Life Cycle Carbon Footprint Assessment of 12 kV C₄F₇N Gas-Insulated Switchgear Systems

Abstract

The C₄F₇N eco-friendly switchgear shows significant application potential, and quantifying its carbon footprint can accelerate the low-carbon transition in the power industry. A life cycle assessment (LCA) model for a 12 kV C₄F₇N eco-friendly switchgear is established in this study, and the carbon footprint across four stages—raw material acquisition, transportation, operation, and recycling—is accurately quantified. Sensitivity analysis of key raw material parameters and Monte Carlo simulation are used to further quantify the impact of uncertainty in these key sensitive parameters. Results indicate that the operational stage contributes the most to the switchgear’s carbon footprint, amounting to 24,794.77 kgCO₂e, mainly due to electricity consumption. Within this stage, C₄F₇N gas leakage contributes minimally at 2.21 kgCO₂e. The raw material acquisition stage follows with 3005.57 kgCO₂e, where C₄F₇N gas, aluminum, and stainless steel are identified as the primary contributing materials. Sensitivity analysis shows that electricity, C₄F₇N, aluminum, and stainless steel are the resources that have the greatest impact on the switchgear’s carbon footprint. Compared with traditional SF₆ switchgear, the C₄F₇N switchgear has a 23.8% lower total carbon footprint, with its total carbon footprint reaching 26,771.58 kgCO₂e compared to 35,136.48 kgCO₂e for SF₆ switchgear. This advantage stems largely from C₄F₇N’s much lower global warming potential—2090 versus 25,200 for SF₆—which reduces gas-related emissions by 96.6%. These findings substantiate the practical viability of C₄F₇N-based eco-friendly switchgear and provide strategies for the power sector to achieve a low-carbon transition.

1. Introduction

In recent years, rapid industrial development has been witnessed nationwide, accompanied by the worsening of the greenhouse effect and environmental issues. The power industry has been identified as one of the major contributors to carbon emissions in China and is assigned a critical responsibility for greenhouse gas mitigation [1,2]. High-voltage electrical equipment serves as indispensable infrastructure in power systems, with medium-voltage switchgear playing a pivotal role by constituting 47% of the market share. Accurately quantifying its carbon footprint is of great significance for promoting the green transition and sustainable development of the power industry [3,4]. SF₆ has been predominantly used as the insulating medium in traditional gas-insulated switchgear; however, owing to its high GWP, the search for eco-friendly insulating alternatives has become imperative [5,6]. Numerous studies have already confirmed that C₄F₇N gas holds significant potential for application in electrical equipment [7,8,9].

Life Cycle Assessment (LCA) serves as a systematic environmental management tool that has been extensively adopted for carbon footprint quantification in the electrical industry [10,11,12]. You et al. analyzed the life cycle carbon footprint of a 40.5 kV C-GIS and found that the operation stage is the primary contributor, accounting for 92.6% of the total footprint [13]. Zhang et al. conducted a carbon footprint study on amorphous oil-immersed distribution transformers based on LCA and performed an uncertainty analysis of the results, in which the operation stage accounted for as much as 99.45%, and the uncertainty is relatively low [14]. Chen et al. found that the life cycle carbon footprint of the new type of circuit breaker is significantly reduced compared to that of SF₆ circuit breakers [15]. Perret et al. compared the life cycle environmental impacts of two 145 kV GIS systems using SF₆ and C₄F₇N insulating gases and found that the C₄F₇N gas-based GIS reduced the carbon footprint by 41.2% compared to the SF₆ gas-based GIS [16]. Cormenier et al. compared the life cycle assessment of medium-voltage switchgear using SF₆ and air, and the results showed that air-insulated switchgear had a smaller environmental impact across most indicators [17]. Additional research efforts have focused on carbon footprint comparisons for 12 kV switchgear. Fu et al. studied the carbon footprint of a 12 kV dry air-insulated switchgear during the raw material and manufacturing stages and compared it with that of an SF₆ switchgear. The carbon emissions are found to be 125.29 kgCO₂e and 117.32 kgCO₂e [18]. Chen and others compared the carbon footprint of 12 kV switchgear using three types of insulation, air, SF₆, and environmentally friendly gas, and they found that the switchgear with environmentally friendly gas had the smallest carbon footprint, while the air-insulated switchgear had the largest carbon footprint [19]. However, existing research lacks quantification of uncertainties in key material parameters and often overlooks the impacts of structural material differences in comparative analyses with SF₆ switchgear. Therefore, this study conducts an in-depth investigation into the carbon footprint of a C₄F₇N, eco-friendly, insulating gas switchgear through an integrated LCA model, incorporating a Monte Carlo simulation, evaluates material-specific contributions to carbon emissions, and identifies dominant drivers via sensitivity indices. By providing reasonable quantification and interpretation of uncertainties in carbon footprint results, this work offers critical insights for advancing low-carbon transition in switchgear technology.

