Using sulfur as a tracer of outdoor fine particulate matter

Residential radon decay products are associated with cough and phlegm in patients with COPD

Radon decay products attach to particulate matter (referred to as particle radioactivity, PR) has been shown to be potential to promote airway damage after inhalation. In this study, we investigated associations between PR with respiratory symptoms and health-related quality of life (HRQL) in patients with COPD. 141 male patients with COPD, former smokers, completed the St. George's Respiratory Questionnaire (SGRQ) after up to four 1-week seasonal assessments (N=474) of indoor (home) and ambient (central site) particulate matter ≤ 2.5 µm in diameter (PM2.5) and black carbon (BC). Indoor PR was measured as α-activity (radiation) on PM2.5 filter samples. The ratio of indoor/ambient sulfur in PM2.5 (a ventilation surrogate) was used to estimate α-PR from indoor radon decay. SGRQ responses assessed frequent cough, phlegm, shortness of breath, wheeze, and chest attacks in the past 3 months. Multivariable linear regression with generalized estimating equations accounting for repeated measures was used to explore associations, adjusting for potential confounders. Median (IQR) indoor α-PR was 1.22 (0.62) mBq/m3. We found that there were positive associations between α-PR with cough and phlegm. The strongest associations were with estimated α-PR of indoor origin for cough (31.1 % increase/IQR, 95 %CI: 8.8 %, 57.8 %), and was suggestive for phlegm (13.0 % increase/IQR, 95 %CI: -2.5 %, 31.0 %), similar adjusting for indoor BC or PM2.5. α-PR of indoor origin was positively associated with an increase in SGRQ Symptoms score [1.2 units/IQR; 95 %CI: -0.3, 2.6] that did not meet conventional levels of statistical significance. Our results suggested that exposure to indoor radon decay products measured as particle radioactivity, a common indoor exposure, is associated with cough, and suggestively associated with phlegm and worse HRQL symptoms score in patients with COPD.

Characterizing the Stoichiometry of Individual Metal Sulfide and Phosphate Colloids in Soils, Sediments, and Industrial Processes by Inductively Coupled Plasma Time-of-Flight Mass Spectrometry

Size and purity of metal phosphate and metal sulfide colloids can control the solubility, persistence, and bioavailability of metals in environmental systems. Despite their importance, methods for detecting and characterizing the diversity in the elemental composition of these colloids in complex matrices are missing. Here, we develop a single-particle inductively coupled plasma time-of-flight mass spectrometry (sp-icpTOF-MS) approach to characterize the elemental compositions of individual metal phosphate and sulfide colloids extracted from complex matrices. The stoichiometry was accurately determined for particles of known composition with an equivalent spherical diameter of ≥∼200 nm. Assisted by machine learning (ML), the new method could distinguish particles of the copper sulfides covellite (CuS), chalcocite (Cu2S), and chalcopyrite particles (CuFeS2) with 75% (for Cu2S) to 99% (for CuFeS2) accuracy. Application of the sp-icpTOF-MS method to particles recovered from natural samples revealed that iron sulfide (FeS) particles in lake sediment contained ∼4% copper and zinc impurities, whereas pure pyrite (FeS2) was identified in hydraulic fracturing wastewater and confirmed by selected area electron diffraction. Colloidal mercury in an offshore marine sediment was present as pure mercury sulfide (HgS), whereas geogenic HgS recovered from an industrial process contained ∼0.08 wt % silver per Hg, enabling source apportionment of these colloids using ML. X-ray absorption spectroscopy confirmed that Hg was predominantly present as metacinnabar (β-HgS) in the industrial process sample. The determination of impurities in individual colloids, such as zinc and copper in FeS, and silver in HgS may enable improved assessment of their origin, reactivity, and bioavailability potential.

Estimating ambient air pollutant concentrations outside and inside homes in the Subpopulations and Intermediate outcomes in COPD air pollution (SPIROMICS air) cohort

BACKGROUND

Valid, high-resolution estimates of population-level exposure to air pollutants are necessary for accurate estimation of the association between air pollution and the occurrence or exacerbation of adverse health outcomes such as Chronic Obstructive Pulmonary Disease (COPD).

OBJECTIVES

We produced fine-scale individual-level estimates of ambient concentrations of multiple air pollutants (fine particulate matter [PM2.5], NOX, NO2, and O3) at residences of participants in the Subpopulations and Intermediate Outcomes in COPD Air Pollution (SPIROMICS Air) study, located in seven regions in the US. For PM2.5, we additionally integrated modeled estimates of particulate infiltration based on home characteristics and measured total indoor concentrations to provide comprehensive estimates of exposure levels.

METHODS

To estimate ambient concentrations, we used a hierarchical high-resolution spatiotemporal model that integrates hundreds of geographic covariates and pollutant measurements from regulatory and study-specific monitors, including ones located at participant residences. We modeled infiltration efficiency based on data on house characteristics, home heating and cooling practices, indoor smoke and combustion sources, meteorological factors, and paired indoor-outdoor pollutant measurements, among other indicators.

RESULTS

Cross-validated prediction accuracy (R2) for models of ambient concentrations was above 0.80 for most regions and pollutants. Particulate matter infiltration efficiency varied by region, from 0.51 in Winston-Salem to 0.72 in Los Angeles, and ambient-source particles constituted a substantial fraction of total indoor PM2.5.

CONCLUSION

Leveraging well-validated fine-scale approaches for estimating outdoor, ambient-source indoor, and total indoor pollutant concentrations, we can provide comprehensive estimates of short and long-term exposure levels for cohorts undergoing follow-up in multiple different regions.

Indoor and ambient black carbon and fine particulate matter associations with blood biomarkers in COPD patients

BACKGROUND

Systemic inflammation contributes to cardiovascular risk and chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between systemic inflammation and exposure to ambient fine particulate matter (PM ≤ 2.5 μm diameter; PM2.5), and black carbon (BC), a PM2.5 component attributable to traffic and other sources of combustion, infiltrating indoors are not well described.

METHODS

Between 2012 and 2017, COPD patients completed in-home air sampling over one-week intervals, up to four times (seasonally), followed by measurement of plasma biomarkers of systemic inflammation, C-reactive protein (CRP) and interleukin-6 (IL-6), and endothelial activation, soluble vascular adhesion molecule-1 (sVCAM-1). Ambient PM2.5, BC and sulfur were measured at a central site. The ratio of indoor/ambient sulfur in PM2.5, a surrogate for fine particle infiltration, was used to estimate indoor BC and PM2.5 of ambient origin. Linear mixed effects regression with a random intercept for each participant was used to assess associations between indoor and indoor of ambient origin PM2.5 and BC with each biomarker.

RESULTS

144 participants resulting in 482 observations were included in the analysis. There were significant positive associations between indoor BC and indoor BC of ambient origin with CRP [%-increase per interquartile range (IQR);95 % CI (13.2 %;5.2-21.8 and 11.4 %;1.7-22.1, respectively)]. Associations with indoor PM2.5 and indoor PM2.5 of ambient origin were weaker. There were no associations with IL-6 or sVCAM-1.

CONCLUSIONS

In homes of patients with COPD without major sources of combustion, indoor BC is mainly attributable to the infiltration of ambient sources of combustion indoors. Indoor BC of ambient origin is associated with increases in systemic inflammation in patients with COPD, even when staying indoors.

Indoor Emissions Contributed the Majority of Ultrafine Particles in Chinese Urban Residences

Ultrafine particle (UFP) pollution should be controlled to reduce its effects on health. The design of control measures is limited owing to the uncertainty of source contributions in Chinese residences, where indoor UFP pollution is more severe than in Western residences. Herein, a source-specific, time-dependent UFP concentration model was developed by applying an infiltration factor model incorporating coagulation effects. A Monte Carlo framework with the UFP concentration model was employed to estimate the probabilistic distribution of source contributions in Chinese residences. The input parameter distributions were determined based on our survey and previous studies. The annually averaged indoor UFP concentration was estimated at (2.75 ± 1.71) × 104 #/cm3, ranging from 2.35 × 103 to 1.27 × 105 #/cm3 outside the kitchen, and at (5.48 ± 3.08) × 104 #/cm3, ranging from 2.90 × 103 to 1.94 × 105 #/cm3 in the kitchen. Indoor sources contributed more to indoor UFPs, accounting for 61% in the nonkitchen and 80% in the kitchen, surpassing their contribution to indoor PM2.5 in Chinese residences. Meanwhile, the indoor UFP emission contributions were higher than those in the United States, Canada, and Germany, owing to higher emissions from cooking and cigarette smoking. These results will aid in elucidating human exposure to UFPs and in designing more targeted control measures.

