Widespread occurrence of pesticides in low-income housing.

BACKGROUND: Low socioeconomic status (SES) residents living in social housing, which is subsidized by government or government-funded agencies, may have higher exposures to pesticides used in indoor residences since pesticides are applied due to structural deficiencies, poor maintenance, etc. OBJECTIVE: To estimate exposure of residents in low-SES social housing built in the 1970s to legacy and current-use pesticides and to investigate factors related to exposures. METHODS: Twenty-eight particle-phase pesticides were measured in the indoor air of 46 units in seven low-income social housing, multi-unit residential buildings (MURBs) in Toronto, Canada using portable air cleaners deployed for 1 week in 2017. Pesticides analyzed were legacy and current use in the classes: organochlorines, organophosphates, pyrethroids, and strobilurins. RESULTS: At least one pesticide was detected in 89% of the units with detection frequencies (DF) for individual pesticides of up to 50%, including legacy organochlorines and current-use pesticides. Current-use pyrethroids had the highest DF and concentrations, with the highest particle-phase concentration for pyrethrin I at 32,000 pg/m3. Heptachlor, restricted for use in Canada in 1985, had the highest estimated maximum total air (particle plus gas phase) concentration of 443,000 pg/m3. Heptachlor, lindane, endosulfan I, chlorothalonil, allethrin, and permethrin (except in one study) had higher concentrations than those measured in low-income residences reported elsewhere. In addition to the intentional use of pesticides to control pests and their use in building materials and paints, tobacco smoking was significantly correlated with the concentrations of five pesticides used on tobacco crops. The distribution of pesticides with high DF in individual buildings suggested that pest eradication programs by the building management and/or pesticide use by residents were the major sources of measured pesticides. IMPACT: Low-income social housing fills a much-needed demand, but the residences are prone to pest infestation and hence pesticide use. We found exposure to at least 1 of 28 particle-phase pesticides in 89% of all 46 units tested, with the highest DF and concentrations for current-use pyrethroids and long-banned organochlorines (e.g., DDT, heptachlor) due to very high persistence indoors. Also measured were several pesticides not registered for use indoors, e.g., strobilurins used to treat building materials and pesticides used on tobacco crops. These results, which are the first Canadian data for most pesticides indoors, show widespread exposure to numerous pesticides.

Estimating Indoor Pollutant Loss Using Mass Balances and Unsupervised Clustering to Recognize Decays.

Low-cost air quality monitors are increasingly being deployed in various indoor environments. However, data of high temporal resolution from those sensors are often summarized into a single mean value, with information about pollutant dynamics discarded. Further, low-cost sensors often suffer from limitations such as a lack of absolute accuracy and drift over time. There is a growing interest in utilizing data science and machine learning techniques to overcome those limitations and take full advantage of low-cost sensors. In this study, we developed an unsupervised machine learning model for automatically recognizing decay periods from concentration time series data and estimating pollutant loss rates. The model uses k-means and DBSCAN clustering to extract decays and then mass balance equations to estimate loss rates. Applications on data collected from various environments suggest that the CO2 loss rate was consistently lower than the PM2.5 loss rate in the same environment, while both varied spatially and temporally. Further, detailed protocols were established to select optimal model hyperparameters and filter out results with high uncertainty. Overall, this model provides a novel solution to monitoring pollutant removal rates with potentially wide applications such as evaluating filtration and ventilation and characterizing indoor emission sources.

Evaluation of fixed and adaptive concentration thresholds for particle filter systems.

