ProOptiMA Lab
Design of the Transition for Sustainable Plastic Waste Management under Carbon Policies in the United States
The growing environmental and economic challenges posed by plastic waste demand innovative and strategic solutions. This study presents a decision-making framework using mathematical programming to determine the technologies, their location, and the transportation method (electric or with conventional trucks) under different scenarios: maximizing profit, maximizing decarbonization, maximizing plastic circularity, and maximizing profit under carbon tax and carbon cap policies. Results suggest upcycling by pyrolysis for maximizing profit; hydrocracking and mechanical recycling for maximizing the decarbonization; hydrocracking, pyrolysis, and mechanical recycling for carbon tax and carbon cap schemes; and mechanical recycling combined with chemical recycling for maximizing circularity. These results highlight the challenges of simultaneously maximizing circularity and meeting the 2050 decarbonization targets proposed by the Paris agreement as chemical recycling involves pyrolysis, a highly energy intensive technology. The assessment of the policies shows that current carbon taxes are not sufficient for achieving those decarbonization targets. To address this, either higher taxes or a carbon cap policy mechanism are needed with four recommended technologies: upcycling based on pyrolysis and hydrocracking, chemical recycling, and mechanical recycling.
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Enabling Flexible Biomass Supply Chains with Mobile Modules
Biomass feedstocks are emerging sources of raw materials for chemical production with potentially lower greenhouse gas (GHG) emissions than traditional feedstocks. Deploying low-carbon chemical technologies that use renewable feedstocks offers promising benefits. However, successful implementation requires more considerations beyond the facility boundary, including supply and transport limitations. With the ongoing effort to decarbonize chemical production and fierce competition, it is essential for chemical companies to account for high uncertainties and their impacts on the biomass supply chain.
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​A notable feature of biomass feedstocks is their temporal and spatial variability since each crop only grows in certain areas and is harvested during a specific season. Unlike most current petrochemical plants that run on a steady supply of raw materials with relatively consistent properties, biorefineries have to address unstable feedstock quantities and compositions as a result of the variable temporal-spatial patterns in supply. Moreover, ever-changing demands and unforeseen disruptions add to the complexity of supply chain planning and product management decision-making.
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Toward Net-Zero Greenhouse Gas Emission: Techno–Economic and Life Cycle Analyses of Routes for Triacetic Acid Lactone (TAL) Bioproduction
A global shift toward sustainable manufacturing is underway, with companies and governments across the globe pledging to achieve net-zero carbon emissions by 2050. However, the path to net-zero is full of challenges, and without substantial changes to manufacturing practices, “net-zero” is unachievable. Biobased manufacturing could be a more sustainable alternative to traditional chemical production processes. We use triacetic acidlactone (TAL) produced from an engineered strain of Yarrowia lipolytica as a model system to explore the economic plausibility and environmental impact of several distinct routes to net-zero carbon emission manufacturing. Shifting away from conventional sugar-based fermentation, we employ a multiroute structure investigating alternative feedstocks including ethanol (2-ET),acetic acid (3-AA), and methanol (4-ME) as potential options for cost-effective and eco-friendly TAL production. Throughcomprehensive evaluation via bioprocess modeling, techno−economic analysis (TEA), and life cycle assessment (LCA), we evaluate the minimum selling price (MSP) and the intensity of GHG emissions for each production route and the environmental impact of raw material selection to gain clarity around net-zero emission strategies. The TEA shows that glucose-based TAL has the most favorable MSP of $28.60/kg at a production scale of 100 metric tons per year. In contrast, the MSPs of the TAL for scenarios 2-ET,3-AA, and 4-ME are higher than glucose-based (1-GL) TAL. At 135 kiloton per year scale, acetic acid-based TAL, where the acetic acid was obtained from industrial off-gas fermentation, is the most cost-effective solution with an MSP of $6.06/kg. This strategy not only outcompetes the MSP of the glucose-based TAL by 8% but reaches net-negative CO2 emissions. The study underscores the economic and environmental benefits of incorporating CO2 utilization into manufacturing practices for net-zero production of TAL and other high-value compounds. Through the use of TAL as an example, this research showcases a cost-effective way to produce one bioproduct with net-zero greenhouse gas (GHG) emissions and also provides perspective on the economic outlook of bioproduction from substrates generated using carbon capture technologies when competing against traditional sugar-based fermentation.
Economic and Environmental Benefits of Modular Microwave-Assisted Polyethylene Terephthalate Depolymerization
The growing amount of plastic waste endangers the environment. Polyethylene terephthalate (PET) is among the most widespread plastics due to its extensive use in fibers and packaging. Recently, chemical recycling and upcycling approaches have been proposed to produce valuable products from bale PET feedstocks. This work performs techno-economic analysis and life cycle assessment to evaluate the environmental and economic performances of various technologies, including electrification via microwaves over a heterogeneous catalyst. We demonstrate that using a microwave-assisted heterogeneous glycolysis process to produce bis(2-hydroxyethyl) terephthalate (BHET) could have lower production costs and emissions than the traditional dimethyl terephthalate (DMT) route due to the high reactivity and excellent reusability of the catalyst. The fast reaction rate and high selectivity render this process ideal for handling spatially distributed PET waste effectively.