Correcting for bias due to mismeasured exposure history in longitudinal studies with continuous outcomes

Epidemiologists are often interested in estimating the effect of functions of time-varying exposure histories in relation to continuous outcomes, for example, cognitive function. However, the individual exposure measurements that constitute the history upon which an exposure history function is constructed are usually mismeasured. To obtain unbiased estimates of the effects for mismeasured functions in longitudinal studies, a method incorporating main and validation studies was developed. Simulation studies under several realistic assumptions were conducted to assess its performance compared to standard analysis, and we found that the proposed method has good performance in terms of finite sample bias reduction and nominal confidence interval coverage. We applied it to a study of long-term exposure toPM 2.5 $\text{PM}_{2.5}$ , in relation to cognitive decline in the Nurses' Health Study Previously, it was found that the 2-year decline in the standard measure of cognition was 0.018 (95% CI, -0.034 to -0.001) units worse per 10μ g/m 3 $\mu \text{g/m}^3$ increase inPM 2.5 $\text{PM}_{2.5}$ exposure. After correction, the estimated impact ofPM 2.5 $\text{PM}_{2.5}$ on cognitive decline increased to 0.027 (95% CI, -0.059 to 0.005) units lower per 10μ g/m 3 $\mu \text{g/m}^3$ increase. To put this into perspective, effects of this magnitude are about 2/3 of those found in our data associated with each additional year of aging: 0.044 (95% CI, -0.047 to -0.040) units per 1 year older after applying our correction method.

Indoor (residential) and ambient particulate matter associations with urinary oxidative stress biomarkers in a COPD cohort

OBJECTIVES

Oxidative stress contributes to chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between indoor (residential) exposure to particulate matter ≤2.5 μm in diameter (PM2.5) and one of its components, black carbon (BC), and oxidative stress are ill-defined.

METHODS

Between 2012 and 2017, 140 patients with COPD completed in-home air sampling over one week intervals, followed by collection of urine samples to measure oxidative stress biomarkers, malondialdehyde (MDA), a marker of lipid peroxidation, and 8-hydroxy-2' -deoxyguanosine (8-OHdG), a marker of oxidative DNA damage. Ambient (central site) BC and PM2.5 were measured, and the ratio of indoor/ambient sulfur in PM2.5, a surrogate for residential ventilation and particle infiltration, was used to estimate indoor BC and PM2.5 of outdoor origin. Mixed effects linear regression models with a participant-specific random intercept were used to assess associations with oxidative biomarkers, adjusting for personal characteristics.

RESULTS

There were positive associations (% increase per IQR; 95 % CI) of directly measured indoor BC with total MDA (6.96; 1.54, 12.69) and 8-OHdG (4.18; -0.67, 9.27), and similar associations with both indoor BC of outdoor origin and ambient BC. There were no associations with directly measured indoor PM2.5, but there were positive associations between indoor PM2.5 of outdoor origin and total MDA (5.40; -0.91, 12.11) and 8-OHdG (8.02; 2.14, 14.25).

CONCLUSIONS

In homes with few indoor combustion sources, directly measured indoor BC, estimates of indoor BC and PM2.5 of outdoor origin, and ambient BC, were positively associated with urinary biomarkers of oxidative stress. This suggests that the infiltration of particulate matter from outdoor sources, attributable to traffic and other sources of combustion, promotes oxidative stress in COPD patients.

Personal and community-level exposure to air pollution and daily changes in respiratory symptoms and oxygen saturation among adults with COPD

Background

Air pollution exposure is associated with hospital admissions for Chronic Obstructive Pulmonary Disease (COPD). Few studies have investigated whether daily personal exposure to air pollutants affects respiratory symptoms and oxygenation among COPD patients.

Methodology

We followed 30 former smokers with COPD for up to 4 non-consecutive 30-day periods in different seasons. Participants recorded worsening of respiratory symptoms (sub-categorized as breathing or bronchitis symptoms) by daily questionnaire, and oxygen saturation by pulse oximeter. Personal and community-level exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃) were measured by portable air quality monitors and stationary monitors in the Boston area. We used generalized and multi-level linear mixed-effects models to estimate associations of the 24-hour average of each pollutant in the previous day with changes in respiratory symptoms and oxygen saturation.

Results

Higher community-level exposure to air pollutants was associated with worsening respiratory symptoms. An interquartile range (IQR) higher community-level O₃ was associated with a 1.35 (95%CI: 1.07-1.70) higher odds of worsening respiratory symptoms. The corresponding ORs for community-level PM_2.5 and NO₂ were 1.18 (95%CI: 1.02-1.37) and 1.06 (95%CI: 0.90-1.25), respectively. Community-level NO₂ was associated with worsening bronchitis symptoms (OR=1.25, 95%CI: 1.00-1.56), but not breathing symptoms. Personal PM_2.5 exposure was associated with lower odds of worsening respiratory symptoms (OR=0.91; 95%CI: 0.81-1.01). Personal exposure to NO₂ was associated with 0.11% lower oxygen saturation (95%CI: -0.22, 0.00) per IQR.

Conclusions

In this COPD population, there was a pattern of worsening respiratory symptoms associated with community-level exposure to O₃ and PM_2.5, and worsening oxygenation associated with personal exposure to NO₂.

Improved indoor air quality during desert dust storms: The impact of the MEDEA exposure-reduction strategies

Desert dust storms (DDS) are natural events that impact not only populations close to the emission sources but also populations many kilometers away. Countries located across the main dust sources, including countries in the Eastern Mediterranean, are highly affected by DDS. In addition, climate change is expanding arid areas exacerbating DDS events. Currently, there are no intervention measures with proven, quantified exposure reduction to desert dust particles. As part of the wider "MEDEA" project, co-funded by LIFE 2016 Programme, we examined the effectiveness of an indoor exposure-reduction intervention (i.e., decrease home ventilation during DDS events and continuous use of air purifier during DDS and non-DDS days) across homes and/or classrooms of schoolchildren with asthma and adults with atrial fibrillation in Cyprus and Crete-Greece. Participants were randomized to a control or intervention groups, including an indoor intervention group with exposure reduction measures and the use of air purifiers. Particle sampling, PM₁₀ and PM_2.5, was conducted in participants' homes and/or classrooms, between 2019 and 2022, during DDS-free weeks and during DDS days for as long as the event lasted. In indoor and outdoor PM₁₀ and PM_2.5 samples, mass and content in main and trace elements was determined. Indoor PM_2.5 and PM₁₀ mass concentrations, adjusting for premise type and dust conditions, were significantly lower in the indoor intervention group compared to the control group (PM_{2.5-intervention}/PM_2.5-control = 0.57, 95% CI: 0.47, 0.70; PM_{10-intervention}/PM_10-control = 0.59, 95% CI: 0.49, 0.71). In addition, the PM_2.5 and PM₁₀ particles of outdoor origin were significantly lower in the intervention vs. the control group (PM_2.5 infiltration intervention-to-control ratio: 0.49, 95% CI: 0.42, 0.58; PM₁₀ infiltration intervention-to-control ratio: 0.68, 95% CI: 0.52, 0.89). Our findings suggest that the use of air purifiers alongside decreased ventilation measures is an effective protective measure that reduces significantly indoor exposure to particles during DDS and non-DDS in high-risk population groups.

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.

Particle radioactivity from radon decay products and reduced pulmonary function among chronic obstructive pulmonary disease patients

BACKGROUND

Radon (222Rn) decay products can attach to particles in the air, be inhaled, and potentially cause airway damage.

RESEARCH QUESTION

Is short-term exposure to particle radioactivity (PR) attributable to radon decay products emitted from particulate matter ≤2.5 μm in diameter (PM2.5) associated with pulmonary function in chronic obstructive pulmonary disease (COPD) patients?

STUDY DESIGN AND METHODS

In this cohort study, 142 elderly, predominantly male patients with COPD from Eastern Massachusetts each had up to 4 one-week long seasonal assessments of indoor (home) and ambient (central site) PR and PM2.5 over the course of a year (467 assessments). Ambient and indoor PR were measured as α-activity on archived PM2.5 filter samples. Ratios of indoor/ambient PR were calculated, with higher ratios representing PR from an indoor source of radon decay. We also considered a measure of outside air infiltration that could dilute the concentrations of indoor radon decay products, the indoor/ambient ratio of sulfur concentrations in PM2.5 filter samples. Spirometry pre- and post-bronchodilator (BD) forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) were conducted following sampling. Generalized additive mixed models were adjusted for meteorologic variables, seasonality, and individual-level determinants of pulmonary function. We additionally adjusted for indoor PM2.5 and black carbon (BC).

RESULTS

PR exposure metrics indicating radon decay product exposure from an indoor source were associated with a reduction in FEV1 and FVC. Patients in homes with high indoor PR (≥median) and low air infiltration (

INTERPRETATION

Our findings raise concern about the harmful effects of PR exposures attributable to residential radon on pulmonary function in patients with COPD.