Particle filtration can effectively reduce indoor concentrations of particulate matter (PM) but may incur high energy use. This study evaluates fixed and adaptive concentration thresholds to automate the operation of filtration systems. Simulated environments were derived from week-long continuous PM measurements from Dylos DC1700 (N = 104) and Alphasense OPC-N2 (N = 100) particle counters deployed in apartments in Toronto. A fixed threshold of 4.0 µg·m-3 resulted in a mean air cleaner runtime of 6.9%-21.0% depending on clean air delivery rate (CADR) and particle sensor, while providing mean concentration reductions of 67%-71% compared to operating the air cleaner constantly (runtime = 100%). In most environments, runtime could be further reduced by raising the fixed threshold while resulting in only a modest decrease in absolute and normalized mean exposure reduction. Using an adaptive threshold derived from a k-means clustering approach generally provided substantial exposure reduction while preventing high runtimes. These results were generally insensitive to cleaning power and the monitor used to measure particle concentrations. Reducing the energy usage of particle filter systems will make them a more viable and sustainable means of improving occupant health.

Modeling Clothing as a Vector for Transporting Airborne Particles and Pathogens across Indoor Microenvironments.

Evidence suggests that human exposure to airborne particles and associated contaminants, including respiratory pathogens, can persist beyond a single microenvironment. By accumulating such contaminants from air, clothing may function as a transport vector and source of "secondary exposure". To investigate this function, a novel microenvironmental exposure modeling framework (ABICAM) was developed. This framework was applied to a para-occupational exposure scenario involving the deposition of viable SARS-CoV-2 in respiratory particles (0.5-20 µm) from a primary source onto clothing in a nonhealthcare setting and subsequent resuspension and secondary exposure in a car and home. Variability was assessed through Monte Carlo simulations. The total volume of infectious particles on the occupant's clothing immediately after work was 4800 µm3 (5th-95th percentiles: 870-32 000 µm3). This value was 61% (5-95%: 17-300%) of the occupant's primary inhalation exposure in the workplace while unmasked. By arrival at the occupant's home after a car commute, relatively rapid viral inactivation on cotton clothing had reduced the infectious volume on clothing by 80% (5-95%: 26-99%). Secondary inhalation exposure (after work) was low in the absence of close proximity and physical contact with contaminated clothing. In comparison, the average primary inhalation exposure in the workplace was higher by about 2-3 orders of magnitude. It remains theoretically possible that resuspension and physical contact with contaminated clothing can occasionally transmit SARS-CoV-2 between humans.

Quantitative filter forensics for semivolatile organic compounds in social housing apartments.

Residents from low-income social housing are vulnerable to adverse health effects from indoor air pollution. Particle-bound concentrations of eight phthalates and 12 polycyclic aromatic hydrocarbons (PAHs) in indoor air were measured using quantitative filter forensics with portable air cleaners deployed for three one-week periods from 2015 to 2017. The sample included 143 apartments across seven multi-unit social housing buildings in Toronto, Canada, that went through energy retrofits in 2016. Eight phthalates and six PAHs were found in more than 50% of the apartments in either of the three sampling periods. Di(2-ethylhexyl) phthalate (DEHP) and phenanthrene were the dominant phthalate and PAH, with median concentrations of 146, 143, and 130 ng/m3 and 1.51, 0.58, and 0.76 ng/m3 in the late spring of 2015, and after retrofits in late spring 2017 and winter of 2017, respectively. SVOC concentrations were generally lower after energy retrofits, with significant differences for phenanthrene, fluoranthene, and pyrene. Lower concentrations post-retrofit may be related to less overheating and less need for opening windows. Concentrations of phthalates and PAHs in this study were similar to or higher than those reported in the literature. Results suggest that the use of portable air filters is a promising method to assess concentrations of indoor particle-bound SVOCs.

The impact of emissions from an essential oil diffuser on cognitive performance.

Essential oil products are increasingly used in indoor environments and have been found to negatively contribute to indoor air quality. Moreover, the chemicals and fragrances emitted by those products may affect the central nervous system and cognitive function. This study uses a double-blind between-subject design to investigate the cognitive impact of exposure to the emissions from essential oil used in an ultrasonic diffuser. In a simulated office environment where other environmental parameters were maintained constant, 34 female and 25 male university students were randomly allocated into four essential oil exposure scenarios. The first two scenarios contrast lemon oil to pure deionized water, while the latter two focus on different levels of particulate matter differentiated by HEPA filters with non-scented grapeseed oil as the source. Cognitive function was assessed using a computer-based battery consisting of five objective tests that involve reasoning, response inhabitation, memory, risk-taking, and decision-making. Results show that exposure to essential oil emissions caused shortened reaction time at the cost of significantly worse response inhabitation control and memory sensitivity, indicating potentially more impulsive decision-making. The cognitive responses caused by scented lemon oil and non-scented grapeseed oil were similar, as was the perception of odor pleasantness and intensity.

