Medical devices, surgical supplies, and implants.

The production and use of single-use disposable items and other consumables emerge as the top contributor to surgical carbon footprints in 17 of 26 studies. For example, consumables accounted for 22% of the TURBT pathway emissions in the UK [10] and 39% of total emissions in CABG procedures [11]. Similarly, in the tonsillectomy LCA, consumables contributed 17%, the largest single category after utilities [12]. This group encompasses surgical gloves, gowns, drapes, single-use instruments or device components, procedure packs, synthetic implants (mesh, screws), and certain pharmaceuticals, with emissions arising from the entire upstream supply chain (raw material extraction, manufacturing, sterilization, packaging) and the downstream disposal (often incineration). Comparative analyses further highlight their impact: in direct laryngoscopy, reusable instrument kits contributed less than 1 kgCO₂e, while sterile single-use supplies added approximately 7 kg CO₂e per procedure, corresponding to nearly 90% of the total footprint [13]; in shoulder arthroscopy, single-use anchors and suture devices were identified as principal drivers of emissions, and their partial replacement achieved roughly a 12% reduction in total carbon output [14]. A German assessment of eight orthopaedic procedures similarly identified consumables as the largest source, accounting for 34.6% of emissions [15]. In spine fusion, metallic implants and bone graft materials were among the most carbon-intensive components due to manufacturing and material processing [16]. Even when comparing abdominal hysterectomy with uterine artery embolization, the higher footprint of the surgical route was partially attributable to more resource-intensive surgical supplies (staplers, sutures, and mesh) compared with interventional materials (coils, catheters) [17].

Energy use (HVAC and lighting).

Hospitals run energy-intensive HVAC systems to maintain strict air exchanges and climate control in operating rooms. Many studies pointed to electricity and natural gas use for OR ventilation, heating, and lighting as a major hotspot. One analysis of tonsillectomy procedures found utilities (mainly HVAC) to be the largest source of GHGs (over 50%) [12]. In another CABG LCA, energy use contributed 48 kgCO2e (12%), and they note most of that was from OR HVAC systems [11]. In maxillofacial surgery, energy use was a smaller contributor (0,5%−0,8%) compared with patient travel, which dominated the total footprint [18]. The contribution of energy can vary substantially depending on the type of energy carrier used (e.g., electricity, natural gas, district heating) and, in the case of electricity, on the carbon emission factor of the national grid. For example, heating with natural gas has broadly similar carbon intensity across countries, whereas electricity-related emissions differ widely: a kWh in France, largely produced from nuclear energy, has a much lower emission factor than in countries with coal or gas-intensive grids. This might explain why, for example, the French tonsil study doesn’t mention energy as a factor (likely low impact per case, and they focused on devices) whereas the UK and NL studies do [19–21]. Nonetheless, keeping an OR running (lights, anaesthesia machine, monitors) for a procedure has a non-trivial footprint, and when OR time or efficiency is studied, it connects to this. For instance, endoscopic carpal tunnel release surgery (CTR) had a higher footprint than the open approach largely because of its longer OR time (hence more facility energy use) than open CTR [21]. Facilities-related emissions in that study were a big portion of the 83 kgCO₂e (meaning HVAC, lights, etc.).

Anaesthetic gases and pharmaceuticals.