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Key Words

• Chronic obstructive pulmonary disease
• Particle radioactivity
• Pulmonary function
• Radiation
• Radon
• Spirometry

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MESH Headings

• Humans
• Male
• Aged
• Female
• Radon Daughters
• Air Pollutants/analysis
• Radioactivity
• Cohort Studies
• Particulate Matter/analysis
• Pulmonary Disease, Chronic Obstructive
• Soot
• Radon
• Environmental Exposure/analysis

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Grants

• R01 ES019853 NIEHS NIH HHS
• R21 ES029637 NIEHS NIH HHS

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Affiliation(s)

Veronica A Wang Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Petros Koutrakis Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Longxiang Li Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Man Liu Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Carolina L Z Vieira Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Brent A Coull Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Edward F Maher Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Choong-Min Kang Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Eric Garshick Pulmonary, Allergy, Sleep and Critical Care Medicine Section, Veterans Affairs Boston Healthcare System, Boston, MA, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.

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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.

Quantifying factors affecting contributions of roadway exhaust and non-exhaust emissions to ambient PM10-2.5 and PM2.5-0.2 particles

Traffic-related particulate matter (PM) plays an important role in urban air pollution. However, sources of urban pollution are difficult to distinguish. This study utilises a mobile particle concentrator platform and statistical tools to investigate factors affecting roadway ambient coarse particle (PM_10-2.5) and fine particle (PM_2.5-0.2) concentrations in greater Boston, USA. Positive matrix factorization (PMF) identified six PM_10-2.5 sources (exhaust, road salt, brake wear, regional pollution, road dust resuspension and tyre-road abrasion) and seven fine particle sources. The seven PM_2.5-0.2 sources include the six PM_10-2.5 sources and a source rich in Cr and Ni. Non- exhaust traffic-related sources together accounted for 65.6% and 29.1% of the PM_10-2.5 and PM_2.5-0.2 mass, respectively. While the respective contributions of exhaust sources were 10.4% and 20.7%. The biggest non-exhaust contributor in the PM_10-2.5 was road dust resuspension, accounting for 29.6%, while for the PM_2.5-0.2, the biggest non-exhaust source was road-tyre abrasion, accounting for 12.3%. We used stepwise general additive models (sGAMs) and found statistically significant (p < 0.05) effects of temperature, number of vehicles and rush hour periods on exhaust, brake wear, road dust resuspension and road-tyre abrasion with relative importance between 19.1 and 62.2%, 12.5-42.1% and 4.4-42.2% of the sGAM model's explained variability. Speed limit and road type were also important factors for exhaust, road-tyre and brake wear sources. Meteorological variables of wind speed and relative humidity were significantly associated with both coarse and fine road dust resuspension and had a combined relative importance of 38% and 48%. The quantifying results of the factors that influence traffic-related sources can offer key insights to policies aiming to improve near-road air quality.

Survey of residential indoor particulate matter measurements 1990-2019

We surveyed literature on measurements of indoor particulate matter in all size fractions, in residential environments free of solid fuel combustion (other than wood for recreation or space heating). Data from worldwide studies from 1990 to 2019 were assembled into the most comprehensive collection to date. Out of 2752 publications retrieved, 538 articles from 433 research projects met inclusion criteria and reported unique data, from which more than 2000 unique sets of indoor PM measurements were collected. Distributions of mean concentrations were compiled, weighted by study size. Long-term trends, the impact of non-smoking, air cleaners, and the influence of outdoor PM were also evaluated. Similar patterns of indoor PM distributions for North America and Europe could reflect similarities in the indoor environments of these regions. Greater observed variability for all regions of Asia may reflect greater heterogeneity in indoor conditions, but also low numbers of studies for some regions. Indoor PM concentrations of all size fractions were mostly stable over the survey period, with the exception of observed declines in PM2.5 in European and North American studies, and in PM10 in North America. While outdoor concentrations were correlated with indoor concentrations across studies, indoor concentrations had higher variability, illustrating a limitation of using outdoor measurements to approximate indoor PM exposures.

Factors Influencing Classroom Exposures to Fine Particles, Black Carbon, and Nitrogen Dioxide in Inner-City Schools and Their Implications for Indoor Air Quality

BACKGROUND

School classrooms, where students spend the majority of their time during the day, are the second most important indoor microenvironment for children.

OBJECTIVE

We investigated factors influencing classroom exposures to fine particulate matter (PM2.5), black carbon (BC), and nitrogen dioxide (NO2) in urban schools in the northeast United States.

METHODS

Over the period of 10 y (2008-2013; 2015-2019) measurements were conducted in 309 classrooms of 74 inner-city schools during fall, winter, and spring of the academic period. The data were analyzed using adaptive mixed-effects least absolute shrinkage and selection operator (LASSO) regression models. The LASSO variables included meteorological-, school-, and classroom-based covariates.

RESULTS

LASSO identified 10, 10, and 11 significant factors (p<0.05) that were associated with indoor PM2.5, BC, and NO2 exposures, respectively. The overall variability explained by these models was R2=0.679, 0.687, and 0.621 for PM2.5, BC, and NO2, respectively. Of the model's explained variability, outdoor air pollution was the most important predictor, accounting for 53.9%, 63.4%, and 34.1% of the indoor PM2.5, BC, and NO2 concentrations. School-based predictors included furnace servicing, presence of a basement, annual income, building type, building year of construction, number of classrooms, number of students, and type of ventilation that, in combination, explained 18.6%, 26.1%, and 34.2% of PM2.5, BC, and NO2 levels, whereas classroom-based predictors included classroom floor level, classroom proximity to cafeteria, number of windows, frequency of cleaning, and windows facing the bus area and jointly explained 24.0%, 4.2%, and 29.3% of PM2.5, BC, and NO2 concentrations, respectively.

DISCUSSION

The adaptive LASSO technique identified significant regional-, school-, and classroom-based factors influencing classroom air pollutant levels and provided robust estimates that could potentially inform targeted interventions aiming at improving children's health and well-being during their early years of development. https://doi.org/10.1289/EHP10007.

Personal exposure to PM2.5 of indoor and outdoor origin in two neighboring Chinese communities with contrasting household fuel use patterns

The Chinese government is replacing high-polluting, household coal heating stoves with electricity- and natural gas-powered heaters to improve ambient air quality. The evaluation of the intervention impact on outdoor PM_2.5 and personal exposure in community level are in their initial stages. We compared outdoor air pollution and personal exposure in two neighboring communities (~2 km) in northern China with contrasting household fuel use patterns: one where residents primarily used coal for cooking and heating ("coal village") and one where natural gas was the dominant fuel ("gas village"). We collected 24-h outdoor gravimetric PM_2.5 samples in each village and concurrently measured 48-h integrated exposures among 71 participants from 41 and 30 households in the coal and gas villages, respectively. PM_2.5 samples were analyzed for mass and chemical composition. Daily outdoor PM_2.5 concentrations in the coal village (mean ± standard deviation: 109 ± 41 μg/m³) were, on average, 1.3 ± 0.2 times higher than in the gas village (88 ± 38 μg/m³). However, personal PM_2.5 exposures were lower in the coal village (116 ± 121 μg/m³ versus 156 ± 106 μg/m³). PM_2.5 species that can serve as tracers for residential coal combustion (e.g., S, Se, Zn, Pb, etc.) and dust (Al, Ca, Mg, Fe, Si and Ti) were higher in the coal village, and the proportion of personal PM_2.5 of outdoor origin in the coal village was nearly 2 times higher than the gas village. Our results suggest that ambient PM_2.5 and its chemical composition can vary at relatively small spatial scales and may reflect community-level differences in the household energy use. However, personal PM_2.5 exposures may not mirror between-village differences in outdoor air pollution if only PM_2.5 mass is evaluated. Individual chemical composition of PM_2.5 exposure can provide important insight in future studies on the effectiveness of source-targeted air quality interventions.

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.

Improving Predictions of Indoor Aerosol Concentrations of Outdoor Origin by Considering the Phase Change of Semivolatile Material Driven by Temperature and Mass-Loading Gradients

Outdoor aerosols experience environmental changes as they are transported indoors, including outdoor-to-indoor temperature and mass-loading gradients, which can reduce or enhance their indoor concentrations due to repartitioning driven by changes in thermodynamic equilibrium states. However, the complexity required to model repartitioning typically hinders its inclusion in studies predicting indoor exposure to ambient aerosols. To facilitate exposure predictions, this work used an explicit thermodynamic indoor aerosol model to simulate outdoor-to-indoor aerosol repartitioning typical for residential and office buildings across the 16 U.S. climate zones over an annual time horizon. Results demonstrate that neglecting repartitioning when predicting indoor concentrations can produce errors of up to 80-100% for hydrocarbon-like organic aerosol, 40-60% for total organic aerosol, 400% for ammonium nitrate, and 60% (typically 3 μg/m³) for the total PM_2.5 aerosol. Underpredictions were more likely for buildings in hotter than colder regions, and for residences than offices, since both cooler indoor air and more meaningful residential organic aerosol concentrations encourage condensation of semivolatile organics. Furthermore, a method for computing correction factors to more easily account for thermodynamic repartitioning is provided. Applying these correction factors to mechanical-only aerosol predictions significantly reduced errors to <0.5 μg/m³ for the total indoor PM_2.5 while bypassing explicit thermodynamic simulations.

