Plastic recycling technologies are developing rapidly as countries seek to reduce carbon emissions, use resources more efficiently, and move toward circular economy models. Although mechanical recycling remains the most widely applied option worldwide, its environmental performance depends strongly on process design, feedstock quality, and operational stability, especially in emerging economies where automation and process control may be limited. This study provides a process-level environmental assessment of an industrial mechanical recycling facility in Gaziantep, Türkiye, using twelve months of real, meter-based operational data. Unlike many previous assessments based on simplified or short-term assumptions, the present study combines long-term industrial monitoring, scenario-based process modeling, and probabilistic uncertainty analysis within a single facility-scale evaluation. An ISO 14040/14044-compliant life cycle assessment was performed for four major polymers (PET, HDPE, LDPE, and PP), combining digital energy monitoring with Monte Carlo-based uncertainty analysis. The results show that extrusion is the dominant energy hotspot, accounting for 72–79% of cumulative energy demand (CED), and that the baseline configuration leaves substantial room for improvement in terms of energy and emissions performance. Scenario analysis indicates that combining high-efficiency extrusion with sensor-based sorting can reduce CED and GWP by up to 17.6% and 18.1%, respectively. Monte Carlo simulations demonstrate reduced operational variability under improved configurations and confirm the statistical robustness of these improvements. Overall, the findings provide process-level evidence for improving the environmental performance of mechanical recycling systems in developing industrial contexts.
Bozdoğan et al. (2026) studied this question.