Concentrations of PM(2.5) mass and components in residential and non-residential indoor microenvironments: the Sources and Composition of Particulate Exposures study

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 (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.

Status and frontier analysis of indoor PM2.5-related health effects: a bibliometric analysis

Epidemiological data indicate atmospheric particulate matter, especially fine particulate matter (PM_2.5), has many negative effects on human health. Of note, people spend about 90% of their time indoors. More importantly, according to the World Health Organization (WHO) statistics, indoor air pollution causes nearly 1.6 million deaths each year, and it is considered as one of the major health risk factors. In order to obtain a deeper understanding of the harmful effects of indoor PM_2.5 on human health, we used bibliometric software to summarize articles in this field. In conclusion, since 2000, the annual publication volume has increased year by year. America topped the list for the number of articles, and Professor Petros Koutrakis and Harvard University were the author and institution with the most published in this research area, respectively. Over the past decade, scholars gradually paid attention to molecular mechanisms, therefore, the toxicity can be better explored. Particularly, apart from timely intervention and treatment for adverse consequences, it is necessary to effectively reduce indoor PM_2.5 through technologies. In addition, the trend and keywords analysis are favorable ways to find out future research hotspots. Hopefully, various countries and regions strengthen academic cooperation and integration of multi-disciplinary.

Adverse effects of air pollution-derived fine particulate matter on cardiovascular homeostasis and disease

Air pollution is a rapidly growing major health concern around the world. Atmospheric particulate matter that has a diameter of less than 2.5 µm (PM2.5) refers to an air pollutant composed of particles and chemical compounds that originate from various sources. While epidemiological studies have established the association between PM2.5 exposure and cardiovascular diseases, the precise cellular and molecular mechanisms by which PM2.5 promotes cardiovascular complications are yet to be fully elucidated. In this review, we summarize the various sources of PM2.5, its components, and the concentrations of ambient PM2.5 in various settings. We discuss the experimental findings to date that evaluate the potential adverse effects of PM2.5 on cardiovascular homeostasis and function, and the possible therapeutic options that may alleviate PM2.5-driven cardiovascular damage.

In-flight particulate matter concentrations in commercial flights are likely lower than other indoor environments

Air quality in indoor environments can have significant impacts on people's health, comfort, and productivity. Particulate matter (PM; also referred to as aerosols) is an important type of air pollutant, and exposure to outdoor PM has been associated with a variety of diseases. In addition, there is increasing recognition and concern of airborne transmission of viruses, including severe acute respiratory syndrome corona-virus 2 (SARS-CoV-2), especially in indoor environments. Despite its importance, indoor PM data during the COVID-19 pandemic are scarce. In this work, we measured and compared particle number and mass concentrations in aircraft cabins during commercial flights with various indoor environments in Atlanta, GA, during July 2020, including retail stores, grocery stores, restaurants, offices, transportation, and homes. Restaurants had the highest particle number and mass concentrations, dominated by cooking emissions, while in-flight aircraft cabins had the lowest observed concentrations out of all surveyed spaces.

Federated Compressed Learning Edge Computing Framework with Ensuring Data Privacy for PM2.5 Prediction in Smart City Sensing Applications

The sparse data in PM2.5 air quality monitoring systems is frequently happened on large-scale smart city sensing applications, which is collected via massive sensors. Moreover, it could be affected by inefficient node deployment, insufficient communication, and fragmented records, which is the main challenge of the high-resolution prediction system. In addition, data privacy in the existing centralized air quality prediction system cannot be ensured because the data which are mined from end sensory nodes constantly exposed to the network. Therefore, this paper proposes a novel edge computing framework, named Federated Compressed Learning (FCL), which provides efficient data generation while ensuring data privacy for PM2.5 predictions in the application of smart city sensing. The proposed scheme inherits the basic ideas of the compression technique, regional joint learning, and considers a secure data exchange. Thus, it could reduce the data quantity while preserving data privacy. This study would like to develop a green energy-based wireless sensing network system by using FCL edge computing framework. It is also one of key technologies of software and hardware co-design for reconfigurable and customized sensing devices application. Consequently, the prototypes are developed in order to validate the performances of the proposed framework. The results show that the data consumption is reduced by more than 95% with an error rate below 5%. Finally, the prediction results based on the FCL will generate slightly lower accuracy compared with centralized training. However, the data could be heavily compacted and securely transmitted in WSNs.

