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The Plastic Parallel Pathways Platform (4P) combines life cycle assessment, agent-based modeling within a dynamic material flow analysis structure to compute the environmental impacts of different recycling options under various behavioral interventions.
Plastic packaging plays a fundamental role in the food industry, avoiding food waste and facilitating food access. The increasing plastic production and the lack of appropriate plastic waste management technologies represent a threat to the environmental and human welfare. Therefore, there is an urgent need to identify sustainable packaging solutions. Circular economy (CE) promotes reducing waste and increasing recycling practices to achieve sustainability. In this work, we propose a CE framework based on multi-objective optimization, considering both economic and environmental impacts, to identify optimal packaging designs and waste management technologies. Using mixed-integer linear programming (MILP), techno-economic analysis (TEA), and life cycle assessment (LCA), this work aims to build the first steps in packaging design, informing about the best packaging alternatives and the optimal technology or technologies to process packaging waste. For the economic analysis, we consider the minimum increase in price (MIP) when adding recycling to the cost of each packaging solution, while for the environmental analysis, the greenhouse gas emissions impact was considered. A case study on ground coffee packaging is used to illustrate the proposed framework. The results demonstrate that the multilayer bag option is the most convenient when considering both the chosen economic and environmental impacts.
Benzylamines are key intermediates in pharmaceuticals, agrochemicals, and polymers, but their conventional production relies on benzyl chloride - a petroleum-derived compound with high toxicity and energy demands. Lignin, accounting for up to 30% of plant biomass, is the largest renewable source of aromatic carbon on Earth. However, its highly complex and recalcitrant structure poses a major barrier to efficient conversion into high-value chemicals. Here, in this study, we developed a catalytic approach to convert commercial kraft lignin into phenolic benzylamines through selective depolymerization and subsequent functionalization. We systematically evaluated the effects of three alcohol solvents, formic acid (FA), and a ruthenium-on‑carbon (Ru/C) catalyst on monophenol yield and selectivity. Up to 6.5 wt% monophenol yield was achieved using methanol (MeOH), FA, and Ru/C at 300 °C for 2 h. Quantum thermodynamic simulations based on the COSMO-RS model confirmed the superior solvation and reactivity of the MeOH + FA system, rationalizing observed product yield. The purified monophenolic products, primarily guaiacol and alkyl guaiacols, were then converted into functionalized benzylamines with >90% yield via a multicomponent Mannich reaction under mild conditions. Techno economic analysis (TEA) and life cycle assessment (LCA) underscore the importance of improving lignin depolymerization yields and expanding biorefinery scale. Solvent-only configurations outperform other options in both cost and emissions, with the methanol-only case performing the best ($\$$105 /kg and 26 kg CO 2e /kg) at a large-scale facility. This study establishes a scalable, bio-based pathway for producing benzylamines from commercial kraft lignin, advancing lignin valorization and offering a sustainable alternative to produce petrochemical-based benzylamines.
Cooling systems in power plants account for approximately 40% of total freshwater withdrawals in the U.S. Due to dwindling access to freshwater resources worldwide, continued operation of wet cooling systems poses a significant engineering challenge. To reduce water consumption, a novel air-cooled heat exchanger has been developed using encapsulated phase change material (EPCM) for dry cooling of power plants. Compared to traditional finned-tube air-cooled condensers, this novel EPCM heat exchanger improves the heat transfer coefficient and power plant efficiency while reducing the pressure drop and cooling system cost. Life cycle assessment (LCA) and techno-economic analysis (TEA) are used to evaluate the environmental and economic performance of EPCM heat exchangers from cradle-to-grave and to compare them to wet cooling and traditional air-cooled condensers. A thermodynamic model is developed to predict the EPCM heat exchanger performance for plant-scale operations. Equipment and construction costs for heat exchangers are estimated based on design parameters obtained from the thermodynamic model. Both process-LCA and economic-input–output LCA are used to simulate and test the sensitivity of EPCM alternatives with commercial wet and dry cooling technologies. We investigate options for EPCM end-of-life management upon retiring the heat exchanger and construct a process-based LCA model to estimate a greenhouse gas (GHG) emissions credit for recycling the EPCM. The life cycle GHG emission of the novel dry cooling technology is 1.16 kg CO 2 eq. /MWh compared with the 1.1–4.3 kg CO 2 eq. /MWh reported for commercial dry cooling technologies and consumes 9.5 L/MWh e of water for cradle-to-gate life cycle, which is significantly lower than that of wet cooling systems. The TEA shows many advantages of EPCM cooling technology over the state-of-art dry cooling solutions. Overall, the EPCM heat exchanger provides a better alternative compared to existing dry cooling and wet cooling technologies.
