Windsor, Ontario Exposure Assessment Study: Design and Methods Validation of Personal, Indoor, and Outdoor Air Pollution Monitoring

Computational fluid dynamics-based optimal installation strategy of air purification system to minimize NOX exposure inside a public bus stop

At public bus stops, NO_X pollutants discharged by regularly stopping buses quickly accumulate, exposing waiting passengers to high levels of air pollutants, which creates a threat to public health. The environmental protection agency (EPA) presents air quality standards for NO_X, a significant pollutant that causes lung diseases such as asthma when exposed to the human body. To handle this problem, air purification systems are installed inside bus stops in many public places. However, it is challenging to maintain a low concentration of NO_X inside public bus stops due to the persistent inflow of bus exhaust gas. Therefore, it is crucial to design an optimal location for an air purification system to meet air environment standards for respiratory areas. This study proposed a computational fluid dynamics (CFD)-based optimal installation strategy for an air purification system to minimize NO_X exposure inside a public bus stop. The CFD model was developed to numerically analyze NO₂ exposure with the actual design value for a public bus stop in Ulsan, South Korea. The local NO₂ concentration was evaluated in the human breathing zone. The case study was performed according to the locations of the inlet and outlet of the air purification system. A transient CFD simulation was performed to analyze the effect of the air purification system on pollutants generated from the stationary bus by time flow in various cases. NO₂ concentration and exposure reduction effectiveness (ERE) were analyzed and compared for each case in the breathing zone. In the optimal case, the ERE of NO₂ was confirmed to be 35.9 %, and the NO₂ concentration according to the air quality standards of EPA could be maintained at 0.1 ppm or less. The theoretical framework proposed in this study can be generalized to design air purification systems for general external facilities.

Laboratory Chamber Evaluation of Flow Air Quality Sensor PM2.5 and PM10 Measurements

The emergence of low-cost air quality sensors as viable tools for the monitoring of air quality at population and individual levels necessitates the evaluation of these instruments. The Flow air quality tracker, a product of Plume Labs, is one such sensor. To evaluate these sensors, we assessed 34 of them in a controlled laboratory setting by exposing them to PM₁₀ and PM_2.5 and compared the response with Plantower A003 measurements. The overall coefficient of determination (R²) of measured PM_2.5 was 0.76 and of PM₁₀ it was 0.73, but the Flows’ accuracy improved after each introduction of incense. Overall, these findings suggest that the Flow can be a useful air quality monitoring tool in air pollution areas with higher concentrations, when incorporated into other monitoring frameworks and when used in aggregate. The broader environmental implications of this work are that it is possible for individuals and groups to monitor their individual exposure to particulate matter pollution.

An Investigation into Which Methods Best Explain Children’s Exposure to Traffic-Related Air Pollution

There have been several methods employed to quantify individual-level exposure to ambient traffic-related air pollutants (TRAP). These include an individual’s residential proximity to roads, measurement of individual pollutants as surrogates or markers, as well as dispersion and land use regression (LUR) models. Hopanes are organic compounds still commonly found on ambient particulate matter and are specific markers of combustion engine primary emissions, but they have not been previously used in personal exposure studies. In this paper, children’s personal exposures to TRAP were evaluated using hopanes determined from weekly integrated filters collected as part of a personal exposure study in Windsor, Canada. These hopane measurements were used to evaluate how well other commonly used proxies of exposure to TRAP performed. Several of the LUR exposure estimates for a range of air pollutants were associated with the children’s summer personal hopane exposures (r = 0.41–0.74). However, all personal hopane exposures in summer were more strongly associated with the length of major roadways within 500 m of their homes. In contrast, metrics of major roadways and LUR estimates were poorly correlated with any winter personal hopanes. Our findings suggest that available TRAP exposure indicators have the potential for exposure misclassification in winter vs. summer and more so for LUR than for metrics of major road density. As such, limitations are evident when using traditional proxy methods for assigning traffic exposures and these may be especially important when attempting to assign exposures for children’s key growth and developmental windows. If long-term chronic exposures are being estimated, our data suggest that measures of major road lengths in proximity to homes are a more-specific approach for assigning personal TRAP exposures.