PM2.5 exposure of various microenvironments in a community: Characteristics and applications

While the measurement of particulate matter (PM) with a diameter of less than 2.5 μm (PM_2.5) has been conducted for personal exposure assessment, it remains unclear how models that integrate microenvironmental levels with resolved activity and location information predict personal exposure to PM. We comprehensively investigated PM_2.5 concentrations in various microenvironments and estimated personal exposure stratified by the microenvironment. A variety of microenvironments (>200 places and locations, divided into 23 components according to indoor, outdoor, and transit modes) in a community were selected to characterize PM_2.5 concentrations. Infiltration factors calculated from microenvironmental/central-site station (M/S) monitoring campaigns with time-activity patterns were used to estimate time-weighted exposure to PM_2.5 for university students. We evaluated exposures using a four-stage modeling approach and quantified the performance of each component. It was found that the SidePak monitor overestimated the concentration by 3.5 times as compared with the filter-based measurements. Higher mean concentrations of PM_2.5 were observed in the Taoist temple and night market microenvironments; in contrast, lower concentrations were observed in air-conditioned offices and car microenvironments. While the exposure model incorporating detailed time-location information and infiltration factors achieved the highest prediction (R² = 0.49) of personal exposure to PM_2.5, the use of indoor, outdoor, and transit components for modeling also generated a consistent result (R² = 0.44).

A framework for estimating the US mortality burden of fine particulate matter exposure attributable to indoor and outdoor microenvironments

Exposure to fine particulate matter (PM_2.5) is associated with increased mortality. Although epidemiology studies typically use outdoor PM_2.5 concentrations as surrogates for exposure, the majority of PM_2.5 exposure in the US occurs in microenvironments other than outdoors. We develop a framework for estimating the total US mortality burden attributable to exposure to PM_2.5 of both indoor and outdoor origin in the primary non-smoking microenvironments in which people spend most of their time. The framework utilizes an exposure-response function combined with adjusted mortality effect estimates that account for underlying exposures to PM_2.5 of outdoor origin that likely occurred in the original epidemiology populations from which effect estimates are derived. We demonstrate the framework using several different scenarios to estimate the potential magnitude and bounds of the US mortality burden attributable to total PM_2.5 exposure across all non-smoking environments under a variety of assumptions. Our best estimates of the US mortality burden associated with total PM_2.5 exposure in the year 2012 range from ~230,000 to ~300,000 deaths. Indoor exposure to PM_2.5 of outdoor origin is typically the largest total exposure, accounting for ~40-60% of total mortality, followed by residential exposure to indoor PM_2.5 sources, which also drives the majority of variability in each scenario.

Characterizing peak exposure of secondhand smoke using a real-time PM2.5 monitor

Although short-duration elevated exposures (peak exposures) to pollutants may trigger adverse acute effects, epidemiological studies to understand their influence on different health effects are hampered by lack of methods for objectively identifying peaks. Secondhand smoke from cigarettes (SHS) in the residential environment can lead to peak exposures. The aim of this study was to explore whether peaks in continuous PM2.5 data can indicate SHS exposure. A total of 41 children (21 with and 20 without SHS exposure based on self-report) from 28 families in New York City (NY, USA) were recruited. Both personal and residential continuous PM2.5 monitoring were performed for five consecutive days using MicroPEM sensors (RTI International, USA). A threshold detection method based on cumulative distribution function was developed to identify peaks. When children were home, the mean accumulated peak area (APA) for peak exposures was 297 ± 325 hour*µg/m3 for children from smoking families and six times that of the APA from non-smoking families (~50 ± 54 hour*µg/m3 ). Average PM2.5 mass concentrations for SHS exposed and unexposed children were 24 ± 15 µg/m3 and 15 ± 9 µg/m3 , respectively. The average SHS exposure duration represents ~5% of total exposure time, but ~13% of children's total PM2.5 exposure dose, equivalent to an additional 2.6 µg/m3 per day. This study demonstrated the feasibility of peak analysis for quantifying SHS exposure. The developed method can be adopted more widely to support epidemiology studies on impacts of short-term exposures.

