Quantifying carbon dioxide emissions in paediatric anaesthesia practice: The impact of volatile anaesthetic choice: A prospective, randomised, single-blinded comparative study

ABSTRACT

Background and Aims:

Carbon foot printing provides a metric for the environmental burden—energy, waste, and potent greenhouse emissions—inherent in our daily clinical practice. This study quantifies and compares the carbon dioxide (CO₂)-equivalent emissions of sevoflurane versus desflurane in paediatric patients using the validated Dr. Tom Pierce anaesthetic gas calculator.

Methods:

Fifty American Society of Anesthesiologists physical status I-II children aged between 3 and 12 years of either gender with no congenital anomalies undergoing elective surgery with second-generation supraglottic airways were prospectively evaluated. Patients were randomised into Group S (Sevoflurane, n = 25) or Group D (Desflurane, n = 25). Environmental impact was calculated based on real-time consumption data using Dr Tom Pierce’s anaesthetic gases calculator application.

Results:

While haemodynamic stability and bispectal index–monitored depth remained consistent across both cohorts, the ecological divergence was profound. The mean agent consumption was significantly lower in the S group (28.39 ± 15.88) as compared to the D group (49.30 ± 0.29). Most strikingly, the mean CO₂ emission for sevoflurane (3.68 ± 2.02) was a mere fraction of the impact seen with desflurane (100.55 ± 74.68), representing a massive reduction in the global warming potential per case.

Conclusion:

Sevoflurane demonstrated a significantly lower carbon footprint than desflurane. Given that clinical outcomes and haemodynamic stability remained consistent across cohorts, the transition to sevoflurane-based maintenance represents a high-impact, actionable intervention for sustainable paediatric practice. These findings advocate the preferential use of sevoflurane as the primary volatile agent in “green anaesthesia” protocols, though further multicentre validation is required to solidify these environmental benchmarks.

INTRODUCTION

The twenty-first century has introduced a critical paradox within global healthcare: While treating diseases exacerbated by environmental degradation, its intensive energy consumption and high emissions actively fuel the climate crisis.[1] Within the clinical setting, the operating theatre is a primary source of environmental strain. Notably, inhalational anaesthetics account for approximately 5% of the total healthcare carbon footprint[2] because they accumulate in the troposphere and function as potent greenhouse gases (GHGs). Nitrous oxide (N₂O) accounts for over 75% of the anaesthetic-related climate impact.[3] On a global scale, these agents contribute between 0.01% and 0.10% of cumulative carbon dioxide equivalent (CO₂e) emissions.[4] However, assessing environmental harm through global warming potential (GWP) alone is insufficient; a comprehensive evaluation must incorporate clinical variables, such as fresh gas flow (FGF) rates and individual agent potency.[5]

Despite the global urgency of “green anaesthesia”, there is a significant lack of data regarding carbon foot printing in the Indian healthcare context, particularly the paediatric population. This study aims to address this gap by using Dr Tom Pierce’s anaesthetic gases calculator. The primary objective of the study was to compare the CO₂e emissions of two commonly utilised agents: desflurane and sevoflurane. The secondary objective was to calculate and compare the mean agent consumption.

METHODS

This prospective, randomised, single-blinded comparative study was conducted at a tertiary care hospital over a 12-month period from August 2024 to August 2025, following approval from the institutional ethics committee (vide approval number IEC; SRHU/HIMS/ETHICS/2024/144) and registration with the Clinical Trials Registry-India (CTRI/2024/08/072923). The study protocol conformed to the 2013 Declaration of Helsinki and Good Clinical Practice guidelines.

After obtaining written informed consent from parents or legal guardians, children aged between 3 and 12 years of either gender, scheduled for elective surgeries lasting longer than one hour under general anaesthesia using second-generation supraglottic airway devices, were eligible for inclusion. Patients were excluded for parental refusal, systemic illness, or complex congenital anomalies, if procedures lasted less than 1 h or required endotracheal intubation.