The use of volatile anaesthetic agents (such as desflurane, sevoflurane) and nitrous oxide (N₂O) can be a major GHG contributor because these gases are themselves potent greenhouse gases when released unscavenged [22–24]. However, their impact in the carbon footprint results varies widely depending on if and how studies included them. In several recent studies, anaesthetic gases were purposefully minimized or omitted: one study demonstrated that eliminating volatile gases via regional anaesthesia reduced the footprint by 40.9 kgCO₂e (which we infer largely came from eliminating desflurane) [14]. Another assessment of labour analgesia illustrated the extreme case with nitrous oxide: just that gas usage can dwarf all other sources, adding 230 kgCO₂e per case [19]. In contexts like standard surgery under general anaesthesia, the footprint of anaesthetic gases depends on which agents are used and for how long. Desflurane has a GWP c.a. 2,500 times CO₂ and N₂O c.a. 300, so even a few litres can equal tens of kg of CO₂. Anaesthesia/drugs and associated adjuncts were 27% of TURBT pathway emissions, although they clarify much of that was from consumables in anaesthesia (e.g., disposable breathing circuits, meds) rather than the gases themselves [10]. Indeed, a trend is that many centres have shifted away from high-emission gases: the CABG study mentioned total intravenous anaesthesia (TIVA) was used, so anaesthetic gases didn’t feature heavily in that footprint [11]. In contrast, where older practices involved desflurane or N₂O, these agents typically dominated the total emissions profile. Overall, anaesthetic practice remains a controllable hotspot: when high-GWP gases are employed, they can be the largest single contributor to surgical emissions, whereas adoption of low-GWP or gas-free approaches markedly reduces this impact, though drug production and supply chains still contribute residual emissions. A particularly striking example comes from plastic and reconstructive surgery: in DIEP flap breast reconstruction, the induction, maintenance and running of anaesthesia together contributed approximately 67.6% of the total procedural footprint (158 of 234 kgCO₂e), reflecting the long operative time (typically 8–10 hours) characteristic of microvascular procedures and the use of nitrous oxide plus oxygen at 5 L/min for maintenance [25]. In contrast, the breast implant reconstruction pathway at the same centre [26] adopted total intravenous anaesthesia (propofol + remifentanil) with no volatile maintenance gases: under this protocol, anaesthesia-related emissions fell to 16.6% of total procedural footprint, illustrating in practice how the choice of anaesthetic technique alone can reduce this hotspot by several-fold within the same clinical setting.

Patient and staff travel.

Travel emissions can be significant, especially in studies with broader pathways. In maxillofacial surgeries, patient transportation accounted for 66–70% of total emissions, because patients travelled for multiple consults and follow-ups for their surgery [18]. In an assessment of coronary artery bypass grafting, staff commuting contributed around 9% (36 kg CO₂e) of total emissions, ranking as the third-largest source after consumables and energy use [11]. Patient travel for pre-op was 18.6% of TURBT emissions [10]. In comparative assessments of childbirth in different European countries, travel mode and distance contributed to inter-country variability, although their influence was overshadowed by the dominant impact of nitrous oxide use [19]. Travel didn’t feature in some studies that only considered OR time [21,27], but where it is counted, travel often emerges as a major emissions source, especially when the procedure itself has relatively low inherent emissions or when multiple visits are required. This underscores the importance of defining system boundaries clearly: decarbonizing hospital operations alone may not substantially reduce overall emissions if extensive patient or staff travel persists. The integration of telemedicine, consolidation of appointments, and scheduling strategies to minimize round trips have been proposed as practical interventions [28,29]. It is context-dependent: a single outpatient visit might be small, but numerous visits for complex care can add up to more than the surgery itself [18]. Similar findings were reported for autologous breast reconstruction: in the DIEP flap pathway, combined patient and staff travel contributed more than 15% of total emissions [25], and in the autologous microtia reconstruction pathway patient travel alone represented the dominant source when excluding inpatient stay (83.4% of bottom-up calculated emissions), reflecting the geographical centralization of quaternary plastic surgery services [30].

Sterilization and reprocessing.

The energy and water needed to sterilize reusable instruments or linens contributes some emissions. In tonsil surgery, instrument decontamination was 5.4% (2 kgCO₂e of the 41 kgCO₂e) [12]. One study specifically tested an alternative to steam sterilization (high-level disinfection) and found it could cut 11% of the procedure’s GHG by saving energy [13]. Although sterilization is not typically the dominant contributor, it remains a consistent component of surgical footprints. Transitions from reusable to single-use systems essentially shift emissions from sterilization to manufacturing processes, often increasing overall impacts, though results depend on usage rates and local energy sources. Generally, life cycle analyses favour reusable instruments when reprocessed a sufficient number of times, since the manufacturing of a new disposable item for each procedure tends to be far more carbon-intensive than repeated steam sterilization cycles

It should be noted that sterilization and laundry emissions are frequently approximated in surgical LCAs rather than directly measured. Many studies rely on standardized emission factors from reference assessments [31], which provided baseline energy and water consumption estimates per reprocessing cycle for orthopaedic instruments. This practice, while practical for comparability, introduces some uncertainty that should be considered when interpreting absolute values.

Waste disposal.

