Assessing the GHG Emissions and Savings during the Recycling of NMC Lithium-Ion Batteries Used in Electric Vehicles in China

Abstract

Driven by the global campaign against the dual pressures of environmental pollution and resource exhaustion, the Chinese government has proposed the target of carbon neutrality. On account of this, the increasing number of waste lithium-ion batteries (LIBs) from electric vehicles (EVs) is causing emergent waste-management challenges and it is urgent that we implement an appropriate waste-LIB recycling program, which would bring significant environmental benefits. In order to comprehensively estimate the total greenhouse gas (GHG) emissions from waste-LIB recycling, the GHG savings also need to be taken into account. Based on the requirements of a carbon-neutral target, this study adopted the Intergovernmental Panel on Climate Change (IPCC) method to established a mathematical model for measuring the GHG emissions and GHG savings of waste LIBs and a numerical experiment is presented to verify the model. The results were analyzed and are discussed as follows: (1) To achieve carbon neutrality, the resultant GHG emissions and GHG savings are equal, and the corresponding value is 706.45 kg CO₂-eq/t. (2) The influence of the ratio of recovery from different collection centers on the net GHG emissions is relatively weak and the ratio of different processing strategies significantly affects the net GHG emissions. (3) There are three directions including recycling technologies, type of batteries, and environmental pollutants, that warrant investigation in the future research.

1. Introduction

To cope with increasingly serious environmental pollution and climate change issues, the Chinese Government, at a meeting of the United Nations General Assembly in 2020, promised to reach the peak of CO₂ emissions by 2030 and become carbon-neutral before 2060 [1]. Considering the multiple uncertainties that exist in the implementation of carbon reduction, such as economic growth and low-carbon transition [2], it is a formidable task to achieve the goal of carbon neutrality.

Due to the arrival of the peak of the first wave of lithium-ion battery (LIB) recycling in the market, LIB recycling has become a burgeoning industry. According to the China Automotive Technology and Research Center, the cumulative number of retired LIBs in China has increased to 200,000 tons (about 25 GWh) in 2020 and is expected to reach 780,000 tons (about 116 GWh) in 2025 [3]. Unrecycled effectively, these waste batteries will not only bring great environmental pollution, but also cause a waste of resources.

Remanufacturing, being an effective strategy with promising prospects for the recycling of waste LIB [4], cut down the environmental impacts of both the waste disposal and battery production. On the basis of a report of the International Resource Panel, remanufacturing can save 80 to 98 percent of new materials and help reduce GHG emissions in some industries by 79 to 99 percent, which has great potential to achieve reductions in GHG emissions [5].

It has already been confirmed that the recycling of waste LIBs of EVs can bring significant environmental benefits including energy savings and reduction in environmental pollution [6]. On the one hand, the residual value of batteries can be utilized through echelon utilization and a large number of high-value metal resources such as cobalt, lithium, nickel, and manganese in decommissioned LIBs can be extracted by smelting [7]. On the other hand, harmful substances including heavy metals, electrolytes, and organic solvents in waste LIB can be protected from leakage under careful and proper disposal. For this reason, research on the recycling of LIBs is meaningful for reaching sustainable development.

In recent years, increasing attention is being paid to the environmental impact of LIB recycling of EVs. However, previous research has mainly focused on two aspects. From the perspective of using the GHG emissions as an indicator of the recycling model, Lei et al. (2020) established a recycling model of EV batteries considering carbon emission, which included three potential battery-handling strategies including recycling, remanufacturing, and disposal [8]. Tang et al. (2018) used the carbon emission reduction effect as an indicator to select the optimal battery recycling modes [9]. Sun et al. (2020) established a cost–benefit model of a battery energy storage system that was constructed by the recycled LIBs, in which the environmental benefit was calculated through GHG emissions trading [10]. From the standpoint of the calculation of the GHG emissions of the recycling process, Yu et al. (2021) evaluated the life-cycle GHG emissions based on the EverBatt model in remanufacturing, which includes four types of lithium batteries—NCM111, NCM622, NCM811, and NCA. In addition, three different recycling methods—pyrometallurgical recycling (PR), hydrometallurgical recycling (HR), and direct physical recycling (DPR) were considered [11]. Golroudbary et al. (2019) estimated the GHG emissions of the recycling of five different LIBs (LMO, LCO, LFP, NCM, and LiNCA), which was based on energy consumption in each process and the recovery of critical minerals including lithium, cobalt, and manganese [12]. Xiong et al. (2020) calculated the environmental impacts during each remanufacturing process of NMC111 batteries based on the materials and energy flows [4].

