Comparative study on air gasification of plastic waste and conventional biomass based on coupling of AHP/TOPSIS multi-criteria decision analysis

State-of-the-art and perspectives of hydrogen generation from waste plastics

Waste plastic utilization and hydrogen production present significant economic and social challenges but also offer opportunities for research and innovation. This review provides a comprehensive analysis of the latest advancements and innovations in hydrogen generation coupled with waste plastic recycling. It explores various strategies, including pyrolysis, gasification, aqueous phase reforming, photoreforming, and electrocatalysis. Pyrolysis and gasification in combination with catalytic reforming or water gas-shift are currently the most feasible and scalable technologies for hydrogen generation from waste plastics, with pyrolysis operating in an oxygen-free environment and gasification in the presence of steam, though both require high energy inputs. Aqueous phase reforming operates at moderate temperatures and pressures, making it suitable for oxygenated plastics, but it faces challenges related to feedstock limitations, catalyst costs and deactivation. Photoreforming and electrocatalytic reforming are emerging, sustainable methods that use sunlight and electricity, respectively, to convert plastics into hydrogen. Still, they suffer from low efficiency, scalability issues, and limitations to specific plastic types like oxygenated polymers. The challenges and solutions to commercializing plastic-to-hydrogen technologies, drawing on global industrial case studies have been outlined. Maximizing hydrogen productivity and selectivity, minimizing energy consumption, and ensuring stable operation and scaleup of plastic recycling are crucial parameters for achieving commercial viability.

An appropriate artificial intelligence technique for plastic materials recycling using bipolar dual hesitant fuzzy set

Plastic recycling has become more important than ever as the globe struggles with growing environmental issues. This research explores the significant environmental impact of recycling plastic and its growing relevance. The pervasive material known as plastic presents a complex risk to both human health and ecosystems in contemporary life. It exacerbates problems including marine pollution, habitat damage, and wildlife entanglement because of its persistence in landfills and seas, which leads to serious ecological deterioration. In addition, producing plastic uses a lot of energy and produces a lot of greenhouse gas emissions, which exacerbate climate change. Through the use of multi-criteria decision making (MCDM), this study emphasizes how vital it is to support recycling activities in order to protect the environment and promote a sustainable future. The elimination and choice ex-pressing reality (ELECTRE) approach is used to rank the alternatives in this proposed research study that employs bipolar dual hesitant fuzzy sets (BDHFs). The most efficient and versatile outranking method for making decisions is the BDHF-ELECTRE approach. The weights of environment, economic, social, technical, and finally safety is computed using the entropy distance metric. The economic factor received the highest score of 0.2945 among the other factors since economic considerations are crucial in choosing the most efficient plastic recycling method, as they ensure sustainability, cost-effectiveness, resource allocation, and overall feasibility in managing plastic waste. The decision-makers determined that the mechanical recycling approach ought to be prioritized over all others for the efficient recycling of plastic waste. The robustness of the system is examined in the sensitive and comparative analyses. The proposed MCDM technique thus presents a viable solution, mitigating the adverse effects of plastic waste by conserving resources, reducing energy consumption, and curbing pollution.

A Regression Analysis on Steam Gasification of Polyvinyl Chloride Waste for an Efficient and Environmentally Sustainable Process

Over the last few years, researchers have shown a growing interest in polyvinyl chloride (PVC) gasification and have conducted several studies to evaluate and enhance the process. These studies have recognized that processing parameters have a crucial impact on the assessment of PVC gasification. Despite this, there has been limited exploration of the use of machine learning techniques, particularly regression models, to optimize PVC waste gasification. This study aims to investigate the effectiveness of regression models as machine learning algorithms in predicting the performance of PVC waste gasification. The study uses data collected through a validated thermodynamic model, and three different regression models are tested and compared in detail. Cold gas efficiency and normalized carbon dioxide emission are predicted using linear, quadratic, and quadratic with interaction algorithms. The outcomes for emission algorithms reveal that the linear emission algorithm possesses a high R-square value of 97.49%, which indicates its strong predictive capability. Nevertheless, the quadratic algorithm outperforms it, exhibiting an R-square value of 99.81%. The quadratic algorithm with an interaction term, however, proves to be the best among them all, displaying a perfect R-square value of 99.90%. A similar observation is detected for the cold gas efficiency algorithms. These findings suggest that the quadratic algorithm with an interaction term is superior and has a greater predictive accuracy. This research is expected to provide valuable insight into how regression algorithms can be used to maximize the efficiency of PVC waste gasification and reduce its associated environmental concerns.