Personal exposure to PM2.5 constituents associated with gestational blood pressure and endothelial dysfunction

Ambient fine particulate matter (PM_2.5) pollution has been implicated in the development of hypertensive disorders of pregnancy. However, evidence on the effects of PM_2.5-derived chemical constituents on gestational blood pressure (BP) is limited, and the potential mechanisms underlying the association remain unclear. In this study, we repeated three consecutive 72-h personal air sampling and BP measurements in 215 pregnant women for 590 visits during pregnancy. Individual PM_2.5 exposure level was assessed by gravimetric method and 28 PM_2.5 chemical constituents were analyzed by ED-XRF method. Plasma biomarkers of endothelial function and inflammation were measured using multiplexed immunoassays. Robust multiple linear regression models were used to estimate the associations among personal PM_2.5 exposure and chemical constituents, BP changes (compared with pre-pregnancy BP) and plasma biomarkers. Mediation analyses were performed to evaluate underlying potential pathways. Result showed that exposure to PM_2.5 was significantly associated with increases in systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean arterial pressure (MAP) in the early second trimester. Meanwhile, elevated concentration of lead (Pb) constituent in PM_2.5 was significant associated with increases in DBP and MAP after adjusting for PM_2.5 total mass. PM_2.5 and Pb constituent also presented positive associations with plasma biomarkers of endothelial function (ET-1, E-selectin, ICAM-1) and inflammation (IL-1β, IL-6, TNFα) significantly. After multiple adjustment, elevated ET-1 and IL-6 were significantly correlated with increased gestational BP, and respectively mediated 1.24%-25.06% and 7.01%-10.69% of the increased BP due to PM_2.5 and Pb constituent exposure. In conclusion, our results suggested that personal exposure to PM_2.5 and Pb constituent were significantly associated with increased BP during pregnancy, and the early second trimester might be the sensitive window of PM_2.5 exposure. The endothelial dysfunction and elevated inflammation partially mediated the effect of PM_2.5 and Pb constituent on BP during pregnancy.

A review of the chemical and biological pollutants in indoor air in hospitals and assessing their effects on the health of patients, staff and visitors

Indoor air quality in hospitals has been specifically considered in terms of its impact on health. Air quality is an important risk factor influencing the health of staff and patients who are in contact with indoor air inhaled in hospitals. Over the past two decades, hundreds of studies have been developed to assess pollution in hospital environment. Two hundred and fitfy papers from around the world, from the last two decades, were identified and reviewed. Recent studies have found that the presence of various chemical and biological pollutants affected the health of patients, staff and visitors. Nearly all the reports agree that chemical and biological pollutants in the hospital environment have adverse effects. In most of the reviewed papers, analysis of health hazards was conducted for personnel and patients to toxic metals, chlorine, fine (PM2.5) and coarse (PM2.5−10) particles, and bio-aerosol in the inhaled air of the hospital environment. Some papers showed that some of the metals are carcinogens and others do not have a carcinogenic risk. Bio-aerosols as a biological pollutant are usually defined as airborne bacteria, fungi, viruses, pollen and their by products. These biological pollutants are associated with a wide range of health effects in hospital environments. This review can serve as an introduction and as the statement of the problem for more original research in this regard.

