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Download fileHaze Air Pollution Health Impacts of Breath-Borne VOCs
dataset
posted on 2022-05-13, 18:04 authored by Lu Zhang, Xinyue Li, Haoxuan Chen, Zhijun Wu, Min Hu, Maosheng YaoHere,
we investigated the use of breath-borne volatile organic
compounds (VOCs) for rapid monitoring of air pollution health effects
on humans. Forty-seven healthy college students were recruited, and
their exhaled breath samples (n = 235) were collected
and analyzed for VOCs before, on, and after two separate haze pollution
episodes using gas chromatography-ion mobility spectrometry (GC-IMS).
Using a paired t-test and machine learning model (Gradient Boosting
Machine, GBM), six exhaled VOC species including propanol and isoprene
were revealed to differ significantly among pre-, on-, and post-exposure
in both haze episodes, while none was found between clean control
days. The GBM model was shown capable of differentiating between pre-
and on-exposure to haze pollution with a precision of 90–100%
for both haze episodes. However, poor performance was detected for
the same model between two different clean days. In addition to gender
and particular haze occurrence influences, correlation analysis revealed
that NH4+, NO3–, acetic acid, mesylate, CO, NO2, PM2.5, and
O3 played important roles in the changes in breath-borne
VOC fingerprints following haze air pollution exposure. This work
has demonstrated direct evidence of human health impacts of haze pollution
while identifying potential breath-borne VOC biomarkers such as propanol
and isoprene for haze air pollution exposure.
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played important rolesion mobility spectrometryhuman health impactsgradient boosting machinedemonstrated direct evidenceclean control days90 – 100borne voc biomarkersmachine learning modelidentifying potential breathcorrelation analysis revealed3 </ subn </shown capablerapid monitoringpoor performanceims ).haze pollutionhaze episodesgbm modelborne vocs