Recent Advances in Extended Producer Responsibility Initiatives for Plastic Waste Management in Germany and UK

Extended producer responsibility (EPR) initiatives have shown success in enhancing the independent collection of plastic waste, but the existing recycling industry framework poses challenges to achieving optimal recyclability levels. For addressing this issue, various legislative strategies, including non-profit EPR, door-to-door collection systems, and deposit refund schemes (DRS), have been implemented in some countries such as the UK and Germany. As plastic waste management responsibility is shared between consumers and producers in Europe, with consumers generating 40% of plastic waste and producers being responsible for the remaining 60%, this review examines the impact of EPR and DRS programs on consumer and producer behaviors. The article also explores the potential for circularity and sustainability of recycling technologies, including their challenges and limitations. The significance of this study lies in its examination of the impact of EPR and DRS programs on consumer and producer behaviors, providing insight into sustainable practices that promote waste minimization and foster the adoption of recycling methods. Ultimately, the review recommends quick action in four crucial areas, including standardization, infrastructure investment, partnership models, and the production of higher-value recycled materials, all of which require supply chain collaboration.

Polyurethane Foam Waste Upcycling into an Efficient and Low Pollutant Gasification Syngas

Waste treatment has attracted much attention and, in this regard, gasification processes offer an efficient thermochemical technique that can produce a syngas rich in hydrogen. This technique has been well developed for solid waste and biomass while investigations on gasification of polymeric foam are rare. Therefore, this study explores the treatment of polyurethane foam waste with different gasifying agents, based on thermodynamic modeling. The polymeric foam gasification was developed using the best model for estimating higher heating value (gross calorific value). As the results indicated, models based on both ultimate and proximate analyses had better performance in predicting higher heating value. As one of the main objectives and novelties, the steam and air gasification performance of flexible and rigid polyurethane foam wastes was investigated and compared from efficiency and CO₂ emission viewpoints. Polyurethane foam gasification by steam resulted in higher hydrogen efficiency, led to lower energy efficiency and produced lower CO₂ emissions compared to gasification by air. A hydrogen efficiency of 41.4% was obtained for gasification of waste flexible polyurethane foam by steam. An energy efficiency of 76.6% and CO₂ emission of 7.43 g per mole of feedstock were attained for waste flexible polyurethane foam gasified by air.

Identification of critical operational hazards in a biogas upgrading pilot plant through a multi-criteria decision-making and FTOPSIS-HAZOP approach

The hazard and operability analysis (HAZOP) is one of the most popular approaches for risk management, although weaknesses such as the limited number of risk factors considered, the inaccuracy of experts' opinions or the limited process knowledge might compromise the quality of the results. In this context, conventional HAZOP analysis can be improved via a Fuzzy Multi-Attribute HAZOP technique. Under a fuzzy logic, Analytic Hierarchy Process and the Technique for Order of Preference by Similarity to Ideal Solution can be combined with Fuzzy Multi-Attribute HAZOP to determine the weight of risk factors and to rank critical hazards. The inherent risks biogas upgrading, such as explosiveness, overpressure, or premature deterioration of equipment, should be identified for planning of critical control points and for enabling a proper maintenance plan. Previous models were applied to a photosynthetic biogas upgrading and a biogas-to-polyhydroxyalkanoates production pilot plant in order to identify and get more information about associated risks of the operation of these valorization biotechnologies, sometimes not fully provided by HAZOP analysis. Biotrickling filter and the polyhydroxyalkanoates production tank were identified as the most critical subsystems, with contributions of 33.3% and 17.8% to the overall risk, respectively (within quartile 1, Q₁). Additionally, biogas and recycling/feeding streams clustered a large number of operational risks (up to 83.4% of total risk within Q₁). The sensibility analysis demonstrated the reliability and robustness of the final ranking. The results of this analysis will support preventive maintenance by identifying critical monitored points when scaling-up biological biogas upgrading processes.

Integrating Industry 4.0 and Total Productive Maintenance for global sustainability

Purpose

The integration of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) is an emerging model, and the global pressure of various stakeholders raises scepticism of any emerging model towards providing sustainability. Therefore, this research aims to identify and rank the potential significant drivers of an integrated model of I4.0 and TPM to guide manufacturing enterprises towards sustainability.

Design/methodology/approach

This research follows a four-phase methodology including literature review and expert opinion to select the sustainability indicators and I4.0-integrated TPM key drivers, followed by employing the analytic hierarchy process approach for weight determination of sustainability indicators. The research then deploys the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritise the I4.0-integrated TPM key drivers based on their effect on various sustainability indicators. Finally, a sensitivity analysis is conducted to check the robustness of the TOPSIS.

