Michael Brauer

Professor

Research Classification

Environmental Health
Community Health / Public Health

Research Interests

air pollution
environmental health
built environment
environmental epidemiology
remote sensing

Relevant Degree Programs

 

Research Methodology

Epidemiology
Exposure Assessment
Geospatial modeling

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Doctoral students
Postdoctoral Fellows
2020
2021
I support public scholarship, e.g. through the Public Scholars Initiative, and am available to supervise students and Postdocs interested in collaborating with external partners as part of their research.
I am open to hosting Visiting International Research Students (non-degree, up to 12 months).

Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - Mar 2019)
Health, climate, and time-use impacts from a carbon-financed cookstove intervention in rural India (2017)

No abstract available.

Childhood asthma and allergies in birth cohort studies : tools for environmental exposure assessment (2015)

Pediatric asthma and allergies represent global health problems causing substantial disability. Epidemiological research has established a link between air pollution and exacerbation of asthma. However, the role of air pollutants in relation to atopy and on the development of asthma is unclear.This thesis examines the relationship between traffic-related air pollution and the development of atopy and asthma using two complementary Canadian birth cohorts where the impact of different exposure assessment approaches on observed associations was evaluated. Hopanes in house dust, collected in the Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort study, were evaluated as markers of indoor infiltrated traffic-related air pollution by measuring their correlation with geographic predictors of outdoor concentrations of nitrogen dioxide. This correlation was dependent on the inclusion of behavioral characteristics, hindering the utility of measuring hopanes in settled dust for exposure assessment. As an alternative approach to assess exposures in CHILD, city-specific land use regression models, questionnaires and home assessments were used to model personal exposure, including accounting for indoor/outdoor infiltration and time-activity patterns, in relation to early atopy. Spatio-temporally adjusted exposure in the first year of life was positively associated with sensitization to common food or inhalant allergens at age 1 (Odds ratio [95% confidence interval] per interquartile increase in nitrogen dioxide = 1.16 [1.00 – 1.41]). Because atopy is often a precursor for allergic asthma, 10 years of longitudinal data from the Border Air Quality Study population-based birth cohort were used to evaluate the role of air pollution on asthma development. An interquartile range increase in nitrogen dioxide, adjusted for temporal and spatial variability, increased incident asthma among preschool (age 0-5) children by 9% (95% confidence interval: 4 – 13%). Surrounding residential greenness mitigated this effect. In further analysis, the course of asthma was found to follow three trajectories: transient asthma, early-, and late-infancy chronic asthma, the latter two being significantly associated with fine particulate matter and nitrogen dioxide. This dissertation highlights the importance of integrating temporal and spatial variation in traffic-related air pollution exposure assessment and clarifies the role of early exposures on atopy and asthma initiation.

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Childhood allergic rhinitis : the role of the environment and genetics (2014)

Allergic rhinitis is a global health problem that causes major illness and disability. Inherited and environmental factors influence its development. This thesis examined the role of traffic-related air pollution, genetic variants and their potential interactions, on childhood allergic rhinitis. Global spatial associations with climatic factors known to influence aeroallergen distributions were also studied. Data from two Canadian (CAPPS and SAGE) and four European birth cohorts (BAMSE, GINIplus, LISAplus and PIAMA) participating in the Traffic, Asthma and Genetics collaboration were pooled. No consistent associations between individual-level traffic-related air pollutants (NO2, PM2.5 mass, PM2.5 absorbance and ozone) estimated to the home address and childhood allergic rhinitis were observed in a longitudinal analysis (up to ten years) of two cohorts (GINIplus and LISAplus; N=6,604) and a pooled analysis of all six cohorts (N=15,299). These latter null associations were not modified by ten tested single nucleotide polymorphisms in the GSTP1, TNF, TLR2 and TLR4 genes. Although these results do not support an adverse role of traffic-related air pollution on childhood allergic rhinitis, much remains to be learned regarding for whom, when and how air pollution may impact disease.In further analyses, genetic variants in the TNF and TLR4 genes and at the 17q21 gene locus were found to be associated with childhood allergic rhinitis in pooled analyses of the six cohorts. As genetic variability in these regions has also been linked to asthma, the observed associations support the hypothesis of shared genetic susceptibility between asthma and allergic rhinitis. These results may be important for public health given the large proportion of the population carrying the studied risk variants.Lastly, using cross-sectional data from 6-7 and 13-14 year-olds participating in the International Study of Asthma and Allergies in Childhood, several ecological spatial associations between climatic factors (temperature, precipitation and vapour pressure) and intermittent and persistent rhinitis symptom prevalences were identified. Although not conclusive, these results represent a first step in investigating how climate change may affect rhinitis symptom prevalence.Collectively, this dissertation contributes to our understanding of the effects of air pollution, genetic variability and climate on childhood allergic rhinitis.

