Assessing Avoided Burden and Net Environmental Impact by Recycling and Repurposing of Retiring Wind Turbines

Abstract

Wind turbines are reaching end-of-life in increasing volumes, presenting a growing sustainability challenge. In the United States, prevailing waste management practices, primarily landfilling, undermine circular economy objectives by discarding recoverable materials and energy. This study applies life cycle assessment (LCA) to quantify 16 midpoint environmental impacts across three end-of-life pathways—landfilling, recycling, and repurposing—of major turbine components (steel, concrete, and composite blades). An avoided burden approach is used to quantify environmental credits from substituting recovered materials for virgin equivalents. Results show that nearly all recycling and repurposing pathways outperform landfilling across most impact categories. Mechanical recycling of both glass and carbon fiber blades performed better than landfilling in all 16 categories, while pyrolysis and solvolysis improved outcomes in 14–15 of 16 categories (CO₂ eq emissions were higher for pyrolysis and solvolysis than for the landfilling option). Repurposing blades likewise showed broad advantages (15 of 16 categories; ozone depletion was slightly higher), extending material lifetimes before waste treatment. For conventional materials, steel and concrete recycling reduced impacts in most categories, with concrete outperforming landfilling in 15 of 16 categories (marine eutrophication was nearly equal to the landfilling option). The only mixed pathway was cement co-processing of GFRP, which split evenly between benefits and burdens. Sensitivity analysis underscores that improving the quality of recovered materials is critical to maximizing environmental benefits. Overall, both recycling and repurposing offer substantial environmental advantages over landfilling, reinforcing the importance of circular end-of-life strategies in sustaining wind energy across its full life cycle.

1. Introduction

Wind energy offers significantly lower emissions than fossil fuels at the point of electricity generation [1,2]. However, the environmental sustainability of wind energy is increasingly challenged by the growing volume of turbine components reaching the end of their operational lives. With global wind capacity tripling over the past decade [3], the industry faces a mounting need for sustainable end-of-life (EOL) management pathways other than the discarding of retired blades and other components. Without proper recycling or disposal practices, up to 43 million tons of waste from decommissioned turbines could be generated by 2050, with nearly half expected in Europe and the United States [4,5,6].

The Vestas wind turbine serves as a representative model, as it holds the highest market share for onshore wind turbines in the U.S. As with the Vestas, a wind turbine has five major components: foundation, tower, nacelle, generator, and rotor. In terms of material composition, steel accounts for up to 79% of the total mass, primarily found in the tower and nacelle [7,8]. The foundation consists mainly of concrete, reinforced with small amounts of iron and steel. The blades are predominantly composed of glass fiber (GF) and carbon fiber (CF) embedded in unsaturated polyester resin (UPR). While well-established recycling processes exist for steel and concrete, blade recycling processes are less mature. However, recycling blades via mechanical, thermal, and chemical methods or repurposing them into functional products are gaining traction, with increasing interest from startups and industry innovators.

One way to assess the positive and negative environmental impacts of various EOL waste treatment pathways for wind turbine components is through life cycle assessment (LCA), a standardized method for comprehensively evaluating the environmental impacts of products and processes. In the context of wind turbine waste, integrating LCA with robust recycling and material reuse scenarios enables researchers to quantify the burdens associated with each treatment method and the environmental credits gained through avoided emissions, also known as avoided burden. Avoided burden refers to the environmental benefits achieved through co-production, recycling, repurposing, and process optimization. Avoided burden plays a pivotal role in advancing circular economic principles by minimizing waste and maximizing resource efficiency by extending product lifespans and reincorporating materials into productive use. When materials are recovered through recycling or repurposing rather than being landfilled, upstream processes such as mining, ore refinement, and virgin material manufacturing can be partially or wholly avoided [9]. This substitution effect can be compared directly to the environmental impact of using virgin materials. The extent of avoided burden varies depending on both the quality and quantity of recovered materials, as well as the efficiency of the recycling or repurposing process. Each major wind turbine material group requires separate EOL decisions and assumptions. For instance, recycling structural steel avoids the need for extracting and processing iron, nickel, and other alloying elements used in virgin steel production. Recycling composite blades, however, is more complex to characterize. Recycled GF retains approximately 50% to 80% of its original tensile strength, while recycled carbon fiber CF retains about 90% [10,11] under best recycling practices. For mechanical recycling, recycled CF can perform comparably to virgin GF, which has inherently lower strength [12].

These trade-offs can be condensed into a single holistic metric, the net environmental impact of a process [13].

Net Environmental Impact = Environmental Burden of waste treatment option – Avoided Burden Credit of waste treatment option

(1)

where a negative value indicates net environmental savings, suggesting that the EOL strategy contributes to sustainability, while a positive value indicates a net burden and higher environmental load.

