Use of real-time light scattering data to estimate the contribution of infiltrated and indoor-generated particles to indoor air

Practical considerations for using low-cost sensors to assess wildfire smoke exposure in school and childcare settings

BACKGROUND

More frequent and intense wildfires will increase concentrations of smoke in schools and childcare settings. Low-cost sensors can assess fine particulate matter (PM2.5) concentrations with high spatial and temporal resolution.

OBJECTIVE

We sought to optimize the use of sensors for decision-making in schools and childcare settings during wildfire smoke to reduce children's exposure to PM2.5.

METHODS

We measured PM2.5 concentrations indoors and outdoors at four schools in Washington State during wildfire smoke in 2020-2021 using low-cost sensors and gravimetric samplers. We randomly sampled 5-min segments of low-cost sensor data to create simulations of brief portable handheld measurements.

RESULTS

During wildfire smoke episodes (lasting 4-19 days), median hourly PM2.5 concentrations at different locations inside a single facility varied by up to 49.6 µg/m3 (maximum difference) during school hours. Median hourly indoor/outdoor ratios across schools ranged from 0.22 to 0.91. Within-school differences in concentrations indicated that it is important to collect measurements throughout a facility. Simulation results suggested that making handheld measurements more often and over multiple days better approximates indoor/outdoor ratios for wildfire smoke. During a period of unstable air quality, PM2.5 over the next hour indoors was more highly correlated with the last 10-min of data (mean R2 = 0.94) compared with the last 3-h (mean R2 = 0.60), indicating that higher temporal resolution data is most informative for decisions about near-term activities indoors.

IMPACT STATEMENT

As wildfires continue to increase in frequency and severity, staff at schools and childcare facilities are increasingly faced with decisions around youth activities, building use, and air filtration needs during wildfire smoke episodes. Staff are increasingly using low-cost sensors for localized outdoor and indoor PM2.5 measurements, but guidance in using and interpreting low-cost sensor data is lacking. This paper provides relevant information applicable for guidance in using low-cost sensors for wildfire smoke response.

Traffic-related air pollution and dementia incidence in the Adult Changes in Thought Study

BACKGROUND

While epidemiologic evidence links higher levels of exposure to fine particulate matter (PM2.5) to decreased cognitive function, fewer studies have investigated links with traffic-related air pollution (TRAP), and none have examined ultrafine particles (UFP, ≤100 nm) and late-life dementia incidence.

OBJECTIVE

To evaluate associations between TRAP exposures (UFP, black carbon [BC], and nitrogen dioxide [NO2]) and late-life dementia incidence.

METHODS

We ascertained dementia incidence in the Seattle-based Adult Changes in Thought (ACT) prospective cohort study (beginning in 1994) and assessed ten-year average TRAP exposures for each participant based on prediction models derived from an extensive mobile monitoring campaign. We applied Cox proportional hazards models to investigate TRAP exposure and dementia incidence using age as the time axis and further adjusting for sex, self-reported race, calendar year, education, socioeconomic status, PM2.5, and APOE genotype. We ran sensitivity analyses where we did not adjust for PM2.5 and other sensitivity and secondary analyses where we adjusted for multiple pollutants, applied alternative exposure models (including total and size-specific UFP), modified the adjustment covariates, used calendar year as the time axis, assessed different exposure periods, dementia subtypes, and others.

RESULTS

We identified 1,041 incident all-cause dementia cases in 4,283 participants over 37,102 person-years of follow-up. We did not find evidence of a greater hazard of late-life dementia incidence with elevated levels of long-term TRAP exposures. The estimated hazard ratio of all-cause dementia was 0.98 (95 % CI: 0.92-1.05) for every 2000 pt/cm3 increment in UFP, 0.95 (0.89-1.01) for every 100 ng/m3 increment in BC, and 0.96 (0.91-1.02) for every 2 ppb increment in NO2. These findings were consistent across sensitivity and secondary analyses.

DISCUSSION

We did not find evidence of a greater hazard of late-life dementia risk with elevated long-term TRAP exposures in this population-based prospective cohort study.

Assessing residential PM2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM2.5). To study PM2.5 spatiotemporal variability in residences, we acquired paired indoor and outdoor PM2.5 measurements at 3,977 residences across the United States totaling >10,000 monitor-years of time-resolved data (10-min resolution) from the PurpleAir network. Time-series analysis and statistical modeling apportioned residential PM2.5 concentrations to outdoor sources (median residential contribution = 52% of total, coefficient of variation = 69%), episodic indoor emission events such as cooking (28%, CV = 210%) and persistent indoor sources (20%, CV = 112%). Residences in the temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time with open windows in milder climates. Likewise, for all climate zones, infiltration factors were highest in summer and lowest in winter, decreasing by approximately half in most climate zones. Large outdoor-indoor temperature differences were associated with lower infiltration factors, suggesting particle losses from active filtration occurred during heating and cooling. Absolute contributions from both outdoor and indoor sources increased during wildfire events. Infiltration factors decreased during periods of high outdoor PM2.5, such as during wildfires, reducing potential exposures from outdoor-origin particles but increasing potential exposures to indoor-origin particles. Time-of-day analysis reveals that episodic emission events are most frequent during mealtimes as well as on holidays (Thanksgiving and Christmas), indicating that cooking-related activities are a strong episodic emission source of indoor PM2.5 in monitored residences.

Air pollution accountability research: Moving from a chain to a web

Air pollution accountability studies examine the relationship(s) between an intervention, regulation, or event and the resulting downstream impacts, if any, on emissions, exposure, and/or health. The sequence of events has been schematically described as an accountability chain. Here, we update the existing framework to capture real-life complexities and to highlight important factors that fall outside the linear chain. This new "accountability web" is intended to convey the intricacies associated with conducting an accountability study to various audiences, including researchers, policy makers, and stakeholders. We also identify data considerations for planning and completing a robust accountability study, including those relevant to novel and innovative air pollution and exposure data. Finally, we present a series of recommendations for the accountability research community that can serve as a guide for the next generation of accountability studies.

Fine particulate matter infiltration at Western Montana residences during wildfire season

BACKGROUND/AIMS

Wildfire air pollution is a growing public health concern as wildfires increase in size, intensity, and duration in the United States. The public is often encouraged to stay indoors during wildfire smoke events to reduce exposure. However, there is limited information on how much wildfire smoke infiltrates indoors at residences and what household/behavioral characteristics contribute to higher infiltration. We assessed fine particulate matter (PM2.5) infiltration into Western Montana residences during wildfire season.

METHODS

We measured continuous outdoor and indoor PM2.5 concentrations from July-October 2022 at 20 residences in Western Montana during wildfire season using low-cost PM2.5 sensors. We used paired outdoor/indoor PM2.5 data from each household to calculate infiltration efficiency (Finf; range 0-1; higher values indicate more outdoor PM2.5 infiltration to the indoor environment) using previously validated methods. Analyses were conducted for all households combined and for various household subgroups.

RESULTS

Median (25th percentile, 75th percentile) daily outdoor PM2.5 at the households was 3.7 μg/m3 (2.1, 7.1) during the entire study period and 29.0 μg/m3 (19.0, 49.4) during a 2-week period in September impacted by wildfire smoke. Median daily indoor PM2.5 at the households was 2.5 μg/m3 (1.3, 5.5) overall and 10.4 μg/m3 (5.6, 21.0) during the wildfire period. Overall Finf was 0.34 (95 % Confidence Interval [95%CI]: 0.33, 0.35) with lower values during the wildfire period (0.32; 95%CI: 0.28, 0.36) versus non-wildfire period (0.39; 95%CI: 0.37, 0.42). Indoor PM2.5 concentrations and Finf varied substantially across household subgroups such as household income, age of the home, presence of air conditioning units, and use of portable air cleaners.

CONCLUSIONS

Indoor PM2.5 was substantially higher during wildfire-impacted periods versus the rest of the study. Indoor PM2.5 and Finf were highly variable across households. Our results highlight potentially modifiable behaviors and characteristics that can be used in targeted intervention strategies.