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A spacial assessment of environmental risk factors for lung cancer in Canada: The role of air pollution, radon and neighborhood socioeconomic status (2013)

No abstract available.

Traffic-related air pollution, community noise, and coronary heart disease (2012)

No abstract available.

Exposure to residential air pollution and physician diagnosis of otitis media during the first two years of life in British Columbia, Canada (2010)

No abstract available.

Spatial assessment of forest fire smoke exposure and its health impacts in Southeastern British Columbia during the summer of 2003 (2009)

Forest fires are a significant source of episodic air pollution resulting in elevated ambient concentrations of inhalable particulate matter (PM). Although PM from fossil fuel combustion has been conclusively associated with respiratory and cardiovascular morbidity and mortality, the health effects of fire-related PM are not clearly understood. Air quality monitoring is sparse in many fire-affected areas, so it is challenging to apply epidemiologic methods that require individual-level exposure assessment. Data from dispersion models and remote sensors are spatially extensive and may provide viable exposure estimation alternatives. Firestorms across southeastern British Columbia during the summer of 2003 produced a unique opportunity to compare rigorous epidemiologic results based on new exposure assessment methods to those based on air quality monitoring data. A population-based cohort of ~280 000 subjects was identified from administrative health data and three daily smoke exposure estimates were assigned for each individual according to residential location: TEOM averaged PM concentrations measured by the nearest of six air quality monitors; SMOKE indicated the presence of a plume over the area in satellite imagery; and CALPUFF averaged PM concentrations estimated by a dispersion model. The latter was initialized and run for this project using remote sensing data to simplify the model as much as possible. For example, emissions were calculated with the radiative power of satellite-detected fires and were comparable to those estimated by much more complex methods. Overall performance of the model was moderate when evaluated using PM measurements, satellite imagery and atmospheric aerosol measurements. Longitudinal logistic regression was used to examine the independent effects of each exposure over the 92-day study period. Respiratory outcomes were associated with smoke-related PM, but no cardiovascular effects were detected. While odds ratios for the TEOM metric were consistent with other reports, those for the CALPUFF metric were biased towards the null. Results for SMOKE tracked with those for TEOM, but with much wider confidence intervals. This study (1) highlights the potential of new smoke exposure assessment methods, (2) demonstrates that plume dispersion models can be simplified with remote sensing data, and (3) confirms the respiratory health effects of forest fire smoke.

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Master's Student Supervision (2010-2017)
A spatial and temporal analysis of neighborhood air quality in downtown Vancouver (2017)

Rapid urban densification and an enhanced understanding of the health consequences of intra-urban air pollution exposure variability has led to a need for accurate estimation of traffic-related air pollution (TRAP) exposures, including temporal and spatial variability. To address this goal, a wireless real-time air pollution monitor was evaluated and the effect of street canyon geometry on TRAP levels was assessed. The AQMesh wireless monitor (with sensors for CO, NO, NO₂, O₃ and SO₂)—was evaluated in a co-location study with regulatory air quality monitoring stations in London, England and Vancouver, Canada. The amount of variability (R²) explained by AQMesh sensors (algorithm version 3.0) ranged from 0.02% to 34.5% in Vancouver and 1.5% to 82.3% in London. Sensors for NO₂ and O₃ displayed the highest accuracy while the CO sensor accuracy was much weaker. AQMesh, as examined in this co-location, was not sufficiently robust for use in regulatory applications. A simple GIS-based model for the identification of potential street canyons where TRAP levels may be elevated was created using 3D building information, aspect ratio and the prevailing wind direction. The model was evaluated in a mobile monitoring campaign in which particulate matter smaller than 2.5 micrometers (PM2.5) and particle number concentration (PNC) were measured along 4 road segments: canyon high traffic (C HT), canyon low traffic (C LT), non-canyon high-traffic (NC HT) and non-canyon low traffic (NC LT). A linear mixed effects model found the effect estimates for C LT (i.e. the effect of canyon) to be 8% higher for PM2.5 and 17% higher for PNC when compared to the reference road segment category, NC LT. In comparison, the effect estimates for NC HT (i.e. the effect of traffic) was 16% higher for PM2.5 and 34% higher for PNC when compared to NC LT. This research suggests that the impact of traffic may be greater than the impact of street canyons in determining TRAP exposures.

