Cross-jurisdiction modelling reveals that grid carbon intensity influences the electricity-related carbon footprint in robot-assisted radical prostatectomy, suggesting pathways for reduction.
Electricity consumed during robot-assisted radical prostatectomy (RARP) generates greenhouse-gas emissions that vary with local grid carbon intensity, yet existing environmental reports are mostly single-centre or single-country and therefore cannot separate procedure electricity demand from jurisdictional electricity context. In this cross-sectional modelling study, a standardised intraoperative plug-load model for RARP was linked to publicly available electricity carbon-intensity data from 208 jurisdictions. The base-case demand was 6.5 kW over a reference operative-time distribution with a median of 170 min (IQR 140–180), corresponding to 18.42 kWh per case, with uncertainty propagated to 12.24–20.48 kWh. Structural sensitivity analyses examined robot-only incremental load, low-resource, infrastructure-conditioning, and high plug-load upper-bound settings, together with counterfactual grid-decarbonisation scenarios. Electricity carbon intensity in the archived analytical extraction ranged from 23.8 to 738.8 gCO2eq/kWh, yielding 0.44–13.61 kgCO2eq per case in the base case (median 6.41; IQR 4.19–8.83). Across scenarios, power-demand assumptions changed absolute values, while jurisdictional grid carbon intensity remained the main source of cross-jurisdiction variation within this electricity-only model. Achieving an electricity-related footprint of < 1 kgCO2eq per case required a grid carbon intensity of < 54.3 gCO2eq/kWh and was achieved by 10 jurisdictions in the archived dataset. Within the defined intraoperative plug-load electricity boundary, using life-cycle grid-intensity factors, these results support location-specific reporting and indicate where electricity decarbonisation or operating-theatre energy management can reduce the electricity component of RARP. The analysis is not a full life-cycle assessment of RARP and should be interpreted alongside non-electricity sources such as consumables, sterilisation, anaesthesia, building services, and hospital stay.
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Rafał B. Drobot (2026) studied this question.
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