A Holistic Framework for Sustainable Environmental Impact Assessment in Polymer Production: Systematic Review and Validation

Abstract

Global polymer production has rapidly escalated in response to the increasing global demand. These materials are highly regarded due to their superior strength-to-weight ratio, cost-effectiveness, and ease of manufacturing. This study presents a systematic review aimed at addressing the environmental challenges associated with polymer production. It also seeks to develop a Sustainable Conceptual Model for Environmental Impact Assessment (EIA), integrating key sustainability factors, which are often overlooked in existing frameworks. A systematic literature review was conducted following PRISMA guidelines, covering peer-reviewed studies published between 2015 and 2025 in the Scopus and Web of Science databases. Critical gaps in conventional EIA practices for polymer manufacturing were identified, forming the basis for the proposed integrated sustainability framework. The proposed model provides a structured methodology for assessing key sustainability dimensions across polymer production, enabling a more comprehensive evaluation of environmental impacts throughout the polymer production process. As validation for the model, a pilot study with 68 industry experts was analyzed through reliability testing, confirmatory factor analysis, and regression-based hypothesis testing. The results supported the proposed model. Industries can utilize the model to develop targeted sustainability strategies, minimize environmental footprints, and inform policymaking efforts aimed at improving the environmental performance of polymer manufacturing.

1. Introduction

The global polymer industry underpins critical sectors such as packaging, automotive, construction, and healthcare, with annual plastic production exceeding 400 million metric tons [1]. Driven by rising demand in developing economies, this figure will double by 2050 [2], solidifying polymers’ role as essential materials. However, the environmental costs associated with polymer production are severe, including significant resource depletion, greenhouse gas emissions, and persistent waste accumulation. In 2022 alone, plastic-related emissions were estimated at approximately 1.8 billion tons of CO₂-equivalent, primarily due to fossil-based feedstocks and energy-intensive manufacturing processes [3,4]. In addition to emissions, plastic waste generation remains a pressing issue, with over 300 million tons produced annually and less than 9% effectively recycled [5,6]. This waste contributes to marine pollution and strains landfill capacities, exacerbating environmental degradation. As the impacts of climate change and resource scarcity intensify, there is an urgent need to transition polymer production toward sustainable practices. Environmental Impact Assessment (EIA) frameworks are designed to evaluate and guide industrial sustainability; however, current models often exhibit critical shortcomings when applied to the polymer sector. Traditional EIA approaches typically isolate stages such as raw material extraction or end-of-life waste disposal [7,8].

Life Cycle Assessment (LCA) remains the primary method for evaluating environmental impacts throughout the polymer life cycle. EIA models must consistently apply LCA across the supply chain process. LCA is now considered a key approach to assessing the sustainability of polymers. Still, differences in goal definitions, functional units, and system boundaries among studies make comparisons difficult [9]. For instance, LCA studies have shown that the feedstock type greatly influences carbon emissions, with bio-based polymers reducing CO₂ outputs by up to 60% compared to fossil-based alternatives [9]. Nevertheless, such findings are seldom systematically incorporated into broader EIA methodologies. One of the limitations of existing models is the absence of an integrated evaluation of feedstock selection, process optimization, energy efficiency, recycling strategies, and waste management practices, factors inherently interconnected and collectively shape sustainability outcomes. The fragmented treatment of these aspects results in inconsistent environmental evaluations and limits the utility of EIA in informing sustainable development strategies [10]. Furthermore, the lack of standardized sustainability metrics complicates benchmarking efforts and impedes alignment with international targets, such as the carbon reduction goals outlined in the Paris Agreement [11].

Industrial polymer production has a significant environmental impact because it relies on non-renewable resources and energy-intensive processes. The carbon footprint of polymer manufacturing is high, resulting from raw material extraction, production, and disposal at the end of the product life cycle [12]. Developing sustainable technologies for biopolymer creation and post-consumer recycling should follow sustainable chemistry principles, focusing on renewable resources, reducing environmental harm, and improving conversion efficiency. In industrial polymer manufacturing, the choice of raw materials, production methods, and end-of-life disposal significantly influence the environment. Therefore, selecting bio-based feedstocks, eco-friendly production techniques, and sustainable recycling practices is essential for reducing the industry’s environmental footprint [12].

The environmental impacts of polymer products vary greatly depending on assumptions about end-of-life scenarios. For example, mechanical recycling typically offers a better environmental profile than incineration or landfilling but relies heavily on effective collection and sorting systems [8,9]. Furthermore, to justify the need for the SCM-EIAPP (Sustainable Conceptual Model for Environmental Impact Assessment in Polymer Production) model, the authors in [13] found that 42% of the studies they reviewed included full-scale LCA, highlighting the importance of more comprehensive environmental assessments.

This study proposes a Sustainable Conceptual Model for Environmental Impact Assessment in Polymer Production (SCM-EIAPP) to address these deficiencies. Although there are many literature reviews [5,6,7,8,9,10,11,12,13], to our knowledge, none have constructed a model that includes the influencing factors for sustainable EIA in polymer production. The primary contribution of this research is to identify the factors that influence it and propose an actionable theoretical framework for EIA in the polymer industry. Environmental improvement can be achieved when considered jointly. The proposed model in this study allows researchers to address the following specific research questions:

RQ: How can integrating these factors within an EIA framework improve the accuracy and practical applicability of sustainability assessments in polymer manufacturing?

By narrowing the analytical scope to these key areas, the research offers a deeper and more integrated exploration of critical sustainability challenges and potential solutions. We performed a PRISMA-guided systematic review of peer-reviewed studies from 2015 to 2025 and used MMAT to ensure consistent quality assessment across qualitative, quantitative, and mixed-methods evidence. The combined findings were summarized into five key sustainability levers—Choice of Feedstock, Process Optimization, Energy Efficiency, Waste Management Practices, and Recycling Options—that serve as the foundation of the proposed SCM-EIAPP framework. To enhance the framework’s practical application, we also conducted an initial pilot validation to evaluate construct reliability and validity, supporting preliminary hypotheses testing.

The paper is organized as follows: Section 2 reviews methodology and analysis on sustainability factors in polymer EIA models; Section 3 presents the results; Section 4 discusses theoretical and practical implications; Section 5 concludes with recommendations for sustainable polymer production.

2. Methodology and Analysis

A systematic literature review (SLR) was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Supplementary Materials) to ensure a rigorous and transparent process [14,15,16]. Comprehensive searches were performed across Scopus, Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, and SpringerLink using keywords such as “sustainability in polymer production”, “EIA in polymers”, “circular economy in plastics”, “recycling technologies for polymers”, and “life cycle assessment (LCA) of polymer manufacturing”. Also, Boolean combinations (AND/OR) were adopted. The search concepts employed combinations such as (“Sustainability” OR “EIA” OR “Circular Economy”) AND (“Polymer Production” OR “Plastic Manufacturing” OR “Recycling Technologies”). We considered only English-language articles to maintain consistency in language. The review targeted peer-reviewed articles published between 2015 and 2025, focusing on empirical and theoretical contributions addressing sustainable polymer production’s environmental, economic, and technological aspects. Articles broadly covering plastics without a clear sustainability component were excluded. The search window was purposely set from 2015 to 2025 to emphasize recent evidence and enable consistent comparison across studies. The year 2015 marks a well-known shift in sustainability policy and reporting, after which research on sustainable manufacturing, circular economy strategies, and standardized life-cycle environmental assessments grew rapidly and increasingly influenced polymer-sector practices. Additionally, many technologies related to polymer production, recycling, and energy efficiency have significantly progressed over the past decade. Including older studies could introduce inconsistencies due to differences in baselines, system boundaries, and metrics. The end year, 2025, represents the most recent complete publication year at the time the database searches were completed, ensuring the synthesis reflects the latest peer-reviewed evidence.