Indoor exposure to phthalates and polycyclic aromatic hydrocarbons (PAHs) to Canadian children: the Kingston allergy birth cohort.

BACKGROUND: Canadian children are widely exposed to phthalates and polycyclic aromatic hydrocarbons (PAHs) from indoor sources. Both sets of compounds have been implicated in allergic symptoms in children. OBJECTIVE: We characterize concentrations of eight phthalates and 12 PAHs in floor dust from the bedrooms of 79 children enrolled in the Kingston Allergy Birth Cohort (KABC). METHOD: Floor dust was collected from the bedrooms of 79 children who underwent skin prick testing for common allergens after their first birthday. Data were collected on activities, household, and building characteristics via questionnaire. RESULTS: Diisononyl phthalate (DiNP) and phenanthrene were the dominant phthalate and PAH with median concentrations of 561 µg/g and 341 ng/g, respectively. Benzyl butyl phthalate (BzBP) and chrysene had the highest variations among all tested homes, ranging from 1-95% to 1-99%, respectively. SIGNIFICANCE: Some phthalates were significantly associated with product and material use such as diethyl phthalate (DEP) with fragranced products and DiNP and DiDP with vinyl materials. Some PAHs were significantly associated with household characteristics, such as benzo[a]pyrene with smoking, and phenanthrene and fluoranthene with the presence of an attached garage. Socioeconomic status (SES) had positive and negative relationships with some concentrations and some explanatory factors. No significant increases in risk of atopy (positive skin prick test) was found as a function of phthalate or PAH dust concentrations.

Modeling the Removal of Water-Soluble Trace Gases from Indoor Air via Air Conditioner Condensate.

Water-soluble trace gas (WSTG) loss from indoor air via air conditioning (AC) units has been observed in several studies, but these results have been difficult to generalize. In the present study, we designed a box model that can be used to investigate and estimate WSTG removal due to partitioning to AC coil condensate. We compared the model output to measurements of a suite of organic acids cycling in an indoor environment and tested the model by varying the input AC parameters. These tests showed that WSTG loss via AC cycling is influenced by Henry's law constant of the compound in question, which is controlled by air and water temperatures and the condensate pH. Air conditioning unit specifications also impact WSTG loss through variations in the sensible heat ratio, the effective recirculation rate of air through the unit, and the timing of coil and fan operation. These findings have significant implications for indoor modeling. To accurately model the fate of indoor WSTGs, researchers must either measure or otherwise account for these unique environmental and operational characteristics.

Distribution of SARS-CoV-2 RNA signal in a home with COVID-19 positive occupants.

Although many COVID-19 patients isolate and recover at home, the dispersal of SARS-CoV-2 onto surfaces and dust within the home environment remains poorly understood. To investigate the distribution and persistence of SARS-CoV-2 in a home with COVID-19 positive occupants, samples were collected from a household with two confirmed COVID-19 cases (one adult and one child). Home surface swab and dust samples were collected two months after symptom onset (and one month after symptom resolution) in the household. The strength of the SARS-CoV-2 molecular signal in fomites varied as a function of sample location, surface material and cleaning practices. Notably, the SARS-CoV-2 RNA signal was detected at several locations throughout the household although cleaning appears to have attenuated the signal on many surfaces. Of the 24 surfaces sampled, 46% were SARS-CoV-2 positive at the time of sampling. The SARS-CoV-2 concentrations in dust recovered from floor and HVAC filter samples ranged from 104 to 105 N2 gene copies/g dust. While detection of viral RNA does not imply infectivity, this study confirms that the SARS-CoV-2 RNA signal can be detected at several locations within a COVID-19 isolation home and can persist after symptoms have resolved. In addition, the concentration of SARS-CoV-2 (normalized per unit mass of dust) recovered in home HVAC filters may prove useful for estimating SARS-CoV-2 airborne levels in homes. In this work, using the quantitative filter forensics methodology, we estimated an average integrated airborne SARS-CoV-2 concentration of 69 ± 43 copies/m3. This approach can be used to help building scientists and engineers develop best practices in homes with COVID-19 positive occupants.

