Environmental performance assessment of biocomposite production reinforced with plantain pseudostem using life cycle assessment (LCA)

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A life cycle assessment (LCA) was conducted to evaluate the environmental performance of biocomposites reinforced with plantain pseudostem fiber and a polyester resin matrix under a "cradle-to-manufacture" approach. Two scenarios with chemical treatment and two without treatment, each with different fiber content, were analyzed. The environmental impact assessment applied the Intergovernmental Panel on Climate Change (IPCC 2021) method, expressed as the 100-year global warming potential (GWP100) in kg of CO₂, and the ReCiPe Midpoint (H) 2016 method for 16 impact categories, using SimaPro software. The scenario with treatment and an 86% fiber content showed a higher environmental impact according to the IPCC 2021 (GWP100) method, with emissions of 27.6 kg of CO₂ per kilogram of composite material. In the ReCiPe 2016 analysis, the most affected impact categories included terrestrial and marine ecotoxicity, fossil resource scarcity, and human carcinogenic toxicity, primarily due to the chemical treatment involving acetic acid and sodium hydroxide, which significantly increased CO₂ emissions. Conversely, untreated scenarios exhibited significantly lower impacts across multiple categories, positioning them as more sustainable alternatives. Agricultural Waste Circular Economy Environmental Performance Life Cycle Assessment Natural Fiber Biocomposites Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction The increase in population has led to a rapid expansion of agricultural practices, significantly increasing post-harvest waste generation (Duque-Acevedo et al., 2020 ; Koul et al., 2022 ). The most common disposal methods for this waste are open-field burning and dumping (Bracco et al., 2018 ; Sadh et al., 2023 ), which increases greenhouse gases (GHGs) emissions, including CO₂, CH₄, and NOₓ, negatively impacting ecosystem sustainability and human health (Kaza et al., 2018 ; Odubo & Kosoe, 2024 ). According to the Intergovernmental Panel on Climate Change (IPCC), emissions from the combustion of various agricultural waste types amount to 1.52 ± 0.18 kg CO₂/kg of waste, highlighting the need for exploration of alternative valorization strategies (Khosavithitkul et al., 2012 ). In this context, agricultural waste recycling not only offers a viable solution for its disposal but also promotes the circular economy by integrating sustainable practices, such as the production of natural fibers (NFs) (Dungani et al., 2016 ; Mansor et al., 2019 ; Sanjay et al., 2018 ). This approach has enabled the development of biocomposites, reducing dependence on petroleum-derived materials (Mahieu et al., 2013 ; Weligama & Karim, 2022 ). As a result, studies have focused on developing natural fiber-reinforced composites due to their superior mechanical properties, making them suitable for technical applications (Pradhan et al., 2022 ; Shinoj et al., 2010 ). The use of biocomposites has grown across various industries, particularly in the automotive sector, where they have been utilized for years due to their excellent insulation properties (Ita-Nagy et al., 2020 ; Sassoni et al., 2014 ). NFs exhibit mechanical properties comparable to their synthetic counterparts and can be obtained from agricultural waste such as plantain, coconut, bamboo, and hemp (Sanjay et al., 2019 ). Their increased use and production are driven by environmental concerns regarding the Earth's limited resources, as well as their wide availability and low carbon emissions (De et al., 2023 ). They offer a high strength-to-weight ratio, making them suitable for manufacturing materials or tools (Elfaleh et al., 2023 ). Among the various sources of natural fibers derived from agricultural waste, plantain cultivation stands out due to its high potential and significant role in the global economy and food supply (Lau et al., 2020 ). By-products such as leaves, pseudostem, and inflorescence are often burned in situ or discarded, generating large amounts of residual biomass and causing negative environmental impacts (Mago et al., 2021 ; Reyes et al., 2021 ). For every ton of harvested plantain, four tons of waste are generated, primarily pseudostem (three tons) (de Oliveira et al., 2018 ). Pseudostem fibers are notable for their high tensile strength, excellent moisture absorption, and biodegradability, making them ideal for composite applications (Komal et al., 2020 ; Patel & Patel, 2022 ; Venkateshwaran & Elayaperumal, 2010 ). To evaluate the efficiency of these materials, life cycle assessment (LCA) (ISO 14040, 2006a; ISO 14044 2006b) is used for the environmental assessment of products and services, from raw material acquisition, through the production and use stages, to waste treatment, including disposal and recycling (Laca et al., 2019 ; Ramanujan et al., 2017 ). LCA studies comparing natural fibers with conventional materials have proven to be an objective approach that highlights their environmental benefits (Xue, 2019 ). The evaluation of environmental performance is of great importance, as in some cases, the use of natural fibers does not guarantee an environmentally friendly product due to the high consumption of water, soil, and chemicals throughout its life cycle (Mansor et al., 2015 ). The objective of this study is to evaluate the environmental impacts associated with the production of biocomposites with a polyester resin matrix reinforced with plantain pseudostem fiber, using life cycle assessment (LCA) under a cradle-to-manufacture approach. Additionally, different agricultural waste utilization scenarios are compared using SimaPro software (version 9.6.0.1), which provides scientific data for analyzing, monitoring, and measuring the environmental impact of products and services throughout their entire life cycle (Fernández-López et al., 2024 ; Mares et al., 2018 ; Zalazar-Garcia et al., 2022 ). 2. Materials and Methods To evaluate the environmental impacts associated with the production of biocomposites reinforced with plantain pseudostem fiber, the life cycle assessment (LCA) methodology was applied following the guidelines established by the International Organization for Standardization (ISO) (ISO 14040, 2006a; ISO 14044 2006b). Figure 1 presents the four life cycle stages and sub-stages as defined by the ISO standard, which were applied in this study and are described below: 2.1 Definition of objectives and scope This stage aims to evaluate the environmental performance of biocomposite production reinforced with plantain pseudostem fiber by establishing different sensitivity scenarios to identify the most environmentally efficient alternative. 2.1.1 Definition of the Functional Unit (FU) The functional unit (FU) defines the quantification of a product, process, or service by providing a reference to which the inputs and outputs of a system are related (ISO, 2006a ). In this study, the FU is 1 kg of biomaterial reinforced with plantain pseudostem fiber. The mass unit (kg) is used because the product is not intended for a specific application (Schultz & Suresh, 2018 ). 2.1.2 System Boundaries A cradle-to-manufacture approach is adopted, covering the process from the extraction of treated fibers (CF) or raw fibers (RF) to the production of biocomposites reinforced with plantain pseudostem fiber (PNT) using the Vacuum-Assisted Resin Transfer Molding (VARTM) process (Fig. 2 ). The extraction process was established as the starting point, or “cradle,” since the LCA scope does not include the environmental burdens associated with agricultural cultivation (such as fertilizer or water use), aligning with methodologies applied in other studies (Desole et al., 2024 ; Yadav et al., 2024 ). In this study, plantain pseudostems, considered agricultural waste, are treated as environmental burden-free resources, as they are not intentionally produced but are a natural byproduct of plantain cultivation, whose primary purpose is fruit production (Cherubini & Ulgiati, 2010 ; Rodríguez et al., 2020 ). 2.1.3 sensitivity scenarios The sensitivity scenarios consider factors that may influence the environmental performance of biocomposite production (Table 1 ). First, the chemical treatment (mercerization) and coating (flexible epoxy resin) applied to plantain pseudostem fibers. Second, the resulting biocomposite may have different fiber and polyester matrix compositions (Altamiranda, 2024 ). The use of different mixtures and chemical treatment with coating allows for the identification of the alternative with the highest environmental performance (Liu et al., 2024 ). Table 1 Sensitivity scenarios for the production of plantain pseudostem fiber-reinforced biocomposites with a polyester matrix using the VARTM process. Scenarios Reinforcement % Polyester resin (%) Treatment/coating Label* 1 86% 14% YES CF-PNT/86 2 85% 15% NOT RF-PNT/85 3 48% 52% YES CF-PNT/48 4 46% 54% NOT RF-PNT/46 Note: *CF: Chemically treated/coated fiber *RF: Raw fiber *PNT: Plantain pseudostem fiber 2.2 Life Cycle Inventory (LCI) and Data Quality This study developed specific life cycle inventories (LCIs) for the fiber extraction and biocomposite production stages, integrating both primary and secondary data. Data collection included on-site sampling, small-scale experiments described in this section, information from the Ecoinvent 3.10 database processed using SimaPro 9.6.0.1 software (Moreno-Ruiz et al., 2023 ; Wernet et al., 2016 ), as well as technical and scientific literature. Additionally, proprietary calculations were performed to quantify system inputs and outputs, including mass and energy balances of unit processes. 2.2.1 Raw material collection The raw material was sourced fron the municipality of Puerto Escondido, located in northern Colombia. This region covers an area of 426.2 km², has an altitude of 30 meters above sea level, and an average temperature of 28°C (Alcaldía Municipal de Puerto Escondido, 2001 ). According to 2022 data, the municipality reported 2,072 hectares of plantain cultivation (Agronet, 2022 ). Pseudostems from post-harvest waste of the Hartón plantain ( Musa paradisiaca spp ) were obtained from La Bendición farm. 2.2.2 Production of Plantain Pseudostem Fiber The manual cleaning and cutting of the pseudostem sheaths were carried out on-site using a semi-mechanical method, which involves a comb with metal bristles for manual decortication. This process helps reduce water content and remove waste (Mumthas et al., 2019 ). The extracted fibers were washed in hot water at 100°C to eliminate excess cellulosic material. Subsequently, for scenarios 1 and 3, a chemical treatment and epoxy resin coating (Mercerization) were applied using 5% NaOH and 50% CH3COOH solutions, both dissolved in distilled water (Altamiranda, 2024 ). The CF-PNT and RF-PNT fibers were then dried in a BPG-9070A oven (220V, 1100W) at 45°C for two and a half hours. 2.2.3 Production of Biocomposite Using VARTM The CF-PNT and RF-PNT fibers proceed to the biocomposite production phase using the Vacuum-Assisted Resin Transfer Molding (VARTM) process. This is an open-mold composite manufacturing method that operates at atmospheric pressure and room temperature (Tamakuwala, 2021 ). Following the procedure described by Pico et al. ( 2023 ), a release wax was applied to prevent adhesion to the mold. The pre-mixed polyester resin was then injected onto the chemically treated and coated fibers or raw fibers by applying pressure inside a closed vessel, ultimately forming the biocomposite. 2.2.4 Data Quality Analysis The life cycle inventory (LCI) data were evaluated using the International Reference Life Cycle Data System (ILCD) method (Balcioglu et al., 2024 ; Wolf et al., 2010 ) For this analysis, the Pedigree matrix was defined, which assesses six quality parameters: Technological representativeness (Ter), Geographical representativeness (GR), Temporal representativeness (Tir), Completeness (C), Parameter uncertainty (P) (i.e., the accuracy of inventory data concerning direct measurements), and Methodological adequacy and consistency (M). Each parameter is assigned a value ranging from 1 (Very high quality) to 5 (Low quality) (Chen & Lee, 2021 ; Füchsl et al., 2022 ). Eq. 1 presents the Data Quality Rating (DQR) formula, which calculates the average of these indicators and determines the overall quality level of the LCI data. $$\:DQR=\frac{TeR+GR+TiR+C+P+M+{X}_{W}*4}{i+4}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(1\right)$$ Where X W represents the lowest quality level obtained, meaning the highest numerical value among the data quality indicators, and indicates the number of applicable data indicators. Table 2 shows how these values relate to the final quality level of the obtained data (Godoy León & Dewulf, 2020 ). Table 2 Data Quality Indicator and Quality Level. Data quality indicator Data quality level 1.0–1.6 Very high quality 1.7–2.4 High quality 2.5–3.2 Satisfactory quality 3.3–4.0 Low quality 2.3 Life Cycle Impact Assessment (LCIA) LCIA was used to analyze the relevance of potential impacts throughout the entire life cycle (Suppen-Reynaga et al., 2024 ). The LCI results were transformed into a limited number of environmental impact scores using characterization factors (Hauschild & Huijbregts, 2015 ). The method of the Intergovernmental Panel on Climate Change (IPCC 2021) and the ReCiPe Midpoint (H) method (hierarchical version) were employed. 