Electronic Nose Development and Preliminary Human Breath Testing for Rapid, Non-Invasive COVID-19 Detection.

We adapted an existing, spaceflight-proven, robust "electronic nose" (E-Nose) that uses an array of electrical resistivity-based nanosensors mimicking aspects of mammalian olfaction to conduct on-site, rapid screening for COVID-19 infection by measuring the pattern of sensor responses to volatile organic compounds (VOCs) in exhaled human breath. We built and tested multiple copies of a hand-held prototype E-Nose sensor system, composed of 64 chemically sensitive nanomaterial sensing elements tailored to COVID-19 VOC detection; data acquisition electronics; a smart tablet with software (App) for sensor control, data acquisition and display; and a sampling fixture to capture exhaled breath samples and deliver them to the sensor array inside the E-Nose. The sensing elements detect the combination of VOCs typical in breath at parts-per-billion (ppb) levels, with repeatability of 0.02% and reproducibility of 1.2%; the measurement electronics in the E-Nose provide measurement accuracy and signal-to-noise ratios comparable to benchtop instrumentation. Preliminary clinical testing at Stanford Medicine with 63 participants, their COVID-19-positive or COVID-19-negative status determined by concomitant RT-PCR, discriminated between these two categories of human breath with a 79% correct identification rate using "leave-one-out" training-and-analysis methods. Analyzing the E-Nose response in conjunction with body temperature and other non-invasive symptom screening using advanced machine learning methods, with a much larger database of responses from a wider swath of the population, is expected to provide more accurate on-the-spot answers. Additional clinical testing, design refinement, and a mass manufacturing approach are the main steps toward deploying this technology to rapidly screen for active infection in clinics and hospitals, public and commercial venues, or at home.

Impacts of COVID-19's restriction measures on personal exposure to VOCs and aldehydes in Taipei City.

The Coronavirus Disease 2019 (COVID-19) pandemic provided an unprecedented natural experiment, that allowed us to investigate the impacts of different restrictive measures on personal exposure to specific volatile organic compounds (VOCs) and aldehydes and resulting health risks in the city. Ambient concentrations of the criteria air pollutants were also evaluated. Passive sampling for VOCs and aldehydes was conducted for graduate students and ambient air in Taipei, Taiwan, during the Level 3 warning (strict control measures) and Level 2 alert (loosened control measures) of the COVID-19 pandemic in 2021-2022. Information on the daily activities of participants and on-road vehicle counts nearby the stationary sampling site during the sampling campaigns were recorded. Generalized estimating equations (GEE) with adjusted meteorological and seasonal variables were used to estimate the effects of control measures on average personal exposures to the selected air pollutants. Our results showed that ambient CO and NO2 concentrations in relation to on-road transportation emissions were significantly reduced, which led to an increase in ambient O3 concentrations. Exposure to specific VOCs (benzene, methyl tert-butyl ether (MTBE), xylene, ethylbenzene, and 1,3-butadiene) associated with automobile emissions were remarkably decreased by ~40-80 % during the Level 3 warning, resulting in 42 % and 50 % reductions of total incremental lifetime cancer risk (ILCR) and hazard index (HI), respectively, compared with the Level 2 alert. In contrast, the exposure concentration and calculated health risks in the selected population for formaldehyde increased by ~25 % on average during the Level 3 warning. Our study improves knowledge of the influence of a series of anti-COVID-19 measures on personal exposure to specific VOCs and aldehydes and its mitigations.

Diagnostic performance of eNose technology in COVID-19 patients after hospitalization.

