Fine and ultrafine particle removal efficiency of new residential HVAC filters

Particle air filters used in central residential forced‐air systems are most commonly evaluated for their size‐resolved removal efficiency for particles 0.3‐10 µm using laboratory tests. Little information exists on the removal efficiency of commercially available residential filters for particles smaller than 0.3 µm or for integral measures of mass‐based aerosol concentrations (eg, PM_2.5) or total number concentrations (eg, ultrafine particles, or UFPs) that are commonly used in regulatory monitoring and building measurements. Here, we measure the size‐resolved removal efficiency of 50 new commercially available residential HVAC filters installed in a recirculating central air‐handling unit in an unoccupied apartment unit using alternating upstream/downstream measurements with incense and NaCl as particle sources. Size‐resolved removal efficiencies are then used to estimate integral measures of PM_2.5 and total UFP removal efficiency for the filters assuming they are challenged by 201 residential indoor particle size distributions (PSDs) gathered from the literature. Total UFP and PM_2.5 removal efficiencies generally increased with manufacturer‐reported filter ratings and with filter thickness, albeit with numerous exceptions. PM_2.5 removal efficiencies were more influenced by the assumption for indoor PSD than total UFP removal efficiencies. Filters with the same ratings but from different manufacturers often had different removal efficiencies for PM_2.5 and total UFPs.     

Quantitative filter forensics with residential HVAC filters to assess indoor concentrations

Analysis of the dust from heating, ventilation, and air conditioning (HVAC) filters is a promising long‐term sampling method to characterize airborne particle‐bound contaminants. This filter forensics (FF) approach provides valuable insights about differences between buildings, but does not allow for an estimation of indoor concentrations. In this investigation, FF is extended to quantitative filter forensics (QFF) by using measurements of the volume of air that passes through the filter and the filter efficiency, to assess the integrated average airborne concentrations of total fungal and bacterial DNA, 36 fungal species, endotoxins, phthalates, and organophosphate esters (OPEs) based on dust extracted from HVAC filters. Filters were collected from 59 homes located in central Texas, USA, after 1 month of deployment in each summer and winter. Results showed considerable differences in the concentrations of airborne particle‐bound contaminants in studied homes. The airborne concentrations for most of the analytes are comparable with those reported in the literature. In this sample of homes, the HVAC characterization measurements varied much less between homes than the variation in the filter dust concentration of each analyte, suggesting that even in the absence of HVAC data, FF can provide insight about concentration differences for homes with similar HVAC systems.     

Size distribution and lung-deposited doses of particulate matter from household exposure to biomass smoke

Exposure to high concentrations of particulate matter (PM) is associated with a number of adverse health effects. However, it is unclear which aspects of PM are most hazardous, and a better understanding of particle sizes and personal exposure is needed. We characterized particle size distribution (PSD) from biomass-related pollution and assessed total and regional lung-deposited doses using multiple-path deposition modeling. Gravimetric measurements of kitchen and personal PM_2.5 (<2.5 µm in size) exposures were collected in 180 households in rural Puno, Peru. Direct-reading measurements of number concentrations were collected in a subset of 20 kitchens for particles 0.3-25 µm, and the continuous PSD was derived using a nonlinear least-squares method. Mean daily PM_2.5 kitchen concentration and personal exposure was 1205 ± 942 µg/m³ and 115 ± 167 µg/m³, respectively, and the mean mass concentration consisted of a primary accumulation mode at 0.21 µm and a secondary coarse mode at 3.17 µm. Mean daily lung-deposited surface area (LDSA) and LDSA during cooking were 1009.6 ± 1469.8 µm²/cm³ and 10,552.5 ± 8261.6 µm²/cm³, respectively. This study presents unique data regarding lung deposition of biomass smoke that could serve as a reference for future studies and provides a novel, more biologically relevant metric for exposure-response analysis compared to traditional size-based metrics.     