Effects of particulate matter gamma radiation on oxidative stress biomarkers in COPD patients

Inhalation of particulate matter (PM) radioactivity is an important pathway of ionizing radiation exposure. We investigated the associations between short-term exposures to PM gamma radioactivity with oxidative stress in COPD patients. Urinary concentrations of 8-hydroxy-2'-deoxyguanosine (8-OHdG) and malondialdehyde (MDA) of 81 COPD patients from Eastern Massachusetts were measured 1-4 times during 2012-2014. Daily ambient and indoor PM gamma activities (gamma-3 through gamma-9) were calculated based on EPA RadNet data and indoor-outdoor infiltration ratios. Linear mixed-effects models were used to examine the associations between biomarkers with PM gamma activities for moving averages from urine collection day to 7 days before. Our results indicate that ambient and indoor PM gamma activities were positively associated with 8-OHdG, with stronger effects for exposure windows closer to urine collection day. For per interquartile range increase in indoor PM gamma activities averaged over urine collection day and 1 day before, 8-OHdG increased from 3.41% (95% CI: -0.88, 7.88) to 8.87% (95% CI: 2.98, 15.1), adjusted for indoor black carbon. For MDA, the timing of greatest effects across the exposure week varied but was nearly all positive. These findings provide insight into the toxigenic properties associated with PM radioactivity and suggest that these exposures promote systemic oxidative stress.

Composition and exposure characteristics of PM2.5 on subway platforms and estimates of exposure reduction by protective masks

There is limited information on exposure to metallic constituents of fine particulate matter in subway stations. We characterized the concentrations and composition of airborne fine particulate pollution on six subway platforms in Nanjing, China in both summer and winter of 2019. A microenvironment exposure model was used to evaluate the concentrations of elements in fine particulate matter and the contribution of exposure duration (time spent in the subway station) to overall daily exposure of subway workers and commuters with and without the use of N95 respirators, surgical masks, and cotton masks. We found that airborne fine particulate pollution on station platforms was much higher than in an urban reference site of ambient air, and the same was true for metallic constituents of the particles, such as iron, copper, manganese, strontium, and vanadium. Subway workers were exposed to higher levels of these airborne metals than commuters. The average daily exposure concentration of fine particulate matter was 73.5 μg/m³ for subway workers and 61.8 μg/m³ for commuters, while the average daily exposure to iron was 15.5 μg/m³ for subway workers and 2.0 μg/m³ for commuters. Subway workers were exposed to iron, copper, manganese, and strontium/vanadium at levels approximately eight-fold, four-fold, three-fold, and two-fold greater than the exposure sustained by commuters, respectively. We calculated that wearing N95 respirators or surgical masks can reduce the exposure to these airborne metallic particles significantly for both subway workers and commuters. Overall, we estimate that personal exposure to airborne fine particulate matter on subway platforms can be reduced through the use of N95 respirators or properly fitting masks.

Sources of indoor PM2.5 gross α and β activities measured in 340 homes

Particle radioactivity (PR) exposure has been linked to adverse health effects. PR refers to the presence of α- and β-emitting radioisotopes attached to fine particulate matter (PM_2.5). This study investigated sources contributing to indoor PM_2.5 gross α- and β-radioactivity levels. We measured activity from long-lived radon progeny radionuclides from archived PM_2.5 samples collected in 340 homes in Massachusetts during the period 2006-2010. We analyzed the data using linear mixed effects models and positive matrix factorization (PMF) analysis. Indoor PM_2.5 gross α-activity levels were correlated with sulfur (S), iron (Fe), bromine (Br), vanadium (V), sodium (Na), lead (Pb), potassium (K), calcium (Ca), silicon (Si), zinc (Zn), arsenic (As), titanium (Ti), radon (²²²Rn) and black carbon (BC) concentrations (p <0.05). Indoor PM_2.5 β-activity was correlated with S, As, antimony (Sb), Pb, Br and BC. We identified four indoor PM_2.5 sources: outdoor air pollution (62%), salt aerosol source (14%), fireworks and environmental tobacco smoke (7%) and indoor mixed dust (17%). Outdoor air pollution was the most significant contributor to indoor PM_2.5 α- and β-activity levels. The contributions of this source were during the summer months and when windows were open. Indoor mixed dust was also found to contribute to PM_2.5 α-activity. PM_2.5 α-activity was further associated with radon during winter months, showing radon's important role as an indoor source of ionizing radiation.

Particulate matter emitted from ultrasonic humidifiers-Chemical composition and implication to indoor air

Household humidification is widely practiced to combat dry indoor air. While the benefits of household humidification are widely perceived, its implications to the indoor air have not been critically appraised. In particular, ultrasonic humidifiers are known to generate fine particulate matter (PM). In this study, we first conducted laboratory experiments to investigate the size, quantity, and chemical composition of PM generated by an ultrasonic humidifier. The mass of PM generated showed a correlation with the total alkalinity of charge water, suggesting that CaCO₃ is likely making a major contribution to PM. Ion chromatography analysis revealed a large amount of SO₄^2- in PM, representing a previously unrecognized indoor source. Preliminary results of organic compounds being present in humidifier PM are also presented. A whole-house experiment was further conducted at an actual residential house, with five low-cost sensors (AirBeam) monitoring PM in real time. Operation of a single ultrasonic humidifier resulted in PM_2.5 concentrations up to hundreds of μg m^-3 , and its influence extended across the entire household. The transport and loss of PM_2.5 depended on the rate of air circulation and ventilation. This study emphasizes the need to further investigate the impact of humidifier operation, both on human health and on the indoor atmospheric chemistry, for example, partitioning of acidic and basic compounds.

Estimating climate change-related impacts on outdoor air pollution infiltration

BACKGROUND

Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects.

METHODS

We measured indoor fine particulate matter (PM_2.5) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046-2065) and past (1981-2000) scenarios.

RESULTS

The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months.

DISCUSSION

We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM_2.5 infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM_2.5, and provide a better understanding of the potential influence of climate change on PM_2.5 health effects.

Concentration, composition, and exposure contributions of fine particulate matter on subway concourses in China

Concentrations of airborne metal-rich particles are typically higher on subway platforms and in subway tunnels than in ambient air. The subway concourse is an area of direct air exchange with both platforms and the outside environment, but few researchers have measured the concentrations and composition of fine particles on subway concourses. We characterized the concentrations and composition of fine particles on six subway concourses in Nanjing, China in both summer and winter. We used a respiration rate-adjusted microenvironment exposure model to estimate the contribution of a 6-h work period to daily mean exposure to fine particulate matter of subway workers and compared the estimate with those for general indoor and outdoor workers. We found that particle concentrations were typically higher on the station concourses than in ambient air. The most abundant elements composing the particles were Fe, S, Ca, Si, and K in both subway concourses and reference ambient air, but their contents varied greatly between indoor and outdoor air. The indoor/outdoor ratios of Fe, Cu, and Mn were highest, and subway workers were disproportionately exposed to these three metals. The mean daily exposure dose to Fe was 44.8 μg for subway workers, approximately five times the exposure dose of indoor and outdoor workers. Daily exposure doses of Cu, Mn, V, Sr, As, Co, Sn, and Cr were also higher for subway workers. The quality of indoor air at subway stations is therefore of occupational health concern and strategies should be formulated to reduce worker exposure.

Indoor acids and bases

Numerous acids and bases influence indoor air quality. The most abundant of these species are CO₂ (acidic) and NH₃ (basic), both emitted by building occupants. Other prominent inorganic acids are HNO₃ , HONO, SO₂ , H₂ SO₄ , HCl, and HOCl. Prominent organic acids include formic, acetic, and lactic; nicotine is a noteworthy organic base. Sources of N-, S-, and Cl-containing acids can include ventilation from outdoors, indoor combustion, consumer product use, and chemical reactions. Organic acids are commonly more abundant indoors than outdoors, with indoor sources including occupants, wood, and cooking. Beyond NH₃ and nicotine, other noteworthy bases include inorganic and organic amines. Acids and bases partition indoors among the gas-phase, airborne particles, bulk water, and surfaces; relevant thermodynamic parameters governing the partitioning are the acid-dissociation constant (K_a ), Henry's law constant (K_H ), and the octanol-air partition coefficient (K_oa ). Condensed-phase water strongly influences the fate of indoor acids and bases and is also a medium for chemical interactions. Indoor surfaces can be large reservoirs of acids and bases. This extensive review of the state of knowledge establishes a foundation for future inquiry to better understand how acids and bases influence the suitability of indoor environments for occupants, cultural artifacts, and sensitive equipment.