2.3.1 IPCC 2021 Method The IPCC 2021 method uses emission metrics for the Global Warming Potential (GWP100), which quantifies the increase in integrated infrared radiative forcing of a greenhouse gas (GHG) relative to CO₂ over a 100-year period, expressed in kg CO₂-eq (Lynch et al., 2020 ). 2.3.2 The ReCiPe 2016 Midpoint (H) Assessment method encompasses all potential impacts generated by various processes, representing them through impact categories expressed with midpoint indicators (Dekker et al., 2020 ; Hauschild et al., 2013 ; Kiss & Boskovic, 2013 ). This method employs a cause-effect approach, enhancing the understanding of environmental effects and highlighting opportunities for improvement (Mezzanotte et al., 2025 ). In this study, only 16 impact categories were considered (Huijbregts et al., 2017 ): (1) Ozone depletion (ODP), (2) Ionizing radiation (IRP), (3) Fine particulate matter formation (PMFP), (4) Photochemical oxidant formation in terrestrial ecosystems (EOFP), (5) Photochemical oxidant formation affecting human health (HOFP), (6) Terrestrial acidification (TAP), (7) Freshwater eutrophication (FEP), (8) Marine eutrophication (MEP), (9) Human carcinogenic toxicity (HTPc), (10) Human non-carcinogenic toxicity (HTPnc), (11) Terrestrial ecotoxicity (TETP), (12) Freshwater ecotoxicity (FETP), (13) Marine ecotoxicity (METP), (14) Water consumption (WCP), (15) Mineral resource scarcity (SOP), and (16) Fossil resource scarcity (FFP). For category interpretation, normalization was conducted using software. 2.4 Life Cycle Interpretation This stage involved reviewing the results of the inventory analysis and impact assessment to validate their consistency with the study's objective and scope. The unit processes that represented the highest environmental burdens within the life cycle were identified, allowing for a comparison between scenarios to determine which of the proposed options resulted in the least environmental impact (Laurent et al., 2020 ). 3. Results 3.1 Life Cycle Inventory (LCI) The results of the life cycle inventory (LCI) compiled material and energy consumption, as well as waste generation and emissions (inputs and outputs) associated with each stage of the life cycle for plantain pseudostem fiber extraction and the production of fiber-reinforced biomaterial using the VARTM process (see Table 3 and Table 4 ). Activities and processes from the Ecoinvent 3.10 database were used to model the flows in the SimaPro software (Wernet et al., 2016 ). Table 3 Life cycle inventory (LCI) for the extraction of plantain pseudostem fiber. EXTRACTION OF RAW MATERIALS CF-PNT/86 RF-PNT/85 CF-PNT/48 RF-PNT/46 INPUTS Unit Amount Pseudostem plantain {CO*}| Recycled Content cut-off kg 57,793 96,392 32,257 52,165 Tap water {CO}| market for tap water | Cut-off, S kg 15,762 26,289 8,797 14,227 Water, deionised {RoW*}| market for water, deionised | Cut-off, S kg 10,954 6,114 Sodium hydroxide, without water, in 50% solution state {RoW}| market for sodium hydroxide, without water, in 50% solution state | Cut-off, S kg 1,206 0,673 Acetic acid, without water, in 98% solution state {GLO*}| market for acetic acid, without water, in 98% solution state | Cut-off, S kg 4,220 2,355 Epoxy resin {GLO}| market for epoxy resin | Cut-off, S kg 0,175 0,098 Monoethanolamine {GLO}| market for monoethanolamine | Cut-off, S kg 0,175 0,098 ELECTRICAL CONSUMPTION Electricity, low voltage {CO}| market for electricity, low voltage | Cut-off, S kWh 17,075 28,479 9,530 15,412 OUTPUTS Dry fiber kg 0,850 0,460 Coated fiber kg 0,860 0,480 Waste Pseudostem untreated {GLO}| Treatment of waste Pseudostem, untreated, open dump, wet infiltration class (500mm) | Cut-off, S kg 45,709 76,237 25,512 41,258 Emissions to air Water/m3, CO kg 12,457 20,619 6,953 11,159 Emissions to water Wastewater, average {RoW}| treatment of wastewater, average, wastewater treatment | Cut-off, S kg 31,259 24,974 17,447 13,515 Note: * These are 2-letter country codes or 3-letter region codes, indicating the geography represented by the dataset: Colombia (CO), Global (GLO), and Rest of the World (RoW). The LCI results (Table 4 ) for biomaterial production in the four scenarios proposed in this study are shown below. Table 4 Life cycle inventory (LCI) for the production of biomaterial with plantain pseudostem reinforcement using VARTM. BIOMATERIAL PRODUCTION CF-PNT/86 RF-PNT/85 CF-PNT/48 RF-PNT/46 INPUTS Unit Amount Petroleum slack wax {CO*}| petroleum slack wax production, petroleum refinery operation | Cut-off, S kg 0,0035 0,0035 0,0035 0,0035 Orthophthalic acid based unsaturated polyester resin {GLO*}| market for orthophthalic acid based unsaturated polyester resin | Cut-off, S kg 0,140 0,150 0,520 0,540 ELECTRICAL CONSUMPTION Electricity, low voltage {CO}| market for electricity, low voltage | Cut-off, S kWh 0,007 0,007 0,007 0,007 OUTPUTS Biocomposite kg 1 1 1 1 Note: * These are 2-letter country codes or 3-letter region codes, indicating the geography represented by the dataset: Colombia (CO), Global (GLO). 3.1.1 Data Quality Assessment The quality indicators (M, C, TiR, GR, TeR, and P) reflect various results in the pedigree matrix (see Table 5 ) for the LCIs, and their application can be observed in the results presented in the annexes. The methodological consistency (M) and temporal representativeness (TiR) indicators predominantly show values of 1, ensuring compliance with established requirements, high methodological consistency, and data relevance for the studied period. Completeness (C) values range between 1 and 2, indicating adequate coverage for most of the analyzed flows. However, a specific process reaches a value of 5, indicating limited representativeness in this particular case. This is because steam quality was estimated through a mass balance rather than being directly measured with specialized equipment. Geographical representativeness (GR), on the other hand, presents values between 1 and 3, representing a high coverage of the study area. Technological representativeness (TeR) values range between 1 and 4, indicating that some processes align directly with the technology used, while others show a lower degree of similarity. Finally, parameter uncertainty (P) ranges between 2 and 3, indicating an overall acceptable level of accuracy. 3.2 Environmental impact assessment for each of the scenarios 3.2.1 IPCC 2021 Method In terms of global warming potential (GWP100, including CO₂ capture), the results (Table 6 ) indicate that treatment and a higher natural fiber content tend to increase carbon dioxide equivalent emissions. Conversely, scenarios without treatment and with a lower percentage of plantain pseudostem fiber exhibit lower value in this impact category. Table 6 Impact assessment results for each scenario using the IPCC 2021 method. Impact category Unit CF-PNT/86 RF-PNT/85 CF-PNT/48 RF-PNT/46 GWP100 incl. CO2 ptake Kg CO2-eq 27,7 17,2 17,4 11,3 In the CF-PNT/86 and CF-PNT/48 scenarios, the magnitude of the impact is mainly attributed to the chemical treatment (Fig. 3 ), as this process significantly increases CO₂ emissions, accounting for 56.7% of the total emissions in this category (50.2% from acetic acid and 6.5% from sodium hydroxide). In scenarios without chemical treatment (RF-PNT/85 and RF-PNT/46), the increase is associated with electricity consumption and the treatment of plantain pseudostem waste. 3.2.1. ReCiPe Midpoint (H) Method The categories with the highest results were analyzed. The impact categories evaluated in the CF-PNT/86 and CF-PNT/48 scenarios show higher values in terrestrial ecotoxicity (TETP) and marine ecotoxicity (METP), fossil resource scarcity (FFP), and human carcinogenic toxicity (HTPc) indicators compared to the scenarios without chemical fiber treatment (RF-PNT/85 and RF-PNT/46) (Fig. 4 ). Figure 5 A to 5 D illustrate the influence of different processes on the TETP, METP, FFP, and HTPc impact categories. In the CF-PNT/86 and CF-PNT/48 scenarios, the highest environmental impact contribution is associated with the use of chemicals such as acetic acid and sodium hydroxide, particularly in the terrestrial ecotoxicity (TETP) category. Similarly, in the marine ecotoxicity (METP), fossil resource scarcity (FFP), and human carcinogenic toxicity (HTPc) categories, chemical treatment processes and the use of the polymeric matrix contribute the most to impact magnitude. Electricity and other remaining processes have a smaller share compared to these substances. 4. Discussion The data quality results (DQR) indicate that most values exhibit high quality (1.7–2.4) or satisfactory quality (2.5–3.3) (see Table 5 ). These results align with those reported by Desole et al. ( 2024 ) in their LCA study, which evaluated alternatives for replacing fossil-based and non-renewable materials. In that study, the application of the DQR methodology yielded excellent quality values ranging from 2.1 to 2.4 and a satisfactory quality of 2.6. Conversely, the output associated with evaporation (air emissions) in our study reflects low quality (> 3.3), reaching a value of 3.5. This is attributed to the quality indicators C, TeR, and P, which obtained values of 5, 4, and 3, respectively, directly influencing the final DQR score. This result is likely due to the reliance on mass balance as a methodological approach and the lack of direct measurements. The results obtained using the IPCC 2021 GWP100 environmental impact assessment methodology indicated that the CF-PNT/86 scenario generated the highest level of pollution, primarily due to the chemical treatment process (Fig. 3 ). This is due to acetic acid production being an energy-intensive industrial process, leading to increased CO₂ emissions (Bordón et al., 2022 ). Similarly, the alkaline treatment of natural fibers with sodium hydroxide (NaOH) imposes a significant environmental burden, as its production via electrolysis also requires substantial energy input (Kim et al., 2008 ). During post-treatment, wastewater is generated as fibers are removed from the solutions, raising concerns regarding both wastewater treatment and disposal (Van Dam & Bos, 2004 ). Related studies, such as that conducted by Alcivar-Bastidas et al. ( 2024 ), which assessed the environmental impact of alkaline treatment on natural abaca fibers while reusing the NaOH solution, found that conventional chemical treatment considerably increased the environmental footprint compared to untreated fibers. Specifically, the carbon footprint of conventional alkaline treatment was 1.48 kg CO₂ eq/kg of fiber—three times higher than that of untreated fibers, which exhibited a footprint of 0.47 kg CO₂ eq/kg of fiber. Consequently, several authors suggest that reusing the alkaline solution could significantly enhance the circular economy strategy for waste utilization (Alcivar-Bastidas et al., 2024 ; Ita-Nagy et al., 2020 ; Juradin et al., 2023 ; Nguyen et al., 2019 ; Tran et al., 2020 ). Furthermore, Anastasiou ( 2024 ) found that epoxy resin composites reinforced with chemically treated Luffa cylindrica fibers exhibited greater environmental impacts than those reinforced with untreated fibers, primarily due to the use of chemicals in the treatment process. Regarding electricity consumption across scenarios, the findings indicate that, within the extraction processes, electricity accounts for 18% of global warming in the CF-PNT/86 scenario—a lower proportion compared to the 49.4% recorded in RF-PNT/85. This disparity arises because, in the absence of chemical treatment and coating, a larger amount of fiber requires drying, as the coating increases the total fiber weight by approximately 50%. A similar trend is observed in the CF-PNT/48 and RF-PNT/46 scenarios, where electricity consumption contributes 16.3% and 40.5% to global warming, respectively. In the RF-PNT/85 scenario, which contains a similar amount of