Volatile organic compound and particulate matter emissions from an ultrasonic essential oil diffuser.

Ultrasonic essential oil diffusers (EODs) are a popular type of indoor scenting source. We performed a chamber study in which we measured the emissions from EODs used with lemon, lavender, eucalyptus, and grapeseed oils. Over the course of 15 min, the most abundant VOCs released from lemon, lavender, eucalyptus, and grapeseed oils were 2.6 ± 0.7 mg of d-limonene, 3.5 ± 0.4 mg of eucalyptol, 1.0 ± 0.1 mg of linalyl acetate, and 0.2 ± 0.02 mg of linalyl acetate, respectively. Each oil had a unique particulate matter (PM) emission profile in terms of size, number density, and rate. The dominant size ranges of the PM were 10-100 nm for lemon oil, 50-100 nm for lavender oil, 10-50 nm for lemon oil, and above 200 nm for grapeseed oil. PM1 emission rates of approximately 2 mg/h, 0.1 mg/h, and 3 mg/h, were observed for lemon, lavender/eucalyptus, and grapeseed oils, respectively. A fivefold increase in PM1 emission was measured when the EOD with eucalyptus oil was filled with tap water as opposed to deionized water. Modeling suggests that reasonable use cases of EODs can contribute substantially to primary and secondary PM in indoor environments, but this potential varies depending on the oil and water types used.

HVAC filtration of particles and trace metals: Airborne measurements and the evaluation of quantitative filter forensics.

Filters installed in the heating, ventilation, and air-conditioning (HVAC) systems can serve as air-cleaning and sampling devices for indoor particles. The purpose of this article is to evaluate these dual roles. An occupied home with a central HVAC system equipped with a Minimum Efficiency Reporting Value (MERV, from ASHRAE Standard 52.2) 11 filter was monitored for six weeks. Weekly airborne gravimetric and real-time sampling was performed to measure the particle size distribution and the concentration of total suspended particles (TSP), PM10, PM2.5, PM1, and 12 trace metals. The weekly system runtimes were intentionally changed to provide a wide range of weekly filtration volumes. The quantitative filter forensics (QFF) concentrations of particulate matter (PM) and trace metals were calculated using the analysis of the dust collected on the HVAC filter, the filtration volume, and filter in-situ efficiency. The results indicated that filtration was not influential to remove PM and trace metals as the concentrations during the weeks with continuous HVAC operation were not consistently lower than those during the other weeks. This suggests the dominance of other particle and trace metal source and loss mechanisms weakens the influence of filtration in this home. The QFF evaluation results indicated that the concentration of TSP and over half of the tested trace metals (e.g., Pb, Cd, Ni, V, Sb, K, and Sr) could be estimated by QFF within a factor of two when compared to airborne sampling results. PM10, PM2.5, and PM1 concentrations were significantly underestimated by QFF potentially due to the limitations of size distribution analysis by a laser diffraction particle sizer (LDPS) for the detection of <1 µm particles. Overall, while QFF was promising for TSP and some trace metals, improvement in size distribution analysis could extend the application of QFF for airborne sampling.

Quantitative filter forensics: Size distribution and particulate matter concentrations in residential buildings.