Nevertheless, there has not been research that assesses the contribution of GHG savings, which can make the calculation of carbon emissions more comprehensive and accurate from the perspective of avoiding virgin resource production and new battery production in the process of waste-LIB recycling. In recycling waste electrical and electronic equipment (WEEE), Menikpura et al. (2014) assessed the GHG emissions and savings via material recovery and avoiding virgin resource production based on life-cycle assessment (LCA) methodology [13]. The findings make a significant contribution to climate-change mitigation and resource savings. Therefore, it is necessary to comprehensively evaluate the GHG emissions and savings during the recycling of LIBs. The uncertainty of influencing factors makes the quantification of GHG savings difficult and complicated, requiring the comparison between the GHG emissions of equal materials or products produced through remanufacturing with the original production. To fill this knowledge gap, this study assesses the environmental benefits of waste-LIB recycling from two aspects including life-cycle GHG emissions of the overall recycling process and GHG savings through product recovery. The results of this research will bring guidance and reference to LIB recycling enterprises under the background of carbon neutrality. Furthermore, this study will be beneficial for promoting sustainable development in the EV industry. Most importantly, this study can help control CO₂ emissions and achieve near-zero emissions.

The remainder of the paper is organized as follows: The methodology of this research is introduced in Section 2 and a mathematical model is provided in Section 3. Section 4 presents numerical experiments to verify the model and sensitivity analysis is presented in Section 5. Section 6 presents several important conclusions.

2. Methodology

Motivated by the need for assessing the environmental benefits from waste-LIB recycling of EVs, this research follows the methodology shown in Figure 1. The four steps are: (1) objective design; (2) modeling; (3) numerical experiments; (4) sensitivity analysis.

(1)

Objective design: With the aim of assessing the environmental impact and achieving carbon neutrality in the recycling process of LIB, this paper introduces a carbon-emission assessment model which compares the variations between GHG emissions and GHG savings.

(2)

Modeling: Based on the above objective analysis, the second step consists of building the model formulation to estimate the net GHG emissions of the waste-LIB recycling process under the carbon-neutral target. The objective of the proposed model is to reach a balance between GHG emissions and GHG savings. In addition, this step will propose the method to calculate the carbon emissions and carbon savings of waste-LIB recycling.

(3)

Numerical experiments: According to the data collected during the previous research, a typical case will be applied to verify the model put forward in the previous step. Furthermore, the results of GHG emissions and GHG savings from the LIB recycling process will be shown.

(4)

Sensitivity analysis: To analyze the impacts of the relevant variables on the carbon-neutral target model, a sensitivity was applied considering that the recycling technology and battery type were unchanged.

3. Modeling

This section introduces the numerical model developed to quantify the net GHG emissions from recycling process under the carbon-neutral target. Furthermore, it shows the approach to estimate the GHG emissions and GHG savings of waste-LIB recycling.

