Long-Term Indoor-Outdoor PM2.5 Measurements Using PurpleAir Sensors: An Improved Method of Calculating Indoor-Generated and Outdoor-Infiltrated Contributions to Potential Indoor Exposure.

Low-cost monitors make it possible now for the first time to collect long-term (months to years) measurements of potential indoor exposure to fine particles. Indoor exposure is due to two sources: particles infiltrating from outdoors and those generated by indoor activities. Calculating the relative contribution of each source requires identifying an infiltration factor. We develop a method of identifying periods when the infiltration factor is not constant and searching for periods when it is relatively constant. From an initial regression of indoor on outdoor particle concentrations, a Forbidden Zone can be defined with an upper boundary below which no observations should appear. If many observations appear in the Forbidden Zone, they falsify the assumption of a single constant infiltration factor. This is a useful quality assurance feature, since investigators may then search for subsets of the data in which few observations appear in the Forbidden Zone. The usefulness of this approach is illustrated using examples drawn from the PurpleAir network of optical particle monitors. An improved algorithm is applied with reduced bias, improved precision, and a lower limit of detection than either of the two proprietary algorithms offered by the manufacturer of the sensors used in PurpleAir monitors.

Spatial Variation of PM2.5 Indoors and Outdoors: Results from 261 Regulatory Monitors Compared to 14,000 Low-Cost Monitors in Three Western States over 4.7 Years.

Spatial variation of indoor and outdoor PM2.5 within three states for a five-year period is studied using regulatory and low-cost PurpleAir monitors. Most of these data were collected in an earlier study (Wallace et al., 2022 Indoor Air 32:13105) investigating the relative contribution of indoor-generated and outdoor-infiltrated particles to indoor exposures. About 260 regulatory monitors and ~10,000 outdoor and ~4000 indoor PurpleAir monitors are included. Daily mean PM2.5 concentrations, correlations, and coefficients of divergence (COD) are calculated for pairs of monitors at distances ranging from 0 (collocated) to 200 km. We use a transparent and reproducible open algorithm that avoids the use of the proprietary algorithms provided by the manufacturer of the sensors in PurpleAir PA-I and PA-II monitors. The algorithm is available on the PurpleAir API website under the name "PM2.5_alt". This algorithm is validated using several hundred pairs of regulatory and PurpleAir monitors separated by up to 0.5 km. The PM2.5 spatial variation outdoors is homogeneous with high correlations to at least 10 km, as shown by the COD index under 0.2. There is also a steady improvement in outdoor PM2.5 concentrations with increasing distance from the regulatory monitors. The spatial variation of indoor PM2.5 is not homogeneous even at distances < 100 m. There is good agreement between PurpleAir outdoor monitors located <100 m apart and collocated Federal Equivalent Methods (FEM).

Indoor contribution to PM2 .5 exposure using all PurpleAir sites in Washington, Oregon, and California.

Low-cost monitors have made it possible for the first time to measure indoor PM2.5 concentrations over extended periods of time (months to years). Coupled with concurrent outdoor measurements, these indoor measurements can be divided into particles entering the building from outdoors and particles generated from indoor activities. Indoor-generated particles are not normally considered in epidemiological studies, but they can have health effects (e.g., passive smoking and high-temperature cooking). We employed The Random Component Superposition (RCS) regression model to estimate infiltration factors for up to 790 000 matched indoor and outdoor sites. The median infiltration factors for subgroups in the 3-state region ranged between 0.22 and 0.24, with an interquartile range (IQR) of 0.13-0.40. These infiltration factors allowed calculation of both the indoor-generated and outdoor-infiltrated PM2.5 . Indoor-generated particles contributed, on average, 46%-52% of total indoor PM2.5 concentrations. However, the site-specific fractional contribution of these indoor sources to total indoor PM2.5 ranged from near-zero to nearly 100%. The influence of indoor-generated particles on potential exposures varied widely relative to outdoor concentrations. The greatest influence of indoor-generated particles occurred at low-to-moderate daily mean outdoor PM2.5 levels around 6 µg/m3 and was negligible at outdoor concentrations >20 µg/m3 . Epidemiological studies incorporating only estimated exposures due to the particles of ambient origin may benefit from the newly available knowledge of long-term indoor-generated particle concentrations.

