Keith Van Ryswyk

Validation of continuous particle monitors for personal, indoor, and outdoor exposures

Continuous monitors can be used to supplement traditional filter-based methods of determining personal exposure to air pollutants. They have the advantages of being able to identify nearby sources and detect temporal changes on a time scale of a few minutes. The Windsor Ontario Exposure Assessment Study (WOEAS) adopted an approach of using multiple continuous monitors to measure indoor, outdoor (near-residential) and personal exposures to PM2.5, ultrafine particles and black carbon. About 48 adults and households were sampled for five consecutive 24-h periods in summer and winter 2005, and another 48 asthmatic children for five consecutive 24-h periods in summer and winter 2006. This article addresses the laboratory and field validation of these continuous monitors. A companion article (Wheeler et al., 2010) provides similar analyses for the 24-h integrated methods, as well as providing an overview of the objectives and study design. The four continuous monitors were the DustTrak (Model 8520, TSI, St. Paul, MN, USA) and personal DataRAM (pDR) (ThermoScientific, Waltham, MA, USA) for PM2.5; the P-Trak (Model 8525, TSI) for ultrafine particles; and the Aethalometer (AE-42, Magee Scientific, Berkeley, CA, USA) for black carbon (BC). All monitors were tested in multiple co-location studies involving as many as 16 monitors of a given type to determine their limits of detection as well as bias and precision. The effect of concentration and electronic drift on bias and precision were determined from both the collocated studies and the full field study. The effect of rapid changes in environmental conditions on switching an instrument from indoor to outdoor sampling was also studied. The use of multiple instruments for outdoor sampling was valuable in identifying occasional poor performance by one instrument and in better determining local contributions to the spatial variation of particulate pollution. Both the DustTrak and pDR were shown to be in reasonable agreement (R2 of 90 and 70%, respectively) with the gravimetric PM2.5 method. Both instruments had limits of detection of about 5 μg/m3. The DustTrak and pDR had multiplicative biases of about 2.5 and 1.6, respectively, compared with the gravimetric samplers. However, their average bias-corrected precisions were <10%, indicating that a proper correction for bias would bring them into very good agreement with standard methods. Although no standard methods exist to establish the bias of the Aethalometer and P-Trak, the precision was within 20% for the Aethalometer and within 10% for the P-Trak. These findings suggest that all four instruments can supply useful information in environmental studies.

Personal, Indoor, and Outdoor Concentrations of Fine and Ultrafine Particles Using Continuous Monitors in Multiple Residences

Concentrations of airborne continuous fine particulate matter or (PM2.5), black carbon (BC), and ultrafine particles (UFP) were continuously measured over 5 days in winter and summer both indoors and outdoors at residences for forty-eight adults in 2005 and forty-seven asthmatic children in 2006. During 2006, personal concentrations of PM2.5 were also measured continuously. All 4 continuous instruments employed performed well both in laboratory and field conditions. Mean outdoor concentrations of PM2.5, BC, and UFP were significantly higher than either indoor or personal concentrations. Air exchange rates were low (median value only 0.2/h), there was widespread use of central forced air and high-quality furnace filters. Outdoor concentrations of all particle-related pollutants showed overnight decreases followed by increases during the morning rush hours. Afternoon concentrations increased for UFP and decreased for BC, with PM2.5 staying about the same. Between 5:00 pm and 7:00 pm, indoor UFP and PM2.5 concentrations exceeded their mean daily values by 160% and 60%, respectively, suggesting that cooking is an extremely important source for these two pollutants. However, BC values did not increase at these hours. The highest indoor–outdoor ratios were observed for UFP suggesting that indoor sources were relatively more important for UFP than for other particle components. BC measurements in Windsor agreed moderately well (R2 = 41%) with an independent measure of elemental carbon (EC) in Detroit. This large residential air pollution study has provided data making it possible to identify short-term variations and possible sources that can influence the relationships between pollutants and environments.