A review and analysis of personal and ambient PM2.5 measurements: Implications for epidemiology studies

BACKGROUND

In epidemiology studies, ambient measurements of PM_2.5 are often used as surrogates for personal exposures. However, it is unclear the degree to which ambient PM_2.5 reflects personal exposures.

OBJECTIVE

In order to examine potential sources of bias in epidemiology studies, we conducted a review and meta-analysis of studies to determine the extent to which short-term measurements of ambient PM_2.5 levels are related to short-term measurements of personal PM_2.5 levels.

METHODS

We conducted a literature search of studies reporting both personal and ambient measurements of PM_2.5 published in the last 10 years (2009-2019) and incorporated studies published prior to 2009 from reviews.

RESULTS

Seventy-one studies were identified. Based on 17 studies reporting slopes, a meta-analysis revealed an overall slope of 0.56 μg/m³ (95% CI: [0.39, 0.73]) personal PM_2.5 per μg/m³ increase in ambient PM_2.5. Slopes for summer months were higher (slope = 0.73, 95% CI: [0.64, 0.81]) than for winter (slope = 0.46, 95% CI: [0.36, 0.57]). Based on 44 studies reporting correlations, we calculated an overall personal-ambient PM_2.5 correlation of 0.63 (95% CI: [0.55, 0.71]). Correlations were stronger in studies conducted in Canada (r = 0.86, 95% CI: [0.67, 0.94]) compared to the USA (r = 0.60, 95% CI: [0.49, 0.70]) and China (r = 0.60, 95% CI: [0.46, 0.71]). Correlations also were stronger in urban areas (r = 0.53, 95% CI: [0.43, 0.62]) vs. suburban areas (r = 0.36, 95% CI: [0.21, 0.49]).

SIGNIFICANCE

Our results suggest a large degree of variability in the personal-ambient PM_2.5 association and the potential for exposure misclassification and measurement error in PM_2.5 epidemiology studies.

Household determinants of biocontaminant exposures in Canadian homes

Exposure to biocontaminants, such as dust mites, animal dander, bacteria, and mold, is associated with a range of health effects. This study identified household characteristics associated with indoor biocontaminant loadings in four Canadian cities. Floor dust was collected in 290 Canadian homes in Edmonton, Halifax, Montreal, and Windsor. The dust samples were analyzed for house dust mite allergens (Der f 1 and Der p 1), cat allergen (Fel d 1), cockroach allergen (Bla g 1), beta-(1,3)-D-glucan, and endotoxin. Household information was obtained through questionnaires and home inspections. We performed univariate and multivariate analyses to identify household determinants of biocontaminant loadings and mold odor presence. We observed large regional variations for all biocontaminants, except for cockroach allergen. The ranges of the contaminants measured in loadings and concentrations were similar to that of previous Canadian studies. Household characteristics including presence of carpeting, low floor cleaning frequency, older home age, presence of pets, and indoor relative humidity above 45% were positively associated with the presence of multiple indoor biocontaminants. High floor cleaning frequency and use of dehumidifiers were negatively associated with the presence of multiple indoor biocontaminants. Mold odor was positively associated with older home age, past water damage, and visible mold growth.

Personal black carbon and ultrafine particles exposures among high school students in urban China

