Protocol for the air purification for eosinophilic COPD study (APECS): a randomised controlled trial of home air filtration by HEPA.

INTRODUCTION: Exposure to particulate matter (PM) pollution has been associated with lower lung function in adults with chronic obstructive pulmonary disease (COPD). Patients with eosinophilic COPD have been found to have higher levels of airway inflammation, greater responsiveness to anti-inflammatory steroid inhalers and a greater lung function response to PM pollution exposure compared with those with lower eosinophil levels. This study will evaluate if reducing home PM exposure by high-efficiency particulate air (HEPA) air filtration improves respiratory health in eosinophilic COPD. METHODS AND ANALYSIS: The Air Purification for Eosinophilic COPD Study (APECS) is a double-blinded randomised placebo-controlled trial that will enrol 160 participants with eosinophilic COPD living in the area of Boston, Massachusetts. Real and sham air purifiers will be placed in the bedroom and living rooms of the participants in the intervention and control group, respectively, for 12 months. The primary trial outcome will be the change in forced expiratory volume in 1 s (FEV1). Lung function will be assessed twice preintervention and three times during the intervention phase (at 7 days, 6 months and 12 months postrandomisation). Secondary trial outcomes include changes in (1) health status by St. George's Respiratory Questionnaire; (2) respiratory symptoms by Breathlessness, Cough and Sputum Scale (BCSS); and (3) 6-Minute Walk Test (6MWT). Inflammatory mediators were measured in the nasal epithelial lining fluid (NELF). Indoor PM will be measured in the home for the week preceding each study visit. The data will be analysed to contrast changes in outcomes in the intervention and control groups using a repeated measures framework. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Institutional Review Board of Beth Israel Deaconess Medical Centre (protocol #2019P0001129). The results of the APECS trial will be presented at scientific conferences and published in peer-reviewed journals. TRIAL REGISTRATION: NCT04252235. Version: October 2023.

Characterization of chemical transport in human skin and building material.

Volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) are ubiquitous in indoor environment. They can emit from source into air, and subsequently penetrate human skin into blood through dermal uptake, causing adverse health effects. This study develops a two-layer analytical model to characterize the VOC/SVOC dermal uptake process, which is then extended to predict VOC emissions from two-layer building materials or furniture. Based on the model, the key transport parameters of chemicals in every skin or material layer are determined via a hybrid optimization method using data from experiments and literature. The measured key parameters of SVOCs for dermal uptake are more accurate than those from previous studies using empirical correlations. Moreover, the association between the absorption amount of studied chemicals into blood and age is preliminarily investigated. Further exposure analysis reveals that the contribution of dermal uptake to the total exposure can be comparable with that of inhalation for the examined SVOCs. This study makes the first attempt to accurately determine the key parameters of chemicals in skin, which is demonstrated to be critical for health risk assessment.

Radon sampling methodologies: A case for accurate, accessible measurements using household instruments.

Radon is a prevalent carcinogenic gas and the leading cause of lung cancer in the United States besides smoking. As the residential environment is the primary source of radon exposure, accessible and accurate measurements of radon in this environment are essential. However, no radon monitors have been evaluated that are inexpensive enough for regular household use. In this study, we examine two household-grade, continuous monitoring devices, the Ecosense RadonEye and EcoQube. We compare them to two research-grade instruments, the Durridge Company Rad7 and the Rad Elec Inc. E-PERM. In our study, the Ecosense household radon monitors performed accurately and can be used by homeowners and researchers alike as an affordable and reliable radon sensor.Implications: The ability of homeowners and renters to regularly monitor the radon levels inside their home is an important preventative health measure. However, low-cost instrumentation is needed that can provide accurate radon measurements. In this study, we show that the affordable Ecosense continuous monitors produce results that are in line with expensive research-grade instruments in a residential environment, over a range of concentrations. The Ecosense monitors may be suitable for home use, and they may provide a solution that can be used by policymakers and home-dwellers alike to improve regular radon monitoring in residences.

Estimation of fine particulate matter in an arid area from visibility based on machine learning.