The selection process followed four PRISMA phases: Identification: 350 articles were retrieved based on titles, abstracts, and keywords. Screening: Duplicates, gray literature, non-indexed sources, and conference proceedings were removed, narrowing the selection to 220 peer-reviewed journal papers. Eligibility: A detailed assessment excluded articles focused solely on polymer synthesis, mechanical properties, or unrelated industrial topics, resulting in 89 eligible studies. Inclusion: The final set of 89 articles offered empirical insights into environmental impact assessments (EIAs) and sustainable polymers.

The final 89 articles provided empirical insights into environmental impact assessments (EIAs) and sustainable polymers. These themes were chosen to narrow down the extensive polymer literature. Studies solely on chemical synthesis pathways (like molecular bonding) or mechanical property optimization (such as tensile strength) were excluded, as they do not provide direct environmental data despite their technical relevance. Priority was given only to studies that focus on ‘carbon footprint reduction,’ ‘pollution control strategies,’ and ‘renewable feedstocks,’ since these offer the essential empirical evidence needed for populating the environmental variables of the SCM-EIAPP model. Figure 1 illustrates the PRISMA flow diagram summarizing the selection process. This streamlined and systematic approach ensures the review captures the most critical advancements and establishes a strong foundation for developing the Sustainable Conceptual Model for Environmental Impact Assessment in Polymer Production (SCM-EIAPP).

• Quality Assessment:

To maintain methodological thoroughness, this study utilized the Mixed Methods Appraisal Tool [17] to assess the quality of the included studies. The MMAT was chosen because it accommodates various study designs—qualitative, quantitative, and mixed-methods—found in our sample. Each study was examined using MMAT screening questions and design-specific criteria, focusing on the clarity of research questions, the appropriateness of methods, the sufficiency of data collection, and the transparency of analysis. The evaluation results are summarized in

Table 1. Mixed methods appraisal tool for criterion selection.

Criterion Questions	Yes/No	Comments
1. Are the research questions clearly defined?	Yes	The question asks: “How can integrating these factors into an EIA framework improve the accuracy and usefulness of sustainability assessments in polymer manufacturing?”
2. Can the collected data sufficiently answer the research questions?	Yes	Data from 89 studies + pilot quantitative test directly addresses the RQ.
For Systematic Review Component
1. Is the qualitative approach appropriate to answer the research question?	Yes	A systematic review (PRISMA-based) is appropriate for mapping influencing factors.
2. Are the data collection methods adequate?	Yes	Databases (e.g., Scopus, WoS) were searched, and peer-reviewed articles were considered.
3. Are the findings adequately derived from the data?	Yes	Factors (such as feedstock, waste, and recycling) are thematically synthesized in tables.
4. Is the interpretation of results adequately supported by data?	Yes	Tables (including a literature summary and influencing factors) support the interpretation.
5. Is interpretation?	Yes	Overall, coherence exists.
For Quantitative Component (Pilot Validation)
1. Is the sampling strategy relevant to address the research question?	Yes	A pilot study is mentioned.
2. Is the sample representative of the population?	Yes	Representativeness is clear.
3. Are measurements appropriate (i.e., valid and reliable)?	Yes	Reliability is high (Cronbach’s α > 0.80); validity has been partially tested.
4. Is there an acceptable risk of non-response bias?	No	According to our study, no risk is associated with non-response.
5. Is the statistical analysis suitable for addressing the research question?	Yes	Regression analysis aligns with the hypotheses.

, showing that most studies aligned well with their research aims and methods. However, some gaps were identified in the transparency of the sampling strategies. Including this quality assessment enhances the reliability of our review and promotes a transparent evaluation process.

3. Results

3.1. Descriptive Overview: Industry Context and Publication Trends

This study initiates by contextualizing polymer sustainability research within the broader global landscape and examining evolving publication trends to fulfill the descriptive objectives of a systematic review. As depicted in Figure 2, Figure 3 and Figure 4, global plastic production has grown substantially from 1950 to 2022 and is projected to continue rising through 2050. The production remains predominantly concentrated in vital regions such as China, North America, and Europe. Furthermore, the volume of global plastic waste has increased markedly, particularly from 2016 to 2020.

Figure 5 illustrates annual publication trends derived from targeted keyword searches for the period 2014–2024. The data reveal a pronounced upward trajectory in research activity, with publications concerning “natural polymer” experiencing a notable surge—particularly in environmental applications—followed by a significant growth in “synthetic polymer” topics, which peaked around 2021–2022. The observed decline in 2024 should be interpreted with caution, as the database covers only January to March 2024. Overall, these trends emphasize both the magnitude of the global polymer challenge and the rapid expansion of sustainability-oriented research, underscoring the need for a structured review to facilitate better understanding and consolidation.

3.2. Industrial Polymer Production Processes and Their Environmental Impacts

Industrial polymer production involves complex processes critical for modern society [19]. Key stages include polymerization methods, such as addition and condensation polymerization. In addition, polymerization involves monomers reacting without generating by-products, producing polymers such as polyethylene and polypropylene [20]. Small molecules are released as by-products in condensation polymerization, resulting in materials like polyesters and polyamides [21,22]. Raw material extraction, primarily from fossil fuels such as crude oil and natural gas, supports polymer demand but leads to environmental degradation, habitat destruction, biodiversity loss, and increased greenhouse gas emissions [23,24]. During polymer synthesis, monomers are transformed into long chains through chemical reactions, often requiring catalysts and solvents that generate hazardous waste and risk environmental contamination [25]. Industrial polymer production poses several environmental challenges throughout its life cycle, impacting air quality, water systems, and waste management. Manufacturing processes such as synthesis, extrusion, injection molding, and blow molding consume large amounts of energy, especially when fossil fuels are the primary source, leading to significant greenhouse gas emissions [26,27,28,29]. In addition to climate change, air pollution can result from VOCs released during synthesis, which contribute to smog formation [30], while the extraction and transportation of fossil fuels add particulate matter and emissions [31]. Water contamination risks arise from chemicals and solvents released during production, threatening aquatic ecosystems and human health [14,15,16,19]. Poor end-of-life handling results in persistent plastic waste, which causes marine pollution and threatens biodiversity [20,21,22,23]. These interconnected issues emphasize the need for holistic, life-cycle-based approaches to assess and mitigate the environmental impacts of polymer production [32,33,34,35,36]. Significant waste is generated during polymerization and manufacturing, and ineffective waste management practices lead to persistent environmental pollution [37,38,39]. Furthermore, the processes involved contribute substantially to CO₂ and CH₄ emissions, recognized as major drivers of global warming [40,41,42,43]. The literature reflects growing awareness of these environmental challenges, emphasizing air and water pollution, energy demands, waste issues, and carbon emissions [13,14,15,16,19,44,45,46,47]. The geographic coverage of the evidence base is uneven. Of the final set of 89 studies, only a few focus specifically on the environmental impacts of polymer production in the Gulf/GCC regions. Notably, one study examines the effects of polypropylene production and the recycling opportunities within the GCC. This underscores the necessity of more localized environmental evaluations tailored to regional industrial practices and waste management systems [38,39,40,41,42], indicating opportunities to enhance global sustainability efforts in the polymer industry.