3.1. Carbon-Neutral Target Model Formulation

Similar to general waste recycling, the recycling processes of LIBs can be classified into three stages: (1) The collection stage, in which the battery after-sales service enterprise collects waste LIB packs replaced by customers and automobile scrap plants collect waste LIB packs from scrapped vehicles. (2) The logistics stage, which refers to these waste LIBs being transported from collection centers to a pre-treatment facility and then to different processing scenarios. Pre-treatment also includes dismantling the EV battery packs and diagnosing the current state-of-health (SOH) of the modules [14]. (3) The treatment stage, in which the recycling enterprise treats LIBs. As mentioned in Figure 2, there are two processing strategies for LIBs after pre-treatment, including being recycled for cascade utilization or only for recovery utilization. Recovery utilization involves recovering material from retired batteries for remanufacturing, and cascade utilization involves applying retired batteries for energy-storage applications [15]. The cascade utilization and recovery utilization of waste lithium batteries is one life-cycle, and the recovery utilization after a second-life service of retired lithium batteries is another life-cycle. The life-cycle boundaries assessed in this paper are cascade utilization and recovery utilization. According to the standard of remanufactured products, the remanufactured battery product’s life-span is required to be same as the brand-new battery’s life-span.

At present, the GHG emission calculation methods mainly utilize the Intergovernmental Panel on Climate Change (IPCC) method, the factor decomposition method, and the input−output method [16]. However, the results of the input−output method can only obtain industry data, but cannot obtain the situation of products, and the factorization method uses macroeconomic data to calculate GHG emissions, which leads to high uncertainty. As the IPCC method is a national-level mature estimation method that has been widely recognized internationally, we adopted the IPCC method in this work to assess the GHG emissions and savings during the recycling of LIBs.

Based on the analysis above, a mathematical model was developed under the carbon-neutral target through considering both GHG emissions and savings throughout the life-cycle of LIB recycling. The net GHG emissions from the process of waste-LIB recycling is as follows:

$$E_{Netemissions}=E_{Totalemissions}-E_{Totalsavings}$$

(1)

where $E_{Netemissions}$ is the net GHG emissions of waste-LIB recycling, $E_{Totalemissions}$ represents the total GHG emissions, and $E_{Totalsavings}$ is the total indirect GHG savings.

$$E_{Totalemissions}=E_T+E_P+E_C\times {\rho }_1+E_R\times {\rho }_2$$

(2)

where $E_T$ represents the GHG emissions from transportation process, $E_P$ is GHG emissions from the pre-treatment process, $E_C$ is GHG emissions from the cascade utilization process, ${\rho }_1$ represents the ratio of waste batteries to cascade utilization, $E_R$ is GHG emissions from recovery utilization process and ${\rho }_2$ represents the ratio of waste batteries to recovery utilization.

$$E_T=E_i\times {\eta }_i$$

(3)

where $E_i$ represents the GHG emissions generated through route $i$ and ${\eta }_i$ is the ratio that goes through route $i$.

$$E_{Totalsavings}=E_{sr}\times {\rho }_1+E_{sm}\times {\rho }_2$$

(4)

$${\eta }_i\in \left\{0,1\right\},{\rho }_1,{\rho }_2\in \left\{0,1\right\}$$

(5)

where $E_{sr}$ represents the GHG savings from battery remanufacturing and $E_{sm}$ is the GHG savings from recovery of materials.

3.2. Calculation Method of GHG Emissions from the Recycling Process

In this research, life-cycle assessment (LCA) was used to evaluate the environmental impact (GHG emissions) of waste-LIB recycling. The LCA approach identifies the life-cycle inputs/outputs of the recycling system in relation to all phases of the life-cycle [13]. In the recycling process, the emission of waste LIBs to the environment are primarily concentrated in four stages—transportation, pre-treatment, cascade utilization, and recovery utilization. As a consequence, from the perspective of the GHGs of the waste-LIB recycling process to the environment, this study takes recycling, battery remanufacturing, and material refining as the system boundary of waste-LIB recycling. In addition, the present study defines the functional unit of LCA as one ton of recovered waste LIBs.

3.2.1. GHG Emissions from Transportation Process

The transportation process of waste LIBs can use petrol vehicles or EVs. As EVs have little impact on the environment during the stage of transportation, this is not considered in this paper. In the following section, the type of vehicle listed as transporting lithium batteries is petrol vehicles. Detailed assessment was done in relation to GHG emissions in the transport process as the fuel consumption during transportation of LIB recycling is a significant aspect that accounts for an important amount of GHG emissions. In the process of LIB transportation, the amount of GHG emissions is determined by the amount of fuel used and the emission factor. According to the IPCC (2006) guidelines [17], the calculation method of GHG emissions in transportation process can be represented as follows:

$$E_T={\displaystyle \sum }_j\left(F{C}_T\times E{F}_j\times GW{P}_j\right)$$

(6)

where $F{C}_T$ is the amount of fuel used, $E{F}_j$ is the emission factor of type $j$ GHG, and $GW{P}_j$ represents the global warming potential of type $j$ GHG.

