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Quantification of the Seasonality and Vertical Dispersion Environment of PM2.5 Variation: A Comparative Analysis of Micro-Scale Wind-Based Buffer Methods

Increasing PM2.5 (particulate matter smaller than 2.5 micrometers) poses a significant health risk to people. Understanding variables critical to PM2.5 spatial and temporal variation is a first step towards protecting vulnerable populations from exposure. Previous studies investigate variables responsible for PM2.5 variation but have a limited temporal span. Moreover, although land-use classes are often taken into account, the vertical environment's influence (e.g., buildings, trees) on PM2.5 concentrations is often ignored and on-road circle buffers are used. To understand variables most critical to PM2.5 concentration variation, an air pollution sensor and GPS unit were affixed to a bicycle to sample for variables over three seasons (spring, summer, fall). Samples were taken on a route during the weekdays at four targeted hours (7AM, 11AM, 3PM, and 7PM) and joined with meteorological data. 3D morphology was assessed using LiDAR data and novel wind-based buffers. Wind speed only, wind direction only, and wind speed and direction buffers were computed and compared for their performance at capturing micro-scale urban morphological variables. Zonal statistics were used to compute morphological indicators under different wind assumptions in seasonal ordinary least squares regression models. A comprehensive wind and buffer performance analysis compares statistical significance for spatial and temporal variation of PM2.5. This study identifies the best wind parameters to use for wind-based buffer generation of urban morphology, which is expected to have implications for buffer design in future studies. Additionally, significant exposure hotspots for UNT students to PM2.5 pollution are identified.

Identiferoai:union.ndltd.org:unt.edu/info:ark/67531/metadc2137667
Date05 1900
CreatorsRay, Noah R.
ContributorsLiang, Lu, Dong, Pinliang, Kang, Wei
PublisherUniversity of North Texas
Source SetsUniversity of North Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation
FormatText
RightsPublic, Ray, Noah R., Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved.

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