BACKGROUND: Volatile organic compounds (VOCs) produced by human cells reflect metabolic and pathophysiological processes which can be detected with the use of electronic nose (eNose) technology. Analysis of exhaled breath may potentially play an important role in diagnosing COVID-19 and stratification of patients based on pulmonary function or chest CT. METHODS: Breath profiles of COVID-19 patients were collected with an eNose device (SpiroNose) 3 months after discharge from the Leiden University Medical Centre and matched with breath profiles from healthy individuals for analysis. Principal component analysis was performed with leave-one-out cross validation and visualised with receiver operating characteristics. COVID-19 patients were stratified in subgroups with a normal pulmonary diffusion capacity versus patients with an impaired pulmonary diffusion capacity (DLCOc < 80% of predicted) and in subgroups with a normal chest CT versus patients with COVID-19 related chest CT abnormalities. RESULTS: The breath profiles of 135 COVID-19 patients were analysed and matched with 174 healthy controls. The SpiroNose differentiated between COVID-19 after hospitalization and healthy controls with an AUC of 0.893 (95-CI, 0.851-0.934). There was no difference in VOCs patterns in subgroups of COVID-19 patients based on diffusion capacity or chest CT. CONCLUSIONS: COVID-19 patients have a breath profile distinguishable from healthy individuals shortly after hospitalization which can be detected using eNose technology. This may suggest ongoing inflammation or a common repair mechanism. The eNose could not differentiate between subgroups of COVID-19 patients based on pulmonary diffusion capacity or chest CT.

Measuring the quantity of harmful volatile organic compounds inhaled through masks.

An increase in the concentration of environmental particulate matter and the spread of the COVID-19 virus have dramatically increased our time spent wearing masks. If harmful chemicals are released from these masks, there may be harmful effects on human health. In this study, the concentration of volatile organic compounds (VOCs) emitted from some commonly used masks was assessed qualitatively and quantitatively under diverse conditions (including different mask material types, time between opening the product and wearing, and mask temperature). In KF94 masks, 1-methoxy-2-propanol (221 ± 356 µg m-3), N,N-dimethylacetamide (601 ± 450 µg m-3), n-hexane (268 ± 349 µg m-3), and 2-butanone (160 ± 244 µg m-3) were detected at concentrations 22.9-147 times higher than those found in masks made from other materials, such as cotton and other functional fabrics. In addition, in KF94 masks, the total VOC (TVOC) released amounted to 3730 ± 1331 µg m-3, about 14 times more than that released by the cotton masks (267.5 ± 51.6 µg m-3). In some KF94 masks, TVOC concentration reached over 4000 µg m-3, posing a risk to human health (based on indoor air quality guidelines established by the German Environment Agency). Notably, 30 min after KF94 masks were removed from their packaging, TVOC concentrations decreased by about 80% from their initial levels to 724 ± 5.86 µg m-3; furthermore, 6 h after removal, TVOC concentrations were found to be less than 200 µg m-3. When the temperature of the KF94 masks was raised to 40 oC, TVOC concentrations increased by 119-299%. Since the types and concentrations of VOCs that will be inhaled by mask wearers vary depending on the mask use conditions, it is necessary to comply with safe mask wearing conditions.

Virus-induced breath biomarkers: A new perspective to study the metabolic responses of COVID-19 vaccinees.

Coronavirus disease 2019 (COVID-19) vaccines can protect people from the infection; however, the action mechanism of vaccine-mediated metabolism remains unclear. Herein, we performed breath tests in COVID-19 vaccinees that revealed metabolic reprogramming induced by protective immune responses. In total, 204 breath samples were obtained from COVID-19 vaccinees and non-vaccinated controls, wherein numerous volatile organic compounds (VOCs) were detected by comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry system. Subsequently, 12 VOCs were selected as biomarkers to construct a signature panel using alveolar gradients and machine learning-based procedure. The signature panel could distinguish vaccinees from control group with a high prediction performance (AUC, 0.9953; accuracy, 94.42%). The metabolic pathways of these biomarkers indicated that the host-pathogen interactions enhanced enzymatic activity and microbial metabolism in the liver, lung, and gut, potentially constituting the dominant action mechanism of vaccine-driven metabolic regulation. Thus, our findings of this study highlight the potential of measuring exhaled VOCs as rapid, non-invasive biomarkers of viral infections. Furthermore, breathomics appears as an alternative for safety evaluation of biological agents and disease diagnosis.

Intelligent COVID-19 screening platform based on breath analysis.

