Material Flow Analysis and Occupational Exposure Assessment in Additive Manufacturing End-of-Life Material Management.

Additive manufacturing (AM) offers a variety of material manufacturing techniques for a wide range of applications across many industries. Most efforts at process optimization and exposure assessment for AM are centered around the manufacturing process. However, identifying the material allocation and potentially harmful exposures in end-of-life (EoL) management is equally crucial to mitigating environmental releases and occupational health impacts within the AM supply chain. This research tracks the allocation and potential releases of AM EoL materials within the US through a material flow analysis. Of the generated AM EoL materials, 58% are incinerated, 33% are landfilled, and 9% are recycled by weight. The generated data set was then used to examine the theoretical occupational hazards during AM EoL material management practices through generic exposure scenario assessment, highlighting the importance of ventilation and personal protective equipment at all stages of AM material management. This research identifies pollution sources, offering policymakers and stakeholders insights to shape pollution prevention and worker safety strategies within the US AM EoL management pathways.

Prehospital Validation of the Assessment of Blood Consumption (ABC) Score.

INTRODUCTION: The Assessment of Blood Consumption (ABC) score is a previously validated scoring system designed to predict which severely injured trauma patients will require massive transfusion. When the ABC score is used in the prehospital setting to activate massive transfusion at the receiving hospital, a 23% decrease in mortality has been demonstrated. However, the ABC score was developed and validated using hospital data from the emergency department (ED). The sensitivity and specificity of the ABC score when calculated using data from the prehospital setting are unknown. We hypothesized that the sensitivity and specificity of the prehospital ABC score will be similar to the sensitivity and specificity of the ED ABC score. METHODS: A 5-year retrospective analysis (2015-2019) of highest-activation adult trauma patients arriving to a quaternary Level I trauma center by hospital-based helicopter air medical service (HEMS) was performed. Demographic, prehospital, ED triage, and blood product utilization data were collected. Prehospital ABC score was calculated using the highest heart rate, lowest systolic blood pressure, and focused assessment with sonography for trauma (FAST) exam results obtained prior to arrival at the trauma center. ED ABC score was calculated using ED triage vital signs and ED FAST results. Sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristics (AUROC) curve were calculated for each ABC score. RESULTS: 2,067 patients met inclusion criteria. Mean age 39 (±17) years, 76% male, 22% penetrating mechanism. Of these, 128 patients (6%) received massive transfusion using the definition from the original study. Prehospital ABC score at a cutoff of 2 was 51% sensitive and 85% specific for predicting massive transfusion, with 83% correctly classified and an AUROC = 0.73. ED ABC score at the same cutoff was 60% sensitive and 84% specific, with 83% correctly classified and an AUROC = 0.81. By logistic regression, the odds of massive transfusion increased by 2.76 for every 1-point increase in prehospital ABC score (95%CI 2.25-3.37, p < 0.001). CONCLUSIONS: The ABC score is a useful prehospital tool for identifying who will require massive transfusion. Future studies to evaluate the effect of the prehospital ABC score on clinical care and mortality are necessary.

Understanding the trade-offs of national municipal solid waste estimation methods for circular economy policy.