Recent literature reviews emphasize the need to reform traditional polymer production methods to minimize their significant environmental impact. The entire life cycle of conventional polymers (that are petroleum-based) substantially contributes to greenhouse gas emissions, water pollution, and microplastic pollution. These insights are crucial for understanding the environmental effects of polymer manufacturing and for developing comprehensive models that incorporate both process-level and life-cycle-wide sustainability strategies [13].

3.3. Focusing the Scope: Sustainable Practices in the Polymer Industry

The articles reviewed, summarized in

Table 2. Summary of literature and gap analysis in sustainable practices of polymer industries.

Refs.	Research Area	Findings	Expected Future Work & Gap Research
[48]	Sustainable polymer processing techniques	Examined energy-efficient polymer processing methods.	Investigate the scalability and commercialization of energy-efficient processes.
[49]	Recycling of electronic waste in polymer production	Focus on reusing polymers from electronic waste.	Develop improved methods for extracting and purifying polymer materials from electronic waste.
[50]	Bio-based polymers in the packaging industry	Discusses bio-based polymers for sustainable packaging.	Evaluate the cost-effectiveness and scalability of bio-based polymers for packaging.
[51]	Sustainable materials in automotive manufacturing	The framework enables selecting sustainable materials.	Enhance the robustness of the model and explore diverse alternatives in material selection.
[52]	Zero waste manufacturing (ZWM)	Focus on recycling and eco-friendly production.	Develop techniques for chemical waste handling and sustainability in specific industries.
[53]	Cloud manufacturing for process sectors	CM aids in waste valorization and process improvements.	Advance CM applications in waste management and process sectors.
[54]	Sustainable polymers (degradable)	Focus on degradable polymers and chemical recycling methods.	Optimize the performance of sustainable polymers to meet industry standards.
[55]	Environmental sustainability of additive manufacturing	AM reduces material waste but needs better environmental impact analysis.	Conduct a detailed EIA comparing AM with traditional methods.
[56]	Development of advanced membrane materials	Focus on renewable materials for membranes.	Research on micro/nanofabrication for next-gen membranes.
[57]	Renewable bio-composites	Discusses methods for developing bio-composites.	Perform life-cycle assessments of bio-composites’ environmental impact.
[58]	Sustainable polymers from renewable resources	Focus on login as a precursor for sustainable polymers.	Further, explore lignin’s polymerization potential.
[59]	PET-RAFT polymerization for precision manufacturing	PET-RAFT process supports green, sustainable polymer production.	Optimize the PET-RAFT process for efficiency and scalability.
[60]	Green chemistry in polymer reaction engineering	Applies green chemistry principles to polymer production.	Investigate non-toxic alternatives and reduce VOCs in polymer products.
[61]	Sustainable PHAs production	PHAs reduce emissions and waste and support green innovation.	Develop market strategies and applications for PHAs.
[62]	Environmental impact of polymer membrane production	Focus on the polymer and solvent choices that affect environmental performance.	Explore wastewater treatment impacts on membrane production.
[63]	Bio-composites from plant fibers	Recycling plant fibers has a lower environmental impact than landfilling.	Focus on improving fiber-to-polymer adhesion for better bio-composite performance.
[64]	Circular economy in polymer manufacturing	Explores the potential of circular economic strategies in polymer production.	Design optimized circular economy models for polymer industries.
[65]	Sustainable polymerization methods for renewable resources	Investigate low-energy polymerization of bio-based polymers.	Scale up the polymerization methods for industrial use in polymer production.
[66]	Innovations in biodegradable plastics	Focus on the development of new biodegradable polymer materials.	Conduct life-cycle assessments of new biodegradable polymers in real-world applications.

, offer significant insights into sustainability efforts within the polymer industries, emphasizing environmental factors. Table 1 includes key details, such as authorship, publication information, and summaries of the main findings and discussion. Topics explored encompass sustainable material choices, environmentally friendly manufacturing methods, waste management strategies, and the circular economy within the polymer sector. This selective search facilitates a deeper understanding of the specific challenges and issues surrounding implementing sustainable practices in the polymer industry.

Table 2 provides a comprehensive overview of key research gaps in sustainable polymer production, emphasizing the critical challenges that hinder the industry’s transition to environmentally responsible practices. Despite growing awareness of sustainability, the practical implementation of sustainable manufacturing strategies remains a significant barrier due to resource constraints, technological limitations, and concerns about economic feasibility. Polymer manufacturers often face difficulties integrating sustainable processes, including the high cost of bio-based feedstock, inefficient energy utilization, and inadequate waste management infrastructure. These challenges underscore the pressing need for interdisciplinary research that integrates industrial engineering, materials science, and environmental policy to develop scalable and cost-effective solutions for sustainability. A significant research gap lies in the comprehensive life cycle assessment (LCA) of emerging polymer production techniques and alternative feedstocks [49,50,51,52,53]. While bio-based and recycled polymers have gained attention, existing LCA studies often lack depth in evaluating their long-term sustainability across multiple environmental dimensions, such as water footprint, carbon emissions, and land use impact. Future studies should adopt holistic LCA frameworks that assess the entire supply chain, from raw material sourcing to end-of-life disposal, to provide actionable insights into minimizing the ecological footprint of polymer production. Furthermore, there is insufficient research on the trade-offs between bio-based and petroleum-based polymers, particularly regarding durability, recyclability, and energy consumption in large-scale production. Research indicates that the polymer industry is shifting towards production methods focused on environmental responsibility and economic sustainability [24,26]. Sustainable polymers such as PLA and PHA are increasingly considered replacements for fossil-fuel-based plastics, contributing to environmental protection by minimizing carbon emissions and offering biodegradability [12].

Another critical gap is the limited understanding of bio-based polymers’ long-term environmental performance and scalability [61,62,63,64]. Although these materials present a promising alternative to fossil-based plastics, their degradation behavior, chemical stability, and environmental persistence over extended periods remain underexplored. Research should focus on comprehensive biodegradability studies under real-world conditions to assess potential microplastic formation, soil and water contamination risks, and the overall viability of bio-based polymers in diverse industrial applications. Additionally, large-scale production challenges, such as feedstock availability, processing efficiency, and economic competitiveness, must be systematically investigated to support widespread adoption. Energy efficiency in large-scale polymer manufacturing remains relatively underexplored, despite its significant potential to reduce carbon emissions. This gap largely stems from limited empirical research on incorporating renewable energy sources and optimization methods. To fill this void, the SCM-EIAPP framework specifically includes ‘Energy Efficiency’ and ‘Process Optimization’ as separate, quantifiable components. By integrating these often-neglected factors into a comprehensive model, the study seeks to establish the theoretical basis for assessing their combined influence on environmental sustainability. Future studies should focus on developing and validating innovative energy-saving technologies, such as hybrid polymerization processes, heat recovery systems, and AI-driven process automation. Collaborative research with industry partners through case studies and pilot projects could provide valuable real-world insights into these energy-efficient innovations’ economic and environmental benefits. Moreover, the development of innovative recycling technologies represents another pressing research gap. Current methods, such as mechanical and chemical recycling, face limitations in processing complex polymer composites, multi-layer packaging, and thermosetting plastics. Advanced recycling techniques, including solvent-based depolymerization, enzymatic degradation, and molecular-level upcycling, require further exploration to enhance efficiency, reduce energy input, and minimize secondary pollution. Future research should focus on assessing the environmental and economic feasibility of these emerging recycling technologies and their integration into circular economy frameworks to achieve higher recycling rates and waste reduction within the industry.

