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Aerosol and Gas Measurements to Inform Public Health Policies.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Aerosol and Gas Measurements to Inform Public Health Policies./
Author:	Stockman, Tehya.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2024,
Description:	222 p.
Notes:	Source: Dissertations Abstracts International, Volume: 85-11, Section: A.
Contained By:	Dissertations Abstracts International85-11A.
Subject:	Environmental engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30995332
ISBN:	9798382718484

Aerosol and Gas Measurements to Inform Public Health Policies.
Stockman, Tehya.

Aerosol and Gas Measurements to Inform Public Health Policies. - Ann Arbor : ProQuest Dissertations & Theses, 2024 - 222 p.

Source: Dissertations Abstracts International, Volume: 85-11, Section: A.

Thesis (Ph.D.)--University of Colorado at Boulder, 2024.

This work addresses the growing need to include the science of aerosols and gases in public health policies. The COVID-19 pandemic brought to the forefront the importance of understanding aerosol respiratory emissions and how to control them to limit the spread of airborne diseases, particularly in indoor environments. Some respiratory activities are riskier than others, so I delved deeply into understanding aerosol emissions from musical performance to understand how risky it may be compared to other respiratory activities. The pandemic also highlighted disparities in those who had the highest mortality rates being those in lower-income neighborhoods and regularly experience higher exposures to PM2.5. To reduce exposure to both PM2.5 and respiratory aerosols, first, the science must be understood, and then policies must be implemented that are easily actionable, communicated clearly, and are ultimately used at a large scale by the public.The first project I conducted was characterizing respiratory aerosol emissions from various musical performers, including singers, theatre performers, woodwind players, and brass players. I conducted aerosol measurements using an aerosol particle sizer (APS) and ultra-high sensitivity aerosol spectrometer (UHSAS) to capture aerosol size distributions from 60nm - 10{phono}{aelig}m. I also used a Licor to measure CO2 as a tracer gas for the respiratory plumes, a technique often used by atmospheric chemists to understand highly variable plumes. I used the aerosol to CO2 ratio to estimate emission rates for the various musical performers. Most of the musicians had similar aerosol emission rates, except for the flute performers, who had significantly lower respiratory aerosol emissions.To complete this project, I collaborated with an interdisciplinary team across the University of Colorado Boulder, University of Maryland, Clemson University, and the National Federation of High School Associations to provide insights into respiratory aerosol production from musical performance and mitigation strategies to limit the spread of potentially infectious aerosol. The multi-disciplinary approach enabled the team to work quickly and understand various components of the system of aerosol production from musical performance. This work provides a framework for additional studies of respiratory aerosol by combining techniques of aerosol/gas phase measurements, flow visualization, and computational fluid dynamics (CFD) modeling.In addition, I summarize the respiratory aerosol mitigation policies for music classrooms that I co-developed with my team and presented to a multitude of stakeholders over the course of the COVID-19 pandemic. I show, using a completely-mixed-flow reactor model, how each of the recommendations lowers exposure to respiratory aerosols. This chapter ties together the findings from our research and others conducting similar research on respiratory aerosol emissions and transmission during the COVID-19 pandemic. A layered approach to reducing risk from respiratory aerosol transmission is presented. This includes strategies that reduce emissions from the source, reduce room-level aerosol concentrations, and reduce risk of others inhaling aerosol in the room.For my second project, I worked with the Love My Air team at the Denver Department of Public Health and Environment (DDPHE). LMA has been operating a network of over 30 low-cost PM2.5 sensors, with the oldest sensors brought online in 2018. While sensor networks are{A0}growing in popularity and many corrections have been developed for low-cost PM2.5 sensors, there is a gap in understanding how these low-cost sensors and corrections perform over multiple years. Through this work, I evaluated sensor bias and variability over multiple years. I expand upon previous work on PM2.5 sensor corrections by evaluating the corrections for the sensor network using multi-linear regression and machine learning models and considering additional variables for these models including meteorology, smoke events, dust events, and sensor age.After developing correction algorithms to improve the performance of the Love My Air sensor network, I presented my findings to DDPHE. I used the top-performing correction algorithm to create a comprehensive 5-year data set of PM2.5 sensor data for the LMA network and performed spatial analysis on the data. I shared my findings on the variations in PM2.5 concentrations across Denver and how these disparities related to Denver's neighborhoods and demographics to DDPHE so they can begin to act on data from the Love My Air network.Through my dissertation work with various multi-disciplinary teams, I discovered the importance of aerosol and gas-phase science in promoting healthy environments and reducing the public's exposure to health risks from aerosols, whether it be respiratory aerosols or PM2.5.