Associations of daily weather and ambient air pollution with objectively assessed sleep duration and fragmentation: a prospective cohort study

OBJECTIVE

Given the lack of studies examining the associations between daily weather and air pollution with nightly objective sleep over multiple weeks, we quantified these associations in a prospective cohort of healthy participants with episodic migraine.

METHODS

Ninety-eight participants completed daily electronic diaries and wore an actigraph for an average of 45 ds, and a total 4406 nights of data were collected. Nightly sleep characteristics including duration, wake after sleep onset (WASO), and efficiency were assessed using wrist actigraphy. Daily weather parameters and air pollution levels were collected from local weather station and ground-level air quality monitors. We used linear fixed effects models adjusting for participant, day of the week, and day of the year (for weather analysis), and additionally adjusted for temperature and relative humidity (for air pollution analysis).

RESULTS

The participants were 35 ± 12 yrs old and 86 were women. A 10 °F higher daily average temperature was associated with 0.88 (95% CI: 0.06, 1.70) minutes longer WASO and 0.14% (95% CI: -0.01%, 0.30%) lower sleep efficiency on that night. A 14 parts per billion (ppb) (interquartile range) higher daily maximum eight-h ozone was associated with 7.51 (95% CI: 3.23, 11.79) minutes longer sleep duration on that night. Associations did not differ between cold (October-March) and warm (April-September) seasons.

CONCLUSIONS

Higher daily ozone was associated with longer sleep duration and modest associations were observed between higher temperature and lower WASO and lower efficiency.

Indoor Particle Alpha Radioactivity Origins in Occupied Homes

Exposure to radioactivity inside homes potentially poses severe health risks which can be exacerbated by the interaction between radioactive particles and fine indoor particles; in particular, the presence of α particles are a key risk factor. Hence, in this study, particle radioactivity was concurrently measured in the family rooms and basements of 26 homes to assess its concentrations and identify its sources, both indoors and outdoors, across two seasons. The levels of radon, air ions, and particle radioactivity, which included short- and long-lived α-activity (SLA and LLA, respectively), varied greatly but were substantially higher in the basements. Also, particle radioactivity-as well as PM_2.5 and sulfur concentrations-were lower during the heating season. SLA was associated with radon, which was consistently of indoor origin, whereas LLA was more strongly related to the sulfur measured in indoor PM_2.5, which is a proxy of outdoor infiltration. A regression model adjusted for sulfur and SLA also indicated a predominance of outdoor sources, likely due to the short residence time of indoor particles. Our results suggest that radiation in homes originates from both the decay of indoor radon and the infiltration of outdoor radioactivity.

Short-term exposures to particulate matter gamma radiation activities and biomarkers of systemic inflammation and endothelial activation in COPD patients

BACKGROUND

We hypothesized that particulate matter (PM) gamma activity (gamma radiation associated with PM) is associated with systemic effects.

OBJECTIVE

Examine short-term relationships between ambient and indoor exposures to PM gamma activities with systemic inflammation and endothelial activation in chronic obstructive pulmonary disease (COPD) patients.

METHODS

In 85 COPD patients from Eastern Massachusetts, USA from 2012 to 2014, plasma C-reactive protein (CRP), interleukin-6 (IL-6), and soluble vascular cell adhesion molecule-1 (sVCAM-1) were measured seasonally up to four times. We used US EPA RadNet data measuring ambient gamma radiation attached to PM adjusted for background radiation, and estimated in-home gamma radiation exposures using the ratio of in-home-to-ambient sulfur in PM2.5. Linear mixed-effects regression models were used to determine associations between moving averages of PM gamma activities through the week before phlebotomy with these biomarkers. We explored ambient and indoor PM2.5, black carbon (BC), and NO2 as confounders.

RESULTS

Ambient and indoor PM gamma activities measured as energy spectra classes 3 through 9 were positively associated with CRP and IL-6. For example, averaged from phlebotomy day through previous 6 days, each IQR increase in indoor PM gamma activity for each spectra class, was associated with an CRP increase ranging from 7.45% (95%CI: 2.77, 12.4) to 13.4% (95%CI: 5.82, 21.4) and for ambient exposures were associated with an increase of 8.75% (95%CI: -0.57, 18.95) to 14.8% (95%CI: 4.5, 26.0). Indoor exposures were associated with IL-6 increase of 3.56% (95%CI: 0.31, 6.91) to 6.46% (95%CI:1.33, 11.85) and ambient exposures were associated with an increase of 0.03% (95%CI: -6.37, 6.87) to 3.50% (95%CI: -3.15, 10.61). There were no positive associations with sVCAM-1. Sensitivity analyses using two-pollutant models showed similar effects.

CONCLUSIONS

Our results demonstrate that short-term exposures to environmental PM gamma radiation activities were associated with systemic inflammation in COPD patients.

Classroom indoor PM2.5 sources and exposures in inner-city schools

Children spend over 6 h a day in schools and have higher asthma morbidity from school environmental exposures. The present study aims to determine indoor and outdoor possible sources affecting indoor PM_2.5 in classrooms. Weeklong indoor PM_2.5 samples were collected from 32 inner-city schools from a Northeastern U.S. community during three seasons (fall, winter and spring) during the years 2009 to 2013. Concurrently, daily outdoor PM_2.5 samples were taken at a central monitoring site located at a median distance of 4974 m (range 1065-11,592 m) from the schools. Classroom indoor concentrations of PM_2.5 (an average of 5.2 μg/m³) were lower than outdoors (an average of 6.5 μg/m³), and these averages were in the lower range compared to the findings in other schools' studies. The USEPA PMF model was applied to the PM_2.5 components measured simultaneously from classroom indoor and outdoor to estimate the source apportionment. The major sources (contributions) identified across all seasons of indoor PM_2.5 were secondary pollution (41%) and motor vehicles (17%), followed by Calcium (Ca)-rich particles (12%), biomass burning (15%), soil dust (6%), and marine aerosols (4%). Likewise, the major sources of outdoor PM_2.5 across all seasons were secondary pollution (41%) and motor vehicles (26%), followed by biomass burning (17%), soil dust (7%), road dust (3%), and marine aerosols (1%). Secondary pollution was the greatest contributor to indoor and outdoor PM_2.5 over all three seasons, with the highest contribution during spring with 53% to indoor PM_2.5 and 45% to outdoor PM_2.5. Lower contributions of this source during fall and winter are most likely attributed to less infiltration indoors. In contrast, the indoor contribution of motor vehicles source was highest in the fall (29%) and winter (25%), which was presumably categorized by a local source. From the relationship between indoor-to-outdoor sulfur ratios and each source contribution, we also estimated the local and regional influence on indoor PM_2.5 concentration. Overall, the observed differences to indoor PM_2.5 are related to seasonality, and the distinct characteristics and behavior of each classroom/school.

Short-term effects of particle gamma radiation activities on pulmonary function in COPD patients

BACKGROUND

It is not known whether environmental gamma radiation measured in US cities has detectable adverse health effects. We assessed whether short-term exposure to gamma radiation emitted from ambient air particles [gamma particle activity (PRγ)] is associated with reduced pulmonary function in chronic obstructive pulmonary disease (COPD) patients.

OBJECTIVE

We hypothesize that the inhalation of gamma radiation emitted from ambient air particles may be associated with reduced pulmonary function in individuals with COPD.

METHODS

In 125 patients with COPD from Eastern Massachusetts who had up to 4 seasonal one-week assessments of particulate matter ≤2.5 μm (PM_2.5), black carbon (BC), and sulfur followed by spirometry. The US EPA continuously monitors ambient gamma (γ) radiation including γ released from radionuclides attached to particulate matter that is recorded as 9 γ-energy spectra classes (i = 3-9) in counts per minute (CPMγ) in the Boston area (USA). We analyzed the associations between ambient and indoor PRγi (up to one week) and pre and post-bronchodilator (BD) forced expiratory volume in 1 s (FEV₁) and with forced vital capacity (FVC) using mixed-effects regression models. We estimated indoor PRγi using the ratio of the indoor-to-outdoor sulfur in PM_2.5 as a proxy for infiltration of ambient radionuclide-associated particles.

