The rapid global expansion of renewable energy sources has created an unprecedented demand for efficient and reliable energy storage solutions. Among these, electrochemical batteries have emerged as a dominant technology, with lithium-ion and lead-acid batteries collectively accounting for over 97% of the market share for stationary energy storage applications. The core function of any energy storage battery is to serve as a medium for energy transfer, storing electricity when supply exceeds demand and releasing it when needed. As the deployment of these energy storage batteries scales up to gigawatt levels, a critical question arises: what are the environmental implications of their widespread use across their entire life cycle? While their role in enabling a cleaner grid is paramount, the production, use, and end-of-life management of these energy storage batteries themselves consume resources and generate emissions.
This investigation aims to provide a comprehensive, comparative environmental profile of five prominent energy storage battery technologies. The analysis focuses on two primary new lithium-ion chemistries: Lithium Iron Phosphate (LFP) and Lithium Nickel Cobalt Manganese Oxide (NCM). Furthermore, it examines the emerging paradigm of giving electric vehicle batteries a second life, evaluating Secondary-Use LFP (SULFP) and Secondary-Use NCM (SUNCM) batteries. Finally, the established technology of Lead-Acid Batteries (LAB) is included as a baseline for comparison. A rigorous Life Cycle Assessment (LCA) methodology is employed to quantify and compare the environmental burdens associated with 1 kWh of energy delivered by each system, from raw material extraction to final disposal or recycling.
1. Methodology and Scope Definition
The foundation of this comparative study is the ISO 14040/44 standards for Life Cycle Assessment. The goal is to establish detailed life cycle inventories for the five energy storage battery types, identify environmental hotspots within their life cycles, and assess the sensitivity of the results to key parameters like allocation methods and operational efficiency.
1.1 Functional Unit and System Boundary
A critical step in any LCA is defining a consistent functional unit that allows for a fair comparison. Many previous studies have used 1 kWh of battery capacity, which fails to account for the performance differences over the battery’s operational life. The true function of an energy storage battery is to deliver energy over time. Therefore, this study defines the functional unit as 1 kilowatt-hour of energy delivered (kWhdelivered) over the battery’s useful life. This approach intrinsically considers both the initial capacity and the cycle life of the battery.
The system boundary encompasses the entire “cradle-to-grave” journey, as illustrated below. For new batteries (LFP, NCM, LAB), this includes:
- Production: Raw material acquisition, component manufacturing (e.g., cathode, anode, electrolyte, casing), and battery pack assembly.
- Use: Operational phase where the battery is charged and discharged, accounting for energy losses due to round-trip efficiency.
- End-of-Life: Collection, recycling (using prevailing metallurgical processes in China), and final disposal of any unrecycled fractions.
For secondary-use batteries (SULFP, SUNCM), the boundary is adapted:
- Reproduction: This stage replaces primary production. It involves the collection and testing of retired electric vehicle batteries, disassembly, replacement of degraded components (like the Battery Management System), and reassembly into a stationary energy storage battery pack.
- Secondary Use: The second-life operational phase in a stationary application.
- End-of-Life: Final recycling after the second life.
Transport between stages and manufacturing infrastructure are excluded due to high variability.
1.2 Life Cycle Inventory and Key Assumptions
Detailed inventory data was compiled for each process stage, drawing from environmental impact reports, scientific literature, and the Ecoinvent 3.8 database. The key operational parameters for each energy storage battery type are summarized in Table 1. These parameters are crucial for calculating the total energy delivered and lost during the use phase.
| Parameter | Unit | LFP | NCM | SULFP | SUNCM | LAB |
|---|---|---|---|---|---|---|
| Initial Capacity | % | 100 | 100 | 80 | 80 | 100 |
| Retirement Capacity | % | 60 | 60 | 60 | 60 | 60 |
| Nominal Capacity (EI) | kWh | 1 | 1 | 1 | 1 | 1 |
| Pack Energy Density | Wh/kg | 145.7 | 204.3 | 120.7 | 166.7 | 40 |
| Depth of Discharge (DoD) | % | 80 | 80 | 80 | 80 | 80 |
| Round-trip Efficiency (α) | % | 90 | 90 | 88 | 88 | 77.5 |
| Cycle Life (n) | cycles | Calculated* | Calculated* | Calculated* | Calculated* | 850 |
*Cycle life for lithium-based batteries is determined by a capacity fade model.