Characterizing Aggregated Exposure to Primary Particulate Matter: Recommended Intake Fractions for Indoor and Outdoor Sources

Exposure to fine particulate matter (PM_2.5) from indoor and outdoor sources is a leading environmental contributor to global disease burden. In response, we established under the auspices of the UNEP/SETAC Life Cycle Initiative a coupled indoor-outdoor emission-to-exposure framework to provide a set of consistent primary PM_2.5 aggregated exposure factors. We followed a matrix-based mass balance approach for quantifying exposure from indoor and ground-level urban and rural outdoor sources using an effective indoor-outdoor population intake fraction and a system of archetypes to represent different levels of spatial detail. Emission-to-exposure archetypes range from global indoor and outdoor averages, via archetypal urban and indoor settings, to 3646 real-world cities in 16 parametrized subcontinental regions. Population intake fractions from urban and rural outdoor sources are lowest in Northern regions and Oceania and highest in Southeast Asia with population-weighted means across 3646 cities and 16 subcontinental regions of, respectively, 39 ppm (95% confidence interval: 4.3-160 ppm) and 2 ppm (95% confidence interval: 0.2-6.3 ppm). Intake fractions from residential and occupational indoor sources range from 470 ppm to 62 000 ppm, mainly as a function of air exchange rate and occupancy. Indoor exposure typically contributes 80-90% to overall exposure from outdoor sources. Our framework facilitates improvements in air pollution reduction strategies and life cycle impact assessments.

The Association between Ambient Fine Particulate Air Pollution and Lung Cancer Incidence: Results from the AHSMOG-2 Study

BACKGROUND

There is a positive association between ambient fine particulate matter ≤ 2.5 μm in aerodynamic diameter (PM_2.5) and incidence and mortality of lung cancer (LC), but few studies have assessed the relationship between ambient PM_2.5 and LC among never smokers.

OBJECTIVES

We assessed the association between PM_2.5 and risk of LC using the Adventist Health and Smog Study-2 (AHSMOG-2), a cohort of health conscious nonsmokers where 81% have never smoked.

METHODS

A total of 80,285 AHSMOG-2 participants were followed for an average of 7.5 years with respect to incident LC identified through linkage with U.S. state cancer registries. Estimates of ambient air pollution levels at participants' residences were obtained for 2000 and 2001, the years immediately prior to the start of the study.

RESULTS

A total of 250 incident LC cases occurred during 598,927 person-years of follow-up. For each 10-μg/m³ increment in PM_2.5, adjusted hazard ratio (HR) with 95% confidence interval (CI) for LC incidence was 1.43 (95% CI: 1.11, 1.84) in the two-pollutant multivariable model with ozone. Among those who spent > 1 hr/day outdoors or who had lived 5 or more years at their enrollment address, the HR was 1.68 (95% CI: 1.28, 2.22) and 1.54 (95% CI: 1.17, 2.04), respectively.

CONCLUSION

Increased risk estimates of LC were observed for each 10-μg/m³ increment in ambient PM_2.5 concentration. The estimate was higher among those with longer residence at enrollment address and those who spent > 1 hr/day outdoors. Citation: Gharibvand L, Shavlik D, Ghamsary M, Beeson WL, Soret S, Knutsen R, Knutsen SF. 2017. The association between ambient fine particulate air pollution and lung cancer incidence: results from the AHSMOG-2 study. Environ Health Perspect 125:378-384; http://dx.doi.org/10.1289/EHP124.

Physiochemical characteristics of aerosol particles in the typical microenvironment of hospital in Shanghai, China

