Assessing Energy and Waste Impacts in Orthopaedic Departments: A Case Study from an Italian Public Hospital ^†

Abstract

Hospitals are major consumers of natural resources, and their continuous 24/7 demands exert significant environmental repercussions. Notably, energy utilization and waste generation constitute primary determinants of the ecological footprint associated with healthcare facilities. This study aims to provide a replicable framework for estimating operational carbon account of orthopedic hospital operations using readily available data, without requiring expert-level life cycle assessment tools. A three-level analysis was applied to a case study in a large Italian public hospital, focusing on CO₂e emissions from energy consumption and hazardous waste generation. Operational data from the hospital and detailed audits of orthopedic procedures were used to estimate energy consumption, ventilation loads, and waste volumes. Results showed that HVAC systems dominated energy-related emissions, while surgical waste was a major contributor at the meso- and micro-levels. Several mitigation strategies were proposed, including reducing off-hours air exchange rates and improving waste segregation, leading to potential emission reductions. The study highlights that even a simplified carbon accounting approach can generate valuable insights for healthcare managers, supporting internal benchmarking and sustainability action.

1. Introduction

The healthcare sector presents a fundamental paradox: its primary mission of safeguarding and enhancing human health stands in contrast to its increasing recognition as a significant contributor to environmental degradation, notably climate change, which poses an escalating and direct threat to global public health. As the adverse health consequences of climate disruption intensify, manifested through extreme weather events, air pollution, and the proliferation of vector-borne diseases, the sector functions both as a critical first responder and an unintended driver of these crises. This dual role has spurred considerable research focused on quantifying the environmental footprint of healthcare systems worldwide. The management of healthcare waste is particularly challenging due to the presence of complex and heterogeneous waste streams, often composed of mixed materials and subject to contamination risks. These characteristics make effective segregation comparable to other complex systems such as municipal or packaging waste streams, where improper sorting can significantly increase environmental impacts [1]. Recent studies have highlighted the critical role of energy systems and energy efficiency measures in healthcare facilities, emphasizing the contribution of hospital buildings, HVAC systems, and energy supply strategies to overall carbon emissions and operational sustainability [2].

A seminal global analysis [3] estimated that the healthcare sector accounts for approximately 4.4% of total global greenhouse gas (GHG) emissions, thereby ranking it among the most carbon-intensive service industries. National-level studies from Europe, North America, Asia, and Oceania consistently show that the healthcare sector represents a non-negligible share of national greenhouse gas emissions, although with substantial variability depending on energy mixes, healthcare organization, and service intensity. In Australia, healthcare accounts for 7% of national emissions [4]; in the United States, estimates range from 8 to 10% [5], in Canada, 5% [6], while in Japan and China, healthcare contributes 4.6% and 2.7%, respectively [7,8].

In the Netherlands, a study [9] broadened the scope of analysis beyond climate change to encompass other environmental stressors, including material extraction, blue water consumption, and land use. Similarly, the healthcare sector’s “extinction-risk footprint” was quantified in the Netherlands and across Europe [10], revealing that food supply chains, rather than pharmaceuticals or energy consumption, are disproportionately responsible for threats to biodiversity.

Hospitals consistently emerge as major sources of emissions within national healthcare systems. Building infrastructure and catering were identified as primary environmental hotspots across 33 Swiss hospitals [11], while the emissions of a German hospital using a hybrid financial model were quantified [12], demonstrating the dominance of indirect (Scope 3) emissions in the carbon footprint.

Indeed, supply chain emissions, classified as Scope 3 under the GHG Protocol [13], represent a recurrent theme. A hybrid assessment approach employed at Erasmus MC [14] in the Netherlands found that 72% of the institution’s emissions stemmed from Scope 3 activities, particularly pharmaceuticals and medical devices. Similarly, another study [15] reported that medicines and devices accounted for nearly 60% of Geneva’s healthcare carbon footprint, followed by hospital operations and patient transport. In England, ref. [16] reported that 62% of the entire National Health Service’s (NHS) emissions in 2019 originated from its supply chain, further emphasizing the central role of indirect emissions.

The environmental impact of anesthetic gases and pharmaceuticals has also garnered increasing attention. Several studies [17,18,19] have demonstrated substantial carbon intensities associated with desflurane and single-use medical devices. Within operating rooms, the emissions per surgical procedure exhibit considerable variability, influenced by energy consumption and the choice of anesthetic agents, with reported differences exceeding an order of magnitude across institutions [20]. In Japan [7], those patients aged 65 and older account for over half of the nation’s healthcare emissions, primarily due to hospitalization and pharmaceutical consumption. Similar trends have been observed in Austria, where overall healthcare emissions have decreased over a decade due to increased use of renewable energy sources, although emissions from patient travel have increased [21].

Significantly, methodological approaches have evolved to more accurately capture these dynamics. Hybrid models, integrating bottom-up Life Cycle Assessment (LCA) with top-down environmentally extended input–output (EEIO) methods, have been widely adopted [4,16], enabling enhanced granularity and system-level insights. While EEIO methods capture broad systemic flows, LCA remains indispensable for assessing individual products or procedures, a complementarity that several authors emphasize as essential for policy-relevant analysis [9,19].

Despite this expanding body of research, notable knowledge gaps persist, particularly within national contexts characterized by regionally decentralized healthcare systems or a lack of standardized environmental reporting frameworks. Italy represents such a context. Although research addressing the environmental impact of Italian healthcare is emerging, comprehensive studies remain limited, especially those examining environmental performance at the departmental or procedural level. A preliminary assessment of energy and waste impacts in an orthopaedic department of an Italian public hospital was presented in a conference proceeding [22], laying the groundwork for the comprehensive multilevel analysis developed in this study.

Recent studies have begun to quantify the environmental burdens associated with Italian hospitals, providing valuable insights into sustainability challenges and potential interventions. A significant area of investigation concerns hospital food services, which contribute substantially to both waste generation and GHG emissions. One study revealed that meals with lower carbon footprints were often discarded more frequently, thereby negating their ecological benefit [23]. Weekly per-patient emissions were estimated to be as high as 11.5 kg of carbon dioxide equivalent (kgCO₂e) at lunch and 7.0 kgCO₂e at dinner.

At a systemic level, a national study identified deficiencies in energy governance across 1062 hospitals, with an estimated annual energy consumption of 1062 kilotons of oil equivalent (ktep) [24]. Other energy-intensive domains, such as diagnostic imaging, have also been assessed: in diagnostic imaging, up to 91% of the energy consumption of computed tomography (CT) and magnetic resonance imaging (MRI) scanners was found to be wasted during idle periods [25].

