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Mortality Attributable to Ambient Fine Particulate Matter Exposure in a Changing Canadian Population, 2001 to 2021
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Mortality Attributable to Ambient Fine Particulate Matter Exposure in a Changing Canadian Population, 2001 to 2021
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  • Elysia G. Fuller-Thomson
    Elysia G. Fuller-Thomson
    Water and Air Quality Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, Canada
  • Amanda J. Pappin*
    Amanda J. Pappin
    Water and Air Quality Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, Canada
    *[email protected]
  • Mathieu Rouleau
    Mathieu Rouleau
    Water and Air Quality Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, Canada
  • Guoliang Xi
    Guoliang Xi
    Environmental Health Science and Research Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, Canada
    More by Guoliang Xi
  • Aaron van Donkelaar
    Aaron van Donkelaar
    McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri 63130-4899, United States
  • Randall V. Martin
    Randall V. Martin
    McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri 63130-4899, United States
  • Richard T. Burnett
    Richard T. Burnett
    Environmental Health Science and Research Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, Canada
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ACS ES&T Air

Cite this: ACS EST Air 2024, 1, 9, 1177–1189
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https://doi.org/10.1021/acsestair.4c00130
Published August 20, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

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Abstract

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We aim to understand how changes in ambient fine particulate matter (PM2.5) over the last two decades have influenced PM2.5-attributable mortality in a Canadian population experiencing both growth and changing baseline health status. We conducted a health impact analysis using dynamic estimates of population, baseline mortality rates, and satellite-based PM2.5 concentrations to estimate mortality attributable to long-term PM2.5 exposure every five years between 2001 and 2021, applying risk estimates from the 2006 Canadian Census Health and Environment Cohort (CanCHEC) to the population aged 25 and older. We conducted a decomposition analysis to examine the influences of population exposure, size, and health status on trends in PM2.5-attributable mortality. Between 2001 and 2021, population-weighted exposure to PM2.5 declined by 18% in Canada, with improvements occurring in most urban areas. In recent years, these changes have led to 4,400 (95% CI: 3,700–5,000) to 4,700 (95% CI: 4,100–5,400) fewer PM2.5-attributable deaths annually based on log–linear and log–log shapes of concentration–response. However, a growing population alongside higher baseline mortality risks in several regions, likely due to aging, has led to a small net increase in total PM2.5-attributable deaths between 2001 and 2021. These findings suggest that the Canadian population has benefitted broadly from air quality management strategies implemented in North America over recent decades.

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Copyright © 2024 The Authors. Published by American Chemical Society

Synopsis

Limited research exists on the health benefits of air quality improvements achieved in recent years in Canada. This study finds that improvements in fine particulate matter (PM2.5) exposure have led to thousands of fewer PM2.5-attributable deaths annually in recent years.

1. Introduction

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Air pollution is a major contributor to the development of disease and death and is the largest environmental risk factor to human health globally. (1,2) Long-term exposure to ambient fine particulate matter (PM2.5) is causally associated with mortality, with no clear evidence of a threshold at low levels of exposure below which risks are zero. (3−5) Ambient PM2.5 concentrations in Canada are among the lowest levels worldwide, yet the mortality burden is still estimated at 12,500 PM2.5-attributable deaths annually due to long-term exposure, signifying that further improvements in air quality would yield substantial health benefits. (6−8)
Increasingly stringent national, provincial, and state regulations under the Canadian Environmental Protection Act in Canada, Clean Air Act in the United States, and Canada-United States Air Quality Agreement have been adopted in recent decades, notably for transportation sources (e.g., on-road vehicles, marine vessels, off-road engines), fuels (e.g., fuel sulfur content), electricity generation (e.g., coal and natural gas-fired generation), and industrial emissions (e.g., upstream oil and gas sector). (9−11) An accompanying decline has generally been observed in PM2.5 concentrations and associated chronic exposure mortality burdens despite growth in economic activity and population. (12−14)
A growing body of work worldwide has begun to evaluate air pollution mortality trends retrospectively. (6,12,15−22) Throughout the last few decades, many countries experienced decreases in population exposure to PM2.5, which have resulted in reductions in PM2.5-attributable deaths, yet these reductions can either be attenuated (17,18,20) or amplified (16) by changing population growth, age, and other factors underlying population health. The latter include public health infrastructure, socioeconomic status, health care interventions, diet, demographics, and the prevalence of certain chronic diseases, which are reflected broadly in baseline mortality rates. (6,23,24) Similar to other high-income countries, mortality in Canada has been impacted by the concurrent but opposing forces of an aging population and decreasing age-standardized mortality rates for most leading causes of death. (25) A previous Canadian analysis examined changes in PM2.5-attributable mortality retrospectively between 2000 and 2011 and highlighted a reduction in the PM2.5 health burden related to chronic PM2.5 exposure changes, but did not account for time-varying population characteristics. (13) This study will further contribute to this body of research by evaluating health impacts of air pollution over longer periods of time, while considering population dynamics, all in a comparatively low-exposure environment.
We analyzed how changes in ambient PM2.5 over the last two decades in Canada have influenced PM2.5-attributable mortality in a changing Canadian population. Beginning in 2001 and ending in 2021, we conducted a health impact analysis in five-year increments corresponding to years when the Canadian Census of Population was enumerated, using time-varying population counts, baseline mortality rates, and satellite-based PM2.5 concentrations. Ours is the first Canadian study that examines driving factors of PM2.5-attributable mortality over time, by decomposing temporal changes in PM2.5-attributable deaths resulting from changing population counts, baseline mortality rates, and PM2.5 concentrations. We conducted our analysis both nationally and regionally to illustrate potentially differential effects across Canada’s diverse populations and regions.