Air pollution is a major public health challenge in the highly urbanized megacities of China. However, knowledge on exposure to ambient unregulated air pollutants such as black carbon (BC) and ultrafine particles (UFP) among the Chinese population, especially among urban high school students who may have highly variable time-activity patterns, is scarce. To address this, the personal exposures to BC and UFP of high school students (aged 17 to 18) in Chengdu, China were measured at 1-min intervals via portable samplers. Monitoring lasted for 2 consecutive 24-h periods with days classified as "school days" or "non-school days". Time-activity diaries and measurements were combined to explore spatial, temporal, and behavioral factors that contribute to different exposure profiles. The overall geometric means of BC and UFP were 3.60 μg/m³ and 1.83 × 10⁴p/cm³, respectively with notable spatiotemporal variation in exposures observed. In general, the household and transport microenvironments were the predominant contributors to total BC (74.5%) and UFP (36.5%) exposure. However, the outdoor public microenvironment was found to have significantly higher overall average levels of BC than the household and transport microenvironments (p < 0.001) while also presenting the greatest exposure dose intensity (EDI - a measure of exposure in a microenvironment in proportion to time spent in that environment) of 4.79. The largest overall average level of UFP occurred in the indoor public microenvironment followed by transport. The outdoor public microenvironment also presented the greatest EDI of UFP (4.17). This study shows notable spatiotemporal variety in exposure patterns and will inform future exposure and population health studies. The high EDI outdoors may mean that health positive activities, such as exercise, may be being undermined by ambient pollution.

Associations Between Sub-Clinical Markers of Cardiometabolic Risk and Exposure to Residential Indoor Air Pollutants in Healthy Adults in Perth, Western Australia: A Study Protocol

BACKGROUND

A growing body of epidemiological and clinical evidence has implicated air pollution as an emerging risk factor for cardiometabolic disease. Whilst individuals spend up to two-thirds of daily time in their domestic residential environment, very few studies have been designed to objectively measure the sub-clinical markers of cardiometabolic risk with exposure to domestic indoor air pollutants. This cross-sectional study aims to investigate associations between the components of domestic indoor air quality and selected sub-clinical cardiometabolic risk factors in a cohort of healthy adults living in Perth, Western Australia.

METHODS

One hundred and eleven non-smoking adults (65% female) living in non-smoking households who were aged between 35-69 years were recruited for the project. Study subjects were invited to participate in all sections of the study, which included: Domestic indoor air monitoring along with the concurrent 24 h ambulatory monitoring of peripheral and central blood pressure and measures of central hemodynamic indices, standardized questionnaires on aspects relating to current health status and the domestic environment, a 24 h time-activity diary during the monitoring period, and clinic-based health assessment involving collection of blood and urine biomarkers for lipid and glucose profiles, as well as measures of renal function and an analysis of central pulse wave and pulse wave velocity.

RESULTS

This study provides a standardized approach to the study of sub-clinical cardiometabolic health effects that are related to the exposure to indoor air pollution.

CONCLUSION

The findings of this study may provide direction for future research that will further contribute to our understanding of the relationship that exists between indoor air pollution and sub-clinical markers of cardiometabolic risk.

Characterization of a High PM2.5 Exposure Group in Seoul Using the Korea Simulation Exposure Model for PM2.5 (KoSEM-PM) Based on Time⁻Activity Patterns and Microenvironmental Measurements

The Korea Simulation Exposure Model for fine particulate matter (PM_2.5) (KoSEM-PM) was developed to estimate population PM_2.5 exposure in Korea. The data were acquired based on 59,945 min of the actual microenvironmental PM_2.5 measurements and on the time–activity patterns of 8072 residents of Seoul. The aims of the study were to estimate daily PM_2.5 exposure of Seoul population, and to determine the characteristics of a high exposure group. KoSEM-PM estimated population exposures by applying the PM_2.5 distribution to the matching time–activity patterns at 10-min intervals. The mean personal PM_2.5 exposure level of the surveyed subjects in Seoul was 26.0 ± 2.7 µg/m³ (range: 21.0–40.2 µg/m³) in summer. Factors significantly associated with high exposure included day of the week, age, industry sector, job type, and working hours. Individuals surveyed on Saturdays were more likely to be in the high exposure group than those surveyed on weekdays and Sundays. Younger, non-office-working individuals with longer working hours were more likely to be in the high exposure group. KoSEM-PM could be a useful tool to estimate population exposure levels to other region in Korea; to expand its use, microenvironmental measurements are required for other region in Korea.