Real-time measurements of PM2.5 and ozone to assess the effectiveness of residential indoor air filtration in Shanghai homes

Portable air cleaners are increasingly used in polluted areas in an attempt to reduce human exposure; however, there has been limited work characterizing their effectiveness at reducing exposure. With this in mind, we recruited forty-three children with asthma from suburban Shanghai and deployed air cleaners (with HEPA and activated carbon filters) in their bedrooms. During both 2-week filtration and non-filtration periods, low-cost PM_2.5 and O₃ air monitors were used to measure pollutants indoors, outdoors, and for personal exposure. Indoor PM_2.5 concentrations were reduced substantially with the use of air cleaners, from 34 ± 17 to 10 ± 8 µg/m³, with roughly 80% of indoor PM_2.5 estimated to come from outdoor sources. Personal exposure to PM_2.5 was reduced from 40 ± 17 to 25 ± 14 µg/m³. The more modest reductions in personal exposure and high contribution of outdoor PM_2.5 to indoor concentrations highlight the need to reduce outdoor PM_2.5 and/or to clean indoor air in multiple locations. Indoor O₃ concentrations were generally low (mean = 8±4 ppb), and no significant difference was seen by filtration status. The concentrations of pollutants and the air cleaner effectiveness were highly variable over time and across homes, highlighting the usefulness of real-time air monitors for understanding individual exposure reduction strategies.     

Variation in indoor particle number and PM2.5 concentrations in a radio station surrounded by busy roads before and after an upgrade of the HVAC system

Indoor particle number and PM_2.5 concentrations were investigated in a radio station surrounded by busy roads. Two extensive field measurement campaigns were conducted to determine the critical parameters affecting indoor air quality. The results indicated that indoor particle number and PM_2.5 concentrations were governed by outdoor air, and were significantly affected by the location of air intake and design of HVAC system. Prior to the upgrade of the HVAC system and relocation of the air intake, the indoor median particle number concentration was 7.4×10³ particles/cm³ and the median PM_2.5 concentration was 7 μg/m³. After the relocation of air intake and the redesign of the HVAC system, the indoor particle number concentration was between 2.3×10³ and 3.4×10³ particles/cm³, with a median value of 2.7×10³ particles/cm³, and the indoor PM_2.5 concentration was in the range of 3–5 μg/m³, with a median value of 4 μg/m³. By relocating the air intake of the HVAC, the outdoor particle number and PM_2.5 concentrations near the air intake were reduced by 35% and 55%, respectively. In addition, with the relocation of air intake and the redesign of the HVAC system, the particle number penetration rate was reduced from 42% to 14%, and the overall filtration efficiency of the HVAC system (relocation of air intake, pre-filter, AHU and particle losses in the air duct) increased from 58% to 86%. For PM_2.5, the penetration rate after the upgrade was approximately 18% and the overall filtration efficiency was 82%. This study demonstrates that by using a comprehensive approach, including the assessment of outdoor conditions and characterisation of ventilation and filtration parameters, satisfactory indoor air quality can be achieved, even for those indoor environments facing challenging outdoor air conditions.     

Comparison of next-generation portable pollution monitors to measure exposure to PM2.5 from household air pollution in Puno,Peru