2. Methods

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2.1. Ambient PM2.5 Concentrations

We utilized gridded, annual average concentrations of ambient PM2.5 for North America that combine data from satellites, chemical transport model simulations, and ground-based observations to estimate population exposure to PM2.5 between 2000 and 2022 from both anthropogenic and nonanthropogenic sources including wildfires. We restricted our analysis to post-2000 as this period has the most consistent timeseries of input data without needing to back-cast. (5) The hybrid PM2.5 concentrations used update and extend previously established methods (26−28) and are available on a 0.01° × 0.01° gridded surface (V5.NA.04.02). (29) Briefly, PM2.5 concentrations were geophysically estimated by combining satellite retrievals of total column aerosol optical depth (AOD) from multiple satellite-based instruments with simulations from the high-performance, stretched-grid configuration of the GEOS-Chem (http://www.geos-chem.org) chemical transport model (30,31) over Canada to relate AOD to ground-level PM2.5, as well as to provide an additional AOD data set. Satellite AOD retrievals included the Multiangle Imaging SpectroRadiometer (MISR; early 2000s-2022), Moderate Resolution Imaging Spectroradiometer (MODIS; two instruments from early-2000–2022 and mid-2003–2022), Suomi-National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (SNPP-VIIRS; 2012–2022) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; 2000–2010). Year-specific Canadian emissions for GEOS-Chem were from the 2018 Air Pollutant Emissions Inventory (APEI) for years 2000 to 2016, with provincial and territorial growth rates applied to 2016 emissions to represent subsequent years using the 2021 APEI. Ground-based PM2.5 observations available from the Canadian National Air Pollution Surveillance (NAPS) network alongside the United States Environmental Protection Agency (EPA) Air Quality System (AQS) were statistically incorporated using a Geographically Weighted Regression to develop the final, hybrid PM2.5 concentration estimates over North America. (27) Summary statistics of the PM2.5 concentration distribution are shown in Supporting Information, Table S1.

2.1.1. Population Exposure to PM2.5

To estimate health impacts, gridded, hybrid PM2.5 concentrations were averaged using population-weighting for standard Canadian Census of Population geographic units. We estimated PM2.5-attributable mortality for Canadian census divisions, which are intermediate geographic areas in size between a municipality and provinces or territories and contain a median population in 2016 of 41,900, ranging from 550 to 2,865,100. (32) It was necessary to use multiple geographic units to conduct population weighting as population counts were not available on the original PM2.5 concentration grid. We therefore first allocated gridded concentrations to dissemination areas, the smallest geographic unit for which population count data were publicly available, using area-weighting for each annual average from 2000 to 2022. Dissemination areas are small geographic units typically containing 400 to 700 persons, with a median size of 26 ha. (32) We then combined dissemination area concentrations with their population data to estimate census division-level, population-weighted, three-year average PM2.5 concentrations for health impact analysis (refer to section 2.2 for further explanation).
We utilized three-year average PM2.5 concentrations to estimate mortality attributable to long-term or chronic PM2.5 exposure. Epidemiological cohort studies that estimate mortality risks generally use multiyear average concentrations to determine long-term exposure. Further, multiyear averaging attenuates year-to-year variability in ambient PM2.5 concentrations and is well suited to studying decadal trends. (7,33,34) Our choice of a three-year averaging period ensures consistency with the risk estimates we used from a modern Canadian cohort study with follow-up over our study period. (7,33,34) Three-year averaging periods for PM2.5 concentrations encompassed one year preceding and following each census year (Supporting Information, Table S2). Final data sets of population-weighted concentrations for census divisions were derived using population counts from the nearest Census of Population enumeration year (2001, 2006, 2011, 2016, and 2021).

2.2. Health Impact Analysis

We estimated Canadian PM2.5-attributable deaths resulting from long-term PM2.5 exposure using Health Canada’s Air Quality Benefits Assessment Tool (AQBAT) version 3.0 in our first set of analyses. (35) AQBAT employs a health impact function to estimate health impacts for Canadian census divisions (eq 1), comparable to the Benefits Mapping and Analysis Program (BenMAP) in the United States (15,16,36,37) or the methodology used for Global Burden of Disease analyses. (1,2,19,38) Geographic units of analysis of AQBAT include census divisions, which are the smallest geographic unit with the necessary baseline health information needed for estimating PM2.5-attributable mortality. (32)
ADj=i=1nM0,i,j×Pi,j×PAFi,j
(1)
Here, AD is the total number of deaths attributable to PM2.5 exposure in year j; M0, ij is the nonaccidental mortality rate in census division i and year j (also referred to as the baseline mortality rate (BMR); number per million population per year); and Pij is the specified population aged 25 and over in location i and year j. Here, the population attributable fraction (PAF) refers to the proportion of nonaccidental deaths in persons aged 25 and over that are attributable to long-term exposure to PM2.5. The PAF can be derived from the definition of relative risk as in eq 2:
PAFi,j=11/Rθ(Ci,j|Ccf)
(2)
where Rθ(Cij|Ccf) is the risk of mortality at concentration Cij (for census division i and year j) relative to a predefined counterfactual concentration Ccf, indexed by a parameter θ that regulates the magnitude of R. We consider two algebraic forms of R. The first, often termed the log–linear model, has the form: Rθ(Cij|Ccf) = exp{θ(CijCcf)}, since the logarithm of R is linear in concentration. The second form, termed the log–log model, follows a supra-linear form of concentration–response and is given by Rθ(Cij|Ccf) = exp{θ(ln (Cij + 1) – ln (Ccf + 1))}, since the logarithm of R is a function of the logarithm of concentration. Studies have suggested that the concentration–response between long-term PM2.5 exposure and mortality is supra-linear at low levels of exposure. (5,7,38) Given these two forms, the PAF can be written as
PAFf(C|Ccf)=1exp{θ(f(C)f(Ccf))}
(3)
where f(C) = C for the log–linear model and f(C) = ln(C + 1) for the log–log model. We used a counterfactual concentration of 2.5 μg/m (3) as the lowest PM2.5 exposure level represented in recent Canadian cohort studies, below which relative risks are defined as 1.0. (5,7,39) For a description of how the choice of counterfactual affects estimates, see Supporting Information, Table S3.
In our first set of AQBAT simulations, we applied eqs 1 and 2 for each census enumeration year using time-varying estimates of population, baseline mortality rates, and concentrations (Supporting Information, Table S2). AQBAT simulates eqs 1 and 2 in a Monte Carlo Framework using 10,000 iterations to estimate confidence intervals (CIs) associated with uncertainty in the parameter θ. Uncertainty estimates were unavailable for the V5.NA.04.02 hybrid PM2.5 concentration data set and because of this, we did not account for exposure uncertainty in the Monte Carlo simulations.
While mortality was calculated in AQBAT for Canadian census divisions, we report some of our results as nationally or regionally aggregated estimates to characterize trends more broadly across Canada’s diverse populations and regions. We use Canadian airsheds as defined by Canada’s Air Quality Management System for the regional unit of analysis, of which there are six. (40) In cases where airshed boundaries overlay multiple census divisions, we assigned the PM2.5-attributable mortality for a census division to the airshed whose area it overlapped with the most. Owing to the small number of occurrences where airsheds overlay multiple boundaries (n = 8, compared to 293 census divisions), with only 1% of the population involved, and the large area covered by airsheds, we consider this to be a reasonable approximation.

