Michael Brauer

Prospective Graduate Students / Postdocs

This faculty member is currently not actively recruiting graduate students or Postdoctoral Fellows, but might consider co-supervision together with another faculty member.


Research Interests

air pollution
built environment
Community Health / Public Health
environmental health
environmental epidemiology
environmental health
healthy cities
remote sensing

Relevant Thesis-Based Degree Programs

Affiliations to Research Centres, Institutes & Clusters


Research Methodology

Exposure Assessment
Geospatial modeling
machine learning

Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

Epidemiology and geospatial analysis of built environment determinants of healthy and resilient cities (2022)

Urbanisation and climate change are expected to introduce novel public health, environmental, and sustainability challenges. Epidemiological studies indicate that climate and public health vulnerabilities vary by neighbourhood. However, data at these spatial levels are largely unavailable despite studies demonstrating that geographically aggregated data mask disparities. To address this gap, this dissertation developed and applied high resolution geospatial vulnerability and health indicators across British Columbia (BC), Canada. The first dataset applied principal components analysis to more than 30 measures to map exposures, population sensitivities, adaptive capacities, and overall vulnerabilities of four climate hazards (extreme heat, inland flooding and sea level rise, wildfire smoke, and ground-level ozone) across 4188 dissemination areas in two health regions. A principal components analysis revealed varied opportunities for adaptive capacities across all hazards (16%-47% contribution to variation in overall vulnerability), with the greatest contribution found for flooding (47%). Overall, sensitivity explained the most variance, suggesting strategies targeting age and those with pre-existing health conditions in public health and emergency responses. Building on this result, the second dataset linked mortality data and sociodemographic information in a Bayesian small area model to estimate life expectancy (LE) at birth and 20 causes of mortality over 27 years across 368 Census Tracts (CTs) in Metro Vancouver, BC. The dataset identified spatial LE gaps of more than 10 years that widened in recent years. Absolute inequalities decreased for all diseases except for neoplasms, but relative inequalities increased for all causes. In the final study, difference-in-differences models were applied to the small area mortality data to evaluate relationships with population density and sociodemographic measures to assess optimum density levels, and the effects of density changes over time. At densities above ~9,400 persons per km2, LE began to decrease more rapidly. By cause, densification was linked to decreased mortality for major causes of mortality in the region, such as cardiovascular diseases, neoplasms, and diabetes. Through these three studies, this dissertation provided evidence for the importance of local-level indicators of health, vulnerability, and built environment variables for future and ongoing surveillance of healthy and resilient cities.

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Multinational modeling of household air pollution (2021)

Cooking with polluting fuels (e.g. wood, coal, dung) generates household air pollution (HAP), which adversely impacts the environment and health of ~3.8 billion individuals worldwide, primarily in low- and middle-income countries. Large-scale household transition from polluting to cleaner cooking fuels (e.g. gas, electricity) is necessary to achieve maximum health benefits. In this dissertation, I address key research questions for understanding facilitators of the clean cooking transition and the health impacts of HAP exposure: (1) What are household, community and national determinants of ‘natural’ cooking fuel switching? (2) How do fine particulate matter (PM₂.₅) and black carbon levels from HAP vary by country and primary cooking fuel type on a global scale? (3) Which cooking environment characteristics are predictors of PM₂.₅ measurements on a multinational scale? (4) How accurately can survey data on cooking environment factors predict quantitative PM₂.₅ exposures?I evaluated drivers of ‘natural’ polluting-to-clean primary cooking fuel switching using longitudinal survey data from rural communities within nine countries (Bangladesh, Chile, Colombia, Pakistan, South Africa, Tanzania, Zimbabwe, China, India) from the Prospective Urban and Rural Epidemiology (PURE) cohort study. Community-level (e.g. travel time to closest densely populated area, population density) factors were most strongly associated with polluting-to-clean fuel switching, and the degree of association of socioeconomic factors (e.g. education, income) with primary cooking fuel switching varied by country (highest in India, lowest in China). To quantify potential health benefits associated with a global transition to cleaner cooking fuels, I measured and modeled multinational variation in PM₂.₅ exposures. The models revealed that average PM₂.₅ concentrations at PURE baseline varied four-fold among primary cooking fuel types, ranging from 47 ug/m³ (95%CI:[47,47]) (gas) to 204 ug/m³ (95%CI:[195,213]) (animal dung). Modeled average male PM₂.₅ exposures were higher than female exposures among households primarily cooking with gas and charcoal, and across all primary fuel types in Chile, Colombia and India. Only 4% of average PM₂.₅ kitchen concentrations at PURE baseline were below the WHO Interim-1 Target (35 ug/m³); 87% of these households used cleaner primary cooking fuels (gas:85%; electricity:2%). This dissertation presents quantitative exposure estimates to be used globally for policy and disease burden assessments.