BACKGROUND: The absence of air pollution monitoring networks makes it difficult to assess historical fine particulate matter (PM2.5) exposures for countries in the areas, such as Kuwait, which are severe impacted by desert dust and anthropogenic pollution. OBJECTIVE: We constructed an ensemble machine learning model to predict daily PM2.5 concentrations for regions lack of PM2.5 observations. METHODS: The model was constructed based on daily PM2.5, visibility, and other meteorological data collected at two sites in Kuwait. Then, our model was applied to predict the daily level of PM2.5 concentrations for eight airports located in Kuwait and Iraq from 2013 to 2020. RESULTS: As compared to traditional statistic models, the proposed machine learning methods improved the accuracy in using visibility to predict daily PM2.5 concentrations with a cross-validation R2 of 0.68. The predicted level of daily PM2.5 concentrations were consistent with previous measurements. The predicted average yearly PM2.5 concentration for the eight stations is 50.65 µg/m3. For all stations, the monthly average PM2.5 concentrations reached their maximum in July and their minimum in November. SIGNIFICANCE: These findings make it possible to retrospectively estimate daily PM2.5 exposures using the large-scale databases of historical visibility in regions with few particulate matter monitoring stations. IMPACT STATEMENT: The scarcity of air pollution ground monitoring networks makes it difficult to assess historical fine particulate matter exposures for countries in arid areas such as Kuwait. Visibility is closely related to atmospheric particulate matter concentrations and historical airport visibility records are commonly available in most countries. Our model make it possible to retrospectively estimate daily PM2.5 exposures using the large-scale databases of historical visibility in arid regions with few particulate matter ground monitoring stations. The product of such models can be critical for environmental risk assessments and population health studies.

Factors Influencing Classroom Exposures to Fine Particles, Black Carbon, and Nitrogen Dioxide in Inner-City Schools and Their Implications for Indoor Air Quality.

BACKGROUND: School classrooms, where students spend the majority of their time during the day, are the second most important indoor microenvironment for children. OBJECTIVE: We investigated factors influencing classroom exposures to fine particulate matter (PM2.5), black carbon (BC), and nitrogen dioxide (NO2) in urban schools in the northeast United States. METHODS: Over the period of 10 y (2008-2013; 2015-2019) measurements were conducted in 309 classrooms of 74 inner-city schools during fall, winter, and spring of the academic period. The data were analyzed using adaptive mixed-effects least absolute shrinkage and selection operator (LASSO) regression models. The LASSO variables included meteorological-, school-, and classroom-based covariates. RESULTS: LASSO identified 10, 10, and 11 significant factors (p<0.05) that were associated with indoor PM2.5, BC, and NO2 exposures, respectively. The overall variability explained by these models was R2=0.679, 0.687, and 0.621 for PM2.5, BC, and NO2, respectively. Of the model's explained variability, outdoor air pollution was the most important predictor, accounting for 53.9%, 63.4%, and 34.1% of the indoor PM2.5, BC, and NO2 concentrations. School-based predictors included furnace servicing, presence of a basement, annual income, building type, building year of construction, number of classrooms, number of students, and type of ventilation that, in combination, explained 18.6%, 26.1%, and 34.2% of PM2.5, BC, and NO2 levels, whereas classroom-based predictors included classroom floor level, classroom proximity to cafeteria, number of windows, frequency of cleaning, and windows facing the bus area and jointly explained 24.0%, 4.2%, and 29.3% of PM2.5, BC, and NO2 concentrations, respectively. DISCUSSION: The adaptive LASSO technique identified significant regional-, school-, and classroom-based factors influencing classroom air pollutant levels and provided robust estimates that could potentially inform targeted interventions aiming at improving children's health and well-being during their early years of development. https://doi.org/10.1289/EHP10007.

Quantifying factors affecting contributions of roadway exhaust and non-exhaust emissions to ambient PM10-2.5 and PM2.5-0.2 particles.