2.3. Population and Baseline Mortality Rates

We used population counts for persons aged 25 years and over from the Canadian Census of Population, which is enumerated by Statistics Canada every five years: 2001, 2006, 2011, and 2016. (35) As outlined in Supporting Information, Table S2, we used three-year average baseline mortality rates for Canadian census divisions (M0,i,j) for ages 25 and older based on reported data from Statistics Canada. Unlike the previous years, population counts and baseline mortality rates in 2021 were derived from a population projection. (41) For a description of how this choice may affect estimates, see Supporting Information, Table S2.

2.4. Concentration–Response Functions

We used concentration–response functions (CRFs) from the 2006 Canadian Census Health and Environment Cohort (CanCHEC) to represent the association between long-term exposure to PM2.5 and nonaccidental mortality. (7) Our selection of nonaccidental mortality from long-term exposure to PM2.5 was based on causality conclusions and our interest in capturing the totality of PM2.5 mortality impacts in the Canadian population. (4,8) We utilized Chen et al.’s (7) risk estimates as the 2006 CanCHEC is a modern, population-based, Canadian cohort whose study period most closely aligns with our analytical period, and because these risk estimates reflect a three-year exposure averaging window as used in our analysis. Their study reported parameter estimates from both log–linear and log–log models, both of which we applied in AQBAT. These concentration–response functions are demographically representative of the Canadian population and mortality experience and are not transferred from another population. Chen and colleagues (7) noted that the log–log model fit the 2006 CanCHEC data better than the log–linear model based on a smaller log-likelihood value. We used 0.1001 (se = 0.0128) as the parameter estimate (θ) for the log–log CRF and 0.0106 (se = 0.00166) for the log–linear CRF. Supporting Information, Figure S1 highlights the difference in shape between these log–linear and log–log CRFs. Our use of these two CRFs allows us to estimate the varied PM2.5 mortality risk under different assumptions about the shape of the concentration–response, in light of a growing body of research that suggests nonlinearity in the CRF at low levels of exposure. (2,7,38,42) These CRFs were derived for persons aged 30 and over in the 2006 CanCHEC. We applied them to the population aged 25 and older in AQBAT. We assume that these CRFs remain static throughout the study period from 2001 to 2021; an assumption that we believe to be reasonable given the similarity between the 2006 CanCHEC period of follow-up (2007–2016) and our study period (2001–2021).
The concentration–response functions we used originate from a cohort that is representative of the Canadian population and mortality experience. (7) The Cox survival model used to estimate the CRFs was stratified by age and sex. It represents a common risk estimate based on pooling of the risk estimates for each age-sex group, demographically representative of the Canadian population. Thus, the CRFs and the ensuing PAFs (as per eqs 1 to 3) are nationally representative of Canada’s population and reflect the varying baseline rates of mortality across the country.

2.5. Isolating Health Impacts Solely Due to Changing PM2.5

Our first set of AQBAT-based analyses for 2001, 2006, 2011, 2016, and 2021 used time-varying population, baseline mortality rates, and PM2.5 concentrations. We undertook a second set of AQBAT-based analyses to estimate the reduction in PM2.5-attibutable mortality in any given Canadian population due solely to changes in PM2.5 concentrations since 2001. To estimate this, we calculated the mortality change resulting from the difference between a given population’s actual PM2.5 exposure and a hypothetical exposure in which that population had been exposed to 2001 concentrations. This was calculated by replacing Ccf with Ci,2001 to calculate (f(Cij)–f(Ci,2001)) in eqs 1-3 while keeping the rest of the inputs unchanged from the initial AQBAT simulations.

2.6. Decomposition Analysis of Individual Factors Influencing PM2.5 Mortality Burden

Over time, changes in PM2.5-attributable mortality arise from the combined interaction of changes in population growth, population susceptibility, and PM2.5 exposure. We isolated the impact of these individual factors on PM2.5-attributable mortality by employing a decomposition method similar to those employed elsewhere. (16,17,21,43) In this approach, the net change in PM2.5-attributable mortality since 2001 for a given year is calculated by incorporating each individual factor sequentially. We first assessed the expected change in mortality due solely to population growth by keeping concentrations and baseline mortality rates unchanged since 2001, and allowing the population counts to change from 2001 to the year j (eq 4). Then, keeping concentrations fixed at 2001 levels, both population and baseline mortality rates were changed simultaneously (eq 5). Finally, all factors were changed simultaneously (eq 6). We note that ADi,2001 in eq 4-6 is as calculated in eq 1.
ΔADPopulation,i,j=i=1nM0,i,2001×(Pi,j)×(1eθ[f(Ci,2001)f(Ccf)])ADi,2001
(4)
ΔADPopulationandBMR,i,j=i=1nM0,i,j×(Pi,j)×(1eθ[f(Ci,2001)f(Ccf)])ADi,2001
(5)
ΔADAllfactors,i,j=i=1nM0,i,j×(Pi,j)×(1eθ[f(Ci,j)f(Ccf)])ADi,2001
(6)
A factor’s influence on mortality burden, ΔADij, can be calculated by a difference in these equations. Specifically, ΔADPopulationij due only to population changes since 2001 is given directly by eq 4, ΔADBMRij due to changes in baseline mortality rates since 2001 is given by eq 5eq 4, and ΔADConcentrationij for a given year due to changing concentrations since 2001 is given by eq 6eq 5. The total ΔADij is given directly by eq 6. We report the difference in mortality burden due to these individual driving factors as a percent change in PM2.5-attributable deaths from the reference year, 2001.