Emerging technologies, such as telemedicine, demonstrate promise for reducing patient transport emissions. Remote consultations reduced per-visit emissions from 9.77 kg to 0.41 kgCO₂e [26]. Similarly, inappropriate endoscopic examinations alone could account for over 4100 tons of CO₂ annually [27]. Collectively, these studies underscore the pressing need for data-driven strategies to mitigate the environmental footprint of the Italian healthcare sector. Among clinical specialties, Orthopedics and Trauma stands out as one of the most resource-intensive. Recent research indicates that orthopedic surgeries are responsible for up to 57.5% of the total carbon footprint of a surgical procedure, with energy consumption and waste disposal procedures being the primary factors. Further, the average quantity of waste generated per orthopedic procedure can be as high as 14–16.5 kg, with a substantial proportion of this waste consisting of single-use plastics and potentially recyclable materials. These figures emphasize the significance of focusing on orthopedic departments in environmental performance assessments, as they present significant opportunities for operational optimization and carbon reduction [28,29].

Despite the growing number of studies addressing the environmental impact of orthopedic surgery, existing research predominantly adopts either a full life cycle perspective at the level of individual procedures or a hospital-wide perspective without specialty-level resolution. As a result, the interaction between hospital energy systems, departmental organization, and procedure-level waste generation remains insufficiently explored. In particular, multiscale frameworks capable of linking hospital-wide energy consumption, departmental performance, and operating-room-level impacts within a single clinical specialty are still lacking, especially in national contexts such as Italy where standardized environmental reporting in healthcare is limited. This study addresses this gap by proposing a replicable, multilevel assessment framework focusing on operational energy use and infectious waste management within an orthopedic department of a large Italian public hospital.

2. Materials and Methods

This study investigates the environmental impacts in terms of carbon dioxide equivalent (CO₂e) associated with orthopedic surgical interventions at a major public hospital in Italy, situated in the Lombardy region. This extensive healthcare facility encompasses over 1200 beds and more than 130,000 m² of functional space. Given the complexity of this healthcare infrastructure, the study adopts a multiscale framework to assess system-wide resource flows, departmental consumption, and procedure-level performance.

2.1. Study Design

The analysis is structured across three distinct levels:

• Macro-level, representing hospital-wide resource consumption and waste generation;
• Meso-level, focusing specifically on the Orthopedic and Trauma (O&T) department;
• Micro-level, assessing the environmental burden of operating rooms (Ors) and individual orthopedic surgical procedures.

This layered methodological approach facilitates both top-down allocation and bottom-up measurement strategies, thereby capturing variations in resource intensity across functional domains.

2.2. Data Collection and Sources

2.2.1. Macro-Level: Hospital-Wide Data

Annual energy consumption data for the year 2023, encompassing electricity, district heating, and district cooling, were retrieved from institutional utility records. These values were normalized to kilowatt-hours (kWh) to enable aggregation and comparison. The hospital’s total floor area (132,816 m²) and the total number of installed beds (1294) were used to calculate intensity indicators. Bed occupancy rates were not explicitly considered, as intensity indicators based on installed beds and floor area are commonly adopted to represent the structural and operational capacity of healthcare facilities. This approach allows comparability across hospitals and time periods, independently of short-term fluctuations in patient occupancy. GHG emissions were estimated based on vector-specific conversion factors. Waste data were sourced from official disposal records and included detailed breakdowns according to the European Waste Catalogue (CER) code. Total waste mass and the proportion of hazardous waste were calculated. Per-bed and per-square-meter values were used for benchmarking purpose.

2.2.2. Meso-Level: Orthopedic and Trauma Department

The orthopedic and trauma department includes two 20-bed inpatient wards and a surgical suite containing four ORs. Surface area measurements were extracted from facility floor plans. In the absence of sub-metering, departmental energy consumption was estimated via surface-based allocation, applying the hospital’s average kWh/m² intensity. The total volume of infectious healthcare waste generated over the study period was obtained from hospital waste management logs and recorded in liters. To estimate the corresponding waste mass, a reference density value for solid infectious healthcare waste was applied. Based on the national and international literature, reported density values typically range between 120 and 150 kg per cubic meter. For this study, an intermediate reference value of 135 kg/m³ was adopted, consistent with national guidelines [30].

2.2.3. Micro-Level: Operating Rooms and Surgical Procedures

Prospective data collection was conducted in two of the four orthopedic ORs. Direct electricity consumption was recorded over two weeks using power quality analyzer GSC59 (HT Instruments, Faenza, Italy). Waste audits were performed over two surgical days. The operational procedures included in the waste audit were selected based on predefined criteria aimed at representativeness rather than exhaustiveness. Specifically, procedures were chosen to reflect typical orthopedic surgical activity in terms of duration, surgical complexity, and resource use, and were limited to elective procedures performed in standard operating rooms under routine conditions. All generated waste was sorted, weighed, and categorized. The number of annual orthopedic procedures (2186 in 2023) was used to extrapolate Micro-level impacts. HVAC energy was not directly metered at the room level, and it was modelled separately

No inferential statistical analysis was performed on the collected data. The study adopts a descriptive case-study approach, focusing on the quantification of energy use and waste generation under routine operating conditions

2.3. Environmental Impact Analysis

2.3.1. CO₂e Emission Factors for Energy Sources

Official data from the local energy provider specify the CO₂e emission factors for three main energy sources used in hospitals: electricity, district heating, and district cooling. These emission factors are expressed in kgCO₂e/kWh, with a breakdown of fossil, biogenic, and other greenhouse gas components where available [31]. For electricity, the local energy provider reports a CO₂e emission factor of approximately 0.258 kgCO₂e/kWh for 2023, reflecting a decrease from 0.307 kgCO₂e/kWh in 2022. This reduction is attributed to an increased integration of renewable energy sources. The projected fossil CO₂ intensity for 2024 is approximately 0.215 kgCO₂e/kWh, representing a 17% reduction compared to 2023 [26,32]. Emissions of methane (CH₄) and nitrous oxide (N₂O) are considered negligible, with emissions from the Italian national grid estimated at 0.0176 gCH₄/kWh and 0.0028 gN₂O/kWh, values consistent with the local provider’s energy mix [33]. Regarding district heating, the CO₂e emission factor reported by the local energy provider is 0.12 kgCO₂e/kWh, based on 2021 certification data. This represents one of the lowest emission factors in Italy, largely due to the use of heat generated from waste-to-energy plants and industrial heat recovery processes, thereby minimizing reliance on fossil fuels. Previously, the emission factor was 0.24 but was halved due to the increased use of renewable energy sources [34]. The fossil CO₂ component accounts for 0.12 kgCO₂/kWh, while the biogenic share contributes 0.11 kgCO₂/kWh, resulting in a total emission of about 0.23 kgCO₂ per kWh of heat distributed. Emissions of other greenhouse gases, such as CH₄ and N₂O, are considered negligible.

