01) with coal energy. In comparison, a 3.22-fold increase in CO2 emissions was detected with moderate vs ultra-hypofx RT regimens (67 vs 21 kgCO2, p<0.01) with nuclear energy. Finally, for a standard moderate hypofx regimen, coal Es use led to a 68-fold increase (5235 vs 77 gC02, p<0.01) in CO2 emissions vs nuclear Es use.

Conclusion

To our knowledge, we present the first model of key emission-altering variables and CO₂ production in RT of ESBC patients. We identify the largest CO₂ drivers to be related to patient commute and LINAC Es—both of which are exacerbated by extended fx courses. This model provides a foundation to further investigate the impact of cancer care on the environment and inform clinical practice changes related to sustainable energy policies.