Intercomparison of PurpleAir Sensor Performance over Three Years Indoors and Outdoors at a Home: Bias, Precision, and Limit of Detection Using an Improved Algorithm for Calculating PM2.5.

Low-cost particle sensors are now used worldwide to monitor outdoor air quality. However, they have only been in wide use for a few years. Are they reliable? Does their performance deteriorate over time? Are the algorithms for calculating PM2.5 concentrations provided by the sensor manufacturers accurate? We investigate these questions using continuous measurements of four PurpleAir monitors (8 sensors) under normal conditions inside and outside a home for 1.5-3 years. A recently developed algorithm (called ALT-CF3) is compared to the two existing algorithms (CF1 and CF_ATM) provided by the Plantower manufacturer of the PMS 5003 sensors used in PurpleAir PA-II monitors. Results. The Plantower CF1 algorithm lost 25-50% of all indoor data due in part to the practice of assigning zero to all concentrations below a threshold. None of these data were lost using the ALT-CF3 algorithm. Approximately 92% of all data showed precision better than 20% using the ALT-CF3 algorithm, but only approximately 45-75% of data achieved that level using the Plantower CF1 algorithm. The limits of detection (LODs) using the ALT-CF3 algorithm were mostly under 1 µg/m3, compared to approximately 3-10 µg/m3 using the Plantower CF1 algorithm. The percentage of observations exceeding the LOD was 53-92% for the ALT-CF3 algorithm, but only 16-44% for the Plantower CF1 algorithm. At the low indoor PM2.5 concentrations found in many homes, the Plantower algorithms appear poorly suited.

Calibration of PurpleAir PA-I and PA-II Monitors Using Daily Mean PM2.5 Concentrations Measured in California, Washington, and Oregon from 2017 to 2021.

Large quantities of real-time particle data are becoming available from low-cost particle monitors. However, it is crucial to determine the quality of these measurements. The largest network of monitors in the United States is maintained by the PurpleAir company, which offers two monitors: PA-I and PA-II. PA-I monitors have a single sensor (PMS1003) and PA-II monitors employ two independent PMS5003 sensors. We determine a new calibration factor for the PA-I monitor and revise a previously published calibration algorithm for PA-II monitors (ALT-CF3). From the PurpleAir API site, we downloaded 83 million hourly average PM2.5 values in the PurpleAir database from Washington, Oregon, and California between 1 January 2017 and 8 September 2021. Daily outdoor PM2.5 means from 194 PA-II monitors were compared to daily means from 47 nearby Federal regulatory sites using gravimetric Federal Reference Methods (FRM). We find a revised calibration factor of 3.4 for the PA-II monitors. For the PA-I monitors, we determined a new calibration factor (also 3.4) by comparing 26 outdoor PA-I sites to 117 nearby outdoor PA-II sites. These results show that PurpleAir PM2.5 measurements can agree well with regulatory monitors when an optimum calibration factor is found.

Contributions of Coagulation, Deposition, and Ventilation to the Removal of Airborne Nanoparticles in Indoor Environments.

Airborne nanoparticles are frequently released in occupied spaces due to episodic indoor source activities. Once generated, nanoparticles undergo aerosol transformation processes such as coagulation and deposition. These aerosol processes lead to changes in particle concentration and size distribution over time and accordingly affect human exposure to nanoparticles. The present study establishes a framework for an indoor particle dynamic model that can predict time- and size-dependent particle concentrations after episodic indoor emission events. The model was evaluated with six experimental data sets obtained from previous measurement studies in the literature. The indoor particle dynamic model quantified the relative contributions of three particle loss mechanisms (i.e., coagulation, deposition, and ventilation) to the total reduction in number concentration. The results show that particle coagulation and indoor surface deposition are two dominant processes responsible for temporal changes in particle size and concentration following indoor emission events. The first-order equivalent coagulation loss rate notably varies with indoor emission source and accounts for up to 59% of the total particle loss for burning a candle, 42% for broiling a fish, and 10% for burning incense. The results reveal that while the coagulation loss rate changes markedly with the particle concentration and source type, the deposition loss rate is more dependent on particle size. Compared to coagulation and deposition, the effect of ventilation is marginal for most of the nanoparticle emission events indoors; however, ventilation loss becomes pronounced with the decrease of particle concentration below 5 × 104 cm-3, especially for particles larger than 100 nm in aerodynamic diameter.