pseudostem but without chemical treatment, emissions were mainly associated with electricity consumption and the treatment of plantain pseudostem waste, accounting for 49.4% (energy consumption) and 46.6% (treatment) of the total environmental burden. Nevertheless, this scenario demonstrated better environmental performance compared to CF-PNT/86. In the CF-PNT/48 scenario, where chemical treatment was maintained but the amount of replacement fiber was reduced, an increase in CO₂ emissions was observed due to the polymeric matrix manufacturing process. This is attributed to the higher proportion of polymeric matrix used in the mixture, explaining why the most environmentally viable scenario was RF-PNT/46. By reducing the amount of processed fiber, energy consumption decreases, and chemical treatment is avoided, resulting in a lower carbon footprint.Similar results were reported by Yadav et al. ( 2024 ), where the manufacturing of chemically treated plantain fiber composites coated with copper showed that electricity accounted for approximately 73% to 74% of global warming emissions, significantly higher than raw composites, which accounted for around 64%. Likewise, Bordón et al. ( 2022 ) determined that untreated plantain fibers generate a lower environmental impact, as they do not require energy-intensive chemical processes, contributing to a significant reduction in global CO₂ emissions. Furthermore, Paul et al. ( 2024 ) stated that untreated fibers can achieve similar mechanical properties without the environmental costs associated with chemical treatments, findings also reported by Altamiranda ( 2024 ), a researcher and producer of the fibers supplied for this study. Applying the ReCiPe 2016 methodology, the results for the TETP indicator in the CF-PNT/86 and CF-PNT/48 scenarios are primarily attributed to the use of chemicals (Fig. 5 A). According to George & Bressler ( 2017 ), the production chains of these compounds generate potentially harmful emissions. Additionally, the polymer matrix had a significant impact in scenarios with lower fiber replacement ratios (CF-PNT/48 and RF-PNT/46), mainly due to emissions from its manufacturing process. The substances contributing to this impact category are shown in Fig. 6 A, where cobalt (II) emissions are predominant, mainly originating from the production of acetic acid and the polymeric matrix. These findings align with the trend observed in Fig. 5 A, reinforcing that the combination of chemical treatment and synthetic polymer use considerably increases terrestrial ecotoxicity. The relationship between acetic acid and cobalt (II) compounds (Fig. 6 B), such as cobalt acetate, stems from their presence as emissions within the product’s life cycle, primarily due to their role in acetic acid oxidation processes, where cobalt (II) compounds function as catalysts in the production of aromatic acids (Partenheimer, 2011 ). Upon reaching the soil, cobalt (II) compounds exhibit toxic properties, which can disrupt microbial communities and enzymatic activities, ultimately affecting soil health and plant growth (Kosiorek, 2019 ). Additionally, according to data from Ecoinvent ( 2023 ), acetic acid production has a significant environmental impact, mainly due to the use of liquefied petroleum gas (LPG) as an energy source. This process generates pollutant emissions that increase the toxic load in both marine and terrestrial ecosystems (Deshmukh et al., 2020 ; Suresh et al., 2023 ). Figure 5 B illustrates a clear trend in the marine ecotoxicity (METP) category: as polymeric matrix consumption increases, so does its environmental impact. In this context, the CF-PNT/48 scenario exhibits the best environmental performance, as it maintains a high fiber replacement percentage without the additional environmental burden associated with acetic acid or the increased use of the polymeric matrix, followed by the RF-PNT/46 scenario. Regarding emitted substances, anthracene is the primary contributor, accounting for 42%, 45%, 40%, and 42% across the evaluated scenarios, followed by cobalt (II) (previously discussed) and, to a lesser extent, copper ions (Fig. 7 A). Anthracene, primarily emitted during the manufacturing processes of acetic acid and the polymeric matrix (Fig. 7 B), can volatilize into the atmosphere due to industrial activities or vehicle emissions and subsequently be deposited in marine ecosystems through precipitation or atmospheric sedimentation (Pathak et al., 2020 ; Ravindra et al., 2008 ). Studies have shown that polycyclic aromatic hydrocarbons (PAHs), including anthracene, are frequently detected in coastal waters, highlighting a direct connection between atmospheric and marine pollution (Karthikeyan et al., 2024 ). Its increasing prevalence in these ecosystems poses a significant risk to biodiversity. Furthermore, its potential for photoinduced toxicity suggests that current assessments may underestimate the risks associated with this compound and similar contaminants in marine environments (Gomes et al., 2009 ; Oris et al., 1984 ) The results for the fossil resource scarcity (FFP) category are attributed to the use of nonrenewable fossil resources, such as liquefied petroleum gas (LPG) and coal, as energy inputs in processes related to chemical treatment, particularly in the production of acetic acid, sodium hydroxide, and the polymer matrix derived from crude oil. Due to their finite nature, these substances have a significant impact on fossil resource scarcity, as their extraction and consumption contribute to the depletion of limited reserves (Clasen et al., 2024 ). Among the evaluated scenarios, RF-PNT/85 exhibited the best performance in this category, primarily due to the omission of chemical treatment and the reduction in polymer matrix usage (Fig. 5 C). Additionally, the human carcinogenic toxicity (HTPc) category was among the most significant in the environmental impact assessment (Fig. 4 ). Processes associated with chemical treatment, particularly the production of acetic acid and sodium hydroxide, along with electricity consumption, were the main contributors to this impact (Fig. 5 D). This is attributed to the emission of hazardous substances, such as chromium (VI) into the air and water, dioxin 2,3,7,8-tetrachlorodibenzo-p-, as well as arsenic and nickel (II) ions (Fig. 8 ). Chromium (VI) emissions are linked to the life cycle of acetic acid (Fig. 9 A), as its production involves high-carbon ferrochromium, according to industrial manufacturing inventories. This represents a secondary impact derived from the evaluated processes. Similarly, 2,3,7,8-Tetrachlorodibenzo-p-dioxin is generated to a lesser extent during polymer matrix production, mainly due to the use of sodium hydroxide, which serves to neutralize residual acids, stabilize the final product, or facilitate other laboratory procedures (Radenkov et al., 2016 ). Furthermore, this compound is primarily emitted during sodium hydroxide production via chlor-alkali electrolysis, a key industrial process for chlorine and NaOH synthesis (Fig. 9 B) (Ecoinvent, 2025 ). Finally, nickel (II) (Fig. 9 C) and arsenic (Fig. 9 D) emissions are mainly attributed to electricity consumption, particularly from Colombia’s energy mix, according to Ecoinvent. These emissions likely result from power generation using nonrenewable sources such as coal and oil, which release arsenic and other pollutants into the environment. 5. Conclusions The production of biomaterials from plantain pseudostem fiber has significant environmental impacts, primarily due to chemical treatment. This process accounts for 56.7% and 50.3% of the greenhouse gas emissions contributing to global warming potential (GWP) in the CF-PNT/86 and CF-PNT/48 scenarios, respectively, as a result of the high energy demand of industrial processes. Although increasing the amount of untreated pseudostem required raises the GWP due to the higher energy demand for drying, its overall impact remains lower than that associated with chemical treatment. Chemical treatment notably impacts multiple environmental categories. First, it increases terrestrial and marine ecotoxicity due to hazardous emissions generated along the production chains of the chemical compounds used. Although these emissions are not directly linked to the fiber extraction processes evaluated, they should be considered relevant secondary impacts. Additionally, the fossil resource scarcity indicator presents higher values in scenarios involving chemical treatment. This results from the consumption of nonrenewable resources such as liquefied petroleum gas (LPG) and coal, which play a crucial role in the production of acetic acid, sodium hydroxide, and crude oil derivatives used in the polymer matrix. The exploitation of these resources significantly contributes to the depletion of finite reserves. Finally, the human carcinogenic toxicity category shows a marked increase, primarily driven by secondary emissions from substances associated with the chemical life cycle. Overall, the global assessment demonstrates that untreated fibers achieve better environmental performance than chemically treated fibers, highlighting the sustainability benefits of avoiding chemical treatments. Therefore, prioritizing this scenario is recommended, as it enables the attainment of comparable mechanical properties without incurring the environmental costs associated with chemical processing. However, further research on fiber processing and treatment is necessary, considering that biocomposites may help reduce landfill disposal or mitigate degradation rates if released into the environment, as currently observed. This potential environmental benefit should be integrated into future assessments to achieve a more comprehensive evaluation. Declarations Acknowledgments The authors wish to the Fondo Nacional de Regalias of Colombia for the financial support provided through the project "Strengthening the Circular Economy by Generating Added Value from Agricultural Waste in the Departments of Córdoba and Sucre," with BPIN code: 2021000100052 – SGR. Special thanks to Mr. José Tafur for allowing the use of the facilities at “La Bendición” farm and for sharing his knowledge related to plantain cultivation. Funding This research was funded by the Fondo Nacional de Regalias of Colombia through the project "Strengthening the Circular Economy by Generating Added Value from Agricultural Waste in the Departments of Córdoba and Sucre," with BPIN code: 2021000100052 – SGR. Author Contributions VS-B. supervision, conceptualization, methodology, writing, review, and editing; KV-M. literature review, processing, result analysis, drafting of the original manuscript, and final translation; FB-G. research, discussion of results, and drafting of the original manuscript, DF-F; literature review, processing, and drafting of the original manuscript; FT-B. thorough critical review of the research, evaluation of the methodology, results, and conclusions; JU-S. conceptualization and funding acquisition; DM-A. review and editing. All authors have read and agreed to the published version of the manuscript. Competing interests The authors declare no competing interests. Ethics approval not applicable. Consent to participate not applicable. Consent to participate Not applicable. Data availability The datasets generated or analyzed during the current study are not publicly available because they were part of a funded study, with data from susceptible private associations and commercial entities, but are available upon reasonable request from the corresponding author. Code availability Not applicable. Permits to collect plants or plant parts The University of Córdoba holds a Permiso Marco de Recolección de Especímenes de Especies Silvestres de la Diversidad Biológica con Fines de Investigación Científica No Comercial , originally granted through Resolution No. 00914 of August 4, 2017, and subsequently modified by Resolution No. 1147 of June 5, 2023, issued by the National Authority of Environmental Licenses (ANLA). This framework permit authorizes the collection of biological specimens for scientific research by permanent faculty members. 