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Land use regression modelling of NO₂, NO, PM₂.₅ and black carbon in Hong Kong (2016)

Land use regression (LUR) modelling is a common method for estimating pollutant concentrations. This project created two-dimensional LUR models for nitrogen dioxide (NO₂), nitric oxide (NO), fine particulate matter (PM₂.₅), and black carbon (BC) for Hong Kong, a prototypical high-density high-rise city. Two sampling campaigns (April-May and November-January) were carried out in Hong Kong. Measurements of NO₂ and NO (2-3-week averaged) and PM₂.₅ and BC (24-hour averaged) were adjusted for instrument bias and temporal variation, and offered to multiple linear regression models along with 365 potential geospatial predictor variables. Variables were created from a number of geospatial metrics including land use and traffic variables (road length, average annual daily traffic [AADT], traffic loading [AADT * road length]). Measurement averaged across both campaigns were: a) NO₂ (M = 106 μg/m³, SD = 38.5, N = 95), b) NO (M = 147 μg/m³, SD = 88.9, N = 40), c) PM₂.₅ (M = 35 μg/m³, SD = 6.3, N = 64), and BC (M = 10.6 μg/m³, SD = 5.3, N = 76). Thirty-six LUR models were created (4 pollutants * 3 combined and separate sampling campaigns * 3 traffic variable type). The annual (combined values from both campaigns) road length models were selected as preferred models based on data reliability and overall model fit. Road length, car park density, and land use types were commonly selected predictors in the final preferred models. The preferred models had the following parameters: a) NO₂ (R² = 0.46, RMSE = 28 μg/m³) b) NO (R² = 0.50, RMSE = 62 μg/m³), c) PM₂.₅ (R² = 0.59; RMSE = 4 μg/m³), and d) BC (R² = 0.50, RMSE = 4 μg/m³). NO₂ predictions were strongly influenced by traffic and higher around Kowloon and northern Hong Kong Island. PM₂.₅ predictions had a strong northwest (high) to southeast (low) gradient. BC had a similar gradient and high predictions around the port. This matched with existing literature of spatial variation and sources in Hong Kong. Spatial patterns varied by pollutant. The success of this modelling suggests LUR modelling is appropriate in high-density high-rise cities.

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Air pollution exposure and subclinical health impacts in commuter cyclists (2014)

Background: Cycling is a form of active transportation, resulting in health benefits via increased physical activity. Less is known of traffic-related air pollution exposures and the resulting physiological responses experienced by urban commuter cyclists. The aim of this study was to measure systemic inflammation and lung function changes amongst cyclists by comparing responses between high and low- air pollution routes. Methods: Male and female participants (n = 38) rode an instrumented bicycle for approximately 1- hour along a Residential and a Downtown designated bicycle route in a randomized crossover trial during the summer and fall of 2010 and 2011. Heart rate, power output, location and particulate matter air pollution (PM₁₀, ₂₅, and ₁ and particle number concentration [PNC]) were measured at 6- second intervals during trials. Endothelial function [RHI], lung function, and blood measurements of C-reactive protein [CRP], Interleukin-6 [IL-6], and 8-hydroxy-2’-deoxyguanosine [8-OHdG] were assessed within one hour pre- and post-trial. A subset of 23 participants each completed a post-ride cycle ergometer minute ventilation (V̇E) measurement to estimate air pollution intake, based on heart rate measurements. Results: Geometric mean (GM) PNC exposures and intakes were higher along the Downtown (GM exposure = 16 226 particles/cm³; intake = 4.54 x 10¹⁰ particles) compared to the Residential route (GM exposure = 10 011 particles/cm³; intake = 3.13 x 10¹⁰ particles). The mean V̇E cycling: rest ratio was 3.0. In linear mixed-effect regression models, post-cycling RHI was 22% lower following the Downtown route compared to the Residential route (RHI of -0.38, 95% CI of -0.75 to -0.02), but this was not associated with exposure or intake of measured air pollutants. IL-6 and 8-OHdG levels increased after cycling trials along the Downtown route, but no significant association was found with PNC exposure or intake in mixed effect models. Conclusions: Although air pollution exposures and intakes were higher along the Downtown route and RHI was significantly decreased following trials on this route, this decrease was not associated with air pollution exposure or intake. This suggests other drivers of systemic inflammation related to cycling on the Downtown route may have been responsible for the observed association.