Another overlooked research area is the effectiveness of existing regulatory frameworks in driving sustainable polymer production. While environmental policies and industry standards aim to promote sustainability, there is insufficient empirical evidence on their impact on manufacturing practices and corporate compliance. Future studies should conduct comparative analyses of different regulatory approaches across regions, identifying best practices that encourage sustainable innovations. Policymakers should be provided with evidence-based recommendations for refining regulations, incentivizing green technologies, and fostering industry-wide adoption of environmentally responsible manufacturing.

3.4. Comparison with Existing EIA Frameworks

To highlight the novelty of the SCM-EIAPP, it is compared with established approaches from the literature [48,49,50,51,52,59,60,61,62,63]. For example, ref. [51] presents a multi-criteria decision analysis for sustainable manufacturing, while refs. [62,63] focus on environmental impact assessments, such as EIA. Other sources [52,60] discuss sustainability but lack formal, integrated models. Table 1 summarizes these findings, illustrating how SCM-EIAPP advances by integrating key factors into a unified, testable framework for polymer-specific EIA, filling gaps in integration and validation.

SCM-EIAPP initially considers its factors as independent to facilitate testing and analysis. However, this simplification can hinder understanding real-world interconnections, such as how varying feedstock choices influence energy efficiency. We acknowledge that this independence assumption constitutes a significant limitation, as it neglects potential interactions and trade-offs. Moving forward, it is advisable to incorporate these interconnected relationships. Employing Structural Equation Modeling (SEM) or network analysis could enhance the framework’s accuracy in representing systemic relationships.

Table 3. Comparison of SCM-EIAPP with prior EIA frameworks.

Framework/Approach	Key Factors Included	Integration of Factors	Focus Area	Limitations	How SCM-EIAPP Advances
Sustainable materials in automotive manufacturing [51]	Material selection, sustainability criteria (environmental, economic, social)	Moderate (links criteria via decision analysis but limited to automotive context)	Sustainable material selection in the automotive industry	Lacks depth in polymer-specific production factors; requires enhanced robustness for diverse alternatives.	SCM-EIAPP expands to include polymer production by focusing on key factors such as feedstock and recycling, while also testing hypotheses to improve the applicability for EIA.
Zero waste manufacturing (ZWM) [52]	Recycling, eco-friendly production, waste valorization	Low (multidisciplinary review; discusses processes but isolates sectors)	Zero-waste strategies across industries, including polymers	Overlooks specific chemical waste handling in polymer contexts; not a formal model.	SCM-EIAPP integrates waste management as a core factor with empirical validation, bridging gaps in targeted polymer sustainability.
Environmental impact of polymer membrane production [62]	Polymer/solvent choices, energy use, emissions, wastewater	Moderate (assesses production impacts but focuses on membranes)	EIA for membrane manufacturing processes	Limited to specific products; overlooks broader interdependencies, such as recycling.	SCM-EIAPP broadens to general polymer production.
Life-Cycle and EIA Review on Plant Bio-Composites from plant fibers [63]	Feedstock (plant fibers), processing, life-cycle impacts, biodegradability	Moderate (reviews LCA/EIA but treats stages somewhat independently)	Environmental assessments of bio-composites	Addresses adhesion and processing issues but does not include a comprehensive model for complete polymer sustainability.	SCM-EIAPP synthesizes similar factors into a unified model with pilot validation.
SCM-EIAPP (Proposed)	Waste Management, Recycling Options, Choice of Feedstock, Process Optimization, Energy Efficiency.	Moderate (treats factors as independent	Polymer production sustainability with EIA focus	Assumes factor independence; limited to selected variables.	Develops a clear, testable model that links theory and practice through well-formed hypothesis validation.

addresses specific gaps in integration and validation, demonstrating the evolution of SCM-EIAPP by integrating key factors into a unified, testable model for polymer-specific EIA, thereby addressing previous gaps in integration and validation.

Model Assumptions and Justification

Table 3 illustrates that SCM-EIAPP advances previous EIA-focused frameworks. First, many existing methods are limited or context-specific, often focusing on one or two areas such as emissions, waste, or energy, without considering upstream decisions and downstream management as a connected sustainability challenge. In contrast, SCM-EIAPP combines the five main levers identified in the literature into a comprehensive framework directly applicable to polymer manufacturing. Second, the framework enhances practical usefulness by turning these levers into testable hypotheses and providing initial empirical evidence through a pilot study, moving beyond purely theoretical models. Third, it clarifies the current model’s boundaries: SCM-EIAPP focuses on the most actionable production and management factors, offering a structured approach to improving EIA while allowing future expansion to include additional system components, such as supply-chain interactions and trade-offs, as more data and scope become available.

Finally, in the Environmental Impact Assessment (EIA) field, there is a lack of comprehensive studies on end-of-life scenarios and their implications for polymer waste management. Existing research often neglects long-term environmental monitoring, leading to an incomplete understanding of how disposal methods, such as landfilling, incineration, and biodegradation, affect ecosystems over time. Longitudinal studies are needed to assess the cumulative environmental effects of polymer production and disposal while identifying opportunities for improvement in waste reduction and resource recovery. Additionally, social factors, including worker health and safety, public perception, and community engagement, are frequently overlooked in EIA studies. Incorporating these aspects into future research is essential for achieving socially responsible and sustainable polymer production. Furthermore, region-specific studies are needed to account for environmental conditions, regulations, and industrial capabilities variations. Climate, waste management infrastructure, and energy availability affect sustainable polymer production differently across geographic locations. Research tailored to specific regions will ensure that sustainability strategies are locally relevant and globally scalable. Additionally, emerging technologies, such as biodegradable polymers and nanomaterial-based composites, should be prioritized in future studies to facilitate responsible implementation and regulatory approval. By addressing these gaps, research can contribute to developing more sustainable, economically viable, and environmentally friendly polymer production systems.

3.5. Influencing Factors on Environmental Impact in Polymer Production

The environmental impact of polymer production is influenced by various factors throughout its life cycle. These factors include feedstock choice, process optimization, waste management, energy efficiency, and recycling options, all of which play significant roles in shaping the ecological footprint and sustainability of the process. This section discusses each influencing factor in detail, providing supporting references and corresponding tables.

3.5.1. Choice of Feedstock

The selection of feedstock used in polymer production directly impacts its environmental consequences. Raw materials sourced from fossil fuels, such as crude oil and natural gas, are associated with higher carbon footprints due to their non-renewable nature and high carbon content [44,45,46,47,48,49]. On the other hand, using renewable, bio-based feedstocks can help reduce reliance on fossil fuels, making the polymer production process more sustainable [67,68].

Table 4. Factors related to “Choice of Feedstock” in polymer production.

Measurement Items	Short Definition	References
Raw Material Origin	The source and origin of the raw material used in polymer production.	[12]
Carbon Footprint	The amount of greenhouse gas emissions produced during the extraction and processing of the feedstock.	[38,39]
Resource Renewability	The extent to which the feedstock is renewable and can be replenished over time.	[19]
Environmental Impact	The overall environmental consequences of using the particular feedstock in polymer production.	[26,34,41,42,44]
Sustainability	The ability of the feedstock to meet current needs without compromising future generations.	[24,26,39,41,42,44,68]
Biodegradability	The ability of the feedstock or resulting polymer to break down naturally in the environment.	[25]
Ecological Footprint	The total impact of feedstock on the environment in terms of resource consumption and waste generation.	[13]

summarizes the factors related to the “Choice of Feedstock” in polymer production.

3.5.2. Process Optimization

Process optimization plays a critical role in reducing the environmental impact of polymer production. Technological advancements and improved engineering practices can significantly reduce energy consumption, waste generation, and emissions. Employing efficient polymerization methods and refining production techniques helps optimize resource use and minimize environmental impact [12,13,14,15,57,69,70,71].