To eliminate selection bias, allocation concealment was maintained using sequentially numbered, opaque, sealed envelopes (SNOSE). Block randomisation was carried out using the sealed envelope system, with 10 opaque envelopes per block, each marked A (Sevoflurane) or B (Desflurane) [Figure 1]. Due to the distinct physical differences, vaporiser designs, and operational requirements of the vaporisers on the Dräger Primus workstation, the intraoperative anaesthesia provider could not be blinded. However, to minimise detection and analytical bias, a strict triple-blind design was maintained. The patients and their legal guardians, the researcher recording postoperative recovery parameters, and finally the investigators executing the final carbon footprint calculations and statistical analyses were kept masked to group assignments until the database was locked. The outcome assessors were strictly prohibited from entering the operating room during the maintenance phase of anaesthesia.

Figure 1.

CONSORT flow diagram for enrolment, group allocation, follow-up, and analysis. CONSORT: Consolidated Standards of Reporting Trials; Group S: Sevoflurane; Group D: Desflurane

All patients received intranasal midazolam (0.1 mg/kg) premedication, and an intravenous (IV) line was secured. Anaesthesia was induced with IV fentanyl (2 µg/kg), propofol (2 mg/kg), and atracurium (0.5 mg/kg), followed by the insertion of a second-generation supraglottic airway device. Patients were randomised into two groups: Group S received sevoflurane for maintenance, while Group D received desflurane. Anaesthesia was delivered in all patients using the Dräger Primus workstation (Ref: 8606800-50/SN: ASED-0238), with oxygen and air [fraction of inspired oxygen (FiO₂) = 0.5] at a fixed FGF of 2 L/min, maintaining the minimum alveolar concentration (MAC) between 1 and 1.5, and the bispectral index (BIS) at 40–60. Neuromuscular reversal was achieved with IV glycopyrrolate 0.01 mg/kg and neostigmine 0.05 mg/kg. An independent anaesthesiologist managed intraoperative analgesics, fluids, and muscle relaxants.

Dr Tom Pierce’s real-time anaesthetic gases calculator application quantifies CO₂e emissions from various inhalational gases and simultaneously calculates the total volatile agent cost consumed during surgery.[2] This application is available free of charge and compatible with both Android and iPhone operating system (iOS). To operate the calculator, the user first selects the appropriate tab based on the specific carrier gas characteristics: either N₂O, and oxygen, oxygen and air with rotameters, or by configuring the FiO₂ and FGF exactly as they would appear on an anaesthesia workstation [Figure 2].

Figure 2.

Dr Tom Pierce’s real-time anaesthetic gases calculator.[2] FiO₂: Fraction of inspired oxygen; FGF: Fresh gas flow; CO₂e: Carbon dioxide equivalent; Vol: Volume; N₂O: Nitrous oxide; GWP:Global warming potential; MW: Molecular weight; calcs: Calculations; mls: Millilitres

After this selection, the user enters the specific vaporiser setting percentage (%) and the carrier gas flow rate, which prompts the visual graphs to adapt automatically. At that designated FGF and vaporiser setting, the calculator automatically displays the carbon dioxide (CO₂) emissions, measured in kg of CO₂ per h. Using this standardised interface, the parameters recorded for final analysis in this study were the total volatile agent consumption and the cumulative CO₂ emission of the specific agent utilised.

The specific type of surgery and total duration of anaesthesia were recorded. Intraoperative ventilatory variables—FGF, FiO₂, tidal volume (TV), respiratory rate (RR), minute ventilation (MV), peak inspiratory pressure (PIP), mean airway pressure (Pmean), and end-tidal carbon dioxide (EtCO2)—were documented. Haemodynamic parameters, specifically systolic (SBP), diastolic (DBP), and mean arterial blood pressure (MAP); electrocardiography (ECG), peripheral oxygen saturation (SpO₂); and core body temperature, were recorded at baseline (before induction), immediately post induction, at 10 min post induction, and at subsequent 10-min intervals until the completion of surgery.