District cooling in the study area is currently produced by electrically driven compression chillers. Since no certified emission factor is published by the local provider, the CO₂ emission factor for district cooling was calculated based on the electricity emission factor and an average coefficient of performance (COP). Assuming a conservative average COP of 2.5, consistent with large-scale district cooling plants, the resulting emission factor for district cooling was estimated as the electricity emission factor divided by the COP. This approach reflects the actual energy conversion process and ensures consistency with the fossil CO₂ accounting applied to electricity. Accordingly, a fossil CO₂ emission factor of approximately 0.10 kgCO₂e/kWh was adopted for district cooling.

In conclusion, the following fossil CO₂ emission factors have been selected for the study, consistent with the GHG Protocol, which excludes biogenic emissions:

• Electricity: The emission factor is 0.258 kgCO₂e/kWh for 2023, reflecting the renewable energy mix, and representing the fossil CO₂ component after the reduction from 2022.
• District Heating: The emission factor for fossil CO₂ is 0.12 kgCO₂e/kWh, excluding biogenic emissions, which are considered carbon neutral.
• District Cooling: The emission factor for fossil CO₂ is estimated at 0.10 kgCO₂e/kWh, with the total cooling emissions adjusted to exclude biogenic emissions, which are also considered carbon neutral.

2.3.2. Emission Factors in Infectious Waste Management

Italian laws regulate the management of infectious medical waste (CER 180103) [35], requiring treatment through high-temperature incineration or sterilization (autoclaving). Depending on the method employed, these processes have varying impacts on CO₂ emissions.

The collection and transport of infectious waste contribute a relatively minor proportion to overall CO₂ emissions compared to the subsequent treatment process. This phase involves the use of sealed containers and specialized vehicles for transport. The associated emissions are relatively low, as the waste is usually conveyed to regional treatment plants, thereby limiting transport distances and fuel consumption. Furthermore, local waste management operators complement route optimization strategies and invest in renewable energy sources to achieve further emissions reduction. The primary treatment methods and their associated emissions are as follows:

• Incineration: Waste-to-energy plants employ high-temperatures combustion (>1000 °C) to incinerate waste, with the concurrent recovery of energy in the form of electricity and heat. The principal source of emissions is the fossil content in the waste stream (such as plastics and synthetic materials). On average, the incineration of one ton of waste generates about 500–1200 kg CO₂e. However, when energy recovery is considered, the net emission factor ranges from 500 to 700 kgCO₂e per ton of treated waste. This method partially offsets emissions by generating renewable energy, thus decreasing reliance on fossil fuels [30].
• Sterilization: Autoclaving, a sterilization method, uses high-temperature, high-pressure steam to render waste non-hazardous. This process results in significantly lower emissions compared to incineration, with an emission factor ranging from 100–200 kg CO₂e per ton of waste. The reduced environmental impact is attributed to the absence of direct combustion of carbon-based materials, positioning sterilization as a more environmentally friendly option, particularly when coupled with energy recovery in waste-to-energy plants for the disposal of post-treatment residues [36].

Following treatment, the waste is either incinerated in municipal waste plants or disposed of in landfills. Emissions from sterilized waste are lower than those from incinerated waste; however, some CO₂ is still released, particularly from any remaining fossil content if incineration is the final disposal method. Landfill disposal can lead to the generation of biogenic CO₂ and methane emissions over time [36].

The total CO₂ emissions associated with infectious waste management are largely determined by the chosen treatment method. Incineration with energy recovery offers a significant reduction in net emissions due to the energy produced, while sterilization, although inherently less emissive, still incurs an environmental impact due to energy consumption. Local waste management operators are adopting renewable energy sources and energy-efficient practices to minimize their carbon footprint. According to the IPCC Guidelines for National Greenhouse Gas Inventories, gross CO₂ emissions from waste incineration are typically in the order of 0.7–1.2 kgCO₂ per kg of waste [37]. Conversely, Italian technical documentation based on ENEA sources reports lower average values for municipal waste incineration, around 0.29 kgCO₂ per kg, reflecting national plant performance and energy recovery practices [38].

Given the higher fossil carbon content of healthcare-related infectious waste compared to municipal solid waste, and considering the presence of energy recovery systems in local waste management operators, this study adopts a representative net emission factor in the range of 0.5–0.7 kgCO₂e per kg of waste treated. This interval reflects a conservative compromise between gross incineration emissions and national average values and is consistent with common life cycle and operational carbon accounting practices.

3. Results

3.1. Macro-Level Analysis

At the Macro scale, the public hospital under investigation registered a total energy consumption of 113,604,273 kWh in the year 2023. This consumption was distributed across electricity (31,476,237 kWh, 28%), district heating (46,656,036 kWh, 41%), and district cooling (35,472,000 kWh, 31%). When normalized by the facility’s functional area of 132,816 m², this yields an average energy intensity of 855.4 kWh/m²/year. Considering the specific regional emission factor applicable in Italy, the results of the Macro-level analysis are reported in

Table 1. Energy consumption at Macro-level.

Energy Vector	kWh/Year	kgCO2e/kWh	kgCO2e/Year
Electrical Energy	31,476,237	0.258	8,120,869
District Heating	46,656,036	0.120	5,598,724
District Cooling	35,472,000	0.10	3,547,200
Total	113,604,273	/	17,266,793

.

Regarding waste management at the hospital level, official disposal records for 2023 indicated a total of 833,415 kg, with 65% (approx. 541,719 kg) classified as hazardous waste. Assuming standard incineration treatment with an average emission factor of 0.6 kgCO₂e/kg, the associated emissions are:

$$Hospital Hazardous Waste {CO}_2\mathrm{e}: \mathrm{541,719}{\displaystyle \frac{\mathrm{k}\mathrm{g}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}·0.6{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{k}\mathrm{g}}}=\mathrm{325,031}{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}$$

(1)

This estimation highlights the carbon burden associated with infectious waste streams at the hospital level.