This report describes an activity-based cost estimation method, proposed for the Space Exploration Initiative (SEI), as an alternative to NASA's traditional mass-based cost estimation method. A case study demonstrates how the activity-based cost estimation technique can be used to identify the operations that have a significant impact on costs over the life cycle of the SEI. The case study yielded an operations cost of $101 billion for the 20-year span of the lunar surface operations for the Option 5a program architecture. In addition, the results indicated that the support and training costs for the missions were the greatest contributors to the annual cost estimates. A cost-sensitivity analysis of the cultural and architectural drivers determined that the length of training and the amount of support associated with the ground support personnel for mission activities are the most significant cost contributors.
This report briefly reviews the characteristics of solid-state batteries (SSBs) and the life-cycle analysis (LCA) studies that have been completed for SSBs. Compared with conventional lithium-ion batteries (LIBs), SSBs offer improved safety and potentially higher energy density — both enabled by replacing liquid electrolytes with solid electrolytes and using lithium metal anodes. Several challenges impede the commercialization of SSBs, primarily related to the stability of the interface between the solid electrolyte and the electrodes. Several options are under consideration for SSB electrolyte and cathode chemistries. As a result, the production processes for these components and the corresponding battery packs are still under development and can differ significantly from those used for conventional LIB pack production. A robust comparison of SSBs with LIBs through LCA is important to analyze the environmental benefits and challenges associated with this alternative battery system. While the literature provides only a few LCA studies focused on SSBs, with significant uncertainty in their life-cycle inventories (LCIs), those studies collectively suggest that solid electrolyte manufacturing is the major environmental hotspot, followed by cathode and anode production.
The transition to a more circular economy (CE) is complex and hard to predict, including in sustainable energy technologies. Many sources of uncertainty make it challenging to model CE scenarios and their potential benefits. As an example, the high variability in costs and revenues of different recycling options makes future wind turbine blade recycling highly uncertain. To better understand this challenge, the circular economy, life cycle assessment and visualization (CELAVI) framework - a discrete event simulation and life cycle assessment framework - is modified to incorporate uncertainty analysis capabilities. Moreover, a 3-step procedure that covers different aspects of uncertainty in CE studies and includes a Monte-Carlo analysis is proposed. The procedure is tested in a case study on wind turbine blade recycling using CELAVI. Results highlight that grinding and landfilling costs are the most influential parameters for wind power circularity. The model's output coefficients of variation (when input parameter uncertainties are propagated) are between 92% and 384% depending on the indicator. The approach developed in this study may help researchers and decision-makers who study circularity prioritize their data collection effort. Finally, our method contributes to a mounting yet critical body of research: the measurement of uncertainty in circularity transitions.