Dynamic behavior of indoor ultrafine particles (2.3-64 nm) due to burning candles in a residence.

A major source of human exposure to ultrafine particles is candle use. Candles produce ultrafine particles in the size range under 10 nm, with perhaps half of the particles less than 5 nm. For these small particles at typically high concentrations, coagulation and deposition are two dominant mechanisms in aerosol size dynamics. We present an updated coagulation model capable of characterizing the relative contributions of coagulation, deposition, and air exchange rates. Size-resolved coagulation and decay rates are estimated for three types of candles. Number, area, and mass distributions are provided for 93 particle sizes from 2.33 to 64 nm. Total particle production was in the range of 1013  min-1 . Peak number, area, and mass concentrations occurred at particle sizes of <3, 20, and 40 nm, respectively. Both the number and area concentrations greatly exceeded background concentrations in the residence studied. Contributions of coagulation, deposition, and air exchange rates to particle losses were 65%, 34%, and 0.3% at high concentrations (106  cm-3 ), while they are 17%, 81%, and 1.7% at lower concentrations (3 × 104  cm-3 ), respectively. The increased particle production for the very smallest particles (2.33-2.50 nm) suggests that even smaller particles may be important to study.

Desorption of SVOCs from Heated Surfaces in the Form of Ultrafine Particles.

Ultrafine particles (UFP) produced by electric heating of stoves and metal cooking pans, absent food, have been hypothesized to be created from a surface film of semivolatile organic compounds (SVOCs) sorbed from the surrounding air. This study tests that hypothesis by size-resolved measurements extending the lower range of the UFP studied from 10 to 2.3 nm, and including other surfaces (glass, aluminum, and porcelain). Heating glass Petri dishes or squares of aluminum foil to about 350-400 °C for 4-6 min removed all sorbed organic substances completely. Subsequent exposure of these "clean" Petri dishes and foil squares to indoor air in two different residences for successively longer periods (1 h to 281 days), followed by heating the materials for 4-6 min, indicated a strong relationship of the number, size distribution, and mass of the UFP to the time exposed. Estimates of the accumulation rate of SVOCs on surfaces were similar to those in studies of organic film buildup on indoor windows. Transfer of skin oils by touching the glass or foil surfaces, or after washing the glass surface with detergent and bare hands, was also observed, with measured particle production comparable with that produced by long-term exposure to indoor air.

Metro Commuter Exposures to Particulate Air Pollution and PM2.5-Associated Elements in Three Canadian Cities: The Urban Transportation Exposure Study.

System-representative commuter air pollution exposure data were collected for the metro systems of Toronto, Montreal, and Vancouver, Canada. Pollutants measured included PM2.5 (PM = particulate matter), PM10, ultrafine particles, black carbon, and the elemental composition of PM2.5. Sampling over three weeks was conducted in summer and winter for each city and covered each system on a daily basis. Mixed-effect linear regression models were used to identify system features related to particulate exposures. Ambient levels of PM2.5 and its elemental components were compared to those of the metro in each city. A microenvironmental exposure model was used to estimate the contribution of a 70 min metro commute to daily mean exposure to PM2.5 elemental and mass concentrations. Time spent in the metro was estimated to contribute the majority of daily exposure to several metallic elements of PM2.5 and 21.2%, 11.3% and 11.5% of daily PM2.5 exposure in Toronto, Montreal, and Vancouver, respectively. Findings suggest that particle air pollutant levels in Canadian metros are substantially impacted by the systems themselves, are highly enriched in steel-based elements, and can contribute a large portion of PM2.5 and its elemental components to a metro commuter's daily exposure.

Size-Resolved Source Emission Rates of Indoor Ultrafine Particles Considering Coagulation.