A convenient sampling technique was employed, including all eligible paediatric patients aged 12 months or older. Given the prevalence of cases requiring paediatric surgery in 2022 and the scarcity of prospective clinical data directly comparing real-time operational CO₂e emissions between these agents in paediatric anaesthesia, this study was designed as an exploratory pilot trial. The sample size was calculated using Cohen’s standardised effect size method with α = 0.05 and a power of 80%. A large anticipated effect size (d = 0.8) was selected based on established environmental modelling data demonstrating that desflurane exhibits a GWP roughly 20 times that of sevoflurane.[4] This yielded a minimum requirement of 25 participants per group (n = 50) total. While sufficient for the primary environmental outcome, we acknowledge that this exploratory sample size may limit the statistical power for subtle secondary clinical outcomes. Data were analysed using the Statistical Package for the Social Sciences (SPSS) software [International Business Machines (IBM) manufacturer, Chicago, USA] version 23.0. Continuous variables were first evaluated for normality using the Shapiro–Wilk test paired with visual inspection of histograms and Q-Q plots. Normally distributed continuous data were expressed as mean ± standard deviation (SD) and analysed using the unpaired (t)-test. For continuous variables demonstrating a skewed or non-parametric distribution (indicated by a mean ± SD ratio <2), data were expressed as median (interquartile range) and analysed using the Mann–Whitney U test. Categorical variables were expressed as frequencies (percentages) and evaluated using the Chi-square test or Fisher’s exact test where expected cell counts were less than 5. To demonstrate the precision and reliability of our findings, we report effect sizes and 95% confidence intervals (CIs) for the primary outcomes. A P value < 0.05 was considered statistically significant.

RESULTS

Both groups were well matched, ensuring comparability for further analysis of CO₂ emissions [Table 1]. There was no significant difference in haemodynamic parameters [Table 2] and BIS values throughout the surgery between the two groups.

Table 1.

Comparison of baseline demographic, anthropometric, and clinical variables between group D (desflurane) and group S (sevoflurane)

Variable	Domain	Group D		Group S		P
		Mean or n	SD or %	Mean or n	SD or %
Age group	Mean age	6.44	3.40	7.64	3.10	0.199
	3-6 years	7	28	13	52	0.220
	6.1-9 years	7	28	5	20
	9.1-12 years	11	44	7	28
Gender	Female	11	44	5	20	0.064
	Male	14	56	20	80
Anthropometric variables	Height (cm)	120.94	27.52	129.34	22.27	0.242
	Weight (kg)	21.48	9.36	24.46	8.30	0.240
Type of surgeries	Urological	16	64	12	48	0.069
	General surgery	6	24	3	12
	Orthopaedic	3	12	10	40
Duration of surgery	Duration (min)	90.40	44.39	85.60	36.18	0.677
SGAD type	Proseal LMA	25	100	25	100

SGAD: supraglottic airway device, LMA: laryngeal mask airway SGAD: Supraglottic airway device; LMA: Laryngeal mask airwy; SD: Standard deviation

Table 2.

Comparison of haemodynamic changes between the two groups: Group D (desflurane) and Group S (sevoflurane)