Assessing Lifetime Cancer Risk Associated with Population Exposure to PM-Bound PAHs and Carcinogenic Metals in Three Mid-Latitude Metropolitan Cities

Lifetime cancer risk characterization of ambient PM-bound carcinogenic metals and polycyclic aromatic hydrocarbons (PAHs) were examined in the cities of Los Angeles (USA), Thessaloniki (Greece) and Milan (Italy), which share similar Mediterranean climates but are different in their urban emission sources and governing air quality regulations. The samples in Milan and Thessaloniki were mostly dominated by biomass burning activities whereas the particles collected in Los Angeles were primary impacted by traffic emissions. We analyzed the ambient PM2.5 mass concentration of Cadmium (Cd), Hexavalent Chromium (Cr(VI)), Nickel (Ni), Lead (Pb), as well as 13 PAH compounds in the PM samples, collected during both cold and warm periods at each location. Pb exhibited the highest annual average concentration in all three cities, followed by Ni, As, Cr(VI), Cd and PAHs, respectively. The cancer risk assessment based on outdoor pollutants was performed based on three different scenarios, with each scenario corresponding to a different level of infiltration of outdoor pollutants into the indoor environment. Thessaloniki exhibited a high risk associated with lifetime inhalation of As, Cr(VI), and PAHs, with values in the range of (0.97-1.57) × 10-6, (1.80-2.91) × 10-6, and (0.77-1.25) × 10-6, respectively. The highest cancer risk values were calculated in Milan, exceeding the US EPA standard by a considerable margin, where the lifetime risk values of exposure to As, Cr(VI), and PAHs were in the range of (1.29-2.08) × 10-6, (6.08-9.82) × 10-6, and (1.10-1.77) × 10-6, respectively. In contrast, the estimated risks associated with PAHs and metals, except Cr(VI), in Los Angeles were extremely lower than the guideline value, even when the infiltration factor was assumed to be at peak. The lifetime cancer risk values associated with As, Cd, Ni, Pb, and PAHs in Los Angeles were in the range of (0.04-0.33) × 10-6. This observation highlights the impact of local air quality measures in improving the air quality and lowering the cancer risks in Los Angeles compared to the other two cities.

The infiltration of wildfire smoke and its potential dose on pregnant women: Lessons learned from Indonesia wildfires in 2019

The occurrence of wildfires in Indonesia is prevalent during drought seasons. Multiple toxic pollutants emitted from wildfires have deleterious effects on pregnant women. However, the evidence for these on pregnant women was underreported. The study conducted 24-h monitoring of fine particulate matter (PM2.5) concentrations indoors and outdoors in 9 low-income homes in Palangka Raya during the 2019 wildfire season and 6 low-income homes during the 2019 non-wildfire season. A hundred and seventy pregnant women had their PM exposure assessed between July and October 2019 using personal monitors. It was observed that outdoor air pollutant levels were greater than those found indoors without indoor sources. The findings indicate that indoor PM2.5 concentrations were modestly increased by 1.2 times higher than outdoor, suggesting that buildings only partially protected people from exposure during wildfires. The concentrations of PM2.5 were found to be comparatively higher indoors in residential buildings with wood material than in brick houses. The study findings indicate that 8 out of 12 brick houses exhibited a notable RI/O24 h of less than 1 during the wildfires, whereas all I/O24 h ratios during the non-wildfire season were >1, suggesting the influence of indoor sources. Based on the estimation of daily PM2.5 dose, pregnant women received around 21% of their total daily dose during sedentary activity involving cooking. The present research offers empirical support for the view that indoor air quality in low-income households is affected by a complex combination of factors, including wildfire smoke, air tightness, and occupant behaviour. Also, this situation is more likely a potential risk to pregnant women being exposed to wildfire smoke.

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.

Uncertainty and sensitivity analyses for the reduction factor of sheltering for radiation exposures

Sheltering is one of the countermeasures used to mitigate radiation exposure during nuclear power plant accidents. The effectiveness of sheltering for inhalation exposure is often expressed by the reduction factor, which is defined as the ratio of the indoor to the outdoor cumulative radioactivity concentrations or doses. The indoor concentration is mainly controlled by the air exchange rate, penetration factor, and indoor deposition rate. Meanwhile, the air exchange rate depends on surrounding environmental conditions: the wind speed, leakage area normalised by the floor area of the house, and gross building coverage ratio. In this study, the ranges of the uncertainty of the reduction factors for particles and iodine in reactive gas form were investigated under various environmental conditions, and sensitivity analyses were conducted to understand the parameter with the most influence on the uncertainty of the reduction factor. From the results of the uncertainty analyses, the calculated reduction factor was highly variable depending on the environmental condition and the airtightness of the houses. The median and 95th percentile of the reduction factors for the older houses were 0.5 and 0.9 for particles and 0.07 and 0.4 for iodine in reactive gas form, respectively and these ranges were smaller for newer houses. From the results of the sensitivity analyses, the wind speed was the most influential parameter determining the reduction factor. Additionally, the wind speed was less influential for the reduction factor in newer houses.

Partitioning indoor-generated and outdoor-generated PM2.5 from real-time residential measurements in urban and peri-urban Beijing

Limited number of projects have attempted to partition and quantify indoor- and outdoor-generated PM_2.5 (PM_2.5^ig and PM_2.5^og) where strong indoor sources (e.g., solid fuel, tobacco smoke, or kerosene) exist. This study aimed to apply and refine a previous recursive model used to derive infiltration efficiency (F_inf) to additionally partition pollution concentrations into indoor and outdoor origins within residences challenged by elevated ambient and indoor combustion-related sources. During the winter of 2016 and summer of 2017 we collected residential measurements in 72 homes in urban and peri-urban Beijing, 12 of which had additional paired residential outdoor measurements during the summer season. Local ambient measurements were collected throughout. We then compared the calculated PM_2.5^ig and using (i) outdoor and (ii) ambient measurements as model inputs. The results from outdoor and ambient measurements were not significantly different, which suggests that ambient measurements can be used as a model input for pollution origin partitioning when paired outdoor measurements are not available. From the results calculated using ambient measurements, the mean percentage contribution of indoor-generated PM_2.5 was 19 % (σ = 22 %), and 7 % (11 %) of the total indoor PM_2.5 for peri-urban and urban homes respectively during the winter; and 18 % (18 %) and 6 % (10 %) of the total indoor PM_2.5 during the summer. Partitioning pollution into PM_2.5^ig and PM_2.5^og is important to allow investigation of distinct associations between health outcomes and particulate mixes, often with different physiochemical composition and toxicity. It will also inform targeted interventions that impact indoor and outdoor sources of pollution (e.g., domestic fuel switching vs. power generation), which are typically radically different in design and implementation.

The impact of climate change on the risk factors for tuberculosis: A systematic review

BACKGROUND

Tuberculosis (TB) continues to pose a major public health risk in many countries. The current incidence of disease exceeds guidelines proposed by the World Health Organisation and United Nations. Whilst the relationship between climate change and TB has surfaced in recent literature, it remains neglected in global agendas. There is a need to acknowledge TB as a climate-sensitive disease to facilitate its eradication.

OBJECTIVE

To review epidemiological and prediction model studies that explore how climate change may affect the risk factors for TB, as outlined in the Global Tuberculosis Report 2021: HIV infection, diabetes mellitus, undernutrition, overcrowding, poverty, and indoor air pollution.

METHODS

We conducted a systematic literature search of PubMed, Embase, and Scopus databases to identify studies examining the association between climate variables and the risk factors for TB. Each study that satisfied the inclusion criteria was assessed for quality and ethics. Studies then underwent vote-counting and were categorised based on whether an association was found.

RESULTS

53 studies met inclusion criteria and were included in our review. Vote-counting revealed that two out of two studies found a positive association between the examined climate change proxy and HIV, nine out of twelve studies for diabetes, eight out of seventeen studies for undernutrition, four out of five studies for overcrowding, twelve out of fifteen studies for poverty and one out of three studies for indoor air pollution.