Elemental analysis of infant airborne particulate exposures

Air pollution is hypothesized to have negative impacts on infant pulmonary health because of infants' increased rates of respiration and ongoing lung development. The severity and type of impact may differ depending on elemental concentrations. We conducted a study of 21 infants <6 months old whose parents carried a small personal particulate monitoring device (RTI MicroPEM) and GPS unit with the infant for 7 days in January and February 2015. The study area was Utah County, UT, USA. Real-time particulate exposure levels, as well as optical density and elemental analysis of the particulate matter (PM), were compared with levels from an outdoor stationary monitor. Infants spent an average of 87.4% of their time indoors. PM levels varied widely by infant and time of day (average=19.07 μg/m³, range=0.63-170.25 μg/m³). Infant particulate exposures were not well approximated by the outdoor monitor. Infants had lower exposures to Sb, Mn, Pb, W and Fe than the outdoor monitor and higher exposures to Cd, Ni and Na. Differences were most pronounced for Na. Brown carbon was only detected by personal monitors and not by the outdoor monitor. Further research is needed to understand the potential implications of indoor elemental exposures on early respiratory development.

Comparison of particulate matter exposure estimates in young children from personal sampling equipment and a robotic sampler

Accurate characterization of particulate matter (PM) exposure in young children is difficult, because personal samplers are often too heavy, bulky or impractical to be used. The Pretoddler Inhalable Particulate Environmental Robotic (PIPER) sampler was developed to help address this problem. In this study, we measured inhalable PM exposures in 2-year-olds via a lightweight personal sampler worn in a small backpack and evaluated the use of a robotic sampler with an identical sampling train for estimating PM exposure in this age group. PM mass concentrations measured by the personal sampler ranged from 100 to almost 1,200 μg/m³, with a median value of 331 μg/m³. PM concentrations measured by PIPER were considerably lower, ranging from 14 to 513 μg/m³ with a median value of 56 μg/m³. Floor cleaning habits and activity patterns of the 2-year-olds varied widely by home; vigorous play and recent floor cleaning were most associated with higher personal exposure. Our findings highlight the need for additional characterization of children's activity patterns and their effect on personal exposures.

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.

Estimation of bias with the single-zone assumption in measurement of residential air exchange using the perfluorocarbon tracer gas method

Residential air exchange rates (AERs) are vital in understanding the temporal and spatial drivers of indoor air quality (IAQ). Several methods to quantify AERs have been used in IAQ research, often with the assumption that the home is a single, well-mixed air zone. Since 2005, Health Canada has conducted IAQ studies across Canada in which AERs were measured using the perfluorocarbon tracer (PFT) gas method. Emitters and detectors of a single PFT gas were placed on the main floor to estimate a single-zone AER (AER(1z)). In three of these studies, a second set of emitters and detectors were deployed in the basement or second floor in approximately 10% of homes for a two-zone AER estimate (AER(2z)). In total, 287 daily pairs of AER(2z) and AER(1z) estimates were made from 35 homes across three cities. In 87% of the cases, AER(2z) was higher than AER(1z). Overall, the AER(1z) estimates underestimated AER(2z) by approximately 16% (IQR: 5-32%). This underestimate occurred in all cities and seasons and varied in magnitude seasonally, between homes, and daily, indicating that when measuring residential air exchange using a single PFT gas, the assumption of a single well-mixed air zone very likely results in an under prediction of the AER.

PRACTICAL IMPLICATIONS

The results of this study suggest that the long-standing assumption that a home represents a single well-mixed air zone may result in a substantial negative bias in air exchange estimates. Indoor air quality professionals should take this finding into consideration when developing study designs or making decisions related to the recommendation and installation of residential ventilation systems.

