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Atmospheric Modeling of Gas-Phase Po...

Horne, Jeremy Ryan.

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Atmospheric Modeling of Gas-Phase Pollutants, New Particle Formation, and Aerosol Aging under Future Climate and Emissions Scenarios.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Atmospheric Modeling of Gas-Phase Pollutants, New Particle Formation, and Aerosol Aging under Future Climate and Emissions Scenarios./
Author:	Horne, Jeremy Ryan.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	260 p.
Notes:	Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Contained By:	Dissertation Abstracts International80-01B(E).
Subject:	Engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10749535
ISBN:	9780438294660

Atmospheric Modeling of Gas-Phase Pollutants, New Particle Formation, and Aerosol Aging under Future Climate and Emissions Scenarios.
Horne, Jeremy Ryan.

Atmospheric Modeling of Gas-Phase Pollutants, New Particle Formation, and Aerosol Aging under Future Climate and Emissions Scenarios. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 260 p.

Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.

Thesis (Ph.D.)--University of California, Irvine, 2018.

The studies presented in this dissertation represent cutting-edge research in both fundamental and applied air quality modeling. In the first three chapters, a multidisciplinary approach is used to understand and investigate the importance of new chemistry that is not included in current air quality models. The results of laboratory experiments and theoretical calculations are used to develop and implement new chemical mechanisms into the UCI-CIT airshed model. In addition to the modifications to the model's chemical mechanism, changes to the model's inputs were also necessary prior to running air quality simulations. New chemical species that are unaccounted for in existing emissions inventories needed to be added, based on a combination of published information, experimental results, and field measurements conducted specifically for these studies. Additionally, emissions rates for existing species needed to be adjusted to better reflect present day conditions, or in some cases, explore potential future emissions scenarios. Results from these studies highlight the importance of collaborations between multidisciplinary teams of chemists and engineers to continuously improve air quality modeling capabilities. The novel chemistry included in these state-of-the-science modeling studies allows improved capability to simulate gas-phase pollutants, new particle formation, and aerosol aging in ways unachievable with other air quality models currently available. For example, results from Chapter 1 show that as fossil fuel combustion is phased out in an urban coastal area, particle formation will decrease substantially but still continue at a reduced rate due to the contribution of organosulfur compound (OSC) oxidation products. Furthermore, methanesulfonic acid generated simultaneously in OSC oxidation will become a significant contributor to particle formation, which should be taken into account in air quality and climate models. Chapter 2 demonstrates that indole is an effective precursor to SOA, and the UCI-CIT model showed significant potential for indole SOA formation driven by the oxidation of indole by OH. Indole SOA represents a previously unconsidered source of SOA that should be included in regional and global models, which tend to underestimate SOA concentrations. The air quality simulations conducted in Chapter 3 indicate that the inclusion of a previously unaccounted for sink for gas-phase ammonia intro an airshed model can significantly affect modeled ammonia and PM2.5 concentrations. Because inorganic particles comprise a large fraction of total PM2.5 mass, accurate modeling of gas-phase ammonia concentrations is essential for predicting future air quality. Models used in the development of air quality management strategies should account for changes in the concentration of ammonia due to its uptake by SOA to ensure accurate prediction of PM2.5 concentrations.

ISBN: 9780438294660Subjects--Topical Terms:

586835
Engineering.

Atmospheric Modeling of Gas-Phase Pollutants, New Particle Formation, and Aerosol Aging under Future Climate and Emissions Scenarios.
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245 1 0 $a Atmospheric Modeling of Gas-Phase Pollutants, New Particle Formation, and Aerosol Aging under Future Climate and Emissions Scenarios.
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500 $a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
500 $a Adviser: Donald Dabdub.
502 $a Thesis (Ph.D.)--University of California, Irvine, 2018.
520 $a The studies presented in this dissertation represent cutting-edge research in both fundamental and applied air quality modeling. In the first three chapters, a multidisciplinary approach is used to understand and investigate the importance of new chemistry that is not included in current air quality models. The results of laboratory experiments and theoretical calculations are used to develop and implement new chemical mechanisms into the UCI-CIT airshed model. In addition to the modifications to the model's chemical mechanism, changes to the model's inputs were also necessary prior to running air quality simulations. New chemical species that are unaccounted for in existing emissions inventories needed to be added, based on a combination of published information, experimental results, and field measurements conducted specifically for these studies. Additionally, emissions rates for existing species needed to be adjusted to better reflect present day conditions, or in some cases, explore potential future emissions scenarios. Results from these studies highlight the importance of collaborations between multidisciplinary teams of chemists and engineers to continuously improve air quality modeling capabilities. The novel chemistry included in these state-of-the-science modeling studies allows improved capability to simulate gas-phase pollutants, new particle formation, and aerosol aging in ways unachievable with other air quality models currently available. For example, results from Chapter 1 show that as fossil fuel combustion is phased out in an urban coastal area, particle formation will decrease substantially but still continue at a reduced rate due to the contribution of organosulfur compound (OSC) oxidation products. Furthermore, methanesulfonic acid generated simultaneously in OSC oxidation will become a significant contributor to particle formation, which should be taken into account in air quality and climate models. Chapter 2 demonstrates that indole is an effective precursor to SOA, and the UCI-CIT model showed significant potential for indole SOA formation driven by the oxidation of indole by OH. Indole SOA represents a previously unconsidered source of SOA that should be included in regional and global models, which tend to underestimate SOA concentrations. The air quality simulations conducted in Chapter 3 indicate that the inclusion of a previously unaccounted for sink for gas-phase ammonia intro an airshed model can significantly affect modeled ammonia and PM2.5 concentrations. Because inorganic particles comprise a large fraction of total PM2.5 mass, accurate modeling of gas-phase ammonia concentrations is essential for predicting future air quality. Models used in the development of air quality management strategies should account for changes in the concentration of ammonia due to its uptake by SOA to ensure accurate prediction of PM2.5 concentrations.
520 $a In the final chapter, a diverse team of industry personnel and researchers is assembled to assess the potential implementation of natural gas-fired distributed generation of electricity (DG) in the contiguous United States, including displacement of power from central power generation, and determine the potential impacts on air quality. DG market penetration estimates are translated into spatially and temporally resolved emissions and combined with other emissions projected to the year 2030 to conduct the air quality modeling. The Comprehensive Air Quality Model with Extensions (CAMx) is used to conduct the air quality simulations, which span several weeks and cover both summer and winter periods. This study explores a range of plausible scenarios and provides a modeling framework and methodology that can be applied in future studies to assess the potential implementation and impacts of DG. Results indicate that the operation of central power generation units can be affected by increased DG penetration and that most DG units in the U.S. emit at relatively high levels and significant emission reductions can be achieve through the implementation of stricter emissions limits. Overall, air quality impacts from DG are found to vary greatly based on meteorological conditions, proximity to emissions sources, the number and type of DG installations, and the emissions factors used for DG units.
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