Health risk of populations dwelling in the hospital has been a global concern, but has not been adequately examined. PM_2.5 and PM₁ samples were collected in two indoor locations (outpatient department and inpatient department) and one outdoor location (courtyard) of the hospital in Shanghai. The concentrations of size-fractionated trace metals and the morphology of single particles were determined to accurately assess the health risk for populations in the hospital. The results indicated that the mean concentrations of PM_2.5 and PM₁ were in the order of outpatient department>courtyard>inpatient department. The mean concentrations of PM₁ decreased with floors (first floor: 78.0μg/m³, second floor: 64.1μg/m³, fourth floor: 48.4μg/m³). However, the mean PM_2.5 concentrations were in the order of first floor (124.0μg/m³)>fourth floor (91.4μg/m³)>second floor (90.6μg/m³), which was likely associated with the number of patients. The PM_2.5 and PM₁ concentrations have begun to increase rapidly from 9:00am and decreased after 15:00pm in the first floor, whereas they remain relatively stable in the second and fourth floor. The abundance of Mg, Ca, Al and K in the fine particles and coarse particles were both higher than other elements for all floors. The concentrations of trace metals (e.g., Zn, Ba, Fe, Mn, Cr, Ca, Ti, Na, and K) except Mg and Al in the coarse particles (>2.5μm) decreased with floors, whereas Zn, Ba, Fe, and Cr in the fine particles (<2.5μm) displayed opposite variation. Trace metals in the first floor were mainly concentrated in the >2.5μm and 1-2.5μm, whereas they chiefly peaked at 0.25-0.5μm and below 0.25μm in the second and fourth floor. Single particles analysis showed that mineral particles, soot, and Fe-rich particles were mainly concentrated in the first floor, indicating the impacts of walking of patients, traffic emissions, and food cooking, respectively. Sulfate particles were internally mixed with soot, fly ash and Fe-rich particles in the second floor, which suggested that these sulfate particles probably underwent aging processes during the atmospheric long-range transport. In the fourth floor, fly ash, sulfate particles, Zn-rich particles, and biogenic particles were identified under the transmission electron microscopy (TEM). Higher abundance of sulfates and absence of chlorate hinted existence of heterogeneous reactions during long-range transport with the Cl^- replaced by SO₄^2-. The index of average daily intake (ADI), hazard quotient (HQ), and carcinogenic risks (CR) indicated that Cr pose carcinogenic risks to the surrounding populations, while non-carcinogenic risks of Mn, Zn, and Cr were not remarkable.

Cooking-related PM2.5 and acrolein measured in grocery stores and comparison with other retail types

We measured particulate matter (PM), acrolein, and other indoor air contaminants in eight visits to grocery stores in California. Retail stores of other types (hardware, furniture, and apparel) were also sampled on additional visits. Based on tracer gas decay data, most stores had adequate ventilation according to minimum ventilation rate standards. Grocery stores had significantly higher concentrations of acrolein, fine and ultrafine PM, compared to other retail stores, likely attributable to cooking. Indoor concentrations of PM2.5 and acrolein exceeded health guidelines in all tested grocery stores. Acrolein emission rates to indoors in grocery stores had a mean estimate about 30 times higher than in other retail store types. About 80% of the indoor PM2.5 measured in grocery stores was emitted indoors, compared to only 20% for the other retail store types. Calculations suggest a substantial increase in outdoor air ventilation rate by a factor of three from current level is needed to reduce indoor acrolein concentrations. Alternatively, acrolein emission to indoors needs to be reduced 70% by better capturing of cooking exhaust. To maintain indoor PM2.5 below the California annual ambient standard of 12 μg/m(3) , grocery stores need to use air filters with an efficiency rating higher than the MERV 8 air filters commonly used today.

Detection of Common Respiratory Viruses and Mycoplasma pneumoniae in Patient-Occupied Rooms in Pediatric Wards

Few studies have assessed viral contamination in the rooms of hospital wards. This cross-sectional study evaluated the air and objects in patient-occupied rooms in pediatric wards for the presence of common respiratory viruses and Mycoplasma pneumoniae.Air samplers were placed at a short (60-80 cm) and long (320 cm) distance from the head of the beds of 58 pediatric patients, who were subsequently confirmed to be infected with enterovirus (n = 17), respiratory syncytial virus (RSV) (n = 13), influenza A virus (n = 13), adenovirus (n = 9), or M pneumoniae (n = 6). Swab samples were collected from the surfaces of 5 different types of objects in the patients' rooms. All air and swab samples were analyzed via real-time quantitative polymerase chain reaction assay for the presence of the above pathogens.All pathogens except enterovirus were detected in the air, on the objects, or in both locations in the patients' rooms. The detection rates of influenza A virus, adenovirus, and M pneumoniae for the long distance air sampling were 15%, 67%, and 17%, respectively. Both adenovirus and M pneumoniae were detected at very high rates, with high concentrations, on all sampled objects.The respiratory pathogens RSV, influenza A virus, adenovirus, and M pneumoniae were detected in the air and/or on the objects in the pediatric ward rooms. Appropriate infection control measures should be strictly implemented when caring for such patients.