Assessment of personal exposure to PM_2.5 is critical for understanding intervention effectiveness and exposure-response relationships in household air pollution studies. In this pilot study, we compared PM_2.5 concentrations obtained from two next-generation personal exposure monitors (the Enhanced Children MicroPEM or ECM; and the Ultrasonic Personal Air Sampler or UPAS) to those obtained with a traditional Triplex Cyclone and SKC Air Pump (a gravimetric cyclone/pump sampler). We co-located cyclone/pumps with an ECM and UPAS to obtain 24-hour kitchen concentrations and personal exposure measurements. We measured Spearmen correlations and evaluated agreement using the Bland-Altman method. We obtained 215 filters from 72 ECM and 71 UPAS co-locations. Overall, the ECM and the UPAS had similar correlation (ECM ρ = 0.91 vs UPAS ρ = 0.88) and agreement (ECM mean difference of 121.7 µg/m³ vs UPAS mean difference of 93.9 µg/m³) with overlapping confidence intervals when compared against the cyclone/pump. When adjusted for the limit of detection, agreement between the devices and the cyclone/pump was also similar for all samples (ECM mean difference of 68.8 µg/m³ vs UPAS mean difference of 65.4 µg/m³) and personal exposure samples (ECM mean difference of −3.8 µg/m³ vs UPAS mean difference of −12.9 µg/m³). Both the ECM and UPAS produced comparable measurements when compared against a cyclone/pump setup.     

Particle characterization in retail environments: concentrations,sources, and removal mechanisms

Particles in retail environments can have consequences for the occupational exposures of retail workers and customers, as well as the energy costs associated with ventilation and filtration. Little is known about particle characteristics in retail environments. We measured indoor and outdoor mass concentrations of PM₁₀ and PM_2.5, number concentrations of submicron particles (0.02–1 μm), size‐resolved 0.3–10 μm particles, as well as ventilation rates in 14 retail stores during 24 site visits in Pennsylvania and Texas. Overall, the results were generally suggestive of relatively clean environments when compared to investigations of other building types and ambient/occupational regulatory limits. PM₁₀ and PM_2.5 concentrations (mean ± s.d.) were 20 ± 14 and 11 ± 10 μg/m³, respectively, with indoor‐to‐outdoor ratios of 1.0 ± 0.7 and 0.88 ± 1.0. Mean submicron particle concentrations were 7220 ± 7500 particles/cm³ with an indoor‐to‐outdoor ratio of 1.18 ± 1.30. The median contribution to PM₁₀ and PM_2.5 concentrations from indoor sources (vs. outdoors) was 83% and 53%, respectively. There were no significant correlations between measured ventilation rates and particle concentrations of any size. When examining options to lower PM_2.5 concentrations below regulatory limits, the required changes to ventilation and filtration efficiency were site specific and depended on the indoor and outdoor concentration, emission rate, and infiltration level.     

Coarse particulate matter and airborne endotoxin within wood stove homes

Emissions from indoor biomass burning are a major public health concern in developing areas of the world. Less is known about indoor air quality, particularly airborne endotoxin, in homes burning biomass fuel in residential wood stoves in higher income countries. A filter‐based sampler was used to evaluate wintertime indoor coarse particulate matter (PM_10‐2.5) and airborne endotoxin (EU/m³, EU/mg) concentrations in 50 homes using wood stoves as their primary source of heat in western Montana. We investigated number of residents, number of pets, dampness (humidity), and frequency of wood stove usage as potential predictors of indoor airborne endotoxin concentrations. Two 48‐h sampling events per home revealed a mean winter PM_10‐2.5 concentration (± s.d.) of 12.9 (± 8.6) μg/m³, while PM_2.5 concentrations averaged 32.3 (± 32.6) μg/m³. Endotoxin concentrations measured from PM_10‐2.5 filter samples were 9.2 (± 12.4) EU/m³ and 1010 (± 1524) EU/mg. PM_10‐2.5 and PM_2.5 were significantly correlated in wood stove homes (r = 0.36, P < 0.05). The presence of pets in the homes was associated with PM_10‐2.5 but not with endotoxin concentrations. Importantly, none of the other measured home characteristics was a strong predictor of airborne endotoxin, including frequency of residential wood stove usage.     