DISCUSSION

We found evidence supporting a positive association between climate change and each of the discussed risk factors for TB, excluding indoor air pollution. Our findings suggest that climate change is likely to affect the susceptibility of individuals to TB by increasing the prevalence of its underlying risk factors, particularly in developing countries. This is an evolving field of research that requires further attention in the scientific community.

Indoor Air Quality Considerations for Laboratory Animals in Wildfire-Impacted Regions-A Pilot Study

Wildfire events are increasing across the globe. The smoke generated as a result of this changing fire landscape is potentially more toxic than air pollution from other ambient sources, according to recent studies. This is especially concerning for populations of humans or animals that live downwind of areas that burn frequently, given that ambient exposure to wildfire smoke cannot be easily eliminated. We hypothesized that a significant indoor air pollution risk existed for laboratory animal facilities located proximal to fire-prone areas. Here, we measured real time continuous outdoor and indoor air quality for 28 days at a laboratory animal facility located in the Rocky Mountain region. We demonstrated that during a wildfire event, the indoor air quality of this animal facility is influenced by ambient smoke events. The daily average indoor fine particulate matter value in an animal room exceeded the Environmental Protection Agency's ambient annual standard 14% of the time and exceeded the World Health Organization's ambient annual guideline 71% of the time. We further show that specialized cage filtration systems are capable of mitigating air pollution penetrance and could improve an animal's microenvironment. The potential effects for laboratory animal physiology that occur in response to the exposure levels and durations measured in this study remain to be determined; yet, even acute wildfire exposure events have been previously correlated with significant differences in gene regulatory and metabolic processes in vivo. We believe these findings warrant consideration for indoor laboratory animal facility air quality monitoring and development of smoke exposure prevention and response protocols, especially among facilities located downwind of fire-prone landscapes.

Outdoor and indoor fine particulate matter at skilled nursing facilities in the western United States during wildfire and non-wildfire seasons

Wildfire activity is increasing in parts of the world where extreme drought and warming temperatures contribute to fireprone conditions, including the western United States. The elderly are among the most vulnerable, and those in long-term care with preexisting conditions have added risk for adverse health outcomes from wildfire smoke exposure. In this study, we report continuous co-located indoor and outdoor fine particulate matter (PM_2.5 ) measurements at four skilled nursing facilities in the western United States. Throughout the year 2020, over 8000 h of data were collected, which amounted to approximately 300 days of indoor and outdoor sampling at each facility. The highest indoor 24 h average PM_2.5 recorded at each facility was 43.6 µg/m³ , 103.2 µg/m³ , 35.4 µg/m³ , and 202.5 µg/m³ , and these peaks occurred during the wildfire season. The indoor-to-outdoor PM_2.5 ratio and calculated infiltration efficiencies indicated high variation in the impact of wildfire events on Indoor Air Quality between the four facilities. Notably, infiltration efficiency ranged from 0.22 to 0.76 across the four facilities. We propose that this variability is evidence that PM_2.5 infiltration may be impacted by modifiable building characteristics and human behavioral factors, and this should be addressed in future studies.

Identifying the contribution of charge effects to airborne transmission of aerosols in confined spaces

Aerosols in indoor air have various adverse effects on human health. Considering the use of forced ventilation and fan mixing (individually and in combination), the variation in charge number and their effects on aerosol transmission in confined spaces were explored in this study with the distinction of particle sources. In the case of sources originating from the external space, natural penetration acquires a greater number of negative charges. Forced ventilation of a confined space acts on the fate of particles in the neighboring confined space, while the internal fan has a negligible effect on both the number concentration and charge number of particles in the exterior. The combination of forced ventilation and fan mixing increases charge numbers, altering the lifetime of particles in the external regional environment by deposition or adsorption, particularly for neutralized particles. In the case of sources originating from the interior area, application of an internal fan weakens the ventilation effect from forced ventilation, resulting in internal particle loss by depositing on internal surfaces due to electrostatic charge, increasing the potential risk of resuspension. Additionally, source origin is associated with particle fate, and the charge generated under the action of external forces contributes to the transmission pathways and the fate of the particles in the air. This study investigates the transmission pathways and the fate of aerosols from the perspective of charge number, hopefully contributing to an in-depth understanding of the transmission mechanisms of toxic substances in confined spaces with aerosols as carriers.

Reductions in particulate matter concentrations resulting from air filtration: A randomized sham-controlled crossover study

One-hundred seventy-two households were recruited from regions with high outdoor air pollution (Fresno and Riverside, CA) to participate in a randomized, sham-controlled, cross-over study to determine the effectiveness of high-efficiency air filtration to reduce indoor particle exposures. In 129 households, stand-alone HEPA air cleaners were placed in a bedroom and in the main living area. In 43 households, high-efficiency MERV 16 filters were installed in central forced-air heating and cooling systems and the participating households were asked to run the system on a clean-air cycle for 15 min per hour. Participating households that completed the study received true air filtration for a year and sham air filtration for a year. Air pollution samples were collected at approximately 6-month intervals, with two measurements in each of the sham and true filtration periods. One week indoor and outdoor time-integrated samples were collected for measurement of PM2.5 , PM10 , and ultrafine particulate matter (UFP) measured as PM0.2 . Reflectance measurements were also made on the PM2.5 filters to estimate black carbon. True filtration significantly improved indoor air quality, with a 48% reduction in the geometric mean indoor PM0.2 and PM2.5 concentrations, and a 31% reduction in PM10 . Geometric mean concentrations of indoor/outdoor reflectance values, indicating fraction of particles of outdoor origin remaining indoors, decreased by 77%. Improvements in particle concentrations were greater with continuously operating stand-alone air cleaners than with intermittent central system filtration. Keeping windows closed and increased utilization of the filtration systems further improved indoor air quality.

Traffic exposure, air pollution and children's physical activity at early childhood education and care

BACKGROUND

A significant number of children attend Early Childhood Education and Care (ECEC). ECEC is an important environment and behaviour setting for young children. Time spent outdoors is positively associated with children's physical activity levels, yet increased time spent physically active outdoors may expose young children to traffic-related air pollution, particularly in ECEC centres located in high traffic areas.

METHODS

This study was part of the Play Spaces and Environments for Children's Physical Activity (PLAYCE) study, Perth, Western Australia. Data from 22 ECEC centres and 478 children were collected. Continuous measures of indoor and outdoor fine particulate matter (PM_2.5) were conducted for 48-72 h in each ECEC. Children wore ActiGraph GT3X + accelerometers to measure their physical activity at ECEC. The total length of high traffic roads within a 300m road network service area buffer around each ECEC was used to identify high and low traffic centres.

RESULTS

Outdoor PM_2.5 concentrations peaked in the afternoon (1pm, 2pm and 6pm) at ECEC centres. Outdoor and indoor PM_2.5 concentrations were significantly higher for centres located in high compared with low traffic areas (both p < 0.05). There was no significant association between a centre being located in a high or low traffic area and the time preschoolers spent outdoors or their physical activity levels.

DISCUSSION

Time periods when air pollution concentrations in ECECs are highest correspond with times when preschoolers are likely to be physically active outdoors. Children's potential exposure to traffic-related air pollutants is occurring during a period of rapid lung development. Given there is no evidence of a safe level of exposure to PM_2.5 or a threshold below which no adverse health effects occur, careful planning should be a consideration to avoid locating ECEC centres in high traffic areas.

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants' window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5  monitoring using low-cost light-scattering sensors.