When calculating the amount of fuel used in transportation process, we considered the transportation distance $D_T$ and fuel consumption efficiency $FCE$, as shown in Equation (7).

$$F{C}_T=D_T/FCE$$

(7)

3.2.2. GHG Emissions from the Pre-Treatment Process

When considering the GHG emissions of the pre-treatment process, this research mainly adopted the IPCC 2006 assessment method [17], focusing on the GHG emissions derived from the consumption of fossil fuels and electricity for the operating machines. This can be seen in Equation (8).

$$E_P={\displaystyle \sum }_i\left(E{C}_i\times E{F}_{el}\right)+{\displaystyle \sum }_{i,j}\left(F{C}_i\times NC{V}_{FF}\times E{F}_{i.j}\times GW{P}_j\right)$$

(8)

where $E{C}_i$ is electricity consumption apportioned to the activity type $i,$ $E{F}_{el}$ represents the emission factor for grid electricity generation, $F{C}_i$ is the fuel consumption apportioned to the activity type $i,$ $NC{V}_{FF}$ represents net calorific value of the fossil fuel consumed, $E{F}_{i.j}$ is the emission factor of a $j$th GHG by activity type $i$; $\mathrm{and} GW{P}_j$ represents global warming potential of type $j$ GHG.

3.2.3. GHG Emissions from the Cascade Utilization Process

Regarding the GHG emissions in cascade utilization process, the consumption of electricity for the operating machines in the battery remanufacturing process was taken into account. Therefore, the approach in Section 3.2.2 can be used to calculate the GHG emissions in cascade utilization process.

3.2.4. GHG Emissions from the Recovery Utilization Process

The GHG emissions in the metal refining process was also calculated based on fossil fuels and electricity for the operating machines, as shown in Equation (8).

3.3. Calculation Method of GHG Savings from the Recycling Process

3.3.1. GHG Savings from the Cascade Utilization Process

As mentioned in Section 3.1, a part of the LIBs is used in the echelon after the pre-treatment process. Compared with manufacturing batteries with virgin materials, remanufacturing can realize the largest amount of carbon reduction, as a large amount of fossil fuels and electricity use for battery production can be avoided. Based on the modelling equations in previous research [18], emissions of battery production can be estimated as follows:

$$E_{bm}=B\left(C_B+C_{El-B}\times E{F}_E\right)$$

(9)

where $B$ is the battery pack weight, $C_B$ is a coefficient representing emissions from processing of battery materials, $C_{El-B}$ is the coefficient representing electricity usage during battery production, and $E{F}_E$ represents the electricity emission factor.

Therefore, GHG savings from battery remanufacturing can be quantified by Equation (10).

$$E_{sr}=E_{bm}\times r\left(\alpha \right)$$

(10)

where $r\left(\alpha \right)$ represents the equivalence coefficient of old and new batteries.

3.3.2. GHG Savings from the Recovery Utilization Process

If the battery cannot be used in cascade utilization, it will be disassembled to extract valuable metals and materials. GHG savings via recovery of metals and materials from waste LIB and replacement of an equivalent amount of virgin resources can be calculated as follows:

$$E_{sm}={\displaystyle \sum }_i\left(P{A}_i\times E{F}_i\right)$$

(11)

where $P{A}_i$ is the potential avoidance of $i$th GHG via materials/metal recovery and $E{F}_i$ represents the equivalency factor of $i$th GHG.

4. Numerical Experiments

The model proposed in Section 3 was applied to a specific case study. All the data and assumptions considered for all relevant stages of the LIB recycling life-cycle are presented in Section 4.1. The results of GHG emissions and GHG savings from the recycling process are then described in Section 4.2.