Traffic-related particulate matter (PM) plays an important role in urban air pollution. However, sources of urban pollution are difficult to distinguish. This study utilises a mobile particle concentrator platform and statistical tools to investigate factors affecting roadway ambient coarse particle (PM10-2.5) and fine particle (PM2.5-0.2) concentrations in greater Boston, USA. Positive matrix factorization (PMF) identified six PM10-2.5 sources (exhaust, road salt, brake wear, regional pollution, road dust resuspension and tyre-road abrasion) and seven fine particle sources. The seven PM2.5-0.2 sources include the six PM10-2.5 sources and a source rich in Cr and Ni. Non- exhaust traffic-related sources together accounted for 65.6% and 29.1% of the PM10-2.5 and PM2.5-0.2 mass, respectively. While the respective contributions of exhaust sources were 10.4% and 20.7%. The biggest non-exhaust contributor in the PM10-2.5 was road dust resuspension, accounting for 29.6%, while for the PM2.5-0.2, the biggest non-exhaust source was road-tyre abrasion, accounting for 12.3%. We used stepwise general additive models (sGAMs) and found statistically significant (p < 0.05) effects of temperature, number of vehicles and rush hour periods on exhaust, brake wear, road dust resuspension and road-tyre abrasion with relative importance between 19.1 and 62.2%, 12.5-42.1% and 4.4-42.2% of the sGAM model's explained variability. Speed limit and road type were also important factors for exhaust, road-tyre and brake wear sources. Meteorological variables of wind speed and relative humidity were significantly associated with both coarse and fine road dust resuspension and had a combined relative importance of 38% and 48%. The quantifying results of the factors that influence traffic-related sources can offer key insights to policies aiming to improve near-road air quality.

The association between daily-diagnosed COVID-19 morbidity and short-term exposure to PM1 is larger than associations with PM2.5 and PM10.

Exposure to particulate matter (PM) could increase both susceptibility to SARS-CoV-2 infection and severity of COVID-19 disease. Prior studies investigating associations between PM and COVID-19 morbidity have only considered PM2.5 or PM10, rather than PM1. We investigated the associations between daily-diagnosed COVID-19 morbidity and average exposures to ambient PM1 starting at 0 through 21 days before the day of diagnosis in 12 cities in China using a two-step analysis: a time-series quasi-Poisson analysis to analyze the associations in each city; and then a meta-analysis to estimate the overall association. Diagnosed morbidities and PM1 data were obtained from National Health Commission in China and China Meteorological Administration, respectively. We found association between short-term exposures to ambient PM1 with COVID-19 morbidity was significantly positive, and larger than the associations with PM2.5 and PM10. Percent increases in daily-diagnosed COVID-19 morbidity per IQR/10 PM1 for different moving averages ranged from 1.50% (-1.20%, 4.30%) to 241% (95%CI: 80.7%, 545%), with largest values for exposure windows starting at 17 days before diagnosis. Our results indicate that smaller particles are more highly associated with COVID-19 morbidity, and most of the effects from PM2.5 and PM10 on COVID-19 may be primarily due to the PM1. This study will be helpful for implementing measures and policies to control the spread of COVID-19.

Effect of School Integrated Pest Management or Classroom Air Filter Purifiers on Asthma Symptoms in Students With Active Asthma: A Randomized Clinical Trial.

Importance: School and classroom allergens and particles are associated with asthma morbidity, but the benefit of environmental remediation is not known. Objective: To determine whether use of a school-wide integrated pest management (IPM) program or high-efficiency particulate air (HEPA) filter purifiers in the classrooms improve asthma symptoms in students with active asthma. Design, Setting, and Participants: Factorial randomized clinical trial of a school-wide IPM program and HEPA filter purifiers in the classrooms was conducted from 2015 to 2020 (School Inner-City Asthma Intervention Study). There were 236 students with active asthma attending 41 participating urban elementary schools located in the Northeastern US who were randomized to IPM by school and HEPA filter purifiers by classroom. The date of final follow-up was June 20, 2020. Interventions: The school-wide IPM program consisted of application of rodenticide, sealing entry points, trap placement, targeted cleaning, and brief educational handouts for school staff. Infestation was assessed every 3 months, with additional treatments as needed. Control schools received no IPM, cleaning, or education. Classroom portable HEPA filter purifiers were deployed and the filters were changed every 3 months. Control classrooms received sham HEPA filters that looked and sounded like active HEPA filter purifiers. Randomization was done independently (split-plot design), with matching by the number of enrolled students to ensure a nearly exact 1:1 student ratio for each intervention with 118 students randomized to each group. Participants, investigators, and those assessing outcomes were blinded to the interventions. Main Outcomes and Measures: The primary outcome was the number of symptom-days with asthma during a 2-week period. Symptom-days were assessed every 2 months during the 10 months after randomization. Results: Among the 236 students who were randomized (mean age, 8.1 [SD, 2.0] years; 113 [48%] female), all completed the trial. At baseline, the 2-week mean was 2.2 (SD, 3.9) symptom-days with asthma and 98% of the classrooms had detectable levels of mouse allergen. The results were pooled because there was no statistically significant difference between the 2 interventions (P = .18 for interaction). During a 2-week period, the mean was 1.5 symptom-days with asthma after use of the school-wide IPM program vs 1.9 symptom-days after no IPM across the school year (incidence rate ratio, 0.71 [95% CI, 0.38-1.33]), which was not statistically significantly different. During a 2-week period, the mean was 1.6 symptom-days with asthma after use of HEPA filter purifiers in the classrooms vs 1.8 symptom-days after use of sham HEPA filter purifiers across the school year (incidence rate ratio, 1.47 [95% CI, 0.79-2.75]), which was not statistically significantly different. There were no intervention-related adverse events. Conclusions and Relevance: Among children with active asthma, use of a school-wide IPM program or classroom HEPA filter purifiers did not significantly reduce symptom-days with asthma. However, interpretation of the study findings may need to consider allergen levels, particle exposures, and asthma symptoms at baseline. Trial Registration: ClinicalTrials.gov Identifier: NCT02291302.