3.2. Meso-Level Analysis

The Orthopedics and Traumatology department encompasses a total area of 2425.3 m², including both inpatient wards and an operating suite. Based on hospital-wide average intensities and proportional allocations by surface area, the estimated total annual consumption for the department is detailed in

Table 2. Energy consumption at Meso-level.

Energy Vector	kWh/Year	kgCO2e/kWh	kgCO2e/Year
Electrical Energy	574,776	0.258	148,292
District Heating	851,969	0.120	102,236
District Cooling	647,742	0.10	64,774
Total	2,074,487	/	315,303

.

Waste generation from the Orthopedics and Traumatology department was assessed using departmental waste consignment records and data on the utilization of various waste containers throughout 2023. The analysis considered the quantity and capacity of containers designated for infectious and potentially infectious materials.

A total volume of 258,977 liters (corresponding to 258.977 m³) of waste was collected during the year. The corresponding waste mass was estimated by applying the reference density value for solid infectious healthcare waste described in the Methods section.

Applying this density factor, the total annual mass of waste was estimated as follows:

$$O\&T Hazardous Waste Mass: 258.977{\displaystyle \frac{{\mathrm{m}}^3}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}·135{\displaystyle \frac{\mathrm{k}\mathrm{g}}{{\mathrm{m}}^3}}=\mathrm{34,462}{\displaystyle \frac{\mathrm{k}\mathrm{g}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}\left(34.5 \mathrm{t}\mathrm{o}\mathrm{n}\mathrm{n}\mathrm{e}\mathrm{s}\right)$$

(2)

The composition of this waste primarily includes solid infectious materials (e.g., surgical drapes, gloves, absorbent pads), sharps and cutting instruments, organic fluids captured via suction systems, and sealed containers.

Assuming that all waste underwent high-temperature incineration with energy recovery, the associated greenhouse gas (GHG) emissions were calculated:

$$O\&T Hazardous Waste {CO}_{2}e: \mathrm{34,462}{\displaystyle \frac{\mathrm{k}\mathrm{g}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}·0.6{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{k}\mathrm{g}}}=\mathrm{20,677.2}{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}$$

(3)

Although representing a small fraction of the hospital’s total waste mass, the intensive nature of surgical activities and the widespread use of single-use items amplify the environmental burden per unit of clinical output.

3.3. Micro-Level Analysis

At the Micro-level, a high-resolution analysis was conducted to assess both direct and indirect energy consumption associated with individual orthopedic surgical procedures. Energy use was quantified through a dual-channel approach: direct measurement of electrical demand from the operating theater’s dedicated circuit and modelling of heating, ventilation and air conditioning (HVAC) requirements based on volumetric parameters. Each operating theater had an area of 42 m² and a volume of 126 m³. HVAC consumption was estimated using a standard energy model based on 20 air changes per hour, a maintained internal temperature of 17 °C, and a unit energy load for air handling of 0.6 Wh/m³ [39]. The temperature value corresponds to the set-point recorded on the operating room thermostat at the time of the audit, reflecting the operational conditions of the orthopaedic operating room during routine surgical activity.

Using portable metering systems connected to the electrical panels supplying two orthopedic operating rooms, an average daily consumption of 26 kWh per room was recorded. Assuming 312 active surgical days per year, the annual energy use for all the operating rooms was calculated (

Table 3. HVAC energy consumption in the operating rooms.

Electricity Consumption		HVAC
Daily	26 kWh/day/room	Volume	126 m3
Annual surgical days	312 days/year	Parameters	17 °C
			20 ACH
			0.6 Wh/m3
Annual energy consumption	8112 kWh/year/room	Demand per room	36.29 kWh/day/room
N°rooms	4 rooms	Annual	11,322 kWh/year/room
Total	32,448 kWh/year	Total	45,290 kWh/year

).

The combined direct electrical consumption and HVAC loads for the operating rooms amount to:

$$\mathrm{O}\mathrm{R} \mathrm{A}\mathrm{n}\mathrm{n}\mathrm{u}\mathrm{a}\mathrm{l} \mathrm{E}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y} \mathrm{C}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{u}\mathrm{m}\mathrm{p}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}: \mathrm{32,448}{\displaystyle \frac{\mathrm{k}\mathrm{W}\mathrm{h}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}+\mathrm{45,290}{\displaystyle \frac{\mathrm{k}\mathrm{W}\mathrm{h}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}=\mathrm{77,738}{\displaystyle \frac{\mathrm{k}\mathrm{W}\mathrm{h}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}$$

(4)

$$\mathrm{O}\mathrm{R} {\mathrm{A}\mathrm{n}\mathrm{n}\mathrm{u}\mathrm{a}\mathrm{l} \mathrm{E}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y} \mathrm{C}\mathrm{O}}_2\mathrm{e}: \mathrm{77,738}{\displaystyle \frac{\mathrm{k}\mathrm{W}\mathrm{h}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}·0.258{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{k}\mathrm{W}\mathrm{h}}}=\mathrm{20,057}{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}$$

(5)

Considering the 2186 surgical procedures performed annually, the average energy consumption and associated emissions per procedure are:

$$\mathrm{S}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{l}\mathrm{e} \mathrm{S}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{y} \mathrm{E}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y} \mathrm{C}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{u}\mathrm{m}\mathrm{p}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}:{\displaystyle \frac{\mathrm{77,738}\frac{\mathrm{k}\mathrm{W}\mathrm{h}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}{2186\frac{\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{e}\mathrm{s}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}}=35.56{\displaystyle \frac{\mathrm{k}\mathrm{W}\mathrm{h}}{\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{y}}}$$

(6)

$$\mathrm{S}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{l}\mathrm{e} \mathrm{S}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{y} {Energy CO}_2\mathrm{e}:{\displaystyle \frac{\mathrm{20,057}\frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}{2186\frac{\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{e}\mathrm{s}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}}=9.17{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{y}}}$$

(7)

To assess the waste profile associated with typical orthopedic interventions, a dedicated waste audit was conducted over two surgical days. Thirteen surgeries were audited, encompassing a representative range of procedures, including total joint replacements, ligament repairs, and tissue biopsies (

Table 4. Operating rooms waste audit.

