This study is part of a project which aims to compute the total deposition of sulfur, nitrogen and ozone over both Canada and the US. This initiative is named ADAGIO (Atmospheric Deposition Analysis Generated by Interpo-lation of model and Observations) and is led by Environment and Climate Change Canada. More details about the overall methodology were given in Part I of this project. Similarly, here, a deterministic data fusion methodology is used to combine information from air quality models and surface observations to produce seasonal objective analyses (OAs) for six gas species (O3,SO2, NO2, NO, HNO3, NH3) and three dry particulate species (p-NH4+, p-NO3-, p-SO4=) for multiple years during the period 2010-2019. The main difference in the methodology with PART II is that for dry species, the OAs are obtained for concentration instead of wet deposition measurements. The seasonal dry deposition fluxes and concentrations obtained from air quality model simulations for each species are corrected using the OA concentration fields to obtain the corrected total annual dry deposition. In part II, we focus on the species which contribute the most to the N deposition, that is NO2, HNO3, and NH3. ADAGIO yields total dry nitrogen deposition results that are in good agreement with those of the US/TDep project of the US. Comparison with satellite-derived concentrations for NH3 and NO2 are also presented and found reasonable. This paper demonstrated that the simple algorithm based on data fusion presented in part I (for wet species) also works for dry species deposition over large territories.

This study constitutes Part I of the ADAGIO project (Atmospheric Deposition Analysis Generated by Integrating Observations into model), initiated by Environment and Climate Change Canada (ECCC) to improve the accuracy of sulfur (S), nitrogen (N), and ozone deposition estimates across Canada and the United States. Using deterministic data fusion, it combines numerical models and ground-level observations to generate seasonal objective analyses (OAs) for twelve chemical species, including gases, particulates, and precipitation species, over multiple years (2010, 2013, 2014, 2015, 2016, 2019). OAs are computed seasonally to enable high-resolution estimates of annual total deposition, validate air quality models, assess model errors, and evaluate ecosystem impacts, such as acidification and eutrophication. ADAGIO employs Optimal Interpolation, optimized through sensitivity tests, to integrate measurements with archived outputs from ECCC's GEM-MACH regional air quality model. The ADAGIO project spans three papers, addressing wet deposition (pollutants in precipitation), dry deposition (gas and particles deposited onto surfaces), and total annual deposition (wet and dry combined). Objectives of ADAGIO include deriving total annual N and S deposition over North America and comparing seasonal OAs with model outputs to identify biases and errors. Part I, presented here, focuses on wet deposition and represents the first application of optimal interpolation for fusing wet deposition estimates with observational data over a conti- nental scale. This innovative approach using OI marks a significant advancement in deposition data fusion methodologies over North America

Air pollution, aeroallergens, and weather conditions can worsen health symptoms such as asthma. While studying the impact of these factors, the use of weather types (WTs) rather than individual meteorological variables (such as temperature, relative humidity, wind, cloudiness, or precipitation) is more appropriate since it is holistic and integrative. Moreover, several studies have shown that the human body responds to WTs, rather than to individual meteorological variables. In this study, the use of Sheridan’s WTs is adopted and compared with a so-called “In-House” WTs. The analysis presented here deals with the links between asthma hospitalization and the synergy among air pollution, birch tree pollen and WTs. Knowing the daily WT in a region can provide valuable information for health planning and management of asthma hospitalization, emergency visits and sub-clinical symptoms in the population. This is because air pollution and birch pollen both occur within only a few specific WTs, such as the TROWAL (trough of warm air aloft) or tropical airmasses. These specific WTs need to be more scrutinized since, in Montreal, these are often linked with higher daily mean hospitalization. The findings of this study emphasize the importance of specific WTs in determining the maximum daily concentrations of ozone, fine particles, Betula pollen concentrations and health effects such as asthma hospitalization. Moreover, the use of data filters in the analysis (for temperature and total count of hospitalization) also reveals new insights in the complex nature of asthma disease and its relationship with environmental factors.

Owing to their greater outdoor activity and ongoing lung development, children are particularly vulnerable to the harmful effects of exposure to fine particulate matter (PM2.5). However, the effects of PM2.5 components are poorly understood. This study aimed to use a longitudinal birth cohort of children with physician-diagnosed incident asthma to investigate the effect of PM2.5 components at birth on morbidity measured by health services utilization. Of 1277 Toronto Child Health Evaluation Questionnaire (T-CHEQ) participants, the study population included 362 children diagnosed with asthma who were followed for a mean of 13 years from birth until March 31, 2016, or loss-to-follow-up. Concentrations of PM2.5 and its components were assigned based on participants' postal codes at birth. Study outcomes included counts of asthma, asthma-related, and all-cause health services use. Poisson regression in single-, two-, and multi-pollutant models was used to estimate rate ratios (RR) per interquartile range (IQR) increase of exposures. Covariates were included in all models to further adjust for potential confounding. The adjusted RR for sulfate (SO4) and all-cause hospitalizations was statistically significant with RR = 2.23 (95% confidence interval [CI]: 1.25-3.96) in a multi-pollutant model with nitrogen dioxide (NO2) and ozone (O3). In multi-pollutant models with oxidants, the adjusted RRs for SO4 of all-cause hospitalizations and emergency department (ED) visits were also statistically significant with RR = 2.31 (95% CI: 1.32-4.03) and RR = 1.39 (95% CI: 1.02-1.90), respectively. While unadjusted single-pollutant RRs for asthma-specific and asthma-related health services use with the SO4 component of PM2.5 were above one, none were statistically significant. This study found significant associations with exposure to SO4 in PM2.5 and all-cause acute care, chiefly for hospitalizations, in children with asthma.