Predictors of indoor radon levels in the Midwest United States.

Radon (Rn) is a natural and toxic radioactive gas that accumulates indoors, mainly in low-ventilated underground floors and basements. Several factors make prediction of indoor Rn exposure in enclosed spaces challenging. In this study, we investigated the influence of soil, geology, topography, atmospheric variables, radiation, urbanization, community economic well-being, and monthly and yearly variations on indoor Rn concentrations. We analyzed 7,515 monthly indoor Rn measurements in 623 zip codes from two U.S. States (Michigan and Minnesota) during 2005-2018 using a random forest model. Using Shapley Additive exPlanations (SHAP) values we investigated the contribution of each factor using variable importance and partial dependence plots. Factors that predict indoor Rn differed between states, with topographical, geological and soil composition being most influential. Cross-validated Pearson correlation between predictions and measurements was 0.68 (RMSE = 47.8 Bq/m3) in Minnesota, and 0.67 (RMSE = 52.5 Bq/m3) in Michigan. Our results underline the importance of soil structure for radon exposure, presumably due to strapped Rn in soil. The differences across states also suggest that Rn studies performing model development should consider geographical variables, along with other factors. As indoor Rn levels are multifactorial, an understanding of the factors that influence its emanation and build up indoors will help better assess spatial and temporal variations, which will be useful to improve prevention and mitigation control strategies.Implications: Radon exposure has become a year-round problem as people spend most of their time indoors. In North America, radon exposure is increasing over time and awareness related to its health effects remains low in the general population. Several factors make prediction of indoor radon exposure in enclosed spaces challenging. In this study, we used random forest to investigate the influence of factors on indoor radon in the Midwest United States. We found that topography, geology, and soil composition were the most influential factors on indoor radon levels. These results will help better assess spatial and temporal variations, which will further help better prevention and mitigation control strategies.

A two-year assessment of particulate air pollution and sources in Kuwait.

BACKGROUND: Kuwait and the Gulf region have a desert, hyper-arid and hot climate that makes outdoor air sampling challenging. The region is also affected by intense dust storms. Monitoring challenges from the harsh climate have limited data needed to inform appropriate regulatory actions to address air pollution in the region. OBJECTIVES: To compare gravimetric measurements with existing networks that rely on beta-attenuation measurements in a desert climate; determine the annual levels of PM2.5 and PM10 over a two-year period in Kuwait; assess compliance with air quality standards; and identify and quantify PM2.5 sources. METHODS: We custom-designed particle samplers that can withstand large quantities of dust without their inlet becoming overloaded. The samplers were placed in two populated residential locations, one in Kuwait City and another near industrial and petrochemical facilities in Ali Sabah Al-Salem (ASAS) to collect PM2.5 and PM10 samples for mass and elemental analysis. We used positive matrix factorization to identify PM2.5 sources and apportion their contributions. RESULTS: We collected 2339 samples during the period October 2017 through October 2019. The beta-attenuation method in measuring PM2.5 consistently exceeded gravimetric measurements, especially during dust events. The annual levels for PM2.5 in Kuwait City and ASAS were 41.6 ± 29.0 and 47.5 ± 27.6 µg/m3, respectively. Annual PM2.5 levels in Kuwait were nearly four times higher than the U.S. National Ambient Air Quality Standard. Regional pollution was a major contributor to PM2.5 levels in both locations accounting for 44% in Kuwait City and 46% in ASAS. Dust storms and re-suspended road dust were the second and third largest contributors to PM2.5, respectively. CONCLUSIONS: The premise that frequent and extreme dust storms make air quality regulation futile is dubious. In this comprehensive particulate pollution analysis, we show that the sizeable regional anthropogenic particulate sources warrant national and regional mitigation strategies to ensure compliance with air quality standards.