ISBN: 9798382718484Subjects--Topical Terms:

548583
Environmental engineering.
Subjects--Index Terms:

Aerosols

Aerosol and Gas Measurements to Inform Public Health Policies.
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300 $a 222 p.
500 $a Source: Dissertations Abstracts International, Volume: 85-11, Section: A.
500 $a Advisor: Miller, Shelly.
502 $a Thesis (Ph.D.)--University of Colorado at Boulder, 2024.
520 $a This work addresses the growing need to include the science of aerosols and gases in public health policies. The COVID-19 pandemic brought to the forefront the importance of understanding aerosol respiratory emissions and how to control them to limit the spread of airborne diseases, particularly in indoor environments. Some respiratory activities are riskier than others, so I delved deeply into understanding aerosol emissions from musical performance to understand how risky it may be compared to other respiratory activities. The pandemic also highlighted disparities in those who had the highest mortality rates being those in lower-income neighborhoods and regularly experience higher exposures to PM2.5. To reduce exposure to both PM2.5 and respiratory aerosols, first, the science must be understood, and then policies must be implemented that are easily actionable, communicated clearly, and are ultimately used at a large scale by the public.The first project I conducted was characterizing respiratory aerosol emissions from various musical performers, including singers, theatre performers, woodwind players, and brass players. I conducted aerosol measurements using an aerosol particle sizer (APS) and ultra-high sensitivity aerosol spectrometer (UHSAS) to capture aerosol size distributions from 60nm - 10{phono}{aelig}m. I also used a Licor to measure CO2 as a tracer gas for the respiratory plumes, a technique often used by atmospheric chemists to understand highly variable plumes. I used the aerosol to CO2 ratio to estimate emission rates for the various musical performers. Most of the musicians had similar aerosol emission rates, except for the flute performers, who had significantly lower respiratory aerosol emissions.To complete this project, I collaborated with an interdisciplinary team across the University of Colorado Boulder, University of Maryland, Clemson University, and the National Federation of High School Associations to provide insights into respiratory aerosol production from musical performance and mitigation strategies to limit the spread of potentially infectious aerosol. The multi-disciplinary approach enabled the team to work quickly and understand various components of the system of aerosol production from musical performance. This work provides a framework for additional studies of respiratory aerosol by combining techniques of aerosol/gas phase measurements, flow visualization, and computational fluid dynamics (CFD) modeling.In addition, I summarize the respiratory aerosol mitigation policies for music classrooms that I co-developed with my team and presented to a multitude of stakeholders over the course of the COVID-19 pandemic. I show, using a completely-mixed-flow reactor model, how each of the recommendations lowers exposure to respiratory aerosols. This chapter ties together the findings from our research and others conducting similar research on respiratory aerosol emissions and transmission during the COVID-19 pandemic. A layered approach to reducing risk from respiratory aerosol transmission is presented. This includes strategies that reduce emissions from the source, reduce room-level aerosol concentrations, and reduce risk of others inhaling aerosol in the room.For my second project, I worked with the Love My Air team at the Denver Department of Public Health and Environment (DDPHE). LMA has been operating a network of over 30 low-cost PM2.5 sensors, with the oldest sensors brought online in 2018. While sensor networks are{A0}growing in popularity and many corrections have been developed for low-cost PM2.5 sensors, there is a gap in understanding how these low-cost sensors and corrections perform over multiple years. Through this work, I evaluated sensor bias and variability over multiple years. I expand upon previous work on PM2.5 sensor corrections by evaluating the corrections for the sensor network using multi-linear regression and machine learning models and considering additional variables for these models including meteorology, smoke events, dust events, and sensor age.After developing correction algorithms to improve the performance of the Love My Air sensor network, I presented my findings to DDPHE. I used the top-performing correction algorithm to create a comprehensive 5-year data set of PM2.5 sensor data for the LMA network and performed spatial analysis on the data. I shared my findings on the variations in PM2.5 concentrations across Denver and how these disparities related to Denver's neighborhoods and demographics to DDPHE so they can begin to act on data from the Love My Air network.Through my dissertation work with various multi-disciplinary teams, I discovered the importance of aerosol and gas-phase science in promoting healthy environments and reducing the public's exposure to health risks from aerosols, whether it be respiratory aerosols or PM2.5.
590 $a School code: 0051.
650 4 $a Environmental engineering. $3 548583
650 4 $a Public health. $3 534748
650 4 $a Atmospheric chemistry. $3 544140
650 4 $a Public policy. $3 532803
653 $a Aerosols
653 $a Machine learning
653 $a PM2.5 sensors
653 $a Airborne diseases
653 $a Ultra-high sensitivity aerosol spectrometer
653 $a Respiratory aerosols
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690 $a 0630
690 $a 0800
690 $a 0371
690 $a 0573
710 2 $a University of Colorado at Boulder. $b Civil, Environmental, and Architectural Engineering. $3 3350108
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791 $a Ph.D.
792 $a 2024
793 $a English
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