Real-time air monitoring of occupational exposures to particulate matter among hairdressers in Maryland: A pilot study

Hairdressers are exposed to particulate matter (PM), a known air pollutant linked to adverse health effects. Still, studies on occupational PM exposures in hair salons are sparse. We characterized indoor air PM concentrations in three salons primarily serving an African/African American (AA) clientele, and three Dominican salons primarily serving a Latino clientele. We also assessed the performance of low-cost sensors (uRAD, Flow, AirVisual) by comparing them to high-end sensors (DustTrak) to conduct air monitoring in each salon over 3 days to quantify work shift concentrations of PM_2.5, respirable PM (RPM), and PM₁₀. We observed high spatial and temporal variability in 30-min time-weighted average (TWA) RPM concentrations (0.18–5518 μg/m³). Readings for the uRAD and AirVisual sensors were highly correlated with the DustTrak (R² = 0.90–0.99). RPM 8-hour TWAs ranged from 18 to 383 µg/m³ for AA salons, and 9–2115 µg/m³ for Dominican salons. Upper 95th percentiles of daily RPM exposures ranged from 439 to 2669 µg/m³. The overall range of 30-min TWA PM_2.5 and PM₁₀ concentrations was 0.13–5497 and 0.36-,541 μg/m³, respectively. Findings suggest that hairdressers could be overexposed to RPM during an 8-hour shift. Additional comprehensive monitoring studies are warranted to further characterize temporal and spatial variability of PM exposures in this understudied occupational population.     

Characterizing peak exposure of secondhand smoke using a real-time PM2.5 monitor

Although short-duration elevated exposures (peak exposures) to pollutants may trigger adverse acute effects, epidemiological studies to understand their influence on different health effects are hampered by lack of methods for objectively identifying peaks. Secondhand smoke from cigarettes (SHS) in the residential environment can lead to peak exposures. The aim of this study was to explore whether peaks in continuous PM_2.5 data can indicate SHS exposure. A total of 41 children (21 with and 20 without SHS exposure based on self-report) from 28 families in New York City (NY, USA) were recruited. Both personal and residential continuous PM_2.5 monitoring were performed for five consecutive days using MicroPEM sensors (RTI International, USA). A threshold detection method based on cumulative distribution function was developed to identify peaks. When children were home, the mean accumulated peak area (APA) for peak exposures was 297 ± 325 hour*µg/m³ for children from smoking families and six times that of the APA from non-smoking families (~50 ± 54 hour*µg/m³). Average PM_2.5 mass concentrations for SHS exposed and unexposed children were 24 ± 15 µg/m³ and 15 ± 9 µg/m³, respectively. The average SHS exposure duration represents ~5% of total exposure time, but ~13% of children's total PM_2.5 exposure dose, equivalent to an additional 2.6 µg/m³ per day. This study demonstrated the feasibility of peak analysis for quantifying SHS exposure. The developed method can be adopted more widely to support epidemiology studies on impacts of short-term exposures.     

Concurrent assessment of personal,indoor, and outdoor PM2.5 and PM1 levels and source contributions using novel low-cost sensing devices

The intensity, frequency, duration, and contribution of distinct PM_2.5 sources in Asian households have seldom been assessed; these are evaluated in this work with concurrent personal, indoor, and outdoor PM_2.5 and PM₁ monitoring using novel low-cost sensing (LCS) devices, AS-LUNG. GRIMM-comparable observations were acquired by the corrected AS-LUNG readings, with R² up to 0.998. Twenty-six non-smoking healthy adults were recruited in Taiwan in 2018 for 7-day personal, home indoor, and home outdoor PM monitoring. The results showed 5-min PM_2.5 and PM₁ exposures of 11.2 ± 10.9 and 10.5 ± 9.8 µg/m³, respectively. Cooking occurred most frequently; cooking with and without solid fuel contributed to high PM_2.5 increments of 76.5 and 183.8 µg/m³ (1 min), respectively. Incense burning had the highest mean PM_2.5 indoor/outdoor (1.44 ± 1.44) ratios at home and on average the highest 5-min PM_2.5 increments (15.0 µg/m³) to indoor levels, among all single sources. Certain events accounted for 14.0%-39.6% of subjects’ daily exposures. With the high resolution of AS-LUNG data and detailed time-activity diaries, the impacts of sources and ventilations were assessed in detail.     