When making decisions regarding strategies, factoring the avoided burden offers a practical framework to support the global shift from linear economic models, defined by—a production–consumption–waste trajectory approach, toward circular economic strategies that prioritize long-term environmental and economic value [14]. According to the U.S. Environmental Protection Agency, nearly half of global greenhouse gas emissions are from the extraction and processing of natural resources [15]. Circular strategies like recycling and repurposing not only reduce these emissions but also alleviate pressures on land, water, and ecosystems [16]. For the wind energy sector, landfilling turbine components reflect a linear, high-impact model. In contrast, reusing recovered materials in new wind infrastructure or alternate applications reduces virgin material demand, indirectly lowering upstream emissions and resource use. Conducting a comprehensive study to identify the most environmentally sustainable approach is essential for advancing these efforts.

While numerous LCA studies on wind turbines exist (e.g., [1,17,18,19]), most focus on manufacturing processes or the operational phase. Fewer studies center on EOL recycling or repurposing, and those that do often limit their scope to blade recycling technologies (e.g., [20,21,22]). Even fewer studies consider second-life applications for blades, such as those described by Nagel et al. (2022a) [23], Nagel et al. (2022b) [24], Henao et al. (2024) [25], and Ruane et al. (2023) [26]. In the broader materials context, significant work has been conducted on fiber-reinforced polymer recycling ([12,27,28]), though often within European contexts. Studies like Gennitsaris et al. (2023) [7] offer valuable insights, but their findings are influenced by Europe’s high landfill costs and lack of available space, conditions that differ from those in the U.S. While the United States currently lacks national mandates for circular economy practices, relying instead on limited local- or state-level incentives, several countries in Europe (e.g., Germany, Austria, Finland) have restricted landfilling of decommissioned blades, with industry implementing new processes aimed at supporting circularity. These differences provide an opportunity to examine how policy frameworks may influence the adoption of circular practices. To address this gap, Sproul et al. (2023; 2024) [10,11] conducted region-specific LCAs for wind turbine blade recycling in Texas, focusing nearly entirely on greenhouse gas emissions.

The present study explicitly expands this scope in two ways. First, it applies the ReCiPe 2016 (H) methodology [29] to evaluate net environmental impacts across 16 midpoint categories, rather than focusing solely on CO₂ eq emissions, which is common in how LCA studies are reported. Our multi-impact assessment enables a fuller understanding of burdens and benefits across human health, ecosystem quality, and resource use. Including these other impact pathways here also avoids bias by only showing a few pathways that were chosen at random by the authors. Second, the study incorporates sensitivity analysis to evaluate how material recovery quality and quantity influence the avoided burden, providing insight into how industry can maximize the benefits of innovation, recycling, and repurposing strategies. By combining a multi-material, multi-pathway, and multi-midpoint framework with avoided burden accounting, this work clarifies which EOL strategies deliver the greatest environmental advantage under U.S. conditions. The focus on West Texas is particularly relevant, as the region’s dense wind deployment and imminent retirements make sustainable waste management especially critical. In doing so, the study positions novelty, not in methodological invention, but in the breadth and practical applicability of the analysis, offering guidance for startups, industry practitioners, and policymakers seeking to implement circular solutions. A comprehensive evaluation of these impacts to determine the most environmentally sustainable disposal strategies will be performed by achieving the following three goals:

• To identify EOL disposal options available for wind power technology
• To evaluate these options by LCA, applied credits, and sensitivity analysis
• To analyze the results and provide recommendations

2. Materials and Methods

Assessment of the net environmental impacts (hereafter called NEI) of recycling and repurposing versus landfilling was conducted through LCAs, as well as a sensitivity analysis to evaluate the potential for optimizing avoided burden. The analysis categorizes the wind turbine into three primary material groups based on their predominant composition: structural steel, foundation concrete, and fiber-reinforced polymer blades (comprising both GF and CF). Established industry practices and the literature informed the recycling methods analyzed for each group. For the complex and evolving field of blade recycling, three methods were evaluated for both glass fiber-reinforced polymer (GFRP) and carbon fiber-reinforced polymer (CFRP): mechanical recycling, thermal recycling via pyrolysis, and chemical recycling via solvolysis. Cement co-processing is also considered for GFRP blades. Finally, we assumed that environmental impacts were fully allocated to the process or product being produced (i.e., 100% of the recycled fiber were used in future wind turbine blades, and lubricants produced from recycled resins fully offset virgin lubricants, etc.), creating an easier side-by-side comparison of options.

2.1. LCA Parameters

This study considered 16 midpoint impact categories using ReCiPe 2016 characterization factors [29]. The LCA follows International Organization for Standardization, ISO 14040 and 14044 standards [30,31] and was conducted using OpenLCA (version 2.3) [32]. The LCA process followed several predetermined steps:

