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Browsing Research Data by Author "Bilsback, Kelsey"

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    ItemOpen Access
    Dataset associated with "A laboratory assessment of 120 air pollutant emissions from biomass and fossil fuel cookstoves
    (Colorado State University. Libraries, 2018) Bilsback, Kelsey
    Cookstoves emit many pollutants that are harmful to human health and the environment. However, most of the existing scientific literature focuses on fine particulate matter (PM2.5) and carbon monoxide (CO). We present an extensive dataset of speciated air pollution emissions from wood, charcoal, kerosene, and liquefied petroleum gas (LPG) cookstoves. One-hundred and twenty gas- and particle-phase constituents—including organic carbon, elemental carbon (EC), ultrafine particles (10-100 nm), inorganic ions, carbohydrates, and volatile/semi-volatile organic compounds (e.g., alkanes, alkenes, alkynes, aromatics, carbonyls, and polycyclic aromatic hydrocarbons [PAHs])—were measured in the exhaust from 26 stove/fuel combinations. We find that improved biomass stoves tend to reduce PM2.5 emissions, however, certain design features (e.g., insulation or a fan) tend to increase relative levels of other co-emitted pollutants (e.g., EC, ultrafine particles, formaldehyde, or PAHs depending on stove type). In contrast, the pressurized kerosene and LPG stoves reduced all pollutants relative to a traditional three-stone fire (≥93% and ≥79%, respectively). Finally, we find that PM2.5 and CO are not strong predictors of co-emitted pollutants, which is problematic because these pollutants may not be indicators of other cookstove smoke constituents (such as formaldehyde and acetaldehyde) that may be emitted at concentrations that are harmful to human health.
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    ItemOpen Access
    simpleSOM models for "A Computationally Efficient Model to Represent the Chemistry, Thermodynamics, and Microphysics of Secondary Organic Aerosol (simpleSOM): Model Development and Application to alpha-pinene SOA"
    (Colorado State University. Libraries, 2021) Jathar, Shantanu; Cappa, Christopher; He, Yicong; Pierce, Jeffrey; Chuang, Wayne; Bilsback, Kelsey; Seinfeld, John; Zaveri, Rahul; Shrivastava, Manish
    Secondary organic aerosols (SOAs) constitute an important fraction of fine-mode atmospheric aerosol mass. Frameworks used to develop SOA parameters from laboratory experiments and subsequently used to simulate SOA formation in atmospheric models make many simplifying assumptions about the processes that lead to SOA formation in the interest of computational efficiency. These assumptions can limit the ability of the model to predict the mass, composition, and properties of SOAs accurately. In this work, we developed a computationally efficient, process-level model named simpleSOM to represent the chemistry, thermodynamic properties, and microphysics of SOAs. simpleSOM simulates multigenerational gas-phase chemistry, phase-state-influenced kinetic gas/particle partitioning, heterogeneous chemistry, oligomerization reactions, and vapor losses to the walls of Teflon chambers. As a case study, we used simpleSOM to simulate SOA formation from the photooxidation of a-pinene. This was done to demonstrate the ability of the model to develop parameters that can reproduce environmental chamber data, to highlight the chemical and microphysical processes within simpleSOM, and discuss implications for SOA formation in chambers and in the real atmosphere. SOA parameters developed from experiments performed in the chamber at the California Institute of Technology (Caltech) reproduced observations of SOA mass yield, O:C, and volatility distribution gathered from other chambers. Sensitivity simulations suggested that multigenerational gas-phase aging contributed to nearly half of all SOAs and that in the absence of vapor wall losses, SOA production in the Caltech chamber could be nearly 50% higher. Heterogeneous chemistry did not seem to affect SOA formation over the short timescales for oxidation experienced in the chamber experiments. Simulations performed under atmospherically relevant conditions indicated that the SOA mass yields were sensitive to whether and how oligomerization reactions and the particle phase state were represented in the chamber experiment from which the parameters were developed. simpleSOM provides a comprehensive, process-based framework to consistently model the SOA formation and evolution in box and 3D models.