4.1. Basic Data

The case study was selected based on the available real data gathered during the research. In order to assess the environmental benefits of LIB recycling in China, L Battery Recycling Co., Ltd.’s recycling chain was selected as the study case. For calculating the GHG emissions and GHG savings from LIB recycling, we collected the consumption of fossil fuels and electricity and their emission factor. The emission factors of fossil fuels and electricity were obtained from IPCC (2006) guidelines [17] and Guidance on Accounting Methods and Reporting of Greenhouse Gas Emissions from Enterprises Power Generation Facilities [19]. The consumption of fossil fuels and electricity were from previous research on LIB recycling process ([18,20,21,22,23]). In addition, the data on GHG emissions from virgin production processes were obtained from the database of the China Nonferrous Metals Industry Association.

Table 1. The logistic chain of LIB recycling.

Transportation Route	Transportation Distance 1 (km/One Way)	Fuel Consumption Efficiency 2 (km/L)	Loading Capacity 3/(t)	Ratio 4
Battery after-sales service enterprise A to pre-treatment (dismantling) facility C	32	3.5	5	50%
Automobile scrap plant B to pre-treatment (dismantling) facility C	62	3.5	5	50%
Pre-treatment (dismantling) facility C to cascade utilization (restructuring) facility D	165	3.5	5	30%
Pre-treatment (dismantling) facility C to recovery utilization (smelting) facility F	180	3.5	5	70%

¹ Own assumptions based on the actual investigation. ² Assuming that the fuel is diesel, the fuel consumption efficiency of diesel is 3.5 km/L [13]. ³ Assuming that the transport vehicle is the medium-sized truck. According to the relevant provisions of the state estimate, the average load of medium-sized trucks is 5 t. ⁴ Own assumptions.

lists the transportation distance, fuel consumption efficiency, and loading capacity in different transportation routes. Combustion of fossil fuels during LIB transportation can emit various GHGs such as CO₂, CH₄, and N₂O. According to IPCC emissions factors [17], CH₄ and N₂O concentrations can be assumed to be negligible. Hence, the GHG emissions in this study were converted into CO₂-equivalent (CO₂-eq), and the global warming potential was 1.

Table 2. The calorific values and emission factors of various fuels.

Fuel Type	Calorific Value	Emission Factor	Source of Information
Diesel	43 MJ/L	0.0739 kg CO2-eq/MJ	IPCC (2006) guidelines [17]
Natural gas	48 MJ/kg	0.056 kg CO2-eq/MJ	IPCC (2006) guidelines [17]
Grid electricity	-	0.5839 kg CO2-eq/kWh	[19]

shows the calorific values and emission factors of various fuels used in the model. The energy consumption of the pre-treatment process can be seen in

Table 3. The energy consumption of the pre-treatment process.

Fuel Type	LIB	Source of Information
Natural gas (kg/t)	0.010437	[18]
Grid electricity (kw h/t)	0.0536	[18]

.

Table 4. The energy consumption of the cascade utilization process.

Fuel Type	LIB	Source of Information
Grid electricity (kw h/t)	35.68	[18]

shows the energy consumption of the cascade utilization process.

Since different recovery technologies lead to different energy consumptions, pyrometallurgical recycling was considered in this study to recover metal materials. The energy consumption of recovery utilization process is shown in

Table 5. The energy consumption of the recovery utilization process.

Fuel Type	LIB	Source of Information
Diesel (L/t)	139.95	[20]
Grid electricity (kw h/t)	1300	[20]

. Assuming that the battery type is NCM811, the data used for the battery manufacturing process can be seen in

Table 6. Data used for the battery manufacturing process.

Parameter	NMC	Source of Information
Coefficient representing emissions (kg eq-CO2/kg)	10.9	[18]
Coefficient representing electricity usage (kw h/kg)	16.8	[18]
The equivalence coefficient of old and new batteries	0.04	[21]

.

Table 7. Data used for quantizing GHG savings from recovery of materials.