In this paper, the lifecycle stages of the C₄F₇N, eco-friendly, insulated gas switchgear are divided into raw material acquisition, transportation, operation, and recycling stages based on the LCA method. A detailed data model is established to quantify the carbon footprint contributions of each stage, with the carbon footprint contribution sources and their proportions for key stages or materials being identified. Sensitivity analysis of key parameters is conducted, and Monte Carlo simulation is used to assess the impact of uncertainties in different parameter inputs on the carbon footprint results of the switchgear. The findings are used to help promote low-carbon and sustainable development in the power industry.

Section 1 introduces the research background, significance, existing studies, and research gaps regarding C₄F₇N switchgear’s carbon footprint. Section 2 details research methods, including the LCA framework, carbon footprint calculation for each life cycle stage, and the Monte Carlo-based uncertainty analysis. Section 3 presents and discusses results, covering carbon footprint distribution and sensitivity and uncertainty analyses. Section 4 compares carbon footprints of C₄F₇N and SF₆ switchgears. Section 5 summarizes conclusions, notes limitations, and suggests future research.

2. Research Method

2.1. Data-Verified Standard Framework

In this study, the life cycle assessment is conducted in strict accordance with the ISO 14040:2006 and ISO 14044:2006 standards [20,21]. The technical framework is recognized as equivalent to the Chinese National Standard GB/T 24040-2008 [22]. Four phases are encompassed: goal and scope definition, inventory analysis, impact assessment, and interpretation. A C₄F₇N gas-insulated ring main unit with a rated voltage of 12 kV, rated current of 630 A, service life of 20 years, and annual leakage rate ≤ 0.01% is selected as the research object.

Material inventory data are obtained from supplier technical documentation and manufacturer production records. The system structure and process flow are illustrated in Figure 1 and Figure 2, respectively. In Figure 2, the gray part represents the raw material preprocessing module, the blue part represents the product manufacturing module, the yellow part represents the assembly and wiring stage, and the green part represents some parallel processes. Full lifecycle modeling is performed using SimaPro 9.0 software, with carbon emission factors being supplemented through the Ecoinvent database [23,24,25]. Key component material data are presented in

Table 1. Raw material data for key components of switchgear.

Categorization	Materials	Quantity (kg)
Sheet metal for inflatable cabinets	aluminum zinc clad plate	94.83
	Q235	12.34
	304	56.37
Vacuum circuit breaker switch	steel	55.09
	aluminum alloy	1.78
	copper	12.44
	epoxy resin	6.22
	rubber	3.11
	plastic	2.67
	ceramic	2.67
Cable strut, lower isolation side expansion sleeve	epoxy resin	7.34
Environmentally friendly straight sleeve	epoxy resin	4.09
V copper rods, copper pillars	copper	5.989
Busbar	copper	3.146
C4F7N gas	C4F7N	0.53
CO2 gas	CO2	0.6

.

The system boundary is divided into four stages based on the LCA method: raw material acquisition, transportation, operation, and recycling. The carbon footprint calculation model for the switchgear can be represented as follows:

$$C=C_{mi}+C_{pi}+C_{ui}+C_{yi}$$

(1)

Here, C represents the carbon footprint of the switchgear, kgCO₂e, C_mi denotes the carbon emission from the raw material acquisition stage, kgCO₂e, C_pi indicates the carbon emission generated during the transportation stage, kgCO₂e, C_ui refers to the carbon emission produced in the operation stage, kgCO₂e, and C_yi stands for the effectively reduced carbon emission during the material recycling process, kgCO₂e.

2.2. Carbon Footprint Calculation Method

2.2.1. Raw Material Acquisition Stage

The carbon emission calculation formula for the raw material acquisition stage consists of three components: metallic materials, insulating materials, and insulating gas, as expressed in Equation (2):

$$C_{mi}={\displaystyle \sum _{i=1}^n(E_{mi}}\times E{F}_{mi})$$

(2)

In the equation, EF_mi denotes the carbon emission factor of material type i, kgCO₂e/kg; E_mi is the consumption of material type i, kg.

2.2.2. Transportation Stage

The transportation stage refers to the movement process of products or raw materials from production sites to usage locations or disposal sites through various transportation modes during their life cycle. The transportation distances for each component are listed in

Table 2. Transportation distances of each component.