• Goal and Scope Definition: The goal was to assess the environmental impacts of recycling and landfilling each material group, and of repurposing blades. The scope was limited to the Permian Basin region of West Texas, USA, incorporating local transportation and energy grid data. The functional unit (FU) was defined as 1000 kg of wind turbine material at its EOL. The system boundary was consistent across all waste management pathways; it began when the turbine reached EOL and ended when the material was either landfilled, recycled, or repurposed. This system boundary includes dismantling, transporting, and treating the waste (Figure S1). Dismantling burdens were applied consistently across material groups, with adjustments for material-specific requirements. For blades, cutting energy was scaled by a ratio of tensile strength and density, resulting in CFRP requiring ~1.8× more energy than GFRP. Structural steel and foundation concrete followed separate dismantling processes. Landfill pathways were modeled with the same general dismantling as recycling, but with lower shredding energy and shorter transport distances. Repurposing scenarios assumed reduced dismantling effort, given that blade integrity was largely preserved. Full energy inventories are provided in the Supplementary Information.
• Life Cycle Inventory (LCI): Data was drawn from Ecoinvent 3.8.1 [33] (cutoff system model), with custom modifications based on the literature and consultations with industry and academia that reflect current best practices in wind blade recycling pathways. Full LCI details are available in the Supplementary Material.
• Life Cycle Impact Assessment (LCIA): Inventory data was mapped to the 16 selected impact categories using the ReCiPe 2016 (H) methodology [29].
• Interpretation: Key contributors to environmental impact were identified by material group and waste pathway. Reliability of data sources and assumptions regarding material quality and recovery rate were also assessed.

2.2. Avoided Burden Credit Assignment

Each waste management process, excluding landfilling, generates secondary materials. These secondary products avoid the production or processing of virgin materials; therefore, credit is assigned based on the avoided environmental impacts of producing comparable virgin materials. This credit is scaled by two factors: the recovered quantity and the quality of the secondary material. The experimental design of the analysis includes the various waste management pathways analyzed per component group, the recovered material, the avoided virgin material, and the percentage of credit applied based on quality of recovered material (Figure 1).

Quality is scaled based on structural equivalence, tensile strength retention, or heating value, depending on the material type. The quantity of recovered material is determined from recovery rates for each recycling method, as documented in the literature (

Table 1. Parameters for quantifying avoided burden credit.

Material	Process	Output	Quantity (%) ±10% †	Avoided Virgin Material	Quality-Basis	Reference
Steel	Recycling	Recycled Steel	87%	Virgin Steel	Structural Equivalence	[34,35]
Concrete	Recycling	Recycled Concrete	60%	Virgin Concrete (<20 MPa)	Structural Equivalence	[36]
Glass Fiber Reinforced Polymer (GFRP)	Mechanical Recycling	Recovered GF	42%	Virgin GF	Tensile Strength	[10,11] and Cement Kiln Mass Balance
		Fine Powder	58%	Construction Mortar	Functional Equivalence
	Pyrolysis	Recovered GF	58%	Virgin GF	Tensile Strength
		Fine Powder	14%	Construction Mortar
		Oil	16%	Lubricant/Light Fuel Oil	Functional Equivalence/Heating Value
		Gas	12%	None Used To Offset Thermal Energy Demand	N/A
	Solvolysis	Recovered GF	61%	Virgin GF	Tensile Strength
	Cement Co-Processing	Clinker	56%	Clinker Raw Materials	Functional and Structural Equivalence
Carbon Fiber Reinforced Polymer (CFRP)	Mechanical Recycling	Recovered CF	24%	Virgin GF	Tensile Strength	[12,37,38,39]
		Fine Powder	19%	Construction Mortar	Functional Equivalence
		Coarse Fraction	57%	No Landfill Waste	N/A
	Pyrolysis	Recovered CF	55%	Virgin CF	Variable Fiber Content
		Oil	28%	Lubricant/Light Fuel Oil	Heating Value
		Gas	1%	Natural Gas	Heating Value
		Char	12%	No Waste	N/A
		Water	3%	No Waste	N/A
	Solvolysis	Recovered CF	55%	Virgin CF	Variable Fiber Content
		Recovered Epoxy Resin	35%	Virgin Epoxy Resin	Functional Equivalence

†—All quantity values are central estimates. A ±10% uncertainty is assumed to reflect process variability.

).

Each process assumes some material loss based on energy or mass balances. The avoided burden varies depending on how the secondary material is used and its equivalency to virgin materials. For instance, pyrolysis oil receives 100% credit if used as a lubricant because it directly substitutes for virgin lubricant. If used as light fuel oil, the avoided burden is scaled by its heating value relative to that of virgin light fuel oil. For GFRP solvolysis, solvent recovery was modeled at 99.5%, consistent with laboratory-scale demonstrations reported in the literature. This was treated as an aspirational best-case condition rather than established industrial practice, with a comparison also made to the limiting case of no solvent recovery (0%) to illustrate potential variability. For recovered CF, the variable fiber content method is applied, adjusting for stiffness and tensile modulus per density of virgin CF. Repurposing credits are treated separately, as the blades are converted into products like transmission poles, pedestrian bridges, and furniture. In these applications, they are assumed to substitute steel due to equivalent structural performance. Because blades often retain over 50% of their original lifespan and are engineered for dynamic loads, they are credited at 100% for structural equivalence in static applications.

Once the secondary materials, their quantities, and qualities were established, the avoided burden was calculated by modeling the environmental impact of producing the equivalent virgin material, scaled using the equation as follows:

Total Avoided Burden = Burden of producing 1 kg virgin material × Recovered quantity × Quality compared to virgin material

(2)

The NEI was then determined by subtracting the avoided burden (represented in green) from the total environmental burden (represented in purple) associated with each waste management pathway (Equation (1)). Positive NEI values represent conditions where emissions from EOL options are larger than the savings associated with reusing the recovered material, and negative NEI values represent emissions savings from recovering and reusing material compared to the production of virgin material. The graphing approach is similar to that used by Sproul et al. (2023; 2024) [10,11], which we saw as efficient.

