Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cumulative impacts”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tailoring Cementitious Materials Towards Value-Added Use of Large CO 2 Volumes

Hydraulic cements with alternative chemistries were developed for large-volume and value-added use of carbon dioxide. The hydraulic cements were processed using the energy-efficient mechanochemical technique at room temperature and atmospheric pressure. Carbon dioxide was captured directly from combustion emissions during processing. For this purpose, mechanochemical processing of hydraulic cements was accomplished under a flow of combustion emissions prior to the release of emissions to the atmosphere. The process removed a significant fraction of carbon dioxide from combustion emissions. The hydraulic cements captured carbon dioxide at about 10% of their weight. Two hydraulic cement chemistries were developed, and their mechanochemical processing was successfully scaled-up. The characteristic feature of one chemistry was its relatively low (near-neutral) pH where the integration of carbon dioxide yielded clear value. The second cement chemistry was based on alkali activation of industrial wastes. This chemistry could make value-added use of carbon dioxide, but it had to be refined to control the pH drop caused by CO 2 integration. These two cements render binding effects upon hydration by forming a combination of stable carbonates and aluminosilicates or phosphates. Efforts to develop cement chemistries based solely on carbonates were not successful. The mechanochemical process was found to integrate carbon dioxide into the alternative cement chemistries in the form of disordered and metastable carbonates. During hydration reactions, the disordered/metastable carbonates are either transformed into stable carbonate phases with desired binding efforts, or carbonates get integrated into the primary inorganic binders (hydrates). When compared with mechanochemical processing in pure carbon dioxide, mechanochemical processing in combustion emissions produced hydraulic cements with improved engineering properties. The mechanochemical process was scaled-up, and its variables as well as the raw materials formulations were optimized for implementation at pilot scale. Scale-up was found to enhance the carbon capture potential and the engineering qualities of the resulting hydraulic cements. This was because scale-up raises the intensity of mechanical energy input to raw materials. Certain mechanochemical phenomena cannot be induced, irrespective of the cumulative mechanical energy input, unless the intensity of impact is raised above a minimum level that cannot be achieved in laboratory-scale implementation of the process. Due to this effect, the duration of the mechanochemical process as well as its energy demand could be reduced significantly (by an order of magnitude) upon transition from laboratory to pilot scale, with the hydraulic cements produced at pilot scale offering engineering properties that were superior to those realized in laboratory-scale mechanochemical processing. The hydraulic cements produced at pilot scale via mechanochemical processing under a flow of combustion emissions were thoroughly characterized. They were found to meet standard requirements for ‘General Use’ hydraulic cements. They were compatible with the industrial-scale concrete production and construction practices that are used with the currently prevalent hydraulic cements. The new hydraulic cements with integrated carbon dioxide were found to offer distinct advantages over the currently prevalent Portland cement in terms of net carbon footprint and energy content. The combined raw materials and energy costs of the new hydraulic cements are competitive, and major cost savings can be realized because of the simplified production process that significantly lowers the capital investment in cement production plants. Mechanochemical processing of the new hydraulic cements under a flow of combustion emissions can be implemented using some existing components of cement manufacturing plants; this facilitates adoption of the technology by the cement industry.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Proposed Potential Mitigation of Wastewater Disposal Through Treated Produced Water in Bakken Formation

The recent global expansion in the development of unconventional oil and gas assets has also resulted in a tremendous increase in the number of extended horizontal drilling and hydraulic fracturing projects in the Bakken. The United States is presently the largest global crude oil producer, and the Bakken Formation in North Dakota is one of the major contributors to this achievement. However, the wastewater produced from these increased oilfield activities are highly saline (∼170,000 to 350,000 ppm TDS) and no technology currently available can satisfactorily treat it. As a result, more than 90% of wastewater in the Bakken is disposed of by deep injection into disposal wells. However, there are growing environmental and operational concerns about the sustainability and impacts of this approach. Research has shown that cumulative wastewater injection in some areas could increase the chances of earthquakes in those areas. However, if this produced water is efficiently treated, it could be reused in hydraulic fracturing operations or to support coal mining and irrigation activities. All these applications would reduce the need for wastewater injection and reduce the demand for fresh water used in hydraulic fracturing operations across North Dakota. For this purpose, we propose an enhanced supercritical technology we call Supercritical Water Extraction – Enhance Targeted Recovery to handle the issue of high TDS of flowback and produced water in the Bakken.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2022

Dynamic land use implications of rapidly expanding and evolving wind power deployment