3. Results and Discussion

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3.1. PM2.5 Concentrations Across Canada

Over the last two decades, Canadian population-weighted PM2.5 concentrations have decreased by 1.5 μg/m3 or 18%, from a population-weighted mean of 8.3 μg/m3 in 2001 to 6.8 μg/m3 in 2021 (Table 1). Canadian concentrations of PM2.5 are low relative to concentrations experienced worldwide (Figure 1). (6) Most of this nationwide decrease in exposure occurred between 2006 and 2016, during which PM2.5 concentrations decreased by 20%. The direction of change in ambient PM2.5 exposure reversed between 2016 and 2021, during which national population-weighted PM2.5 concentrations increased by 0.2 μg/m3 or 3%.
Table 1. Population-Weighted PM2.5 Concentrations, Population Counts, and Baseline Mortality Rates in Canada
 Three-year average PM2.5concentration(μg/m3)aPopulationb 
YearMin25%Mean75%MaxAll agesAges ≥65 yearsBaseline mortality rate for ages 25+(per million)b,c
20010.46.88.310.015.831,010,0003,903,0009,600
20060.86.68.310.414.832,566,0004,299,0009,300
20110.75.77.07.911.134,343,0004,950,0009,300
20160.65.66.67.620.636,229,0005,975,0009,600
20210.85.96.87.719.837,999,000d7,097,000d10,000e
a

Statistics based on population-weighted PM2.5 concentrations.

b

Estimates have been rounded only for reporting purposes.

c

Baseline mortality rates refer to nonaccidental mortality rates.

d

The baseline mortality rates used for health impact estimation in AQBAT were projected from 2018.

e

The 2021 population data was projected based on the 2016 census.

Figure 1

Figure 1. Three-year average concentrations of ambient PM2.5 (μg/m3) in Canada over time, with cutouts of Southwestern British Columbia and Vancouver (I), Southwestern Ontario and the Greater Toronto Area (II), and Southern Quebec and the Greater Montreal region (III).

The general decadal improvement in air quality seen in Table 1 is broadly consistent with other North American findings. For example, Fann and colleagues (36) reported a 25% decrease in population-weighted, annual average PM2.5 concentrations in the United States (US) between 2005 and 2014 using the Community Multiscale Air Quality (CMAQ) chemical transport model, run for those two years. We estimated smaller decreases in population-weighted mean PM2.5 concentrations than Stieb et al., (13) who reported a 2.0 μg/m3 or 23% drop in population-weighted average PM2.5 concentrations between 2000 and 2011 in Canada using satellite-based PM2.5 concentrations. Over a similar period between 2001 and 2011, we find a decrease of 1.3 μg/m3 or a 16% reduction in population-weighted concentrations. On the other hand, we find larger decreases in PM2.5 concentrations over time compared to the Canadian Environmental Sustainability Indicators, which detected a 9% decrease in annual average PM2.5 concentrations, across ground-level monitors in Canada between 2005 and 2019, but no significant downward trend. (44) The reversal of declining PM2.5 concentrations in Table 1 after 2016 is similar to the findings of Burke et al. (45) in the US. Briefly, Burke and colleagues observed a stagnation or reversal of decreasing trends in PM2.5 concentrations in 2016 using breakpoint analysis of ground-level, annual average concentrations from 2000 to 2022. Changes in PM2.5 concentrations reported across these studies rely on different exposure models and averaging periods, which may explain the variability in their findings. Whereas in some cases, single-year estimates of concentrations were used, in other cases, moving, multiyear averages were used.
Trends in ambient PM2.5 concentrations show substantial regional variation (Figure 2). The largest improvements in PM2.5 concentrations since 2001 have occurred close to the Canada-US border, in urban areas, and to a lesser degree, across the eastern provinces. Consistent decreases in PM2.5 concentrations have occurred in most Canadian urban areas. In particular, large decreases were seen in some of the densest and most polluted population centers. For example, from 2001 to 2021, the population-weighted concentrations in Toronto, Vancouver, and Montreal decreased by 2.8, 3.6, and 0.7 μg/m3, respectively. By contrast, Canada has experienced increasing PM2.5 concentrations across much of western Canada. Areas of increasing PM2.5 concentrations tend to be spatially more sporadic, with regions of peak concentrations varying throughout the entirety of western Canada depending on the year due to variations in wildfire events.

Figure 2

Figure 2. Change in three-year average PM2.5 concentrations in Canada from 2001 (negative values reflect decreasing PM2.5 concentrations), with cutouts of Southwestern British Columbia and Vancouver (I), Southwestern Ontario and the Greater Toronto Area (II) and Southern Quebec and the Greater Montreal region (III).

3.2. Regional Variations in PM2.5 Concentrations

Due to diverging subnational patterns in PM2.5 concentrations, examining airsheds, defined as broad geographic areas having distinct atmospheric conditions, (5,40) can better capture variations in exposure that are masked when observing nationwide averages. Figure 3 depicts the trends in population-weighted PM2.5 concentrations across Canadian airsheds. Decreases in the East Central (southern Ontario and Quebec) and Western (British Columbia and Yukon) airsheds are evident and contribute to the nationwide decreases seen in Table 1. Trends in the Western airshed are largely influenced by decreases in and surrounding the densely populated Greater Vancouver Area, which represent only a small area of the airshed, but whose populous census division experienced a reduction of 2.8 μg/m3 from 2001 to 2021. By contrast, increases in PM2.5 concentrations occurred in more sparsely populated areas of the Western airshed, having a limited effect on population-weighted concentrations. Unlike trends observed in the rest of Canada, population-weighted PM2.5 concentrations in the Prairies airshed have increased enough to become the highest in the country in recent years.

Figure 3

Figure 3. Changes in three-year, population-weighted, rolling averages of PM2.5 concentrations over time across the six Canadian airsheds.