Indoor ultrafine particles (UFP, <100 nm) released from combustion and consumer products lead to elevated human exposure to UFP. UFP emitted from the sources undergo aerosol transformation processes such as coagulation and deposition. The coagulation effect can be significant during the source emission due to high concentration and high mobility of nanosize particles. However, few studies have estimated size-resolved UFP source emission strengths while considering coagulation in their theoretical and experimental research work. The primary objective of this study is to characterize UFP source strength by considering coagulation in addition to other indoor processes (i.e., deposition and ventilation) in a realistic setting. A secondary objective is to test a hypothesis that size-resolved UFP source emission rates are unimodal and log-normally distributed for three common indoor UFP sources: an electric stove, a natural gas burner, and a paraffin wax candle. Experimental investigations were performed in a full-scale test building. Size- and time-resolved concentrations of UFP ranging from 2 to 100 nm were monitored using a scanning mobility particle sizer (SMPS). Based on the temporal evolution of the particle size distribution during the source emission period, the size-dependent source emission rate was determined using a material-balance modeling approach. The results indicate that, for a given UFP source, the source strength varies with particle size and source type. The analytical model assuming a log-normally distributed source emission rate could predict the temporal evolution of the particle size distribution with reasonable accuracy for the gas stove and the candle. Including the effect of coagulation was found to increase the estimates of source strengths by up to a factor of 8. This result implies that previous studies on indoor UFP source strengths considering only deposition and ventilation might have largely underestimated the true values of UFP source strengths, especially for combustion due to the natural gas stove and the candle.

In-vehicle exposures to particulate air pollution in Canadian metropolitan areas: the urban transportation exposure study.

Commuters may be exposed to increased levels of traffic-related air pollution owing to close proximity to traffic-emissions. We collected in-vehicle and roof-top air pollution measurements over 238 commutes in Montreal, Toronto, and Vancouver, Canada between 2010 and 2013. Voice recordings were used to collect real-time information on traffic density and the presence of diesel vehicles and multivariable linear regression models were used to estimate the impact of these factors on in-vehicle pollutant concentrations (and indoor/outdoor ratios) along with parameters for road type, land use, and meteorology. In-vehicle PM2.5 and NO2 concentrations consistently exceeded regional outdoor levels and each unit increase in the rate of encountering diesel vehicles (count/min) was associated with substantial increases (>100%) in in-vehicle concentrations of ultrafine particles (UFPs), black carbon, and PM2.5 as well as strong increases (>15%) in indoor/outdoor ratios. A model based on meteorology and the length of highway roads within a 500 m buffer explained 53% of the variation in in-vehicle UFPs; however, models for PM2.5 (R(2) = 0.24) and black carbon (R(2) = 0.30) did not perform as well. Our findings suggest that vehicle commuters experience increased exposure to air pollutants and that traffic characteristics, land use, road types, and meteorology are important determinants of these exposures.

Indoor and Outdoor Levels and Sources of Submicron Particles (PM1) at Homes in Edmonton, Canada.

Exposure to submicron particles (PM1) is of interest due to their possible chronic and acute health effects. Seven consecutive 24-h PM1 samples were collected during winter and summer 2010 in a total of 74 nonsmoking homes in Edmonton, Canada. Median winter concentrations of PM1 were 2.2 µg/m(3) (interquartile range, IQR = 0.8-6.1 µg/m(3)) and 3.3 µg/m(3) (IQR = 1.5-6.9 µg/m(3)) for indoors and outdoors, respectively. In the summer, indoor (median 4.4 µg/m(3), IQR = 2.4-8.6 µg/m(3)) and outdoor (median 4.3 µg/m(3), IQR = 2.6-7.4 µg/m(3)) levels were similar. Positive matrix factorization (PMF) was applied to identify and apportion indoor and outdoor sources of elements in PM1 mass. Nine sources contributing to both indoor and outdoor PM1 concentrations were identified including secondary sulfate, soil, biomass smoke and environmental tobacco smoke (ETS), traffic, settled and mixed dust, coal combustion, road salt/road dust, and urban mixture. Three additional indoor sources were identified i.e., carpet dust, copper-rich, and silver-rich. Secondary sulfate, soil, biomass smoke and ETS contributed more than 70% (indoors: 0.29 µg/m(3), outdoors: 0.39 µg/m(3)) of measured elemental mass in PM1. These findings can aid understanding of relationships between submicron particles and health outcomes for indoor/outdoor sources.

Respiratory and cardiovascular effects of metals in ambient particulate matter: a critical review.