Findings

The findings establish the top five most influential key drivers of an I4.0-integrated TPM system, which include top management support, formal I4.0 adoption program, mid-management involvement and support, solid TPM baseline knowledge and high engagement of the production team. These top drives can lead manufacturing firms towards sustainability.

Research limitations/implications

The digitalisation of shop floor practices, such as TPM, could be adapted by shop floor managers and policymakers of manufacturing companies to deliver sustainability-oriented outcomes. In addition, this research may aid decision-makers in the manufacturing sector in identifying the most important drivers of I4.0 and TPM, which will assist them in more effectively implementing an integrated system of I4.0 and TPM to practice sustainability. The scope of TPM applicability is wide, and the current research is limited to manufacturing companies. Therefore, there is a huge scope for developing and testing the integrated system of I4.0 and TPM in other industrial settings, such as the textile, food and aerospace industries.

Originality/value

This research makes a first-of-its-kind effort to examine how an I4.0-integrated TPM model affects manufacturing companies' sustainability and how such effects might be maximised.

Syngas biomethanation: Current state and future perspectives

In regions highly dependent on fossil fuels imports, biomethane represents a promising biofuel for the transition to a bio-based circular economy. While biomethane is typically produced via anaerobic digestion and upgrading, biomethanation of the synthesis gas (syngas) derived from the gasification of recalcitrant solid waste has emerged as a promising alternative. This work presents a comprehensive and in-depth analysis of the state-of-the-art and most recent advances in the field, compiling the potential of this technology along with the bottlenecks requiring further research. The key design and operational parameters governing syngas production and biomethanation (e.g. organic feedstock, gasifier design, microbiology, bioreactor configuration, etc.) are critically analysed.

Low-emission and energetically efficient co-gasification of coal by incorporating plastic waste: A modeling study

The issues of global plastic waste generation and demand for hydrogen energy can be simultaneously resolved by gasification process. In this regard, feasibility and efficiency of steam and air co-gasification of coal by incorporating five different and prevalent types of plastic waste were investigated in this modeling study. All steam and air coal/plastic waste co-gasification types were multi-objective optimized utilizing a response surface methodology. The best co-gasification types were selected using VIekriterijumsko KOmpromisno Rangiranje (VIKOR) analysis. Overall, the results showed that incorporating plastic waste into coal gasification improved hydrogen concentration in the syngas and increased normalized carbon dioxide production due to the high carbon content of plastic waste and activation of water-gas and CO shift reactions. VIKOR analysis revealed that steam coal/low density polyethylene was the best optimized co-gasification type with hydrogen concentration of 62.8 mol %, normalized carbon dioxide production of 2.60 g/mol, based on the feedstock entering the system, and energy efficiency of 76.6%. Increasing gasifier temperature enhanced hydrogen concentration and decreased normalized carbon dioxide production. The energy efficiency was markedly improved by increasing the moisture content and decreasing the ratio of steam/feedstock. This study confirmed the hypothesis of efficient utilization of plastic waste in coal/plastic waste co-gasification.

Evaluation of supply sustainability of vaccine alternatives with multi-criteria decision-making methods

BACKGROUND

The treatment of the COVID-19 epidemic, whose contagious features are changing day by day, is the most current problem today throughout of the world. In order to be protected from COVID-19 and reduce its spread, it is of great importance to follow the rules such as mask, distance and hygiene. In addition, one of the most important ways to prevent the epidemic is to develop population immunity. The most important tool in having population immunity is vaccination.

AIMS

During the COVID-19 pandemic, there have been problems in the supply process of many products in food and health sectors. Vaccine is also one of the most difficult tools to supply. In this context, the study focused on the selection of the vaccine provided by the countries within the scope of population vaccination studies.

MATERIALS & METHODS

At the selection point, the criteria affecting the purchasing process were determined and the weights of these criteria were calculated using the AHP method. Then, the criteria weights obtained were used to rank the alternatives in an integrated manner in the Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The results of both methods were analyzed comparatively.

RESULTS

According to the TOPSIS Method, the first alternative is Oxford-AstraZeneca for all countries, and BioNTech for all countries in the PROMETHEE method.

DISCUSSION

The vaccine storage conditions criterion is the most important in vaccine supply. The criterion with the lowest importance is Supply Cost. It has been revealed that cost elements remain in the background under pandemic conditions.

CONCLUSION

Vaccine evaluation studies and policy recommendations are presented by considering public health in the selection of vaccine alternatives.