The spread of coronavirus disease 2019 (COVID-19) results in an increasing incidence and mortality. The typical diagnosis technique for severe acute respiratory syndrome coronavirus 2 infection is reverse transcription polymerase chain reaction, which is relatively expensive, time-consuming, professional, and suffered from false-negative results. A reliable, non-invasive diagnosis method is in urgent need for the rapid screening of COVID-19 patients and controlling the epidemic. Here we constructed an intelligent system based on the volatile organic compound (VOC) biomarkers in human breath combined with machine learning models. The VOC profiles of 122 breath samples (65 of COVID-19 infections and 57 of controls) were identified with a portable gas chromatograph-mass spectrometer. Among them, eight VOCs exhibited significant differences (p< 0.001) between the COVID-19 and the control groups. The cross-validation algorithm optimized support vector machine (SVM) model was employed for the prediction of COVID-19 infection. The proposed SVM model performed a powerful capability in discriminating COVID-19 patients from healthy controls, with an accuracy of 97.3%, a sensitivity of 100%, a specificity of 94.1%, and a precision of 95.2%, and anF1 score of 97.6%. The SVM model was also compared with other common machine models, including artificial neural network,k-nearest neighbor, and logistic regression, and demonstrated obvious superiority in the prediction of COVID-19 infection. Furthermore, user-friendly software was developed based on the optimized SVM model. The developed intelligent platform based on breath analysis provides a new strategy for the point-of-care screening of COVID and shows great potential in clinical application.

Assessment of an e-nose performance for the detection of COVID-19 specific biomarkers.

Early, rapid and non-invasive diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is needed for the prevention and control of coronavirus disease 2019 (COVID-19). COVID-19 mainly affects the respiratory tract and lungs. Therefore, analysis of exhaled breath could be an alternative scalable method for reliable SARS-CoV-2 screening. In the current study, an experimental protocol using an electronic-nose ('e-nose') for attempting to identify a specific respiratory imprint in COVID-19 patients was optimized. Thus the analytical performances of the Cyranose®, a commercial e-nose device, were characterized under various controlled conditions. In addition, the effect of various experimental conditions on its sensor array response was assessed, including relative humidity, sampling time and flow rate, aiming to select the optimal parameters. A statistical data analysis was applied to e-nose sensor response using common statistical analysis algorithms in an attempt to demonstrate the possibility to detect the presence of low concentrations of spiked acetone and nonanal in the breath samples of a healthy volunteer. Cyranose®reveals a possible detection of low concentrations of these two compounds, in particular of 25 ppm nonanal, a possible marker of SARS-CoV-2 in the breath.

A review on characteristics and mitigation strategies of indoor air quality in underground subway stations.

Due to the rapidly increasing ridership and the relatively enclosed underground space, the indoor air quality (IAQ) in underground subway stations (USSs) has attracted more public attention. The air pollutants in USSs, such as particulate matter (PM), CO2 and volatile organic compounds (VOCs), are hazardous to the health of passengers and staves. Firstly, this paper presents a systematic review on the characteristics and sources of air pollutants in USSs. According to the review work, the concentrations of PM, CO2, VOCs, bacteria and fungi in USSs are 1.1-13.2 times higher than the permissible concentration limits specified by WHO, ASHRAE and US EPA. The PM and VOCs are mainly derived from the internal and outdoor sources. CO2 concentrations are highly correlated with the passenger density and the ventilation rate while the exposure levels of bacteria and fungi depend on the thermal conditions and the settled dust. Then, the online monitoring, fault detection and prediction methods of IAQ are summarized and the advantages and disadvantages of these methods are also discussed. In addition, the available control strategies for improving IAQ in USSs are reviewed, and these strategies are classified and compared from different viewpoints. Lastly, challenges of the IAQ management in the context of the COVID-19 epidemic and several suggestions for underground stations' IAQ management in the future are put forward. This paper is expected to provide a comprehensive guidance for further research and design of the effective prevention measures on air pollutants in USSs so as to achieve more sustainable and healthy underground environment.

Determination of global chemical patterns in exhaled breath for the discrimination of lung damage in postCOVID patients using olfactory technology.