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Assessing sub-daily exposure to wildfire smoke and its public health effects in British Columbia (2019)

Global climate change has created new public health issues, and evidence-based policies are needed for mitigating the health impacts. The increasing frequency and intensity of wildfires is one of the pressing concerns in Canada and globally. Epidemiological studies have found that daily average exposure to wildfire smoke is associated with a wide range of cardiopulmonary conditions. However, few studies have looked at the health effects of sub-daily exposures measured in hours, and little is known about the lag-response relationship at such temporal scales. Sub-daily impacts are highly relevant for public health response, especially for smoke episodes of limited duration. To address these knowledge gaps, this dissertation presents a machine learning approach to identify variables relevant to the vertical distribution of smoke in the atmosphere, which can improve the application of remote sensing data for population exposure assessment. Relevant variables included fire activity in the vicinity, geographic location of the smoke, and meteorological conditions. These variables were next combined with data from air quality monitors and ecological information, to develop an empirical model for estimating 1-hour average population exposure to fine particulate matter (PM₂.₅) during wildfire seasons from 2010 to 2015 in British Columbia, Canada, at a 5 km² resolution. Compared with observations, model predictions had a correlation of 0.93, root mean squared error of 3.2 μg/m³, mean fractional bias of 15.1%, and mean fractional error of 44.7%. The model estimates were then linked to ambulance dispatches, paramedic assessments, and subsequent hospital admissions. Increased PM₂.₅ was associated with increased dispatches for respiratory and cardiovascular reasons within one hour following exposure, and for diabetic reasons within the first 24-hour period. Each 10 μg/m³ increase in PM₂.₅ was associated with an increase in the cumulative odds over 48 hours of up to 10%, 20% and 10% for respiratory, cardiovascular, and diabetes calls, respectively. These results support further investigation into the health effects of sub-daily exposures and suggest that air quality standards and public health actions during wildfire smoke events should be based on the hourly time scale. Public health agencies and the general public should act promptly to reduce exposure when affected by wildfire smoke.

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Connecting natural space exposure to mental health outcomes across Vancouver, Canada (2019)

In an increasingly urbanized world, identifying evidence-based strategies to guide the design and maintenance of healthy cities is an essential public health function. Two pressing urban health concerns are high rates of mental disorders and low levels of social connection. Epidemiological studies indicate that access to natural space – either greenspace, such as parks and street trees, or bluespace, such as oceans and lakes – may strengthen social connections and improve mental health. However, gaps remain regarding effects of specific forms of nature, their impacts on objective measures of mental health, and pathways by which any benefits occur. To address these gaps, this dissertation developed and applied a robust model of the presence, form, accessibility, and quality of greenspace and bluespace across the Vancouver, Canada region. This Natural Space Index (NSI) included more than 50 measures at 100-to-1,600-meter buffers for 60,000-plus six-digit postal codes. Analyses based on residential addresses highlighted the extent to which distinct measures result in different assessments, particularly in comparison with standard metrics of surrounding greenness such as the Normalized Difference Vegetation Index (NDVI). Using data from the Canadian Community Health Survey-Mental Health, the percentage of publicly accessible neighborhood nature within 500m had indirect mental health benefits via increased neighborhood social cohesion: each 1% increase was associated with 3-5% increases in reporting higher levels of social cohesion. In turn, individuals with the highest social cohesion had an 86% decrease in the odds of major depressive disorder, a 91% decrease in negative mental health, and a 2.8-point reduction in psychological distress (on a 0-40 scale). When the same question was approached using data on prescriptions related to mental illness, a 0.1-point increase in 250-meter surrounding greenness was linked to a 2% decrease in total psychotropic prescription dispensation and a 3% decrease in antidepressant prescription dispensation. The presence of ten additional street trees within 100m was associated with a 4% reduction in total psychotropic prescriptions. Although many NSI measures showed no association with mental health outcomes, the indirect and direct effects identified by this thesis support calls for expanding equitable access to natural space as part of a broader healthy-city strategy.

