Indoor secondary organic aerosols: Towards an improved representation of their formation and composition in models.

The formation of secondary organic aerosol (SOA) indoors is one of the many consequences of the rich and complex chemistry that occurs therein. Given particulate matter has well documented health effects, we need to understand the mechanism for SOA formation indoors and its resulting composition. This study evaluates some uncertainties that exist in quantifying gas-to-particle partitioning of SOA-forming compounds using an indoor detailed chemical model. In particular, we investigate the impacts of using different methods to estimate compound vapour pressures as well as simulating the formation of highly oxygenated organic molecules (HOM) via auto-oxidation on SOA formation indoors. Estimation of vapour pressures for 136 α-pinene oxidation species by six investigated methods led to standard deviations of 28-216%. Inclusion of HOM formation improved model performance across three of the six assessed vapour pressure estimation methods when comparing against experimental data, particularly when the NO2 concentration was relatively high. We also explored the predicted SOA composition using two product classification methods, the first assuming the molecule is dominated by one functionality according to its name, and the second accounting for the fractional weighting of each functional group within a molecule. The SOA composition was dominated by the HOM species when the NO2-to-α-terpineol ratio was high for both product classification methods, as these conditions promoted formation of the nitrate radical and hence formation of HOM monomers. As the NO2-to-α-terpineol ratio decreased, peroxides and acids dominated the simple classification, whereas for the fractional classification, carbonyl and alcohol groups became more important.

Outcome-based ventilation: A framework for assessing performance, health, and energy impacts to inform office building ventilation decisions.

This article presents an outcome-based ventilation (OBV) framework, which combines competing ventilation impacts into a monetized loss function ($/occ/h) used to inform ventilation rate decisions. The OBV framework, developed for U.S. offices, considers six outcomes of increasing ventilation: profitable outcomes realized from improvements in occupant work performance and sick leave absenteeism; health outcomes from occupant exposure to outdoor fine particles and ozone; and energy outcomes from electricity and natural gas usage. We used the literature to set low, medium, and high reference values for OBV loss function parameters, and evaluated the framework and outcome-based ventilation rates using a simulated U.S. office stock dataset and a case study in New York City. With parameters for all outcomes set at medium values derived from literature-based central estimates, higher ventilation rates' profitable benefits dominated negative health and energy impacts, and the OBV framework suggested ventilation should be ≥45 L/s/occ, much higher than the baseline ~8.5 L/s/occ rate prescribed by ASHRAE 62.1. Only when combining very low parameter estimates for profitable impacts with very high ones for health and energy impacts were all outcomes on the same order. Even then, however, outcome-based ventilation rates were often twice the baseline rate or more.

Reactive indoor air chemistry and health-A workshop summary.

The chemical composition of indoor air changes due to the reactive nature of the indoor environment. Historically, only the stable parent compounds were investigated due to their ease of measurement by conventional methods. Today, however, scientists can better characterize oxidation products (gas and particulate-phase) formed by indoor chemistry. An understanding of occupant exposure can be developed through the investigation of indoor oxidants, the use of derivatization techniques, atmospheric pressure detection, the development of real-time technologies, and improved complex modeling techniques. Moreover, the connection between exposure and health effects is now receiving more attention from the research community. Nevertheless, a need still exists for improved understanding of the possible link between indoor air chemistry and observed acute or chronic health effects and long-term effects such as work-related asthma.

Airborne particles in indoor environment of homes, schools, offices and aged care facilities: The main routes of exposure.