We applied filter forensics, the analysis of dust from the heating, ventilation, and air-conditioning (HVAC) filters, to measure particle size distribution in 21 residences in Toronto, Canada over a year. Four filters with different nominal efficiencies (Minimum Efficiency Reporting Value (MERV) 8-14 from ASHRAE Standard 52.2) were deployed in each residence each for three months, while the effective filtration volumes (the product of flow rate, runtime, and in-situ filter efficiency) were characterized over each filter lifetime. Using extraction and laser diffraction, we found that approximately 90% of the volumetric distributions were >10 µm and the volume median diameter (VMD) ranged from 23.4 to 75.1 µm. Using quantitative filter forensics (QFF), total suspended particle (TSP) concentrations ranged from 2.9 to 823.7 µg/m3 (median = 89.8 µg/m3 ) with a moderate correlation with the content of TSP on the filters (in terms of g) and with the TSP effective filtration volume (m3 ) indicating the importance of both filter forensics and HVAC metadata parameters to QFF concentration estimates. There was no strong correlation between PM10 or PM2.5 concentrations and hourly airborne particle number concentrations measured by low-cost sensors suggesting an evaluation of QFF is warranted, particularly for the exploration of smaller particles.

Indoor CO2 concentrations and cognitive function: A critical review.

Poor indoor air quality indicated by elevated indoor CO2 concentrations has been linked with impaired cognitive function, yet current findings of the cognitive impact of CO2 are inconsistent. This review summarizes the results from 37 experimental studies that conducted objective cognitive tests with manipulated CO2 concentrations, either through adding pure CO2 or adjusting ventilation rates (the latter also affects other indoor pollutants). Studies with varied designs suggested that both approaches can affect multiple cognitive functions. In a subset of studies that meet objective criteria for strength and consistency, pure CO2 at a concentration common in indoor environments was only found to affect high-level decision-making measured by the Strategic Management Simulation battery in non-specialized populations, while lower ventilation and accumulation of indoor pollutants, including CO2 , could reduce the speed of various functions but leave accuracy unaffected. Major confounding factors include variations in cognitive assessment methods, study designs, individual and populational differences in subjects, and uncertainties in exposure doses. Accordingly, future research is suggested to adopt direct air delivery for precise control of CO2 inhalation, include brain imaging techniques to better understand the underlying mechanisms that link CO2 and cognitive function, and explore the potential interaction between CO2 and other environmental stimuli.

Modeling microbial growth in carpet dust exposed to diurnal variations in relative humidity using the "Time-of-Wetness" framework.

Resuspension of microbes in floor dust and subsequent inhalation by human occupants is an important source of human microbial exposure. Microbes in carpet dust grow at elevated levels of relative humidity, but rates of this growth are not well established, especially under changing conditions. The goal of this study was to model fungal growth in carpet dust based on indoor diurnal variations in relative humidity utilizing the time-of-wetness framework. A chamber study was conducted on carpet and dust collected from 19 homes in Ohio, USA and exposed to varying moisture conditions of 50%, 85%, and 100% relative humidity. Fungal growth followed the two activation regime model, while bacterial growth could not be evaluated using the framework. Collection site was a stronger driver of species composition (P = 0.001, R2  = 0.461) than moisture conditions (P = 0.001, R2  = 0.021). Maximum moisture condition was associated with species composition within some individual sites (P = 0.001-0.02, R2  = 0.1-0.33). Aspergillus, Penicillium, and Wallemia were common fungal genera found among samples at elevated moisture conditions. These findings can inform future studies of associations between dampness/mold in homes and health outcomes and allow for prediction of microbial growth in the indoor environment.

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 PM2.5 effectiveness of the non-electret filters when compared to electret filters (16% vs. 36%) of the same nominal efficiency (MERV 8). However, median PM2.5 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.

In situ efficiency of filters in residential central HVAC systems.

