ABSTRACT
We conducted an experimental case study to demonstrate the application of proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) for mobile breathing zone (BZ) monitoring of volatile chemical exposures in workplace environments during COVID-19 disinfection activities. The experiments were conducted in an architectural engineering laboratory-the Purdue zero Energy Design Guidance for Engineers (zEDGE) Tiny House, which served as a simulated workplace environment. Controlled disinfection activities were carried out on impermeable high-touch indoor surfaces, including the entry door, kitchen countertop, toilet bowl, bathroom sink, and shower. Worker inhalation exposure to volatile organic compounds (VOCs) was evaluated by attaching the PTR-TOF-MS sampling line to the researcher's BZ while the disinfection activity was carried out throughout the entire building. The results demonstrate that significant spatiotemporal variations in VOC concentrations can occur in the worker's BZ during multi-surface disinfection events. Application of high-resolution monitoring techniques, such as PTR-TOF-MS, are needed to advance characterization of worker exposures towards the development of appropriate mitigation strategies for volatile disinfectant chemicals.
Subject(s)
COVID-19 , Occupational Exposure , Humans , Protons , Disinfection , Mass Spectrometry/methods , WorkplaceABSTRACT
Surface cleaning using commercial disinfectants, which has recently increased during the coronavirus disease 2019 pandemic, can generate secondary indoor pollutants both in gas and aerosol phases. It can also affect indoor air quality and health, especially for workers repeatedly exposed to disinfectants. Here, we cleaned the floor of a mechanically ventilated office room using a commercial cleaner while concurrently measuring gas-phase precursors, oxidants, radicals, secondary oxidation products, and aerosols in real-time; these were detected within minutes after cleaner application. During cleaning, indoor monoterpene concentrations exceeded outdoor concentrations by two orders of magnitude, increasing the rate of ozonolysis under low (<10 ppb) ozone levels. High number concentrations of freshly nucleated sub-10-nm particles (≥105 cm-3) resulted in respiratory tract deposited dose rates comparable to or exceeding that of inhalation of vehicle-associated aerosols.
ABSTRACT
BACKGROUND: COVID-19 has caused a worldwide pandemic, making the early detection of the virus crucial. We present an approach for the determination of COVID-19 infection based on breath analysis. METHODS: A high sensitivity mass spectrometer was combined with artificial intelligence and used to develop a method for the identification of COVID-19 in human breath within seconds. A set of 1137 positive and negative subjects from different age groups, collected in two periods from two hospitals in the USA, from 26 August, 2020 until 15 September, 2020 and from 11 September, 2020 until 11 November, 2020, was used for the method development. The subjects exhaled in a Tedlar bag, and the exhaled breath samples were subsequently analyzed using a Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-ToF-MS). The produced mass spectra were introduced to a series of machine learning models. 70% of the data was used for these sub-models' training and 30% was used for testing. FINDINGS: A set of 340 samples, 95 positives and 245 negatives, was used for the testing. The combined models successfully predicted 77 out of the 95 samples as positives and 199 out of the 245 samples as negatives. The overall accuracy of the model was 81.2%. Since over 50% of the total positive samples belonged to the age group of over 55 years old, the performance of the model in this category was also separately evaluated on 339 subjects (170 negative and 169 positive). The model correctly identified 166 out of the 170 negatives and 164 out of the 169 positives. The model accuracy in this case was 97.3%. INTERPRETATION: The results showed that this method for the identification of COVID-19 infection is a promising tool, which can give fast and accurate results.
ABSTRACT
The COVID-19 pandemic has resulted in increased usage of ethanol-based disinfectants for surface inactivation of SARS-CoV-2 in buildings. Emissions of volatile organic compounds (VOCs) and particles from ethanol-based disinfectant sprays were characterized in real-time (1 Hz) via a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) and a high-resolution electrical low-pressure impactor (HR-ELPI+), respectively. Ethanol-based disinfectants drove sudden changes in the chemical composition of indoor air. VOC and particle concentrations increased immediately after application of the disinfectants, remained elevated during surface contact time, and gradually decreased after wiping. The disinfectants produced a broad spectrum of VOCs with mixing ratios spanning the sub-ppb to ppm range. Ethanol was the dominant VOC emitted by mass, with concentrations exceeding 103 µg m-3 and emission factors ranging from 101 to 102 mg g-1. Listed and unlisted diols, monoterpenes, and monoterpenoids were also abundant. The pressurized sprays released significant quantities (104-105 cm-3) of nano-sized particles smaller than 100 nm, resulting in large deposited doses in the tracheobronchial and pulmonary regions of the respiratory system. Inhalation exposure to VOCs varied with time during the building disinfection events. Much of the VOC inhalation intake (>60 %) occurred after the disinfectant was sprayed and wiped off the surface. Routine building disinfection with ethanol-based sprays during the COVID-19 pandemic may present a human health risk given the elevated production of volatile chemicals and nano-sized particles.