Component Name	Transportation Distance (km)
Through-wall casing, environmental protection cabinet casing, others	1155
Microcomputer protection devices, copper core wires, others	340
Environmental protection cabinet V, rear lower sealing plate, others	1208
Circuit breaker isolation switch, mechanism kit, others	1155
Ring network box shell, others	464

. The carbon emission of this stage is calculated through reverse accounting based on the total fuel consumption during this process. The primary calculation formula for this stage’s carbon emission is given by Equation (3):

$$C_{pi}={\displaystyle \sum _{i=1}^n(L_{mi}}\times E{F}_{mi})$$

(3)

In the equation, EF_mi is the carbon emission factor of diesel, kgCO₂e /L; L_mi is the diesel consumption of each component during the transportation stage, L.

2.2.3. Operation Stage

The carbon emission of the operation stage of the C₄F₇N environmentally friendly switchgear consists of two parts: the carbon emissions generated by the electricity consumption during operation and the carbon emissions caused by the leakage of C₄F₇N gas during operation. The carbon emission is calculated using Equation (4):

$$C_{ui}=E\times E{F}_i+M\times GWP$$

(4)

In the equation, E is the electricity consumed during the operation stage, kWh; EF_i is the average emission factor of the national power grid, kgCO₂e/kWh; M is the amount of C₄F₇N gas leaked during the operation stage, kg; and GWP is the global warming potential of the C₄F₇N insulating gas.

2.2.4. Recycling Stage

Recycling materials effectively reduces the product’s lifecycle carbon emission [23]. The recyclable material mass equals the product of the recycling rate and total material quantity. Thus, Equation (5) gives the calculation for various materials’ recyclable mass and corresponding carbon emission reduction:

$$C_{\mathrm{yi}}={\displaystyle \sum _{i=1}^n(E{F}_{mi}\times M_{mi})}$$

(5)

In the equation, M_mi is the physical quantity of the i-th recyclable material, kg; EF_mi is the emission factor of the i-th recyclable material, kgCO₂e/kg.

In this study, the aluminum-zinc coated steel sheets used in the switchgear are recyclable. The recovery rates for aluminum and zinc are 85.74% and 80%, respectively. The recovery rate for stainless steel is 85%, and for steel, it is 80%. The main resources involved across the full lifecycle stages and their corresponding emission factors are shown in

Table 3. Data on major resources and their corresponding carbon emission factors.

Life Cycle Stage	Resource Type	Value	Unit	Carbon Emission Factor	Unit
Raw material acquisition	stainless steel	56.37	kg	4.958	kgCO2e/kg
	steel	67.43		1.97
	aluminum alloy	1.78		10.27
	copper	21.58		5.272
	epoxy resin	17.65		8.808
	rubber	3.11		1.64
	plastic	2.67		17.98
	ceramic	2.67		1.12
	aluminum	52.16		19.468
	silicon	1.42		10.917
	zinc	41.2		2.694
Transportation	distance	4322	km	0.162	kgCO2e/tkm
	weight	268.04	kg
Operation	electricity	26,280	kwh	0.9434	kgCO2e/kwh
	C4F7N	1.06 × 10−3	kg	2090	kgCO2e/kg
Recycling	aluminum	44.72	kg	19.468	kgCO2e/kg
	zinc	32.96		2.694
	stainless steel	4.21		4.958
	steel	9.87		1.97

.

2.3. Uncertainty Analysis Method

In this study, a local sensitivity analysis is conducted to assess key factors influencing the carbon footprint of C₄F₇N ring main units, employing single-parameter perturbation while holding other variables constant. To quantify data collection biases and model uncertainties, Monte Carlo simulation is implemented through MATLAB 2023B with 10,000 sampling iterations [26,27,28,29]. The workflow comprised the following: (1) Key input parameters are selected based on sensitivity analysis. (2) Probability distributions are defined (triangular for material quantities and normal for electricity consumption); (3) parameter sets X_j = {X_1j, X_2j, …, X_ij} are generated via Latin Hypercube Sampling; (4) each parameter set is input into the carbon footprint model to compute outputs Y_j; and (5) statistical characteristics including mean, standard deviation, coefficient of variation, and 95% confidence intervals are derived from the output set {Y₁, Y₂, …, Y₁₀₀₀}.

3. Results and Discussion

3.1. Carbon Footprint by Lifecycle Stage

The carbon footprint distribution and corresponding percentages for each stage of the C₄F₇N-insulated gas switchgear are presented in

Table 4. Carbon emission distribution and proportion by life cycle stage.