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

ABSTRACT The Windsor, Ontario Exposure Assessment Study evaluated the contribution of ambient air pollutants to personal and indoor exposures of adults and asthmatic children living in Windsor, Ontario, Canada. In addition, the role of personal, indoor, and outdoor air pollution exposures upon asthmatic childrens respiratory health was assessed. Several active and passive sampling methods were applied, or adapted, for personal, indoor, and outdoor residential monitoring of nitrogen dioxide, volatile organic compounds, particulate matter (PM; PM ≤ 2.5 μm [PM2.5] and ≤ 10 μm [PM10] in aerodynamic diameter),elemental carbon, ultrafine particles, ozone, air exchange rates, allergens in settled dust, and particulate-associated metals. Participants completed five consecutive days of monitoring during the winter and summer of 2005 and 2006. During 2006, in addition to undertaking the air pollution measurements, asthmatic children completed respiratory health measurements (including peak flow meter tests and exhaled breath condensate) and tracked respiratory symptoms in a diary. Extensive quality assurance and quality control steps were implemented, including the collocation of instruments at the National Air Pollution Surveillance site operated by Environment Canada and at the Michigan Department of Environmental Quality site in Allen Park, Detroit, MI. During field sampling, duplicate and blank samples were also completed and these data are reported. In total, 50 adults and 51 asthmatic children were recruited to participate, resulting in 922 participant days of data. When comparing the methods used in the study with standard reference methods, field blanks were low and bias was acceptable, with most methods being within 20% of reference methods. Duplicates were typically within less than 10% of each other, indicating that study results can be used with confidence. This paper covers study design, recruitment, methodology, time activity diary, surveys, and quality assurance and control results for the different methods used. IMPLICATIONS It is important to obtain data to identify any factors that can influence the relationships among personal, indoor, and outdoor concentrations for a range of air pollutants. Ensuring that the methods used are valid and comparable to reference methods used in typical air pollution, monitoring is crucial for data to be of use to regulators. These exposure data can then be used to develop risk management policies that reduce personal and indoor exposures to air pollutants.

Predictors of Indoor Air Concentrations in Smoking and Non-Smoking Residences

Indoor concentrations of air pollutants (benzene, toluene, formaldehyde, acetaldehyde, acrolein, nitrogen dioxide, particulate matter, elemental carbon and ozone) were measured in residences in Regina, Saskatchewan, Canada. Data were collected in 106 homes in winter and 111 homes in summer of 2007, with 71 homes participating in both seasons. In addition, data for relative humidity, temperature, air exchange rates, housing characteristics and occupants’ activities during sampling were collected. Multiple linear regression analysis was used to construct season-specific models for the air pollutants. Where smoking was a major contributor to indoor concentrations, separate models were constructed for all homes and for those homes with no cigarette smoke exposure. The housing characteristics and occupants’ activities investigated in this study explained between 11% and 53% of the variability in indoor air pollutant concentrations, with ventilation, age of home and attached garage being important predictors for many pollutants.

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.

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/m3 (95% CI 6.3–13.8) and 11.6 μg/m3 (95% CI 8.1–15.1) in winter and summer, respectively, as estimated by a personal nephelometer.

A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach

Existing evidence suggests that ambient ultrafine particles (UFPs) (<0.1µm) may contribute to acute cardiorespiratory morbidity. However, few studies have examined the long-term health effects of these pollutants owing in part to a need for exposure surfaces that can be applied in large population-based studies. To address this need, we developed a land use regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure.

Acute changes in lung function associated with proximity to a steel plant: a randomized study.