The IVAIRE project--a randomized controlled study of the impact of ventilation on indoor air quality and the respiratory symptoms of asthmatic children in single family homes

A randomized controlled trial was carried out to measure the impact of an intervention on ventilation, indoor air contaminants, and asthma symptoms of children. Eighty-three asthmatic children living in low-ventilated homes were followed over 2 years. Several environmental parameters were measured during the summer, fall, and winter. The children were randomized after Year 1 (43 Intervention; 40 Control). The intervention included the installation of either a Heat Recovery Ventilator (HRV) or Energy Recovery Ventilator (ERV). During the fall and winter seasons, there was a significant increase in the mean ventilation rate in the homes of the intervention group. A statistically significant reduction in mean formaldehyde, airborne mold spores, toluene, styrene, limonene, and α-pinene concentrations was observed in the intervention group. There was no significant group difference in change in the number of days with symptoms per 14 days. However, there was a significant decrease in the proportion of children who experienced any wheezing (≥1 episode) and those with ≥4 episodes in the 12-month period in the intervention group. This study indicates that improved ventilation reduces air contaminants and may prevent wheezing. Due to lack of power, a bigger study is needed.

PRACTICAL IMPLICATIONS

Positive findings from this study include the fact that, upon recruitment, most of the single family homes with asthmatic children were already equipped with a mechanical ventilation system and had relatively good indoor air quality. However, the 8-h indoor guideline for formaldehyde (50 μg/m3) was frequently exceeded and the ventilation rates were low in most of the homes, even those with a ventilation system. Both ERVs and HRVs were equally effective at increasing air exchange rates above 0.30 ACH and at preventing formaldehyde concentrations from exceeding the 50 μg/m3 guideline during the fall and winter seasons. Furthermore, the ERVs were effective at preventing excessively low relative humidities in the homes. Based on observed difference of risk, intervention to increase ventilation in five sample homes and children would prevent 1 home to exceed the indoor air long-term formaldehyde guideline and prevent 1 asthmatic child experiencing at least one episode of wheezing over a year.

Estimating risk of emergency room visits for asthma from personal versus fixed site measurements of NO2

BACKGROUND

We examined the impact of data source and exposure measurement error for ambient NO2 on risk estimates derived from a case-crossover study of emergency room visits for asthma in Windsor, Canada between 2002 and 2009.

METHODS

Paired personal and fixed-site NO2 data were available from an independent population (47 children and 48 adults) in Windsor between 2005 and 2006. We used linear regression to estimate the relationship and measurement error variance induced between fixed site and personal measurements of NO2, and through a series of simulations, evaluated the potential for a Bayesian model to adjust for this change in scale and measurement error. Finally, we re-analyzed data from the previous case-crossover study adjusting for the estimated change in slope and measurement error.

RESULTS

Correlations between paired NO2 measurements were weak (R(2)≤0.08) and slopes were far from unity (0.0029≤β≤0.30). Adjusting the previous case-crossover analysis suggested a much stronger association between personal NO2 (per 1ppb) (Odds Ratio (OR)=1.276, 95% Credible Interval (CrI): 1.034, 1.569) and emergency room visits for asthma among children relative to the fixed-site estimate (OR=1.024, 95% CrI 1.004-1.045).

CONCLUSIONS

Our findings suggest that risk estimates based on fixed-site NO2 concentrations may differ substantially from estimates based on personal exposures if the change in scale and/or measurement error is large. In practice, one must always keep the scale being used in mind when interpreting risk estimates and not assume that coefficients for ambient concentrations reflect risks at the personal level.

Fifteen-year trends in criteria air pollutants in oil sands communities of Alberta, Canada

An investigation of ambient air quality was undertaken at three communities within the Athabasca Oil Sands Region (AOSR) of Alberta, Canada (Fort McKay, Fort McMurray, and Fort Chipewyan). Daily and seasonal patterns and 15-year trends were investigated for several criteria air pollutants over the period of 1998 to 2012. A parametric trend detection method using percentiles from frequency distributions of 1h concentrations for a pollutant during each year was used. Variables representing 50th, 65th, 80th, 90th, 95th and 98th percentile concentrations each year were identified from frequency distributions and used for trend analysis. Small increasing concentration trends were observed for nitrogen dioxide (<1ppb/year) at Fort McKay and Fort McMurray over the period consistent with increasing emissions of oxides of nitrogen (ca. 1000tons/year) from industrial developments. Emissions from all oil sands facilities appear to be contributing to the trend at Fort McKay, whereas both emissions from within the community (vehicles and commercial) and oil sands facility emissions appear to be contributing to the trend at Fort McMurray. Sulfur dioxide (SO2) emissions from industrial developments in the AOSR were unchanged during the period (101,000±7000tons/year; mean±standard deviation) and no meaningful trends were judged to be occurring at all community stations. No meaningful trends occurred for ozone and fine particulate matter (PM2.5) at all community stations and carbon monoxide at one station in Fort McMurray. Air quality in Fort Chipewyan was much better and quite separate in terms of absence of factors influencing criteria air pollutant concentrations at the other community stations.