RESULTS

Overall, exposures to ambient and indoor PRγi were associated with a similar decrease in pre- and post-BD FEV₁ and FVC. For example, ambient PRγ₃ exposure averaged from the day of pulmonary function testing through the previous 3 days [IQR of 55.1 counts per minute (CPMγ)] was associated with a decrease in pre-BD FEV₁ of 21.0 ml (95%CI: -38.5 to -3.0 ml; p < 0.01) and pre-BD FVC of 27.5 ml [95% confidence interval (CI): -50.7 to -5.0 ml; p < 0.01] with similar effects adjusting for indoor and outdoor BC and PM_2.5.

CONCLUSION

Our results show that short-term ambient and indoor exposures to environmental gamma radiation associated with particulate matter are associated with reduced pre- and post-BD pulmonary function in patients with COPD.

Estimation of personal exposure to fine particles (PM2.5) of ambient origin for healthy adults in Hong Kong

Personal exposure and ambient fine particles (PM_2.5) measurements for 13 adult subjects (ages 19-57) were conducted in Hong Kong between April 2014 and June 2015. Six to 21 personal samples (mean = 19) per subject were obtained throughout the study period. Samples were analyzed for mass by gravimetric analysis, and 19 elements (from Na to Pb) were analyzed using X-Ray Fluorescence. Higher subject-specific correlations between personal and ambient sulfur (r_s = 0.92; p < 0.001) were found as compared to PM_2.5 mass (r_s = 0.79; p < 0.001) and other elements (0.06 < r_s < 0.86). Personal vs. ambient sulfur regression yielded an average exposure factor (F_pex) of 0.73 ± 0.02, supporting the use of sulfur as a surrogate to estimate personal exposure to PM_2.5 of ambient origin (E_a). E_a accounted for 41-82% and 57-73% of total personal PM_2.5 exposures (P) by season and by subject, respectively. The importance of both E_a and non-ambient exposures (E_na, 11.2 ± 5.6 μg/m³; 32.5 ± 10.9%) are noted. Mixed-effects models were applied to estimate the relationships between ambient PM_2.5 concentrations and their corresponding exposure variables (E_a, P). Higher correlations for E_a (0.90; p < 0.001) than for P (0.58; p < 0.01) were found. A calibration coefficient < 1 suggests an attenuation of 22% (ranging 16-28%) of the true effect estimates when using average ambient concentrations at central monitoring stations as surrogates for E_a. Stationary ambient data can be used to assess population exposure only if PM exposure is dominated by E_a.

Different health effects of indoor- and outdoor-originated PM2.5 on cardiopulmonary function in COPD patients and healthy elderly adults

Numerous research has explored the associations of outdoor or indoor fine particulate matter (PM_2.5 ) and health effects; however, few studies compared the effects of indoor PM_2.5 originated from outdoor (PM_2.5,os ) and indoor sources (PM_2.5,is ). To assess the associations of PM_2.5,os and PM_2.5,is with cardiopulmonary function in patients with chronic obstructive pulmonary disease (COPD) and healthy elderly adults, blood pressure (BP) and pulmonary function were repeatedly examined in 43 COPD patients and their 32 healthy spouses in Beijing, China. Iron was used as tracer element to separate PM_2.5,os and PM_2.5,is . Mixed-effects models were applied to assess the associations of PM_2.5,os or PM_2.5,is and health effects after controlling for potential confounders. There was a reduction in forced expiratory volume in first second (FEV₁ ) in COPD patients associated with PM_2.5,is during the heating season. PM_2.5,os was positively associated with diastolic BP (DBP) in healthy elderly adults during the heating season. There was a reduction in peak expiratory flow (PEF) in healthy elderly adults associated with PM_2.5,os during the non-heating season. Exposure to indoor- and outdoor-originated PM_2.5 had different health effects on cardiopulmonary function in different populations. The results provide supporting evidence for improving indoor air quality to promote public health among susceptible population.

Estimating ambient-origin PM2.5 exposure for epidemiology: observations, prediction, and validation using personal sampling in the Multi-Ethnic Study of Atherosclerosis

OBJECTIVES

We aim to characterize the qualities of estimation approaches for individual exposure to ambient-origin fine particulate matter (PM_2.5), for use in epidemiological studies.

METHODS

The analysis incorporates personal, home indoor, and home outdoor air monitoring data and spatio-temporal model predictions for 60 participants from the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). We compared measurement-based personal PM_2.5 exposure with several measured or predicted estimates of outdoor, indoor, and personal exposures.

RESULTS

The mean personal 2-week exposure was 7.6 (standard deviation 3.7) µg/m³. Outdoor model predictions performed far better than outdoor concentrations estimated using a nearest-monitor approach (R = 0.63 versus R = 0.43). Incorporating infiltration indoors of ambient-derived PM_2.5 provided better estimates of the measurement-based personal exposures than outdoor concentration predictions (R = 0.81 versus R = 0.63) and better scaling of estimated exposure (mean difference 0.4 versus 5.4 µg/m³ higher than measurements), suggesting there is value to collecting data regarding home infiltration. Incorporating individual-level time-location information into exposure predictions did not increase correlations with measurement-based personal exposures (R = 0.80) in our sample consisting primarily of retired persons.

CONCLUSIONS

This analysis demonstrates the importance of incorporating infiltration when estimating individual exposure to ambient air pollution. Spatio-temporal models provide substantial improvement in exposure estimation over a nearest monitor approach.

Cave drip water solutes in south-eastern Australia: Constraining sources, sinks and processes

Constraining sources and site-specific processes of trace elements in speleothem geochemical records is key to an informed interpretation. This paper examines a 10-year data set of drip water solutes from Harrie Wood Cave, south-eastern Australia, and identifies the processes that control their response to El Niño-Southern Oscillation events which varies the site water balance. The contributions of aerosol and bedrock end-members are quantified via hydrochemical mass balance modelling. The parent bedrock is the main source for the drip water solutes: Mg, Sr, K and trace elements (Ba, Al, V, Cr, Mn, Ni, Co, Cu, Pb and U), while atmospheric aerosol inputs also contribute significantly to drip water trace elements and Na, K and Zn. A laboratory investigation evaluating water-soluble fractions of metals in soil samples and soil enrichment factors provided a basis for understanding metal retainment and release to solution and transport from the soil zone. These results identified the role of the soil as a sink for: trace metals, Na and K, and a secondary source for Zn. Further, soil processes including: cation exchange, K-fixation, metal adsorption to colloids and the release of Zn associated with organic matter degradation further modify the chemical composition of the resultant drip waters. This research is significant for the south-eastern Australian region, as well as other sites in a karst setting with clay-rich soil. In particular these results reveal that the response of drip water chemistry to hydroclimatic forcing is non-linear, with the greatest response observed when the long-term gradient in the cumulative water balance reverses. This longer-term drip water monitoring dataset is significant because it provides the pivotal framework required to reliably identify suitable trace element proxies for interpretation in geochemical speleothem records on multi-decadal timescales.

Road proximity influences indoor exposures to ambient fine particle mass and components

Exposure to traffic-related PM_2.5 mass and its components can affect human health. Meanwhile, indoor concentrations are better exposure predictors as compared to outdoor concentrations because individuals spend the majority of their time indoors. We estimated the impact of traffic emissions on indoor PM_2.5 mass and its species as a function of road proximity in Massachusetts. A linear regression model was built using 662 indoor samples and 580 ambient samples. Analysis shows that indoor exposures to traffic-related particles increased dramatically with road proximity. We defined relative concentration decrease, R(α), as the ratio of the indoor concentration at perpendicular distance α in meters from the closest major road to the indoor concentration at 1800 m from the major road. R(13) values for PM_2.5 mass and Black Carbon (BC) were 1.3 (95%CI: 1.4, 1.6) and 2.1 (95%CI: 1.3, 2.8) for A12 roads, and 1.3 (95%CI: 1.2, 1.4) and 1.2 (95%CI: 1.1, 1.3) for A3 roads. R(α) values were also estimated for Fe, Mn, Mo, Sr and Ti for A12 roads, and Ca, Cu, Fe, Mn, Mo, Ni, Si, Sr, V and Zn for A3 roads. R(α) values for species associated mainly with brakes, tires or road dust (e.g., Mn, Mo and Sr) were higher than others. For A12 roads, R(13) values for Mn and Mo were 10.9 (95%CI: 0.9, 20.9) and 6.5 (95%CI: 1.4, 11.5), and ranged from 1.3 to 2.1 for other species; for A3 roads, R(13) values for Mn, Mo and Sr were 1.9 (95%CI: 1.1, 2.9), 1.8 (95%CI: 1.1, 2.4), and 8.5 (95%CI: 5.9, 10.9), and ranged from 1.2 to 1.6 for others. Our results indicate a significant impact of local traffic emissions on indoor air, which depends on road proximity. Thus road proximity which has been used in many epidemiological studies is a reasonable exposure metric.