Using Low-Cost Sensors to Assess Fine Particulate Matter Infiltration (PM2.5) during a Wildfire Smoke Episode at a Large Inpatient Healthcare Facility

Wildfire smoke exposure is associated with a range of acute health outcomes, which can be more severe in individuals with underlying health conditions. Currently, there is limited information on the susceptibility of healthcare facilities to smoke infiltration. As part of a larger study to address this gap, a rehabilitation facility in Vancouver, Canada was outfitted with one outdoor and seven indoor low-cost fine particulate matter (PM_2.5) sensors in Air Quality Eggs (EGG) during the summer of 2020. Raw measurements were calibrated using temperature, relative humidity, and dew point derived from the EGG data. The infiltration coefficient was quantified using a distributed lag model. Indoor concentrations during the smoke episode were elevated throughout the building, though non-uniformly. After censoring indoor-only peaks, the average infiltration coefficient (range) during typical days was 0.32 (0.22–0.39), compared with 0.37 (0.31–0.47) during the smoke episode, a 19% increase on average. Indoor PM_2.5 concentrations quickly reflected outdoor conditions during and after the smoke episode. It is unclear whether these results will be generalizable to other years due to COVID-related changes to building operations, but some of the safety protocols may offer valuable lessons for future wildfire seasons. For example, points of building entry and exit were reduced from eight to two during the pandemic, which likely helped to protect the building from wildfire smoke infiltration. Overall, these results demonstrate the utility of indoor low-cost sensors in understanding the impacts of extreme smoke events on facilities where highly susceptible individuals are present. Furthermore, they highlight the need to employ interventions that enhance indoor air quality in such facilities during smoke events.

Field measurements of PM2.5 infiltration factor and portable air cleaner effectiveness during wildfire episodes in US residences

Wildfires have frequently occurred in the western United States (US) during the summer and fall seasons in recent years. This study measures the PM2.5 infiltration factor in seven residences recruited from five dense communities in Seattle, Washington, during a 2020 wildfire episode and evaluates the impacts of HEPA-based portable air cleaner (PAC) use on reducing indoor PM2.5 levels. All residences with windows closed went through an 18-to-24-h no filtration session, with five of seven following that period with an 18-to-24-h filtration session. Auto-mode PACs, which automatically adjust the fan speed based on the surrounding PM2.5 levels, were used for the filtration session. 10-s resolved indoor PM2.5 levels were measured in each residence's living room, while hourly outdoor levels were collected from the nearest governmental air quality monitoring station to each residence. Additionally, a time-activity diary in minute resolution was collected from each household. With the impacts of indoor sources excluded, indoor PM2.5 mass balance models were developed to estimate the PM2.5 indoor/outdoor (I/O) ratios, PAC effectiveness, and decay-related parameters. Among the seven residences, the mean infiltration factor ranged from 0.33 (standard deviation [SD]: 0.06) to 0.76 (SD: 0.05). The use of auto-mode PAC led to a 48%-78% decrease of indoor PM2.5 levels after adjusting for outdoor PM2.5 levels and indoor sources. The mean (SD) air exchange rates ranged from 0.30 (0.13) h-1 to 1.41 (3.18) h-1 while the PM2.5 deposition rate ranged from 0.10 (0.54) h-1 to 0.49 (0.47) h-1. These findings suggest that staying indoors, a common protective measure during wildfire episodes, is insufficient to prevent people's excess exposure to wildfire smoke, and provides quantitative evidence to support the utilization of auto-mode PACs during wildfire events in the US.

Using Crowd-Sourced Data to Assess the Temporal and Spatial Relationship between Indoor and Outdoor Particulate Matter

Using hourly measures across a full year of crowd-sourced data from over 1000 indoor and outdoor pollution monitors in the state of California, we explore the temporal and spatial relationship between outdoor and indoor particulate matter (PM) concentrations for different particle sizes. The scale of this study offers new insight into both average penetration rates and drivers of heterogeneity in the outdoor-indoor relationship. We find that an increase in the daily outdoor PM concentration of 10% leads to an average increase of 4.2-6.1% in indoor concentrations. The penetration of outdoor particles to the indoor environment occurs rapidly and almost entirely within 5 h. We also provide evidence showing that penetration rates are associated with building age and climatic conditions in the vicinity of the monitor. Since people spend a substantial amount of each day indoors, our findings fill a critical knowledge gap and have significant implications for government policies to improve public health through reductions in exposure to ambient air pollution.

Health Impact Assessment of the 2020 Washington State Wildfire Smoke Episode: Excess Health Burden Attributable to Increased PM2.5 Exposures and Potential Exposure Reductions

Major wildfires starting in the summer of 2020 along the west coast of the United States made PM2.5 concentrations in this region rank among the highest in the world. Washington was impacted both by active wildfires in the state and aged wood smoke transported from fires in Oregon and California. This study aims to estimate the magnitude and disproportionate spatial impacts of increased PM2.5 concentrations attributable to these wildfires on population health. Daily PM2.5 concentrations for each county before and during the 2020 Washington wildfire episode (September 7-19) were obtained from regulatory air monitors. Utilizing previously established concentration-response function (CRF) of PM2.5 (CRF of total PM2.5) and odds ratio (OR) of wildfire smoke days (OR of wildfire smoke days) for mortality, we estimated excess mortality attributable to the increased PM2.5 concentrations in Washington. On average, daily PM2.5 concentrations increased 97.1 μg/m3 during the wildfire smoke episode. With CRF of total PM2.5, the 13-day exposure to wildfire smoke was estimated to lead to 92.2 (95% CI: 0.0, 178.7) more all-cause mortality cases; with OR of wildfire smoke days, 38.4 (95% CI: 0.0, 93.3) increased all-cause mortality cases and 15.1 (95% CI: 0.0, 27.9) increased respiratory mortality cases were attributable to the wildfire smoke episode. The potential impact of avoiding elevated PM2.5 exposures during wildfire events significantly reduced the mortality burden. Because wildfire smoke episodes are likely to impact the Pacific Northwest in future years, continued preparedness and mitigations to reduce exposures to wildfire smoke are necessary to avoid excess health burden.

Automating the interpretation of PM2.5 time-resolved measurements using a data-driven approach

The rapid development of automated measurement equipment enables researchers to collect greater quantities of time-resolved data from indoor and outdoor environments. While significant, the interpretation of the resulting data can be a time-consuming effort. This paper introduces an automated process of interpreting PM_2.5 time-resolved data and differentiating PM_2.5 emissions resulting from indoor and outdoor sources. We use Random Forest (RF), a machine learning approach, to study a dataset of 836 indoor emission events that occurred over a 2-week period in 18 apartments in California. In this paper, we show model development and evaluate its performance as the sample size and source vary. We discuss the characteristics of the dataset that tended to help the source identification and why. For example, we show that data from many events and from different apartments are essential for the model to be suitable for analyzing a new separate dataset. We also show that longitudinal data appear to be more helpful than the time frequency of measurements within a given apartment. We use the resulting RF model to analyze PM_2.5 data of an entirely separate dataset collected from 65 new homes in California. The RF model identifies 442 indoor emission events, with only a few misidentifications.

Performance characteristics of a fan filter unit (FFU) in mitigating particulate matter levels in a naturally ventilated classroom during haze conditions

The performance of a low-cost fan filter unit (FFU) in mitigating hazardous particulate matter (PM) levels in a naturally ventilated school classroom is presented. The FFU can be considered as a simplified mechanical ventilation and air-conditioning system without heating and cooling functions. The FFU improves indoor air quality through introduction of cleaned outdoor air to flush out internally generated heat and moisture and reducing infiltration by maintaining indoor pressurization. Indoor particle number concentrations were reduced between 85% and 95%. The particle removal performance (PRF_FFU ) of the FFU is determined and incorporated into the augmented façade penetration factor (P_aug ). A case-specific recursive dynamic mass balance model is used to characterize the infiltration factor (F_INF ), deposition rate (K), and the penetration efficiency (P_aug ) from continuously monitored indoor and outdoor mass concentration levels. Computed "P_aug " (0.07, 0.09, and 0.13) and "F_INF " (0.06, 0.08, and 0.11), respectively, for PM10, PM2.5, and PM1 suggest that exposure to PM was significantly reduced indoors. The effectiveness of the FFU for reduced "F_INF " and "P_aug " may be attributed to its superior filtration, dilution, and exfiltration mechanisms. In comparison with alternative PM mitigation solutions, the FFU is effective, affordable, and sustainable.