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Chemical Engineering Transactions , 78 , 307–312. https://doi.org/https://doi.org/10.3303/CET2078052 Van Dam, J. E. G., & Bos, H. L. (2004). The environmental impact of fibre crops in industrial applications. Hintergrundpapier Zu: Van Dam, JEG. Venkateshwaran, N., & Elayaperumal, A. (2010). Banana fiber reinforced polymer composites - A review. Journal of Reinforced Plastics and Composites , 29 (15), 2387–2396. https://doi.org/10.1177/0731684409360578 Weligama, V., & Karim, M. A. (2022). A comprehensive review on the properties and functionalities of biodegradable and semibiodegradable food packaging materials. Comprehensive Reviews in Food Science and Food Safety , 21 (1), 689–718. https://doi.org/10.1111/1541-4337.12873 Wernet, G., Bauer, C., Steubing, B., Reinhard, J., Moreno-Ruiz, E., & Weidema, B. (2016). The ecoinvent database version 3 (part I): overview and methodology. The International Journal of Life Cycle Assessment , 21 (9), 1218–1230. https://doi.org/10.1007/s11367-016-1087-8 Wolf, M.-A., Chomkhamsri, K., Brandao, M., Pant, R., Ardente, F., Pennington, D., Manfredi, S., De Camilis, C., & Goralczyk, M. (2010). International Reference Life Cycle Data System (ILCD) Handbook - General guide for Life Cycle Assessment - Detailed guidance. Constraints , 417. https://doi.org/10.2788/38479 Xue, L. (2019). Composite life cycle assessment and Management . https://www.clausiuspress.com/conferences/ACSS/ICAMCS%202019/AMC03.pdf Yadav, V., Singh, S., Singh, S., & Powar, S. (2024). Life cycle assessment of chemically treated and copper coated sustainable biocomposites. Science of The Total Environment , 948 , 174474. https://doi.org/10.1016/j.scitotenv.2024.174474 Zalazar-Garcia, D., Fernandez, A., Rodriguez-Ortiz, L., Torres, E., Reyes-Urrutia, A., Echegaray, M., Rodriguez, R., & Mazza, G. (2022). Exergo-ecological analysis and life cycle assessment of agro-wastes using a combined simulation approach based on Cape-Open to Cape-Open (COCO) and SimaPro free-software. Renewable Energy , 201 , 60–71. https://doi.org/10.1016/j.renene.2022.10.084 Table 5 Table 5 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table5.docx Cite Share Download PDF Status: Published Journal Publication published 20 Jan, 2026 Read the published version in Discover Sustainability → Version 1 posted Editorial decision: Revision requested 20 Nov, 2025 Reviews received at journal 17 Nov, 2025 Reviewers agreed at journal 13 Nov, 2025 Reviewers agreed at journal 11 Nov, 2025 Reviews received at journal 11 Nov, 2025 Reviewers agreed at journal 11 Nov, 2025 Reviewers agreed at journal 18 Oct, 2025 Reviews received at journal 05 Oct, 2025 Reviews received at journal 04 Oct, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers invited by journal 29 Sep, 2025 Editor invited by journal 26 Sep, 2025 Editor assigned by journal 26 Sep, 2025 Submission checks completed at journal 17 Sep, 2025 First submitted to journal 17 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7474191","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":527120990,"identity":"d17bf06c-263d-42d2-be29-44f647f6a068","order_by":0,"name":"Viviana 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1","display":"","copyAsset":false,"role":"figure","size":145553,"visible":true,"origin":"","legend":"\u003cp\u003eLife cycle assessment stages: (1) Definition of goals and scope, (2) Life cycle inventory (LCI), (3) Life cycle impact assessment (LCIA), and (4) Interpretation for decision-making and improvement. Adapted from ISO (2006a).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/8999e3991b4a3c868e24ee42.png"},{"id":93220324,"identity":"8b9247a4-0aa5-4ff3-810e-7ebfb9db5e56","added_by":"auto","created_at":"2025-10-10 10:39:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":242384,"visible":true,"origin":"","legend":"\u003cp\u003eSystem boundary from cradle to biocomposite production: (1A) Extraction of treated and coated fiber, (1B) Extraction of raw fiber, (2) Biocomposite production via VARTM.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/3568e24d0603b9d57c657840.png"},{"id":93221346,"identity":"bca81e4a-ccfa-4535-bb5f-6c37bccddf7f","added_by":"auto","created_at":"2025-10-10 10:55:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":237169,"visible":true,"origin":"","legend":"\u003cp\u003eResults by process with the IPCC 2021 method.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/6ab9797e08af0dbbaf8c5cc8.png"},{"id":93220328,"identity":"0f7f313f-3f3b-4e47-b966-8d3c19e07c04","added_by":"auto","created_at":"2025-10-10 10:39:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":198401,"visible":true,"origin":"","legend":"\u003cp\u003eImpact assessment for the CF-PNT/86, RF-PNT/85, CF-PNT/48, RF-PNT/46 scenarios with the ReCiPe Midpoint (H) method.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/392be4a53a5570f93237b2c5.png"},{"id":93220504,"identity":"bf8c2979-c4a2-415d-a0e6-fbbf6a2e6e17","added_by":"auto","created_at":"2025-10-10 10:47:29","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":148711,"visible":true,"origin":"","legend":"\u003cp\u003eImpact by processes in the impact categories TETP(A), METP(B), FFP (C) and HTPc (D) with the ReCiPe Midpoint (H) method.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/917c99263d1a20eec9fe5888.png"},{"id":93220329,"identity":"6079de7e-05b4-4db9-a07c-b826f3b67de4","added_by":"auto","created_at":"2025-10-10 10:39:29","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":139117,"visible":true,"origin":"","legend":"\u003cp\u003eA. Substance specifications for category TETP. B. Processes producing cobalt (II) substance for category TETP.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/72b94183264f97be6bbf6080.png"},{"id":93220506,"identity":"3dcacff9-4f96-4f78-9732-cc1f806523e6","added_by":"auto","created_at":"2025-10-10 10:47:29","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":142127,"visible":true,"origin":"","legend":"\u003cp\u003eSubstance specifications for the METP category. B. Processes that produce the substance Anthracene for the METP category.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/00a0bd97e4cede5e19c27c4c.png"},{"id":93220505,"identity":"4700827a-ec11-43de-b88d-a3061486ed2b","added_by":"auto","created_at":"2025-10-10 10:47:29","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":231563,"visible":true,"origin":"","legend":"\u003cp\u003eSpecifications by substance for the HTPc category.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/fe65828a5ec9e2ff4755958d.png"},{"id":93220333,"identity":"8491bf50-c682-48b8-931f-92f021f7b1fb","added_by":"auto","created_at":"2025-10-10 10:39:29","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":154561,"visible":true,"origin":"","legend":"\u003cp\u003eProcesses that produce the substances. A. Chromium (VI), B. Dioxin 2,3,7,8-Tetrachlorodibenzo-p-, C. Nickel (II) and D. Arsenic for the HTPc category.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/1d1f18cf89fbe1a18d5e042b.png"},{"id":101152851,"identity":"104a31a7-4bc8-47da-a9b8-3f2672205a2d","added_by":"auto","created_at":"2026-01-26 16:13:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2879508,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/457d20b8-d477-4070-930c-7769a40f4c78.pdf"},{"id":93220500,"identity":"df0de324-8e87-460d-9e39-e99dd2f0801f","added_by":"auto","created_at":"2025-10-10 10:47:29","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20279,"visible":true,"origin":"","legend":"","description":"","filename":"Table5.docx","url":"https://assets-eu.researchsquare.com/files/rs-7474191/v1/ecbdccbdc3a29b7da88a41b5.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Environmental performance assessment of biocomposite production reinforced with plantain pseudostem using life cycle assessment (LCA)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe increase in population has led to a rapid expansion of agricultural practices, significantly increasing post-harvest waste generation (Duque-Acevedo et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Koul et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The most common disposal methods for this waste are open-field burning and dumping (Bracco et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sadh et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which increases greenhouse gases (GHGs) emissions, including CO₂, CH₄, and NOₓ, negatively impacting ecosystem sustainability and human health (Kaza et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Odubo \u0026amp; Kosoe, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). According to the Intergovernmental Panel on Climate Change (IPCC), emissions from the combustion of various agricultural waste types amount to 1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18 kg CO₂/kg of waste, highlighting the need for exploration of alternative valorization strategies (Khosavithitkul et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this context, agricultural waste recycling not only offers a viable solution for its disposal but also promotes the circular economy by integrating sustainable practices, such as the production of natural fibers (NFs) (Dungani et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mansor et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sanjay et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This approach has enabled the development of biocomposites, reducing dependence on petroleum-derived materials (Mahieu et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Weligama \u0026amp; Karim, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As a result, studies have focused on developing natural fiber-reinforced composites due to their superior mechanical properties, making them suitable for technical applications (Pradhan et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Shinoj et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The use of biocomposites has grown across various industries, particularly in the automotive sector, where they have been utilized for years due to their excellent insulation properties (Ita-Nagy et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sassoni et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNFs exhibit mechanical properties comparable to their synthetic counterparts and can be obtained from agricultural waste such as plantain, coconut, bamboo, and hemp (Sanjay et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Their increased use and production are driven by environmental concerns regarding the Earth's limited resources, as well as their wide availability and low carbon emissions (De et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). They offer a high strength-to-weight ratio, making them suitable for manufacturing materials or tools (Elfaleh et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among the various sources of natural fibers derived from agricultural waste, plantain cultivation stands out due to its high potential and significant role in the global economy and food supply (Lau et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). By-products such as leaves, pseudostem, and inflorescence are often burned in situ or discarded, generating large amounts of residual biomass and causing negative environmental impacts (Mago et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Reyes et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For every ton of harvested plantain, four tons of waste are generated, primarily pseudostem (three tons) (de Oliveira et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Pseudostem fibers are notable for their high tensile strength, excellent moisture absorption, and biodegradability, making them ideal for composite applications (Komal et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Patel \u0026amp; Patel, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Venkateshwaran \u0026amp; Elayaperumal, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo evaluate the efficiency of these materials, life cycle assessment (LCA) (ISO 14040, 2006a; ISO 14044 2006b) is used for the environmental assessment of products and services, from raw material acquisition, through the production and use stages, to waste treatment, including disposal and recycling (Laca et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ramanujan et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). LCA studies comparing natural fibers with conventional materials have proven to be an objective approach that highlights their environmental benefits (Xue, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe evaluation of environmental performance is of great importance, as in some cases, the use of natural fibers does not guarantee an environmentally friendly product due to the high consumption of water, soil, and chemicals throughout its life cycle (Mansor et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The objective of this study is to evaluate the environmental impacts associated with the production of biocomposites with a polyester resin matrix reinforced with plantain pseudostem fiber, using life cycle assessment (LCA) under a cradle-to-manufacture approach. Additionally, different agricultural waste utilization scenarios are compared using SimaPro software (version 9.6.0.1), which provides scientific data for analyzing, monitoring, and measuring the environmental impact of products and services throughout their entire life cycle (Fern\u0026aacute;ndez-L\u0026oacute;pez et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Mares et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zalazar-Garcia et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003eTo evaluate the environmental impacts associated with the production of biocomposites reinforced with plantain pseudostem fiber, the life cycle assessment (LCA) methodology was applied following the guidelines established by the International Organization for Standardization (ISO) (ISO 14040, 2006a; ISO 14044 2006b). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the four life cycle stages and sub-stages as defined by the ISO standard, which were applied in this study and are described below:\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Definition of objectives and scope\u003c/h2\u003e\u003cp\u003eThis stage aims to evaluate the environmental performance of biocomposite production reinforced with plantain pseudostem fiber by establishing different sensitivity scenarios to identify the most environmentally efficient alternative.\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003e2.1.1 Definition of the Functional Unit (FU)\u003c/h2\u003e\u003cp\u003eThe functional unit (FU) defines the quantification of a product, process, or service by providing a reference to which the inputs and outputs of a system are related (ISO, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006a\u003c/span\u003e). In this study, the FU is 1 kg of biomaterial reinforced with plantain pseudostem fiber. The mass unit (kg) is used because the product is not intended for a specific application (Schultz \u0026amp; Suresh, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.1.2 System Boundaries\u003c/h2\u003e\u003cp\u003eA cradle-to-manufacture approach is adopted, covering the process from the extraction of treated fibers (CF) or raw fibers (RF) to the production of biocomposites reinforced with plantain pseudostem fiber (PNT) using the Vacuum-Assisted Resin Transfer Molding (VARTM) process (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The extraction process was established as the starting point, or \u0026ldquo;cradle,\u0026rdquo; since the LCA scope does not include the environmental burdens associated with agricultural cultivation (such as fertilizer or water use), aligning with methodologies applied in other studies (Desole et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yadav et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this study, plantain pseudostems, considered agricultural waste, are treated as environmental burden-free resources, as they are not intentionally produced but are a natural byproduct of plantain cultivation, whose primary purpose is fruit production (Cherubini \u0026amp; Ulgiati, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Rodr\u0026iacute;guez et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.1.3 sensitivity scenarios\u003c/h2\u003e\u003cp\u003eThe sensitivity scenarios consider factors that may influence the environmental performance of biocomposite production (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). First, the chemical treatment (mercerization) and coating (flexible epoxy resin) applied to plantain pseudostem fibers. Second, the resulting biocomposite may have different fiber and polyester matrix compositions (Altamiranda, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The use of different mixtures and chemical treatment with coating allows for the identification of the alternative with the highest environmental performance (Liu et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSensitivity scenarios for the production of plantain pseudostem fiber-reinforced biocomposites with a polyester matrix using the VARTM process.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScenarios\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReinforcement %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePolyester resin (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTreatment/coating\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLabel*\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e86%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYES\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCF-PNT/86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNOT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRF-PNT/85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eYES\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCF-PNT/48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNOT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRF-PNT/46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: *CF: Chemically treated/coated fiber\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*RF: Raw fiber\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e*PNT: Plantain pseudostem fiber\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Life Cycle Inventory (LCI) and Data Quality\u003c/h2\u003e\u003cp\u003eThis study developed specific life cycle inventories (LCIs) for the fiber extraction and biocomposite production stages, integrating both primary and secondary data. Data collection included on-site sampling, small-scale experiments described in this section, information from the Ecoinvent 3.10 database processed using SimaPro 9.6.0.1 software (Moreno-Ruiz et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wernet et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), as well as technical and scientific literature. Additionally, proprietary calculations were performed to quantify system inputs and outputs, including mass and energy balances of unit processes.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Raw material collection\u003c/h2\u003e\u003cp\u003eThe raw material was sourced fron the municipality of Puerto Escondido, located in northern Colombia. This region covers an area of 426.2 km\u0026sup2;, has an altitude of 30 meters above sea level, and an average temperature of 28\u0026deg;C (Alcald\u0026iacute;a Municipal de Puerto Escondido, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). According to 2022 data, the municipality reported 2,072 hectares of plantain cultivation (Agronet, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Pseudostems from post-harvest waste of the Hart\u0026oacute;n plantain (\u003cem\u003eMusa paradisiaca spp\u003c/em\u003e) were obtained from La Bendici\u0026oacute;n farm.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Production of Plantain Pseudostem Fiber\u003c/h2\u003e\u003cp\u003eThe manual cleaning and cutting of the pseudostem sheaths were carried out on-site using a semi-mechanical method, which involves a comb with metal bristles for manual decortication. This process helps reduce water content and remove waste (Mumthas et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The extracted fibers were washed in hot water at 100\u0026deg;C to eliminate excess cellulosic material. Subsequently, for scenarios 1 and 3, a chemical treatment and epoxy resin coating (Mercerization) were applied using 5% NaOH and 50% CH3COOH solutions, both dissolved in distilled water (Altamiranda, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The CF-PNT and RF-PNT fibers were then dried in a BPG-9070A oven (220V, 1100W) at 45\u0026deg;C for two and a half hours.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Production of Biocomposite Using VARTM\u003c/h2\u003e\u003cp\u003eThe CF-PNT and RF-PNT fibers proceed to the biocomposite production phase using the Vacuum-Assisted Resin Transfer Molding (VARTM) process. This is an open-mold composite manufacturing method that operates at atmospheric pressure and room temperature (Tamakuwala, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Following the procedure described by Pico et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), a release wax was applied to prevent adhesion to the mold. The pre-mixed polyester resin was then injected onto the chemically treated and coated fibers or raw fibers by applying pressure inside a closed vessel, ultimately forming the biocomposite.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.2.4 Data Quality Analysis\u003c/h2\u003e\u003cp\u003eThe life cycle inventory (LCI) data were evaluated using the International Reference Life Cycle Data System (ILCD) method (Balcioglu et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Wolf et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) For this analysis, the Pedigree matrix was defined, which assesses six quality parameters: Technological representativeness (Ter), Geographical representativeness (GR), Temporal representativeness (Tir), Completeness (C), Parameter uncertainty (P) (i.e., the accuracy of inventory data concerning direct measurements), and Methodological adequacy and consistency (M). Each parameter is assigned a value ranging from 1 (Very high quality) to 5 (Low quality) (Chen \u0026amp; Lee, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; F\u0026uuml;chsl et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Eq.\u0026nbsp;1 presents the Data Quality Rating (DQR) formula, which calculates the average of these indicators and determines the overall quality level of the LCI data.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:DQR=\\frac{TeR+GR+TiR+C+P+M+{X}_{W}*4}{i+4}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere X\u003csub\u003eW\u003c/sub\u003e represents the lowest quality level obtained, meaning the highest numerical value among the data quality indicators, and indicates the number of applicable data indicators. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows how these values relate to the final quality level of the obtained data (Godoy Le\u0026oacute;n \u0026amp; Dewulf, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eData Quality Indicator and Quality Level.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eData quality indicator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eData quality level\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1.0\u0026ndash;1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery high quality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1.7\u0026ndash;2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh quality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2.5\u0026ndash;3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSatisfactory quality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3.3\u0026ndash;4.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLow quality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Life Cycle Impact Assessment (LCIA)\u003c/h2\u003e\u003cp\u003eLCIA was used to analyze the relevance of potential impacts throughout the entire life cycle (Suppen-Reynaga et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The LCI results were transformed into a limited number of environmental impact scores using characterization factors (Hauschild \u0026amp; Huijbregts, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The method of the Intergovernmental Panel on Climate Change (IPCC 2021) and the ReCiPe Midpoint (H) method (hierarchical version) were employed.\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1 IPCC 2021 Method\u003c/h2\u003e\u003cp\u003eThe IPCC 2021 method uses emission metrics for the Global Warming Potential (GWP100), which quantifies the increase in integrated infrared radiative forcing of a greenhouse gas (GHG) relative to CO₂ over a 100-year period, expressed in kg CO₂-eq (Lynch et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2 The ReCiPe 2016 Midpoint (H)\u003c/h2\u003e\u003cp\u003eAssessment method encompasses all potential impacts generated by various processes, representing them through impact categories expressed with midpoint indicators (Dekker et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hauschild et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Kiss \u0026amp; Boskovic, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This method employs a cause-effect approach, enhancing the understanding of environmental effects and highlighting opportunities for improvement (Mezzanotte et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In this study, only 16 impact categories were considered (Huijbregts et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2017\u003c/span\u003e): (1) Ozone depletion (ODP), (2) Ionizing radiation (IRP), (3) Fine particulate matter formation (PMFP), (4) Photochemical oxidant formation in terrestrial ecosystems (EOFP), (5) Photochemical oxidant formation affecting human health (HOFP), (6) Terrestrial acidification (TAP), (7) Freshwater eutrophication (FEP), (8) Marine eutrophication (MEP), (9) Human carcinogenic toxicity (HTPc), (10) Human non-carcinogenic toxicity (HTPnc), (11) Terrestrial ecotoxicity (TETP), (12) Freshwater ecotoxicity (FETP), (13) Marine ecotoxicity (METP), (14) Water consumption (WCP), (15) Mineral resource scarcity (SOP), and (16) Fossil resource scarcity (FFP). For category interpretation, normalization was conducted using software.