High-efficiency filtration in residential forced-air heating, ventilation, and air conditioning (HVAC) systems protects equipment and can reduce exposure to particulate matter. Laboratory tests provide a measure of the nominal efficiency, but they may not accurately reflect the in situ efficiency of the filters because of variations in system conditions and changes in filter performance over time. The primary focus of this paper is to evaluate the effective filtration efficiency, which is inclusive of any loading and system impacts, in 21 occupied residential homes through in-duct concentration measurements. We considered the role of filter media by testing both electret and non-electret media, as well as the role of loading by considering new and used filters. The results show that filters with higher nominal efficiency generally had higher effective filtration efficiency in the same home. In terms of performance change, there is no significant difference in efficiency between initial and 3-month non-electret filters, but the efficiency of electret filters generally decreased over time. However, both nominal efficiency and performance change were vastly overshadowed by the wide variety in loading and system conditions across homes, making it hard to predict filter efficiency in a given home without in situ measurements.

Bacterial and fungal ecology on air conditioning cooling coils is influenced by climate and building factors.

The presence of biofilms on the cooling coils of commercial air conditioning (AC) units can significantly reduce the heat transfer efficiency of the coils and may lead to the aerosolization of microbes into occupied spaces of a building. We investigated how climate and AC operation influence the ecology of microbial communities on AC coils. Forty large-scale commercial ACs were considered with representation from warm-humid and hot-dry climates. Both bacterial and fungal ecologies, including richness and taxa, on the cooling coil surfaces were significantly impacted by outdoor climate, through differences in dew point that result in increased moisture (condensate) on coils, and by the minimum efficiency reporting value (MERV 8 vs MERV 14) of building air filters. Based on targeted qPCR and sequence analysis, low efficiency upstream filters (MERV 8) were associated with a greater abundance of pathogenic bacteria and medically relevant fungi. As the implementation of air conditioning continues to grow worldwide, better understanding of the factors impacting microbial growth and ecology on cooling coils should enable more rational approaches for biofilm control and ultimately result in reduced energy consumption and healthier buildings.

Illuminating the dark side of indoor oxidants.

The chemistry of oxidants and their precursors (oxidants*) plays a central role in outdoor environments but its importance in indoor air remains poorly understood. Ozone (O3) chemistry is important in some indoor environments and, until recently, ozone was thought to be the dominant oxidant indoors. There is now evidence that formation of the hydroxyl radical by photolysis of nitrous acid (HONO) and formaldehyde (HCHO) may be important indoors. In the past few years, high time-resolution measurements of oxidants* indoors have become more common and the importance of event-based release of oxidants* during activities such as cleaning has been proposed. Here we review the current understanding of oxidants* indoors, including drivers of the formation and loss of oxidants*, levels of oxidants* in indoor environments, and important directions for future research.

Sources of isocyanic acid (HNCO) indoors: a focus on cigarette smoke.

The sources and sinks of isocyanic acid (HNCO), a toxic gas, in indoor environments are largely uncharacterized. In particular, cigarette smoke has been identified as a significant source. In this study, controlled smoking of tobacco cigarettes was investigated in both an environmental chamber and a residence in Toronto, Canada using an acetate-CIMS. The HNCO emission ratio from side-stream cigarette smoke was determined to be 2.7 (±1.1) × 10-3 ppb HNCO/ppb CO. Side-stream smoke from a single cigarette introduced a large pulse of HNCO to the indoor environment, increasing the HNCO mixing ratio by up to a factor of ten from background conditions of 0.15 ppb. Although there was no evidence for photochemical production of HNCO from cigarette smoke in the residence, it was observed in the environmental chamber via oxidation by the hydroxyl radical (1.1 × 107 molecules per cm3), approximately doubling the HNCO mixing ratio after 30 minutes of oxidation. Oxidation of cigarette smoke by O3 (15 ppb = 4.0 × 1017 molecules per cm3) and photo-reaction with indoor fluorescent lights did not produce HNCO. By studying the temporal profiles of both HNCO and CO after smoking, it is inferred that gas-to-surface partitioning of HNCO acts as an indoor loss pathway. Even in the absence of smoking, the indoor HNCO mixing ratios in the Toronto residence were elevated compared to concurrent outdoor measurements by approximately a factor of two.

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.