The objective of this work was to evaluate the use of an electronic nose and chemometric analysis to discriminate global patterns of volatile organic compounds (VOCs) in breath of postCOVID syndrome patients with pulmonary sequelae. A cross-sectional study was performed in two groups, the group 1 were subjects recovered from COVID-19 without lung damage and the group 2 were subjects recovered from COVID-19 with impaired lung function. The VOCs analysis was executed using a Cyranose 320 electronic nose with 32 sensors, applying principal component analysis (PCA), Partial Least Square-Discriminant Analysis, random forest, canonical discriminant analysis (CAP) and the diagnostic power of the test was evaluated using the ROC (Receiver Operating Characteristic) curve. A total of 228 participants were obtained, for the postCOVID group there are 157 and 71 for the control group, the chemometric analysis results indicate in the PCA an 84% explanation of the variability between the groups, the PLS-DA indicates an observable separation between the groups and 10 sensors related to this separation, by random forest, a classification error was obtained for the control group of 0.090 and for the postCOVID group of 0.088 correct classification. The CAP model showed 83.8% of correct classification and the external validation of the model showed 80.1% of correct classification. Sensitivity and specificity reached 88.9% (73.9%-96.9%) and 96.9% (83.7%-99.9%) respectively. It is considered that this technology can be used to establish the starting point in the evaluation of lung damage in postCOVID patients with pulmonary sequelae.

Chemical profile of anti-epidemic sachet based on multiple sample preparation coupled with gas chromatography-mass spectrometry analysis combined with an embedded peaks resolution method and their action mechanisms.

The anti-epidemic sachet (Fang Yi Xiang Nang, FYXN) in traditional Chinese medicine (TCM) can prevent COVID-19 through volatile compounds that can play the role of fragrant and dampness, heat-clearing and detoxifying, warding off filth and pathogenic factors. Nevertheless, the anti-(mutant) SARS-CoV-2 compounds and the compounds related to the mechanism in vivo, and the mechanism of FYXN are still vague. In this study, the volatile compound set of FYXN was constructed by gas chromatography-mass spectrometry (GC-MS) based on multiple sample preparation methods, which include headspace (HS), headspace solid phase microextraction (HS-SPME) and pressurized liquid extraction (PLE). In addition, selective ion analysis (SIA) was used to resolve embedded chromatographic peaks present in HS-SPME results. Preliminary analysis of active compounds and mechanism of FYXN by network pharmacology combined with disease pathway information based on GC-MS results. A total of 96 volatile compounds in FYXN were collected by GC-MS analysis. 39 potential anti-viral compounds were screened by molecular docking. 13 key pathways were obtained by KEGG pathway analysis (PI3K-Akt signaling pathway, HIF-1 signaling pathway, etc.) for FYXN to prevent COVID-19. 16 anti-viral compounds (C95, C91, etc.), 10 core targets (RELA, MAPK1, etc.), and 16 key compounds related to the mechanism in vivo (C56, C30, etc.) were obtained by network analysis. The relevant pharmacological effects of key pathways and key compounds were verified by the literature. Finally, molecular docking was used to verify the relationship between core targets and key compounds, which are related to the mechanism in vivo. A variety of sample preparation methods coupled with GC-MS analysis combined with an embedded peaks resolution method and integrated with network pharmacology can not only comprehensively characterize the volatile compounds in FYXN, but also expand the network pharmacology research ideas, and help to discover the active compounds and mechanisms in FYXN.

Characteristics, sources and health risk assessment of atmospheric carbonyls during multiple ozone pollution episodes in urban Beijing: Insights into control strategies.

Carbonyls have attracted continuous attention due to their critical roles in atmospheric chemistry and their potential hazards to the ecological environment and human health. In this study, atmospheric carbonyls were measured during several ground-level-ozone (O3) pollution episodes at three urban sites (CRAES, IEP and BJUT) in Beijing in 2019 and 2020. Comparative analysis revealed that the carbonyl concentrations were 20.25 ± 6.91 ppb and 13.43 ± 5.13 ppb in 2019 and 2020 in Beijing, respectively, with a significant spatial trend from north to south, and carbonyl levels in urban Beijing were in an upper-intermediate range in China, and higher than those in other countries reported in the literature. A particularly noteworthy phenomenon is the consistency of carbonyl concentrations with variations in O3 concentrations. On O3 polluted days, the carbonyl concentrations were 1.3-1.5 times higher than those on non-O3 polluted days. Secondary formation contributed more to formaldehyde (FA) and acetaldehyde (AA) on O3 polluted days, while the anthropogenic emissions were more significant for acetone (AC) on non-O3 polluted days. Vehicle exhaust and solvent utilization were the main primary contributors to carbonyls. Due to reduced anthropogenic emissions caused by the COVID-19 lockdown and the "Program for Controlling Volatile Organic Compounds in 2020" in China, the contributions of primary emissions to carbonyls decreased in 2020 in Beijing. Human cancer risks to exposed populations from FA and AA increased with elevated O3 levels, and the risks still remained on non-O3 polluted days. The residents around the BJUT site might experience relatively higher human cancer risks than those around the other two sites. The findings in this study confirmed that atmospheric carbonyl pollution and its potential human health hazards cannot be ignored in urban Beijing; therefore, more strict control strategies for atmospheric carbonyls are urgently needed to better protect human health in Beijing in the future.