The calculation for the total energy delivered (EOut) and energy lost (ELoss) during the use phase is fundamental. For lithium-ion energy storage batteries, capacity fade is modeled using an empirical equation:
$$ \xi_i = A \cdot e^{(-\frac{E_a}{R \cdot T})} \cdot n_i^z $$
where $\xi_i$ is the relative capacity loss at cycle $i$, $A$ is a constant, $E_a$ is activation energy, $R$ is the gas constant, $T$ is temperature, $n_i$ is the cycle number, and $z$ is the power law factor. Model parameters from literature are applied for LFP and NCM chemistries. The total energy input, output, and loss over the battery’s life (from cycle 1 to final cycle N where capacity reaches 60%) are then calculated as:
$$ E_{In} = \sum_{i=1}^{N} (1 – \xi_i) \cdot E_I \cdot DoD \cdot \alpha^{-1} $$
$$ E_{Out} = \sum_{i=1}^{N} (1 – \xi_i) \cdot E_I \cdot DoD \cdot \alpha $$
$$ E_{Loss} = E_{In} – E_{Out} = \sum_{i=1}^{N} (1 – \xi_i) \cdot E_I \cdot DoD \cdot \frac{1-\alpha^2}{\alpha} $$
For the lead-acid energy storage battery, a linear capacity degradation is assumed, modifying the formula accordingly.
End-of-life scenarios are based on current Chinese practices: hydrometallurgical recycling for lithium-ion batteries (recovering Li, Co, Ni, Mn, FePO₄, etc.) and pyrometallurgical recycling for lead-acid batteries (recovering Pb). Formal collection/recycling rates of 20% for lithium-ion and 90% for lead-acid energy storage batteries are used, with the remainder assumed to be disposed of as waste.
1.3 Impact Assessment and Allocation Methods
The life cycle impact assessment is conducted using the CML-IA baseline method, evaluating eight common environmental impact categories (Table 2). The final result, the Levelized Environmental Impact of Energy (LEIOE) per kWh delivered, is calculated as:
$$ LEIOE = \frac{EI_{Unit}}{E_{Out}} $$
where $EI_{Unit}$ is the total environmental impact of a 1 kWh nominal capacity battery pack over its life cycle, covering production ($EI_{pro}$), use ($EI_{use}$), and end-of-life management.
$$ EI_{Unit} = EI_{pro} + EI_{use} + [ \rho \cdot EI_{rec} + (1-\rho) \cdot EI_{dis} ] $$
Here, $\rho$ is the formal recycling rate, $EI_{rec}$ is the impact of the recycling process, and $EI_{dis}$ is the impact of disposal.
| Impact Category | Abbreviation | Unit |
|---|---|---|
| Abiotic Depletion (elements) | ADP | kg Sb eq |
| Abiotic Depletion (fossil fuels) | ADP-ff | MJ |
| Global Warming Potential (100y) | GWP | kg CO₂ eq |
| Human Toxicity | HT | kg 1,4-DB eq |
| Acidification Potential | AP | kg SO₂ eq |
| Eutrophication Potential | EP | kg PO₄³⁻ eq |
| Ozone Layer Depletion | ODP | kg CFC-11 eq |
| Photochemical Oxidation | PO | kg C₂H₄ eq |
A specific challenge for secondary-use energy storage batteries is allocating the environmental burden between the first (vehicle) and second (storage) life. Four different allocation methods are compared for sensitivity analysis:
- Economic Allocation: Based on the relative market value of the second-life battery (assumed 33% of a new one). This is the baseline method.
- Physical Allocation: Based on the share of total energy delivered in the second life (calculated as 59%).
- 50/50 Allocation: Equal split between the two life cycles, assuming a mature secondary-use market.
- Cut-off Allocation: All production impacts are assigned to the first life; all recycling impacts are assigned to the second life. This method strongly favors the secondary-use energy storage battery.