Life Cycle Stage	Carbon Emission/kgCO2e	Proportion
Raw material acquisition	3005.57	11.23%
Transportation	187.7	0.7%
Operation (electricity)	24,792.55	92.61%
Operation (leakage)	2.21	/
Recycling	−1216.45	−4.54%

and Figure 3a. The total carbon footprint of the switchgear is calculated as 26,771.58 kgCO₂e. Among these, the operation stage contributes the most, accounting for 24,794.77 kgCO₂e, which represents 92.61% of the total carbon footprint. This is primarily attributed to electricity consumption during operation. Notably, the leakage of C₄F₇N gas in this stage contributes merely 2.21 kgCO₂e, which is substantially lower than the 16,491 kgCO₂e reported in literature [13] for SF₆ GIS leakage during its entire lifecycle. These results further demonstrate the necessity of replacing SF₆ with environmentally friendly insulating gases. The second-largest contributor is the raw material acquisition stage, with a carbon emission of 3005.57 kgCO₂e. The distribution of the carbon emission in this stage is shown in Figure 3b. C₄F₇N insulating gas, aluminum, and stainless steel are the main contributing materials, accounting for 36.86%, 33.79%, and 9.3%, respectively. During the recycling stage, the used metal resources can be recovered and reused, effectively reducing the carbon emission of the switchgear product and contributing to its green development.

3.2. Carbon Footprint Sensitivity and Uncertainty Analysis

To identify the influence of key materials on the product’s carbon footprint, a sensitivity analysis is conducted by varying the consumption of major materials by ±10% and calculating the corresponding changes in carbon footprint. The resulting variations and sensitivity indices are presented in

Table 5. Carbon footprint sensitivity analysis results.

Resource	Carbon Emission Change (kgCO2e)	Sensitivity (×10−2)
Aluminum	101.55	3.79
C4F7N	110.77	4.13
Stainless Steel	27.95	1.04
Steel	13.28	0.50
Aluminum	1.83	0.07
Copper	11.38	0.42
Epoxy Resin	15.55	0.58
Rubber	0.51	0.02
Plastic	4.8	0.18
Zinc	11.1	0.41
Ceramics	0.3	0.01
Silicon	1.55	0.05
Transportation	18.77	0.70
Electricity	24,792.26	92.46

. The sensitivity results show that changes in electricity consumption have the most significant impact on the carbon footprint of the switchgear, with a sensitivity coefficient as high as 0.9246. This is primarily due to the cumulative effect of continuous energy consumption during the operation stage of the C₄F₇N switchgear throughout its life cycle. Additionally, the sensitivity of the four components, C₄F₇N, aluminum, stainless steel, and transportation processes, is relatively high, with values of 4.13 × 10⁻², 3.79 × 10⁻², 1.04 × 10⁻², and 0.70 × 10⁻², respectively, and they have a significant impact on the carbon footprint of the switchgear. The high sensitivity of aluminum is due to the high energy consumption of aluminum electrolysis during production, which results in significant carbon emissions, whereas the sensitivity of the transportation process is relatively high because the transportation of switchgear components involves long distances, with higher uncertainty arising from traffic congestion and the transition between major and minor roads.

To evaluate the reliability of the LCA results, this study further analyzes the uncertainty in carbon footprint assessment introduced by these four key sensitive parameters. For the uncertainty analysis, variations of ±10% are applied to C₄F₇N gas, stainless steel, and aluminum parameters, while electricity consumption is assigned a ±5% variation range [30,31]. A total of 10,000 Monte Carlo simulations are performed by MATLAB, with all key sensitive parameters following either triangular or normal distributions. The probability distributions of all key sensitive parameters conform to either triangular or normal distributions, ultimately generating characteristic lifecycle carbon footprint distribution profiles as shown in Figure 4. When key sensitive parameters follow a triangular distribution, the 95% confidence interval ranges from 25,809.24 to 27,743.19 kgCO₂e with a median of 26,779.35 kgCO₂e. Under the normal distribution assumption, the 95% confidence interval widens significantly to 21,826.80–31,536.99 kgCO₂e, indicating greater uncertainty, while the median remains highly consistent at 26,776.44 kgCO₂e. Both distribution assumptions demonstrate good agreement with actual conditions.

This study has certain limitations. Specifically, the data sources are geographically restricted, as they rely on specific suppliers and databases, which may limit the generalizability of the findings across different regions. Additionally, the fluctuation ranges of parameter assumptions are set based on experience, and there may be deviations from actual conditions in practical applications. To address these limitations, future research can expand the scope of data collection to include more diverse sources, optimize parameter assumptions by incorporating real-world operational data, and conduct multi-technical comparisons with other alternative gases and switchgear systems. These efforts will help enhance the reliability and robustness of the research conclusions.