Over the last two decades, trends in Canadians’ exposure to PM2.5 have diverged. While Eastern Canada’s concentrations have decreased, vast areas of Western Canada have experienced increasing PM2.5 concentrations, with the exception of coastal regions (Figures 2 and 3). The Prairies now supersede East Central Canada as the airshed with the highest population exposure. Similar to the results in our study, an analysis of the Canadian Sustainability Indicators found a decreasing or no trend in annual average PM2.5 concentrations from 2005 to 2019 in Eastern Canada, along with observed increases or no trend in Western Canada. (44) Furthermore, the Canadian Sustainability Indicators highlighted increases in peak PM2.5 concentrations in regions coinciding with the Prairies, West Central and Western airsheds, consistent with increased wildfire activity. (44) This regional divergence has also been reported in the United States, where most of the decreases in PM2.5 concentrations that occurred since the 2000s are located in eastern states. (36,46) For example, Burke et al. (45) also found that the western and midwestern states were the only regions that saw increasing trends in ground-level, annual average PM2.5 concentrations between 2016 and 2022.
PM2.5 concentrations in Canadian urban areas, where most of the decreases have been seen, are influenced by a variety of local, regional, and transboundary sources. (47−49) Decreasing PM2.5 concentrations noted in our study likely reflect the adoption of increasingly stringent air pollution regulations in Canada and the United States in recent decades, notably for vehicles, off-road equipment, fuels, and electric power generation, including mitigation initiatives taken at federal, provincial, territorial, state, and municipal levels, as well as transnational efforts to reduce air pollution. Collectively, these efforts have led to substantial reductions in anthropogenic emissions of several air pollutants across the two countries. Several PM2.5 precursor emissions decreased in Canada between 2001 and 2021, excluding any changes related to prescribed fires and wildfires. Emission reductions of 72% in sulfur oxides (SOx), 49% in nitrogen oxides (NOx), and 42% in volatile organic compounds (VOCs) were seen, while NH3 emissions increased by 5%, and primary PM2.5 emissions decreased by 12%. (50) Over a similar period from 2002 to 2021, the United States experienced even larger emission decreases in SOx (87%), NOx (70%), and PM2.5 (16%), while VOCs decreased by 30% and NH3 emissions increased by 16%, excluding any changes related to prescribed burning and wildfires. (51)
Geographic patterns observed in Figures 2 and 3 yield information about factors potentially influencing these changes in PM2.5. Over our study period, the ten census divisions with the largest decreases in estimated PM2.5 concentrations resided in the southernmost tip of the East Central airshed (see cutout II in Figure 2), where PM2.5 contributions from the United States are highest. (49) Furthermore, this region of Canada has been exposed to very little PM2.5 from wildfire smoke compared to the rest of Canada throughout the past decade. (47,52) Worsening PM2.5 concentrations across northern and western Canada may be driven by increasingly frequent and large-sized wildfire events since the mid-2000s, since this region of Canada has faced the greatest increases in total burned area. (53,54) Wildfire smoke could also contribute to the spatially varied nature of increasing PM2.5 in Western Canada (Figure 2), reflecting the wide interannual variations in PM2.5 associated with wildfires in the region. (52) Alberta’s oil sands region was affected by the 2016 Fort McMurray Fire that likely contributed to the degraded air quality seen in Figures 1D and 2C. Broadly, the spatial trends of west-east divergence and increasing PM2.5 exposure in wildfire prone regions we observe align with complementary American research. (36,45,46) Trends observed by ground-level monitors in the United States between 2000 and 2022, and satellite-derived smoke plume analysis, showed that, for eight out of the 11 states with increasing PM2.5 conditions since 2016, smoke was a contributor to the increasing trend. (45)

3.3. PM2.5 Mortality Burden

As exposure has changed over the last two decades, so has the resultant PM2.5-attributable mortality. The fraction of all nonaccidental deaths in persons aged 25 and over attributable to long-term exposure to PM2.5, otherwise known as the population attributable fraction (PAF), expresses the change based on relative risks due to exposure alone (eq 1). Nationally, the PAF has declined from 9.0% (95% CI: 7.9–10.1%) in 2001 to 7.4% (95% CI: 6.5–8.3%) in 2021 when using a log–log CRF, and from 5.9% (95% CI: 5.0–6.8%) to 4.4% (95% CI: 3.7–5.0%) when using a log–linear CRF (Table 2). However, despite these reductions due to decreasing PM2.5 concentrations, a growing and increasingly vulnerable population has led to a net estimated increase in the total number of PM2.5-attributable deaths. We estimate that this number increased from 18,200 (95% CI: 16,000–20,400) PM2.5-attributable deaths in 2001 to 20,300 (95% CI: 17, 800–22, 800) in 2021 using a log–log CRF (Table 2). Normalized to population, this burden is equivalent to 59 deaths per 100,000 people (95% CI: 51–66) in 2001 and 54 deaths per 100,000 (95% CI: 47–60) in 2021. Smaller increases were found using the log–linear CRF, with 11,900 (95% CI 10,100–13,700) PM2.5-attributable deaths in 2001 and 12,000 (95% CI: 10,200–13,800) in 2021, which is equivalent to 38 deaths per 100,000 people (CI: 33–44) in 2001 and 32 deaths per 100,000 (CI: 27–36) in 2021.
Table 2. Mortality Attributable to Long-Term PM2.5 Exposure in Canada from 2001-2021
Concentration–Response FunctionYearPopulation Attributable Fraction (PAF)a(%)PM2.5-Attributable Deaths(yr–1)aReductions in PM2.5-Attributable Deaths Due Solely to Changing Concentrations Since2001a
Log–log20019.0 (95% CI: 7.9–10.1)18,200 (95% CI: 16,000–20,400)-
20068.9 (95% CI: 7.8–9.9)18,600 (95% CI: 16,300–20,800)290 (95% CI: 250–330)
20117.6 (95% CI: 6.6–8.5)17,000 (95% CI: 14,900–19,000)3,500 (95% CI: 3,000–4,000)
20167.2 (95% CI: 6.3–8.1)17,900 (95% CI: 15,600–20,100)5,000 (95% CI: 4,300–5,600)
20217.4 (95% CI: 6.5–8.3)20,300 (95% CI: 17,800–22,800)4,700 (95% CI: 4,100–5,400)
Log–linear20015.9 (95% CI: 5.0–6.8)11,900 (95% CI: 10,100–13,700)-
20065.8 (95% CI: 4.9–6.7)12,200 (95% CI: 10,300–13,900)190 (95% CI: 160–220)
20114.5 (95% CI: 3.8–5.2)10,100 (95% CI: 8,600–11,600)3,300 (95% CI: 2,800–3,800)
20164.2 (95% CI: 3.5–4.8)10,400 (95% CI: 8,800–11,900)4,600 (95% CI: 3,900–5,300)
20214.4 (95% CI: 3.7–5)12,000 (95% CI: 10,200–13,800)4,400 (95% CI: 3,700–5,000)
a

Estimates have been rounded only for reporting purposes.