A new exposure route to trace elements in indoor particulate matter

Concentrations and emission rates of sixteen trace elements in emitted PM during heating soybean oil using three types of pans, including Teflon, granitium, and cast-iron, were investigated. Statistically significant decreases in Mn and Co emission rates were observed when the oil was heated in the cast-iron pan compared to Teflon and granitium pans. Among the released trace elements, Ni, Ba, Zn, and Cr had more contribution to the emission rate. The concentrations of Fe in the emitted PM₁ were found to be higher when cast-iron pan (8.49 ± 3.35 µg/m³) was utilized compared to Teflon (8.05 ± 2.27 µg/m³) and granitium (7.45 ± 1.38 µg/m³). However, these increases were statistically insignificant. The results of our study support the hypothesis that the trace elements translocate from cooking pans into the heated oil and subsequently to the particulate phase. This translocation creates a new inhalation exposure route to trace elements in indoor environments.     

Exposure to fine,ultrafine particles and black carbon in two preschools in nur-sultan city of kazakhstan

Children in preschools were studied as an exceptionally vulnerable group to lung diseases due to their immature immune system. Few data are available in the literature addressing the exposure of children in preschools to ultrafine (>10 nm) particles. Exposure of children to fine, ultrafine (10 nm–1 µm) particles and black carbon particles present inside and near two preschools in Nur-Sultan, Kazakhstan, during Fall 2019 was investigated. For Preschool I, the average daily (6 h) indoor (outdoor) PM₁, PM_2.5, and PM₁₀ concentrations over three-week measurements were 15.0 (SD 12.5) µg/m³, 34.6 (SD 35.1) µg/m³, and 47.2 (SD 45.2) µg/m³, respectively. Average indoor UFP concentrations (>10.0 nm) including candle burning events were 5.20 × 10³ (SD 8.80 × 10³) particles/cm³, with the background UFP concentration to be 3.30 × 10³ (SD 1.80 × 10³) particles/cm³. In Preschool II, the average UFP concentration (>30.0 nm) in the morning and afternoon was 3.94 × 10³ (SD 5.34 × 10²) and 3.36 × 10³ (SD 1.90 × 10³) particles/cm³, respectively. Indoor black carbon (BC) concentrations were correlated with the outdoor smoking activity. The major sources of the indoor particles in the preschools were dust resuspension, candle burning, and infiltrated outdoor particles.     

Electrostatic dust collectors compared to inhalable samplers for measuring endotoxin concentrations in farm homes

Paired electrostatic dust collectors (EDCs) and daily, inhalable button samplers (BS) were used concurrently to sample endotoxin in 10 farm homes during 7‐day periods in summer and winter. Winter sampling included an optical particle counter (OPC) to measure PM_2.5 and PM_2.5–10. Electrostatic dust collectors and BS filters were analyzed for endotoxin using the kinetic chromogenic Limulus amebocyte lysate assay. Optical particle counter particulate matter (PM) data were divided into two PM categories. In summer, geometric mean (geometric standard deviation) endotoxin concentrations were 0.82 EU/m³ (2.7) measured with the BS and 737 EU/m² (1.9) measured with the EDC. Winter values were 0.52 EU/m³ (3.1) for BS and 538 EU/m² (3.0) for EDCs. Seven‐day endotoxin values of EDCs were highly correlated with the 7‐day BS sampling averages (r = 0.70; P < 0.001). Analysis of variance indicated a 2.4‐fold increase in EDC endotoxin concentrations for each unit increase of the ratio of PM_2.5 to PM_2.5–10. There was also a significant correlation between BS and EDCs endotoxin concentrations for winter (r = 0.67; P < 0.05) and summer (r = 0.75; P < 0.05). Thus, EDCs sample comparable endotoxin concentrations to BS, making EDCs a feasible, easy to use alternative to BS for endotoxin sampling.     