Modeling individual exposures to ambient PM2.5 in the diabetes and the environment panel study (DEPS)

Air pollution epidemiology studies of ambient fine particulate matter (PM_2.5) often use outdoor concentrations as exposure surrogates, which can induce exposure error. The goal of this study was to improve ambient PM_2.5 exposure assessments for a repeated measurements study with 22 diabetic individuals in central North Carolina called the Diabetes and Environment Panel Study (DEPS) by applying the Exposure Model for Individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM_2.5 using outdoor concentrations, questionnaires, weather, and time-location information. Using EMI, we linked a mechanistic air exchange rate (AER) model to a mass-balance PM_2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (F_{inf_home}, Tier 2), indoor concentrations (C_in, Tier 3), personal exposure factors (F_pex, Tier 4), and personal exposures (E, Tier 5) for ambient PM_2.5. We applied EMI to predict daily PM_2.5 exposure metrics (Tiers 1-5) for 174 participant-days across the 13 months of DEPS. Individual model predictions were compared to a subset of daily measurements of F_pex and E (Tiers 4-5) from the DEPS participants. Model-predicted F_pex and E corresponded well to daily measurements with a median difference of 14% and 23%; respectively. Daily model predictions for all 174 days showed considerable temporal and house-to-house variability of AER, F_{inf_home}, and C_in (Tiers 1-3), and person-to-person variability of F_pex and E (Tiers 4-5). Our study demonstrates the capability of predicting individual-level ambient PM_2.5 exposure metrics for an epidemiological study, in support of improving risk estimation.

Indoor PM2.5 in an urban zone with heavy wood smoke pollution: The case of Temuco, Chile

Temuco is a mid-size city representative of severe wood smoke pollution in southern Chile; however, little is known about the indoor air quality in this region. A field measurement campaign at 63 households in the Temuco urban area was conducted in winter 2014 and is reported here. In this study, indoor and outdoor (24-hr) PM_2.5 and its elemental composition were measured and compared. Infiltration parameters and outdoor/indoor contributions to indoor PM_2.5 were also determined. A statistical evaluation of how various air quality interventions and household features influence indoor PM_2.5 was also performed. This study determined median indoor and outdoor PM_2.5 concentrations of 44.4 and 41.8 μg/m³, respectively. An average infiltration factor (0.62 ± 0.06) was estimated using sulfur as a tracer species. Using a simple mass balance approach, median indoor and outdoor contributions to indoor PM_2.5 concentrations were then estimated as 12.5 and 26.5 μg/m³, respectively; therefore, 68% of indoor PM_2.5 comes from outdoor infiltration. This high percentage is due to high outdoor pollution and relatively high household air exchange rates (median: 1.06 h^-1). This study found that S, Br and Rb were dominated by outdoor contributions, while Si, Ca, Ti, Fe and As originated from indoor sources. Using continuous indoor and outdoor PM_2.5 measurements, a median indoor source strength of 75 μg PM_2.5/min was estimated for the diurnal period, similar to literature results. For the evening period, the median estimate rose to 135 μg PM_2.5/min, reflecting a more intense wood burning associated to cooking and space heating at night. Statistical test results (at the 90% confidence level) support the ongoing woodstove replacement program (reducing emissions) and household weatherization subsidies (reducing heating demand) for improving indoor air quality in southern Chile, and suggest that a cookstove improvement program might be helpful as well.

Development of a modeling approach to estimate indoor-to-outdoor sulfur ratios and predict indoor PM2.5 and black carbon concentrations for Eastern Massachusetts households

The effects of indoor air pollution on human health have drawn increasing attention among the scientific community as individuals spend most of their time indoors. However, indoor air sampling is labor-intensive and costly, which limits the ability to study the adverse health effects related to indoor air pollutants. To overcome this challenge, many researchers have attempted to predict indoor exposures based on outdoor pollutant concentrations, home characteristics, and weather parameters. Typically, these models require knowledge of the infiltration factor, which indicates the fraction of ambient particles that penetrates indoors. For estimating indoor fine particulate matter (PM_2.5) exposure, a common approach is to use the indoor-to-outdoor sulfur ratio (S_indoor/S_outdoor) as a proxy of the infiltration factor. The objective of this study was to develop a robust model that estimates S_indoor/S_outdoor for individual households that can be incorporated into models to predict indoor PM_2.5 and black carbon (BC) concentrations. Overall, our model adequately estimated S_indoor/S_outdoor with an out-of-sample by home-season R² of 0.89. Estimated S_indoor/S_outdoor reflected behaviors that influence particle infiltration, including window opening, use of forced air heating, and air purifier. Sulfur ratio-adjusted models predicted indoor PM_2.5 and BC with high precision, with out-of-sample R² values of 0.79 and 0.76, respectively.

Estimation of residential fine particulate matter infiltration in Shanghai, China

Ambient concentrations of fine particulate matter (PM_2.5) concentration is often used as an exposure surrogate to estimate PM_2.5 health effects in epidemiological studies. Ignoring the potential variations in the amount of outdoor PM_2.5 infiltrating into indoor environments will cause exposure misclassification, especially when people spend most of their time indoors. As it is not feasible to measure the PM_2.5 infiltration factor (F_inf) for each individual residence, we aimed to build models for residential PM_2.5F_inf prediction and to evaluate seasonal F_inf variations among residences. We repeated collected paired indoor and outdoor PM_2.5 filter samples for 7 continuous days in each of the three seasons (hot, cold and transitional seasons) from 48 typical homes of Shanghai, China. PM_2.5-bound sulfur on the filters was measured by X-ray fluorescence for PM_2.5F_inf calculation. We then used stepwise-multiple linear regression to construct season-specific models with climatic variables and questionnaire-based predictors. All models were evaluated by the coefficient of determination (R²) and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV). The 7-day mean (±SD) of PM_2.5F_inf across all observations was 0.83 (±0.18). F_inf was found higher and more varied in transitional season (12-25 °C) than hot (>25 °C) and cold (<12 °C) seasons. Air conditioning use and meteorological factors were the most important predictors during hot and cold seasons; Floor of residence and building age were the best transitional season predictors. The models predicted 60.0%-68.4% of the variance in 7-day averages of F_inf, The LOOCV analysis showed an R² of 0.52 and an RMSE of 0.11. Our finding of large variation in residential PM_2.5F_inf between seasons and across residences within season indicated the important source of outdoor-generated PM_2.5 exposure heterogeneity in epidemiologic studies. Our models based on readily available data may potentially improve the accuracy of estimates of the health effects of PM_2.5 exposure.

Modeling indoor particulate exposures in inner-city school classrooms

Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed effects linear models were used to determine the relationships between indoor PM2.5 (particulate matter) and black carbon (BC), and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor-outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM2.5 and BC in 199 samples from 136 classrooms (30 school buildings) were compared with those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: (1) there are important PM2.5 sources in classrooms; (2) the penetration of outdoor PM2.5 particles varies by school and (3) the site-specific outside PM2.5 levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (out of sample correlations: PM2.5: r2=0.68, BC; r2=0.61). Our results suggest that PM2.5 has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available.

Survival analysis with functions of mismeasured covariate histories: the case of chronic air pollution exposure in relation to mortality in the nurses' health study

Environmental epidemiologists are often interested in estimating the effect of functions of time-varying exposure histories, such as the 12-month moving average, in relation to chronic disease incidence or mortality. The individual exposure measurements that comprise such an exposure history are usually mis-measured, at least moderately, and, often, more substantially. To obtain unbiased estimates of Cox model hazard ratios for these complex mis-measured exposure functions, an extended risk set regression calibration method for Cox models is developed and applied to a study of long-term exposure to the fine particulate matter (PM_2.5) component of air pollution in relation to all-cause mortality in the Nurses' Health Study. Simulation studies under several realistic assumptions about the measurement error model and about the correlation structure of the repeated exposure measurements were conducted to assess the finite sample properties of this new method, and found that the method has good performance in terms of finite sample bias reduction and nominal confidence interval coverage.