Can Public Spaces Effectively Be Used as Cleaner Indoor Air Shelters during Extreme Smoke Events?

During extreme air pollution events, such as bushfires, public health agencies often recommend that vulnerable individuals visit a nearby public building with central air conditioning to reduce their exposure to smoke. However, there is limited evidence that these "cleaner indoor air shelters" reduce exposure or health risks. We quantified the impact of a "cleaner indoor air shelter" in a public library in Port Macquarie, NSW, Australia when concentrations of fine particulate matter (PM_2.5) were elevated during a local peat fire and nearby bushfires. Specifically, we evaluated the air quality improvements with central air conditioning only and with the use of portable high efficiency particulate air (HEPA) filter air cleaners. We measured PM_2.5 from August 2019 until February 2020 by deploying pairs of low-cost PM_2.5 sensors (i) inside the main library, (ii) in a smaller media room inside the library, (iii) outside the library, and (iv) co-located with regulatory monitors located in the town. We operated two HEPA cleaners in the media room from August until October 2019. We quantified the infiltration efficiency of outdoor PM_2.5 concentrations, defined as the fraction of the outdoor PM_2.5 concentration that penetrates indoors and remains suspended, as well as the additional effect of HEPA cleaners on PM_2.5 concentrations. The infiltration efficiency of outdoor PM_2.5 into the air-conditioned main library was 30%, meaning that compared to the PM_2.5 concentration outdoors, the concentrations of outdoor-generated PM_2.5 indoors were reduced by 70%. In the media room, when the HEPA cleaners were operating, PM_2.5 concentrations were reduced further with a PM_2.5 infiltration efficiency of 17%. A carefully selected air-conditioned public building could be used as a cleaner indoor air shelter during episodes of elevated smoke emissions. Further improvements in indoor air quality within the building can be achieved by operating appropriately sized HEPA cleaners.

Energy consumption of using HEPA-based portable air cleaner in residences: A monitoring study in Seattle, US

Portable air cleaners (PACs), offering both auto and manual (adjustable) operation modes, are commonly used in residences. Compared with adjustable mode, auto mode's advantage of reducing indoor PM2.5 has been previously demonstrated. This study examines the energy consumption of such PACs in six residences recruited in Seattle, United States, and compares the power consumption between auto and adjustable modes. Each residence went through a one-week-long PAC filtration session under auto and adjustable modes, respectively. PAC power consumption, indoor PM2.5, temperature, and relative humidity (RH) were measured at 10-second intervals in each residence. A linear mixed-effects regression (LMER) model was used to compare the PAC power consumption between the two modes after adjusting for indoor PM2.5, temperature, and RH. Results show that the mean (standard deviation) PAC power consumption under adjustable and auto modes were 7.0 (3.5) and 6.8 (2.6) W, respectively. The average monthly energy consumption of continuous PAC operation was estimated to be ~5 kWh for both modes. Based on the LEMR model, PAC power consumption under auto mode was approximately 3% larger than that under adjustable mode, after adjusting for living-room PM2.5, temperature, and RH levels. The implications for PAC operation mode selection in residential environments were discussed.

Indoor air quality in California homes with code-required mechanical ventilation

Data were collected in 70 detached houses built in 2011-2017 in compliance with the mechanical ventilation requirements of California's building energy efficiency standards. Each home was monitored for a 1-week period with windows closed and the central mechanical ventilation system operating. Pollutant measurements included time-resolved fine particulate matter (PM_2.5 ) indoors and outdoors and formaldehyde and carbon dioxide (CO₂ ) indoors. Time-integrated measurements were made for formaldehyde, NO₂ , and nitrogen oxides (NO_X ) indoors and outdoors. Operation of the cooktop, range hood, and other exhaust fans was continuously recorded during the monitoring period. Onetime diagnostic measurements included mechanical airflows and envelope and duct system air leakage. All homes met or were very close to meeting the ventilation requirements. On average, the dwelling unit ventilation fan moved 50% more airflow than the minimum requirement. Pollutant concentrations were similar to or lower than those reported in a 2006-2007 study of California new homes built in 2002-2005. Mean and median indoor concentrations were lower by 44% and 38% for formaldehyde and 44% and 54% for PM_2.5 . Ventilation fans were operating in only 26% of homes when first visited, and the control switches in many homes did not have informative labels as required by building standards.

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.

Impact of Outdoor Air Pollution on Indoor Air Quality in Low-Income Homes during Wildfire Seasons

Indoor and outdoor number concentrations of fine particulate matter (PM2.5), black carbon (BC), carbon monoxide (CO), and nitrogen dioxide (NO2) were monitored continuously for two to seven days in 28 low-income homes in Denver, Colorado, during the 2016 and 2017 wildfire seasons. In the absence of indoor sources, all outdoor pollutant concentrations were higher than indoors except for CO. Results showed that long-range wildfire plumes elevated median indoor PM2.5 concentrations by up to 4.6 times higher than outdoors. BC, CO, and NO2 mass concentrations were higher indoors in homes closer to roadways compared to those further away. Four of the homes with mechanical ventilation systems had 18% higher indoor/outdoor (I/O) ratios of PM2.5 and 4% higher I/O ratios of BC compared to other homes. Homes with exhaust stove hoods had PM2.5 I/O ratios 49% less than the homes with recirculating hoods and 55% less than the homes with no stove hoods installed. Homes with windows open for more than 12 hours a day during sampling had indoor BC 2.4 times higher than homes with windows closed. This study provides evidence that long-range wildfire plumes, road proximity, and occupant behavior have a combined effect on indoor air quality in low-income homes.

Human exposure factors as potential determinants of the heterogeneity in city-specific associations between PM2.5 and mortality

Multi-city population-based epidemiological studies of short-term fine particulate matter (PM_2.5) exposures and mortality have observed heterogeneity in risk estimates between cities. Factors affecting exposures, such as pollutant infiltration, which are not captured by central-site monitoring data, can differ between communities potentially explaining some of this heterogeneity. This analysis evaluates exposure factors as potential determinants of the heterogeneity in 312 core-based statistical areas (CBSA)-specific associations between PM_2.5 and mortality using inverse variance weighted linear regression. Exposure factor variables were created based on data on housing characteristics, commuting patterns, heating fuel usage, and climatic factors from national surveys. When survey data were not available, air conditioning (AC) prevalence was predicted utilizing machine learning techniques. Across all CBSAs, there was a 0.95% (Interquartile range (IQR) of 2.25) increase in non-accidental mortality per 10 µg/m³ increase in PM_2.5 and significant heterogeneity between CBSAs. CBSAs with larger homes, more heating degree days, a higher percentage of home heating with oil had significantly (p < 0.05) higher health effect estimates, while cities with more gas heating had significantly lower health effect estimates. While univariate models did not explain much of heterogeneity in health effect estimates (R² < 1%), multivariate models began to explain some of the observed heterogeneity (R² = 13%).

Is remaining indoors an effective way of reducing exposure to fine particulate matter during biomass burning events?

Bushfires, prescribed burns, and residential wood burning are significant sources of fine particles (aerodynamic diameter <2.5 μm; PM_2.5) affecting the health and well-being of many communities. Despite the lack of evidence, a common public health recommendation is to remain indoors, assuming that the home provides a protective barrier against ambient PM_2.5. The study aimed to assess to what extent houses provide protection against peak concentrations of outdoor PM_2.5 and whether remaining indoors is an effective way of reducing exposure to PM_2.5. The effectiveness of this strategy was evaluated by conducting simultaneous week-long indoor and outdoor measurements of PM_2.5 at 21 residences in regional areas of Victoria, Australia. During smoke plume events, remaining indoors protected residents from peak outdoor PM_2.5 concentrations, but the level of protection was highly variable, ranging from 12% to 76%. Housing stock (e.g., age of the house) and ventilation (e.g., having windows/doors open or closed) played a significant role in the infiltration of outdoor PM_2.5 indoors. The results also showed that leaving windows and doors closed once the smoke plume abates trapped PM_2.5 indoors and increased indoor exposure to PM_2.5. Furthermore, for approximately 50% of households, indoor sources such as cooking activities, smoking, and burning candles or incense contributed significantly to indoor PM_2.5. Implications: Smoke from biomass burning sources can significantly impact on communities. Remaining indoors with windows and doors closed is a common recommendation by health authorities to minimize exposures to peak concentrations of fine particles during smoke plume events. Findings from this study have shown that the protection from fine particles in biomass burning smoke is highly variable among houses, with information on housing age and ventilation status providing an approximate assessment on the protection of a house. Leaving windows closed once a smoke plume abates traps particles indoors and increases exposures.