Surgery Procedure	Hazardous Waste [kg]	Organic Fluids [kg]	Paper [kg]	Plastic [kg]	Non-Recyclable [kg]	Total [kg]
Medial Patellofemoral Ligament Reconstruction	7.6	1	0.4	0.4	1	10.4
Total Knee Arthroplasty	11.9	0.6	0.8	1.1	1.6	16
Rotator Cuff Tendon Repair	9.8	1.6	0.5	0.5	0.6	13
Anterior Cruciate Ligament Repair	7.5	0.8	0.2	0.2	0.8	9.5
Knee Tissue Biopsy	6.7	1	0.2	0.4	2.5	10.8
Total Knee Arthroplasty	11.1	1.5	0.8	1.1	4.7	19.2
Multiligamentous Knee Reconstruction	10.2	8.9	1.2	2.1	2.2	24.6
Rotator Cuff Tendon Repair	8.4	1.6	0.9	0.7	1.1	12.7
Rotator Cuff Tendon Repair	7.6	0.8	0.6	0.6	0.9	10.5
Rotator Cuff Tendon Repair	6.6	1.4	0.4	0.5	0.3	9.2
Bankart Repair	10.2	1	0.7	0.7	1.8	14.4
Total Shoulder Arthroplasty	8.9	2.1	1	1.1	1.4	14.5
Total Shoulder Arthroplasty	10.6	2	1.1	0.9	2.4	17
Avg	9.0	1.9	0.7	0.8	1.6	14.0
Annual production	19,674	4153	1530	1749	3498	30,604
Avg %	64%	14%	5%	6%	11%	100%

Notes: Each row is one surgery case. “Hazardous Waste” is infectious/biological waste destined for incineration. “Organic Fluids” includes suctioned liquids (with and without solidifying containers). “Non-Recyclable” includes miscellaneous materials not suitable for recycling (textiles, mixed material items).

). Using the data from this audit, the average waste generation per surgical procedure was determined, and the greenhouse gas emissions associated with hazardous waste generation were calculated to ascertain their impact at the Micro-level.

Assuming all hazardous waste undergoes high-temperature incineration with energy recovery, the associated greenhouse gas (GHG) emissions were calculated as follows:

$$\mathrm{S}\mathrm{i}\mathrm{n}\mathrm{g}\mathrm{l}\mathrm{e} \mathrm{S}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{y} \mathrm{H}\mathrm{a}\mathrm{z}\mathrm{a}\mathrm{r}\mathrm{d}\mathrm{o}\mathrm{u}\mathrm{s} \mathrm{W}\mathrm{a}\mathrm{s}\mathrm{t}\mathrm{e} {\mathrm{C}\mathrm{O}}_2\mathrm{e}:9.0{\displaystyle \frac{\mathrm{k}\mathrm{g}}{\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{y}}}·0.6{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{k}\mathrm{g}}}=5.4{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{y}}}$$

(8)

$$\mathrm{A}\mathrm{n}\mathrm{n}\mathrm{u}\mathrm{a}\mathrm{l} \mathrm{H}\mathrm{a}\mathrm{z}\mathrm{a}\mathrm{r}\mathrm{d}\mathrm{o}\mathrm{u}\mathrm{s} \mathrm{W}\mathrm{a}\mathrm{s}\mathrm{t}\mathrm{e} {\mathrm{C}\mathrm{O}}_2\mathrm{e}:5.4{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{y}}}·2186{\displaystyle \frac{\mathrm{s}\mathrm{u}\mathrm{r}\mathrm{g}\mathrm{e}\mathrm{r}\mathrm{i}\mathrm{e}\mathrm{s}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}=\mathrm{11,804}\hspace{0.17em}{\displaystyle \frac{{\mathrm{k}\mathrm{g}\mathrm{C}\mathrm{O}}_2\mathrm{e}}{\mathrm{y}\mathrm{e}\mathrm{a}\mathrm{r}}}$$

(9)

This equates to 11.8 metric tons of CO₂e annually attributable solely to the incineration of infectious surgical waste. When compared to the total energy-related emissions from the department (315,303 kgCO₂e), surgical waste incineration represents approximately 3.7% of the total.

4. Discussion

4.1. Key Metrics for Energy and Environmental Comparison

4.1.1. Energy Intensity per Surface Area (kWh/m²)

It is the most common metric indicating annual energy use per unit of surface area. However, this indicator alone does not capture the level of healthcare activity or operational efficiency. Hospitals with similar kWh/m² can have vastly different services and patient loads. Furthermore, this metric does not distinguish between the mix of energy sources used.

4.1.2. Energy Intensity per Capacity (kWh/Bed)

Relating energy to bed capacity provides an indicator linked to the hospital’s care provision capacity. This metric is often considered an output measure of the healthcare service delivered. For example, a lower kWh/bed value with the same level of services indicates greater energy efficiency per hospitalized patient. It offers an intuitive way to compare hospitals of varying sizes, although it also has limitations as it does not consider outpatient activities or laboratory functions.

4.1.3. Carbon Emission Intensity (kgCO₂e/m²)

This indicator quantifies the greenhouse gas emissions associated with energy consumption per square meter. It is crucial as it incorporates the environmental impact of the energy mix used. Two hospitals with identical kWh/m² consumption can have significantly different carbon footprints if one relies on renewable energy sources while the other uses fossil fuels. For example, studies in Spain have estimated 100 kg CO₂-equivalent emitted per m² of hospital per year. The use of kgCO₂e/m² thus allows for the comparison of the effectiveness of decarbonization and energy efficiency measures, providing a direct indication of the climate impact of healthcare facilities.

Combining these indicators provides a more comprehensive picture of performance. The kWh/m² alone can be misleading as it does not reflect the intensity of hospital use or the associated CO₂ emissions. Instead, the kWh/bed normalizes consumption based on the care capacity, while the kgCO₂e/m² normalizes by surface area but weighs the carbon content of the energy sources. These metrics facilitate a more meaningful comparison of hospitals across different countries (where energy mixes and bed capacity vary) than the simple kWh/m². In summary, kWh/bed measures energy efficiency relative to the healthcare service provided, and kgCO₂e/m² measures the carbon efficiency of the energy used: two complementary perspectives for evaluating the sustainability of hospitals.

These indicators provide the reference framework used in the following subsection to contextualize the energy and carbon performance of the analyzed hospital and orthopedic department.

4.2. Global Comparison of Energy Consumption and Emissions by Geographic Area

Scientific literature indicates notable geographical differences in hospital energy consumption and associated emissions.

Table 5. Energy and environmental indicators among different countries.