CanSat is an international student design-build-launch competition organized by the American Astronautical Society (AAS) and American Institute of Aeronautics and Astronautics (AIAA). The competition is also sponsored by the Naval Research Laboratory (NRL) and the National Aeronautics and Space Administration (NASA). The CanSat competition is designed for college, university and high school students wanting to participate in an applicable space-related competition. The objective of the CanSat competition is to complete space exploration missions by designing a specific system for a small sounding rocket payload which will follow and perform to a specific set of rules and guidelines for each year's competition. The competition encompasses a complete life-cycle of one year which includes all phases of design, integration, testing, judging and competition. The mission guidelines are based from space exploration missions and include bonus requirement options which teams may choose to participate in. The fundamental goal of the competition is to educate future engineers and scientists. This is accomplished by students applying systems engineering practices to a development project that incorporates an end-to-end life cycle, from requirements analysis, through preliminary design, integration and testing, an actual flight of the CanSat, and concluding with a post-mission debrief. This is done specifically with space related missions to bring a unique aspect of engineering and design to the competition. The competition has been progressing since its creation in 2005. The competition was originally meant to purely convey the engineering and design process to its participants, but through many experiences the competition has also undergone a learning experience with respect to systems engineering process and design. According
Manganese-rich oxides are attractive options as next-generation, earth-abundant cathodes and significant efforts are being directed toward commercial implementation. We report here an updated techno-economic analysis of the lithium- and manganese-rich (LMR) class of earth-abundant cathodes for electric vehicle applications. BatPaC modeling was used to define the cell-level metrics that must be met for these materials to be cost and energy competitive with the current commercial earth-abundant benchmark, LiFePO 4 , as well as anticipated variations such as LiMn 0.8 Fe 0.2 PO 4 . The model was used to evaluate a high-performance material from the literature and subsequently define R&D targets as the likely limits of practical performance for similar LMR systems. Experimental validation and BatPaC evaluation of an advanced, cobalt-free LMR cell system was also conducted. Results show that the advanced LMR cells come within ∼5% of the defined limits and exceed the energy of LiFe(Mn)PO 4 cells at a similar cost. Excellent cycle-life, low impedance, and low impedance rise were also achieved under the conditions tested and reveal that cobalt is not necessary to achieve high-performance LMR oxides. Although the analysis conducted herein reports on LMR cell systems, the methodology and target values defined for performance metrics easily extend to the evaluation of other systems under consideration as earth-abundant options.
Long-term spaceflight may induce a variety of harmful effects in astronauts, resulting in altered motor and cognitive behavior. The stresses experienced by humans in space - most significantly weightlessness (microgravity) and cosmic radiation - are difficult to accurately simulate on Earth. In fact, prolonged and concomitant exposure to microgravity and cosmic radiation can only be studied in space. Behavioral studies in space have focused on model organisms, including Drosophila melanogaster. Drosophila is often used due to its short life span and generational cycle, small size, and ease of maintenance. Additionally, the well-characterized genetics of Drosophila behavior on Earth can be applied to the analysis of results from spaceflights, provided that the behavior in space is accurately recorded. In 2001, the BioExplorer project introduced a low-cost option for researchers: the small satellite. While this approach enabled multiple inexpensive launches of biological experiments, it also imposed stringent restrictions on the monitoring systems in terms of size, mass, data bandwidth, and power consumption. Suggested parameters for size are on the order of 100 mm3 and 1 kg mass for the entire payload. For Drosophila behavioral studies, these engineering requirements are not met by commercially available systems. One system that does meet many requirements for behavioral studies in space is the actimeter. Actimeters use infrared light gates to track the number of times a fly crosses a boundary within a small container (3x3x40 mm). Unfortunately, the apparatus needed to monitor several flies at once would be larger than the capacity of the small satellite. A system is presented, which expands on the actimeter approach to achieve a highly compact, low-power, ultra-low bandwidth solution for simultaneous monitoring of the behavior of multiple flies in space. This also provides a simple, inexpensive alternative to the current systems for monitoring Drosophila populations in terrestrial experiments, and could be especially useful in field experiments in remote locations. Two practical limitations of the system should be noted: first, only walking flies can be observed - not flying - and second, although it enables population studies, tracking individual flies within the population is not currently possible. The system used video recording and an analog circuit to extract the average light changes as a function of time. Flies were held in a 5-cm diameter Petri dish and illuminated from below by a uniform light source. A miniature, monochrome CMOS (complementary metal-oxide semiconductor) video camera imaged the flies. This camera had automatic gain control, and this did not affect system performance. The camera was positioned 5-7 cm above the Petri dish such that the imaging area was 2.25 sq cm. With this basic setup, still images and continuous video of 15 flies at one time were obtained. To reduce the required data bandwidth by several orders of magnitude, a band-pass filter (0.3-10 Hz) circuit compressed the video signal and extracted changes in image luminance over time. The raw activity signal output of this circuit was recorded on a computer and digitally processed to extract the fly movement "events" from the waveform. These events corresponded to flies entering and leaving the image and were used for extracting activity parameters such as inter-event duration. The efficacy of the system in quantifying locomotor activity was evaluated by varying environmental temperature, then measuring the activity level of the flies.