Policies embracing circular economy concepts have taken hold in national legislation around the world. As the number of governments and organizations adopting circular economy policies increases, so does the need for accurate and timely measurement of material resource flows. Since many countries do not have access to centrally reported municipal solid waste (MSW) data, estimation and modeling are critical in evaluating circular economy policy effectiveness. The purpose of this paper is to examine three modeling approaches estimating national MSW data in the United States, including industry-based material flow analysis, waste-extended input-output modeling, and aggregated regional waste reporting. We establish five criteria to guide the analysis through the context of policy monitoring (data quality, flow totality, update frequency, sensitivity to disruption, and product granularity) and use these criteria to analyze and score each model. We then use a literature search to identify five, internationally-implemented options for circular economy policy and determine the data and modeling components that are most helpful in evaluating policy effectiveness. Finally, we provide a crosswalk of the model scores and policy needs to inform the suitability of model selection by policy type. We found that data quality and update frequency are identified as critical components for evaluating circular economy policies within the models evaluated, and can both be fulfilled by aggregated regional waste reporting. Flow totality, sensitivity to disruption, and product granularity requirements vary by both model and policy types. While none of the evaluated models satisfy the combination of requirements for any of the five policies, industry-based material flow analysis offers flow totality for extended producer responsibility, landfill bans, and recycling rate target policies that typically require it. The waste-extended input-output model can provide disruption sensitivity and product granularity as needed for policies like minimum recycled content and market restrictions. Policy developers in areas where strong centralized data collection is not an option should design policy action(s) with modeling tradeoffs in mind, including the potential hybridization of modeling approaches that may provide the most accurate national MSW estimates.

Review of generic scenario environmental release and occupational exposure models used in chemical risk assessment.

Under the Toxic Substances Control Act (TSCA), the United States Environmental Protection Agency (USEPA) is required to determine whether a new chemical substance poses an unreasonable risk to human health or the environment before the chemical is manufactured in or imported into the United States. This manuscript provides a review of the process used to evaluate the risk associated with a chemical based on the scenarios and models used in the evaluation. Specifically, the Generic Scenarios and Emission Scenario Documents developed by the USEPA were reviewed, along with background documentation prepared by USEPA to identify the core elements of the environmental release and occupational exposure scenarios used to assess the risk of the chemical being evaluated. Additionally, this contribution provides an overview of methods used to model occupational exposures and environmental releases as part of the chemical evaluation process used in other jurisdictions, along with work being performed to improve these models. Finally, the alternative methods to evaluate occupational exposures and environmental releases that may be used as part of the decision-making process regarding a chemical are identified. The contribution provides a path forward for reducing the time required and improving the chemical evaluation of the unreasonable risk determination regarding the manufacture or import of a chemical.

Analyzing Economy-Scale Solid Waste Generation Using the United States Environmentally-Extended Input-Output Model.

The United States Environmentally-Extended Input-Output (USEEIO) model includes commercial enterprises from 386 industrial sectors of the economy. The purpose of this work is to model the commercial generation of three streams of solid waste from USEEIO sectors: hazardous waste, non-hazardous waste excluding construction, and non-hazardous waste from construction. The waste accounts cover 536 waste materials, with commercial non-hazardous waste presently limited to municipal solid waste and construction and demolition debris. Total combined generation for all streams based on 2015 economic activity is approximately 775 million metric tons, with concrete from construction activities accounting for 44% of this mass. The chemical and plastics industries generate the most commercial hazardous waste per dollar of economic output. In most cases, waste materials such as paper, plastic, and metals are generated in greater quantities per dollar of industry output when compared to commercial construction materials and hazardous waste. When considering direct waste generation within an industry, USEEIO model rankings identified the highway and street construction and chemical manufacturing industries as potential areas to continue to pursue new innovations in material use. The rankings change when considering final consumption of goods and services, with various construction industries and state and local governments becoming more prominent. The full detailed waste models are publicly available and will be incorporated into future USEEIO releases. Quantification of waste material generation across the economy is an essential part of decision making because it will highlight areas where intervention may be beneficial.

Enhancing life cycle chemical exposure assessment through ontology modeling.

In its 2014 report, A Framework Guide for the Selection of Chemical Alternatives, the National Academy of Sciences placed increased emphasis on comparative exposure assessment throughout the life cycle (i.e., from manufacturing to end-of-life) of a chemical. The inclusion of the full life cycle greatly increases the data demands for exposure assessments, including both the quantity and type of data. High throughput tools for exposure estimation add to this challenge by requiring rapid accessibility to data. In this work, ontology modeling was used to bridge the domains of exposure modeling and life cycle inventory modeling to facilitate data sharing and integration. The exposure ontology, ExO, is extended to describe human exposure to consumer products, while an inventory modeling ontology, LciO, is formulated to support automated data mining. The core ontology pieces are connected using a bridging ontology and discussed through a theoretical example to demonstrate how data from LCA can be leveraged to support rapid exposure modeling within a life cycle context.