Type of Metal	Metal Content [22] (kg/t)	Recovery Ratio of Metal 1 (%)	CO2 Emission from Virgin Production Process (kg CO2-eq/kg of Material)
Nickel	99.78	90	7.05 2
Cobalt	12.56	90	0.8 2
Manganese	11.67	90	0.9 [23]
Lithium	14.78	90	0.03 2

¹ It was considered that recyclability of all the metals would be 90% [22,24]. ² The data were obtained from the database of the China Nonferrous Metals Industry Association.

shows data used for quantizing GHG savings from recovery of materials. Based on the research of Li et al. [24], in situ roasting reduction (in situ RR), one of the recovery methods of waste lithium-ion battery pyrometallurgy, can achieve efficient recovery of Li, Ni, Co, and Mn, with recovery rates above 94%. Therefore, the metal recovery rate in this paper was set at 90% [22].

4.2. Model Results

In order to better quantize the environmental benefits of LIB recycling, one ton of waste LIB was set as functional unit and the above data was brought into the formulae in Section 3.2 to obtain the GHG emissions from the recycling process. The results are shown in

Table 8. GHG emissions from the recycling process for waste LIBs.

Processes		CO2 Emissions (kg CO2-eq/t)
Transportation	Battery after-sales service enterprise A to pre-treatment (dismantling) facility C	11.62
	Automobile scrap plant B to pre-treatment (dismantling) facility C	22.52
	Pre-treatment (dismantling) facility C to cascade utilization (restructuring) facility D	59.92
	Pre-treatment (dismantling) facility C to recovery utilization (smelting) facility F	65.37
Pre-treatment		59.35
Cascade utilization		35.68
Recovery utilization		803.41
Total		713.25

.

As previously discussed, there are two processing strategies for LIBs. The life-cycle GHG emissions from the recycling process were compared with the GHG emissions from the virgin manufacturing of the equivalent value of batteries and the virgin production of the equivalent amounts of materials in order to quantize the GHG savings of recycling LIBs.

Table 9. GHG savings from the recycling process for waste LIBs.

Processes	CO2 Emissions (kg CO2-eq/t)
Cascade utilization	651.98
Recovery utilization	828.38
Total	704.90

lists the results of GHG savings from the recycling process.

5. Sensitivity Analysis and Discussion

Due to the uncertainty of some parameters, a sensitivity analysis was run to assess the influence of the ratio of different processing strategies and the ratio of recovery from different collection centers on the GHG emissions and GHG savings from the recycling process.

5.1. Sensitivity Analysis of the Ratio of Collection Centers

We simulated the results according to the model and data mentioned above to determine whether it would achieve the carbon-neutral target of the waste-LIB recycling process. Several values were assumed for the ratio of recovery from the battery after-sales service enterprise on condition that the ratio of cascade utilization ${\rho }_1$ remained at 30%. The total GHG emissions, GHG savings, and net GHG emissions from recycling process were derived for each of values of ${\eta }_i$ specified in Figure 3, taking account of the unchanged recovery technology and the battery type.

In order to reflect the effect of the ratio of recovery from different collection centers on results, this study calculated the total GHG emissions, GHG savings, and net GHG emissions when the ratio of recovery from battery after-sales service enterprise ${\eta }_1$ were 40%, 50%, and 60%. As a result, the values of $E_{Totalsavings}$ remained the same, and the values of $E_{Totalemissions}$ and $E_{Totalsavings}$ were influenced by 1.09 kg CO₂-eq/t when the ${\eta }_1$ increased 10%. According to the analysis, the ratio of recovery from different collection centers ${\eta }_i$ affects the GHG emissions from transport processes, which accounts for a relatively small proportion of total GHG emissions, and the sensitivity to net GHG emissions was comparatively weak.