Abstract The expansion of wind power poses distinct and varied geographic challenges to a sustainable energy transition. However, current knowledge of its land use impacts and synergies is limited by reliance on static characterizations that overlook the role of turbine technology and plant design in mediating interactions with the environment. Here, we investigate how wind technology development and innovation have shaped landscape interactions with social and ecological systems within the United States and contribute to evolving land area requirements. This work assesses trends in key land use facets of wind power using a holistic set of metrics to establish an evidence base that researchers, technology designers, land use managers, and policymakers can use in envisioning how future wind-intensive energy systems may be jointly optimized for clean energy, social, and environmental objectives. Since 2000, we find dynamic land occupancy patterns and regional trends that are driven by advancing technology and geographic factors. Though most historical U.S. wind deployment has been confined to the temperate grassland biome in the nation’s interior, regional expansion has implicated diverse land use and cover types. A large percentage of the typical wind plant footprint (∼96% to > 99%) is not directly impacted by permanent physical infrastructure, allowing for multiple uses in the spaces between turbines. Surprisingly, turbines are commonly close to built structures. Moreover, rangeland and cropland have supported 93.4% of deployment, highlighting potential synergies with agricultural lands. Despite broadly decreasing capacity densities, offsetting technology improvements have stabilized power densities. Land use intensity, defined as the ratio of direct land usage to lifetime power generation of wind facilities, has also trended downwards. Although continued deployment on disturbed lands, and in close proximity to existing wind facilities and other infrastructure, could minimize the extent of impacts, ambitious decarbonization trajectories may predispose particular biomes to cumulative effects and risks from regional wind power saturation. Increased land-use and sustainability feedback in technology and plant design will be critical to sustainable management of wind power.

17 WIND ENERGY↗
DOE OSTI2020

Development and validation of the cavitation-induced erosion risk assessment tool

This work presents the development of a cavitation-induced erosion risk assessment (CIERA) tool that links multiphase flow simulation predictions with the progress towards material erosion. To develop a robust erosion modeling tool, the cavitation and erosion predictions for pressurized diesel fuel flow within a channel geometry were validated over a range of Reynolds and cavitation number conditions in two different aluminum channel geometries, one featuring a rounded inlet corner and the other with a sharp inlet corner. The multiphase flow development within the channel was modeled using a compressible mixture model, where phase change was represented with the homogeneous relaxation model and the turbulent flow evolution was modeled using a dynamic structure approach for Large Eddy Simulations. To improve representation of the incubation period before material rupture over existing approaches, a physics-based metric was derived based on the cumulative energy absorbed by the solid material from repeated hydrodynamic impacts. When the average peak pressure was related to the incubation period, the incubation period and its sensitivity to changes in flow conditions were found to be overpredicted. In contrast, predictions from CIERA provided a more accurate means to qualitatively and quantitatively predict the influence of flow conditions on the incubation period before material erosion. When the predicted stored energy was related to the solid material properties to estimate the incubation period, multiphase flow simulations demonstrated accurate representation of the sensitivity of erosion severity to changes in flow conditions. The use of CIERA led to quantitative agreement of the predicted incubation period within 5% of the experimentally measured incubation period.

42 ENGINEERING↗
DOE OSTI2023

Detection of False Data Injection Attacks in Battery Stacks Using Input Noise-Aware Nonlinear State Estimation and Cumulative Sum Algorithms

Grid-scale battery energy storage systems (BESSs) are vulnerable to false data injection attacks (FDIAs), which could be used to disrupt state of charge (SoC) estimation. Inaccurate SoC estimation has negative impacts on system availability, reliability, safety, and the cost of operation. In this article a combination of a Cumulative Sum (CUSUM) algorithm and an improved input noise-aware extended Kalman filter (INAEKF) is proposed for the detection and identification of FDIAs in the voltage and current sensors of a battery stack. The series-connected stack is represented by equivalent circuit models, the SoC is modeled with a charge reservoir model and the states are estimated using the INAEKF. Further, the root mean squared error of the states’ estimation by the modified INAEKF was found to be superior to the traditional EKF. By employing the INAEKF, this article addresses the research gap that many state estimators make asymmetrical assumptions about the noise corrupting the system. Additionally, the INAEKF estimates the input allowing for the identification of FDIA, which many alternative methods are unable to achieve. The proposed algorithm was able to detect attacks in the voltage and current sensors in 99.16% of test cases, with no false positives. Utilizing the INAEKF compared to the standard EKF allowed for the identification of FDIA in the input of the system in 98.43% of test cases.

