Publications by authors named "William M Barrett"

Chemical release data are essential for performing chemical risk assessments to understand the potential exposures arising from industrial processes. Often, these data are unknown or unavailable and must be estimated. A case study of volatile organic compound releases during extrusion-based additive manufacturing is used here to explore the viability of various regression methods for predicting chemical releases to inform chemical assessments.

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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.

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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.

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The evaluation of potential alternatives for chemicals of concern (CoC) requires an understanding of their potential human health and environmental impacts during the manufacture, use, recycle and disposal life stages. During the manufacturing phase, the processes used to produce a desired chemical are defined based on the sequence of chemical reactions and unit operations required to produce the molecule and separate it from other materials used or produced during its manufacture. This paper introduces and demonstrates a tool that links a chemical's structure to information about its synthesis route and the manufacturing process for that chemical.

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A framework is presented to address the toolbox of chemical release estimation methods available for manufacturing processes. Although scientists and engineers often strive for increased accuracy, the development of fit-for-purpose release estimates can speed results that could otherwise delay decisions important to protecting human health and the environment. A number of release estimation approaches are presented, with the newest using decision trees for regression and prediction.

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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.

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A methodology is described for developing a gate-to-gate life cycle inventory (LCI) of a chemical manufacturing process to support the application of life cycle assessment in the design and regulation of sustainable chemicals. The inventories were derived by first applying process design and simulation to develop a process flow diagram describing the energy and basic material flows of the system. Additional techniques developed by the United States Environmental Protection Agency for estimating uncontrolled emissions from chemical processing equipment were then applied to obtain a detailed emission profile for the process.

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Demands for quick and accurate life cycle assessments create a need for methods to rapidly generate reliable life cycle inventories (LCI). Data mining is a suitable tool for this purpose, especially given the large amount of available governmental data. These data are typically applied to LCIs on a case-by-case basis.

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The releasable asbestos field sampler (RAFS) was developed as an alternative to activity-based sampling (ABS; personal breathing zone sampling during a simulated activity). The RAFS utilizes a raking motion to provide the energy that releases particulate material from the soil and aerosolizes the asbestos fibers. A gentle airflow laterally transports the generated aerosol inside of a tunnel to one end where filter sampling cassettes or real-time instruments are used to measure asbestos and particulate release.

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Tests of the compatibility of geomembrane (GM) samples with waste were conducted using U.S. Environmental Protection Agency (EPA) Method 9090 and the Comprehensive Testing System (CTS).

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