Estimating climate change-related impacts on outdoor air pollution infiltration.

BACKGROUND: Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects. METHODS: We measured indoor fine particulate matter (PM2.5) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046-2065) and past (1981-2000) scenarios. RESULTS: The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months. DISCUSSION: We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM2.5 infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM2.5, and provide a better understanding of the potential influence of climate change on PM2.5 health effects.

The Microbiome of Size-Fractionated Airborne Particles from the Sahara Region.

Diverse airborne microbes affect human health and biodiversity, and the Sahara region of West Africa is a globally important source region for atmospheric dust. We collected size-fractionated (>10, 10-2.5, 2.5-1.0, 1.0-0.5, and <0.5 µm) atmospheric particles in Mali, West Africa and conducted the first cultivation-independent study of airborne microbes in this region using 16S rRNA gene sequencing. Abundant and diverse microbes were detected in all particle size fractions at levels higher than those previously hypothesized for desert regions. Average daily abundance was 1.94 × 105 16S rRNA copies/m3. Daily patterns in abundance for particles <0.5 µm differed significantly from other size fractions likely because they form mainly in the atmosphere and have limited surface resuspension. Particles >10 µm contained the greatest fraction of daily abundance (51-62%) and had significantly greater diversity than smaller particles. Greater bacterial abundance of particles >2.5 µm that are bigger than the average bacterium suggests that most airborne bacteria are present as aggregates or attached to particles rather than as free-floating cells. Particles >10 µm have very short atmospheric lifetimes and thus tend to have more localized origins. We confirmed the presence of several potential pathogens using polymerase chain reaction that are candidates for viability and strain testing in future studies. These species were detected on all particle sizes tested, including particles <2.5 µm that are expected to undergo long-range transport. Overall, our results suggest that the composition and sources of airborne microbes can be better discriminated by collecting size-fractionated samples.

Development and evaluation of a mobile laboratory for collecting short-duration near-road fine and coarse ambient particle and road dust samples.

This study used fine and coarse PM concentrator technology in a Mobile Particle Concentrator Platform (MPCP) designed and built to allow the collection of large amounts of ambient PM, enabling time-resolved speciation analysis, which would not be feasible using conventional methods. One hour of sampling yielded sufficient sample loading for trace elemental analysis using X-Ray Fluorescence (XRF). In addition, we developed a novel Road Dust Aerosolizer (RDA) sampler in order to collect PM2.5 and PM10 surface road dust in situ. This sampler aerosolizes dust from the road surface, simulating ambient road dust resuspension, resulting in measured PM composition and size more appropriately (and less labor-intensive) than those obtained from studies using bulk road dust sieved and re-suspended in the laboratory. Overall, our modified fine and coarse particle concentrators yielded good reproducibility between co-located samples and sufficient loading for trace elemental analysis. For particle mass concentration, we observed a relative error of 3% and 4% among pairs of filters for fine and coarse concentrators, respectively; confirming that the mass collected on an unweighted quartz filter in parallel with a Teflon filter will have the same PM mass as the weighed Teflon filter. For samples with elements that are well above the LOD, relative uncertainty values were between 5% and 10% for the fine and 3% and 10% for the coarse. Our results show that the RDA system has an excellent precision for mass and elements as well. The relative error for mass is 7% for PM10 and 3% for PM2.5 within pairs and ranged from 2 to10% for elements. In conclusion, we developed a method for collecting PM10 and PM2.5 near-road air and surface road dust for short durations, which allows investigation of the composition of direct (airborne) and indirect (re-suspended road dust) non-tailpipe vehicular emissions. Implications: The methods we developed in this study allow the collection of one-hour PM10-2.5 and PM2.5-0.2 samples from near-road ambient air at several distances from the same roadway in 1 day, and collection of road dust directly from the road surface, with sufficient loading for trace elemental analysis. This will allow investigation of the composition of direct (airborne) and indirect (re-suspended road dust) vehicular emissions.