25 ENERGY STORAGE↗
DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗
DOE OSTI2021

Modeling airborne pathogen transport and transmission risks of SARS-CoV-2

An integrated modeling approach has been developed to better understand the relative impacts of different expiratory and environmental factors on airborne pathogen transport and transmission, motivated by the recent COVID-19 pandemic. Computational fluid dynamics (CFD) modeling was used to simulate spatial-temporal aerosol concentrations and quantified risks of exposure as a function of separation distance, exposure duration, environmental conditions (e.g., airflow/ventilation), and face coverings. The CFD results were combined with infectivity models to determine probability of infection, which is a function of the spatial-temporal aerosol concentrations, viral load, infectivity rate, viral viability, lung-deposition probability, and inhalation rate. Uncertainty distributions were determined for these parameters from the literature. Probabilistic analyses were performed to determine cumulative distributions of infection probabilities and to determine the most important parameters impacting transmission. This modeling approach has relevance to both pathogen and pollutant dispersion from expelled aerosol plumes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Decoding Resilience by Modeling Outage and Restoration Processes in Distribution Grids: A Pittsburgh Case Study

Climate-induced extreme weather events, such as floods and heatwaves, pose significant challenges to the resilience of urban power distribution grids. This paper examines the outage and restoration dynamics of Pittsburgh's power grid during the flood event in April 2024 and three heatwaves in June, July, and August 2024. We introduce a comprehensive modeling framework that integrates outage and restoration processes, enabling the quantification of resilience metrics, including total customer-hours of power outage, maximum residual values, and restoration durations across various ZIP codes. Our analysis highlights spatial disparities in outage impacts and restoration efficiencies, with ZIP Code 15222 experiencing the highest cumulative disruptions, while ZIP Code 15217 shows lower susceptibility. By linking statistical trends with weather events, this study underscores the critical need for targeted infrastructure upgrades and advanced restoration strategies. Furthermore, the proposed framework offers valuable insights for planning and managing resilient power systems in the face of increasing climate stress.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

WEST full tungsten operation with an ITER grade divertor

The mission of WEST (tungsten-W Environment in Steady-state Tokamak) is to explore long pulse operation in a full tungsten (W) environment for preparing next-step fusion devices (ITER and DEMO) with a focus on testing the ITER actively cooled W divertor in tokamak conditions. Following the successful completion of phase 1 (2016-2021), phase 2 started in December 2022 with the lower divertor made entirely of actively cooled ITER-grade tungsten mono-blocks. A boronization prior the first plasma attempt allowed for a smooth startup with the new divertor. Despite the reduced operating window due to tungsten, rapid progress has been made in long pulse operation, resulting in discharges with a pulse length of 100 s and an injected energy of around 300 MJ per discharge. Plasma startup studies were carried out with equatorial boron nitride limiters to compare them with tungsten limiters, while Ion Cyclotron Resonance Heating assisted startup was attempted. High fluence operation in attached regime, which was the main thrust of the first campaigns, already showed the progressive build up of deposits and appearance of dust, impacting the plasma operation as the plasma fluence increased. In total, the cumulated injected energy during the first campaigns reached 43 GJ and the cumulated plasma time exceeded 5 h. Demonstration of controlled X-Point Radiator regime is also reported, opening a promising route for investigating plasma exhaust and plasma-wall interaction issues in more detached regime. This paper summarises the lessons learned from the manufacturing and the first operation of the ITER-grade divertor, describing the progress achieved in optimising operation in a full W environment with a focus on long pulse operation and plasma wall interaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Cumulative fidelity of large-momentum-transfer clock atom interferometers in the presence of laser noise

Clock atom interferometry is an emerging technique in precision measurements that is particularly well suited for sensitivity enhancement through large momentum transfer (LMT). While current systems have demonstrated momentum separations of several hundreds of photon momenta, next-generation quantum sensors are targeting an LMT enhancement factor beyond 10 4 . However, the viability of LMT clock interferometers has recently come into question due to the potential impact of laser frequency noise. Here, in this work, we resolve this concern by analyzing the cumulative fidelity of sequential state inversions in an LMT atom interferometer. We show that the population error from 𝑛 pulses applied from alternating directions scales linearly with 𝑛. This is a significant advantage over the 𝑛 2 scaling that occurs when probing a two-level system 𝑛 times from the same direction. We further show that contributions to the interferometer signal from parasitic paths generated by imperfect pulses are negligible, for any loss mechanism. These results establish that laser frequency noise is not a practical limitation for the development of high-fidelity LMT clock atom interferometers.