In this review, we critically evaluated the epidemiological and toxicological evidence for the role of specific transition metals (As. Cr. Cu. Fe. Mn. Ni. Sc. Ti. V and Zn) in causing or contributing to the respiratory and cardiovascular health effects associated with ambient PM. Although the epidemiologic studies arc suggestive. and both the in vivo and in vitro laboratory studies document the toxicity of specific metals (Fe. Ni. V and Zn). the overall weight of evidence does not convincingly implicate metals as major contributors to health effects. None of the epidemiology studies that we reviewed conclusively implicated specific transition metals as having caused the respiratory and cardiovascular effects associated with ambient levels of PM. However, the studies reviewed tended to be internal ly consistent in identifying some metals (Fe, Ni, V and Zn) more frequently than others (As, Cu, Mn and Sc) as having positive associations wi th health effects. The major problem wi th which the epidemiological studies were faced was classifying and quantifying exposure. Community and population exposures to metals or other components of ambient PM were inferred from centrally- located samplers that may not accurately represent individual level exposures. Only a few authors reported findings that did not support the stated premise of the study; indeed, statistic ally significant associations are not necessarily biologically significant. It is likely that ·'negative studies" are under-represented in the published literature, making it a challenge to achieve a balanced evaluation of the role of metals in causing health effects associated with ambient PM. Both the in vivo and in vitro study results demonstrated that individual metals (Cu. Fe. Ni. V and Zn) and extracts of metals from ambient PM sources can produce acute inflammatory responses. However. the doses administered to laboratory animals were many orders of magnitude greater than what humans experience from breathing ambient air. The studies that used intratracheal instillation have the advantage of delivering a known dose to a specific anatomical location. but arc not analogous to an inhaled dose that is distributed over the surface area of the respiratory tract. Studies. in which laboratory animals or human volunteers inhaled CAPs best represent exposures to the general human population. The in vivo and in vitro studies reviewed provide indications that the probable mechanisms involved in the respiratory and cardiac effects from high metal exposures include: an inflammatory response mediated by formation of ROS, upregulation of genes coding for inflammatory cytokines, altered expression of genes involved in cell signaling pathways and maintenance of metals homeostasis.The fact that doses of metals many orders of magnitude greater than those existing in ambient air were required to produce measurable adverse effects in animals makes it doubtful that metals play any major role in respiratory and cardiovascular effects produced from human exposure to ambient PM. We suggest that future research priorities should focus on testing at more environmentally relevant exposure levels and that any new toxicological studies be written to include dosages in units that can be easily compared to human exposure levels.

Impacts of air cleaners on indoor air quality in residences impacted by wood smoke.

Residential wood combustion is an important source of ambient air pollution, accounting for over 25% of fine particulate matter (PM2.5) emissions in Canada. In addition to these ambient contributions, wood smoke pollutants can enter the indoor environment directly when loading or stoking stoves, resulting in a high potential for human exposure. A study of the effectiveness of air cleaners at reducing wood smoke-associated PM2.5 of indoor and outdoor origin was conducted in 31 homes during winter 2009-10. Day 1, the residents' wood burning appliance operated as usual with no air cleaner. Days 2 and 3, the wood burning appliance was not operational and the air cleaner was randomly chosen to operate in "filtration" or "placebo filtration" mode. When the air cleaner was operating, total indoor PM2.5 levels were significantly lower than on placebo filtration days (p = 0.0001) resulting in a median reduction of 52%. There was also a reduction in the median PM2.5 infiltration factor from 0.56 to 0.26 between these 2 days, suggesting the air cleaner was responsible for increased PM2.5 deposition on filtration days. Our findings suggest that the use of an air cleaner reduces exposure to indoor PM2.5 resulting from both indoor and ambient wood smoke sources.

Indoor ultrafine particles of outdoor origin: importance of window opening area and fan operation condition.

Inhalation exposure to ambient ultrafine particles (UFP) has been shown to induce adverse health effects such as respiratory and cardiovascular mortality. Human exposure to particles of outdoor origin often occurs indoors due to entry of UFP into buildings. The objective of the present study is to investigate entry of UFP into a building considering building operational characteristics and their size-dependent effects on UFP concentrations. Indoor and outdoor UFP concentrations along with air change rates were continuously measured in a full-scale test building. Estimates of infiltration factor, penetration coefficient, and deposition rate have been made for a range of particle sizes from 4 to 100 nm. The results show that UFP infiltration factor varies with particle diameter, window position, air change rate, and central fan operation. When the central fan was on continuously, the average infiltration factor ranged from 0.26 (particles <10 nm) to 0.82 (particles >90 nm) for two large window openings, and from 0.07 to 0.60 for two small window openings. Under the central fan-off condition, the average infiltration factor ranged from 0.25 (particles <10 nm) to 0.72 (particles >90 nm) for two small window openings, while it ranged from 0.01 to 0.48 with all windows closed. Larger window openings led to higher infiltration factors due to the larger extent of particle penetration into the building. The fan operation mode (on vs off) also has a strong impact, as the infiltration factor was consistently lower (up to 40%) when the fan was on due to additional particle deposition loss to the furnace filter and duct surfaces.