Characterization of ambient-generated exposure to fine particles using sulfate as a tracer in the Chinese megacity of Guangzhou

Total personal exposures can differ from the concentrations measured at stationary ambient monitoring sites. To provide further insight into factors affecting exposure to particles, chemical tracers were used to separate total personal exposure into its ambient and non-ambient components. Simultaneous measurements of ambient and personal exposure to fine particles (PM_2.5) were conducted in eight districts of Guangzhou, a megacity in South China, during the winter of 2011. Considerable significant correlations (Spearman's Rho, r_s) between personal exposures and ambient concentrations of sulfate (SO₄^2-; r_s>0.68) were found in contrast to elemental carbon (EC; r_s>0.37). The average fraction of personal SO₄^2- to ambient SO₄^2- resulting in an adjusted ambient exposure factor of α=0.72 and a slope of 0.73 was determined from linear regression analysis when there were minimal indoor sources of SO₄^2-. From all data pooled across the districts, the estimated average ambient-generated and non-ambient-generated exposure to PM_2.5 were 55.3μg/m³ (SD=23.4μg/m³) and 18.1μg/m³ (SD=29.1μg/m³), respectively. A significant association was found between ambient-generated exposure and ambient PM_2.5 concentrations (Pearson's r=0.51, p<0.001). As expected, the non-ambient generated exposure was not related to the ambient concentrations. This study highlights the importance of both ambient and non-ambient components of total personal exposure in the megacity of Guangzhou. Our results support the use of SO₄^2- as a tracer of personal exposure to PM_2.5 of ambient origin in environmental and epidemiological studies.

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.

Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5 in Central North Carolina

Air pollution health studies of fine particulate matter (diameter ≤2.5 μm, PM2.5) often use outdoor concentrations as exposure surrogates. Failure to account for variability of indoor infiltration of ambient PM2.5 and time indoors can induce exposure errors. We developed and evaluated an exposure model for individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM2.5 using outdoor concentrations, questionnaires, weather, and time-location information. We linked a mechanistic air exchange rate (AER) model to a mass-balance PM2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (Tier 2), indoor concentrations (Tier 3), personal exposure factors (Tier 4), and personal exposures (Tier 5) for ambient PM2.5. Using cross-validation, individual predictions were compared to 591 daily measurements from 31 homes (Tiers 1-3) and participants (Tiers 4-5) in central North Carolina. Median absolute differences were 39% (0.17 h(-1)) for Tier 1, 18% (0.10) for Tier 2, 20% (2.0 μg/m(3)) for Tier 3, 18% (0.10) for Tier 4, and 20% (1.8 μg/m(3)) for Tier 5. The capability of EMI could help reduce the uncertainty of ambient PM2.5 exposure metrics used in health studies.

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.

Effects of ambient air particles on mortality in Seoul: Have the effects changed over time?

BACKGROUND

Several studies have shown that there may be temporal variation in PM short-term effect on mortality. This temporal pattern may play an important role in evaluating air quality policies.

OBJECTIVES

We investigated temporal variation in the association between PM and mortality in Seoul, Korea, 1998-2011.

METHODS

We adopted a generalized additive model and a series of time windows of five years to analyze temporal variation in associations between PM and all-cause, cardiovascular, and respiratory mortality. This time-window approach offers not only a comparison between one and the other half period but also successive variation. Time-varying associations were estimated only for days without Asian dust (dust storm blown from the Gobi desert) intrusion.

RESULTS

Annual average PM10 and PM2.5 total mass decreased from 70.0 to 46.9 µg/m(3) and 44.4 to 23.4 µg/m(3), respectively, during 2001-2011. A 10 µg/m(3) increase in PM10 was associated with 0.16% (95% CI=-0.03% to 0.35%) additional all-cause deaths in 2002-2006 and it increased to 0.26% (95% CI=0.05-0.48%) in 2007-2011. For PM2.5, the association increased from 0.35% (95% CI=-0.02% to 0.71%) to 0.48% (95% CI=0.08-0.88%). For cardiovascular and respiratory mortality, increasing trends with stronger estimates were found.

CONCLUSIONS

The present study showed temporally increasing trends in associations between PM and mortality. Current policies may not be as effective to reducing health risks attributable to PM as expected. Air quality interventions should be encouraged in terms of causal factors for time-varying association between PM and mortality.

The association of long-term exposure to PM2.5 on all-cause mortality in the Nurses' Health Study and the impact of measurement-error correction

BACKGROUND

Long-term exposure to particulate matter less than 2.5 μm in diameter (PM2.5) has been consistently associated with risk of all-cause mortality. The methods used to assess exposure, such as area averages, nearest monitor values, land use regressions, and spatio-temporal models in these studies are subject to measurement error. However, to date, no study has attempted to incorporate adjustment for measurement error into a long-term study of the effects of air pollution on mortality.

METHODS

We followed 108,767 members of the Nurses' Health Study (NHS) 2000-2006 and identified all deaths. Biennial mailed questionnaires provided a detailed residential address history and updated information on potential confounders. Time-varying average PM2.5 in the previous 12-months was assigned based on residential address and was predicted from either spatio-temporal prediction models or as concentrations measured at the nearest USEPA monitor. Information on the relationships of personal exposure to PM2.5 of ambient origin with spatio-temporal predicted and nearest monitor PM2.5 was available from five previous validation studies. Time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95 percent confidence intervals (95%CI) for each 10 μg/m(3) increase in PM2.5. Risk-set regression calibration was used to adjust estimates for measurement error.

RESULTS

Increasing exposure to PM2.5 was associated with an increased risk of mortality, and results were similar regardless of the method chosen for exposure assessment. Specifically, the multivariable adjusted HRs for each 10 μg/m(3) increase in 12-month average PM2.5 from spatio-temporal prediction models were 1.13 (95%CI:1.05, 1.22) and 1.12 (95%CI:1.05, 1.21) for concentrations at the nearest EPA monitoring location. Adjustment for measurement error increased the magnitude of the HRs 4-10% and led to wider CIs (HR = 1.18; 95%CI: 1.02, 1.36 for each 10 μg/m(3) increase in PM2.5 from the spatio-temporal models and HR = 1.22; 95%CI: 1.02, 1.45 from the nearest monitor estimates).

CONCLUSIONS

These findings support the large body of literature on the adverse effects of PM2.5, and suggest that adjustment for measurement error be considered in future studies where possible.

Quantifying the contribution of ambient and indoor-generated fine particles to indoor air in residential environments

Indoor fine particles (FPs) are a combination of ambient particles that have infiltrated indoors, and particles that have been generated indoors from activities such as cooking. The objective of this paper was to estimate the infiltration factor (Finf ) and the ambient/non-ambient components of indoor FPs. To do this, continuous measurements were collected indoors and outdoors for seven consecutive days in 50 non-smoking homes in Halifax, Nova Scotia in both summer and winter using DustTrak (TSI Inc) photometers. Additionally, indoor and outdoor gravimetric measurements were made for each 24-h period in each home, using Harvard impactors (HI). A computerized algorithm was developed to remove (censor) peaks due to indoor sources. The censored indoor/outdoor ratio was then used to estimate daily Finfs and to determine the ambient and non-ambient components of total indoor concentrations. Finf estimates in Halifax (daily summer median = 0.80; daily winter median = 0.55) were higher than have been reported in other parts of Canada. In both winter and summer, the majority of FP was of ambient origin (daily winter median = 59%; daily summer median = 84%). Predictors of the non-ambient component included various cooking variables, combustion sources, relative humidity, and factors influencing ventilation. This work highlights the fact that regional factors can influence the contribution of ambient particles to indoor residential concentrations.

PRACTICAL IMPLICATIONS

Ambient and non-ambient particles have different risk management approaches, composition, and likely toxicity. Therefore, a better understanding of their contribution to the indoor environment is important to manage the health risks associated with fine particles (FPs) effectively. As well, a better understanding of the factors Finf can help improve exposure assessment and contribute to reduced exposure misclassification in epidemiologic studies.

The effects of PM2.5 and its components from indoor and outdoor sources on cough and wheeze symptoms in asthmatic children

Particulate matter with aerodynamic diameter <2.5 μm (PM2.5) is associated with asthma exacerbation. In the Children's Air Pollution Asthma Study, we investigated the longitudinal association of PM2.5 and its components from indoor and outdoor sources with cough and wheeze symptoms in 36 asthmatic children. The sulfur tracer method was used to estimate infiltration factors. Mixed proportional odds models for an ordinal response were used to relate daily cough and wheeze scores to PM2.5 exposures. The odds ratio associated with being above a given symptom score for a SD increase in PM2.5 from indoor sources (PMIS) was 1.24 (95% confidence interval: 0.92-1.68) for cough and 1.63 (1.11-2.39) for wheeze. Ozone was associated with wheeze (1.82, 1.19-2.80), and cough was associated with indoor PM2.5 components from outdoor sources (denoted with subscript "OS") bromine (BrOS: 1.32, 1.05-1.67), chlorine (ClOS: 1.27, 1.02-1.59) and pyrolyzed organic carbon (OPOS: 1.49, 1.12-1.99). The highest effects were seen in the winter for cough with sulfur (SOS: 2.28, 1.01-5.16) and wheeze with organic carbon fraction 2 (OC2OS: 7.46, 1.19-46.60). Our results indicate that exposure to components originating from outdoor sources of photochemistry, diesel and fuel oil combustion is associated with symptom's exacerbation, especially in the winter. PM2.5 mass of indoor origin was more strongly associated with wheeze than with cough.