Geographical Area	kWh/m2/Year	kWh/Bed/Year	kgCO2e/m2/Year
Europe [40,41,42]	250–300	20,000–60,000	100
North America [43,44]	738	80,000–120,000	200–250
Asia [45,46,47,48]	180–400	5000–15,000	50–150
Oceania [49]	393–460	40,000	180–200
Macro-level	855	87,793	130

presents a comparison between the results obtained in this study and typical values of energy consumption (in kWh/m²/year and kWh/bed/year) and CO₂ emissions (kgCO₂e/m²/year) across major geographic regions, where data are available. These are indicative average values, as significant variability exists within each region based on factors such as facility size, climate, and the specialization of services. Values reported for the literature studies were derived from the original publications. Where necessary, unit conversions were performed to ensure consistency across indicators; however, original system boundaries and methodological assumptions were preserved.

Energy consumption in European hospitals exhibits an average profile on a global scale. Comparative studies indicate a mean intensity ranging from 270 to 333 kWh/m²/year across EU countries. In Spain, energy audits have revealed diverse hospital consumption levels, spanning from 150 kWh/m²/year for efficient facilities to over 500 kWh/m²/year for those with high energy demands. In terms of bed capacity in Spain, this translates to an annual consumption of 20 to 60 MWh per bed [40]. Research conducted in Germany suggests an average energy intensity of 270 kWh/m², a figure consistent with other EU countries [42]. The average CO₂ emissions in Europe are 100 kgCO₂e/m²/year, a relatively lower value attributed to the region’s cleaner energy mix. Hospitals in Northern Europe tend to exhibit less energy consumption per m² due to colder climates and superior building insulation, while those in Southern Europe may require more energy for air conditioning during warmer months. The healthcare sector in Europe accounts for up to 5% of national energy consumption [41].

North American hospitals, particularly in the United States, exhibit the highest energy intensities worldwide, with values around 740 kWh/m²/year, approximately double the European average [42]. This is largely driven by larger floor areas per bed, continuous operation of energy-intensive HVAC systems, and extensive use of advanced medical equipment. In combination with a fossil-fuel-dominated energy mix, these factors result in high carbon intensities, often exceeding 200 kgCO₂e/m²/year [43,44].

In Asia, hospital energy consumption is highly heterogeneous [45,46,47]. Facilities in lower-income contexts, such as public hospitals in India, show relatively low energy intensities (typically below 250 kWh/m²/year), reflecting lower technological endowment and reduced cooling demand [45]. Conversely, modern hospitals in hot or humid climates, or those designed as large, high-tech complexes, can reach energy intensities comparable to North American facilities (>500 kWh/m²/year) [46]. Across the region, climatic conditions and the carbon intensity of national electricity systems play a decisive role, with coal-based grids leading to disproportionately high emissions even at moderate energy consumption levels [47].

Hospitals in Oceania, particularly in Australia, display energy intensities comparable to those observed in North America, with values around 400–460 kWh/m²/year for large facilities [49]. Factors such as warm climates, aging building stock, and reliance on coal-based electricity contribute to carbon intensities significantly higher than European benchmarks. At the same time, national programs promoting energy efficiency and on-site renewable generation indicate growing efforts to mitigate operational emissions [48].

Overall, these comparisons highlight that hospital energy and carbon intensity are not solely determined by healthcare activity levels, but are strongly influenced by structural characteristics, climate, and the energy system context, underscoring the importance of region-specific benchmarking and mitigation strategies.

In this study, the Macro-level energy intensity of the investigated Italian public hospital is 855 kWh/m²/year, placing it significantly above both national and international benchmarks. The facility analyzed is an academic medical center with over 1200 beds, providing highly specialized and research-intensive care. Within the national context, ENEA (the Italian National Agency for New Technologies, Energy and Sustainable Economic Development) reports typical energy intensity values of 300–500 kWh/m² and annual consumption per bed of 60,000–70,000 kWh/bed/year for public hospitals, with very large teaching hospitals occasionally reaching 89,000 kWh/bed/year [50]. Our case hospital records 87,793 kWh/bed/year, approach the upper limit of this category despite already benefitting from scale-related efficiency (Figure 1). These figures highlight the burden imposed by both clinical complexity and infrastructural inertia.

On an international scale, the energy consumption and emissions performance of this hospital more closely resemble that of large academic centers in the U.S. rather than typical EU facilities. Its intensity metrics align with the North American model, characterized by extensive operations, advanced diagnostics, and high technological load.

As an academic institution, the hospital under study encompasses not only inpatient and surgical services, but also teaching spaces, research laboratories, and administrative offices. These non-clinical areas tend to increase total surface area without a proportional increase in the number of beds, which partially accounts for the elevated kWh/m² values. Nonetheless, the per-bed consumption remains high, indicating an urgent need for energy efficiency measures even at the operational level.

Our results show that the carbon intensity at both the Macro- and Meso-levels reaches 130 kgCO₂e/m²/year (Table 5), substantially exceeding the European average of 100 kgCO₂e/m²/year. The primary factors contributing to these high values are the substantial reliance on fossil fuels, the potentially outdated building envelopes and HVAC systems.

Figure 2 provides a concise, yet powerful visual summary of the annual CO₂e emissions at the three analytical levels of the study: Macro-level (entire hospital), Meso-level (O&T department), and Micro-level (OR). This visual representation reinforces the key findings, particularly the elevated carbon intensity observed at the Macro-level, which significantly exceeds the European average. The Meso-level data highlight that, although the orthopedic department accounts for a relatively limited portion of the hospital’s total surface area and energy use, it nonetheless contributes disproportionately to the institution’s environmental emissions. This is primarily due to high HVAC demands and the volume of infectious waste generated. At the Micro-level, emissions per surgical procedure (9.17 kgCO₂e from energy use and 5.4 kgCO₂e from waste incineration) further illustrate how individual interventions cumulatively exert a substantial climate impact.

As shown in

Table 6. Comparison with recent orthopedic surgery environmental impact studies.