Toward Automated Inventory Modeling in Life Cycle Assessment: The Utility of Semantic Data Modeling to Predict Real-World Chemical Production.

A set of coupled semantic data models, i.e., ontologies, are presented to advance a methodology toward automated inventory modeling of chemical manufacturing in life cycle assessment. The cradle-to-gate life cycle inventory for chemical manufacturing is a detailed collection of the material and energy flows associated with a chemical's supply chain. Thus, there is a need to manage data describing both the lineage (or synthesis pathway) and processing conditions for a chemical. To this end, a Lineage ontology is proposed to reveal all the synthesis steps required to produce a chemical from raw materials, such as crude oil or biomaterials, while a Process ontology is developed to manage data describing the various unit processes associated with each synthesis step. The two ontologies are coupled such that process data, which is the basis for inventory modeling, is linked to lineage data through key concepts like the chemical reaction and reaction participants. To facilitate automated inventory modeling, a series of SPARQL queries, based on the concepts of ancestor and parent, are presented to generate a lineage for a chemical of interest from a set of reaction data. The proposed ontologies and SPARQL queries are evaluated and tested using a case study of nylon-6 production. Once a lineage is established, the process ontology can be used to guide inventory modeling based on both data mining (top-down) and simulation (bottom-up) approaches. The ability to generate a cradle-to-gate life cycle for a chemical represents a key achievement toward the ultimate goal of automated life cycle inventory modeling.

Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals.

Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those originating from consumer products and building materials) that have traditionally been excluded from LCA. A new generation of rapid human exposure modeling and high-throughput toxicity testing is transforming chemical risk prioritization and provides an opportunity for integration of screening-level risk assessment (RA) with LCA. The combined LCA and RA approach considers environmental impacts of products alongside risks to human health, which is consistent with regulatory frameworks addressing RA within a sustainability mindset. A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in a consumer product. The case study demonstrates how these new risk screening tools can be used to inform toxicity impact estimates in LCA and highlights needs for future research. The framework provides a basis for developing tools and methods to support decision making on the use of chemicals in products.

Evaluating the environmental impacts of a nano-enhanced field emission display using life cycle assessment: a screening-level study.

Carbon nanotube (CNT) field emission displays (FEDs) are currently in the product development stage and are expected to be commercialized in the near future because they offer image quality and viewing angles comparable to a cathode ray tube (CRT) while using a thinner structure, similar to a liquid crystal display (LCD), and enable more efficient power consumption during use. To address concerns regarding the environmental performance of CNT-FEDs, a screening-level, cradle-to-grave life cycle assessment (LCA) was conducted based on a functional unit of 10,000 viewing hours, the viewing lifespan of a CNT-FED. Contribution analysis suggests the impacts for material acquisition and manufacturing are greater than the combined impacts for use and end-of-life. A scenario analysis of the CNT paste composition identifies the metal components used in the paste are key contributors to the impacts of the upstream stages due to the impacts associated with metal preparation. Further improvement of the manufacturing impacts is possible by considering the use of plant-based oils, such as rapeseed oil, as alternatives to organic solvents for dispersion of CNTs. Given the differences in viewing lifespan, the impacts of the CNT-FED were compared with a LCD and a CRT display to provide more insight on how to improve the CNT-FED to make it a viable product alternative. When compared with CRT technology, CNT-FEDs show better environmental performance, whereas a comparison with LCD technology indicates the environmental impacts are roughly the same. Based on the results, the enhanced viewing capabilities of CNT-FEDs will be a more viable display option if manufacturers can increase the product's expected viewing lifespan.