2.3. Sensitivity Analysis

A sensitivity analysis was conducted to examine how variations in the quantity and quality of recovered fibers affect avoided burden and hence the total environmental credit. The quantity range was defined as from 0 to 70%, reflecting the typical fiber content of wind turbine blades [40], while quality was varied from 0 to 100%, representing full functional equivalence to virgin fiber. For each combination of quantity recovered and quality of the recovered material, we reran OpenLCA to determine the emissions related to each of the 16 ReCiPe midpoint impact categories and then compared the emissions to those of virgin material of the same type. By doing so, we generated nomograms for both GFRP and CFRP materials across the three recycling methods—mechanical, pyrolysis, and solvolysis. These nomograms were then fitted to a second-order polynomial equation, selected for its simplicity and ability to represent smooth data trends:

$$z=a{x}^2+b{y}^2+cxy+dx+ey+f$$

(3)

where

• x represents the quantity of fiber recovered (as % of blade mass)
• y represents the quality of recovered fiber (relative to virgin material)
• z represents the avoided burden (per impact category)
• a–f represents fitted coefficients

To determine which parameter more strongly influences avoided burden, we calculated partial derivatives:

$$\mathrm{Partial} \mathrm{derivative} \mathrm{with} \mathrm{respect} \mathrm{to} \mathrm{quantity}: {\displaystyle \frac{\partial z}{\partial x}}= a^{\prime }x+c^{\prime }y+d^{\prime }$$

(4)

$$\mathrm{Partial} \mathrm{derivative} \mathrm{with} \mathrm{respect} \mathrm{to} \mathrm{quality}: {\displaystyle \frac{\partial z}{\partial x}}=b^{\prime }x+c^{\prime }y+e^{\prime }$$

(5)

The coefficients a′, b′, c′, d′, and e′ define the polynomial fit, where a′ and b′ represent the quadratic effects of quantity and quality, c′ captures their interaction, and d′ and e′ account for the linear contributions. Partial derivatives were computed across the entire parameter grid and then represented on a simple plot that can identify regions where avoided burden for a particular impact category was more sensitive to quantity or more sensitive to quality. To normalize differences in the ranges for quantity (up to 70%) and quality (up to 100%), the partial derivatives were multiplied by their respective ranges for a range-based sensitivity analysis. The results of this analysis can inform where investments in either industrial processes or material choices can yield the highest rate of avoided burdens and hence the most efficient use of capital.

3. Results

This section presents the results of the 16 midpoint environmental impacts associated with various EOL waste treatment methods for wind turbine components, including recycling of structural steel, foundation concrete, and both GFRP and CFRP blades, as well as repurposing of blades. It also emphasizes the environmental influence of secondary applications, examines the implications of different landfill characterization approaches, and concludes with a sensitivity analysis to identify parameters that maximize the avoided burden.

3.1. Net Environmental Impacts (NEI)

Figure 2, Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13, Figure 14, Figure 15, Figure 16 and Figure 17 present the NEI of each waste treatment method, calculated through LCA with avoided burden credits. We generally follow the category order of ReCiPe 2016 Midpoint (H) but focus our discussion on five key impact pathways that capture both local and global effects:

• Fine particulate matter formation (FPMF): reflects human health risks from airborne particles.
• Freshwater ecotoxicity: indicates toxicity to aquatic ecosystems and biodiversity.
• Global warming potential (GWP): quantifies greenhouse gas emissions, linking directly to climate change.
• Land use: measures land occupation and resource pressure.
• Water consumption: highlights impact in water-stressed regions, such as Texas.

For consistency, the tables present results in the same order as the figures rather than the full ReCiPe 2016 sequence [29]. Values shown within each graph correspond to Equation (1), with red numbers indicating a net burden and green numbers a net benefit relative to virgin production.