2. Results and Comparative Analysis
2.1 Environmental Impact Profiles
The life cycle impact assessment results, using economic allocation for secondary-use batteries, are presented in Table 3 and visually compared in Figure 1. The results reveal a clear hierarchy among the five energy storage battery technologies.
| Impact Category | LFP | NCM | SULFP | SUNCM | LAB |
|---|---|---|---|---|---|
| ADP (kg Sb eq) | 4.37E-06 | 1.16E-05 | 4.50E-06 | 1.11E-05 | 3.06E-05 |
| ADP-ff (MJ) | 2.53 | 3.03 | 3.01 | 3.44 | 7.70 |
| GWP (kg CO₂ eq) | 2.78E-01 | 3.16E-01 | 3.33E-01 | 3.69E-01 | 8.21E-01 |
| HT (kg 1,4-DB eq) | 2.37E-01 | 4.48E-01 | 2.24E-01 | 3.87E-01 | 5.35E-01 |
| AP (kg SO₂ eq) | 1.39E-03 | 1.82E-03 | 1.56E-03 | 1.88E-03 | 4.00E-03 |
| EP (kg PO₄³⁻ eq) | 3.21E-04 | 4.25E-04 | 3.79E-04 | 4.80E-04 | 8.88E-04 |
| ODP (kg CFC-11 eq) | 2.50E-09 | 6.80E-09 | 2.90E-09 | 6.11E-09 | 8.04E-09 |
| PO (kg C₂H₄ eq) | 5.38E-05 | 7.21E-05 | 6.09E-05 | 7.50E-05 | 1.56E-04 |
Lithium Iron Phosphate (LFP) demonstrates the most favorable environmental profile, outperforming all other energy storage batteries in seven out of the eight impact categories. Its GWP impact is 2.78E-01 kg CO₂ eq per kWh delivered. The primary reasons are its long cycle life, high round-trip efficiency, and the absence of scarce cobalt and nickel in its chemistry.
Secondary-Use LFP (SULFP) ranks second. It shows a slightly higher GWP than new NCM but outperforms it in most other categories, particularly in ADP and HT, due to avoiding the production of a new cathode. Its impact is lower than new NCM and significantly lower than SUNCM and LAB, highlighting the promise of repurposing this type of energy storage battery.
Nickel Cobalt Manganese (NCM) and Secondary-Use NCM (SUNCM) show mixed results. New NCM has higher ADP, HT, and ODP impacts than SUNCM due to the burden of virgin cobalt and nickel extraction. However, SUNCM has higher GWP, AP, EP, and PO impacts, primarily due to its lower second-life efficiency and reduced total energy delivery.
Lead-Acid Battery (LAB) has the highest environmental impact across almost all categories, with a GWP of 8.21E-01 kg CO₂ eq. This is largely attributable to its low round-trip efficiency (~77.5%) and lower energy density, which result in significantly higher energy losses and material use per kWh delivered over its life cycle. In summary, the environmental impact potential from lowest to highest is: LFP < SULFP < NCM < SUNCM < LAB.
2.2 Contribution Analysis by Life Cycle Stage
Decomposing the total impact reveals the dominant life cycle stages for each energy storage battery type (Figure 2). A consistent pattern emerges:
- Use Phase: This is the single most significant contributor for the majority of impact categories, including GWP, AP, EP, PO, and ADP-ff (fossil fuels). Its contribution ranges from 58% to over 92% for these impacts. This underscores that the carbon intensity of the electricity used to charge and discharge the battery is a paramount factor. The operational losses ($E_{Loss}$), calculated by the formulas above, directly translate into these emissions.
- Production Phase: This stage is the major contributor to abiotic depletion of elements (ADP), human toxicity (HT), and ozone depletion (ODP), accounting for 44% to 235% of the total impact in these categories. For lithium-based energy storage batteries, this is driven by the production of cathode materials (especially for NCM), copper foil, and electronics. For the LAB, lead and copper production are the key drivers.
- End-of-Life Phase: Recycling presents an environmental benefit (negative contribution in the figures) for most impact categories except ADP-ff and GWP. The benefit is more pronounced for LAB due to its high formal recycling rate and mature closed-loop lead recovery. For lithium-ion energy storage batteries, recycling benefits are currently smaller due to lower collection rates and the energy-intensive nature of hydrometallurgical processes, but they are crucial for reducing ADP and HT impacts by recovering valuable metals.
3. Sensitivity and Scenario Analysis
3.1 Influence of Allocation Method on Secondary-Use Batteries
The choice of allocation method profoundly affects the perceived environmental performance of secondary-use energy storage batteries. Compared to the baseline economic allocation:
- Cut-off Allocation drastically reduces the calculated impacts for SULFP and SUNCM, by 6% to 91%, making them appear more favorable than new batteries. This method is often advocated to incentivize circular economy practices.