Different relationships between personal exposure and ambient concentration by particle size

Ambient particulate matter (PM) concentrations at monitoring stations were often used as an indicator of population exposure to PM in epidemiological studies. The correlation between personal exposure and ambient concentrations of PM varied because of diverse time-activity patterns. The aim of this study was to determine the relationship between personal exposure and ambient concentrations of PM₁₀ and PM_2.5 with minimal impact of time-activity pattern on personal exposure. Performance of the MicroPEM, v3.2 was evaluated by collocation with central ambient air monitors for PM₁₀ and PM_2.5. A field technician repeatedly conducted measurement of 24 h personal exposures to PM₁₀ and PM_2.5 with a fixed time-activity pattern of office worker over 26 days in Seoul, Korea. The relationship between the MicroPEM and the ambient air monitor showed good linearity. Personal exposure and ambient concentrations of PM_2.5 were highly correlated with a fixed time-activity pattern compared with PM₁₀. The finding implied a high infiltration rate of PM_2.5 and low infiltration rate of PM₁₀. The relationship between personal exposure and ambient concentrations of PM₁₀ and PM_2.5 was different for high level episodes. In the Asian dust episode, staying indoors could reduce personal exposure to PM₁₀. However, personal exposure to PM_2.5 could not be reduced by staying indoors during the fine dust advisory episode.

A wind tunnel study on the effect of trees on PM2.5 distribution around buildings

Vegetation, especially trees, is effective in reducing the concentration of particulate matter. Trees can efficiently capture particles, improve urban air quality, and may further decrease the introduction of outdoor particles to indoor air. The objective of this study is to investigate the effects of trees on particle distribution and removal around buildings using wind tunnel experiments. The wind tunnel is 18m long, 12m wide, and 3.5m high. Trees were modeled using real cypress branches to mimic trees planted around buildings. At the inlet of the wind tunnel, a "line source" of particles was released, simulating air laden with particulate matter. Experiments with the cypress tree and tree-free models were conducted to compare particle concentrations around the buildings. The results indicate that cypress trees clearly reduce PM_2.5 concentrations compared with the tree-free model. The cypress trees enhanced the PM_2.5 removal rate by about 20%. The effects of trees on PM_2.5 removal and distribution vary at different heights. At the base of the trees, their effect on reducing PM_2.5 concentrations is the most significant. At a great height above the treetops, the effect is almost negligible.

Quantifying fine particle emission events from time-resolved measurements: Method description and application to 18 California low-income apartments

PM_2.5 exposure is associated with significant health risk. Exposures in homes derive from both outdoor and indoor sources, with emissions occurring primarily in discrete events. Data on emission event magnitudes and schedules are needed to support simulation-based studies of exposures and mitigations. This study applied an identification and characterization algorithm to quantify time-resolved PM_2.5 emission events from data collected during 224 days of monitoring in 18 California apartments with low-income residents. We identified and characterized 836 distinct events with median and mean values of 12 and 30 mg emitted mass, 16 and 23 minutes emission duration, 37 and 103 mg/h emission rates, and pseudo-first-order decay rates of 1.3 and 2.0/h. Mean event-averaged concentrations calculated using the determined event characteristics agreed to within 6% of measured values for 14 of the apartments. There were variations in event schedules and emitted mass across homes, with few events overnight and most emissions occurring during late afternoons and evenings. Event characteristics were similar during weekdays and weekends. Emitted mass was positively correlated with number of residents (Spearman coefficient, ρ=.10), bedrooms (ρ=.08), house volume (ρ=.29), and indoor-outdoor CO₂ difference (ρ=.27). The event schedules can be used in probabilistic modeling of PM_2.5 in low-income apartments.

Indoor Air Quality Analysis Using Deep Learning with Sensor Data

Indoor air quality analysis is of interest to understand the abnormal atmospheric phenomena and external factors that affect air quality. By recording and analyzing quality measurements, we are able to observe patterns in the measurements and predict the air quality of near future. We designed a microchip made out of sensors that is capable of periodically recording measurements, and proposed a model that estimates atmospheric changes using deep learning. In addition, we developed an efficient algorithm to determine the optimal observation period for accurate air quality prediction. Experimental results with real-world data demonstrate the feasibility of our approach.

Indoor Air Quality Analysis Using Deep Learning with Sensor Data

Indoor air quality analysis is of interest to understand the abnormal atmospheric phenomena and external factors that affect air quality. By recording and analyzing quality measurements, we are able to observe patterns in the measurements and predict the air quality of near future. We designed a microchip made out of sensors that is capable of periodically recording measurements, and proposed a model that estimates atmospheric changes using deep learning. In addition, we developed an efficient algorithm to determine the optimal observation period for accurate air quality prediction. Experimental results with real-world data demonstrate the feasibility of our approach.

Randomized Trial of Interventions to Improve Childhood Asthma in Homes with Wood-burning Stoves

BACKGROUND

Household air pollution due to biomass combustion for residential heating adversely affects vulnerable populations. Randomized controlled trials to improve indoor air quality in homes of children with asthma are limited, and no such studies have been conducted in homes using wood for heating.

OBJECTIVES

Our aims were to test the hypothesis that household-level interventions, specifically improved-technology wood-burning appliances or air-filtration devices, would improve health measures, in particular Pediatric Asthma Quality of Life Questionnaire (PAQLQ) scores, relative to placebo, among children living with asthma in homes with wood-burning stoves.

METHODS

A three-arm placebo-controlled randomized trial was conducted in homes with wood-burning stoves among children with asthma. Multiple preintervention and postintervention data included PAQLQ (primary outcome), peak expiratory flow (PEF) monitoring, diurnal peak flow variability (dPFV, an indicator of airway hyperreactivity) and indoor particulate matter (PM) PM2.5.

RESULTS

Relative to placebo, neither the air filter nor the woodstove intervention showed improvement in quality-of-life measures. Among the secondary outcomes, dPFV showed a 4.1 percentage point decrease in variability [95% confidence interval (CI)=-7.8 to -0.4] for air-filtration use in comparison with placebo. The air-filter intervention showed a 67% (95% CI: 50% to 77%) reduction in indoor PM2.5, but no change was observed with the improved-technology woodstove intervention.

CONCLUSIONS

Among children with asthma and chronic exposure to woodsmoke, an air-filter intervention that improved indoor air quality did not affect quality-of-life measures. Intent-to-treat analysis did show an improvement in the secondary measure of dPFV.

TRIAL REGISTRATION

ClincialTrials.gov NCT00807183. https://doi.org/10.1289/EHP849.

Measured performance of filtration and ventilation systems for fine and ultrafine particles and ozone in an unoccupied modern California house

This study evaluated nine ventilation and filtration systems in an unoccupied 2006 house located 250 m downwind of the I-80 freeway in Sacramento, California. Systems were evaluated for reducing indoor concentrations of outdoor particles in summer and fall/winter, ozone in summer, and particles from stir-fry cooking. Air exchange rate was measured continuously. Energy use was estimated for year-round operation in California. Exhaust ventilation without enhanced filtration provided indoor PM_2.5 that was 70% lower than outdoors. Supply ventilation with MERV13 filtration provided slightly less protection, whereas supply MERV16 filtration reduced PM_2.5 by 97-98% relative to outdoors. Supply filtration systems used little energy but provided no benefits for indoor-generated particles. Systems with MERV13-16 filter in the recirculating heating and cooling unit (FAU) operating continuously or 20 min/h reduced PM_2.5 by 93-98%. Across all systems, removal percentages were higher for ultrafine particles and lower for black carbon, relative to PM_2.5 . Indoor ozone was 3-4% of outdoors for all systems except an electronic air cleaner that produced ozone. Filtration via the FAU or portable filtration units lowered PM_2.5 by 25-75% when operated over the hour following cooking. The energy for year-round operation of FAU filtration with an efficient blower motor was estimated at 600 kWh/year.