5.2. Sensitivity Analysis of the Ratio of Processing Strategies

For the purpose of quantifying the influence of the ratio of different processing strategies on GHG emissions, a sensitivity analysis was performed on condition that the ratio of recovery from battery after-sales service enterprise remained at 50%. Figure 4 shows the sensitivity of the ratio of cascade utilization ${\rho }_1$ on total GHG emissions, total GHG savings, and net GHG emissions. As the ratio of cascade utilization ${\rho }_1$ increased, the total GHG savings were advanced, and the total GHG emissions and the net GHG emissions were reduced. When the ratio of cascade utilization ${\rho }_1$ reached 40%, the value of net GHG emissions reached −86.61 kg CO₂-eq/t. These findings suggest that the ratio of different processing strategies significantly affects the total GHG emissions, the total GHG savings, and the net GHG emissions.

5.3. Discussion

As mentioned in Section 5.1, the sensitivity of the ratio of recovery from different collection centers ${\eta }_i$ to net GHG emissions was relatively weak. Hence, the value of ${\eta }_1$ was set at 50% in order to obtain the value of ${\rho }_1$ when it achieves the carbon-neutral target of waste-LIB recycling process. The result shows that when the cascading utilization rate reached 30.88% and the life-cycle of LIB recycling reached the carbon-neutral target. Meanwhile, the values of total GHG emissions and total GHG savings were both 706.45 kg CO₂-eq/t.

The contribution of total GHG emissions for different life-cycle stages is showed in Figure 5. According to these data, nearly 79% of total GHG emissions arise from the recovery utilization process because of the large consumption of fossil energy for metal refining. Figure 6 represents the contribution of different processes to total GHG savings. The results indicate that the GHG savings from battery remanufacturing are considerably higher than those from refining metals.

This research also has a few limitations that can be addressed by considering several directions. Firstly, one recycling technology, pyrometallurgy, is considered in this research. Others such as hydrometallurgical recycling and direct physical recycling could be included in the future research since different recycling technologies cause different GHG emissions and savings in the recovery utilization process. Secondly, this paper mainly analyzes the GHG emissions value of NCM. Other typical batteries, such as LFP and NCA, which account for a substantial part of market, can be analyzed in the future, and the GHG emissions and savings of different types of batteries can be compared. Finally, for the purpose of comprehensively assessing the environmental impact of the waste-LIB recycling process, other environmental pollutants (such as N₂O, CH₄, HFCs, PCFs, and SF₆) could be also considered in the model. These factors may affect GHG emissions and savings in the transportation process, the pre-treatment process, and other processes that involve fuel consumption.

6. Conclusions

After analyzing the research status of the environmental impact of LIB recycling of EVs at home and abroad, this paper constructed an environmental benefit assessment model. It also quantized the life-cycle GHG emissions and GHG savings of the waste-LIB recycling process for calculating the net GHG emissions under the background of a carbon-neutral in China. An estimation was proposed on the basis of a case study. The conclusions are as follows:

(1)

When the life-cycle of LIB recycling reaches the carbon-neutral target, namely the total GHG emissions to the environment reach zero, the values of total GHG emissions and total GHG savings are equal, and the corresponding value calculated in this model was 706.45 kg CO₂-eq/t. The results filled a knowledge gap by assessing the contribution of GHG savings and determined the optimal value of remanufacturing emission, therefore avoiding using virgin materials to produce new LIBs.

(2)

The results of sensitivity analysis indicated that net emissions fell from 9.44 kg CO₂-eq/t to 7.26 kg CO₂-eq/t when the ratio of battery recycling from battery after-sales service enterprises to automobile scrap plants changed from 4:6 to 6:4. Conversely, when the ratio of cascade utilization to recovery utilization changed from 2:8 to 4:6, the net emissions decreased from 103.3 kg CO₂-eq/t to −86.61 kg CO₂-eq/t. The results of this paper provided an effective method to improve resource utilization efficiency, so as to obtain the optimal net GHG emissions value of LIBs recycling.

Overall, the results of this research display that the recycling of LIBs would not only contribute to metal resource savings but would also be beneficial for controlling GHG emissions and achieving a carbon-neutral target. Additionally, we believe that the findings of this research will be meaningful to LIB recycling enterprises for their establishment of recycling schemes under the background of carbon neutrality.