Figure 2. Fine particulate matter formation (FPMF) (kg PM2.5 eq) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 2. Fine particulate matter formation (FPMF) (kg PM2.5 eq) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 3. Freshwater ecotoxicity (kg 1,4-dichlorobenzene, DCB) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 3. Freshwater ecotoxicity (kg 1,4-dichlorobenzene, DCB) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 4. Global warming potential (GWP) (kg ${\mathrm{C}\mathrm{O}}_2$ eq) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 4. Global warming potential (GWP) (kg ${\mathrm{C}\mathrm{O}}_2$ eq) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 5. Land use (${\mathrm{m}}^2\mathrm{a}$) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 5. Land use (${\mathrm{m}}^2\mathrm{a}$) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 6. Water consumption (${\mathrm{m}}^3$) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 6. Water consumption (${\mathrm{m}}^3$) of recycling and repurposing approaches compared with landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 7. Freshwater eutrophication (kg 1,4-DCB) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 7. Freshwater eutrophication (kg 1,4-DCB) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 8. Human carcinogenic toxicity (kg 1,4-DCB) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 8. Human carcinogenic toxicity (kg 1,4-DCB) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 9. Human non-carcinogenic toxicity (kg 1,4-DCB) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 9. Human non-carcinogenic toxicity (kg 1,4-DCB) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 10. Ionizing radiation (kBq Co-60 eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 10. Ionizing radiation (kBq Co-60 eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 11. Marine ecotoxicity (kg 1,4-DCB eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 11. Marine ecotoxicity (kg 1,4-DCB eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 12. Marine eutrophication (kg N eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 12. Marine eutrophication (kg N eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 13. Ozone formation, human health (kg ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$ eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 13. Ozone formation, human health (kg ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$ eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 14. Ozone formation, terrestrial ecosystems (kg ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$ eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 14. Ozone formation, terrestrial ecosystems (kg ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$ eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 15. Stratospheric ozone depletion (kg CFC11 eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 15. Stratospheric ozone depletion (kg CFC11 eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 16. Terrestrial acidification (kg ${\mathrm{S}\mathrm{O}}_2$ eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 16. Terrestrial acidification (kg ${\mathrm{S}\mathrm{O}}_2$ eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 17. Terrestrial ecotoxicity (kg 1,4-DCB eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

Figure 17. Terrestrial ecotoxicity (kg 1,4-DCB eq) of recycling and repurposing approaches compared to landfilling (characterized as inert waste) of a retired wind turbine per FU (1000 kg of waste).

GFRP Recycling:

• Pyrolysis reduces net FPMF by ~6.9× compared to landfilling (Figure 2), as avoided burden credits outweigh process emissions. Landfilling has the highest FPMF, then mechanical recycling, cement co-processing, solvolysis, and pyrolysis.
• For freshwater ecotoxicity (Figure 3), all recycling pathways outperform landfilling. Cement co-processing achieves ~75% reduction, but only when avoided burden credits are applied, as kiln combustion can release heavy metals and pollutants.
• For GWP (Figure 4), pyrolysis and solvolysis emit 8–10× more CO2 eq than landfilling, even with solvent recovery for solvolysis, due to resin combustion and high energy demand (15,800 MJ for pyrolysis and 21,360 MJ for solvolysis). Cement co-processing leads to net-negative GWP, because blade materials substitute for coal/pet coke, although these credits may decline as cement decarbonizes.
• Mechanical recycling yields the greatest land-use savings (Figure 5), reducing NEI 8.6× compared to landfilling.
• All recycling options except cement co-processing reduce net water consumption (Figure 6).

Across the remaining 11 categories, most recycling methods outperform landfilling (assuming solvent recovery for solvolysis). Cement co-processing performs worse in freshwater eutrophication, human carcinogenic toxicity, ionizing radiation, stratospheric ozone depletion, and terrestrial ecotoxicity (Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13, Figure 14, Figure 15, Figure 16 and Figure 17). For marine eutrophication (Figure 12), results are essentially equal between landfilling and cement co-processing. This result is primarily attributed to emissions from the combustion of blade resin in cement kilns.

Role of Solvent Recovery in Solvolysis:

Solvolysis is favorable across all categories except GWP, but only if solvent recovery ≥ 99.5%. Without recovery, solvolysis impacts exceed those of landfilling across all categories (

Table 2. Net environmental impacts of GFRP blade waste management: solvolysis with solvent recovery, solvolysis without solvent recovery, and landfilling (inert waste). Net environmental impacts (NEI) of recycling are formatted to indicate performance relative to landfilling: values lower than landfilling represent net savings and are shown in bold, while values higher than landfilling represent greater burden and are shown in italics.

Impact Category	Unit	Solvolysis with Solvent Recovery	Solvolysis Without Solvent Recovery	Landfilling
Fine Particulate Matter Formation	kg PM2.5 eq	−1.86	8.26	0.32
Freshwater Ecotoxicity	kg 1,4-DCB	−42.41	126.99	20.10
Global Warming Potential	kg ${\mathrm{C}\mathrm{O}}_2$ eq	1030.20	9165.94	96.11
Land Use	${\mathrm{m}}^2\mathrm{a}$ crop eq	−8.05	22.45	1.59
Water Consumption	${\mathrm{m}}^3$	−5.54	84.20	0.49
Freshwater Eutrophication	kg P eq	−0.20	1.00	0.08
Human Carcinogenic Toxicity	kg 1,4-DCB	−46.91	189.64	8.02
Human Non-Carcinogenic Toxicity	kg 1,4-DCB	−2120.07	1493.78	960.77
Ionizing Radiation	kBq Co-60 eq	−34.57	60.69	11.00
Marine Ecotoxicity	kg 1,4-DCB	−57.83	166.62	28.08
Marine Eutrophication	kg N eq	−0.03	0.04	0.01
Ozone Formation, Human Health	kg NOx eq	−3.19	18.00	0.19
Ozone Formation, Terrestrial Ecosystems	kg NOx eq	−3.18	21.06	0.19
Stratospheric Ozone Depletion	kg CFC11 eq	−1.18 × 10−3	−4.43 × 10−4	4.39 × 10−5
Terrestrial Acidification	kg SO2 eq	−4.53	23.46	0.23
Terrestrial Ecotoxicity	kg 1,4-DCB	−6947.80	11,183.19	378.37

). Solvent use is intensive (~4 kg solvent per kg blade), so failing to recover it dramatically increases burdens (e.g., GWP rises ~7.9× versus landfilling). This underscores the importance of designing inherently circular recycling systems.