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Life Cycle Interpretation\u003c/h2\u003e\u003cp\u003eThis stage involved reviewing the results of the inventory analysis and impact assessment to validate their consistency with the study's objective and scope. The unit processes that represented the highest environmental burdens within the life cycle were identified, allowing for a comparison between scenarios to determine which of the proposed options resulted in the least environmental impact (Laurent et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Life Cycle Inventory (LCI)\u003c/h2\u003e\u003cp\u003eThe results of the life cycle inventory (LCI) compiled material and energy consumption, as well as waste generation and emissions (inputs and outputs) associated with each stage of the life cycle for plantain pseudostem fiber extraction and the production of fiber-reinforced biomaterial using the VARTM process (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Activities and processes from the Ecoinvent 3.10 database were used to model the flows in the SimaPro software (Wernet et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLife cycle inventory (LCI) for the extraction of plantain pseudostem fiber.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEXTRACTION OF RAW MATERIALS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCF-PNT/86\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRF-PNT/85\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCF-PNT/48\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRF-PNT/46\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINPUTS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e\u003cp\u003eAmount\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePseudostem plantain {CO*}| Recycled Content cut-off\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57,793\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e96,392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32,257\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e52,165\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTap water {CO}| market for tap water | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15,762\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26,289\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e8,797\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14,227\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater, deionised {RoW*}| market for water, deionised | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10,954\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6,114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSodium hydroxide, without water, in 50% solution state {RoW}| market for sodium hydroxide, without water, in 50% solution state | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,673\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAcetic acid, without water, in 98% solution state {GLO*}| market for acetic acid, without water, in 98% solution state | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2,355\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEpoxy resin {GLO}| market for epoxy resin | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonoethanolamine {GLO}| market for monoethanolamine | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,175\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eELECTRICAL CONSUMPTION\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eElectricity, low voltage {CO}| market for electricity, low voltage | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekWh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17,075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28,479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9,530\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15,412\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOUTPUTS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDry fiber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,850\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,460\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoated fiber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,860\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWaste Pseudostem untreated {GLO}| Treatment of waste Pseudostem, untreated, open dump, wet infiltration class (500mm) | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45,709\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e76,237\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25,512\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e41,258\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmissions to air\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater/m3, CO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12,457\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20,619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e6,953\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e11,159\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmissions to water\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWastewater, average {RoW}| treatment of wastewater, average, wastewater treatment | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31,259\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24,974\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17,447\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13,515\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: * These are 2-letter country codes or 3-letter region codes, indicating the geography represented by the dataset: Colombia (CO), Global (GLO), and Rest of the World (RoW).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe LCI results (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) for biomaterial production in the four scenarios proposed in this study are shown below.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLife cycle inventory (LCI) for the production of biomaterial with plantain pseudostem reinforcement using VARTM.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBIOMATERIAL PRODUCTION\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCF-PNT/86\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRF-PNT/85\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eCF-PNT/48\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eRF-PNT/46\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eINPUTS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eAmount\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePetroleum slack wax {CO*}| petroleum slack wax production, petroleum refinery operation | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,0035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0,0035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0,0035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,0035\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrthophthalic acid based unsaturated polyester resin {GLO*}| market for orthophthalic acid based unsaturated polyester resin | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0,150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0,520\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,540\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eELECTRICAL CONSUMPTION\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eElectricity, low voltage {CO}| market for electricity, low voltage | Cut-off, S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekWh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0,007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0,007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0,007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0,007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOUTPUTS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiocomposite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ekg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: * These are 2-letter country codes or 3-letter region codes, indicating the geography represented by the dataset: Colombia (CO), Global (GLO).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003e3.1.1 Data Quality Assessment\u003c/h2\u003e\u003cp\u003eThe quality indicators (M, C, TiR, GR, TeR, and P) reflect various results in the pedigree matrix (see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) for the LCIs, and their application can be observed in the results presented in the annexes. The methodological consistency (M) and temporal representativeness (TiR) indicators predominantly show values of 1, ensuring compliance with established requirements, high methodological consistency, and data relevance for the studied period. Completeness (C) values range between 1 and 2, indicating adequate coverage for most of the analyzed flows. However, a specific process reaches a value of 5, indicating limited representativeness in this particular case. This is because steam quality was estimated through a mass balance rather than being directly measured with specialized equipment. Geographical representativeness (GR), on the other hand, presents values between 1 and 3, representing a high coverage of the study area. Technological representativeness (TeR) values range between 1 and 4, indicating that some processes align directly with the technology used, while others show a lower degree of similarity. Finally, parameter uncertainty (P) ranges between 2 and 3, indicating an overall acceptable level of accuracy.\u003c/p\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Environmental impact assessment for each of the scenarios\u003c/h2\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1 IPCC 2021 Method\u003c/h2\u003e\u003cp\u003eIn terms of global warming potential (GWP100, including CO₂ capture), the results (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) indicate that treatment and a higher natural fiber content tend to increase carbon dioxide equivalent emissions. Conversely, scenarios without treatment and with a lower percentage of plantain pseudostem fiber exhibit lower value in this impact category.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eImpact assessment results for each scenario using the IPCC 2021 method.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eImpact category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnit\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCF-PNT/86\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRF-PNT/85\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCF-PNT/48\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRF-PNT/46\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGWP100 incl. CO2 ptake\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKg CO2-eq\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27,7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11,3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the CF-PNT/86 and CF-PNT/48 scenarios, the magnitude of the impact is mainly attributed to the chemical treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), as this process significantly increases CO₂ emissions, accounting for 56.7% of the total emissions in this category (50.2% from acetic acid and 6.5% from sodium hydroxide). In scenarios without chemical treatment (RF-PNT/85 and RF-PNT/46), the increase is associated with electricity consumption and the treatment of plantain pseudostem waste.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003e3.2.1. ReCiPe Midpoint (H) Method\u003c/h3\u003e\n\u003cp\u003eThe categories with the highest results were analyzed. The impact categories evaluated in the CF-PNT/86 and CF-PNT/48 scenarios show higher values in terrestrial ecotoxicity (TETP) and marine ecotoxicity (METP), fossil resource scarcity (FFP), and human carcinogenic toxicity (HTPc) indicators compared to the scenarios without chemical fiber treatment (RF-PNT/85 and RF-PNT/46) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA to \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD illustrate the influence of different processes on the TETP, METP, FFP, and HTPc impact categories. In the CF-PNT/86 and CF-PNT/48 scenarios, the highest environmental impact contribution is associated with the use of chemicals such as acetic acid and sodium hydroxide, particularly in the terrestrial ecotoxicity (TETP) category. Similarly, in the marine ecotoxicity (METP), fossil resource scarcity (FFP), and human carcinogenic toxicity (HTPc) categories, chemical treatment processes and the use of the polymeric matrix contribute the most to impact magnitude. Electricity and other remaining processes have a smaller share compared to these substances.