We further estimate the number of additional PM2.5-attributable deaths that would have occurred in any given year if PM2.5 concentrations had remained at 2001 levels using the second set of AQBAT-based analyses. We estimate that had concentrations remained constant since 2001, an additional 4,700 (95%CI: 4,100–5,400) PM2.5-attributable deaths would have occurred in 2021 using a log–log CRF, or 4,400 (95% CI: 3,700–5,000) deaths using a log–linear CRF (Table 2). In recent years, reductions in Canadians’ PM2.5 exposure have thus led to thousands fewer PM2.5-attributable deaths annually.
Compared to previous Canadian analyses, we estimate a comparable mortality burden attributable to PM2.5 exposure. (8) In a recent study, Health Canada estimated 12,500 (95% CI: 6,600–18,300) deaths from long-term PM2.5 exposure in 2018 in Canada using satellite-based concentrations averaged between 2017 and 2019. That study applied the AQBAT default log–linear CRF with a risk estimate (θ) of 0.00953 (se = 0.00232) from the 1991 CanCHEC and a counterfactual of 1.8 μg/m3. (8) This is close to our estimate of 12,000 (95% CI: 10,200–13,800) deaths in 2021 using a log–linear CRF and PM2.5 exposures averaged over 2019–2021. For reductions in attributable deaths due solely to reductions in PM2.5 exposure since 2001, our study’s estimate for 2011 (Table 2) fell within the confidence interval of 780–6,100 for Stieb et al.’s similar analysis from 2000 to 2011, despite our use of a different CRF and a smaller exposure difference for the time period. (13) An American study by Fann and colleagues found that the PAF for mortality attributable to long-term PM2.5 exposure in the United States decreased by 1.5% between 2005 and 2014 based on CMAQ modeling for those two years, which is comparable to Canada’s change in PAF over a similar period (Table 2). (36)

3.3.1. Selection of the Concentration–Response Function

Using a log–log CRF resulted in larger estimates of PAF and PM2.5-attributable mortality in any given year than those based on a log–linear CRF (Table 2). Other studies have observed similar findings. (6,39,55) These elevated mortality estimates are a result of the shape of the log–log curve, whose key feature is the rapid rate-of-increase in mortality risk at low levels of exposure, resulting in hazard ratios that lie above those of the log–linear CRF across the vast majority of PM2.5 exposures in Canada (Supporting Information, Figure S1), leading to larger estimates of attributable deaths. (5,56) At PM2.5 concentrations close to 8.5 μg/m3, the marginal change in mortality risk (i.e., the change in risk per unit change in exposure) under the log–log CRF is larger than that of the log–linear CRF. As the majority of reductions in population exposure to PM2.5 between 2001 and 2021 resided within this range in Canada, we observe that the log–log CRF leads to larger reductions in attributable mortality (Table 2, rightmost column). For brevity, we employ the log–log CRF for all analyses hereafter, and present results based on the log–linear CRF in the Supporting Information.

3.3.2. Regional Variation in the Population Attributable Fraction

Canadian regions have experienced unique trends over time that are not apparent in the national mortality estimates presented thus far. To highlight trends driven solely by changes in PM2.5 concentrations, we depict regional variation in the PAF for mortality attributable to long-term PM2.5 exposure across the country in Figure 4, and Supporting Information, Figure S2 depicts the equivalent results when using a log–linear CRF. Select city-specific estimates are noted in Supporting Information, Table S4. A regional pattern emerges in the PAF, with eastern Canada seeing consistent decreases in the PAF, but western Canada facing increases, except coastal areas (Figure 4A). The greatest decreases in PAF have all occurred in the southernmost tip of Central Canada, of which nine of the ten most improved census divisions are located, where PAFs exhibited absolute decreases of between 4.6% (95% CI: 4.0–5.2%) and 5.6% (95% CI: 4.9%–6.4%) between 2001 and 2021 (Figure 4A, Cutout II). This has consistently been the region of greatest overall decrease in PAF across Canada over the last two decades. Similar to Canada, a comparable analysis in the United States showed that some of the largest reductions in PAF for mortality attributable to long-term PM2.5 exposure between 2005 and 2014 occurred in the Eastern United States. (36) We hypothesize that national and bilateral efforts between the United States and Canada have had widespread health benefits in the transboundary region, (49) alongside limited contributions from wildfire exposure, (47,52) but a more targeted analysis would be needed to provide definitive evidence of this connection. Meanwhile, areas with the highest PAFs have migrated (i.e., census divisions with the top 5% PAF) from the southern East Central airshed in 2001 to western Canada outside coastal regions in 2021. We hypothesize that these decadal increases in PAFs are influenced by wildfires as these census divisions tend to have the greatest wildfire smoke PM2.5 levels in Canada. (52)

Figure 4

Figure 4. A) Absolute change in the population attributable fraction (PAF, or the fraction of all nonaccidental deaths in the population aged 25 and over attributable to long-term [three-year average] PM2.5 exposure) between 2001 and 2021 and B) the PAF in 2021 for census divisions across Canada, using a log–log concentration–response function (CRF). Cutouts are shown for Southwestern British Columbia and Vancouver (I), Southwestern Ontario and the Greater Toronto Area (II), and Southern Quebec and the Greater Montreal region (III). See Supporting Information, Figure S2 for equivalent results when using a log–linear CRF.

3.3.3. Decomposition Analysis

In Canada, both a growing and increasingly vulnerable population (as measured by a changing baseline health status) have counteracted decreases in chronic population exposure to PM2.5, with a resulting net increase in PM2.5-attributable mortality counts over time even as the PAF has largely decreased (Table 2). We decompose this net effect into three driving factors in Figure 5: changing exposure (gray), population changes (orange), and changing baseline mortality rates (yellow) over the last two decades. We express this decomposition on a relative basis, using the percentage change in mortality burden since 2001 attributable to each factor for each Canadian airshed. Figure 5 illustrates the relative roles of these factors using a log–log CRF while Supporting Information, Figure S3 demonstrates the equivalent figure using a log–linear CRF. The choice of CRF does not strongly affect results, except for a more pronounced effect of changes in PM2.5 exposure on mortality using the log–linear model.

Figure 5

Figure 5. Contributions of changing baseline mortality rates, population and three-year average PM2.5 exposure to changes in PM2.5-attributable mortality since 2001 in the six Canadian airsheds and Canada overall using a log–log concentration–response function (CRF). Population and baseline mortality rates are for the population aged 25 and over. For the location of airsheds, see Figure 3. Supporting Information, Figure S3 demonstrates the equivalent figure using a log–linear CRF.