Table 5. Factors related to “Process Optimization” in polymer production.

Measurement Items	Definition	References
Reaction Conditions	Adjusting temperature, pressure, and catalyst concentration enhances reaction efficiency and reduces energy consumption.	[3,12,25]
Reaction Kinetics	Understanding the reaction kinetics to optimize the reaction rate and control the product’s molecular weight and properties.	[71]
Solvent Selection	Choosing appropriate solvents improves reaction efficiency, minimizes waste, and reduces environmental impact.	[22,72]
Yield and Selectivity	Maximizing the yield of desired products while minimizing the formation of undesirable by-products.	[4,25,27]
Recycling and Reuse	Implementing recycling and reuse strategies for reactants, catalysts, and solvents to minimize resource consumption.	[3,4,12,27,57]
Continuous Processing	Adopting continuous manufacturing processes to increase productivity, reduce cycle times, and improve energy efficiency.	[25]
Process Monitoring and Control	Employing real-time monitoring and control techniques to ensure process stability and consistency.	[2,3,4,5,69]

presents key factors related to process optimization in polymer production.

3.5.3. Waste Management Practices

Proper waste management practices are essential to mitigating the environmental impact of polymer production. Efficient waste handling, recycling, and reuse strategies can significantly reduce pollution and the burden on natural resources [8,9,10,11,20,21,22,23,73,74]. Effective waste management is crucial to advancing sustainability and minimizing the environmental impact of polymer production.

Table 6. Factors related to “Waste Management Practices” in polymer production.

Measurement Items	Definition	References
Waste Segregation and Sorting	Separating and categorizing different types of waste for efficient processing and recycling.	[74]
Recycling and Reclamation	Recovering and reusing materials from waste to reduce the demand for new resources.	[8,22,23]
Waste Minimization	Implementing measures to minimize waste generation during the production process.	[73,74]
Composting and Biodegradation	Allowing organic waste to decompose naturally converts it into nutrient-rich compost.	[25]
Energy Recovery from Waste	Extracting energy from waste materials through various processes, such as incineration.	[73,74]
Landfill Management	Properly managing waste disposal in landfills to minimize environmental impacts.	[73]
Extended Producer Responsibility (EPR)	Holding producers responsible for the disposal and recycling of their products.	[13,28]

outlines the critical factors involved in waste management practices in polymer production.

3.5.4. Energy Efficiency

Energy efficiency plays a key role in determining the environmental impact of polymer production. Reducing energy consumption and associated greenhouse gas emissions through technological innovations and adopting renewable energy sources can significantly lower the industry’s carbon footprint [28,29,37,38,54,75,76,77].

Table 7. Factors affecting environmental impact in polymer production: “Energy Efficiency”.

Measurement Items	Definition	References
Process Optimization	Implementing technological advancements and best practices to reduce energy use.	[20]
Energy-Efficient Equipment	Utilizing machinery and tools designed for energy efficiency and reduced emissions.	[4,12,54]
Waste Heat Recovery	Capturing and reusing waste heat from processes to improve overall energy efficiency.	[43]
Cogeneration	Simultaneous generation of electricity and heat to optimize energy utilization.	[20]
Energy Monitoring and Control	Implementing real-time monitoring and control systems to manage energy consumption.	[4,5]
Alternative Energy Sources	Integrating renewable energy sources like solar and wind power into the process.	[4]
Life Cycle Energy Analysis	Assessing energy use throughout the product’s life cycle to optimize energy efficiency.	[70]

outlines the key factors influencing energy efficiency in polymer production.

3.5.5. Recycling Options

Recycling is a vital aspect of reducing the environmental impact of polymer production. Recycling polymer waste minimizes the demand for new raw materials and helps divert plastic waste from landfills, promoting a circular economy [6,7,8,9,16,19,20,21,22,23,24,26,27,32,33,34,35,72,78]. Recycling infrastructure for bio-based polymers is limited because of inconsistent waste stream availability and contamination risks. Although mechanical recycling is technically feasible, current economic and logistical challenges make it an unattractive option at scale [72,78]. Developing effective recycling technologies is key to achieving sustainability in the polymer industry.

Table 8. Factors affecting environmental impact on polymer production: “Recycling Options”.

Measurement Items	Definition	References
Material Recycling	Reusing post-consumer and post-industrial waste materials to create new polymer products.	[3,34]
Closed-Loop Recycling	Establishing a continuous recycling process to maintain the value of materials over time.	[2,3,23]
Mechanical Recycling	Mechanically processing waste plastics to produce recycled pellets for new applications.	[2,3,24]
Chemical Recycling	Using chemical processes to break down polymers into monomers for new polymer synthesis.	[2,3,24]
Feedstock Recycling	Converting plastic waste into feedstock for other chemical processes or energy production.	[37,57]
Upcycling	Transforming waste materials into products of higher value or quality.	[33]
Extended Producer Responsibility	Holding producers responsible for the recycling and recovery of their products.	[13,28]

summarizes the factors related to recycling options.

4. Discussion

4.1. Conceptual Model for Sustainable Polymer Production

The environmental implications of polymer production have prompted researchers, policymakers, and industry leaders to explore sustainable solutions that minimize ecological harm while maintaining economic feasibility [25,26,27,32,33]. The core of a sustainable polymer strategy involves balancing economic viability, environmental protection, and social responsibility [39]. Achieving sustainability in polymer manufacturing requires a comprehensive approach integrating key independent variables, including choice of feedstock, process optimization, energy efficiency, waste management practices, and recycling options to assess and mitigate environmental impacts [48,49,50,51,52,53,54,55,56]. These factors not only affect sustainability individually but are also highly interdependent, with changes in one factor often influencing the outcomes of others, thereby shaping the overall environmental footprint and feasibility of transitioning towards a circular economy [68,69,70,71].

The choice of feedstock is a critical determinant in reducing the environmental footprint of polymer production. Conventional fossil-fuel-derived polymers contribute significantly to carbon emissions and resource depletion, prompting a growing interest in bio-based alternatives [79,80,81]. Bio-based polymers from renewable materials such as starch, cellulose, and algae offer a promising solution; however, their sustainability is contingent on agricultural resource availability and land use efficiency [46,51,52,53,72,78,82,83,84]. Intensive use of fertilizers and pesticides during cultivation can offset the environmental benefits, underscoring the need for integrated assessments that simultaneously consider material performance, energy demands, and ecological impacts [85]. Process optimization enhances the efficiency of polymer manufacturing by reducing waste generation and energy consumption. Advances in catalytic polymerization, precision synthesis techniques, and automation have significantly improved production processes [86,87,88]. Yet, their widespread adoption faces barriers such as high costs and technical complexity, particularly in regions with outdated industrial infrastructures [26,28,89]. Optimizing processes also affects waste management efficiency and energy consumption, as streamlined manufacturing produces fewer off-spec materials and requires less energy per production unit. Energy efficiency is another key pillar of sustainable polymer production. Polymer manufacturing is highly energy-intensive, involving substantial energy inputs for raw material processing, polymerization, and product formation [46,64,90,91]. Transitioning to renewable energy sources, such as solar and wind, can help reduce the carbon footprint [79]. Improvements in process heating, energy recovery systems, and smart manufacturing technologies further enhance energy performance [84]. Energy efficiency is directly interlinked with process optimization and recycling, as advanced processes often simultaneously reduce energy use and waste generation. Effective waste management practices are crucial for minimizing the ecological impacts of polymer production. Industrial polymer waste, including off-spec materials, byproducts, and hazardous residues, requires sustainable strategies such as chemical recycling, pyrolysis, and biodegradation technologies [60,61,62,63,64]. The effectiveness of waste management is interconnected with feedstock selection and process efficiency: sustainable feedstocks may generate more easily degradable waste, and optimized processes typically yield less waste. Recycling options further contribute to sustainability by extending the life cycles of materials and conserving resources. Mechanical recycling is a cost-effective method, but it faces limitations due to polymer degradation over multiple cycles. In contrast, chemical recycling allows molecular recovery, although it requires significant energy [12,13,14,15,16,19,57,58,59,60,61]. The success of recycling initiatives is influenced by feedstock types (since some bio-based polymers degrade differently), waste management capabilities, and the overall energy profile of the recycling processes [72,76,77]. Advanced methods like chemical recycling, pyrolysis, and waste valorization techniques such as game changers for closing the loop in polymer production are covered in [2,23].