Paradoxically, disposal of waste (incineration or landfill) was addressed in each article reviewed, but its impact is usually a minor contributor to GHG. In several analyses, waste treatment accounted only 3–5% [11,12]. Evidence from operating room audits confirms that focusing exclusively on waste treatment captures less than 10% of the total footprint [32,33]. Annual waste-related emissions for surgical departments have been measured in the range of a few tonnes of CO₂e, whereas upstream emissions from procurement, manufacturing, and energy use reach tens to hundreds of kilograms per individual procedure. Nevertheless, waste management remains environmentally relevant beyond its carbon impact due to plastic pollution, resource depletion, and the visibility of waste streams within healthcare facilities. Moreover, regulated medical waste incineration carries a substantially higher CO₂ emission factor per kilogram than general waste. Multiple analyses emphasized that improved waste segregation could prevent up to 90% of non-hazardous materials from entering high-energy treatment streams unnecessarily. The hotspot is not the incineration emissions per se, but the choice of disposable vs reusable which affects how much waste is generated in the first place.

The major carbon hotspots identified across studies are: (1) the supply chain of single-use devices and consumables, (2) energy use for OR HVAC/equipment, (3) travel (in broader system-boundary analyses), (4) anaesthetic gases (where used), and (5) to a lesser extent, sterilization processes and waste management. These broadly correspond to what the 2022 Green Theatre Checklist initiatives have targeted and confirmed in 2025: focusing on anaesthetic practices, energy, procurement, and waste segregation. A qualitative systematic review also found anaesthetic gases, sterilization, and habitual practices (like leaving equipment running) as key emission sources, and linked many sustainability measures to structural changes like policy on reusables and recycling [34].

Variability in system boundaries.

A major source of heterogeneity was the definition of system boundaries which varied along two distinct dimensions: the breadth of GHG scopes considered, and the temporal extent of the patient pathway included. Considering first the GHG scope dimension, only about half of the studies explicitly accounted for all three scopes of healthcare GHG emissions (see S2Table for details). In contrast, many studies employed truncated boundaries, omitting one or more scopes. These boundary differences pose a significant comparability challenge, a “carbon footprint” of a procedure in one study might encompass a very different set of processes than in another study. As a result, absolute footprint values cannot be directly compared across studies without accounting for what sources were included. Notably, the highest footprint estimates tended to come from studies with the broadest system boundaries, whereas narrowly focused studies reported much smaller carbon totals. This underscores that boundary scope is a key determinant of the reported footprint. It also represents a potential bias: studies that neglect major upstream or downstream processes are likely to underestimate total emissions, sometimes substantially so. Given that 70–80% of healthcare’s carbon emissions typically arise indirectly along the supply chain (Scope 3) [35], excluding these components can omit the majority of a surgery’s true footprint. Encouragingly, several of the most recent studies did adopt more comprehensive life-cycle boundaries that include supply-chain contributions, aligning with best-practice recommendations to broaden scopes in healthcare sustainability metrics. Variability in system boundaries remains a prominent limitation of the evidence base, and greater standardization is needed to ensure completeness and enable fair comparisons.

A second, equally consequential boundary dimension concerns whether the carbon footprint is estimated for the perioperative phase only (typically from entering to leaving the operating theatre) or for the whole patient care pathway, encompassing preoperative consultations, imaging, travel, inpatient stay and postoperative follow-up. This distinction has profound implications for both the magnitude and the composition of the reported footprint. Narrow-boundary studies focused on operating-theatre activity [21,27] tend to report lower totals dominated by consumables and intraoperative energy use, while whole-pathway assessments [10,11,18,25,26,30,36] capture additional sources such as patient and staff travel, outpatient clinic energy use and inpatient bed-days, which can individually exceed the emissions of the surgical step itself. Recognizing this dichotomy is essential when interpreting comparative figures: whole-pathway assessments are more representative of the true climate burden of surgery, while perioperative-only audits are more suitable for evaluating intraoperative interventions.

Transparency of assumptions and reporting.

