Effects of Vehicle Exhaust in Aged Adults Riding on Los Angeles Freeways.

Cascio, WE; Katwa, LC; Ws, Linn; Stram, DO; Zhu, Yu; Cascio, JL; Hinds, WC

doi:10.1164/ajrccm-conference.2009.179.1_meetingabstracts.a1175

Cited by 4 publications

(2 citation statements)

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“…PM 2.5 can affect the atmospheric visibility, play key roles in the formation of acid rain and climate change, and deteriorate local and regional air quality. Exposure to ambient PM 2.5 is one leading factor in human health [1,2]. In addition, the potential impacts on human health may vary by the chemical compositions of particles, which not only affect toxicity by the presence of specific toxic elements, Moreover, in average, there are 2.31 factories per square kilometer and many of them are located near commercial districts and residential areas [28].…”

Section: Introductionmentioning

confidence: 99%

Developing Land-Use Regression Models to Estimate PM2.5-Bound Compound Concentrations

Hsu

Hsiao

et al. 2018

Remote Sensing

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Epidemiology estimates how exposure to pollutants may impact human health. It often needs detailed determination of ambient concentrations to avoid exposure misclassification. However, it is unrealistic to collect pollutant data from each and every subject. Land-use regression (LUR) models have thus been used frequently to estimate individual levels of exposures to ambient air pollution. This paper used remote sensing and geographical information system (GIS) tools to develop ten regression models for PM2.5-bound compound concentration based on measurements of a six-year period including , OC, EC, Ba, Mn, Cu, Zn, and Sb. The explained variance (R2) of these LUR models ranging from 0.60 to 0.92 confirms that this study successfully estimated the fine spatial variability of PM2.5-bound compound concentrations in Taiwan where the distribution of traffic, industrial area, greenness, and culture-specific PM2.5 sources like temples collected from GIS and remote sensing data were main variables. In particular, while they were much less used, this study showcased the necessity of remote sensing data of greenness in future LUR studies for reducing the exposure bias. In terms of local residents’ health outcome or health effect indicators, this study further offers much-needed support for future air epidemiological studies. The results provide important insights into expanding the application of GIS and remote sensing on exposure assessment for PM2.5-bound compounds.

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Section: Introductionmentioning

confidence: 99%

Developing Land-Use Regression Models to Estimate PM2.5-Bound Compound Concentrations

Hsu

Hsiao

et al. 2018

Remote Sensing

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“…PM 2.5 that contains ultrafine particles (≤ 0.1 µm in aerodynamic diameter) can be more indicative of potential threats to human health than other size fractions (Cascio et al, 2009;Knol et al, 2009;Hoek et al, 2010) because they can easily penetrate into deeper regions of the lung. Recently, more frequent episodes of air quality deterioration have occurred in particular locations and during particular seasons in Taiwan (e.g., the winter episode of elevated PM (PM episode)).…”

Section: Introductionmentioning

confidence: 99%

Using a Mobile Measurement to Characterize Number, Surface Area, and Mass Concentrations of Ambient Fine Particles with Spatial Variability during and after a PM Episode

Hsu

Chiang

Chen

et al. 2016

Aerosol Air Qual. Res.

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Fine particles play a key role in regional air quality deterioration. Commonly used central-site monitoring data, which offer rough determinations of spatial particulate matter (PM) distributions, is insufficient to estimate potential local emissions or population exposure levels. This study characterizes the spatial variability of fine particles in suburban and rural regions during and after a winter episode of elevated PM (PM episode). Commercial instruments of high time resolution in a mobile laboratory platform were deployed to measure the distribution, number, surface area, and mass concentrations of fine particles. Spatial variations of those particle properties were mainly affected by regional feature, PM episode, local primary source and wind speed. Particle concentrations and size distributions were found to differ considerably during and after PM episode. The PM episode was found to exhibit a lower degree of spatial concentration contrast with respect to particle number, surface area and mass, where similar particle size patterns were distributed across all study regions with decreased particle number under nucleation and Aitken modes and increased number under the accumulation mode. The mobile measurement may supplement information on spatial particle distributions for estimating levels of population exposure and for characterizing detailed physical properties of short-term, high-exposed scenarios.

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Trace element characterization of fine particulate matter and assessment of associated health risk in mining area, transportation routes and institutional area of Dhanbad, India

Jena

Perwez

Singh

2019

Environ Geochem Health

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Effects of Vehicle Exhaust in Aged Adults Riding on Los Angeles Freeways.

Cited by 4 publications

References 0 publications

Developing Land-Use Regression Models to Estimate PM2.5-Bound Compound Concentrations

Developing Land-Use Regression Models to Estimate PM2.5-Bound Compound Concentrations

Using a Mobile Measurement to Characterize Number, Surface Area, and Mass Concentrations of Ambient Fine Particles with Spatial Variability during and after a PM Episode

Trace element characterization of fine particulate matter and assessment of associated health risk in mining area, transportation routes and institutional area of Dhanbad, India

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