Electricity Grid Carbon Intensity-Not Imaging Utilization-as the Primary Source of Variation in Greenhouse Gas Emissions for MRI and CT.

Background. MRI- and CT-associated greenhouse gas (GHG) emissions are determined not only by electricity consumption but also the carbon intensity of the power grid supplying such electricity, in turn reflecting local fuel mixtures. Purpose. To assess the relative contributions of imaging utilization and grid carbon intensity to state variation in per-beneficiary GHG emissions attributable to MRI and CT in Medicare Part B fee-for-service beneficiaries. Methods. This retrospective study used national and state-level data from calendar-year 2022 federal datasets. Aggregate MRI and CT service counts in Medicare Part B fee-for-service beneficiaries were obtained from the CMS Medicare Physician and Other Practitioners by Geography and Service file. Medicare Part B FFS enrollment was determined using the CMS Medicare Monthly Enrollment file. Cardon dioxide-equivalent (CO2e) emission rates, measuring GHG emissions associated with electricity generation as an indicator of grid carbon intensity, were obtained from U.S. Environmental Protection Agency data. Per-examination electricity consumption for MRI and CT was obtained from a prior study that extracted scanner data using specialized equipment. GHG emissions were estimated as the product of imaging-associated electricity use (i.e., the product of aggregate service counts and per-examination electricity consumption) and grid carbon intensity. Relative contributions of utilization-weighted electricity use and grid carbon intensity toward variation in per-beneficiary GHG emissions were assessed by log-linear variance decomposition. Results. MRI and CT exhibited national utilization per 1000 beneficiaries of 271 examinations and 805 examinations, respectively; associated estimated electricity use of 157,734 MWh and 28,236 MWh, respectively; and associated estimated GHG emissions of 54,052 MT CO2e and 9991 MT CO2e, respectively Estimated GHG emissions per 1000 beneficiaries nationally were 2.19 MT CO2e, ranging from 0.05 MT CO2e (Vermont) to 4.82 MT CO2e (Missouri). In log-linear decomposition, grid carbon intensity accounted for 76.3% of state variation in per-beneficiary GHG emissions, utilization-weighted electricity use for 16.3%, and their covariance for 7.4%. Conclusion. Per-beneficiary GHG emissions varied widely across states, primarily due to variation in grid carbon intensity rather than utilization-weighted electricity use. Clinical Impact. The findings highlight the role of grid decarbonization and energy procurement strategies in complementing imaging stewardship for reducing imaging's environmental footprint.