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe data quality results (DQR) indicate that most values exhibit high quality (1.7\u0026ndash;2.4) or satisfactory quality (2.5\u0026ndash;3.3) (see Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These results align with those reported by Desole et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in their LCA study, which evaluated alternatives for replacing fossil-based and non-renewable materials. In that study, the application of the DQR methodology yielded excellent quality values ranging from 2.1 to 2.4 and a satisfactory quality of 2.6. Conversely, the output associated with evaporation (air emissions) in our study reflects low quality (\u0026gt;\u0026thinsp;3.3), reaching a value of 3.5. This is attributed to the quality indicators C, TeR, and P, which obtained values of 5, 4, and 3, respectively, directly influencing the final DQR score. This result is likely due to the reliance on mass balance as a methodological approach and the lack of direct measurements.\u003c/p\u003e\u003cp\u003eThe results obtained using the IPCC 2021 GWP100 environmental impact assessment methodology indicated that the CF-PNT/86 scenario generated the highest level of pollution, primarily due to the chemical treatment process (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This is due to acetic acid production being an energy-intensive industrial process, leading to increased CO₂ emissions (Bord\u0026oacute;n et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similarly, the alkaline treatment of natural fibers with sodium hydroxide (NaOH) imposes a significant environmental burden, as its production via electrolysis also requires substantial energy input (Kim et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). During post-treatment, wastewater is generated as fibers are removed from the solutions, raising concerns regarding both wastewater treatment and disposal (Van Dam \u0026amp; Bos, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRelated studies, such as that conducted by Alcivar-Bastidas et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which assessed the environmental impact of alkaline treatment on natural abaca fibers while reusing the NaOH solution, found that conventional chemical treatment considerably increased the environmental footprint compared to untreated fibers. Specifically, the carbon footprint of conventional alkaline treatment was 1.48 kg CO₂ eq/kg of fiber\u0026mdash;three times higher than that of untreated fibers, which exhibited a footprint of 0.47 kg CO₂ eq/kg of fiber. Consequently, several authors suggest that reusing the alkaline solution could significantly enhance the circular economy strategy for waste utilization (Alcivar-Bastidas et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ita-Nagy et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Juradin et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Nguyen et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tran et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, Anastasiou (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that epoxy resin composites reinforced with chemically treated \u003cem\u003eLuffa cylindrica\u003c/em\u003e fibers exhibited greater environmental impacts than those reinforced with untreated fibers, primarily due to the use of chemicals in the treatment process.\u003c/p\u003e\u003cp\u003eRegarding electricity consumption across scenarios, the findings indicate that, within the extraction processes, electricity accounts for 18% of global warming in the CF-PNT/86 scenario\u0026mdash;a lower proportion compared to the 49.4% recorded in RF-PNT/85. This disparity arises because, in the absence of chemical treatment and coating, a larger amount of fiber requires drying, as the coating increases the total fiber weight by approximately 50%. A similar trend is observed in the CF-PNT/48 and RF-PNT/46 scenarios, where electricity consumption contributes 16.3% and 40.5% to global warming, respectively.\u003c/p\u003e\u003cp\u003eIn the RF-PNT/85 scenario, which contains a similar amount of pseudostem but without chemical treatment, emissions were mainly associated with electricity consumption and the treatment of plantain pseudostem waste, accounting for 49.4% (energy consumption) and 46.6% (treatment) of the total environmental burden. Nevertheless, this scenario demonstrated better environmental performance compared to CF-PNT/86. In the CF-PNT/48 scenario, where chemical treatment was maintained but the amount of replacement fiber was reduced, an increase in CO₂ emissions was observed due to the polymeric matrix manufacturing process. This is attributed to the higher proportion of polymeric matrix used in the mixture, explaining why the most environmentally viable scenario was RF-PNT/46. By reducing the amount of processed fiber, energy consumption decreases, and chemical treatment is avoided, resulting in a lower carbon footprint.Similar results were reported by Yadav et al. (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), where the manufacturing of chemically treated plantain fiber composites coated with copper showed that electricity accounted for approximately 73% to 74% of global warming emissions, significantly higher than raw composites, which accounted for around 64%. Likewise, Bord\u0026oacute;n et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) determined that untreated plantain fibers generate a lower environmental impact, as they do not require energy-intensive chemical processes, contributing to a significant reduction in global CO₂ emissions. Furthermore, Paul et al. (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) stated that untreated fibers can achieve similar mechanical properties without the environmental costs associated with chemical treatments, findings also reported by Altamiranda (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), a researcher and producer of the fibers supplied for this study.\u003c/p\u003e\u003cp\u003eApplying the ReCiPe 2016 methodology, the results for the TETP indicator in the CF-PNT/86 and CF-PNT/48 scenarios are primarily attributed to the use of chemicals (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). According to George \u0026amp; Bressler (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the production chains of these compounds generate potentially harmful emissions. Additionally, the polymer matrix had a significant impact in scenarios with lower fiber replacement ratios (CF-PNT/48 and RF-PNT/46), mainly due to emissions from its manufacturing process. The substances contributing to this impact category are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, where cobalt (II) emissions are predominant, mainly originating from the production of acetic acid and the polymeric matrix. These findings align with the trend observed in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, reinforcing that the combination of chemical treatment and synthetic polymer use considerably increases terrestrial ecotoxicity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe relationship between acetic acid and cobalt (II) compounds (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB), such as cobalt acetate, stems from their presence as emissions within the product\u0026rsquo;s life cycle, primarily due to their role in acetic acid oxidation processes, where cobalt (II) compounds function as catalysts in the production of aromatic acids (Partenheimer, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Upon reaching the soil, cobalt (II) compounds exhibit toxic properties, which can disrupt microbial communities and enzymatic activities, ultimately affecting soil health and plant growth (Kosiorek, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, according to data from Ecoinvent (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), acetic acid production has a significant environmental impact, mainly due to the use of liquefied petroleum gas (LPG) as an energy source. This process generates pollutant emissions that increase the toxic load in both marine and terrestrial ecosystems (Deshmukh et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Suresh et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB illustrates a clear trend in the marine ecotoxicity (METP) category: as polymeric matrix consumption increases, so does its environmental impact. In this context, the CF-PNT/48 scenario exhibits the best environmental performance, as it maintains a high fiber replacement percentage without the additional environmental burden associated with acetic acid or the increased use of the polymeric matrix, followed by the RF-PNT/46 scenario. Regarding emitted substances, anthracene is the primary contributor, accounting for 42%, 45%, 40%, and 42% across the evaluated scenarios, followed by cobalt (II) (previously discussed) and, to a lesser extent, copper ions (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnthracene, primarily emitted during the manufacturing processes of acetic acid and the polymeric matrix (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB), can volatilize into the atmosphere due to industrial activities or vehicle emissions and subsequently be deposited in marine ecosystems through precipitation or atmospheric sedimentation (Pathak et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ravindra et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Studies have shown that polycyclic aromatic hydrocarbons (PAHs), including anthracene, are frequently detected in coastal waters, highlighting a direct connection between atmospheric and marine pollution (Karthikeyan et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Its increasing prevalence in these ecosystems poses a significant risk to biodiversity. Furthermore, its potential for photoinduced toxicity suggests that current assessments may underestimate the risks associated with this compound and similar contaminants in marine environments (Gomes et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Oris et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1984\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe results for the fossil resource scarcity (FFP) category are attributed to the use of nonrenewable fossil resources, such as liquefied petroleum gas (LPG) and coal, as energy inputs in processes related to chemical treatment, particularly in the production of acetic acid, sodium hydroxide, and the polymer matrix derived from crude oil. Due to their finite nature, these substances have a significant impact on fossil resource scarcity, as their extraction and consumption contribute to the depletion of limited reserves (Clasen et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Among the evaluated scenarios, RF-PNT/85 exhibited the best performance in this category, primarily due to the omission of chemical treatment and the reduction in polymer matrix usage (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Additionally, the human carcinogenic toxicity (HTPc) category was among the most significant in the environmental impact assessment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Processes associated with chemical treatment, particularly the production of acetic acid and sodium hydroxide, along with electricity consumption, were the main contributors to this impact (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). This is attributed to the emission of hazardous substances, such as chromium (VI) into the air and water, dioxin 2,3,7,8-tetrachlorodibenzo-p-, as well as arsenic and nickel (II) ions (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eChromium (VI) emissions are linked to the life cycle of acetic acid (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA), as its production involves high-carbon ferrochromium, according to industrial manufacturing inventories. This represents a secondary impact derived from the evaluated processes. Similarly, 2,3,7,8-Tetrachlorodibenzo-p-dioxin is generated to a lesser extent during polymer matrix production, mainly due to the use of sodium hydroxide, which serves to neutralize residual acids, stabilize the final product, or facilitate other laboratory procedures (Radenkov et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore, this compound is primarily emitted during sodium hydroxide production via chlor-alkali electrolysis, a key industrial process for chlorine and NaOH synthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB) (Ecoinvent, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Finally, nickel (II) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC) and arsenic (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eD) emissions are mainly attributed to electricity consumption, particularly from Colombia\u0026rsquo;s energy mix, according to Ecoinvent. These emissions likely result from power generation using nonrenewable sources such as coal and oil, which release arsenic and other pollutants into the environment.