Geospatial relationships of air pollution and acute asthma events across the Detroit-Windsor international border: study design and preliminary results

The Geospatial Determinants of Health Outcomes Consortium (GeoDHOC) study investigated ambient air quality across the international border between Detroit, Michigan, USA and Windsor, Ontario, Canada and its association with acute asthma events in 5- to 89-year-old residents of these cities. NO2, SO2, and volatile organic compounds (VOCs) were measured at 100 sites, and particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) at 50 sites during two 2-week sampling periods in 2008 and 2009. Acute asthma event rates across neighborhoods in each city were calculated using emergency room visits and hospitalizations and standardized to the overall age and gender distribution of the population in the two cities combined. Results demonstrate that intra-urban air quality variations are related to adverse respiratory events in both cities. Annual 2008 asthma rates exhibited statistically significant positive correlations with total VOCs and total benzene, toluene, ethylbenzene and xylene (BTEX) at 5-digit zip code scale spatial resolution in Detroit. In Windsor, NO2, VOCs, and PM10 concentrations correlated positively with 2008 asthma rates at a similar 3-digit postal forward sortation area scale. The study is limited by its coarse temporal resolution (comparing relatively short term air quality measurements to annual asthma health data) and interpretation of findings is complicated by contrasts in population demographics and health-care delivery systems in Detroit and Windsor.

Associations between personal exposure to air pollutants and lung function tests and cardiovascular indices among children with asthma living near an industrial complex and petroleum refineries

OBJECTIVE

The acute cardiorespiratory effects of air quality among children living in areas with considerable heavy industry have not been well investigated. We conducted a panel study of children with asthma living in proximity to an industrial complex housing two refineries in Montreal, Quebec, in order to assess associations between their personal daily exposure to air pollutants and changes in pulmonary function and selected indicators of cardiovascular health.

METHODS

Seventy-two children with asthma age 7-12 years in 2009-2010 participated in this panel study for a period of 10 consecutive days. They carried a small backpack for personal monitoring of sulphur dioxide (SO2), benzene, fine particles (PM2.5), nitrogen dioxide (NO2) and polycyclic aromatic hydrocarbons (PAHs) and underwent daily spirometry and cardiovascular testing (blood pressure, pulse rate and oxygen saturation). To estimate these associations, we used mixed regression models, adjusting for within-subject serial correlation, and for the effects of a number of personal and environmental variables (e.g., medication use, ethnicity, temperature).

RESULTS

Children with asthma involved in the study had relatively good pulmonary function test results (mean FEV1 compared to standard values: 89.8%, mean FVC: 97.6%, mean FEF25-75: 76.3%). Median diastolic, systolic blood pressures and oxygen saturation were 60/94 mmHg and 99%, respectively. Median personal concentrations of pollutants were NO2, 5.5 ppb; benzene, 2.1 µg/m(3); PM2.5, 5.7 µg/m(3); and total PAH, 130 µg/m(3). Most personal concentrations of SO2 were below the level of detection. No consistent associations were observed between cardio-pulmonary indices and personal exposure to PM2.5, NO2 and benzene, although there was a suggestion for a small decrease in respiratory function with total concentrations of PAHs (e.g., adjusted association with FVC: -9.9 ml per interquartile range 95%CI: -23.4, 3.7).

CONCLUSIONS

This study suggests that at low daily average levels of exposure to industrial emissions, effects on pulmonary and cardiovascular functions in children with asthma may be difficult to detect over 10 consecutive days.