Estimated effect of ventilation and filtration on chronic health risks in U.S. offices, schools, and retail stores

We assessed the chronic health risks from inhalation exposure to volatile organic compounds (VOCs) and particulate matter (PM2.5) in U.S. offices, schools, grocery, and other retail stores and evaluated how chronic health risks were affected by changes in ventilation rates and air filtration efficiency. Representative concentrations of VOCs and PM2.5 were obtained from available data. Using a mass balance model, changes in exposure to VOCs and PM2.5 were predicted if ventilation rate were to increase or decrease by a factor of two, and if higher efficiency air filters were used. Indoor concentrations were compared to health guidelines to estimate percentage exceedances. The estimated chronic health risks associated with VOC and PM2.5 exposures in these buildings were low relative to the risks from exposures in homes. Chronic health risks were driven primarily by exposures to PM2.5 that were evaluated using disease incidence of mortality, chronic bronchitis, and non-fatal stroke. The leading cancer risk factor was exposure to formaldehyde. Using disability-adjusted life years (DALYs) to account for both cancer and non-cancer effects, results suggest that increasing ventilation alone is ineffective at reducing chronic health burdens. Other strategies, such as pollutant source control and the use of particle filtration, should also be considered.

Applications of GPS-tracked personal and fixed-location PM(2.5) continuous exposure monitoring

Continued development of personal air pollution monitors is rapidly improving government and research capabilities for data collection. In this study, we tested the feasibility of using GPS-enabled personal exposure monitors to collect personal exposure readings and short-term daily PM2.5 measures at 15 fixed locations throughout a community. The goals were to determine the accuracy of fixed-location monitoring for approximating individual exposures compared to a centralized outdoor air pollution monitor, and to test the utility of two different personal monitors, the RTI MicroPEM V3.2 and TSI SidePak AM510. For personal samples, 24-hr mean PM2.5 concentrations were 6.93 μg/m³ (stderr = 0.15) and 8.47 μg/m³ (stderr = 0.10) for the MicroPEM and SidePak, respectively. Based on time-activity patterns from participant journals, exposures were highest while participants were outdoors (MicroPEM = 7.61 µg/m³, stderr = 1.08, SidePak = 11.85 µg/m³, stderr = 0.83) or in restaurants (MicroPEM = 7.48 µg/m³, stderr = 0.39, SidePak = 24.93 µg/m³, stderr = 0.82), and lowest when participants were exercising indoors (MicroPEM = 4.78 µg/m³, stderr = 0.23, SidePak = 5.63 µg/m³, stderr = 0.08). Mean PM(2.5) at the 15 fixed locations, as measured by the SidePak, ranged from 4.71 µg/m³ (stderr = 0.23) to 12.38 µg/m³ (stderr = 0.45). By comparison, mean 24-h PM(2.5) measured at the centralized outdoor monitor ranged from 2.7 to 6.7 µg/m³ during the study period. The range of average PM(2.5) exposure levels estimated for each participant using the interpolated fixed-location data was 2.83 to 19.26 µg/m³ (mean = 8.3, stderr = 1.4). These estimated levels were compared with average exposure from personal samples. The fixed-location monitoring strategy was useful in identifying high air pollution microclimates throughout the county. For 7 of 10 subjects, the fixed-location monitoring strategy more closely approximated individuals' 24-hr breathing zone exposures than did the centralized outdoor monitor. Highlights are: Individual PM(2.5) exposure levels vary extensively by activity, location and time of day; fixed-location sampling more closely approximated individual exposures than a centralized outdoor monitor; and small, personal exposure monitors provide added utility for individuals, researchers, and public health professionals seeking to more accurately identify air pollution microclimates.

IMPLICATIONS

Personal air pollution monitoring technology is advancing rapidly. Currently, personal monitors are primarily used in research settings, but could they also support government networks of centralized outdoor monitors? In this study, we found differences in performance and practicality for two personal monitors in different monitoring scenarios. We also found that personal monitors used to collect outdoor area samples were effective at finding pollution microclimates, and more closely approximated actual individual exposure than a central monitor. Though more research is needed, there is strong potential that personal exposure monitors can improve existing monitoring networks.