Mach-Zehnder atom interferometry↗
DOE OSTI2025

Simulation of the radiological impact during selected space travel scenarios using the Monte Carlo code FLUKA

Radiation is one of the major challenges of space exploration and can negatively impact both biological and electronic systems, particularly in the case of long-term journeys or if the spaceship features inadequate shielding. Here, in this work, the cumulative dose levels from prompt radiation in the spacecraft are quantified alongside the residual dose contributions arising from activation of vessel components. The radiological impact was assessed for various space exploration scenarios, considering the same spaceship model featuring three shielding design variants. In each scenario, the radiation environment was generated with the Monte Carlo particle transport and interaction code FLUKA. These results can be used to quantify the contribution of prompt and residual dose in spacefaring ventures and help determine optimal radiation shielding needed to mitigate the overall radiological impact on both astronauts and equipment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

How Does Flow Alteration Propagate Across a Large, Highly Regulated Basin? Dam Attributes, Network Context, and Implications for Biodiversity

Abstract Large dams are a leading cause of river ecosystem degradation. Although dams have cumulative effects as water flows downstream in a river network, most flow alteration research has focused on local impacts of single dams. Here we examined the highly regulated Colorado River Basin (CRB) to understand how flow alteration propagates in river networks, as influenced by the location and characteristics of dams as well as the structure of the river network—including the presence of tributaries. We used a spatial Markov network model informed by 117 upstream‐downstream pairs of monthly flow series (2003–2017) to estimate flow alteration from 84 intermediate‐to‐large dams representing >83% of the total storage in the CRB. Using Least Absolute Shrinkage and Selection Operator regression, we then investigated how flow alteration was influenced by local dam properties (e.g., purpose, storage capacity) and network‐level attributes (e.g., position, upstream cumulative storage). Flow alteration was highly variable across the network, but tended to accumulate downstream and remained high in the main stem. Dam impacts were explained by network‐level attributes (63%) more than by local dam properties (37%), underscoring the need to consider network context when assessing dam impacts. High‐impact dams were often located in sub‐watersheds with high levels of native fish biodiversity, fish imperilment, or species requiring seasonal flows that are no longer present. These three biodiversity dimensions, as well as the amount of dam‐free downstream habitat, indicate potential to restore river ecosystems via controlled flow releases. Our methods are transferrable and could guide screening for dam reoperation in other highly regulated basins.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sustainable aviation fuel from ethanol: Techno-economic analysis and life cycle analysis

Sustainable aviation fuel (SAF) is crucial for improving energy security, enhancing domestic production, and reducing carbon emissions in the aviation sector. Among various SAF production technologies, the ethanol-to-jet (ETJ) pathway is a promising option due to its economic viability and technological maturity. This study integrates a techno-economic analysis (TEA) and a life cycle analysis (LCA) to evaluate emissions reduction strategies for SAF production via the ETJ pathway, considering use of ethanol derived from both corn grain and corn stover. Conventional corn grain-derived ETJ fuel reduces greenhouse gas (GHG) emissions by 22 % compared to fossil jet fuel, with potential reductions of 26 %–96 % when incorporating renewable energy sources, with a 6 %–32 % increase in the minimum fuel selling price (MFSP). Corn stover-derived ETJ achieves a 77 % GHG reduction but with higher MFSPs compared to corn grain ETJ. Carbon capture and storage (CCS without considering the cost for piping and sequestration, only compression) reduces the emissions of corn grain-derived ETJ by up to 32 gCO 2 e/MJ and enables negative emissions for corn stover-derived ETJ, with MFSP increases ranging from 1 % to 22 %. While carbon capture and utilization (CCU) increase ethanol yield by 47 %, it raises MFSPs by 54 % due to high electricity demand. Sustainable farming practices provide only limited carbon intensity (CI) reductions individually but do offer cumulative benefits when combined. These findings highlight the trade-offs between cost and environmental impact, providing insights to optimize SAF production strategies and support aviation sector goals for emissions reduction.