	Heart rate					Systolic blood pressure					Diastolic blood pressure					Mean arterial pressure
	Group D		Group S		P	Group D		Group S		P	Group D		Group S		P	Group D		Group S		P
	Mean	SD	Mean	SD		Mean	SD	Mean	SD		Mean	SD	Mean	SD		Mean	SD	Mean	SD
Pre induction	117.28	16.72	111.40	14.50	0.19	95.04	12.73	92.32	14.71	0.488	61.32	10.52	60.32	14.46	0.781	72.56	10.60	70.99	14.06	0.657
Post induction	120.88	16.95	117.20	15.20	0.423	102.28	12.24	100.32	15.24	0.619	66.44	9.22	65.64	14.20	0.814	78.39	9.92	77.20	14.33	0.735
10min	115.68	11.53	110.52	13.50	0.153	95.96	12.23	94.28	13.09	0.641	61.20	10.54	59.44	14.00	0.618	72.79	10.65	71.05	13.26	0.613
20min	112.04	12.24	106.48	15.49	0.166	91.68	9.14	92.64	8.85	0.708	60.32	8.53	59.00	10.81	0.634	70.77	8.37	70.21	10.11	0.832
30min	109.64	11.93	105.80	11.65	0.255	93.68	8.26	93.16	7.51	0.817	61.20	6.33	61.28	7.16	0.967	72.03	6.73	71.91	7.02	0.951
40min	108.36	13.17	102.88	10.79	0.114	92.40	9.49	90.48	9.34	0.475	61.16	8.33	60.36	9.05	0.747	71.57	8.43	70.40	8.99	0.63
50min	107.12	12.69	104.80	11.77	0.506	93.80	10.65	91.12	10.37	0.372	63.72	7.64	59.72	7.92	0.075	73.75	8.27	70.19	8.42	0.138
60min	106.72	13.64	106.28	11.59	0.903	93.96	11.07	91.48	9.69	0.404	64.76	7.45	57.84	8.69	0.004	74.49	8.28	69.05	8.79	0.059
70min	104.00	17.70	100.00	7.67	0.483	95.18	10.69	92.67	6.89	0.506	63.00	6.34	59.08	8.21	0.218	73.73	7.41	70.28	7.65	0.285
80min	100.82	17.98	99.00	12.68	0.787	95.27	10.38	93.36	7.63	0.629	63.73	8.16	59.18	7.20	0.181	74.24	8.49	70.58	6.76	0.277
90min	101.70	14.73	102.82	12.51	0.853	97.10	9.94	94.36	8.58	0.507	65.80	7.00	62.09	4.80	0.170	76.23	7.51	72.85	5.75	0.266
100min	103.57	15.26	106.50	19.74	0.768	100.57	13.46	95.83	11.07	0.508	62.57	10.90	63.83	8.58	0.823	75.24	11.53	74.50	9.17	0.900
110min	107.00	18.52	96.33	15.85	0.293	99.43	12.47	98.50	10.31	0.888	66.00	6.50	62.83	9.43	0.490	77.14	7.42	74.72	9.61	0.627
120min	100.17	17.99	99.00	7.40	0.886	103.83	17.04	99.33	9.54	0.585	66.67	9.60	67.20	4.86	0.913	79.06	11.67	78.60	6.06	0.936
130min	108.50	16.60	98.00	4.04	0.611	92.50	9.25	99.50	16.26	0.518	63.75	9.50	66.50	9.19	0.753	73.33	9.40	77.50	11.55	0.708
140min	108.00	17.14	112.00	24.04	0.821	95.00	12.24	93.00	18.38	0.877	60.50	12.76	56.00	19.79	0.744	72.00	12.42	68.33	19.33	0.837
150min	110.75	7.76	97.50	3.53	0.093	93.00	11.80	93.00	25.45	1.000	59.00	10.70	62.50	10.60	0.724	70.33	11.03	72.67	15.56	0.872
160min	115.75	9.43	92.50	4.95	0.035	91.75	8.95	96.00	19.79	0.716	60.50	5.19	59.50	13.43	0.893	70.92	6.45	71.67	15.56	0.957
170min	114.25	10.53	92.50	4.95	0.057	91.75	8.05	91.50	13.43	0.978	60.25	5.18	57.50	10.60	0.671	70.75	6.13	68.83	11.55	0.856
180min	113.00	16.55	104.50	10.60	0.556	95.50	5.74	99.50	3.53	0.431	65.00	5.77	66.00	2.82	0.835	77.17	3.06	75.17	5.64	0.858

P<0.05 is significant. SD: Standard deviation

Throughout the study, both groups maintained physiological ranges for all ventilatory parameters. However, the mean dial concentration was significantly lower in Group S (Sevoflurane) compared to Group D (Desflurane) at all measured time points. The oxygen-to-air ratio (1.26:0.74) was kept constant in both groups, as confirmed by the real-time carbon emission calculator developed by Dr. Tom Pierce [Figure 2].

The mean agent consumption was significantly lower in the S group (28.39 mL ± 15.88 mL) than in the D group (49.3 mL ± 0.29 mL; P = 0.007). The statistical analysis revealed that the agent consumption might be strongly associated with the amount of CO₂ emissions [Table 3].

Table 3.