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Health, climate, and time-use impacts from a carbon-financed cookstove intervention in rural India (2017)

Efforts to introduce efficient stoves and cleaner fuels increasingly leverage carbon-finance to scale up dissemination, highlighting climate, health, and livelihood co-benefits. However, actualization of co-benefits has not been evaluated. Two studies were implemented in Karnataka, India where a local organization initiated a Clean Development Mechanism-approved cookstove intervention. A one-year randomized intervention study assigned 187 households in a village to either receive the intervention or continue using traditional stoves, and evaluated fuelwood usage, indoor fine particle mass (PM₂.₅) and absorbance (Abs) levels, and blood pressure (BP) in women ≥ 25 years old (N=222). Forty percent of intervention homes continued using traditional stoves in combination with the intervention stove ("mixed stove"). There were minor and overlapping differences (post- minus pre-intervention change) between control and intervention groups for median (95% CI) fuel use [-0.60 (-1.02, -0.22) vs. -0.52 (-1.07, 0.00) kg day-¹], and 24-hr absorbance [35 (18, 60) vs. 36 (22, 50) x 10-⁶ m-¹]. For 24-hr PM₂.₅ difference, there was a higher increase in control compared to intervention homes [139 (61,229) vs. 73(-6, 156) μg m-³] between the two seasons. The intervention cookstoves partially mitigated the seasonal increase in PM₂.₅ concentrations but resulted in measurements with a higher ratio of absorbance to PM₂.₅ mass compared to traditional stoves.Exclusive use of intervention stove was not associated with significant changes in systolic or diastolic BP. Mixed stove homes were associated with higher SBP in both within-group (post-pre: 4.1 [(95% confidence interval), 0.4, 7.8] mm Hg) and between-group (9.5 [3.7, 15.3]) mm Hg analyses. In a cross-sectional, mixed-method study of households (N=50) in another village, time spent cooking and collecting fuelwood was similar between intervention and traditional stove homes. Women reported using saved time for farm work, household work, and leisure (e.g. rest, spend time with family). Self-reported time spent cooking and collecting fuelwood was overestimated compared to the observed measured time.Absent rigorous evaluations, stove interventions may be pursued that fail to realize expected carbon reductions or anticipated co-benefits. Carbon financing can help move populations in low-income countries towards cleaner cookstoves by supporting field-proven technologies, and aligning with emerging health and climate guidelines.

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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)

In this dissertation I examined whether three exposures associated with the physical and social residential environment − specifically, ambient air pollution, radon and neighborhood socioeconomic status (SES) − are risk factors for the development of lung cancer in Canada. Throughout this dissertation I used the National Enhanced Cancer Surveillance System (NECSS), a large population-based case-control study conducted in eight Canadian provinces, including 3,280 incident lung cancer cases and 5,073 population controls. In the first section of this dissertation, I developed methods to estimate ambient air pollution, both nationally and retrospectively, and applied these to 20 years of residential histories in the NECSS study. Epidemiological analyses showed that the odds of lung cancer incidence associated with a 10-unit increase in PM₂.₅ (µg/m³), NO₂ (ppb) and O₃ (ppb) were 1.29 (95% CI = 0.95-1.76), 1.11 (1.00-1.24), and 1.09 (0.85-1.39) respectively, indicating that ambient air pollution exposure is associated with lung cancer development in Canada. In the second section, I used maps of radon concentration and potential in combination with the NECSS residential histories to estimate ecological radon exposures. A 50 Bq/m³ increase in average health region radon concentration was associated with a 7% (-6-21%) increase in the odds of lung cancer and for every 10 years that individuals lived in high radon potential zones, the odds of lung cancer increased by 11% (1-23%). This study also indicated that risk mapping may be used to target population health prevention efforts for radon. In the third section, I developed methods to estimate long-term exposure to neighborhood SES and applied these to the residential histories of the NECSS study. The odds of lung cancer cases residing in the most versus least deprived long-term neighborhood SES quintiles were significantly elevated and in the city sub-analysis remained significant (OR: 1.38 (1.01-1.88)) after adjusting for smoking and other lung cancer risk factors. Smoking behavior was the predominant partial-mediating pathway of the neighborhood effect. Collectively, this dissertation contributes to the methodological literature on spatial exposure assessment and spatial epidemiology, as well as to the etiological evidence linking air pollution, radon and neighborhood SES to lung cancer risk.