Short-term exposure to ambient particle gamma radioactivity is associated with increased risk for all-cause non-accidental and cardiovascular mortality.

BACKGROUND: Recent studies have found that particulate matter (PM) attached radioactivity was associated with certain adverse health effects including increased blood pressure and lung dysfunction. However, there has been no investigation on the direct effect of PM radioactivity on mortality. METHODS: Exposures to ambient PM gamma activities were determined using U.S. EPA RadNet data. Data on daily deaths were obtained from individual state Departments of Public Health. We used a generalized additive quasi-Poisson model to estimate the associations between two-day average ambient PM gamma activities (gamma2 through gamma9) with all-cause non-accidental and cardiovascular daily deaths for each of 18 US cities, for each season, adjusting for two-day average PM2.5 exposure, temperature, relative humidity, day of week and long-term trends. Subsequently, we used random-effects meta-analysis to estimate the overall effect in the 18 cities for each season. RESULTS: We found that all-cause non-accidental daily mortality in spring season was positively associated with two-day average ambient PM gamma activities in spring, with significant results for gamma2, gamma5 and gamma6. Similarly, cardiovascular daily mortality was positively associated with two-day average ambient PM gamma activities, with significant results for gamma2, gamma4, gamma5, gamma6, gamma7 and gamma9. For the spring season, each interquartile range (IQR) increase of two-day averaged ambient PM gamma activity was associated with increase in all-cause daily deaths, ranging from 0.15% (95% Confidence Interval (CI): -0.36%, 0.65%) to 1.03 (95%CI: 0.18%, 1.89%). Each IQR was also associated with increase in cardiovascular daily deaths, ranging from 0.01% (95%CI: -0.89, 0.92) to 2.95% (95%CI: 1.33, 4.59). For other seasons overall we found statistically insignificant associations of PM radioactivity with mortality. CONCLUSIONS: Our findings suggest that there are potential systemic toxic effects of inhalation of radionuclides attached to ambient air particles.

Cardiac Autonomic Effects of Secondhand Exposure to Nicotine from Electronic Cigarettes: An Exploratory Study.

BACKGROUND: The rapid increase in prevalence of e-cigarette (EC) use may lead to widespread exposure to secondhand emissions among nonsmokers, but evidence on the potential cardiovascular health risks is limited. We aimed to investigate effect of short-term secondhand exposure to nicotine from e-cigarette (EC) emissions on cardiac autonomic function using heart rate variability (HRV). METHODS: A randomized, repeated measures crossover study of healthy nonsmoking volunteers was conducted. Standard deviation of NN intervals (SDNN), average of the standard deviation of NN intervals (ASDNN), root mean square of successive differences (rMSSD), and heart rate-corrected QT interval (QTc) were calculated during one hour of EC exposure session. RESULTS: Nicotine from EC emissions was associated with a 7.8% decrease in SDNN (95% CI, -11.2% to -4.3%), 7.7% decrease in ASDNN (95% CI, -11.0% to -4.2%) and 3.8 msec decrease in QTc (95% CI, -5.8 to -1.9). Compared with a short exposure time period (<15min), greater nicotine associated with reductions in ASDNN (P for interaction = 0.076) with longer exposure time periods. For QTc, greater nicotine associated with reductions were found during 15-30 min exposure time period (P for interaction = 0.04). CONCLUSION: We present the first evidence of cardiac autonomic effects of short-term secondhand exposure to nicotine from EC emissions among healthy nonsmokers. Further comprehensive research on EC exposure extending to more subjects and flavor compounds is warranted.

Source apportionment of organic pollutants in fine and coarse atmospheric particles in Doha, Qatar.