It has been shown that the exposure to airborne particulate matter is one of the most significant environmental risks people face. Since indoor environment is where people spend the majority of time, in order to protect against this risk, the origin of the particles needs to be understood: do they come from indoor, outdoor sources or both? Further, this question needs to be answered separately for each of the PM mass/number size fractions, as they originate from different sources. Numerous studies have been conducted for specific indoor environments or under specific setting. Here our aim was to go beyond the specifics of individual studies, and to explore, based on pooled data from the literature, whether there are generalizable trends in routes of exposure at homes, schools and day cares, offices and aged care facilities. To do this, we quantified the overall 24h and occupancy weighted means of PM10, PM2.5 and PN - particle number concentration. Based on this, we developed a summary of the indoor versus outdoor origin of indoor particles and compared the means to the WHO guidelines (for PM10 and PM2.5) and to the typical levels reported for urban environments (PN). We showed that the main origins of particle metrics differ from one type of indoor environment to another. For homes, outdoor air is the main origin of PM10 and PM2.5 but PN originate from indoor sources; for schools and day cares, outdoor air is the source of PN while PM10 and PM2.5 have indoor sources; and for offices, outdoor air is the source of all three particle size fractions. While each individual building is different, leading to differences in exposure and ideally necessitating its own assessment (which is very rarely done), our findings point to the existence of generalizable trends for the main types of indoor environments where people spend time, and therefore to the type of prevention measures which need to be considered in general for these environments.

Real-time transformation of outdoor aerosol components upon transport indoors measured with aerosol mass spectrometry.

Outdoor aerosols are transported indoors, where their component concentrations depend on aerosol size, physiochemical properties, indoor sources and losses, and cross-environment gradients of temperature and relative humidity. We explored these dependencies by measuring real-time outdoor and indoor non-refractory, submicron (PM1 ) aerosol component mass concentrations in a mixed-use laboratory space with an Aerodyne mini-aerosol mass spectrometer (AMS) and black carbon (BC) with an aethalometer. The median indoor/outdoor (I/O) ratios were 0.60 for sulfate, 0.25 for nitrate, 0.52 for ammonium, 0.73 for organics, and 0.61 for BC. Positive matrix factorization (PMF) on organic aerosol data identified hydrocarbon-like (HOA), cooking (COA), and oxygenated (OOA) factors. By assuming sulfate was nonvolatile, lost only by mechanical processes, and without indoor sources, the transformations of other components i due to partitioning changes or indoor sources were parameterized by normalizing their I/O ratios by sulfate's I/O ratio, that is, (I/O)i/SO4 . Component-specific behavior was quantified by regressions of (I/O)i/SO4 to outdoor-to-indoor temperature differences. Nitrate and HOA strongly and OOA weakly showed losses with increasing temperatures indoors vs. outdoors, and HOA likely had an indoor source. To our knowledge, this is the first reported deployment of an AMS to analyze real-time indoor aerosol composition and outdoor-to-indoor transformation.

Perceptions in the U.S. building industry of the benefits and costs of improving indoor air quality.

How building stakeholders (e.g. owners, tenants, operators, and designers) understand impacts of Indoor Air Quality (IAQ) and associated energy costs is unknown. We surveyed 112 stakeholders across the United States to ascertain their perceptions of their current IAQ and estimates of benefits and costs of, as well as willingness to pay for, IAQ improvements. Respondents' perceived IAQ scores correlated with the use of high-efficiency filters but not with any other IAQ-improving technologies. We elicited their estimates of the impacts of a ventilation-filtration upgrade (VFU), that is, doubling the ventilation rate from 20 to 40 cfm/person (9.5 to 19 l/s/person) and upgrading from a minimum efficiency reporting value 6 to 11 filter, and compared responses to estimates derived from IAQ literature and energy modeling. Minorities of respondents thought the VFU would positively impact productivity (45%), absenteeism (23%), or health (39%). Respondents' annual VFU cost estimates (mean = $257, s.d. = $496, median = $75 per person) were much higher than ours (always <$32 per person), and the only yearly cost a plurality of respondents said they would pay for the VFU was $15 per person. Respondents holding green building credentials were not more likely to affirm the IAQ benefits of the VFU and were less likely to be willing to pay for it.

Secondary organic aerosol formation initiated by α-terpineol ozonolysis in indoor air.