Fine and ultrafine particle decay rates in multiple homes.

Human exposure to particles depends on particle loss mechanisms such as deposition and filtration. Fine and ultrafine particles (FP and UFP) were measured continuously over seven consecutive days during summer and winter inside 74 homes in Edmonton, Canada. Daily average air exchange rates were also measured. FP were also measured outside each home and both FP and UFP were measured at a central monitoring station. A censoring algorithm was developed to identify indoor-generated concentrations, with the remainder representing particles infiltrating from outdoors. The resulting infiltration factors were employed to determine the continuously changing background of outdoor particles infiltrating the homes. Background-corrected indoor concentrations were then used to determine rates of removal of FP and UFP following peaks due to indoor sources. About 300 FP peaks and 400 UFP peaks had high-quality (median R(2) value >98%) exponential decay rates lasting from 30 min to 10 h. Median (interquartile range (IQR)) decay rates for UFP were 1.26 (0.82-1.83) h(-1); for FP 1.08 (0.62-1.75) h(-1). These total decay rates included, on average, about a 25% contribution from air exchange, suggesting that deposition and filtration accounted for the major portion of particle loss mechanisms in these homes. Models presented here identify and quantify effects of several factors on total decay rates, such as window opening behavior, home age, use of central furnace fans and kitchen and bathroom exhaust fans, use of air cleaners, use of air conditioners, and indoor-outdoor temperature differences. These findings will help identify ways to reduce exposure and risk.

Cracking the code-Matching a proprietary algorithm for a low-cost sensor measuring PM1 and PM2.5.

Some manufacturers of low-cost particle sensors use proprietary algorithms to estimate particle mass concentrations such as PM2.5. Often little or no information is given regarding the calibration aerosol, how the algorithm was created or tested, or how the mass was estimated from the particle number counts. If the algorithm is faulty in some way, researchers have little ability to correct it in a fundamental way, although they can multiply the output by some calibration factor to match the particular aerosol combination they are studying. However, the adjustment still requires the use of the proprietary algorithm, which may have quirks that make it impossible to fix completely using a single calibration factor. It might be possible in some cases to avoid using the proprietary algorithm at all. That is the approach of this study. The low-cost sensor studied is the Plantower PMS 5003, and the algorithm is the CF_1 algorithm offered by the manufacturer. Data from a six-month study of four collocated PurpleAir PA-II monitors, each containing two independent Plantower PMS 5003 sensors, were collected. Two of these monitors had previously been calibrated against research-grade monitors. The best-fitting model for PM1 was found to be of the form PM1 = a*(N1 + N2) + d, where N1 and N2 are the particle numbers in the size categories 0.3-0.5 µm and 0.5-1 µm, and d is an additive constant. The best-fitting model for PM2.5 was of the form a*(N1 + N2) + b*N3 + d, where N3 is the number of particles in the third size fraction (1-2.5 µm). The individual models for all 8 sensors matched the reported CF_1 values for both PM1 and PM2.5 with R2 values exceeding 0.99, intercepts near zero, and slopes in the 0.99-1.01 range. The proposed models may also explain why the CF_1 algorithm reports values of zero for a substantial portion of PM1 and PM2.5 estimates. General models capable of being applied to other datasets were developed and estimated to have mean absolute errors (MAEs) <1 µg/m3.

Size-resolved emission rates of episodic indoor sources and ultrafine particle dynamics.