- 50/50 and Physical Allocation increase the allocated burden for the second life, making secondary-use batteries appear worse than new ones. The 50/50 method may be more appropriate for a mature, established second-life market, while physical allocation based solely on energy delivered may not fully account for the higher quality of service required in the first (vehicle) life.
This analysis highlights that policy and communication regarding the benefits of second-life energy storage batteries must be transparent about the underlying allocation choices.
3.2 Sensitivity to Operational and EoL Parameters
A parametric sensitivity analysis was conducted on three key factors: cycle life (n), round-trip efficiency (α), and formal recycling rate (ρ). The results are striking in their disparity:
- Round-trip Efficiency (α): This is by far the most sensitive parameter. A 5% relative improvement in α (e.g., from 90% to 94.5%) can reduce the GWP impact of an energy storage battery by 18% to 71%, with a sensitivity coefficient exceeding 367%. This is because improving α directly reduces $E_{Loss}$ in the use phase formula and increases $E_{Out}$, thereby diluting the impacts from production and end-of-life. R&D aimed at improving the efficiency of energy storage batteries is therefore one of the most effective levers for reducing environmental footprint.
- Cycle Life (n): Increasing the number of cycles has a moderate positive effect, but with diminishing returns. A 10% increase in cycle life reduces GWP by only about 1-2%. The sensitivity is below 25%. This is because the additional cycles add relatively little to the total energy delivered once the battery is already long-lasting.
- Formal Recycling Rate (ρ): Surprisingly, this has the lowest direct sensitivity on overall GWP (below 5.5%), as it only affects the end-of-life stage, which is a minor contributor to climate change impacts in this model. However, it is critically important for conserving abiotic resources (ADP) and reducing toxicity (HT).
3.3 Future Decarbonization Potential
The environmental impact of an energy storage battery is intrinsically linked to the carbon intensity of the grid electricity it uses. A forward-looking scenario analysis was performed based on projections for China’s power mix in 2025, 2035, and 2050. As the grid decarbonizes, the GWP of all five energy storage battery types decreases substantially (Figure 3).
- Compared to the 2021 baseline, the 2025 grid reduces battery GWP by 31-34%.
- The 2035 grid leads to a reduction of 52-57%.
- The 2050 grid, with a high penetration of renewables, enables a dramatic reduction of 72-79%.
This demonstrates that the clean energy transition has a dual benefit: it not only provides cleaner electricity directly but also dramatically improves the lifecycle performance of the enabling energy storage battery technologies. Furthermore, coupling an energy storage battery directly with a photovoltaic (PV) system can reduce the use-phase GWP to near zero, potentially lowering the total lifecycle GWP of the energy storage battery system by 78% to 92%.
4. Conclusions and Implications
This comprehensive life cycle assessment provides a detailed, comparable environmental profile of five mainstream energy storage battery technologies. The core findings are:
- Performance Hierarchy: Under the defined functional unit of 1 kWh delivered, Lithium Iron Phosphate (LFP) batteries exhibit the lowest environmental impact potential across most categories, followed by second-use LFP, new NCM, second-use NCM, and finally lead-acid batteries. The use phase, governed by the round-trip efficiency and grid carbon intensity, is the dominant contributor to climate change and related impacts for all energy storage battery types.
- Critical Levers for Improvement: The single most effective technological parameter for reducing the carbon footprint of an energy storage battery is its round-trip efficiency. Research and development investments aimed at minimizing energy losses during charge/discharge cycles will yield disproportionately high environmental dividends. In contrast, efforts to marginally increase cycle life or formal recycling rates, while valuable, have a more limited effect on the overall global warming impact per kWh delivered.
- System Context is Key: The environmental benefit of any energy storage battery is magnified when operated with clean electricity. The ongoing global decarbonization of power grids will automatically and significantly reduce the lifecycle impacts of deployed energy storage batteries. The most impactful scenario is the direct integration of energy storage with renewable generation like solar PV, which can nearly eliminate operational emissions.
From a strategic perspective, these results suggest that for sustainable growth in the energy storage sector, priority should be given to the development and deployment of LFP chemistry due to its balanced performance, lower reliance on critical materials, and superior environmental profile. Simultaneously, the industry must focus on innovating to push the boundaries of round-trip efficiency. Policymakers should continue to accelerate the clean energy transition, as this directly amplifies the net environmental benefit of grid-scale and distributed energy storage battery systems. Finally, robust and transparent frameworks for assessing second-life batteries are needed to fairly evaluate their role in a circular economy for energy storage.