CFRP Recycling:

All three CFRP recycling methods yield net savings in 14 of 16 categories (Figure 2, Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13, Figure 14, Figure 15, Figure 16 and Figure 17). Mechanical recycling consistently outperforms landfilling across all categories. Despite higher process burdens, pyrolysis and solvolysis deliver high avoided burden credits because virgin CF production is highly energy-intensive (~29 kg CO₂ eq per kg CF). GWP reductions are ~100× for pyrolysis and ~130× for solvolysis compared to landfilling.

However, pyrolysis performs worse than solvolysis in freshwater eutrophication, ionizing radiation, and non-carcinogenic toxicity, due to added burden of purging the reactor with an inert gas like nitrogen. Still, in the 14 categories where they outperform landfilling, both pyrolysis and solvolysis achieve substantial benefits, retaining ~88–89% of virgin CF quality. The quality advantage explains their higher avoided burden credits relative to mechanical recycling.

Secondary Applications:

The avoided burden credits for pyrolysis depend strongly on secondary product use (

Table 3. Net environmental impacts of pyrolysis of wind turbine blades. Different secondary applications of pyrolysis oil yields different avoided burdens. The net impact is highlighted in bold where greater environmental savings are achieved.

Impact Category	Unit	Net Impact for GF Blade		Net Impact for CF Blade
		Use: Light Fuel Oil	Use: Lubricant	Use: Light Fuel Oil	Use: Lubricant
Fine particulate matter formation	kg PM2.5 eq	−1.88	−2.12	−61.04	−61.65
Freshwater ecotoxicity	kg 1,4-DCB	−39.30	−47.60	−26.85	−43.78
Global warming	kg ${\mathrm{C}\mathrm{O}}_2$ eq	793.20	−651.00	−11,150.22	−11,475.28
Land use	${\mathrm{m}}^2\mathrm{a}$ crop eq	−9.86	−12.13	−24.44	−29.29
Water consumption	${\mathrm{m}}^3$	−5.60	−7.14	−53.87	−56.98
Freshwater eutrophication	kg P eq	−0.18	−0.22	1.56	1.47
Human carcinogenic toxicity	kg 1,4-DCB	−45.13	−54.08	−46.75	−65.91
Human non-carcinogenic toxicity	kg 1,4-DCB	−1,923.65	−2092.67	130.97	−219.07
Ionizing radiation	kBq Co-60 eq	−33.91	−41.67	232.49	214.29
Marine ecotoxicity	kg 1,4-DCB	−53.73	−64.69	−35.40	−57.95
Marine eutrophication	kg N eq	−2.39 × 10−2	−2.71 × 10−2	−2.64	−2.64
Ozone formation, human health	kg NOx eq	−3.31	−4.18	−576.95	−578.86
Ozone formation, terrestrial ecosystems	kg NOx eq	−3.33	−4.55	−577.68	−580.28
Stratospheric ozone depletion	kg CFC11 eq	−1.19 × 10−3	−1.24 × 10−3	−3.25 × 10−3	−3.43 × 10−3
Terrestrial acidification	kg SO2 eq	−4.76	−5.26	−222.41	−223.78
Terrestrial ecotoxicity	kg 1,4-DCB	−6,355.00	−7055.3	−6170.02	−7701.91

). Using pyrolysis oil as lubricant earns full credit (100%), while use as light fuel oil yields only ~47%. Since lubricant production is environmentally intensive, lubricant use maximizes net savings. Figure 2, Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13, Figure 14, Figure 15, Figure 16 and Figure 17 present the conservative case of fuel oil.

Steel Recycling:

Recycling initially incurs higher burdens than landfilling due to energy-intensive dismantling (e.g., plasma/laser cutting, hydraulic shearing). Once avoided burden credits are applied to calculate the NEI, recycling outperforms landfilling in nearly all categories except carcinogenic toxicity, ionizing radiation, marine eutrophication, and water consumption (Figure 2, Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13, Figure 14, Figure 15, Figure 16 and Figure 17). Burdens mainly stem from trace heavy metals during melting, radioactive materials in scrap, and water use for cooling and dust suppression.

Concrete Recycling:

Recycling and landfilling have broadly similar NEI when dismantling burdens are included (Figure 2, Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13, Figure 14, Figure 15, Figure 16 and Figure 17). Removing reinforced concrete foundations requires heavy-duty machinery, such as hydraulic breakers, diamond wire saws, and excavators, which are highly energy-intensive and emit substantial pollutants. However, isolating only the waste treatment phase shows recycling consistently outperforms landfilling except marine eutrophication (Supplementary Material, Table S1). Concrete recycling infrastructure is mature, and secondary uses are diverse (road bases, aggregates, etc.). Landfill disposal is not justified.