Study	Country	System Boundary	Metric	Key Results	Notes on Comparability
[51]	Germany	Full LCA (Scope 1–3)	kgCO2e/procedure	53–126 kgCO2e	Includes implants, anesthetics, supply chain
[52]	Australia	Full LCA	kgCO2e/TKR	~130 kgCO2e	Includes prosthesis, sterilization, single-use devices
[53]	France	Waste-focused	kgCO2e/procedure	Median 4.3 kgCO2e	Waste only
[54]	Netherlands	Waste LCA	kg CO2-eq	19–24 kg CO2e	Full material LCA
[55]	Australia	Waste audit	kg waste/procedure	Avg 8.2 kg	Mass-based, not CO2
This study	Italy	Energy consumption + hazardous waste	kgCO2e/procedure	14.6 kgCO2e	Partial operational account

, when compared with recent orthopedic-specific studies adopting comprehensive life cycle assessment boundaries, the per-procedure emission value estimated in this study is substantially lower. This difference is primarily attributable to the intentionally limited system boundaries applied. While several orthopedic carbon footprint studies include upstream emissions related to implants, pharmaceuticals, single-use medical devices, sterilization processes, and broader supply chains [51,52], the present analysis is restricted to operational energy consumption and hazardous waste treatment.

Despite these boundary differences, the waste-related component estimated in this study (5.4 kgCO₂e per procedure) is consistent with values reported in studies specifically focusing on intraoperative waste. For example, median waste-related footprints of approximately 4–5 kgCO₂e per orthopedic procedure have been reported in the literature [53], while other analyses indicate that waste streams alone can exceed 19 kg CO₂-equivalent per procedure when evaluated using full life cycle approaches [54,55].

This consistency supports the validity of the waste incineration estimates adopted here and suggests that they provide a reasonable order-of-magnitude representation of downstream waste-related emissions within the defined system boundaries.

Collectively, these findings underscore the urgency of targeted energy efficiency and waste reduction strategies, particularly in high-intensity zones such as orthopedic operating theaters.

Figure 3 illustrates the impact of the O&T department on the hospital’s energy- and waste-related emissions, representing about 1.91% of overall CO₂ equivalent emissions. In examining the internal structure of the O&T department, operating rooms are identified as a critical area, contributing 9.48% to the department’s overall environmental effect. This assessment exclusively evaluated emissions associated with energy use and hazardous waste generation. According to this narrow focus, targeted interventions, especially in high-intensity regions like operating rooms, may present significant chances for emission reductions, even within departments with a marginal overall impact.

4.3. Scalable Mitigation Strategies for Environmental Impact Reduction in Hospitals

Environmental sustainability in hospitals can be pursued through interventions at the three levels, analyzed (Macro, Meso, and Micro). Below, we present various environmental impact mitigation strategies for each level, along with scientific evidence quantifying the potential CO₂ emission savings.

4.3.1. Macro-Level

• Energy optimization and renewable sources: at the hospital level, a key lever is the reduction of energy-related emissions. Energy efficiency measures (e.g., smart building management systems, LED lighting, cogeneration) combined with the transition to a renewable energy mix can drastically reduce this footprint [56]. A notable example is the Boston Medical Center (USA), which has undertaken a sustainability plan involving facility renovation. As a result, the hospital has reduced its energy consumption-related CO₂ emissions by 91% (from 2011 to date), with annual operational savings exceeding $40 million reinvested in patient care [57]. This demonstrates the enormous potential of renewable sources on a macro scale. Other facilities have also achieved similar results: for example, some Chinese clinics that have installed photovoltaic systems report a reduction of over 1000 tons of CO₂ per year thanks to 2 GWh of solar electricity produced [58]. These structural interventions, while requiring initial investments, have a large-scale impact and guaranty permanent emission reductions.
• Hospital waste management policies: studies indicate that hazardous waste should typically constitute 10% of the total, but in practice, this proportion is often much higher due to excessive caution [59]. Adequate staff training and clear guidelines can prevent the “over-classification” of waste. Beyond the environmental advantages of minimizing hazardous waste, there exists an economic benefit, since the disposal of hazardous waste can be up to five times more expensive than conventional waste disposal. A hospital intervention showed that proper segregation of healthcare waste led to a reduction of approximately 85% in CO₂ emissions related to that waste [60]. In absolute terms, the carbon footprint of waste treatment in the operating room block decreased from approximately 527 kg CO₂eq to just 79.1 kg CO₂eq per week after the recycling program. This is equivalent to over 23 tons of CO₂ avoided per year, simply by improving waste management at the hospital/department level.

4.3.2. Meso-Level

• Intelligent ventilation management in the operating room: operating rooms (ORs) have stringent air exchange and filtration requirements to ensure sterility. An effective strategy to reduce the HVAC energy consumption is to implement “setback” modes during off-peak hours, reducing the number of air changes when the rooms are not in use (e.g., at night). The literature confirms that reducing the ventilation flow in the operating room outside of surgical hours does not compromise air quality or increase the risk of infection, provided the systems are brought back to full operation before use [61]. A case was documented where reduced mode was extended to 19 out of 22 operating rooms during nights and weekends (leaving three active for emergencies), resulting in a 50% reduction in HVAC energy consumption compared to the baseline [20]. Other simulations indicate that reducing the air changes per hour from 30 to 6 in rest rooms can cut ventilation energy costs by up to 70%, without a significant increase in microbial contamination [62]. In a Spanish study of a surgical block, optimizing microclimate parameters during downtime resulted in an annual energy saving of 70% compared to traditional management [63]. Additionally, new “smart” systems like RFID sensors to automatically detect room occupancy can dynamically adjust ventilation, with pilot studies estimating a further energy saving of 50% compared to constant ventilation [64].
• Reusable materials: implementing programs to replace single-use materials with reusable and sterilizable alternatives at the ward level is a key strategy. Numerous comparisons in the literature highlight the environmental benefits of reusables without compromising safety. For example, a comparative study on single-use vs. reusable anesthesia devices found that switching to reusable can reduce CO₂ emissions by 84% in Europe (thanks also to a cleaner energy mix), by 48% in the USA, and, conversely, could slightly increase them in Australia (+9%) where the electricity mix was more carbon-intensive [61]. This highlights the importance of both choosing reusable items and powering sterilization centers with renewable energy. Another study analyzed the impact of reusable vs. disposable surgical gowns: reusable gowns showed a carbon footprint approximately 60% lower than their disposable equivalents. Similarly, reusable surgical caps have significantly lower carbon footprints and other impact categories compared to single-use TNT caps [65]. At the ward level, the systematic adoption of reusable linens, clothing, and instruments (in line with infection prevention guidelines) can therefore avoid several tons of CO₂ per year. It should be noted that in many hospitals, there has been a shift towards single-use items in recent decades for perceived reasons of convenience or reduced infection risk, but evidence indicates that well-sterilized reusable devices do not increase surgical infections. Therefore, reversing this trend where possible represents a significant sustainability opportunity at the Meso-level.