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe production of biomaterials from plantain pseudostem fiber has significant environmental impacts, primarily due to chemical treatment. This process accounts for 56.7% and 50.3% of the greenhouse gas emissions contributing to global warming potential (GWP) in the CF-PNT/86 and CF-PNT/48 scenarios, respectively, as a result of the high energy demand of industrial processes. Although increasing the amount of untreated pseudostem required raises the GWP due to the higher energy demand for drying, its overall impact remains lower than that associated with chemical treatment.\u003c/p\u003e\u003cp\u003eChemical treatment notably impacts multiple environmental categories. First, it increases terrestrial and marine ecotoxicity due to hazardous emissions generated along the production chains of the chemical compounds used. Although these emissions are not directly linked to the fiber extraction processes evaluated, they should be considered relevant secondary impacts. Additionally, the fossil resource scarcity indicator presents higher values in scenarios involving chemical treatment. This results from the consumption of nonrenewable resources such as liquefied petroleum gas (LPG) and coal, which play a crucial role in the production of acetic acid, sodium hydroxide, and crude oil derivatives used in the polymer matrix. The exploitation of these resources significantly contributes to the depletion of finite reserves. Finally, the human carcinogenic toxicity category shows a marked increase, primarily driven by secondary emissions from substances associated with the chemical life cycle.\u003c/p\u003e\u003cp\u003eOverall, the global assessment demonstrates that untreated fibers achieve better environmental performance than chemically treated fibers, highlighting the sustainability benefits of avoiding chemical treatments. Therefore, prioritizing this scenario is recommended, as it enables the attainment of comparable mechanical properties without incurring the environmental costs associated with chemical processing. However, further research on fiber processing and treatment is necessary, considering that biocomposites may help reduce landfill disposal or mitigate degradation rates if released into the environment, as currently observed. This potential environmental benefit should be integrated into future assessments to achieve a more comprehensive evaluation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to the Fondo Nacional de Regalias of Colombia for the financial support provided through the project \u0026quot;Strengthening the Circular Economy by Generating Added Value from Agricultural Waste in the Departments of C\u0026oacute;rdoba and Sucre,\u0026quot; with BPIN code: 2021000100052 \u0026ndash; SGR. Special thanks to Mr. Jos\u0026eacute; Tafur for allowing the use of the facilities at \u0026ldquo;La Bendici\u0026oacute;n\u0026rdquo; farm and for sharing his knowledge related to plantain cultivation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Fondo Nacional de Regalias of Colombia through the project \u0026quot;Strengthening the Circular Economy by Generating Added Value from Agricultural Waste in the Departments of C\u0026oacute;rdoba and Sucre,\u0026quot; with BPIN code: 2021000100052 \u0026ndash; SGR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVS-B. supervision, conceptualization, methodology, writing, review, and editing; KV-M. literature review, processing, result analysis, drafting of the original manuscript, and final translation; FB-G. research, discussion of results, and drafting of the original manuscript, DF-F; literature review, processing, and drafting of the original manuscript; FT-B. thorough critical review of the research, evaluation of the methodology, results, and conclusions; JU-S. conceptualization and funding acquisition; DM-A. review and editing. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003enot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003enot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated or analyzed during the current study are not publicly available because they were part of a funded study, with data from susceptible private associations and commercial entities, but are available upon reasonable request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePermits to collect plants or plant parts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe University of C\u0026oacute;rdoba holds a \u003cem\u003ePermiso Marco de Recolecci\u0026oacute;n de Espec\u0026iacute;menes de Especies Silvestres de la Diversidad Biol\u0026oacute;gica con Fines de Investigaci\u0026oacute;n Cient\u0026iacute;fica No Comercial\u003c/em\u003e, originally granted through Resolution No. 00914 of August 4, 2017, and subsequently modified by Resolution No. 1147 of June 5, 2023, issued by the National Authority of Environmental Licenses (ANLA). This framework permit authorizes the collection of biological specimens for scientific research by permanent faculty members. The collected plant samples are deposited in and legally registered at the Herbarium of the University of C\u0026oacute;rdoba (HUC), which issues the corresponding certificates of deposit. Under this permit, plant material corresponding to \u003cem\u003eMusa paradisiaca\u003c/em\u003e L. (family \u003cem\u003eMusaceae, Hart\u0026oacute;n variety\u003c/em\u003e), specifically pseudostem fibers, was collected in Puerto Escondido, Department of C\u0026oacute;rdoba, Colombia (9\u0026deg;02\u0026apos;42.4\u0026quot; N, 76\u0026deg;15\u0026apos;14.8\u0026quot; W), on October 9, 2024. The plant was approximately 4.0 m tall. The fibers, cream to light brown in color, with an average length of 1.0 m and an approximate diameter of 250 \u0026micro;m, were characterized as fragile yet resistant, with a thin layer of plant material on the surface and no visible signs of degradation or infestation.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAgronet. (2022). \u003cem\u003eReporte:\u0026Aacute;rea, Producci\u0026oacute;n, Rendimiento y Participaci\u0026oacute;n Municipal en el Departamento por cultivo\u003c/em\u003e. https://www.agronet.gov.co/estadistica/Paginas/home.aspx?cod=4\u003c/li\u003e\n\u003cli\u003eAlcald\u0026iacute;a Municipal de Puerto Escondido. (2001). \u003cem\u003eEsquema de Ordenamiento Territorial Puerto Escondido C\u0026oacute;rdoba 2001 - 2010: EOT Puerto Escondido C\u0026oacute;rdoba 2001 - 2010\u003c/em\u003e. https://repositoriocdim.esap.edu.co/handle/20.500.14471/13676\u003c/li\u003e\n\u003cli\u003eAlcivar-Bastidas, S., Petroche, D. 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Life cycle assessment of chemically treated and copper coated sustainable biocomposites. \u003cem\u003eScience of The Total Environment\u003c/em\u003e, \u003cem\u003e948\u003c/em\u003e, 174474. https://doi.org/10.1016/j.scitotenv.2024.174474\u003c/li\u003e\n\u003cli\u003eZalazar-Garcia, D., Fernandez, A., Rodriguez-Ortiz, L., Torres, E., Reyes-Urrutia, A., Echegaray, M., Rodriguez, R., \u0026amp; Mazza, G. (2022). Exergo-ecological analysis and life cycle assessment of agro-wastes using a combined simulation approach based on Cape-Open to Cape-Open (COCO) and SimaPro free-software. \u003cem\u003eRenewable Energy\u003c/em\u003e, \u003cem\u003e201\u003c/em\u003e, 60\u0026ndash;71. https://doi.org/10.1016/j.renene.2022.10.084\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 5","content":"\u003cp\u003eTable 5 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Agricultural Waste, Circular Economy, Environmental Performance, Life Cycle Assessment, Natural Fiber, Biocomposites","lastPublishedDoi":"10.21203/rs.3.rs-7474191/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7474191/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eComposites incorporating bio-based materials, such as natural fibers (NFs), represent a promising alternative for utilizing agricultural waste, promoting sustainability and a circular economy by transforming NFs into high-value resources with diverse applications. A life cycle assessment (LCA) was conducted to evaluate the environmental performance of biocomposites reinforced with plantain pseudostem fiber and a polyester resin matrix under a \"cradle-to-manufacture\" approach. Two scenarios with chemical treatment and two without treatment, each with different fiber content, were analyzed. The environmental impact assessment applied the Intergovernmental Panel on Climate Change (IPCC 2021) method, expressed as the 100-year global warming potential (GWP100) in kg of CO₂, and the ReCiPe Midpoint (H) 2016 method for 16 impact categories, using SimaPro software. The scenario with treatment and an 86% fiber content showed a higher environmental impact according to the IPCC 2021 (GWP100) method, with emissions of 27.6 kg of CO₂ per kilogram of composite material. In the ReCiPe 2016 analysis, the most affected impact categories included terrestrial and marine ecotoxicity, fossil resource scarcity, and human carcinogenic toxicity, primarily due to the chemical treatment involving acetic acid and sodium hydroxide, which significantly increased CO₂ emissions. Conversely, untreated scenarios exhibited significantly lower impacts across multiple categories, positioning them as more sustainable alternatives.\u003c/p\u003e","manuscriptTitle":"Environmental performance assessment of biocomposite production reinforced with plantain pseudostem using life cycle assessment (LCA)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-10 10:39:24","doi":"10.21203/rs.3.rs-7474191/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-21T04:40:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-17T18:49:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80496089275358327203048084488891357732","date":"2025-11-13T18:51:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128997962917621513957673149740338845098","date":"2025-11-11T17:32:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-11T13:21:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339030087611355684111356026440624823075","date":"2025-11-11T12:16:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48582963743109285846461219195678262138","date":"2025-10-18T11:10:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-05T18:05:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-04T11:51:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51478181395896109860823193958201167102","date":"2025-09-29T13:15:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61591119672808865756268370226947258451","date":"2025-09-29T13:02:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-29T12:47:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-26T08:39:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-26T04:57:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-17T22:42:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2025-09-17T22:39:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"019f97d7-c46b-4380-9186-ce5aa6f37fb8","owner":[],"postedDate":"October 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-26T16:10:15+00:00","versionOfRecord":{"articleIdentity":"rs-7474191","link":"https://doi.org/10.1007/s43621-025-02534-6","journal":{"identity":"discover-sustainability","isVorOnly":false,"title":"Discover Sustainability"},"publishedOn":"2026-01-20 15:57:58","publishedOnDateReadable":"January 20th, 2026"},"versionCreatedAt":"2025-10-10 10:39:24","video":"","vorDoi":"10.1007/s43621-025-02534-6","vorDoiUrl":"https://doi.org/10.1007/s43621-025-02534-6","workflowStages":[]},"version":"v1","identity":"rs-7474191","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7474191","identity":"rs-7474191","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}