Agent consumption and carbon dioxide emission calculated using the Calculator

Variable	Domain	Group D		Group S		P
		Mean	SD	Mean	SD
Agent consumption	Mean agent consumption (in mL)	49.30	0.29	28.39	15.88	0.007*
CO2 emission	Mean CO2 emission (kg CO2e/h)	100.55	74.68	3.68	2.02	0.001*

SD: Standard deviation; CO₂: Carbon dioxide; *P<0.05 is significant

DISCUSSION

A key observation of the study is that desflurane contributes substantially more to carbon emissions compared to sevoflurane, which is consistent with published literature, which confirms desflurane’s higher GWP and greater consumption rates.[2,6] The present study confirmed that mean agent consumption was significantly higher in the desflurane group, reflecting both environmental and economic disadvantages. Notably, the dial concentration, a key predictor of CO₂ emission, was significantly lower in the sevoflurane group throughout the intraoperative period. A fixed oxygen–air ratio (1.26:0.74) and constant FGFs of 2L/min strengthened the reliability of the dial concentration data as a measure of carbon footprint. While historically FGF of 2L/min was classified as low flow, contemporary clinical practice guidelines define true low-flow anaesthesia as a FGF below 1 L/min. Because the Tom Pierce calculator accommodates any user-defined FGF, our data do not capture the maximum potential reduction in environmental impact. Implementation of true low-flow or minimal-flow targets (1 L/min) would be expected to drastically and proportionally lower absolute emissions across both study arms, meeting current best-practice environmental standards. Although FGF rates and operative durations were standardised, a relatively wide variability in volatile agent consumption was observed, particularly in the sevoflurane group. This may be attributable to interpatient differences in anaesthetic requirement, intraoperative adjustments in vaporiser settings to maintain target anaesthetic depth, variability in patient body habitus, and differences in surgical stimulation which could have contributed to the observed dispersion in agent consumption values despite protocol standardisation.

The variation in vaporiser dial settings for sevoflurane and desflurane is mainly related to the difference in their anaesthetic potency, which is commonly described using MAC.[7] Agents with a lower MAC are considered more potent because a smaller concentration is required to achieve the desired anaesthetic effect. Sevoflurane has a lower MAC value of around 2%, whereas desflurane has a higher MAC value of approximately 6%. As a result, desflurane requires higher vaporiser dial concentrations than sevoflurane to maintain a similar depth of anaesthesia.[8] In paediatric patients, MAC values are somewhat higher than in adults due to age-related physiological differences, but the comparative potency pattern remains unchanged. Consequently, the need for higher dial concentrations with desflurane may increase total volatile agent consumption and contribute to a greater environmental burden when FGF settings are kept constant.[9]

Although the distribution of surgery types between groups was not statistically significant, differences in the proportion of orthopaedic and urological procedures may have influenced operative characteristics and anaesthetic requirements. Since surgery duration is an important determinant of volatile agent consumption and associated carbon emissions, the absence of adjustment for procedure type and duration represents a limitation of the present study. Future studies incorporating multivariable analyses such as regression modelling or analysis of covariance (ANCOVA) may better account for these potential confounding factors. Patients requiring endotracheal intubation in the present study were excluded to eliminate confounding variables associated with higher anaesthetic depth requirements, changes in airway resistance, and varying mechanical ventilation strategies, thereby ensuring a homogeneous cohort for gas consumption analysis.

The Life Cycle Assessment (LCA) is a comprehensive method that evaluates a drug or device’s environmental impacts from production to disposal, often referred to as a “cradle-to-grave” analysis.[10] An additional metric, CO₂e, incorporates both the mass of the gas and its GWP—a value representing its heat-trapping capacity over 100 years (GWP100). While the GWP100 of CO₂ is 1, nitrous oxide scores 298, sevoflurane 130, isoflurane 510, and desflurane an alarming 2540.9.[2,5]

While desflurane’s low potency (high MAC) and high GWP100 (2540 vs sevoflurane 130)[11] are established theoretical facts, the current study is scientifically valuable because it transitions from theoretical modelling to real-world clinical quantification within a specific, under-researched healthcare system. Theoretical GWP calculations assume a perfect closed system. Real-world paediatric anaesthesia involves gas leaks around paediatric airways, varied real-time MAC titrations based on surgical stimulus, and differing vaporiser efficiencies. Nevertheless, the present study quantifies actual emissions in live clinical practice.