Advanced setup for safe breath sampling and patient monitoring under highly infectious conditions in the clinical environment.

Being the proximal matrix, breath offers immediate metabolic outlook of respiratory infections. However, high viral load in exhalations imposes higher transmission risk that needs improved methods for safe and repeatable analysis. Here, we have advanced the state-of-the-art methods for real-time and offline mass-spectrometry based analysis of exhaled volatile organic compounds (VOCs) under SARS-CoV-2 and/or similar respiratory conditions. To reduce infection risk, the general experimental setups for direct and offline breath sampling are modified. Certain mainstream and side-stream viral filters are examined for direct and lab-based applications. Confounders/contributions from filters and optimum operational conditions are assessed. We observed immediate effects of infection safety mandates on breath biomarker profiles. Main-stream filters induced physiological and analytical effects. Side-stream filters caused only systematic analytical effects. Observed substance specific effects partly depended on compound's origin and properties, sampling flow and respiratory rate. For offline samples, storage time, -conditions and -temperature were crucial. Our methods provided repeatable conditions for point-of-care and lab-based breath analysis with low risk of disease transmission. Besides breath VOCs profiling in spontaneously breathing subjects at the screening scenario of COVID-19/similar test centres, our methods and protocols are applicable for moderately/severely ill (even mechanically-ventilated) and highly contagious patients at the intensive care.

Evaluating Indoor Air Phthalates and Volatile Organic Compounds in Nail Salons in the Greater New York City Area: A Pilot Study.

The Greater New York City area ranks highest in the United States in the number of nail salon technicians, primarily Asian immigrant women. Nail salon technicians are exposed to toxic phthalates and volatile organic compounds daily in nail salons. The purpose of this pilot study was to measure a mixture of phthalates and volatile organic compounds in nail salons in the Greater New York City area, and to characterize work-related determinants of indoor air quality in these nail salons. Working with four Asian nail salon organizations in the Greater New York City area, we measured indoor air phthalates and volatile organic compounds at 20 nail salons from February to May 2021 using silicone wristbands and passive samplers, respectively. Nail salon characteristics were also examined. We measured six phthalates and 31 volatile organic compounds. Di(2-ethylhexyl) phthalate and Diethyl phthalate had the highest concentrations among the six phthalates measured. Concentrations of toluene, d-limonene, methyl methacrylate, and ethyl methacrylate were higher than that of the rest. Manicure/pedicure tables, the number of customers per day, and application of artificial nail (acrylic) services were positively associated with the levels of phthalates and volatile organic compounds. Given the large number of people employed in the nail industry and the even larger number of customers visiting such establishments, exposures to these toxic chemicals are likely to be widespread.

Clinical studies of detecting COVID-19 from exhaled breath with electronic nose.

The COVID-19 pandemic has attracted numerous research studies because of its impact on society and the economy. The pandemic has led to progress in the development of diagnostic methods, utilizing the polymerase chain reaction (PCR) as the gold standard for coronavirus SARS-CoV-2 detection. Numerous tests can be used at home within 15 min or so but of with lower accuracy than PCR. There is still a need for point-of-care tests available for mass daily screening of large crowds in airports, schools, and stadiums. The same problem exists with fast and continuous monitoring of patients during their medical treatment. The rapid methods can use exhaled breath analysis which is non-invasive and delivers the result quite fast. Electronic nose can detect a cocktail of volatile organic com-pounds (VOCs) induced by virus infection and disturbed metabolism in the human body. In our exploratory studies, we present the results of COVID-19 detection in a local hospital by applying the developed electronic setup utilising commercial VOC gas sensors. We consider the technical problems noticed during the reported studies and affecting the detection results. We believe that our studies help to advance the proposed technique to limit the spread of COVID-19 and similar viral infections.