Indoor air quality in new and renovated low-income apartments with mechanical ventilation and natural gas cooking in California

This paper presents pollutant concentrations and performance data for code-required mechanical ventilation equipment in 23 low-income apartments at 4 properties constructed or renovated 2013-2017. All apartments had natural gas cooking burners. Occupants pledged to not use windows for ventilation during the study but several did. Measured airflows of range hoods and bathroom exhaust fans were lower than product specifications. Only eight apartments operationally met all ventilation code requirements. Pollutants measured over one week in each apartment included time-resolved fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), formaldehyde and carbon dioxide (CO₂) and time-integrated formaldehyde, NO₂ and nitrogen oxides (NO_X). Compared to a recent study of California houses with code-compliant ventilation, apartments were smaller, had fewer occupants, higher densities, and higher mechanical ventilation rates. Mean PM_2.5, formaldehyde, NO₂, and CO₂ were 7.7 µg/m³, 14.1, 18.8, and 741 ppm in apartments; these are 4% lower, 25% lower, 165% higher, and 18% higher compared to houses with similar cooking frequency. Four apartments had weekly PM_2.5 above the California annual outdoor standard of 12 µg/m³ and also discrete days above the World Health Organization 24-hour guideline of 25 µg/m³. Two apartments had weekly NO₂ above the California annual outdoor standard of 30 ppb.     

Modeling approaches and performance for estimating personal exposure to household air pollution: A case study in Kenya

This study assessed the performance of modeling approaches to estimate personal exposure in Kenyan homes where cooking fuel combustion contributes substantially to household air pollution (HAP). We measured emissions (PM_2.5, black carbon, CO); household air pollution (PM_2.5, CO); personal exposure (PM_2.5, CO); stove use; and behavioral, socioeconomic, and household environmental characteristics (eg, ventilation and kitchen volume). We then applied various modeling approaches: a single-zone model; indirect exposure models, which combine person-location and area-level measurements; and predictive statistical models, including standard linear regression and ensemble machine learning approaches based on a set of predictors such as fuel type, room volume, and others. The single-zone model was reasonably well-correlated with measured kitchen concentrations of PM_2.5 (R² = 0.45) and CO (R² = 0.45), but lacked precision. The best performing regression model used a combination of survey-based data and physical measurements (R² = 0.76) and a root mean-squared error of 85 µg/m³, and the survey-only-based regression model was able to predict PM2.5 exposures with an R² of 0.51. Of the machine learning algorithms evaluated, extreme gradient boosting performed best, with an R² of 0.57 and RMSE of 98 µg/m³.     

In-situ effectiveness of residential HVAC filters

In this study, we explore different filter and contextual characteristics that influence effectiveness of high-efficiency filters in 21 residences in Toronto, Canada. The in situ effectiveness was assessed with decay tests at the beginning and the end of filter life with four different filters (MERV 8-14 from ASHRAE Standard 52.2) installed in operational HVAC systems, compared with either the system off or with no filter installed. There was considerable difference between median PM_2.5 effectiveness of the non-electret filters when compared to electret filters (16% vs. 36%) of the same nominal efficiency (MERV 8). However, median PM_2.5 effectiveness of electret filters only slightly improved (between 5% and 9% absolute increase) as MERV increased from 8 to 14. There was more variation in filter effectiveness between the same filter in different homes than there was between different filters in the same home. Variations in filter performance arose because home-specific particle loss rates (eg, ventilation rate) vary greatly in different buildings. The higher the loss rates due to non-filter factors, the lower the effectiveness of a filter. Given the relatively large variation in effectiveness for a given filter over time and in different homes, increasing system runtime may be a productive way to improve filter performance in many homes.     

