rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Analyzing Factors Affecting In-cab Air Quality In Heavy-Duty Diesel Construction Equipment
  name:
    name part: Kasar, Hardik
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Lewis, Phil
    role:
      role term: thesis advisor.
  name:
    name part: Behzadan, Amir
    role:
      role term: thesis advisor.
  name:
    name part: Texas A&M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2023
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: The United States construction industry is one of the largest sectors providing labor jobs. As construction involves several hazards on the job site every day, ensuring a safe and healthy workplace for all construction workers is a challenge. One of the hazards is exposure to air pollutants, which can have many adverse effects on human health. Among all the construction workers, six percent are construction equipment operators. The operator sits inside an enclosed cabin near the exhaust tailpipe of the equipment. Given the number of pollutants emitted through the tailpipe, the air quality inside the cabin is a significant concern for the operator's health. The purpose of this study was to add knowledge to the understudied occupation of construction equipment operators exposed to diesel exhaust pollutants. The primary objectives of this research were to identify and characterize factors affecting air quality inside the operator cabin of heavy-duty diesel construction equipment. This research considered six factors to collect and analyze the data: (a) tailpipe pollutant emissions, (b) in-cab air quality data, (c) equipment duty cycles, (d) diesel engine performance, (e) operator behavior, (f) job site/environmental conditions. We collected real-world 13 number of datasets for 13 days of testing. The data analysis was performed in two stages. In the first stage, descriptive statistics such as mean, standard deviation, maximum, and minimum were determined. The simple regression analysis was performed in the second stage to determine the correlation among potential factors. The electronic version of this dissertation is accessible from https://hdl.handle.net/1969.1/197344
  note: by Hardik Kasar.
  note: "Major Subject: Construction Management"
  note: Includes vita.
  note: Master of Science Texas A&M University 2022 https://hdl.handle.net/1969.1/197344
  note: Includes bibliographical references.
  note: Text (Thesis)
  subject:
    topic: Major Construction Management
  subject:
    topic: Indoor Air Quality
  subject:
    topic: Heavy-Duty Diesel
  subject:
    topic: Diesel Exhaust
  subject:
    topic: Construction Equipment
  subject:
    topic: Construction Operator
  subject:
    topic: Carbon Dioxide
  subject:
    topic: Particulate Matter
  subject:
    topic: Air Pollution
  identifier: https://hdl.handle.net/1969.1/197344
  record info:
    record content source: TXA
    record creation date: 240819
    record change date: 20240820145900.4
    record identifier: in00005463676
    language of cataloging:
      language term: eng