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Assessing the impacts of traffic-related and woodsmoke particulate matter on subclinical measures of cardiovascular health : a HEPA filter intervention study (2014)

Fine particulate matter (PM2.5) plays an important role in the link between air pollution and a range of health effects including respiratory and cardiovascular morbidity and mortality. The specific sources of PM2.5 responsible for these effects have not been definitively identified. With traffic-related air pollution (TRAP) and woodsmoke (WS) as two of the major contributors to ambient PM2.5 concentrations, this study was the first to investigate the difference in health outcomes between these two sources. The purpose of this study was to compare cardiovascular exposure-response relationships for TRAP and WS and to evaluate the impact of HEPA filtration on indoor TRAP and WS PM₂.₅ levels. In this single-blind randomized crossover study, 83 healthy adults (54 living in high TRAP and 29 living in high WS areas) between the ages of 19 and 72 living in Metro Vancouver were recruited. Areas with high TRAP or high WS were identified using previously developed spatial models and subjects were recruited by letters sent to households in these areas. Sampling was conducted over two consecutive one-week periods, one with filtration and one with no filtration. Two filtration devices were used, one in the main living room and one in main bedroom. Endothelial function was measured at the end of each week and blood was drawn at baseline and at the end of each week. Mixed effect models were used to investigate the relationship between exposure and outcome variables.Overall, HEPA filtration was associated with a 40% decrease in indoor PM₂.₅ concentrations. There was inconclusive evidence on the potential relationship between TRAP or WS PM₂.₅ exposure and endothelial function. However, there was some suggestion of an association between PM₂.₅ exposure and CRP specifically among male participants in high-TRAP locations (20.6% increase in CRP levels per unit median increase in PM₂.₅, 95% CI, 2.62% – 41.7%). There was no association between any exposure indicators and IL-6 or BCC. In summary, the results support the hypothesis that HEPA filtration can be effective in reducing indoor PM₂.₅ concentrations with some support for the a priori hypothesis of a greater impact on markers of inflammation in areas of high TRAP.

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A land use regression model for ultrafine particles in Vancouver, Canada (2012)

Background and Aims:Epidemiologic studies have associated adverse health outcomes with exposure to traffic-related air pollutants, principally NO₂, at levels below those showing effects in controlled exposure studies. This suggests the importance of related outdoor air contaminants, such as ultrafine particles (UFP) (
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Assessment of the temporal stability of land use regression models for traffic-related air pollution (2012)

Background: Land-use regression (LUR) modeling is a cost-effective approach for assessing intra-urban air pollution contrasts. It has been widely used to estimate long-term exposure to traffic-related air pollution in epidemiologic studies. The application was based on the assumption that spatial patterns of pollution are stable over time so that a model developed for a particular time point could be applied to other time points. However, this assumption has not been adequately examined. This has specific relevance to cohort studies where models are developed in one particular year and then retrospectively or prospectively applied over periods of ~10 other years. Methods: Metro Vancouver LUR models for annual average NO and NO₂ were developed in 2003, based on 116 measurements. In 2010, we repeated these measurements; 73 were made at the same location as in 2003, while the remaining 43 sites were within ~50 m. We then developed new models using updated data for the same predictor variables, and also explored additional variables. The temporal stability of LUR models over a 7-year period was evaluated by comparing model predictions and measured spatial contrasts between 2003 and 2010. Results: Annual average NO and NO₂ concentrations decreased from 2003 to 2010. From the 73 sites that were identical between 2003 and 2010, the correlation between NO 2003 and 2010 measurements was r = 0.87 with a mean (sd) decrease of 11.3 (9.9) ppb, and between NO₂ measurements was r = 0.74 with a mean (sd) decrease of 2.4 (3.2) ppb. 2003 and 2010 LUR models explained similar amounts of spatial variation (R² difference of 0.01 to 0.11). The 2003 models explained more variability in 2010 measurements (R²= 0.52 – 0.65) than 2010 models did for 2003 measurements (R²= 0.38 – 0.55). Conclusions: Forecasting will be more appropriate than back-casting in the case of Metro Vancouver where concentrations and their variability decreased over time. Back-casting explains nearly the same amount of variability (R²= 0.38 – 0.55) in measured concentrations as did the original model (R² = 0.52 – 0.58). These results support the validity of applying LUR models to cohort studies over periods as long as 7 years.  

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