Secondary organic aerosol (SOA) owing to reactive organic gas (ROG) ozonolysis can be an important indoor particle source. However, SOA formation owing to ozonolysis of α-terpineol, which is emitted by consumer product usage and reacts strongly with ozone, has not been systematically quantified. Therefore, we conducted 21 experiments to investigate the SOA formation initiated by α-terpineol ozonolysis for high (0.84 h-1 ), moderate (0.61 h-1 ), and low (0.36 h-1 ) air exchange rates (AER), which is the frequency with which indoor is replaced by outdoor air. α-Terpineol concentrations of 6.39 to 226 ppb were combined with high ozone (~25 ppm) to ensure rapid and complete ozonolysis. No reactants were replenished, so SOA peaked quickly and then decreased due to AER and surface losses, and peak SOA ranged from 2.03 to 281 µg/m3 at unit density. SOA mass formation was parameterized with the aerosol mass fraction (AMF), a.k.a. the SOA yield, and AMFs ranged from 0.056 to 0.24. The AMFs strongly and positively correlated with reacted α-terpineol, whereas they weakly and negatively correlated with higher AERs. One-product, two-product, and volatility basis set (VBS) models were fit to the AMF data. Predictive modeling demonstrated that α-terpineol ozonolysis could meaningfully form SOA in indoor air.

Do time-averaged, whole-building, effective volatile organic compound (VOC) emissions depend on the air exchange rate? A statistical analysis of trends for 46 VOCs in U.S. offices.

We used existing data to develop distributions of time-averaged air exchange rates (AER), whole-building 'effective' emission rates of volatile organic compounds (VOC), and other variables for use in Monte Carlo analyses of U.S. offices. With these, we explored whether long-term VOC emission rates were related to the AER over the sector, as has been observed in the short term for some VOCs in single buildings. We fit and compared two statistical models to the data. In the independent emissions model (IEM), emissions were unaffected by other variables, while in the dependent emissions model (DEM), emissions responded to the AER via coupling through a conceptual boundary layer between the air and a lumped emission source. For 20 of 46 VOCs, the DEM was preferable to the IEM and emission rates, though variable, were higher in buildings with higher AERs. Most oxygenated VOCs and some alkanes were well fit by the DEM, while nearly all aromatics and halocarbons were independent. Trends by vapor pressure suggested multiple mechanisms could be involved. The factors of temperature, relative humidity, and building age were almost never associated with effective emission rates. Our findings suggest that effective emissions in real commercial buildings will be difficult to predict from deterministic experiments or models.

Secondary organic aerosol in residences: predicting its fraction of fine particle mass and determinants of formation strength.

UNLABELLED: Indoor secondary organic aerosol (SOA) formation may contribute to particle concentrations within residences, but little systematic work has investigated its magnitude or the determinants of its formation. This work uses a time-averaged modeling approach to predict the indoor SOA mass formed in residences due to the oxidation of 66 reactive organic compounds by ozone or the hydroxyl radical, parameterizing SOA formation with the aerosol mass fraction. Other organic and inorganic aerosols owing to outdoor and indoor sources were also predicted. Model inputs were represented as distributions within a Monte Carlo analysis, so that result distributions and sensitivity of results to inputs could be quantified, using a dataset developed from the study of Relationships between Indoor, Outdoor and Personal Air and other sources. SOA comprised a large amount of indoor organic and total fine particles for a subset of the results (e.g., >47% of indoor organic and >30% of fine aerosol for 10% of the modeled cases), but was often a small fraction. The sensitivity analysis revealed that SOA formation is driven by high terpene emission rates (particularly by d-limonene) and outdoor ozone, along with low air exchange and ozone and particle deposition rates. PRACTICAL IMPLICATIONS: This study predicts that indoor SOA formation can be a substantial fraction of indoor aerosols in residences, for certain combinations of building and reactant parameters. The model herein can predict SOA for risk analyses or be used to design experiments to study indoor SOA formation. The terpene, d-limonene, contributes by far the most to formation, and eliminating this particular compound indoors would be impactful on indoor aerosol concentrations.

Predicting secondary organic aerosol formation from terpenoid ozonolysis with varying yields in indoor environments.