Repurposing Blades:

Repurposing (evaluated for GFRP and CFRP) generally outperforms landfilling in all categories except stratospheric ozone depletion. This exception is largely due to emissions from diesel-powered heavy-duty trucks transporting blades to repurposing sites, which release nitrogen oxides (NO_x) that contribute to ozone layer depletion. Because wind turbine blades are engineered to withstand dynamic loads, they can be repurposed for static or quasi-static applications. Benefits arise from displacing virgin steel in secondary applications (e.g., pedestrian bridges, transmission poles, furniture). Repurposing CFRP blades yield greater net benefits than GFRP due to higher landfilling burdens of CFRP. When it is compared to recycling, trade-offs exist: repurposing avoids burdens in some categories, but pyrolysis and solvolysis can achieve much greater savings where virgin CF substitution is credited.

Synthesis of NEI across Impact Categories:

To aid interpretation across the 16 midpoint categories, a synthesis plot (Figure 18) was developed. The plot compares each waste treatment pathway to landfilling, indicating the number of impact categories where performance is better (upper values in dark green) or worse (lower values in pink). It is immediately evident that the upper portion of the graph is more filled than the lower, indicating that most alternative recovery pathways outperform landfilling across all three material groups.

3.2. Blade Characterization in Landfill

In this study, blades were modeled as inert waste, consistent with Meng et al. (2018) [12]. However, classification varies in the literature: some model blades as plastic mixtures [10,11], while others provide little detail on landfill modeling [7] or broadly specify sanitary landfill disposal ([39,41,42]). For incineration, blades are more commonly modeled as municipal solid waste ([7,12,24]). These assumptions strongly influence results. For freshwater ecotoxicity (Figure 19), burdens are 87.5% lower when blades are inert versus plastic, and over 21× lower than when modeled as MSW. Similar variability is observed for GWP, human toxicity, marine ecotoxicity, and marine eutrophication (Supplementary Material, Figures S2–S4). Differences stem from degradability assumptions in the Ecoinvent database: inert waste = 0% degradation (100 years), plastic = 1%, MSW = 18.7%. Environmental burdens rise with degradability.

Notably, toxicity-related impacts appear high in 1,4-dichlorobenzene (DCB) equivalents, not due to actual 1,4-DCB emissions but because highly toxic metals (cadmium, chromium VI, arsenic, lead, mercury, etc., [43]) are scaled to 1,4-DCB, inflating results. Other contributors include persistent or degradable organics including benzene, formaldehyde, dioxins, solvents, and pesticides ([44,45]). For example, 1 kg cadmium = ~1200 kg 1,4-DCB eq [46]. Landfill leachate is the primary emission pathway, with some gas and erosion contributions. Although engineered landfills reduce releases, they remain imperfect over multi-decadal timescales.

3.3. Sensitivity Analysis

A contour plot of avoided burden for each impact category, fitted with a polynomial (Equation (3)), shows a nonlinear relationship between recovery quantity and quality (Figure 20). Across all categories and both materials, fiber quality exerts stronger influence than quantity, except at very low recovery rates. Beyond ~50% recovery, quality becomes the dominant driver.

This pattern is reinforced by partial derivative analysis (Equations (4) and (5)), which shows that avoided burden is consistently more sensitive to fiber quality than to fiber quantity, except under conditions of very low recovery. The relationship holds across all impact categories for both GFRP and CFRP recycling, since the governing equations and fiber-to-matrix ratios are constant; only the color bar values differ by impact category. Once recovery exceeds 50%, fiber quality becomes the decisive factor in determining net outcomes (Figure 21). Given that the total fiber content of blades rarely exceeds ~70%, but fiber quality can approach 100%, optimization efforts should focus on maximizing quality rather than absolute quantity.

Another key strategy for increasing avoided burden is to target secondary applications where (1) virgin production is highly energy-intensive and (2) recycled products can fully substitute virgin equivalents. For instance, deploying pyrolysis oil as a lubricant rather than as light fuel oil yields larger avoided burdens, both due to the high environmental cost of virgin lubricant production and the functional equivalence of the recycled product (Table 3).

4. Discussion

This study offers a comprehensive environmental assessment of EOL management strategies for wind turbine materials, including recycling, repurposing, and landfilling, across 16 ReCipe midpoint Heuristic (H) impact categories. By applying the avoided burden framework, the analysis quantifies environmental trade-offs and highlights opportunities for circularity across structural steel, concrete foundations, and fiber-reinforced polymer blades.

