| Author: | Chu, Yin Ting |
| Title: | Towards sustainable medical waste valorization : evaluation framework, process simulation and optimization, risk assessment and strategy prioritization |
| Advisors: | Ren, Jingzheng (ISE) Lee, Carmen (ISE) |
| Degree: | Ph.D. |
| Year: | 2025 |
| Department: | Department of Industrial and Systems Engineering |
| Pages: | xviii, 399 pages : color illustrations |
| Language: | English |
| Abstract: | Waste generated in relation to healthcare services is defined as medical waste, which has been remaining at an annual steady climb of approximately 2-3% worldwide owing to accelerating urbanization and technological advancements. With a calorific value of around 24 kJ per kg as more than double that of municipal solid waste, medical waste is redeemed a favorable energy source, and its valorization means turning medical waste into valuable products. It is reported that the case in Hong Kong that around 75% of the medical waste was treated via high-temperature incineration at the Chemical Waste Treatment Centre while the remaining 25% was directly disposed of in a landfill. Its hazardous and infectious characteristics and threats to the environment and public health necessitate sustainable valorization initiatives. In line with Hong Kong’s commitments to achieving carbon neutrality and the goals outlined in the Waste Blueprint for Hong Kong 2035, developing and adopting advanced medical waste valorization technologies has become imperative. So as to provide insightful suggestions to decision-makers, this study proposes an integrated four-phase decision-support roadmap for sustainable medical waste valorization, which combines process evaluation, process simulation and optimization, risk assessment and strategy prioritization. These four elements build a comprehensive, stepwise and systematic pathway to overcome both technical and non-technical challenges that may be encountered by policymakers and stakeholders. With escalating diversities of medical waste valorization technologies being proposed, a standardized framework for process evaluation and selection is demanded. Phase I introduces a brand-new ESG-oriented evaluation framework considering 16 indicators from environmental, social and governance dimensions, offering comprehensive insights into evaluation among performance, efficiency, sustainability and overall efficacy of medical waste valorization processes. The evaluation framework is driven by an innovative multi-criteria decision-making (MCDM) model: Decomposed Fuzzy Sets Weighted Influence Non-linear Gauge System and Decomposed Fuzzy Sets Combinative Distance based Assessment (DFS-WINGS-CODAS), which excels at robustly handling uncertainty by evaluating criteria and alternatives from optimistic and pessimistic scenarios in complex systems. Findings of this phase demonstrate the indicator weights and their interrelations and pinpoint the optimal technologies among numerous innovative medical waste valorization processes. Supply chain traceability, risk monitoring index and renewable energy utilization are highlighted as the most prominent criteria in the ESG metrics. The results also reveal that an incineration-based valorization process emerges as the most preferable alternative for Hong Kong’s long-term sustainability objectives. To address the gap in designing a novel and feasible solution based on the holistic evaluation and infrastructural readiness, Phase II attempts to develop a process based on the findings of Phase I. Despite incineration being the most mature and widely applied method, known for its drawbacks of energy loss and pollutant generation, little is known about process simulation and optimization conducted on medical waste incineration-valorized alternatives. Phase II focuses on designing and simulating a novel integrated incineration process in Aspen Plus, coupling incineration with a heat recovery unit, a supercritical CO₂ cycle and tail gas absorption treatment, in order to address the mentioned deficiencies. Simulation results demonstrate that 100% SO₂ and 75% NO₂ in flue gas are converted into valuable industrial chemicals embracing H2SO4, HNO₂, and HNO₃. Furthermore, process optimization was conducted on the supercritical CO₂ cycle for power generation. Optimization results indicate that the net electricity generation reaches 901.9 kW/tonne of medical waste, highlighting an approximate 20% increase in waste-to-electricity efficiency compared to the non-optimized design. Thus, this novel incineration-based process is confirmed to be technically feasible, aligns seamlessly with Hong Kong’s Waste Blueprint 2035 on waste-to-energy facilities adoption over landfills and a 55% waste recovery rate target and accelerates transition from fossil fuel dependency to net-zero carbon electricity production. Implementing the medical waste valorization process carries significant uncertainties and risks, particularly given the potentially severe consequences of system failures. Two major limitations are evident in the existing risk assessment models, including the design for regional applications and incomplete scopes. Phase III develops a structural risk model covering 6 risk factors extending beyond the conventional Failure Mode and Effect Analysis (FMEA) dimensions and 19 potential failure modes identified from environmental, social, governance, economic and technological perspectives. In order to systematically analyze the risk model of softening ambiguity and imprecise information in linguistic presentations, a robust decision-making model incorporating Trapezoidal Fuzzy Base-Criterion Method (TrF-BCM), Trapezoidal Fuzzy LOgarithmic Percentage Change-driven Objective Weighting (TrF-LOPCOW) and Trapezoidal Fuzzy Combined Compromise Solution (TrF-CoCoSo) is developed to interpret criticalities of the risk factors and priorities of the failure modes. The primary contribution of this phase is the precise and comprehensive analysis of risks associated with medical waste valorization, which guides decision-makers in proactive planning. The results pinpoint the criticalities of severity, time to failure and occurrence and insufficient funding, expensive capital investment and regulatory non-compliance are the determinants for successful implementation of the medical waste incineration-valorized process. To effectively mitigate the identified risks, phase IV explores the root causes of implementation barriers and leverages Industry 4.0, AI-driven solutions and Industry 5.0 principles (sustainability, resilience and human-centricity) to formulate 20 tailored strategies addressing 19 implementation barriers. To our best knowledge, this is the first attempt to incorporate Industry 5.0 paradigm into barrier-strategy analysis for advanced waste-to-energy systems ensuring safe, sustainable and long-term valuable to further promote waste valorization. It is impractical to execute all strategies simultaneously, a decision-support model to prioritize strategies should be suggested. Step-wise Weight Assessment Ratio Analysis (SWARA) and Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) under Interval Type-2 Trapezoidal Fuzzy (IT2TrF) conditions driven by a Generalized Interval Type-2 Trapezoidal Fuzzy Sets Weighted Averaging Operator (GnIT2TrFSWAO) is constructed of broader scale management for uncertainties tailored to strategy prioritization. This model computes the final rankings of 20 Industry 5.0-oriented strategies are determined by their effectiveness in mitigating 19 implementation barriers. The results generate a reference in the sequential adoption approach for decision-makers in Hong Kong, which emphasizes strategies on integrating with renewable energy as an energy source, providing wearable safety-monitoring IoT devices and executing flexible product-switching systems based on AI-forecasted market demands, which are the most urgent explorations for successful implementation of the said advanced incineration process. This study demonstrates that sustainable medical waste valorization could be accomplished through isolated technological assessments or single-dimensional evaluations. Via linking these four phases of ESG-driven process evaluation, technical simulation and optimization, comprehensive risk assessment and Industry 5.0-aligned strategy prioritization, this study develops holistic and uncertainty-aware decision-support tools that enable practitioners and policymakers to evaluate, optimize and implement advanced medical waste valorization technologies effectively while addressing multidimensional challenges. |
| Rights: | All rights reserved |
| Access: | open access |
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