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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

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

A case-crossover investigation of associations between extreme heat and pediatric health (2023)

BACKGROUND: Globally, climates are changing causing more frequent and severe extreme heat events (EHEs). In Canada, annual EHE frequency is anticipated to double in just the next 3 decades. A large body of literature links EHEs to multiple health endpoints, including heatstroke and exacerbating medical conditions. However, there remains a paucity of knowledge concerning the specific health outcomes associated with heat in children. Compared to adults, children have higher surface area to mass ratios, lower sweating capacity, higher temperature at which sweating begins, lower cardiac output, and lower blood volume. They are also believed to be more vulnerable to EHEs due to external factors including activity patterns and dependence on caregivers.METHODS: This space-time stratified case-crossover analysis of Ontario’s 2005-2015 emergency healthcare data applied conditional quasi-Poisson regression to assess associations between FSA-level EHE exposure with primary causes of pediatric emergency hospital admissions and emergency department (ED) visits.RESULTS: Positive associations were found both for pediatric hospital admissions and ED visits for primary causes of asthma; general heat-related illness, heatstroke; and lower respiratory infections. General injuries and transportation related injuries were negatively associated with both pediatric hospital admissions and ED visits. EHEs increased risk of pediatric hospital admissions for causes of general respiratory illnesses by 26% (CI:14%-40%), asthma by 29% (CI:16%-44%); general infectious and parasitic diseases by 36% (CI:24%-50%), lower respiratory infections by 50% (CI:36%-67%), and enteritis by 19% (CI:7%-32%). EHEs also increased risk of ED visits for asthma by 18% (CI:7%-29%) and lower respiratory infections by 10% (CI:0%-21%).All-cause hospital admissions and ED visits were not associated with EHEs. However, in stratified analyses all-cause hospital admissions were positively associated with EHEs for children 13-18 and males, and all-cause ED visits were negatively associated with EHEs among children 5-12.CONCLUSION: EHEs elevate risk of pediatric emergency healthcare utilization for respiratory illnesses, asthma; infectious and parasitic diseases, lower respiratory infections, and enteritis in Ontario. It is imperative that policies and programs be tailored to reflect the specific heat related vulnerabilities of children to respiratory and infections illnesses in face of a rapidly warming climate.

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15-minute city: access to essential services in Metro Vancouver (2022)

This study quantified access to six essential services using the “15-Minute City” concept and the measure of cumulative opportunity in Metro Vancouver. “15-Minute Cities” are suggested to promote multiple health-focused goals such as health equity, active transportation, and sustainable development to improve the well-being of the population. Locations of 3357 Dissemination Area (DA) population-weighted centroids (origins) and healthcare facilities, education centres, greenspace, grocery stores, community centres and public transit stops (destinations) were identified using multiple open data sources. Accessibility was determined by the walking time between each origin-destination pair using a transportation routing engine with two different walking speeds representing people of different ages. Access was then evaluated by population density, municipality, age and a measure of situational deprivation as a proxy for socioeconomic status. Only 22% of DAs in Metro Vancouver had access to all six essential services and were considered “15-Minute City” neighbourhoods in this analysis. These DAs had higher population density, a lower proportion of populations between ages 0 to 14, and the highest proportion in the least situationally deprived category. Greenspace and community centres were the most (99%) and least accessible (36%) essential services within 15 minutes of walking, respectively. This study highlighted access inequity to essential services across Metro Vancouver based on socioeconomic and demographic characteristics. The “15-Minute City” was an innovative framework that was used to quantify disparities in access. This framework can inform decision making and improve resource allocation to support sustainable development in Metro Vancouver of more complete and walkable neighbourhoods.