Our findings align broadly with previous LCAs while extending them in scope. In terms of GWP for GFRP, mechanical recycling, pyrolysis, and solvolysis show NEI within ~10% of Sproul et al. (2023; 2024) [10,11], with minor differences attributable to characterization methods (TRACI v2.1 versus ReCiPe Midpoint H). Landfill GWP appears lower in our results because we treat waste as inert; when characterized as plastic waste, values (~201 kg CO₂ eq) closely match Sproul’s 212 kg CO₂ eq (Supplementary Material, Figure S1) [47,48,49]. Repurposing (−715 kg CO₂ eq) is consistent with Henao et al. (2024) [25] (−819 kg CO₂ eq), though slightly less favorable due to methodological differences (TRACI 2.1 versus ReCiPe 2016 Midpoint H). For CFRP, our mechanical recycling (−439 kg CO₂ eq) and landfilling (109 kg CO₂ eq) align with Meng et al. (2018) [12], while pyrolysis and solvolysis yield more conservative avoided burden estimates. This is likely due to differences in system boundaries and feedstock (aerospace composites versus wind turbine blades). For metals and concrete, our results parallel Gennitsaris et al. (2023) [7], who found that metal recycling provides the largest benefits and concrete recycling favorable only under short transport distance. Overall, our findings align with prior LCAs while offering a broader, multi-material, multi-pathway perspective across 16 impact categories. Regional policy frameworks also shape these outcomes. Europe has enacted multiple circular economy initiatives, including the Ecodesign Directive, Extended Producer Responsibility schemes, the Circular Economy Action Plan, and sector-specific regulations such as the End-of-Life Vehicles Directive and Battery Regulation [50]. These policies incentivize reuse, recycling, and remanufacturing, whereas U.S. policies remain more fragmented and largely limited to local or state programs. Such differences likely affect material flows, recycling efficiency, and life cycle emissions, providing context for divergences between U.S.- and European-based LCA results.

Across majority of the categories, recycling and repurposing outperform landfilling because landfilling entails a total loss of recoverable materials and energy. Among GFRP pathways, mechanical recycling is consistently favorable, while pyrolysis and solvolysis, though more resource-intensive upfront, yield substantial avoided burdens when fiber recovery quality is high. Solvolysis demonstrates particularly strong performance under high solvent recovery. Our model assumes 99.5% solvent recovery, as demonstrated in laboratory-scale studies, while industrial practice typically achieves 90–95%. Consequently, solvolysis remains at a moderate readiness level, and further development is needed to ensure circular recovery systems operate near optimal efficiency. For CFRP, pyrolysis and solvolysis both significantly outperform landfilling due to the high environmental cost of virgin CF but require tight process control to minimize burdens. Steel and concrete recycling also yield net benefits, though operational burdens such as energy and water use must be managed, especially in water-stressed regions such as West Texas. Repurposing emerges as a low-impact strategy with high potential, particularly for CFRP blades that retain structural integrity and can displace steel with minimal processing.

Sensitivity analysis confirms that fiber quality is a more decisive driver of avoided burden—and thus ultimately NEI—than recovery quantity, particularly once recovery exceeds 50%. Targeting secondary applications where recycled materials fully substitute virgin production, especially in energy-intensive sectors, maximizes environmental gains.

Future research should prioritize improving fiber quality through advanced separation techniques, reducing water and energy demands of recycling, and piloting repurposing pathways at scale. Additionally, identifying high-value applications where recovered materials can replace energy-intensive virgin production remains critical. A particularly promising frontier lies in the fast-growing artificial intelligence and automation industries. Currently, artificial intelligence and robotics are being applied to improve CFRP recycling processes, demonstrating the potential for automation and efficiency gains. A compelling next step is to use the recovered CFRP itself in automation applications, such as robotic arms, equipment housings, or server enclosures. This will further close the loop and link advanced recycling with high-value, resource- and energy-intensive sectors. Investigating these applications represents a strategic opportunity to further reduce the environmental footprint of both wind turbine EOL materials and emerging technological industries.

Finally, refining landfill characterizations through leachability studies and incorporating regional environmental conditions will help tailor EOL strategies to specific contexts. As wind deployment expands, embedding circularity into the full turbine life cycle will be essential to ensure that renewable energy transitions remain environmentally sustainable not only during operation but also at EOL.

5. Conclusions

As described above, the synthesis plot (Figure 18) provides a clear summary of NEI across all 16 impact categories when circularity is considered. We show that some forms of recycling and repurposing pathways consistently outperform landfilling for every major category of turbine material. For GFRP and CFRP, mechanical recycling achieved improvements in all categories, while pyrolysis and solvolysis performed nearly as well, with only minor trade-offs (e.g., GWP is higher than landfilling for GFRP and freshwater eutrophication and ionizing radiation are higher than landfilling for CFRP). Cement co-processing of GFRP was the only pathway with a mixed outcome, splitting evenly between benefits and burdens compared to the landfilling option. Blade repurposing demonstrated broad advantages by extending material lifetimes before recycling. For conventional materials, steel recycling was beneficial for most categories, except for water consumption (5.0× higher), human carcinogenic toxicity (87× higher), ionizing radiation (1.2× higher), and marine eutrophication (4.6× higher). Concrete recycling, in particular, outperformed landfilling in nearly every category, except for marine eutrophication, but with values in the range of 0.01 and 0.02 kg N eq per 1000 kg of waste.

Overall, landfilling emerges as the least favorable option, underperforming across a greater number of impact categories than any recovery or repurposing alternative. At the same time, the specific trade-offs vary by process and region, meaning that stakeholders must ultimately decide which impact to prioritize. Recovery and repurposing strategies offer robust and broadly distributed environmental gains. Moving forward, these results underscore the environmental advantage of investing in recycling and repurposing infrastructures and policies that maximize material recovery quality, enabling turbine EOL management to shift from waste disposal toward circular resource systems.