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

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

Air pollution and your brain: what do you need to know right now

Research links air pollution mostly to respiratory and cardiovascular disease. The effects of air pollution on the central nervous system (CNS) are not broadly recognized. Urban outdoor pollution is a global public health problem particularly severe in megacities and in underdeveloped countries, but large and small cities in the United States and the United Kingom are not spared. Fine and ultrafine particulate matter (UFPM) defined by aerodynamic diameter (<2.5-μm fine particles, PM2.5, and <100-nm UFPM) pose a special interest for the brain effects given the capability of very small particles to reach the brain. In adults, ambient pollution is associated to stroke and depression, whereas the emerging picture in children show significant systemic inflammation, immunodysregulation at systemic, intratechal and brain levels, neuroinflammation and brain oxidative stress, along with the main hallmarks of Alzheimer and Parkinson's diseases: hyperphosphorilated tau, amyloid plaques and misfolded α-synuclein. Animal models exposed to particulate matter components show markers of both neuroinflammation and neurodegeneration. Epidemiological, cognitive, behavioral and mechanistic studies into the association between air pollution exposures and the development of CNS damage particularly in children are of pressing importance for public health and quality of life. Primary health providers have to include a complete prenatal and postnatal environmental and occupational history to indoor and outdoor toxic hazards and measures should be taken to prevent or reduce further exposures.

Particle characterization in retail environments: concentrations, sources, and removal mechanisms

Particles in retail environments can have consequences for the occupational exposures of retail workers and customers, as well as the energy costs associated with ventilation and filtration. Little is known about particle characteristics in retail environments. We measured indoor and outdoor mass concentrations of PM10 and PM2.5 , number concentrations of submicron particles (0.02-1 μm), size-resolved 0.3-10 μm particles, as well as ventilation rates in 14 retail stores during 24 site visits in Pennsylvania and Texas. Overall, the results were generally suggestive of relatively clean environments when compared to investigations of other building types and ambient/occupational regulatory limits. PM10 and PM2.5 concentrations (mean ± s.d.) were 20 ± 14 and 11 ± 10 μg/m(3), respectively, with indoor-to-outdoor ratios of 1.0 ± 0.7 and 0.88 ± 1.0. Mean submicron particle concentrations were 7220 ± 7500 particles/cm(3) with an indoor-to-outdoor ratio of 1.18 ± 1.30. The median contribution to PM10 and PM2.5 concentrations from indoor sources (vs. outdoors) was 83% and 53%, respectively. There were no significant correlations between measured ventilation rates and particle concentrations of any size. When examining options to lower PM2.5 concentrations below regulatory limits, the required changes to ventilation and filtration efficiency were site specific and depended on the indoor and outdoor concentration, emission rate, and infiltration level.

PRACTICAL IMPLICATIONS

Little is known about particle concentrations, contribution of indoor sources, and emission rates in retail environments. Knowledge of these particle characteristics informs health scientists with input parameters to include in exposure modeling. The predicted concentration change in response to different ventilation rates and filtration efficiencies may be used for guidance to develop control strategies to lower particulate matter concentrations in retail environments.

Sources of indoor air pollution in New York City residences of asthmatic children

Individuals spend ∼90% of their time indoors in proximity to sources of particulate and gaseous air pollutants. The sulfur tracer method was used to separate indoor concentrations of particulate matter (PM) PM2.5 mass, elements and thermally resolved carbon fractions by origin in New York City residences of asthmatic children. Enrichment factors relative to sulfur concentrations were used to rank species according to the importance of their indoor sources. Mixed effects models were used to identify building characteristics and resident activities that contributed to observed concentrations. Significant indoor sources were detected for OC1, Cl, K and most remaining OC fractions. We attributed 46% of indoor PM2.5 mass to indoor sources related to OC generation indoors. These sources include cooking (NO2, Si, Cl, K, OC4 and OP), cleaning (most OC fractions), candle/incense burning (black carbon, BC) and smoking (K, OC1, OC3 and EC1). Outdoor sources accounted for 28% of indoor PM2.5 mass, mainly photochemical reaction products, metals and combustion products (EC, EC2, Br, Mn, Pb, Ni, Ti, V and S). Other indoor sources accounted for 26% and included re-suspension of crustal elements (Al, Zn, Fe, Si and Ca). Indoor sources accounted for ∼72% of PM2.5 mass and likely contributed to differences in the composition of indoor and outdoor PM2.5 exposures.