Investigation and modeling of the residential infiltration of fine particulate matter in Beijing, China

The objective of this study was to estimate the residential infiltration factor (Finf) of fine particulate matter (PM_2.5) and to develop models to predict PM_2.5 Finf in Beijing. Eighty-eight paired indoor-outdoor PM_2.5 samples were collected by Teflon filters for seven consecutive days during both non-heating and heating seasons (from a total of 55 families between August, 2013 and February, 2014). The mass concentrations of PM_2.5 were measured by gravimetric method, and elemental concentrations of sulfur in filter deposits were determined by energy-dispersive x-ray fluorescence (ED-XRF) spectrometry. PM_2.5 Finf was estimated as the indoor/outdoor sulfur ratio. Multiple linear regression was used to construct Finf predicting models. The residential PM_2.5 Finf in non-heating season (0.70 ± 0.21, median = 0.78, n = 43) was significantly greater than in heating season (0.54 ± 0.18, median = 0.52, n = 45, p < 0.001). Outdoor temperature, window width, frequency of window opening, and air conditioner use were the most important predictors during non-heating season, which could explain 57% variations across residences, while the outdoor temperature was the only predictor identified in heating season, which could explain 18% variations across residences. The substantial variations of PM_2.5 Finf between seasons and among residences found in this study highlight the importance of incorporating Finf into exposure assessment in epidemiological studies of air pollution and human health in Beijing. The Finf predicting models developed in this study hold promise for incorporating PM_2.5 Finf into large epidemiology studies, thereby reducing exposure misclassification.

IMPLICATIONS

Failure to consider the differences between indoor and outdoor PM_2.5 may contribute to exposure misclassification in epidemiological studies estimating exposure from a central site measurement. This study was conducted in Beijing to investigate residential PM_2.5 infiltration factor and to develop a localized predictive model in both nonheating and heating seasons. High variations of PM_2.5 infiltration factor between the two seasons and across homes within each season were found, highlighting the importance of including infiltration factor in the assessment of exposure to PM_2.5 of outdoor origin in epidemiological studies. Localized predictive models for PM_2.5 infiltration factor were also developed.

Influence of exposure differences on city-to-city heterogeneity in PM2.5-mortality associations in US cities

BACKGROUND

Multi-city population-based epidemiological studies have observed heterogeneity between city-specific fine particulate matter (PM_2.5)-mortality effect estimates. These studies typically use ambient monitoring data as a surrogate for exposure leading to potential exposure misclassification. The level of exposure misclassification can differ by city affecting the observed health effect estimate.

METHODS

The objective of this analysis is to evaluate whether previously developed residential infiltration-based city clusters can explain city-to-city heterogeneity in PM_2.5 mortality risk estimates. In a prior paper 94 cities were clustered based on residential infiltration factors (e.g. home age/size, prevalence of air conditioning (AC)), resulting in 5 clusters. For this analysis, the association between PM_2.5 and all-cause mortality was first determined in 77 cities across the United States for 2001-2005. Next, a second stage analysis was conducted evaluating the influence of cluster assignment on heterogeneity in the risk estimates.

RESULTS

Associations between a 2-day (lag 0-1 days) moving average of PM_2.5 concentrations and non-accidental mortality were determined for each city. Estimated effects ranged from -3.2 to 5.1% with a pooled estimate of 0.33% (95% CI: 0.13, 0.53) increase in mortality per 10 μg/m³ increase in PM_2.5. The second stage analysis determined that cluster assignment was marginally significant in explaining the city-to-city heterogeneity. The health effects estimates in cities with older, smaller homes with less AC (Cluster 1) and cities with newer, smaller homes with a large prevalence of AC (Cluster 3) were significantly lower than the cluster consisting of cities with older, larger homes with a small percentage of AC.

CONCLUSIONS

This is the first study that attempted to examine whether multiple exposure factors could explain the heterogeneity in PM_2.5-mortality associations. The results of this study were found to explain a small portion (6%) of this heterogeneity.

Time-location patterns of a diverse population of older adults: the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

The primary aim of this analysis was to present and describe questionnaire data characterizing time-location patterns of an older, multiethnic population from six American cities. We evaluated the consistency of results from repeated administration of this questionnaire and between this questionnaire and other questionnaires collected from participants of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Participants reported spending most of their time inside their homes (average: 121 h/week or 72%). More than 50% of the participants reported spending no time in several of the location options, including at home outdoors, at work/volunteer/school locations indoors or outdoors, or in "other" locations outdoors. We observed consistency between self-reported time-location patterns from repeated administration of the time-location questionnaire and compared with other survey instruments. Comparisons with national cohorts demonstrated the differences in time-location patterns in the MESA Air cohort due to differences in demographics, but the data showed similar trends in patterns by age, gender, season, and employment status. This study was the first to explicitly examine the time-location patterns in an older, multiethnic population and the first to add data on Chinese participants. These data can be used to inform future epidemiological research of MESA Air and other studies that include diverse populations.

Indoor/outdoor PM2.5 elemental composition and organic fraction medications, in a Greek hospital

In the newly constructed General Hospital of Kavala, Greece, air quality was monitored in two indoor locations (the Triage room at the emergency department and the Laboratory of bio-pathology) and also outdoors. Indoor PM2.5 filter samples were collected at both rooms and outdoors, in the yard of the hospital. PM2.5 organic content and elemental composition were determined. Analyses of selected organic compounds in PM2.5 samples, revealed that chemicals from medications were distributed in the air of the hospital. Qualitatively, dehydrocholic acid, hydrocortisone acetate, gama-bufotalin, syrosingopine, dimethyl phthalate and o,p'-DDT were found in the Triage. In the bio-pathology laboratory, triethoxypentylsilane and carbohydrazide were also found. An unexpected air pollutant pathway was the pneumatic system which delivered the blood samples from the emergency department to the bio-pathology laboratory, as the presence of gama-bufotalin and syrosingopine was found in the aerosol samples from both locations. Indoor PM2.5 24-h average mass concentration ranged from 10.16μgm(-3) to 21.87μgm(-3) in the laboratory and between 9.86μgm(-3) to 26.27μgm(-3) in the Triage room, where the limit value set for human health protection, i.e. 25μgm(-3) for 24h, was exceeded once. The I/O 24-h average PM2.5 mass concentration ratio, ranged from 0.74-1.11 in the Triage and from 0.67-1.07 in the Lab, respectively. On the contrary, the I/O elemental concentration ratios were below unity for the whole campaign, indicating an outdoor origin of the monitored elements (Al, Si, Br, P, S, Na, K, Mg, Ca, Co, Cr, Cu, Fe, Mn, Ni, Pb, Ti and Zn). This finding was also confirmed by high sulfur I/O ratios in both rooms. The diurnal variations of PM2.5, Black Carbon, CO2 concentrations and microclimatic conditions were also monitored.