4.2. Justification and Theoretical Foundations

The proposed conceptual model integrates five independent variables Choice of Feedstock, Process Optimization, Energy Efficiency, Waste Management Practices, and Recycling Options to examine their collective and individual impacts on the dependent variable, Environmental Impact Assessment (EIA) of Polymer Production. Grounded in sustainable manufacturing principles and the LCA framework, the model provides a robust basis for evaluating environmental performance in industrial processes. Theoretical foundations include the Circular Economy (CE) model, Sustainable Development Goals (SDGs), and Industrial Ecology principles, which emphasize minimizing resource inputs, waste generation, and environmental emissions [25,26,27,32,33]. The interaction between feedstock, energy use, and recycling highlights the systemic nature of environmental sustainability, where changes in one domain cascade through the production ecosystem.

4.3. Practical Utility of the Model

This model offers a framework for companies and policymakers to design strategies that simultaneously target multiple sustainability factors. For example, selecting bio-based feedstocks with low fertilizer requirements could reduce agricultural impacts and downstream waste toxicity, especially when paired with efficient recycling systems. Similarly, investing in energy-efficient processes can improve yield while reducing waste generation, enhancing overall sustainability. Figure 5 provides a conceptual model that illustrates how five independent variables—Choice of Feedstock, Process Optimization, Energy Efficiency, Waste Management Practices, and Recycling Options—collectively influence polymer production’s Environmental Impact Assessment (EIA). Each factor directly contributes to the overall environmental performance. The Choice of Feedstock affects emissions and resource usage at the very start of the production chain. Process Optimization improves operational efficiency, reducing waste and energy demands. Energy Efficiency initiatives lower carbon emissions and conserve resources. Waste Management Practices ensure that by-products are handled sustainably, minimizing environmental harm. Recycling Options reduce the demand for virgin materials and limit waste accumulation. By considering these interconnected variables together rather than in isolation, the model promotes a comprehensive understanding of how strategic improvements across multiple domains can synergistically enhance the sustainability of polymer production.

Numerous studies (e.g., [92]) support the inclusion of the feedstock, which compares the environmental impacts of synthetic fibers, such as PET and PA6, with bio-based alternatives like PLA. Bio-based fibers reduce the carbon footprint but face challenges in scalability and durability. The production of synthetic polymers remains common due to established infrastructure and lower costs.

Building on the comprehensive literature review from 2015 to 2025, this study introduces the SCM-EIAPP as an integrated framework. It considers five key sustainability levers across the product life cycle—Choice of Feedstock (CF), Process Optimization (PO), Energy Efficiency (EE), Waste Management Practices (WM), and Recycling Options (RO)—as primary, actionable factors that influence Environmental Impact Assessment (EIA) results in polymer manufacturing. The model assumes that each lever has a direct, justifiable effect on EIA performance: for example, feedstock choice impacts carbon footprint and renewability considerations (e.g., fossil versus bio-based inputs), process optimization reduces energy use, waste, and emissions through improved engineering and production methods, and energy efficiency decreases environmental impacts by reducing consumption and associated emissions by adopting technological innovations and integrating renewable energy sources.

Meanwhile, downstream practices like waste management and recycling are thought to reduce pollution and resource depletion by improving handling, recovery, and circularity—such as minimizing landfill waste and lowering reliance on virgin raw materials. Traditional EIA methods often evaluate life-cycle stages separately. Still, SCM-EIAPP integrates these aspects into a single, testable framework for a more comprehensive assessment of the environmental impacts of polymer production. For initial hypothesis testing, the framework simplifies the analysis by assuming the predictors are independent and focusing mainly on their direct effects. However, we recognize that in real-world situations, there are interdependencies and trade-offs, such as how feedstock choices can affect energy efficiency, that may be present.

4.4. Hypothesis Development

Hypothesis development is a critical step in the research process, where testable propositions are formulated to examine the relationships between variables. In the context of EIA for industrial polymer production, this study proposes hypotheses that empirically explore the influence of independent variables. Figure 6 depicts the integrated SCM-EIAPP framework. Instead of examining these factors separately, the model shows how the five independent variables from the literature review come together to shape the overall Environmental Impact Assessment (EIA). These hypotheses are structured to support quantitative analysis using statistical modeling.

H1. 

Choice of feedstock is associated with the environmental impact of polymer production; using bio-based feedstock leads to a statistically significant reduction in emissions compared to petroleum-based alternatives.

H2. 

Process optimization is associated with the environmental impact of polymer production; higher levels of process optimization are significantly linked to lower waste generation and energy consumption.

H3. 

Energy efficiency is associated with the environmental impact of polymer production; higher energy efficiency significantly reduces carbon emissions and resource depletion.

H4. 

Waste management practices are associated with the environmental impact of polymer production; more effective waste management practices significantly mitigate environmental pollution.

H5. 

Recycling options are associated with the environmental impact of polymer production; greater adoption of recycling technologies significantly reduces raw material consumption and waste accumulation.

4.5. Applicability and Potential Benefits of the SCM-EIAPP Model

The United Arab Emirates Polymers and Plastics Market is expected to expand from USD 467.3 billion in 2025 to USD 635.9 billion by 2031, registering a compound annual growth rate (CAGR) of 5.2% during the forecast period. This expansion is chiefly driven by substantial demand for lightweight, versatile materials across sectors, including automotive, packaging, and electronics [93]. Organizations such as Borouge, a joint venture between ADNOC and Borealis, are major international entities specializing in high-quality polyethylene and polypropylene resins utilized across diverse industries, including packaging, automotive, and infrastructure. The United Arab Emirates (UAE) serves as a regional hub. It is assuming a progressively global role in the polymer industry, hosting a diverse array of large-scale petrochemical producers alongside specialized polymer manufacturers. Carbokene observes that the UAE’s strategic geographic location, innovative manufacturing capabilities, and commitment to sustainability have enabled it to emerge as a significant player in the global polymer market [94]. Within this ecosystem, corporations such as Borouge (a joint venture between ADNOC and Borealis) supply polyethylene and polypropylene resins to major downstream sectors, including infrastructure, automotive, and packaging, while also engaging in circularity initiatives such as “Design for Recycling.” Additionally, alongside these global-scale resin producers, UAE-based firms bolster the region’s polymer value chain by producing masterbatch, packaging, construction chemicals, pipes/films, and custom plastic manufacturing, thereby catering to Gulf Cooperation Council (GCC) requirements and supporting exports to broader markets [94].

The primary objective of this paper is to identify the most significant factors that influence the assessment of environmental impact. Although the model is intended for worldwide use, its initial validation took place specifically in the Abu Dhabi polymer manufacturing environment. To validate the proposed framework, we will extend this work’s empirical studies and practical implications in a subsequent article. However, we are already investigating a case study about Polymers in the United Arab Emirates.