Impact of microenvironments and personal activities on personal PM2.5 exposures among asthmatic children

Personal activity patterns have often been suggested as a source of unexplained variability when comparing personal particulate matter (PM2.5) exposure to modeled data using central site or microenvironmental data. To characterize the effect of personal activity patterns on asthmatic children's personal PM2.5 exposure, data from the Windsor, Ontario Exposure Assessment Study were analyzed. The children spent on an average 67.1±12.7% (winter) and 72.3±22.6% (summer) of their time indoors at home where they received 51.7±14.8% and 66.3±19.0% of their PM2.5 exposure, respectively. In winter, 17.7±5.9% of their time was spent at school where they received 38.6±11.7% of their PM2.5 exposure. In summer, they spent 10.3±11.8% 'indoors away from home', which represented 23.4±18.3% of their PM2.5 exposure. Personal activity codes adapted from those of the National Human Activity Pattern Survey and the Canadian Human Activity Pattern Survey were assigned to the children's activities. Of the over 100 available activity codes, 19 activities collectively encompassed nearly 95% of their time. Generalized estimating equation (GEE) models found that, while indoors at home, relative to daytime periods when sedentary activities were conducted, several personal activities were associated with significantly elevated personal PM2.5 exposures. Indoor playing represented a mean increase in PM2.5 of 10.1 μg/m(3) (95% CI 6.3-13.8) and 11.6 μg/m(3) (95% CI 8.1-15.1) in winter and summer, respectively, as estimated by a personal nephelometer.

A new exposure metric for traffic-related air pollution? An analysis of determinants of hopanes in settled indoor house dust

BACKGROUND

Exposure to traffic-related air pollution (TRAP) can adversely impact health but epidemiologic studies are limited in their abilities to assess long-term exposures and incorporate variability in indoor pollutant infiltration.

METHODS

In order to examine settled house dust levels of hopanes, engine lubricating oil byproducts found in vehicle exhaust, as a novel TRAP exposure measure, dust samples were collected from 171 homes in five Canadian cities and analyzed by gas chromatography-mass spectrometry. To evaluate source contributions, the relative abundance of the highest concentration hopane monomer in house dust was compared to that in outdoor air. Geographic variables related to TRAP emissions and outdoor NO2 concentrations from city-specific TRAP land use regression (LUR) models were calculated at each georeferenced residence location and assessed as predictors of variability in dust hopanes.

RESULTS

Hopanes relative abundance in house dust and ambient air were significantly correlated (Pearson's r=0.48, p<0.05), suggesting that dust hopanes likely result from traffic emissions. The proportion of variance in dust hopanes concentrations explained by LUR NO2 was less than 10% in Vancouver, Winnipeg and Toronto while the correlations in Edmonton and Windsor explained 20 to 40% of the variance. Modeling with household factors such as air conditioning and shoe removal along with geographic predictors related to TRAP generally increased the proportion of explained variability (10-80%) in measured indoor hopanes dust levels.

CONCLUSIONS

Hopanes can consistently be detected in house dust and may be a useful tracer of TRAP exposure if determinants of their spatiotemporal variability are well-characterized, and when home-specific factors are considered.

Development of temporally refined land-use regression models predicting daily household-level air pollution in a panel study of lung function among asthmatic children