Use of a Robotic Sampler (PIPER) for Evaluation of Particulate Matter Exposure and Eczema in Preschoolers

While the association of eczema with asthma is well recognized, little research has focused on the potential role of inhalable exposures and eczema. While indoor air quality is important in the development of respiratory disease as children in the U.S. spend the majority of their time indoors, relatively little research has focused on correlated non-respiratory conditions. This study examined the relationship between particulate matter (PM) exposures in preschool age children and major correlates of asthma, such as wheeze and eczema. Air sampling was carried out using a robotic (PIPER) child-sampling surrogate. This study enrolled 128 participants, 57 male and 71 female children. Ages ranged from 3 to 58 months with the mean age of 29.3 months. A comparison of subjects with and without eczema showed a difference in the natural log (ln) of PM collected from the PIPER air sampling (p = 0.049). PIPER's sampling observed an association between the ln PM concentrations and eczema, but not an association with wheezing history in pre-school children. Our findings are consistent with the hypothesis of the role of the microenvironment in mediating atopic dermatitis, which is one of the predictors of persistent asthma. Our findings also support the use of PIPER in its ability to model and sample the microenvironment of young children.

Characterizing the Indoor-Outdoor Relationship of Fine Particulate Matter in Non-Heating Season for Urban Residences in Beijing

OBJECTIVE

Ambient fine particulate matter (PM2.5) pollution is currently a major public health concern in Chinese urban areas. However, PM2.5 exposure primarily occurs indoors. Given such, we conducted this study to characterize the indoor-outdoor relationship of PM2.5 mass concentrations for urban residences in Beijing.

METHODS

In this study, 24-h real-time indoor and ambient PM2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The diurnal variation of pollutant concentrations was characterized. Pearson correlation analysis was used to examine the correlation between indoor and ambient PM2.5 mass concentrations. Regression analysis with ordinary least square was employed to characterize the influences of a variety of factors on PM2.5 mass concentration.

RESULTS

Hourly ambient PM2.5 mass concentrations were 3-280 μg/m3 with a median of 58 μg/m3, and hourly indoor counterpart were 4-193 μg/m3 with a median of 34 μg/m3. The median indoor/ambient ratio of PM2.5 mass concentration was 0.62. The diurnal variation of residential indoor and ambient PM2.5 mass concentrations tracked with each other well. Strong correlation was found between indoor and ambient PM2.5 mass concentrations on the community basis (coefficients: r ≥ 0.90, p < 0.0001), and the ambient data explained ≥ 84% variance of the indoor data. Regression analysis suggested that the variables, such as traffic conditions, indoor smoking activities, indoor cleaning activities, indoor plants and number of occupants, had significant influences on the indoor PM2.5 mass concentrations.

CONCLUSIONS

PM2.5 of ambient origin made dominant contribution to residential indoor PM2.5 exposure in the non-heating season under the high ambient fine particle pollution condition. Nonetheless, the large inter-residence variability of infiltration factor of ambient PM2.5 raised the concern of exposure misclassification when using ambient PM2.5 mass concentrations as exposure surrogates. PM2.5 of indoor origin still had minor influence on indoor PM2.5 mass concentrations, particularly at 11:00-13:00 and 22:00-0:00. The predictive models suggested that particles from traffic emission, secondary aerosols, particles from indoor smoking, resuspended particles due to indoor cleaning and particles related to indoor plants contributed to indoor PM2.5 mass concentrations in this study. Real-time ventilation measurements and improvement of questionnaire design to involve more variables subject to built environment were recommended to enhance the performance of the predictive models.

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.

Estimating mortality derived from indoor exposure to particles of outdoor origin

Following an extensive review of the literature, we further analyze the published data to examine the health effects of indoor exposure to particulate matter (PM) of outdoor origin. We obtained data on all-cause, cardiovascular, and respiratory mortality per 10 μg/m³ increase in outdoor PM₁₀ or PM_2.5; the infiltration factors for buildings; and estimated time spent outdoors by individuals in the United States, Europe, China, and globally. These data were combined log-linear exposure–response model to estimate the all-cause, cardiovascular, and respiratory mortality of exposure to indoor PM pollution of outdoor origin. Indoor PM pollution of outdoor origin is a cause of considerable mortality, accounting for 81% to 89% of the total increase in mortality associated with exposure to outdoor PM pollution for the studied regions. The findings suggest that enhancing the capacity of buildings to protect occupants against exposure to outdoor PM pollution has significant potential to improve public health outcomes.

Indoor particulate matter in rural, wood stove heated homes

Ambient particulate matter (PM) exposures have adverse impacts on public health, but research evaluating indoor PM concentrations in rural homes in the United States using wood as fuel for heating is limited. Our objectives were to characterize indoor PM mass and particle number concentrations (PNCs), quantify infiltration of outdoor PM into the indoor environment, and investigate potential predictors of concentrations and infiltration in 96 homes in the northwestern US and Alaska using wood stoves as the primary source of heating. During two forty-eight hour sampling periods during the pre-intervention winter of a randomized trial, we assessed PM mass (<2.5μm) and PNCs (particles/cm(3)) in six size fractions (0.30-0.49, 0.50-0.99, 1.00-2.49, 2.5-5.0, 5.0-10.0, 10.0+μm). Daily mean (sd) PM2.5 concentrations were 28.8 (28.5)μg/m(3) during the first sampling period and 29.1 (30.1)μg/m(3) during the second period. In repeated measures analyses, household income was inversely associated with PM2.5 and smaller size fraction PNCs, in particular. Time of day was a significant predictor of indoor and outdoor PM2.5 concentrations, and infiltration efficiency was relatively low (Finf (sd)=0.27 (0.20)). Our findings demonstrate relatively high mean PM concentrations in these wood burning homes and suggest potential targets for interventions for improving indoor air quality and health in rural settings.

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.

Size-resolved deposition rates for ultrafine and submicrometer particles in a residential housing unit

We estimated the size-resolved particle deposition rates for the ultrafine and submicrometer particles using a nonlinear regression method with unknown particle background concentrations during nonsourced period following a controlled sourced period in a well-mixed residential environment. A dynamic adjustment method in conjunction with the constant injection of tracer gas was used to maintain the air exchange rate at three target levels across the range of 0.61-1.24 air change per hour (ACH). Particle deposition was found to be highly size dependent with rates ranging from 0.68 ± 0.10 to 5.03 ± 0.20 h(-1) (mean ± s.e.). Our findings also suggest that the effect of air exchange on the particle deposition under enhanced air mixing was relatively small when compared to both the strong influence of size-dependent deposition mechanisms and the effects of mechanical air mixing by fans. Nonetheless, the significant association between air exchange and particle deposition rates for a few size categories indicated potential influence of air exchange on particle deposition. In the future, the proposed approach can be used to explore the separate or composite effects between air exchange and air mixing on particle deposition rates, which will contribute to improved assessment of human exposure to ultrafine and submicrometer particles.

Respiratory risks from household air pollution in low and middle income countries

A third of the world's population uses solid fuel derived from plant material (biomass) or coal for cooking, heating, or lighting. These fuels are smoky, often used in an open fire or simple stove with incomplete combustion, and result in a large amount of household air pollution when smoke is poorly vented. Air pollution is the biggest environmental cause of death worldwide, with household air pollution accounting for about 3·5-4 million deaths every year. Women and children living in severe poverty have the greatest exposures to household air pollution. In this Commission, we review evidence for the association between household air pollution and respiratory infections, respiratory tract cancers, and chronic lung diseases. Respiratory infections (comprising both upper and lower respiratory tract infections with viruses, bacteria, and mycobacteria) have all been associated with exposure to household air pollution. Respiratory tract cancers, including both nasopharyngeal cancer and lung cancer, are strongly associated with pollution from coal burning and further data are needed about other solid fuels. Chronic lung diseases, including chronic obstructive pulmonary disease and bronchiectasis in women, are associated with solid fuel use for cooking, and the damaging effects of exposure to household air pollution in early life on lung development are yet to be fully described. We also review appropriate ways to measure exposure to household air pollution, as well as study design issues and potential effective interventions to prevent these disease burdens. Measurement of household air pollution needs individual, rather than fixed in place, monitoring because exposure varies by age, gender, location, and household role. Women and children are particularly susceptible to the toxic effects of pollution and are exposed to the highest concentrations. Interventions should target these high-risk groups and be of sufficient quality to make the air clean. To make clean energy available to all people is the long-term goal, with an intermediate solution being to make available energy that is clean enough to have a health impact.