4.3.3. Micro-Level

• Optimization of surgical kits and reduction of unused open materials: “streamlining” procedural sets to eliminate non-essential tools or materials can reduce both waste and embodied emissions. An exemplary case comes from ophthalmic surgery [66] in which a recent study calculated the carbon footprint of cataract surgery and evaluated two Micro-level-level interventions: removing unnecessary items from single-use kits and replacing some single-use instruments with reusable equivalents. The result was a saving of 935 kg CO₂/year thanks to the streamlining kit and an additional 309 kg CO₂/year thanks to the switch to reusable items. In total, for the volume of cataracts considered, approximately 1.24 tons of CO₂ per year were avoided. Additionally, the study found that for the devices considered, single-use items had a footprint 27 times greater than reusable versions: this means that reusing a device about 20 times is enough for a reusable device to become advantageous in terms of net emissions compared to 20 equivalent single-use devices. This type of analysis can be extended to other procedures (e.g., arthroplasty kits, laparoscopy sets, etc.), identifying the highest-impact items for each intervention and acting on them (eliminating them if unused, or introducing reusable alternatives). For example, in orthopedic surgery, optimizing open screws and plates for synthesis procedures can avoid costly waste. Similarly, customizing instrument trays (modular instrumentation instead of standard complete sets) reduces the number of materials that need to be sterilely reprocessed after surgery, saving energy and CO₂.
• Sustainable practices in the operating room: there are micro-organizational measures that, although not always quantified in kg of CO₂, contribute to reducing waste and emissions. For example, turning off or putting unnecessary electrical equipment into standby mode during the procedure (or between procedures) reduces the room’s energy consumption without impacting care [67]. Similarly, carefully preparing sterile materials before surgery and opening only what is truly needed can prevent many new items from being unnecessarily contaminated and then discarded. “Lean surgery” projects in the literature have shown that by involving the surgical team in systematically identifying and removing waste, not only is there cost savings, but also a significant reduction in waste per procedure (up to −30%) and consequently in the emissions associated with their life cycle [68,69]. In hand surgery, for example, the adoption of “lean” techniques has allowed for a reduction in the number of instruments opened but not used, resulting in a decrease in the carbon footprint per procedure without compromising clinical outcomes [70]. Although the benefits of these punctual changes may seem small, their sum across thousands of annual procedures makes them significant.

From an implementation perspective, the mitigation strategies discussed above differ substantially in terms of feasibility, time horizon, and potential impact within the analyzed hospital. Measures related to operational optimization, such as improved scheduling of operating rooms, enhanced waste segregation, and behavioral interventions targeting staff practices, represent low-cost and low-barrier options that could be implemented in the short term. These strategies do not require major infrastructural changes and could yield immediate reductions in energy use and waste generation.

Conversely, strategies involving HVAC system retrofitting, electrification of thermal energy supply, or on-site renewable energy generation are associated with higher mitigation potential but face significant implementation barriers in the analyzed unit. These include high upfront investment costs, constraints related to existing building infrastructure, and the need to ensure uninterrupted clinical operations in critical areas such as operating theaters. As a result, while these measures could substantially reduce operational emissions, their deployment is more likely to occur over a medium- to long-term planning horizon.

5. Conclusions

This study provides a comprehensive, multiscale environmental assessment of an orthopedic department within a major Italian public hospital, examining energy consumption and waste generation at Macro-, Meso-, and Micro-levels. The findings reveal that the hospital’s energy intensity (855 kWh/m²/year and 87,793 kWh/bed/year) significantly exceeds both national and international benchmarks, exhibiting a closer alignment with North American academic medical centers rather than European counterparts. Despite its size and complexity, the institution demonstrates considerable potential for enhancing energy efficiency and reducing emissions. At the Meso-level, the Orthopedic and Trauma department emerged as a disproportionate contributor to the hospital’s energy- and waste-related emissions, primarily driven by energy consumption related to HVAC systems and the generation of infectious waste. Micro-level analysis of operating rooms revealed average emissions of 14.6 kgCO₂e per surgical procedure, 9.17 kg from energy use, and 5.4 kg from hazardous waste incineration, highlighting the environmental impact of individual clinical activities.

This study underscores the utility of a multilevel analytical framework for pinpointing specific hotspots and inefficiencies that may be overlooked in aggregated assessments. This approach facilitates the implementation of targeted interventions in high-impact areas, such as surgical theaters, HVAC systems, and waste management protocols. It also emphasizes the importance of integrating sustainability considerations into hospital operations and clinical decision-making processes.

Overall, the proposed methodology offers a replicable and policy-relevant instrument for monitoring environmental performance within healthcare settings. While not intended to represent the full carbon footprint of orthopedic care, the approach lowers the barrier to engagement with sustainability for hospital managers and clinicians. Future research should extend this framework to other departments and institutions, incorporate real-time metering and Scope 3 emissions, and evaluate the effectiveness of mitigation strategies. By doing so, healthcare systems can better align clinical excellence with environmental stewardship, ultimately advancing both public and planetary health.

6. Limitation

This study does not represent the total carbon footprint of orthopedic care, but a partial operational carbon account limited to energy consumption (electricity, district heating and cooling) and infectious waste treatment. Upstream Scope 3 emissions related to pharmaceuticals, medical implants, consumables, food services, and patient or staff transportation were not included. As widely documented in the literature, these omitted sources may account for most healthcare-related emissions; therefore, the results presented here should not be interpreted as the overall carbon footprint of an orthopedic department.

A further limitation concerns data availability and system boundaries. Energy consumption at the departmental and operating-room level was partially estimated through allocation and modelling approaches due to the absence of sub-metering. Similarly, waste-related emissions were calculated using average emission factors for high-temperature incineration with energy recovery, which introduces uncertainty related to treatment efficiency and fossil carbon content.

The Micro-level analysis was based on direct measurements conducted in two operating rooms over a limited observation period. Although the monitored days were selected to be representative of typical surgical activity, the resulting values should be interpreted as order-of-magnitude estimates rather than statistically exhaustive measurements. No inferential statistical analysis was performed due to the exploratory nature of the study and the limited sample size.

Despite these limitations, the proposed framework offers a transparent and replicable approach that can support internal benchmarking and identify priority areas for mitigation. Future research should expand the system boundaries to include upstream Scope 3 emissions, integrate real-time metering, and apply the methodology across multiple hospitals and clinical specialties.