UNLABELLED: The ozonolysis of terpenoids generates secondary organic aerosol (SOA) indoors. Models of varying complexity have been used to predict indoor SOA formation, and many models use the SOA yield, which is the ratio of the mass of produced SOA and the mass of consumed reactive organic gas. For indoor simulations, the SOA yield has been assumed as a constant, even though it depends on the concentration of organic particles in the air, including any formed SOA. We developed two indoor SOA formation models for single terpenoid ozonolysis, with yields that vary with the organic particle concentration. The models have their own strengths and were in agreement with published experiments for d-limonene ozonolysis. Monte Carlo analyses were performed, which simulated different residential and office environments to estimate ranges of SOA concentrations and yields for d-limonene and α-pinene ozonolysis occurring indoors. Results indicate that yields are highly variable indoors and are most influenced by background organic particles for steady-state formation and indoor ozone concentration for transient peak formation. Additionally, a review of ozonolysis yields for indoor-relevant terpenoids in the literature revealed much uncertainty in their values at low concentrations typical of indoors. PRACTICAL IMPLICATIONS: The results in this study suggest important factors that govern indoor secondary organic aerosol (SOA) formation and yields, in typical residential and office spaces. This knowledge informs the development and comparison of control strategies to reduce indoor-generated SOA. The ranges of SOA concentrations predicted indoors allow the quantification of the effects of sorptive interactions of semi-volatile organic compounds or reactive oxygen species with SOA, filter loading owing to SOA formation, and impacts of SOA on health, if links are established.

The effect of an ion generator on indoor air quality in a residential room.

UNLABELLED: Ion generators charge particles with a corona prior to their removal on collector plates or indoor surfaces and also emit ozone, which can react with terpenes to yield secondary organic aerosol, carbonyls, carboxylic acids, and free radicals. This study characterized the indoor air quality implications of operating an ion generator in a 27 m(3) residential room, with four different test room configurations. Two room configurations had carpet overlaying the original flooring of stained/sealed concrete, and for one configuration with and without carpet, a plug-in air freshener was used as a terpene source. Measurements included airborne sampling of particulate matter (0.015-20 µm), terpenes and C(1) -C(4) and C(6) -C(10) aldehydes, ozone concentrations, and air exchange rates. When the heating, ventilating, and air-conditioning system was not operating (room air exchange rate = ∼0.5/h), the use of the ion generator in the presence of the air freshener led to a net increase in ultrafine particles (<0.1 µm). Also, increased concentrations of ozone were observed regardless of air freshener presence, as well as increases in formaldehyde and nonanal, albeit within measurement uncertainty in some cases. Thus, it may be prudent to limit ion generator use indoors until evidence of safety can be ascertained. PRACTICAL IMPLICATIONS: Portable ion generators are intended to clean the air of particles, but they may emit ozone as a byproduct of their operation, which has the potential to degrade indoor air quality. This study showed that under certain conditions in a residential room, the use of a portable ion generator can increase concentrations of ozone and, to a lesser degree, potentially aldehydes. Also, if operated in the presence of a plug-in air freshener that emits terpenes, its use can increase concentrations of secondary organic aerosol in the ultrafine size range.

Particle loading rates for HVAC filters, heat exchangers, and ducts.

UNLABELLED: The rate at which airborne particulate matter deposits onto heating, ventilation, and air-conditioning (HVAC) components is important from both indoor air quality (IAQ) and energy perspectives. This modeling study predicts size-resolved particle mass loading rates for residential and commercial filters, heat exchangers (i.e. coils), and supply and return ducts. A parametric analysis evaluated the impact of different outdoor particle distributions, indoor emission sources, HVAC airflows, filtration efficiencies, coils, and duct system complexities. The median predicted residential and commercial loading rates were 2.97 and 130 g/m(2) month for the filter loading rates, 0.756 and 4.35 g/m(2) month for the coil loading rates, 0.0051 and 1.00 g/month for the supply duct loading rates, and 0.262 g/month for the commercial return duct loading rates. Loading rates are more dependent on outdoor particle distributions, indoor sources, HVAC operation strategy, and filtration than other considered parameters. The results presented herein, once validated, can be used to estimate filter changing and coil cleaning schedules, energy implications of filter and coil loading, and IAQ impacts associated with deposited particles. PRACTICAL IMPLICATIONS: The results in this paper suggest important factors that lead to particle deposition on HVAC components in residential and commercial buildings. This knowledge informs the development and comparison of control strategies to limit particle deposition. The predicted mass loading rates allow for the assessment of pressure drop and indoor air quality consequences that result from particle mass loading onto HVAC system components.