Regulatory monitoring data and land-use regression (LUR) models have been widely used for estimating individual exposure to ambient air pollution in epidemiologic studies. However, LUR models lack fine-scale temporal resolution for predicting acute exposure and regulatory monitoring provides daily concentrations, but fails to capture spatial variability within urban areas. This study coupled LUR models with continuous regulatory monitoring to predict daily ambient nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) at 50 homes in Windsor, Ontario. We compared predicted versus measured daily outdoor concentrations for 5 days in winter and 5 days in summer at each home. We also examined the implications of using modeled versus measured daily pollutant concentrations to predict daily lung function among asthmatic children living in those homes. Mixed effect analysis suggested that temporally refined LUR models explained a greater proportion of the spatial and temporal variance in daily household-level outdoor NO(2) measurements compared with daily concentrations based on regulatory monitoring. Temporally refined LUR models captured 40% (summer) and 10% (winter) more of the spatial variance compared with regulatory monitoring data. Ambient PM(2.5) showed little spatial variation; therefore, daily PM(2.5) models were similar to regulatory monitoring data in the proportion of variance explained. Furthermore, effect estimates for forced expiratory volume in 1 s (FEV(1)) and peak expiratory flow (PEF) based on modeled pollutant concentrations were consistent with effects based on household-level measurements for NO(2) and PM(2.5). These results suggest that LUR modeling can be combined with continuous regulatory monitoring data to predict daily household-level exposure to ambient air pollution. Temporally refined LUR models provided a modest improvement in estimating daily household-level NO(2) compared with regulatory monitoring data alone, suggesting that this approach could potentially improve exposure estimation for spatially heterogeneous pollutants. These findings have important implications for epidemiologic studies - in particular, for research focused on short-term exposure and health effects.

Assessing the spatial distribution of nitrogen dioxide in London, Ontario

Land use regression (LUR) models have been widely used to characterize the spatial distribution of urban air pollution and estimate exposure in epidemiologic studies. However, spatial patterns of air pollution vary greatly between cities due to local source type and distribution. London, Ontario, Canada, is a medium-sized city with relatively few and isolated industrial point sources, which allowed the study to focus on the contribution of different transportation sectors to urban air pollution. This study used LUR models to estimate the spatial distribution of nitrogen dioxide (NO2) and to identify local sources influencing NO2 concentrations in London, ON. Passive air sampling was conducted at 50 locations throughout London over a 2-week period in May-June 2010. NO2 concentrations at the monitored locations ranged from 2.8 to 8.9 ppb, with a median of 5.2 ppb. Industrial land use, dwelling density, distance to highway, traffic density, and length of railways were significant predictors of NO2 concentrations in the final LUR model, which explained 78% of NO2 variability in London. Traffic and dwelling density explained most of the variation in NO2 concentrations, which is consistent with LUR models developed in other Canadian cities. We also observed the importance of local characteristics. Specifically, 17% of the variation was explained by distance to highways, which included the impacts of heavily traveled corridors transecting the southern periphery of the city. Two large railway yards and railway lines throughout central areas of the city explained 9% of NO2 variability. These results confirm the importance of traditional LUR variables and highlight the importance of including a broader array of local sources in LUR modeling. Finally, future analyses will use the model developed in this study to investigate the association between ambient air pollution and cardiovascular disease outcomes, including plaque burden, cholesterol, and hypertension.

New approach for particulate exposure monitoring: determination of inhaled particulate mass by 24 h real-time personal exposure monitoring

The objectives of this study were to measure particulate pollution (PM(10), PM(2.5), and PM(1.0)) continuously (24 h/day for 7 day) using real-time exposure monitoring and to estimate total inhalation mass using breathing rate and time-activity. Breathing rates were calculated from measured heart rates. Participants were asked to record a time-activity diary every 15 min. Five microenvironments were defined based on the time-activity diary: home, workplace/school, other indoor, outdoor, and transportation. The average masses of inhaled PM(10) were 530, 316, and 280 μg/day for two office workers, a housewife, and three students, respectively; those of PM(2.5) were 316, 279, and 210 μg/day; and those of PM(1.0) were 251, 264, and 187 μg/day, respectively. We found that home and office/school microenvironments were the main contributors of PM(10), PM(2.5), and PM(1.0) inhaled mass during weekdays and weekends because dwelling time was a determinant factor for inhaled mass. Considering microenvironmental concentration, breathing rate, and dwelling time in each microenvironment, indoor home microenvironments were the largest source of particulate inhalation, followed in order by workplace, transportation, other indoor, and outdoor microenvironments. 34.6% and 69.6% of PM(10) inhalation mass were accumulated in home microenvironments during weekdays and weekends, respectively. The inhaled mass of particulate <1.0 μm (PM(1.0)) in size occupied largest, followed in order by particulate 10-2.5 μm (coarse particle) and 2.5-1.0 μm in size for all occupations.