De S Cooman et al.[12] demonstrated that automated high-flow modes increase desflurane usage, especially when adjusting anaesthetic depth, further emphasising the environmental burden of desflurane. Previous trials demonstrate that total intravenous anaesthesia (TIVA) with agents like propofol produces significantly lower CO₂ emissions than inhalational anaesthesia.[2] Although TIVA was not compared in the present study, its lower carbon footprint, especially in paediatrics, warrants future investigation.

Waste anaesthetic gases (WAGs) are expelled to the atmosphere, virtually unmetabolised, and unregulated. Minimum flow anaesthesia (<1 L/min FGF) is a safe, efficient, simple, and reliable way to reduce WAGs, thereby reducing GHGs. Furthermore, another study used life cycle inventory (LCI) as a method to examine the direct carbon emissions during manufacturing and procuring general anaesthetics (e.g. energy, water, packaging, and transport) and other indirect carbon emissions from its upstream (i.e. from its raw materials) and downstream processes (i.e. from its use in health care facilities and wastes).[10]

The present study did not assess renal or hepatic function; earlier research found no significant adverse impact of sevoflurane, even in patients with pre-existing conditions.[13] These findings support the safe intraoperative use of sevoflurane in paediatric populations from both clinical and environmental perspectives.

N₂O was purposefully excluded in the current study because it is known for its extremely high GWP and occupational exposure risks. Studies show that even limited N₂O use during induction contributes significantly to the overall carbon footprint, and its elimination should be prioritised.[5,13,14] Nonetheless, waste disposal methods were not analysed in the present study.

It was reported by Pierce JMT that one MAC h of desflurane anaesthesia with FGF of 500 mL has the CO₂e of 36.5 kg, the equivalent of driving 228 km. In contrast, a 1 MAC h of sevoflurane anaesthetic with similar FGF has a CO₂e of only 0.6 kg, the equivalent of driving 4 km.[15] Using the study’s specific mean consumption data, substituting desflurane (49.30 mL) with sevoflurane (28.39 mL) results in an average net reduction of 177.84 kg CO₂e per paediatric case. The calculation uses standard density and 100-year GWP values (desflurane: 2540, sevoflurane: 130). Switching from desflurane to sevoflurane saved an average of 177.84 kg of CO₂e of every single child’s surgery. If a hospital makes this switch for just 100 surgeries a year, it stops 17,784 kg (17.78 metric tonnes) of harmful GHGs from entering the air. Based on United States Environmental Protection Agency (EPA) data, this annual saving is equivalent to avoiding 72,000 kilometers driven, or the annual carbon-sequestering capacity of 808 mature trees.[16]

The key limitations of the present study include the exclusion of hepatic and renal function evaluation and the assumption of similar resource utilisation across both groups. While airway device type and FGFs were standardised, future research should include TIVA comparisons, assess postoperative recovery metrics, and consider broader LCAs of all anaesthetic techniques.

CONCLUSION

To conclude, this study found that sevoflurane resulted in significantly lower mean agent consumption and CO₂ emissions than desflurane, making it a more environmentally sustainable option for green anaesthesia. Demographic, surgical characteristics and strict exclusion criteria minimised confounding variables. Both agents maintained stable haemodynamic parameters, indicating comparable safety profiles. Dial concentration emerged as a key factor influencing CO₂ emissions when FGF and FiO₂ were held constant. Further large-scale studies are recommended to validate these findings and guide environmentally conscious anaesthetic practices.

Study data availability

The data used in this study is available and will be shared by the authors (email to the corresponding author) with a reasonable request.

Disclosure of use of artificial intelligence (AI)-assistive or generative tools

No artificial intelligence was used for manuscript preparation except for Grammarly for academic language editing.

Author contributions

PJ, AC: Concept. PJ, AC, SP: Manuscript writing. PJ, AC, SP: Statistical analysis. PJ, AC, SP: Data collection. All authors approved the final version of the manuscript.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.