4.6. Pilot Study: Research Design, Tools, and Data Analysis

4.6.1. Measurements

In the following, we present the results of the quantitative pilot study, which employed a survey instrument to validate our model. The primary goal is to validate the internal consistency and reliability of the measurement scales and to conduct a preliminary test of the hypothesized relationships between constructs before deploying the primary survey. We build the constructs measured based on expertise in the field, and academics review these constructs. We are measuring the five constructs WM, RO, PO, CF, and EE, as well as independent variables, and the EIA as the dependent variable.

4.6.2. Population and Sampling Technique

Target Population

The target group for this research comprises professionals and experts within the United Arab Emirates polymer industry. Focus is on those involved in environmental, operational, and strategic decision-making roles. This includes polymer manufacturers, waste management and recycling firms, among others. Job roles vary from engineers across all disciplines, managers, operations supervisors, and additional positions. This group was chosen because they hold the practical, in-field expertise necessary for accurately assessing the model’s constructs.

Sampling Technique

The sampling method is best identified as Purposive Sampling, a form of non-probability sampling. This is due to the participant demographics indicating a deliberate focus on selecting specific respondents, namely experts from the polymer industry and related sectors.

4.6.3. Characteristics of the Pilot Study Group

The pilot study sample is representative. The sample comprises 68 respondents, with key characteristics including industry expertise and role expertise.

4.6.4. Survey Instrument and Design

We used a 5-point Likert Scale to assess responses, a method extensively validated for measuring attitudinal data in social and industrial research contexts [95]. Here, 1 indicates Strongly Disagree and 5 indicates Strongly Agree. The survey is multidimensional, assessing each construct with multiple items. Data Preparation and Software: We employed SPSS Version 31.0.0.0 (117) for descriptive and inferential analyses. Data cleaning: missing data were carefully managed.

4.6.5. Demographic Analysis

The distribution of the job role title (

Table 9. The description of the job role title of the pilot study sample.

Job Role Title	Frequency
Commercial	2
Director finance	1
Engineer (Chemical, Environmental, Industrial, Mechanical)	33
Legal Advisor	1
Operation Shift Supervisor	1
Operator	1
Plant VP/Manger	14
Project Planning	1
Research & Development Professional	3
Senior Operator	2
SHIFT SUPERVISOR	4
Supply chain manager	1
Sustainability Manager	1
Team leader operation	3
Total	68

), educational level (Figure 7), and the organization type (

Table 10. The distribution of the organization type of the pilot study sample.

Organization Type	Frequency
Polymer Manufacturer	37
Supplier of Raw Materials	7
Waste Management/Recycling	2
Control engineer	1
Corporate	1
Regulatory Body	8
Data provider	1
Education	1
Gas processing	1
Leadership	1
Medicine	1
Oil and gas	2
Petrochemicals	1
Project management	1
Research and development	1
Specialty polymers production	1
Versatile, Downstream & Upstream	1
Total	68

) is below.

4.6.6. Pilot Study Results/Model Validation Outcomes

To thoroughly validate the measurement model from the pilot study, a Confirmatory Factor Analysis (CFA) was performed. This analysis evaluated effectively the defined constructs, Waste Management (WM), Process Optimization (PO), Recycling Options (RO), Choice of Feedstock (CF), and Energy Efficiency (EE), represented the observed data. Additionally, Cronbach’s alpha was calculated for each construct to assess the internal consistency and reliability of the survey scales. These steps ensure that the instrument is both statistically robust and valid before proceeding to test the structural model and hypotheses.

As a result of the CFA, the item WM7 was deleted because it had a very low loading factor (less than 0.5). Moreover, deletion of WM7 improved Cronbach’s alpha from 0.783 to 0.870. Also, EIA10 had a loading factor less than 0.5, so it was removed. Cronbach’s alpha values for the constructs are presented in

Table 11. Cronbach’s alpha for the constructs.

Factor	Cronbach’s Alpha
Waste Management (6 items)	0.870
Choice of Feedstock (8 items)	0.852
Recycling Options (10 items)	0.868
Energy Efficiency (8 items)	0.880
Process Optimization (7 items)	0.888
Environmental Impact Assessment (9 items)	0.920

, and the detailed CFA loading [95] factors values are available in Appendix A.

The CFA was estimated in the pilot study, using a robust estimator (DWLS) suitable for categorical data. The model exhibited a good to excellent fit to the data: χ²(1019) = 1319.416, p < 0.001; CFI = 0.949; TLI = 0.945; RMSEA = 0.068 (90% CI). Both the CFI and TLI surpassed the recommended threshold of 0.95, in accordance with the stringent cutoff criteria suggested by Hu and Bentler [96], thereby indicating a robust model fit, and the RMSEA remained within the acceptable range. Nevertheless, the SRMR value of 0.101 marginally exceeded the ideal cutoff of 0.08, indicating some localized model misfit. Despite this, the strong performance of the primary comparative indices (CFI, TLI) affirms the robustness of the proposed factor structure and its validity for examining the hypothesized relationships within this research.

4.6.7. Simple Regression Analysis and Hypothesis Testing

Also, we utilized correlation and regression analysis to test the hypotheses. The testing results are shown in

Table 12. Hypotheses testing results.

Hypothesis	β (Standardized)	t (Test Value)	p-Value	Decision
H1 (CF)	0.752	9.051	<0.001	Accepted
H2 (PO)	0.712	8.047	<0.001	Accepted
H3 (EE)	0.794	10.363	<0.001	Accepted
H4 (WM)	0.606	6.051	<0.001	Accepted
H5 (RO)	0.821	11.425	<0.001	Accepted

. To test all hypotheses, we use regression analysis. The SPSS output reveals that both values for t (test value) and the β tell you that the relationship is highly statistically significant (p < 0.001) at a 95% confidence level. The overall results for all hypotheses can be summarized in Table 8.

4.6.8. Multiple Regression Analysis

Observing the five factors’ combined effect on the EIA is very valuable. Here are the results. The results of the multicollinearity test are presented in

Table 13. Collinearity Test Results.

	Standardized Coefficients	t	Sig.	Collinearity Statistics
	Beta			VIF
(Constant)		0.319	0.751
WM	0.054	0.489	0.062	2.545
RO	0.463	3.058	0.003	4.862
PO	0.096	−0.677	0.050	4.235
CF	0.21	1.711	0.092	3.188
EE	0.275	1.729	0.089	4.368

. The VIF values are less than 10, indicating no multicollinearity among the factors. Although none of the VIF values exceed 10, three predictors (PO and RO) have VIFs significantly above 3. This indicates a considerable overlap in variance among these two variables. From the output, we see RO has the most impact on the EIA.

The preliminary findings of the pilot study suggest that few relationships do not achieve statistical significance, and specific predictors demonstrate indications of multicollinearity. These estimates’ significance importance and precision are anticipated to improve with an increased sample size in comprehensive study. An expanded dataset will augment statistical power, thereby facilitating the identification of genuine effects. Consequently, the complete analysis is expected to yield more dependable and consistent coefficient estimates for all variables.

To clearly demonstrate how multicollinearity was addressed, we include the collinearity statistics (VIF) from the regression analysis in Table 13. The Variance Inflation Factor (VIF) values for all constructs range between 2.545 and 4.862. Since all values are comfortably below the conservative threshold of 10 (and even the stricter threshold of 5). Accordingly, the results indicate that multicollinearity is not a significant concern and does not compromise the stability of the parameter estimates.