In this study, we investigated the sources of organic pollutants associated with fine (PM2.5) and coarse (PM2.5-10) atmospheric particulate matter in Doha, Qatar based on an eight-month sampling campaign conducted from May to December 2015. Multiple organic compound tracers including 36 PAH members, 25 n-alkane homologs, 17 hopanes, and 12 steranes were used for organic aerosols source apportionment. Source apportionment based on specific molecular markers, molecular diagnostic ratios/indices, and positive matrix factorization (PMF) modeling showed that similar sources are responsible for both fine- and coarse-particle organic pollutants. PMF analysis showed that biogenic aerosols, fugitive dust emissions, gasoline engine emissions, diesel engine emissions, and heavy oil combustion were the five main pollution sources of organic aerosols, which agreed well with the results from the diagnostic ratios analysis. The conditional bivariate probability functions (CPF) and potential source contribution function (PSCF) indicated that both regional (i.e., mixed biogenic/secondary particles and oil refinery/shipping emissions) and local sources contributed to airborne organic aerosol concentrations observed at the site, depending on the wind speed and direction. It appears that the relatively high levels of organic pollutants were contributed by local anthropogenic sources, such as fossil fuel combustion, vehicular emissions, and fugitive dust emissions. The high levels of local contributions indicated that there might be great opportunities for Qatar to considerably reduce emissions so that population exposures to carbonaceous aerosols and the public health risks associated with air pollution can be minimized. Implications: Multiple organic tracers and various source apportionment techniques have been used for convincing source apportionment. It was found that both long-range and local sources have a significant impact on atmospheric carbonaceous particles in the area, depending on the wind conditions. Relatively high levels of organic pollutants attributed to local anthropogenic sources indicate that there are great opportunities for Qatar to establish and implement more efficient pollution control measures and policies. Regional sources such as petroleum refineries and shipping-vessels emissions in the Gulf region should also be regulated and managed through regional cooperation to improve the air quality in the region.

Review on the treatment of organic pollutants in water by ultrasonic technology.

The application of ultrasonic technology in the treatment of organic pollutants in water has attracted more and more attention in recent years. Compared with conventional treatment, ultrasonic treatment is more efficient and time saving. Ultrasonic technology is effective for the degradation of many refractory organic pollutants. In this paper, the principle, influencing factors and various methods of ultrasonic degradation of organic pollutants are studied in view of ultrasonic treatment alone, ultrasound treatment methods combined with biocatalysts, chemical oxidation and adsorption techniques, respectively. In addition, the problems existing in the treatment of organic pollutants in water by ultrasonic technology are analyzed and the development direction is put forward.

Concentrations of aliphatic and polycyclic aromatic hydrocarbons in ambient PM2.5 and PM10 particulates in Doha, Qatar.

Organic carbon (OC), elemental carbon (EC), and 90 organic compounds (36 polycyclic aromatic hydrocarbons [PAHs], 25 n-alkane homologues, 17 hopanes, and 12 steranes) were concurrently quantified in atmospheric particulate matter of PM2.5 and PM10. The 24-hr PM samples were collected using Harvard Impactors at a suburban site in Doha, Qatar, from May to December 2015. The mass concentrations (mean ± standard deviation) of PM2.5 and PM10 were 40 ± 15 and 145 ± 70 µg m-3, respectively, exceeding the World Health Organization (WHO) air quality guidelines. Coarse particles comprised 70% of PM10. Total carbonaceous contents accounted for 14% of PM2.5 and 10% of PM10 particulate mass. The major fraction (90%) of EC was associated with the PM2.5. In contrast, 70% of OC content was found in the PM2.5-10 fraction. The secondary OC accounted for 60-68% of the total OC in both PM fractions, indicating photochemical conversions of organics are much active in the area due to higher air temperatures and solar radiations. Among the studied compounds, n-alkanes were the most abundant group, followed by PAHs, hopanes, and steranes. n-Alkanes from C25 to C35 prevailed with a predominance of odd carbon numbered congeners (C27-C31). High-molecular-weight PAHs (5-6 rings) also prevailed, within their class, with benzo[b + j]fluoranthene (Bb + jF) being the dominant member. PAHs were mainly (80%) associated with the PM2.5 fraction. Local vehicular and fugitive emissions were predominant during low-speed southeasterly winds from urban areas, while remote petrogenic/biogenic emissions were particularly significant under prevailing northwesterly wind conditions. Implications: An unprecedented study in Qatar established concentration profiles of EC, OC, and 90 organic compounds in PM2.5 and PM10. Multiple tracer organic compounds for each source can be used for convincing source apportionment. Particle concentrations exceeded WHO air quality guidelines for 82-96% of the time, revealing a severe problem of atmospheric PM in Doha. Dominance of EC and PAHs in fine particles signifies contributions from combustion sources. Dependence of pollutants concentrations on wind speed and direction suggests their significant temporal and spatial variability, indicating opportunities for improving the air quality by identifying sources of airborne contaminants.