BACKGROUND Steel production is a major industry worldwide yet there is relatively little information on the pulmonary effects of air quality near steel manufacturing plants. OBJECTIVES The aim of this study was to examine how lung function changes acutely when healthy subjects are situated near a steel plant which is adjacent to a residential area. METHODS Sixty-one subjects were randomly assigned to spend 5 consecutive, 8-hour days in a residential neighborhood approximately 0.9km from a steel plant, or approximately 4.5km away at a college campus. Subjects crossed-over between sites after a nine-day washout period. Lung function was measured daily at both sites along with air pollutants including SO2, NO2, O3, PM2.5, and ultrafine particles. Diffusion capacity and pulse oximetry were also examined. RESULTS Compared with the college site, the forced expiratory volume in 1-second/forced vital capacity, forced expiratory flow between 25% and 75% of the FVC, total lung capacity, functional residual capacity, and residual volume were lower near the steel plant by 0.67% (95% CI: 0.28, 1.06),1.62% (95% CI: 0.50, 2.75), 1.54% (95% CI: 0.68, 2.39), 3.54% (95% CI: 1.95, 5.13) and 11.3% (95% CI: 4.92, 17.75), respectively. Diffusion capacity, forced expiratory volume in 1s, and pulse oximetry were also lower near the plant but these effects were not statistically significant. Sulfur dioxide, ultrafine particulates, and oxides of nitrogen were greater near the steel plant site compared to the college site. CONCLUSIONS Spending short periods of time near a steel plant is associated with a decrease in lung function.

Spatial variations in ambient ultrafine particle concentrations and the risk of incident prostate cancer: A case-control study

Background: Diesel exhaust contains large numbers of ultrafine particles (UFPs, <0.1 &mgr;m) and is a recognized human carcinogen. However, epidemiological studies have yet to evaluate the relationship between UFPs and cancer incidence. Methods: We conducted a case‐control study of UFPs and incident prostate cancer in Montreal, Canada. Cases were identified from all main Francophone hospitals in the Montreal area between 2005 and 2009. Population controls were identified from provincial electoral lists of French Montreal residents and frequency‐matched to cases using 5‐year age groups. UFP exposures were estimated using a land use regression model. Exposures were assigned to residential locations at the time of diagnosis/recruitment as well as approximately 10‐years earlier to consider potential latency between exposure and disease onset. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated per interquartile range (IQR) increase in UFPs (approximately 4000 particles/cm3) using logistic regression models adjusting for individual‐level and ecological covariates. Results: Ambient UFP concentrations were associated with an increased risk of prostate cancer (OR=1.10, 95% CI: 1.01, 1.19) in fully adjusted models when exposures were assigned to residences 10‐years prior to diagnosis. This risk estimate increased slightly (OR=1.17, 95% CI; 1.01, 1.35) when modeled as a non‐linear natural spline function. A smaller increased risk (OR=1.04, 95% CI: 0.97, 1.11) was observed when exposures were assigned to residences at the time of diagnosis. Conclusions: Exposure to ambient UFPs may increase the risk of prostate cancer. Future studies are needed to replicate this finding as this is the first study to evaluate this relationship. HighlightsWe conducted a case‐control study of UFPs and prostate cancer.Exposures were estimated using a land use regression model.Ambient UFPs were associated with an increased risk of prostate cancer.Risks were greatest when using addresses 10‐years prior to diagnosis.

The impact of a landfill fire on ambient air quality in the north: A case study in Iqaluit, Canada

A large landfill fire occurred in Iqaluit, Canada in spring/summer 2014. Air quality data were collected to characterize emissions as well as potential threats to public health. Criteria pollutants were monitored (PM2.5, O3, NO2) along with dioxins/furans, polycyclic aromatic hydrocarbons, and volatile organic compounds. Median daily dioxin/furan concentrations were 66-times higher during active burning (0.2 pg/m(3) Toxic Equivalency Quotient (TEQ)) compared to after the fire was extinguished (0.003 pg/m(3) TEQ). Other pollutants changed less dramatically. Our findings suggest that airborne concentrations of potentially harmful substances may be elevated during landfill fires even when criteria air pollutants remain largely unchanged.