Improvements in ambient PM2.5 concentrations by 2021 have lowered the chronic exposure PM2.5 mortality burden compared to 2001 across Canada, with almost a quarter of PM2.5-attributable deaths across Canada reduced overall. This is driven by decreasing exposure in the populous East Central and Western Airsheds, followed by decreases in the Atlantic Region. The most notable exception to this is the Prairies airshed, and more recently, the West Central airshed, where increasing population growth has compounded with increasing three-year average PM2.5 exposure to result in increasing PM2.5 attributable mortality. While exposure changes have led to reductions in PM2.5-attributable mortality, at the same time, Canada’s population has grown and baseline mortality rates have increased since 2001 (Table 1, Supporting Information, Figure S4), leading to higher PM2.5-attributable mortality despite decreasing PM2.5 exposure. By 2021, a slightly increasing baseline mortality rate (yellow bars in Figure 5) suggests increasing Canadian population vulnerability to the effects of PM2.5 and is present in most airsheds, except the Prairies and Western airsheds. Aging is the primary driver of this trend in increasing baseline mortality rates. Between 2001 and 2021, the population aged 65 and older grew almost six times faster compared to the population younger than 65, with increases of 82% and 14%, respectively. During the same period, age-standardized baseline mortality rates gradually decreased for almost all age groups, indicating an overall healthier population. (25,57) Despite improvements in age-standardized mortality, since persons aged 65 and older still represent more than 80% of annual deaths in Canada, the overall effect of an aging population is a progressively higher death rate, and ultimately, increasing vulnerability to PM2.5 exposure (see Table 1). (57,58) Increased population growth in every airshed has contributed to a higher PM2.5 mortality burden since 2001 than if the population characteristics had remained unchanged in 2001. Regionally, the Prairies combine both the highest population growth and the fastest degrading air quality, creating conditions where a greater proportion of the population may face year-over-year worsening PM2.5-attributable mortality should trends continue. On the other hand, the Atlantic region has seen one of the most substantial increases in population vulnerability, yet this trend has been abated by even more significant decreases in PM2.5 concentrations. Looking forward, our results underline the importance of considering both a population’s exposure, vulnerability (as measured by baseline health status), and size when developing or prioritizing air quality policies and actions.
In recent decades, due to improving PM2.5 exposure, the PAF has declined in many high-income countries, and Canada is no exception. (6,18−20,36) However, despite a 18% decrease in population exposure to PM2.5 in Canada since 2001, and a 1.8% decrease in the PAF overall, the aggregate Canadian PM2.5 mortality burden has not decreased throughout 2001–2021. A similar situation has been characterized in China by Li et al. (22) and Yue et al. (17) who reported how population size and aging alongside regional migration (affecting age structure and population counts) have amplified the PM2.5 mortality burden, offsetting the gains attributable to air quality improvements from 2000 to 2020. In contrast, in the US, improvements in air quality have led to an overall decrease in mortality attributable to long-term PM2.5 exposure in the last two decades, likely due to differences in demographic changes from increasing population growth and vulnerability. (6,15,16,36) Canada follows the overall global pattern, (22) whereby aging or growing populations during the past decades have diminished reductions in PM2.5-attributable mortality resulting from decreased exposure to PM2.5, including in China, (17) Japan, (18) Korea, (18) Italy, (20) and the United States, (6) among other countries. (6,22)

3.4. Strengths and Limitations

This study is the first Canadian health impact analysis of two decades of ambient PM2.5 concentrations. Our use of year-specific population and baseline mortality rates enables us to conduct a dynamic analysis to examine drivers of health impacts over time, including how population growth, changes in baseline health status, and PM2.5 concentrations influence the PM2.5-attributable mortality burden. In addition, our general finding that decadal decreases in exposure to ambient PM2.5 have benefited health in Canada holds even with the use of two differently shaped CRFs. Despite these positive attributes, our study is not without limitations. Several parameters used to estimate PM2.5-attributable mortality contain uncertainty. Mortality estimates themselves are sensitive to the choice of counterfactual and shape of the CRF, as proven in our analyses using both log–linear and log–log CRFs. This was also reported by Chan et al. (37) in their estimates of PM2.5 mortality in the continental United States using several age, race and exposure stratified hazards ratios. They found that temporal trends in the incidence and rate of mortality could vary based on the target population. However, the overall patterns and trends observed in our results, both nationally and regionally, are robust against the choice of CRF, giving confidence that despite uncertainty in how rapidly mortality risk changes across exposures experienced in Canada, reductions in ambient PM2.5 concentrations have broadly benefited population health.
We report 95% CIs in our main analysis that were derived using 10,000 simulations in a Monte Carlo framework whereby the parameter estimate for any given CRF was allowed to vary by its standard error. These CIs do not reflect any uncertainty in PM2.5 concentrations, baseline mortality rates, or population as estimates of uncertainty in those parameters are not readily available, nor do the CIs reflect uncertainty as related to the choice of CRF itself. Due to limitations of the age-specific mortality rate data available, we could not disentangle the effects of population aging specifically in our decomposition analysis. In our analysis, population aging was indirectly reflected in increasing baseline mortality rates over time. Our estimates of PM2.5-attributable mortality were derived using three-year averages of PM2.5 concentrations that may still be influenced by natural variability, including severe or atypical air pollution events, such as wildfire smoke events. Despite this limitation, our findings compare reasonably with other scientific studies conducted in Canada and the United States, in terms of both nationwide trends and the geographic distribution of effects. We used PM2.5 concentration estimates from a single model that covered the entire analysis period and included both natural and anthropogenic sources. (26,27) It was critical to use a consistent, high-quality and peer reviewed modeling approach. No other exposure data sets were available at the time of this analysis. Chan et al. (37) compared PM2.5-attributable mortality estimates for the continental United States using various exposure models and HRs and found that HRs contribute more variability than exposure models to health impact estimates.
The regional variations reported reflect potential contributions from local, regional, and transboundary sources, as well as wildfire activity, concurring with other studies conducted in Canada and the United States. While every effort was made to ensure a consistent and accurate representation of PM2.5 concentrations, certain conditions can increase the uncertainty of our exposure data. Of note for Canada is the limited ability of satellite retrievals to provide an observational constraint away from ground-based observations in remote regions during seasons associated with snow cover. While the chemical transport model that continues to inform PM2.5 concentrations during these times is not without skill, this reduced constraint inherently increases exposure uncertainty. Regions with rapid topographical changes (i.e., mountains) would also experience enhanced uncertainty due to the challenge of representing the associated variability in the relationship between the total aerosol column, as observed by satellite, and PM2.5 concentrations at the surface. (28) Finally, we conducted health impact analysis using census divisions as the geographic unit of analysis due to the availability of baseline mortality data at the census division level. Census divisions are too coarse for investigating intraurban health impacts and limit the specificity of our results as exposure can range quite broadly within a single census division.
Future initiatives to lessen air pollution’s negative effects could benefit from further health impact analyses at finer geographic resolutions to better characterize the population groups most burdened by pollution, and the inequalities in exposure or health burden that may exist therein. Future work should seek to further decompose trends in PM2.5-attributable mortality by quantifying changes due to the effects of population aging, dependent on the availability of high-quality age-specific baseline mortality rates that are geographically resolved and age-specific air pollution risk estimates. Lastly, additional or more extensive sector- and source-specific retrospective health impact analyses could help clarify underlying reasons behind spatiotemporal variations in air pollution-attributable mortality.
Despite the uncertainties and limitations present in our analysis, we show that the Canadian population has benefited broadly from decreased PM2.5 exposure, likely due to air quality management initiatives implemented over the last two decades. Sizeable reductions in exposure to ambient PM2.5 are evident in the most populated parts of Canada, leading to thousands fewer PM2.5-attributable deaths annually in recent years. However, ambient air pollution continues to impact the health of the Canadian population up to the current day. Improvements in exposure are not shared ubiquitously, and a vast landmass now experiences higher PM2.5 levels than in 2001. Nevertheless, historical improvements in PM2.5 exposure in Canada over the last two decades have had significant benefits in reducing the health burden of ambient PM2.5 exposure.