Following life-cycle assessment (LCA) methodology, this study presents a state-level estimation of embodied carbon of wood products harvested in 2019 from California and subsequently processed, manufactured, transported, used, and disposed at the end-of-life (EoL). In a conventional static approach to LCA, all GHG emissions were aggregated and considered to occur at year 0 of the given time horizon (500 years in this study) and used a static characterization factor (CF). In dynamic LCA, GHG emissions occurring in different years were considered, and their global warming impact (GWI) was determined using a time-dependent CF over the selected time horizon of 500 years. Four scenarios were developed to examine the impact of EoL choices on GWI. It was found that dynamic GWI for all scenarios ranged from 0.27 to 0.93 million tonne CO₂e, which were 45–73 % lower than those estimated with static LCA approach, indicating that the static LCA approach could lead to an underestimation of the benefits of substituting wood for non-wood products, compared to those based on dynamic LCA approach. This analysis also demonstrated that the choice of EoL treatment option is a key factor affecting the estimated GWI as it directly determines the annual emission of GHGs released into atmosphere and subsequently their warming effect depending on the time harvested wood products (HWPs) spend in the horizon of assessment. Altogether, the dynamic LCA performed in this study enabled more robust interpretations of embodied carbon by including temporal boundaries associated with the HWPs life cycle.
The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.
The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.
The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.
Environmental Control and Life Support System (ECLSS) architecture selection has profound implications for mission cost and mass extending far beyond the ECLSS itself. Similarly, other mission architecture decisions – particularly involving transportation systems – can influence optimal ECLSS architectures. Loop closure influences requirements for water, oxygen, and other consumables. System maintainability and reliability influences spares mass and risk. System, consumables, and spares mass interact with transportation system architectures and propellant demands and propulsion element sizing. All these interactions with other systems must be considered when evaluating ECLSS options. Analyses that focus only on maximizing ECLSS loop closure – or minimizing ECLSS mass, or minimizing ECLSS life cycle cost – may lead to sub-optimal or even counterproductive system architecture and investment decisions at the mission level. For example, an ECLSS architecture that minimizes ECLSS life cycle cost but results in excessively high logistics mass could lead to significantly increased transportation system costs or make interplanetary transportation infeasible. Increased loop closure could result in higher development costs and higher mass if system/spares mass increases outweigh consumables reduction. In addition, systems mass and consumables mass are not directly comparable and have different impacts on propellant requirements, as consumables mass changes over the course of the mission. This paper presents an integrated analysis examining the overall impact of different ECLSS and transportation architectures on mass for a crewed Mars mission, including the habitat and transportation systems as well as consumables, spares, and propellant. Key observations are discussed, along with opportunities for further sensitivity analysis and model development. Overall, ECLSS development activities must consider their impacts at the mission level, as part of an integrated system, rather than in isolation.