A feasibility study of Covid-19 detection using breath analysis by high-pressure photon ionization time-of-flight mass spectrometry.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a tremendous threat to global health. polymerase chain reaction (PCR) and antigen testing have played a prominent role in the detection of SARS-CoV-2-infected individuals and disease control. An efficient, reliable detection tool is still urgently needed to halt the global COVID-19 pandemic. Recently, the food and drug administration (FDA) emergency approved volatile organic component (VOC) as an alternative test for COVID-19 detection. In this case-control study, we prospectively and consecutively recruited 95 confirmed COVID-19 patients and 106 healthy controls in the designated hospital for treatment of COVID-19 patients in Shenzhen, China. Exhaled breath samples were collected and stored in customized bags and then detected by high-pressure photon ionization time-of-flight mass spectrometry for VOCs. Machine learning algorithms were employed for COVID-19 detection model construction. Participants were randomly assigned in a 5:2:3 ratio to the training, validation, and blinded test sets. The sensitivity (SEN), specificity (SPE), and other general metrics were employed for the VOCs based COVID-19 detection model performance evaluation. The VOCs based COVID-19 detection model achieved good performance, with a SEN of 92.2% (95% CI: 83.8%, 95.6%), a SPE of 86.1% (95% CI: 74.8%, 97.4%) on blinded test set. Five potential VOC ions related to COVID-19 infection were discovered, which are significantly different between COVID-19 infected patients and controls. This study evaluated a simple, fast, non-invasive VOCs-based COVID-19 detection method and demonstrated that it has good sensitivity and specificity in distinguishing COVID-19 infected patients from controls. It has great potential for fast and accurate COVID-19 detection.

Occurrence of and dermal exposure to benzene, toluene and styrene found in hand sanitizers from the United States.

Human exposure to carcinogenic volatile organic compounds (VOCs), such as benzene, from hand sanitizers is a topic of current concern. In light of the heavy use of hand sanitizers during the COVID-19 pandemic, determination of exposure to toxicants present in these products deserves attention. The US Food and Drug Administration (FDA) had set an interim limit for benzene in alcohol-based hand sanitizers at 2000 parts-per-billion (ppb). We determined the concentrations of and exposure to three VOCs namely, benzene, toluene and styrene, in 200 hand sanitizers using high-resolution gas chromatography coupled with high-resolution mass spectrometry (HRGC-HRMS). Benzene, toluene and styrene were found in 31%, 25% and 32%, respectively, of the samples analyzed at mean concentrations of 395 (range: 0.181-22,300), 164 (range: 0.074-20,700) and 61.3 ng/g (range: 0.082-4200 ng/g), respectively. Benzene was found at concentrations > 2000 ng/g (above the FDA interim limit) in 5% of the samples, representing 9 brands. The mean potential dermal exposure doses (DEDs) to benzene (children/teenagers: 34.6; adults: 24.7 ng/kg-bw/d) were higher than those for toluene (children/teenagers: 14.4; adults: 10.3 ng/kg-bw/d) and styrene (children/teenagers: 5.37; adults: 3.83 ng/kg-bw/d) in the 200 hand sanitizers analyzed. The estimated cancer risk from exposure to benzene in children/teenagers and adults from hand sanitizer use (at an estimated usage rate of 5 g/day) was greater than the one-in-a-million risk benchmark (1.0 × 10-6) for 10% and 9% of the samples, respectively. To the best of our knowledge, this is the first study to determine both the concentrations of and exposure risks to benzene, toluene and styrene present in hand sanitizers.

National emissions inventory and future trends in greenhouse gases and other air pollutants from civil airports in China.