Trace metals in size-fractionated particulate matter in a Portuguese hospital: exposure risks assessment and comparisons with other countries

Hospitals are considered as a special and important type of indoor public place where air quality has significant impacts on potential health outcomes. Information on indoor air quality of these environments, concerning exposures to particulate matter (PM) and related toxicity, is limited though. This work aims to evaluate risks associated with inhalation exposure to ten toxic metals and chlorine (As, Ni, Cr, Cd, Pb, Mn, Se, Ba, Al, Si, and Cl) in coarse (PM2.5-10) and fine (PM2.5) particles in a Portuguese hospital in comparison with studies representative of other countries. Samples were collected during 1 month in one urban hospital; elemental PM characterization was determined by proton-induced X-ray emission. Noncarcinogenic and carcinogenic risks were assessed according to the methodology provided by the United States Environmental Protection Agency (USEPA; Region III Risk-Based Concentration Table) for three different age categories of hospital personnel (adults, >20, and <65 years) and patients (considering nine different age groups, i.e., children of 1-3 years to seniors of >65 years). The estimated noncarcinogenic risks due to occupational inhalation exposure to PM2.5-bound metals ranged from 5.88 × 10(-6) for Se (adults, 55-64 years) to 9.35 × 10(-1) for As (adults, 20-24 years) with total noncarcinogenic risks (sum of all metals) above the safe level for all three age categories. As and Cl (the latter due to its high abundances) were the most important contributors (approximately 90 %) to noncarcinogenic risks. For PM2.5-10, noncarcinogenic risks of all metals were acceptable to all age groups. Concerning carcinogenic risks, for Ni and Pb, they were negligible (<1 × 10(-6)) in both PM fractions for all age groups of hospital personnel; potential risks were observed for As and Cr with values in PM2.5 exceeding (up to 62 and 5 times, respectively) USEPA guideline across all age groups; for PM2.5-10, increased excess risks of As and Cr were observed particularly for long-term exposures (adults, 55-64 years). Total carcinogenic risks highly (up to 67 times) exceeded the recommended level for all age groups, thus clearly showing that occupational exposure to metals in fine particles pose significant risks. If the extensive working hours of hospital medical staff were considered, the respective noncarcinogenic and carcinogenic risks were increased, the latter for PM2.5 exceeding the USEPA cumulative guideline of 10(-4). For adult patients, the estimated noncarcinogenic and carcinogenic risks were approximately three times higher than for personnel, with particular concerns observed for children and adolescents.

Implementation and validation of a modeling framework to assess personal exposure to black carbon

Because people tend to move from one place to another during the day, their exposure to air pollution will be determined by the concentration at each location combined with the exposure encountered in transport. In order to estimate the exposure of individuals in a population more accurately, the activity-based modeling framework for Black Carbon exposure assessment, AB(2)C, was developed. An activity-based traffic model was applied to model the whereabouts of individual agents. Exposure to black carbon (BC) in different microenvironments is assessed with a land use regression model, combined with a fixed indoor/outdoor factor for exposure in indoor environments. To estimate exposure in transport, a separate model was used taking into account transport mode, timing of the trip and degree of urbanization. The modeling framework is validated using weeklong time-activity diaries and BC exposure as revealed from a personal monitoring campaign with 62 participants. For each participant in the monitoring campaign, a synthetic population of 100 model-agents per day was made up with all agents meeting similar preconditions as each real-life agent. When these model-agents pass through every stage of the modeling framework, it results in a distribution of potential exposures for each individual. The AB(2)C model estimates average personal exposure slightly more accurately compared to ambient concentrations as predicted for the home subzone; however the added value of a dynamic model lies in the potential for detecting short term peak exposures rather than modeling average exposures. The latter may bring new opportunities to epidemiologists: studying the effect of frequently repeated but short exposure peaks on long term exposure and health.