Most studies were relatively strong in reporting transparency, but there were notable exceptions. Nearly all clearly stated their overarching goals and scope (e.g., defining the surgical procedure and system studied), and 90% explicitly listed which greenhouse gases were counted (typically CO₂, with some also including CH₄ and N₂O in CO₂e) in their calculations. Many also provided detailed breakdowns of results by subprocess or emission source, which enhances interpretability. This level of detail is a strength, as it allows readers to see the major contributors and check consistency with the methods. On the other hand, a minority of studies lacked clarity in important assumptions. In roughly one-third of the papers, the authors did not clearly document the number of data points or measurements underlying each process, for instance, whether energy use was measured directly or estimated, and how many observations informed that estimate. Such omissions make it difficult to judge the reliability of those results. In a few cases, key methodological choices were only vaguely described or buried in supplementary materials (e.g., how equipment utilization was allocated, or why certain items were excluded). The exclusions and assumptions reported by each study (see S3 Table) reveal that while most authors did state their major assumptions and justifications, some provided only limited detail. None of the included studies underwent any external peer audit of their carbon accounting, and only a handful explicitly discussed the completeness of their data or potential gaps. This lack of critical appraisal of data completeness is common in healthcare LCAs, previous work has found that authors often do not assess whether all relevant processes/data were captured [37]. Overall, transparency was one of the stronger areas of quality (reflected in consistently high scoring on this domain), but there remains room for improvement in clearly conveying all assumptions, exclusions, and data collection methods. Clearer reporting would improve reproducibility and allow the research community to more easily identify reasons for differences between studies.

Data sources and quality.

The accuracy and reliability of the footprint estimates depend heavily on data quality. In this regard, the studies showed mixed performance. Only 2 out of 26 studies relied exclusively on primary data (i.e., direct measurements specific to the study hospital) for all inputs considered; the vast majority combined primary and secondary data. Commonly, authors measured a few parameters in situ and obtained others from the literature or databases. While using secondary data is often unavoidable, for example, no single hospital can directly measure the embodied emissions of manufactured drugs or devices, it does introduce uncertainty and potential bias if the data are not representative. Many studies assumed literature values or industry averages that may not reflect the local context of their hospital. For instance, several analyses used national conversion factors for waste disposal or energy, sometimes even from other countries due to data availability. Few studies discussed the implications of these choices. In fact, consistency in data representativeness was generally weak: none of the studies formally evaluated how temporally or geographically representative their data were.

Many studies had to assume usage patterns (for equipment, HVAC, etc.) in the absence of direct monitoring. The specificity of data sources was captured in our quality scoring, nearly all studies scored “1” (on a 0–2 scale) for using a mix of primary and secondary data, indicating moderate fidelity. Importantly, the lack of uncertainty analysis means we do not know how much error these data choices might be introducing. In summary, data quality is a concern across the board. Even where primary data were used, sample sizes were often small: some studies based calculations on just 5–15 procedures, which raises questions about statistical reliability. Secondary data, while necessary for life-cycle modelling, were not always transparently sourced or up-to-date. These issues highlight the need for more robust data collection and validation in future studies, as well as for reporting of data uncertainties.

Adherence to LCA standards.

About half of the studies explicitly stated that they followed a recognized carbon footprinting or LCA standard, whereas the others did not mention any formal guidance. This split was reflected in the consistency domain scores. Those that did cite a standard (such as the ISO 14040/14044 LCA framework or the GHG Protocol Product Standard) generally showed better methodological coherence. For example, several studies referenced using the GHG Protocol or ISO guidelines to define their scope and inventory, and one study applied a < 1% materiality threshold (cut-off rule) for minor emission sources, which is in line with PAS 2050 and other standards. By contrast, studies that did not reference any guidelines sometimes made ad hoc methodological choices, for instance, defining functional units or impact boundaries in non-standard ways, which could introduce bias. In our sample, there was evidence that newer studies are moving toward accepted norms. Many 2024–2025 studies referenced, at minimum, the inclusion of Scope 1–3 emissions per the GHG Protocol taxonomy or cited performing a life-cycle assessment per ISO protocols. This is a positive development because following established frameworks tends to improve consistency: it ensures, for example, that if two studies both claim to do an LCA, they will at least share common definitions and steps (goal and scope definition, inventory analysis, impact assessment, interpretation). Indeed, among the comparative studies in our review, nearly all applied uniform methods to both comparators, yielding high consistency scores. Only one or two comparative studies had minor consistency issues (e.g., slightly different data sources used between the compared groups), and these were flagged as potential biases. Overall, the use of standard methods is a notable strength for roughly half the studies; the remainder would benefit from closer alignment with published LCA guidance to enhance credibility.