4.7. Contributions of the Study to Theory, Industry Practice, and Policymaking

This study offers significant contributions to theory, industry practice, and policymaking, advancing academic understanding and practical approaches to improving sustainability in polymer production.

4.7.1. Contributions to Theory

This study enriches the theoretical framework surrounding the EIA of industrial polymer production by introducing a model that integrates key variables: Choice of Feedstock, Process optimization, Waste Management Practices, Energy Efficiency, and Recycling Options. By establishing the relationships between these independent variables and the environmental impact of polymer production, the study enhances theoretical models of sustainability and environmental management in industrial processes. Additionally, it contributes to the growing body of knowledge on how specific practices within production systems influence the overall environmental footprint, bridging gaps in research regarding sustainable polymer production and providing a basis for further exploration in the field.

4.7.2. Contributions to Industry Practice

This research offers practical and actionable insights into how polymer manufacturers can optimize their processes to minimize environmental impact and improve sustainability. The study establishes clear hypotheses that link key production factors, such as feedstock selection, energy efficiency, waste management, and recycling, to tangible sustainability outcomes. These insights offer industry stakeholders specific, implementable strategies. For instance, optimizing feedstock selection by encouraging the use of renewable or lower-impact raw materials can significantly reduce the carbon footprint of polymer products. Optimizing feedstock selection can significantly reduce the carbon footprint. The literature shows that switching to bio-based polymers can cut CO₂ emissions by as much as 60% compared to fossil-based alternatives. Additionally, enhancing energy efficiency by adopting energy-saving technologies, such as waste heat recovery systems, can lower energy consumption and operational costs. The research also highlights the importance of improving waste management practices, focusing on reducing waste generation, enhancing waste segregation, and integrating sustainable disposal methods, reducing environmental impact and improving cost-efficiency. Furthermore, the study stresses the critical role of recycling in reducing environmental burdens and offers practical methods for improving the efficiency of recycling processes. By integrating these practices, manufacturers can adopt circular economic principles, reducing their reliance on virgin materials and promoting sustainable production cycles. By adopting these recommendations, polymer manufacturers can improve their environmental performance, comply with evolving regulatory requirements, and strengthen their corporate sustainability initiatives. The findings from this study are designed to help industry stakeholders make informed, data-driven decisions that enhance both environmental and operational outcomes.

4.7.3. Contributions to Policymaking

The study has important implications for policymakers promoting sustainable practices in the polymer production industry. By highlighting the environmental impacts of various production factors, the research provides evidence to guide regulatory decisions and encourage the development of standards for sustainable manufacturing. Policymakers can use the findings to develop policies encouraging industries to adopt environmentally friendly practices, such as enhancing energy efficiency, optimizing waste management, and expanding recycling options. Furthermore, the study can inform the design of policy frameworks that support the transition toward a circular economy, encouraging the reduction in virgin material usage and the promotion of waste minimization strategies. This research provides a foundation for crafting policies that align industrial practices with global sustainability goals, ensuring long-term environmental protection and economic resilience.

4.8. Limitations and Recommendations for Future Work

While this study provides valuable insights into polymer production’s Environmental Impact Assessment (EIA) through a systematic literature review, it has some limitations. Addressing these limitations will help refine and enhance the understanding of sustainable practices within the polymer industry. First, we point out that the study is limited to literature published in English between 2015 and 2025. One of the limitations is the scope of the variables considered. The study focuses on five independent variables: Choice of Feedstock, Process Optimization, Waste Management Practices, Energy Efficiency, and Recycling Options. The importance of these factors is strongly reinforced by both the literature and expert perspectives in Abu Dhabi’s polymer manufacturing, where sustainable development agendas emphasize the responsible use of feedstock, improving energy efficiency, and strengthening recycling systems. While these factors are crucial to understanding the sustainability of polymer production, they do not encompass the full range of elements that may impact environmental outcomes. For instance, factors such as transportation and end-of-life disposal of products were not included. These elements could potentially have significant environmental impacts, and future research should explore their inclusion to develop a more comprehensive sustainability model for polymer production. Additionally, the influence of regional differences, such as varying access to technology, raw materials, and waste management systems, was not fully addressed. Future studies should investigate how the model performs in different geographical contexts and production settings to assess its broader applicability and relevance.

Although most existing models focus on environmental and technical aspects, it is increasingly important to consider social dimensions, particularly issues such as workplace safety, labor conditions, and potential health risks associated with exposure to polymers. This is a crucial topic that needs further research. Future studies should operate within circular economic frameworks for polymer production, including waste-to-energy methods and material recovery loops. The SCM-EIAPP model can help facilitate these transitions.

This includes examining worker health, safety, labor conditions, and community well-being—key elements of the broader impact of polymer production. Additionally, assessing the economic viability of bio-based options, energy-efficient methods, and recycling innovations is essential for promoting industry adoption and scalability. These efforts support the United Nations Sustainable Development Goals, especially SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action), and SDG 8 (Decent Work and Economic Growth). Incorporating a triple-bottom-line approach—considering environmental, social, and economic factors—into the SCM-EIAPP framework will enhance its utility, transforming it from solely an environmental assessment tool into a comprehensive guide for sustainable industrial transformation.

A further limitation of this research lies in its long-term focus. The current model does not account for long-term environmental impacts such as material degradation and the life cycle of polymer products. Including the degradation effects in future studies would provide a more accurate picture of the sustainability of polymer production over extended periods.

Currently, short-term progress and upcoming work focus on validating the proposed model with real-world primary data from various polymer production facilities. This is presented in Section 4.6. This step is crucial for verifying that the model is theoretically sound and practically applicable across multiple industries. After validation, the model can be further improved by incorporating additional sustainability factors, such as transportation and disposal, to develop a more comprehensive environmental impact assessment. For long-term sustainability, incorporating degradation and the life cycle of polymer products into the model would make it more relevant for policymaking, extending the analysis beyond production to include end-of-life impacts. This would lead to more precise environmental evaluations, highlight long-term issues such as waste buildup or microplastic pollution, and support fairer comparisons between traditional and biobased polymers. It would also advance sustainability goals, especially in regions like Abu Dhabi, where the circular economy and waste management are top priorities. These enhancements would make the model a more solid life cycle framework, encouraging industry innovation and guiding policies toward sustainable, long-term solutions.

5. Conclusions

This study systematically reviews existing literature to clarify the complex relationships between key variables—Feedstock choice, Process Optimization, Waste Management, Energy Efficiency, and Recycling Options—and their influence on the environmental impact of polymer production. Its main contribution is developing an integrated conceptual framework that links these diverse factors into a coherent model for impact assessment. The effectiveness of this proposed model is backed by empirical evidence from a pilot study, which used Confirmatory Factor Analysis (CFI = 0.949, TLI = 0.945, RMSEA = 0.068) to verify a solid and valid measurement structure.

This combination shows how these variables interact and emphasizes that significant environmental improvements stem from a synergistic approach rather than isolated efforts. The analysis also highlights a critical gap: although progress has been made in areas like bio-based feedstock, the most resource-intensive stages of polymer production still rely on solutions that are not yet fully scalable or economically feasible. The model serves as a strategic tool for industry stakeholders and policymakers to identify priority interventions and guide R&D efforts. In conclusion, the review consolidates current knowledge to argue that achieving true sustainability requires system-wide optimization and encourages future research to focus on integrating alternative feedstock and closing technical loops at the most impactful production stages.

In conclusion, addressing these limitations will enhance the model’s accuracy, applicability, and relevance, thereby ensuring its potential to drive more sustainable practices in polymer production.