Civil aviation is an important source of air pollutants, but this field has received insufficient attention in China. Based on the standard emissions model of the International Civil Aviation Organization (ICAO) and actual flight information from 241 airports, this study estimated a comprehensive emissions inventory for 2010-2020 by considering the impacts of mixing layer height. The results showed that annual pollutant emissions rapidly trended upward along with population and economic growth; however, the emissions decreased owing to the impacts of the COVID-19 pandemic. In 2020, the emissions of carbon monoxide (CO), nitrogen oxides (NOX), particulate matter (PM), methane (CH4), nitrous oxide (N2O), carbon dioxide (CO2), and water vapor (H2O) were 34.34, 65.73, 0.10, 0.34, 0.40, 14,706.26, and 5733.11 Gg, respectively. The emissions of total volatile organic compounds (VOCs) from China's civil airports in 2020 were estimated at 17.20 Gg; the major components were formic acid (1.70 Gg), acetic acid (1.62 Gg), 1-butylene (1.03 Gg), acetone (0.96 Gg), and acetaldehyde (0.93 Gg). The distribution of pollutant emissions was consistent with the level of economic development, mainly in Beijing, Guangzhou, and Shanghai. In addition, we estimated future pollution trends for the aviation industry under four scenarios. Under the comprehensive scenario, which considered the impacts of economic growth, passenger turnover, cargo turnover, COVID-19, and technological efficiency, the levels of typical pollutants were expected to increase by nearly 1.51-fold from 2010 to 2035.

A low cost, easy-to-assemble, open-source modular mobile sampler design for thermal desorption analysis of breath and environmental VOCs.

Exhaled breath vapor contains hundreds of volatile organic compounds (VOCs), which are the byproducts of health and disease metabolism, and they have clinical and diagnostic potential. Simultaneous collection of breath VOCs and background environmental VOCs is important to ensure analyses eliminate exogenous compounds from clinical studies. We present a mobile sampling system to extract gaseous VOCs onto commercially available sorbent-packed thermal desorption tubes. The sampler can be connected to a number of commonly available disposable and reusable sampling bags, in the case of this study, a Tedlar bag containing a breath sample. Alternatively, the inlet can be left open to directly sample room or environmental air when obtaining a background VOC sample. The system contains a screen for the operator to input a desired sample volume. A needle valve allows the operator to control the sample flow rate, which operates with an accuracy of -1.52 ± 0.63% of the desired rate, and consistently generated that rate with 0.12 ± 0.06% error across repeated measures. A flow pump, flow sensor and microcontroller allow volumetric sampling, as opposed to timed sampling, with 0.06 ± 0.06% accuracy in the volume extracted. Four samplers were compared by sampling a standard chemical mixture, which resulted in 6.4 ± 4.7% error across all four replicate modular samplers to extract a given VOC. The samplers were deployed in a clinical setting to collect breath and background/environmental samples, including patients with active SARS-CoV-2 infections, and the device could easily move between rooms and can undergo required disinfection protocols to prevent transmission of pathogens on the case exterior. All components required for assembly are detailed and are made publicly available for non-commercial use, including the microcontroller software. We demonstrate the device collects volatile compounds, including use of chemical standards, and background and breath samples in real use conditions.

Evaluation of air quality in indoor and outdoor environments: Impact of anti-COVID-19 measures.

This study monitors the presence of 88 volatile organic compounds (VOCs) and semi-volatile organic compounds (semi-VOCs) at the gas phase of seven indoor settings in a school in the city of Tarragona, Spain, and five outdoor locations around the city. The VOCs and semi-VOCs monitored were solvents (∑Solvents), aldehydes (∑Aldehydes), emerging organic compounds (∑EOCs), and other VOCs and semi-VOCs (∑Others). Passive sampling campaigns were performed using Carbopack X tubes followed by thermal desorption coupled to gas chromatography with mass spectrometry (TD-GC-MS). Overall, 70 of the target compounds included in the method were determined in the indoor air samples analysed, and 42 VOCs and semi-VOCs in the outdoor air samples. Our results showed that solvents were ubiquitous throughout the school at concentrations ranging from 272 µg m-3 to 423 µg m-3 and representing 68%-83% of total target compounds (∑Total). The values of ∑Total in 2021 were three times as high as those observed at the same indoor settings in 2019, with solvents experiencing the greatest increase. A plausible explanation for these observations is the implementation of anti-COVID-19 measures in the indoor settings, such as the intensification of cleaning activities and the use of hydroalcoholic gels as personal hygiene. The ∑Total values observed in the indoor settings evaluated were twenty times higher than those found outdoors. ∑Solvents were the most representative compounds found indoors (74% of the ∑Total). The concentrations of VOCs and semi-VOCs observed in the outdoors were strictly related to combustion processes from automobile traffic and industrial activities, with ∑Others contributing 58%, ∑Solvents 31%, and ∑Aldehydes 11% of the ∑Total. EOCs, on the other hand, were not detected in any outdoor sample.