Chemical Characterization and Redox Potential of Coarse and Fine Particulate Matter (PM) in Underground and Ground-Level Rail Systems of the Los Angeles Metro

(1) Exposure of informal artisanal cookware makers to fine particles has not yet been characterized. The aim of this study was to characterize occupational exposure to fine particulate matter (PM4 and PM2.5) levels and fine particulate matter (PM2.5) elemental components; (2) Artisanal cookware makers were recruited from five cookware making sites. Exposure to fine particulate matter was measured for 17 male participants. SidePak personal aerosol monitors (AM520) were used to measure personal exposure to PM4, while a DustTrak monitor and an E-sampler were used to assess indoor and outdoor PM2.5 levels, respectively. A questionnaire was administered to capture information on demographic characteristics. The chemical characterization of indoor and outdoor PM2.5 filter mass was conducted using Wavelength Dispersive X-ray Fluorescence. Time series record of 15-min averages for indoor and outdoor PM2.5 levels were assessed; (3) The median (range) was 124 µg/m3 (23−100,000), 64 µg/m3 (1−6097) and 12 µg/m3 (4−1178), respectively, for personal PM4, indoor and outdoor PM2.5. The highest levels for many of the elemental components of PM2.5 were found in the outdoor PM2.5 filter mass and (4). The information generated during this study may assist in extending occupational health and safety strategies to artisanal cookware makers and developing targeted prevention initiatives.

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Optimal estimation for global ground-level fine particulate matter concentrations

Journal of Geophysical Research Atmospheres ◽

10.1002/jgrd.50479 ◽

2013 ◽

Vol 118 (11) ◽

pp. 5621-5636 ◽

Cited By ~ 81

Author(s):

Aaron van Donkelaar ◽

Randall V. Martin ◽

Robert J. D. Spurr ◽

Easan Drury ◽

Lorraine A. Remer ◽

...

Keyword(s):

Particulate Matter ◽

Fine Particulate Matter ◽

Optimal Estimation ◽

Ground Level ◽

Fine Particulate

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Oxidative potential of on-road fine particulate matter (PM 2.5 ) measured on major freeways of Los Angeles, CA, and a 10-year comparison with earlier roadside studies

Atmospheric Environment ◽

10.1016/j.atmosenv.2016.10.042 ◽

2017 ◽

Vol 148 ◽

pp. 102-114 ◽

Cited By ~ 30

Author(s):

Farimah Shirmohammadi ◽

Dongbin Wang ◽

Sina Hasheminassab ◽

Vishal Verma ◽

James J. Schauer ◽

...

Keyword(s):

Particulate Matter ◽

Los Angeles ◽

Fine Particulate Matter ◽

Oxidative Potential ◽

Pm 2.5 ◽

Fine Particulate

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Chemical characterization of fine particulate matter, and source apportionment of organic aerosol at three sites in New Delhi, India

10.5194/egusphere-egu2020-21813 ◽

2020 ◽

Cited By ~ 1

Author(s):

Sachchida Tripathi ◽

Vipul Lalchandani ◽

Varun Kumar ◽

Anna Tobler ◽

Navaneeth Thamban ◽

...

Keyword(s):

Particulate Matter ◽

Mass Spectra ◽

Fine Particulate Matter ◽

Time Of Flight ◽

Chemical Characterization ◽

New Delhi ◽

Aerosol Mass Spectrometer ◽

Aerosol Mass ◽

Fine Particulate

Atmospheric particulate matter has adverse effects on human health, and causes over 4 million deaths per year globally. New Delhi was ranked as world&#8217;s most polluted megacity with annual average PM2.5 concentration of ~140 ug.m-3. Thus, real time chemical characterization of fine particulate matter and identification of its sources is important for developing cost effective mitigation policies.Highly time resolved real-time chemical composition of PM2.5 was measured using Long-Time of Flight-Aerosol Mass Spectrometer (L-ToF-AMS) at Indian Institute of Technology Delhi and Time of Flight-Aerosol Chemical Speciation Monitor (ToF-ACSM) at Indian Institute of Tropical Meteorology, Delhi, and PM1 using High Resolution-Time of Flight-Aerosol Mass Spectrometer (HR-ToF-AMS) at Manav Rachna International University, Faridabad, Haryana located ~40 km downwind of Delhi during Jan-March, 2018. Black carbon concentration was measured using Aethalometer at all three sites. Unit mass resolution (UMR) and high resolution (HR) data analysis were performed on AMS and ACSM mass spectra to calculate organics, nitrate, sulfate and chloride concentrations. Positive Matrix Factorization (PMF) (Paatero and Tapper, 1994) of organic mass spectra was performed by applying multilinear engine (ME-2) algorithm using Sofi (Source finder) for identifying sources of OA.

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