4. Comparison of Carbon Footprints Between Two Types of Switchgears

To more effectively evaluate the market potential of the environmentally friendly C₄F₇N gas-insulated switchgear, a comparative carbon footprint analysis is conducted against conventional SF₆ switchgear. The data for the SF₆ switchgear is sourced from reference [17], which describes a 12 kV SF₆ switchgear with specific parameters shown in

Table 6. List of SF₆ switchgear data.

Material Type	Mass/kg
Steel	412
Copper	161
Aluminum	11.8
Plastic	18.9
Epoxy resin	16.2
Glass (1.4 kgCO2e)	1.2
Rubber	1.3
SF6	1.3

. The material carbon emission factors used in reference [17] differ from those in this study. To ensure consistency for comparison, the carbon emission factors are taken from the data in Table 3. The carbon emission of SF₆ gas in the switchgear is calculated based on its GWP, with the GWP of SF₆ gas being 25,200.

A comparison of the carbon footprint between the environmentally friendly C₄F₇N switchgear and the SF₆ switchgear is illustrated in Figure 5. In the carbon footprint of SF₆ switchgear, the contribution of gas is extremely high, reaching 32,760 kgCO₂e, while the total of other materials is only 2376.48 kgCO₂e. In contrast, the environmentally friendly C₄F₇N switchgear has more advantages in terms of carbon emission performance: not only are the gas carbon emissions much lower than those of SF₆ equipment, but the carbon emissions from other materials are also lower, which is closely related to the differences in material selection and processes among manufacturers.

From a systematic comparison, the gas emissions of C₄F₇N switchgear are significantly reduced. Its usage is 40.8% less than that of SF₆, which is 0.53 kg versus 1.3 kg, and its global warming potential is significantly lower, 2090 versus 25,200. As a result, the related emissions have been reduced by 96.6%, reaching 1110.21 kgCO₂e. In addition, the utilization of aluminum and stainless steel has been optimized, with aluminum reduced by 18.7% and stainless steel by 14.3%. Due to the combination of the above reasons, the total carbon footprint of C₄F₇N switchgear is 23.8% lower than that of SF₆, which is 26,771.58 kgCO₂e versus 35,138.6 kgCO₂e.

This difference in carbon emissions stems from both the inherent properties of the materials, such as differences in global warming potential, and engineering optimizations, such as improvements in material efficiency. This indicates that the environmental advantages of C₄F₇N switchgear do not merely rely on gas replacement but result from the overall redesign of the system. Obviously, C₄F₇N switchgear is more in line with the requirements of low-carbon and environmental protection. As an important solution for the decarbonization of power infrastructure, it will surely occupy a key position in the future development of insulating gases for power equipment.

5. Conclusions

The full life cycle carbon footprint analysis of 12 kV C₄F₇N eco-friendly switchgear is conducted in this study using the Life Cycle Assessment method. Sensitivity analysis and Monte Carlo simulation are combined to quantify the uncertainty of key parameters. The results show that the operation stage is the main contributor to the equipment’s carbon footprint, with 24,794.77 kgCO₂e accounting for 92.61% of the total, mainly due to electricity consumption, while only 2.21 kgCO₂e is contributed by C₄F₇N gas leakage. The raw material acquisition stage contributes 3005.57 kgCO₂e, with C₄F₇N gas, aluminum, and stainless steel identified as the main sources. Compared with traditional SF₆ switchgear, C₄F₇N equipment exhibits significant carbon footprint advantages—its total carbon footprint is 26,771.58 kgCO₂e, 23.8% lower than that of SF₆ equipment at 35,136.48 kgCO₂e. This advantage arises not only from the much lower global warming potential of C₄F₇N (2090) compared to SF₆ (25,200), which reduces gas emissions by 96.6%, but also from the optimized use of materials such as aluminum (with an 18.7% reduction) and stainless steel (with a 14.3% reduction). These results confirm the practical value of C₄F₇N equipment in the low-carbon transition of the power industry and provide a scientific basis for promoting its application. Based on the findings, it is recommended that the industry further optimize equipment operating efficiency to reduce carbon emissions from electricity consumption and continuously improve material selection and production processes. Future research can expand data sources to enhance the generalizability of results, conduct long-term monitoring of gas leakage rates under actual operating conditions, and comprehensively compare C₄F₇N with other alternative gases to provide more comprehensive references for low-carbon choices of insulating media in power equipment.