Unexpected increase in indoor pollutants after the introduction of a smoke‐free policy in a correctional center

Correctional centers (prisons) are one of the few non‐residential indoor environments where smoking is still permitted. However, few studies have investigated indoor air quality (IAQ) in these locations. We quantified the level of inmate and staff exposure to secondhand smoke, including particle number (PN) count, and we assessed the impact of the smoking ban on IAQ. We performed measurements of indoor and outdoor PM_2.5 and PN concentrations, personal PN exposure levels, volatile organic compounds (VOCs), and nicotine both before and after a complete indoor smoking ban in an Australian maximum security prison. Results show that the indoor 24‐h average PM_2.5 concentrations ranged from 6 (±1) μg/m³ to 17 (±3) μg/m³ pre‐ban. The post‐ban levels ranged from 7 (±2) μg/m³ to 71 (±43) μg/m³. While PM_2.5 concentrations decreased in one unit post‐ban, they increased in the other two units. Similar post‐ban increases were also observed in levels of PN and VOCs. We describe an unexpected increase of indoor pollutants following a total indoor smoking ban in a prison that was reflected across multiple pollutants that are markers of smoking. We hypothesise that clandestine post‐ban smoking among inmates may have been the predominant cause.     

Infiltration of fine particles in urban daycares

Singapore is a tropical country with a high density of day-care facilities whose indoor environments may be adversely affected by outdoor fine particle (PM_2.5) air pollution. To reduce this problem requires effective, evidence-based exposure-reduction strategies. Little information is available on the penetration of outdoor PM_2.5 into day-care environments. Our study attempted to address the following objectives: to measure indoor infiltration factor (F_inf) of PM_2.5 from outdoor PM_2.5 and to determine the building parameters that modify the indoor PM_2.5. We collected indoor/outdoor 1-min PM_2.5 from 50 day-care classrooms. We noted mean F_inf ± SD of 0.65 ± 0.22 in day-care rooms which are naturally ventilated and lower F_inf ± SD values of 0.47 ± 0.18 for those that are air-conditioned: values which are lower than those reported in Singapore residences. The air exchange rates were higher in naturally ventilated rooms (1.47 vs 0.86 h⁻¹). However, fine particle deposition rates were lower for naturally ventilated rooms (0.67 ± 0.43 h⁻¹) compared with air-conditioned ones (1.03 ± 0.55 h⁻¹) presumably due to composite rates linked to the filters within the split unit air-conditioners, higher recirculation rates, and interior surfaces in the latter. Our findings indicate that children remaining indoor in daycares where air-conditioning is used can reduce their PM_2.5 exposures during outdoor pollution episodes.     

Environmental and individual exposure to secondhand aerosol of electronic cigarettes in confined spaces: Results from the TackSHS Project†

Secondhand electronic cigarette (e-cigarette) aerosol (SHA) might impair indoor air quality and expose bystanders. This study aims to investigate exposure to SHA in controlled conditions of enclosed settings simulating real-world scenario. An experiment was performed in a car and in a room, in which SHA was generated during a 30-minute ad libitum use of an e-cigarette. The experiment was replicated on five consecutive days in each setting. We measured PM_2.5, airborne nicotine concentrations, and biomarkers of exposure to SHA, such as nicotine metabolites, tobacco-specific nitrosamines, propylene glycol, and glycerol in bystanders’ saliva samples before, during, and after the exposure period. Self-reported health symptoms related to exposure to SHA were also recorded. The results showed that the highest median PM_2.5 concentration was recorded during the exposure period, being 21 µg/m³ in the room setting and 16 µg/m³ in the car setting—about twofold increase compared to the baseline. Most concentrations of the airborne nicotine and all biomarkers were below the limit of quantification in both settings. Bystanders in both settings experienced some short-term irritation symptoms, expressed as dry throat, nose, eyes, and phlegm. In conclusion, short-term use of an e-cigarette in confined spaces increased indoor PM_2.5 level and caused some irritation symptoms in bystanders.