09 BIOMASS FUELS↗
DOE OSTI2024

via-wind (A Visual Impact Assessment Tool for Wind Turbines) [SWR-24-87]

Via-wind is an open-source tool for conducting visual impact assessments for wind turbines. It combines geographic information system (GIS) and 3D simulation methods to account for the key factors driving the visual impact of installed wind turbines, including distance, viewing angle, turbine orientation, visual exposure, and the cumulative effects of multiple turbines. This software is optimized for use in high-performance computing environments to enable large scale (e.g., country-wide) analysis, but can also be run on a single server or personal computer. For more information, please see the related journal article: https://www.sciencedirect.com/science/article/pii/S0306261924021846

Lopez, Anthony↗
DOE OSTI2025

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, “esm-flat10”, has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 – the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as “fast track” simulations.

Sanderson, Benjamin M↗
DOE OSTI2024

Fast neutron irradiation capability in existing thermal test reactors

In today’s nuclear industry, momentum towards the design, licensing, and construction of advanced nuclear demonstration plants, including fast reactors, is at a remarkably high level. However, there are currently no dedicated fast spectrum irradiation test facilities in the United States to support the development of fast spectrum technologies. As a result, a unique situation is developing where most of these plants will likely be designed by leveraging historic nuclear material technologies, but where the further optimization and advancement is impeded by the lack of fast neutron irradiation test facilities. While these circumstances present a challenge, there are some near-term opportunities that, if seized, can still help develop advanced fast reactor materials to a meaningful level of readiness to support future commercial fast reactors. Here, in this paper, we assess the feasibility of using thermal neutron filtering materials in existing experiment positions in the Advanced Test Reactor (ATR) at Idaho National Laboratory and the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory to simulate fast reactor test environments for nonfuel test specimens. Items investigated include the incident neutron flux (both fast and thermal), the total neutron fluence and cumulative atom displacements, helium production rate due to thermal neutron capture in nickel, and the potential impact that the thermal neutron filter material has on the cycle length of a given reactor. It is concluded that while HFIR provides the highest fast flux of all the options investigated, it is limited in the amount of thermal neutron filtering material that can be introduced into an experiment position without significantly affecting the operation of the reactor. Irradiation in Outboard-A positions in the ATR was found to be the most realistic near-term experiment avenue due to having ample space for several capsules in a moderately fast flux.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Role of the social factors in success of solar photovoltaic reuse and recycle programmes

By 2050, the cumulative mass of end-of-life photovoltaic (PV) modules may reach 80 Mt globally. The impacts could be mitigated by module recycling, repair and reuse; however, previous studies of PV circularity omit the consideration of critical social factors. Here we used an agent-based model to integrate social aspects with techno-economic factors, which provides a more realistic assessment of the circularity potential for previously studied interventions that assesses additional interventions that cannot be analysed using techno-economic analysis alone. We also performed a global sensitivity analysis using a machine-learning metamodel. We show that to exclude social factors underestimates the effect of lower recycling prices on PV material circularity, which highlights the relevance of considering social factors in future studies. Interventions aimed at changing customer attitudes about used PV boost the reuse of modules, although used modules can only satisfy one-third of the US demand during 2020–2050, which suggests that reuse should be complemented by recycling.

14 SOLAR ENERGY↗
DOE OSTI2025

Minimum GHG emissions and energy consumption of U.S. PET and polyolefin packaging supply chains in a circular economy

There is a wide agreement on the urgency of transforming linear management of plastics towards a circular economy model. However, no clear pathways exist as to required recycling technologies involved and system-wide environmental impacts. This study explores such pathways in the U.S. for the most commonly used packaging plastics through a combination of mechanical and emerging advanced recycling technologies. A system optimization model aimed at minimizing environmental impacts was developed to determine optimal end-of-life (EOL) management and locations of existing and emerging U.S. recycling infrastructures. Our study includes material flows from virgin resin production through semi-manufacturing processes to existing EOL disposal and recycling processes. An optimized circular plastics packaging system achieved greenhouse gas (GHG) emission savings of up to 28% and cumulative energy demand (CED) savings of up to 46%, compared to the linear economy. Moreover, these savings of GHG emissions and CED impacts represent a reduction of 0.16% and 0.49% compared to annual U.S. GHG emissions and energy consumption in 2022, respectively. The optimal recycling rates and systems-level circularity ranged from 78–99% and 57–75%, respectively. Increased energy savings led to increased GHG emissions showing a potential trade-off between GHG emissions and energy. Analysis of 40 scenarios showed the importance of material collection distances, blend limit of mechanically recycled resins, process yields, and mandated recycling rates for achieving a sustainable circular economy of plastics.

09 - BIOMASS FUELS↗