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Evaluation and application of prototype air quality monitors for household air pollution exposure assessment (2018)

Household air pollution (HAP) from burning of low-quality fuels is a significant contributor to global burden of disease, particularly in low- and middle- income countries. Epidemiological studies of HAP have been hampered in their ability to collect quantitative exposure measurements from a lack of affordable, durable and easily usable air quality monitors. New devices offer potential to overcome these obstacles but must be tested in real world conditions before deployment. This study’s goal was to evaluate the performance of three prototype monitors compared to two reference monitors and their applicability for use in a prospective cohort epidemiologic study. Prototype monitors tested included a filter-based monitor, and two particle counters. Simple linear regression models of HAP exposure were constructed using questionnaires and observational data.55 households were recruited for HAP monitoring in two villages in India in 2015. Monitors were placed in the household kitchens for 24- and 48-hour sample periods. Male and female household residents were recruited for personal fine particle (PM₂.₅) exposure monitoring using the filter-based prototype monitor. All filter samples were analyzed for PM₂.₅ mass concentrations and particle light absorbance. Successful filter samples collected with the V1.0 Ultrasonic Personal Aerosol Sampler (UPAS, Access Sensor Technologies, Fort Collins, CO), were obtained in 81% of homes with successful reference measurements. Fewer successful samples were collected with prototype particle counters, (43% and 75%). Personal monitoring with the UPAS succeeded in 54% of attempts. There was a high level of agreement between prototype filter and reference monitor (R² = 0.85 and slope = 0.98 for PM₂.₅ and R² = 0.88 with slope = 1.63 for absorbance). Neither prototype particle counter performed well enough for subsequent analyses. The best performing models of HAP exposure were for individual communities with a broad pool of predictors; including multiple types and amounts of fuels and cooking times, versus models combining communities with a narrower set of predictors. Using a broader variable pool improved adjusted R² values by as much as 0.35.Recommendations were made for improvements for the UPAS sampler. An updated (V2.0) UPAS sampler was selected by the PURE AIR study of HAP.

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Monitoring residential woodsmoke in British Columbia communities. (2018)

Wood burning is a common home heating method in many communities in British Columbia and an important source of fine particulate matter (PM₂.₅) air pollution. During winter months communities impacted by residential woodsmoke experience high concentrations of PM₂.₅, at levels that have been associated with a wide range of health effects. Characterising levels of woodsmoke within and between communities can support air quality management and reduction of exposures. This project tested novel methods to measure the relative levels and spatial variability of residential woodsmoke PM2.5 using fixed and mobile optical instruments. The methods were applied during the winter heating season (January 5th to March 2nd, 2017) across three communities identified to be impacted by residential woodsmoke from fixed-site monitoring data, and three paired communities without routine monitoring.Continuous monitoring was performed for two weeks at fixed monitoring stations in each monitored community to compare the optical instruments with established methods used to measure PM₂.₅ and woodsmoke. This was combined with nightly mobile monitoring using the same optical instruments, alternating between driving routes around the paired monitored and unmonitored communities to create detailed maps describing woodsmoke levels and variability.The nephelometer (Bsp) and aethalometer (delta C) tested at the fixed-site were strongly correlated with conventional methods of measuring PM₂.₅ (beta attenuation monitor and filter-based) and woodsmoke (levoglucosan). Comparisons between the instruments during mobile monitoring clearly identified times and areas where woodsmoke was dominating PM₂.₅ concentrations.Mobile monitoring indicated considerable spatial variation across all communities and identified hotspot areas with consistently elevated concentrations of both PM₂.₅ and woodsmoke. The spatial variance of PM₂.₅ concentrations was significantly greater than the temporal variance during 71% of the runs, demonstrating the importance of understanding spatial variability when monitoring the air quality impacts of woodsmoke. Strong woodsmoke impacts were found in each community. In general, the unmonitored communities had PM₂.₅ concentrations that were similar to or higher than their partnered monitored communities, despite having smaller sizes and populations.The development of this approach allows for detailed and cost-effective characterisation of woodsmoke in monitored and unmonitored communities, which could inform source control efforts in many Canadian communities.

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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 subclincal 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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Evaluation of the BlueSky smoke forecasting system and its utility for public health protection in British Columbia (2013)

Wildfire smoke is a major contributor to extreme particulate matter (PM) air pollution events and has been associated with respiratory and cardiovascular health effects. With climate change, more frequent and intense wildfires are expected in the future and their impact on public health will likely increase. The existing exposure assessment tools such as the monitoring network and remote sensing platforms have limitations for measuring wildfire smoke, including inadequate coverage and measuring total column instead of ground-level concentrations. From the public health perspective, a system that can supplement these tools and predict smoke concentrations will be valuable. The Western Canada BlueSky Smoke Forecasting System, which can predict PM₂.₅ (PM
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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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