Data Availability

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The data are available from the corresponding author upon reasonable request.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsestair.4c00130.

  • Additional information on exposure estimates, other model input data, and health impact results, including: descriptive statistics of satellite-based ambient PM2.5 concentrations in Canada, temporal data inputs to the health impact analysis, PM2.5-attributable mortality in Canada from 2001 to 2021 using a counterfactual of zero, log–linear and log–log CRFs from a Canadian cohort for long-term PM2.5 exposure and nonaccidental mortality, log–linear CRF analysis equivalents to Figures 4 and 5, regional city-specific estimates for PM2.5 health impacts, as well as regional baseline mortality and population changes in Canada (PDF)

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Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

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  • Corresponding Author
  • Authors
    • Elysia G. Fuller-Thomson - Water and Air Quality Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, CanadaOrcidhttps://orcid.org/0000-0002-1181-5550
    • Mathieu Rouleau - Water and Air Quality Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, Canada
    • Guoliang Xi - Environmental Health Science and Research Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, Canada
    • Aaron van Donkelaar - McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri 63130-4899, United StatesOrcidhttps://orcid.org/0000-0002-2998-8521
    • Randall V. Martin - McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri 63130-4899, United States
    • Richard T. Burnett - Environmental Health Science and Research Bureau, Healthy Environments and Consumer Products Safety Branch, Health Canada, Ottawa, Ontario K1A 0K9, Canada
  • Funding

    Open access funded by the Health Canada Library.

  • Notes
    Randall Martin’s spouse is a scientist at Health Canada; she had no role in the study.
    The authors declare no competing financial interest.

Acknowledgments

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This work was supported by Health Canada and did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. We wish to thank Dave Stieb for his insight and guidance. We obtained ambient PM2.5 concentrations from Washington University under Health Canada’s contract no. 4500432243.

References

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  • Abstract

    Figure 1

    Figure 1. Three-year average concentrations of ambient PM2.5 (μg/m3) in Canada over time, with cutouts of Southwestern British Columbia and Vancouver (I), Southwestern Ontario and the Greater Toronto Area (II), and Southern Quebec and the Greater Montreal region (III).

    Figure 2

    Figure 2. Change in three-year average PM2.5 concentrations in Canada from 2001 (negative values reflect decreasing PM2.5 concentrations), with cutouts of Southwestern British Columbia and Vancouver (I), Southwestern Ontario and the Greater Toronto Area (II) and Southern Quebec and the Greater Montreal region (III).

    Figure 3

    Figure 3. Changes in three-year, population-weighted, rolling averages of PM2.5 concentrations over time across the six Canadian airsheds.

    Figure 4

    Figure 4. A) Absolute change in the population attributable fraction (PAF, or the fraction of all nonaccidental deaths in the population aged 25 and over attributable to long-term [three-year average] PM2.5 exposure) between 2001 and 2021 and B) the PAF in 2021 for census divisions across Canada, using a log–log concentration–response function (CRF). Cutouts are shown for Southwestern British Columbia and Vancouver (I), Southwestern Ontario and the Greater Toronto Area (II), and Southern Quebec and the Greater Montreal region (III). See Supporting Information, Figure S2 for equivalent results when using a log–linear CRF.

    Figure 5

    Figure 5. Contributions of changing baseline mortality rates, population and three-year average PM2.5 exposure to changes in PM2.5-attributable mortality since 2001 in the six Canadian airsheds and Canada overall using a log–log concentration–response function (CRF). Population and baseline mortality rates are for the population aged 25 and over. For the location of airsheds, see Figure 3. Supporting Information, Figure S3 demonstrates the equivalent figure using a log–linear CRF.

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  • Supporting Information

    Supporting Information


    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsestair.4c00130.

    • Additional information on exposure estimates, other model input data, and health impact results, including: descriptive statistics of satellite-based ambient PM2.5 concentrations in Canada, temporal data inputs to the health impact analysis, PM2.5-attributable mortality in Canada from 2001 to 2021 using a counterfactual of zero, log–linear and log–log CRFs from a Canadian cohort for long-term PM2.5 exposure and nonaccidental mortality, log–linear CRF analysis equivalents to Figures 4 and 5, regional city-specific estimates for PM2.5 health impacts, as well as regional baseline mortality and population changes in Canada (PDF)


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