Environmental Control and Life Support System (ECLSS) architecture selection has profound implications for mission cost and mass extending far beyond the ECLSS itself. Similarly, other mission architecture decisions – particularly involving transportation systems – can influence optimal ECLSS architectures. Loop closure influences requirements for water, oxygen, and other consumables. System maintainability and reliability influences spares mass and risk. System, consumables, and spares mass interact with transportation system architectures, including propellant demands and propulsion element sizing. All these interactions with other systems must be considered when evaluating ECLSS options. Analyses that focus only on maximizing ECLSS loop closure – or minimizing ECLSS mass, or minimizing ECLSS life cycle cost – may lead to sub-optimal or even counterproductive system architecture and investment decisions at the mission level. For example, an ECLSS architecture that minimizes ECLSS life cycle cost but results in excessively high logistics mass could lead to significantly increased transportation system costs or make interplanetary transportation infeasible. Increased loop closure could result in higher development costs and higher mass if system/spares mass increases outweigh consumables reduction. In addition, systems mass and consumables mass are not directly comparable and have different impacts on propellant requirements, as consumables mass changes over the course of the mission. This paper presents an integrated analysis examining the overall impact of different ECLSS and transportation architectures on Earth departure mass for a crewed Mars mission, including the habitat and transportation systems as well as consumables, spares, and propellant. Key observations are discussed, along with opportunities for further sensitivity analysis and model development. Overall, ECLSS development activities must consider their impacts at the mission level, as part of an integrated system, rather than in isolation.
Environmental Control and Life Support System (ECLSS) architecture selection has profound implications for mission cost and mass extending far beyond the ECLSS itself. Similarly, other mission architecture decisions – particularly involving transportation systems – can influence optimal ECLSS architectures. Loop closure influences requirements for water, oxygen, and other consumables. System maintainability and reliability influences spares mass and risk. System, consumables, and spares mass interact with transportation system architectures and propellant demands and propulsion element sizing. All these interactions with other systems must be considered when evaluating ECLSS options. Analyses that focus only on maximizing ECLSS loop closure – or minimizing ECLSS mass, or minimizing ECLSS life cycle cost – may lead to sub-optimal or even counterproductive system architecture and investment decisions at the mission level. For example, an ECLSS architecture that minimizes ECLSS lifecycle cost but results in excessively high logistics mass could lead to significantly increased transportation system costs or make interplanetary transportation infeasible. Increased loop closure could result in higher development costs and higher mass if system/spares mass increases outweigh consumables reduction. In addition, systems mass and consumables mass are not directly comparable and have different impacts on propellant requirements, as consumables mass changes over the course of the mission. This paper presents an integrated analysis examining the overall impact of different ECLSS and transportation architectures on mass for a crewed Mars mission, including the habitat and transportation systems as well as consumables, spares, and propellant. Key observations are discussed, along with opportunities for further sensitivity analysis and model development. Overall, ECLSS development activities must consider their impacts at the mission level, as part of an integrated system, rather than in isolation.
Levelized cost of storage (LCOS) can be a simple, intuitive, and useful metric for determining whether a new energy storage plant would be profitable over its life cycle and to compare the cost of different energy storage technologies. However, researchers and industry decision makers still use conflicting definitions of LCOS. For example, some include charging cost, while others only include round trip efficiency (RTE) losses. Additionally, inputs to the existing formulations are not specific enough to generate repeatable results across studies, which reduces trust in the metric. To push for standardization in economic assessment of batteries and other energy storage devices, the authors review existing definitions of LCOS and identify the desired characteristics for a standard. They then propose a new definition and demonstrate that it fits these characteristics very well relative to other prominent options. Unit analysis is applied to this proposed definition to provide a deeper understanding of the equations and to demonstrate its effectiveness. Finally, the sensitivity of LCOS to different input parameters is investigated to help users understand how to compare analyses from literature to their own. The authors also provide a spreadsheet and a Python script to streamline adoption of the proposed definition.