Multifeedstock and Multiproduct Process Design Using Neural Network Surrogate Flexibility Constraints
Biorefineries are designed to utilize a combination of various technologies to transform biomass derived raw materials into different value-added products. This strategy has been highlighted in the literature for reducing waste, increasing profitability, and improving the process resilience to uncertain biomass feedstocks. In this work, a two-stage stochastic programming (TSSP) model is developed to maximize profit and minimize emissions under different sources of uncertainties. Data-driven surrogate models are built for biorefinery’s flexibility index (FI) to quantify and improve its operational flexibility. The neural network with rectified linear unit (ReLU) activation function is established as the appropriate surrogate model because it closely approximates the flexibility index while retaining the mixed-integer linear characteristics of the overall design formulation. Moreover, the stochastic programming demonstrates the magnitude of environmental impact uncertainty quantitatively in each scenario using empirical price/demand/supply uncertainty information, which cannot be addressed by the traditional Pedigree-based life cycle assessment (LCA) uncertainty analysis.
Mathematical Programming Approach to Optimize Tactical and Operational Supply Chain Decisions under Disruptions
Supply chain (SC) networks have become more prominent, complex, and challenging to manage, especially considering the multitude of risks and uncertainty that may manifest. Studies have shown two basic approaches to hedge against the negative impact of SC disruptions: proactive and reactive. While the former methods suggest different approaches to generating robust and resilient structures, the latter approach ensures that the SC recovers effectively. A general shortcoming of existing work is not considering SC dynamics. Consequently, disruptions are considered static events without including the durations and recovery policies. In this work, we develop a SC model that aids decision-making in addressing disruptions by considering proactive and reactive strategies. We adopted a discrete time-expanded model to solve the SC problem and consider the disruption dynamics using the rolling horizon framework. In the proposed SC model, a graph network represents the SC, where the nodes consisting of suppliers, manufacturing sites, warehouses, and customers interact using the arcs. The arcs determine the flow of materials between nodes. Independent disruptions can occur at the nodes and/or arcs, and the time of disruption is quantified using the geometric distribution. In the advent of disruption, we have adopted adjusting routing plans, inventory levels, capacity flexibility, and other tactical and operational decisions to hedge against disruption. To illustrate the proposed approach, we used a small problem to illustrate the effect of arcs and node disruption in decision-making and a realistic case study to demonstrate the proposed framework’s computational complexity. The results suggested that the effect of node disruption is more predominant because the initial network configuration limits the flexibility at the nodes. Furthermore, it was shown that the SC operated efficiently, as the solution offers a balance between the service level and the total cost of operating the SC.
Coupling Process Intensification and Systems Flowsheeting for Economic and Environmental Analysis of 5-Hydroxymethyl Furfural Modular Microreactor Plants
This work evaluates process intensification technologies, microreactors, and adsorption beds, in the production of HMF. The study is performed by developing a flowsheeting capability that accounts for heat and mass transfer in the reactor to allow for comparison of different scales at the design stage. The framework helps provide a detailed description of the reactor across scales and obtain more reliable economic and environmental results. These results show that scaling up the process by means of microreactor modules reduces the minimum selling price by at least 10% and the emissions by at least 5% compared to conventional reactors. The recovery of HMF by adsorption beds instead of vacuum distillation reduces the minimum selling price between 10 and 50% and the CO2 emissions up to 40%.
Comparison of 4,4′-Dimethylbiphenyl from Biomass-Derived Furfural and Oil-Based Resource: Technoeconomic Analysis and Life-Cycle Assessment
Replacing oil-based toluene with biomass-derived furfural for 4,4′-dimethylbiphenyl (DMBP) production can pave the way for sustainable polyester manufacture. This work compared the economic and environmental performances of two conceptual designs of 4,4′-DMBP production. The first toluene-based route consists of toluene alkylation to (methylcyclohexyl)toluene (MCHT), MCHT dehydrogenation to DMBP, and isomerization of lower-valued 3,3′-DMBP. The renewable furfural-based route includes hydrogenation of furfural to 2-methylfuran (MF), oxidative coupling of MF to 5,5′-dimethylfuran (DMBF), and tandem Diels–Alder dehydration of 5,5′-DMBF to 4,4′-DMBP. The reaction conditions are optimized to achieve a more economically feasible process using furfural feedstock. At a scale of 83 kmol/h feedstock, the 4,4′-DMBP minimum selling price of the furfural-based route is $3044/t, while that of the toluene-based route is $2488/t. The feedstock and 3,4′-DMBP isomer prices are identified as critical parameters for the economic evaluation by sensitivity analysis. A “cradle-to-gate” life-cycle assessment confirms that furfural-based DMBP production emits significantly fewer greenhouse gas (5.00 kg CO2 equiv/kg DMBP) as compared to the toluene-based counterpart (8.28 kg CO2 equiv/kg DMBP).