Indoor airborne ultrafine particles (UFPs) are mainly originated from occupant activities, such as candle burning and cooking. Elevated exposure to UFPs has been found to increase oxidative stress and cause DNA damage. UFPs originating from indoor sources undergo dynamic aerosol transformation mechanisms. This study investigates the dynamics of UFPs following episodic indoor releases of the six distinct emission sources: 1) candle, 2) gas stove, 3) clothes dryer, 4) tea & toast, 5) broiled fish, and 6) incense. Based on the analytical model of aerosol dynamic processes, this study reports size-resolved source emission rates along with relative contributions of coagulation, deposition, and ventilation to the particle size distribution dynamics. The study findings indicate a significant variation in the geometric mean diameter (GMD) and size-resolved number concentration over time for the sources that emit a substantial amount of UFPs smaller than 10 nm. As the emission progresses, the UFP number concentrations increase in a log-normal distribution, while the GMD shows a tendency to increase over time. The observed result suggests that coagulation can have a considerable impact on UFP number concentration and size, even during the indoor UFP emission. The estimated emission rates of the six indoor sources appear to follow a log-normal distribution while the emission rate ranges from 107 min-1 to 1012 min-1. The indoor UFP concentration and size distribution dynamics are substantially affected by the interplay of the three aerosol loss mechanisms that compete with each other, and this impact varies according to the source type and the indoor environmental conditions. Ultimately, using the aerosol transformation mechanisms examined in this study, researchers can refine exposure assessment for epidemiological studies on indoor ultrafine particles.

PM2.5 exposure close to marijuana smoking and vaping: A case study in residential indoor and outdoor settings.

We conducted 35 experiments for spatial measurement of marijuana aerosols in a current smoker's residential spaces. Fine particulate matter (PM2.5) concentrations were measured every second at 1, 2, and 3 m horizontal distances from the smoker who performed prescribed 5-min smoking and vaping activities. In each experiment, five SidePak monitors measured PM2.5 concentrations at five different angles facing the front of the smoker, representing the worst-case exposures. We studied the effect of distance from the smoker for two marijuana sources - smoking a marijuana cigarette, or joint, and vaping a liquid-cartridge vaping pen. Experiments were conducted in the family room indoors and in the backyard outdoors where the smoker normally consumes marijuana. Indoor marijuana vaping had higher average exposures (5-min PM2.5) at 1 m distance than indoor marijuana smoking, but the levels from indoor vaping decreased more rapidly with distance (e.g., 77% reduction for vaping versus 33% for smoking from 1 to 2 m). Smoking and vaping in the outdoor environment reduce the average exposures down to <5% of the indoor levels at each distance. Cumulative frequency distributions of the 1-s PM2.5 concentrations revealed the frequencies of exceeding any selected transient peak exposure limit at a given distance. The frequency of exceedance decreased more quickly with distance for vaping than for smoking. Smoking and vaping outdoors made the transient peak exposures close to the source much less frequent than smoking and vaping indoors (e.g., <1% exceeded 1000 µg/m3 outdoors versus >20% indoors at 1 m). Plotting the frequency of exceedance versus distance could offer additional guidance for a recommended minimum distance from a marijuana source.

Measuring PM2.5 concentrations from secondhand tobacco vs. marijuana smoke in 9 rooms of a detached 2-story house.

The widespread legalization of recreational marijuana raises growing concerns about exposure to secondhand marijuana smoke. An important location for marijuana smoking is the home, but few measurements of air pollutant concentrations in the home are available for a marijuana joint fully smoked in one of its rooms. We used research grade calibrated real-time continuous PM2.5 air monitors in controlled 5-hour experiments to measure fine particle concentrations in the 9 rooms of a detached, two-story, 4-bedroom home with either a tobacco cigarette or a marijuana joint fully smoked in the home's living room. The master bedroom's door was closed, and the other bedroom doors were open, as was the custom of occupants of this residence. In two experiments with a Marlboro tobacco cigarette smoked by a machine in the living room, the 5-hour mean PM2.5 concentrations in 9 rooms of the home were 15.2 µg/m3 (SD 5.6 µg/m3) and 15.0 µg/m3 (SD 3.7 µg/m3). In contrast, three experiments with pre-rolled marijuana joints smoked in the same manner in the living room produced 5-hour mean PM2.5 concentrations of 38.9 µg/m3 (SD 10.6 µg/m3), 79.8 µg/m3 (SD 25.7 µg/m3) and 80.7 µg/m3 (SD 28.8 µg/m3). In summary, the average secondhand PM2.5 concentrations from smoking a marijuana joint in the home were found to be 4.4 times as great as the secondhand PM2.5 concentrations from smoking a tobacco cigarette. Opening 3 windows by 12.7 cm reduced the high PM2.5 concentrations from marijuana smoking by 67 %, but the PM2.5 levels still exceeded those produced by tobacco smoking with the windows closed.