We used a large national cohort in Canada to assess the incidence of acute myocardial infarction (AMI) and stroke hospitalizations in association with long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3). The study population comprised 2.7 million respondents from the 2006 Canadian Census Health and Environment Cohort (CanCHEC), followed for incident hospitalizations of AMI or stroke between 2006 and 2016. We estimated 10-year moving average estimates of PM2.5, NO2, and O3, annually. We used Cox proportional hazards models to examine the associations adjusting for various covariates. For AMI, each interquartile range (IQR) increase in exposure was found to be associated with a hazard ratio of 1.026 (95% CI: 1.007-1.046) for PM2.5, 1.025 (95% CI: 1.001-1.050) for NO2, and 1.062 (95% CI: 1.041-1.084) for O3, respectively. Similarly, for stroke, an IQR increase in exposure was associated with a hazard ratio of 1.078 (95% CI: 1.052-1.105) for PM2.5, 0.995 (95% CI: 0.965-1.030) for NO2, and 1.055 (95% CI: 1.028-1.082) for O3, respectively. We found consistent evidence of positive associations between long-term exposures to PM2.5, and O3, and to a lesser degree NO2, with incident AMI and stroke hospitalizations.

Simulating allergenic tree pollen is important to protect sensitive population and to support bioaerosols monitoring effort. Using the regional air quality model GEM-MACH, a simulation was conducted adopting two new main hypotheses: 1) the use of vertical correlation concept to force the vertical dispersion (a method normally used in tracer data assimilation) and, 2) the use of a puff instead of a continuous pollen release. The simulation was compared with pollen observations in Montreal and with the corresponding statistical forecasts (issued daily by the Weather Network) at several locations in the province of Quebec and elsewhere. The comparison with the simulation was found satisfactory (outperform forecasts based on persistence or pollen calendar and is also superior to numerical simulation of tree pollen done elsewhere in North America). Simulation shows that, for the 2012 pollen season, the majority (88%) of the Betula pollen measured in Montreal originated from the Laurentides region. Another result of scientific importance obtained here is that Betula pollen episodes (observed or simulated birch pollen) in Montreal occur only when the average daily temperature is in the range of 10° to 18 °C. This research is considered as a first step in forecasting bioaerosols in Canada within an air quality model.

Environmental factors such as air pollution are known to exacerbate respiratory illness and increase the overall health risk. However, on a daily or seasonal basis, the relation between air pollutants, weather and a disease such as asthma is not clear. When combined with aeroallergens such as birch pollen and under specific weather conditions, synergistic effects may increase symptoms of respiratory illness and morbidity and then reveal interesting links with environmental factors. Hence, it is important to improve the understanding of pollution-pollen-weather and broaden the public health message. Combined analysis and model simulation of aeroallergens, air pollution and weather as presented here is important to correctly evaluate health burdens and allow a better forecast of the potential health risk. However, analyzing the combined effects of several environmental factors is not well understood and represents a challenging task. This paper shows: (1) the results of data analysis performed in Montreal for asthma hospitalization in relation to complex synergistic environmental factors, and (2) model simulation of birch pollen using a coupled weather-air quality model (GEM-MACH) compared with model-data fusion of classical chemical species (e.g., near-surface ozone, nitrogen dioxide and fine particulate matter) in order to evaluate spatiotemporal vulnerable zone for asthma health risk.

According to the literature, it is estimated that outdoor air pollution is responsible for the premature death in a range from 3.7 to 8.9 million persons on an annual basis across the world. Although there is uncertainty on this figure, outdoor air pollution represents one of the greatest global risks to human health. In North America, the rapid evolution of technologies (e.g., nanotechnology, unconventional oil and gas rapid development, higher demand for fertilizers in agriculture) and growing demand for ground, marine and air transportation may result in significant increases of emissions of pollutants that have not been carefully studied so far. As a result, these atmospheric pollutants insufficiently addressed by science in Canada and elsewhere are becoming a growing issue with likely human and environmental impacts in the near future. Here, an emerging pollutant is defined as one that meets the following criteria: 1) potential or demonstrated risk for humans or the environment, 2) absence of Canada-wide national standard, 3) insufficient routine monitoring, 4) yearly emissions greater than one ton in Canada, 5) insufficient data concerning significant sources, fate, and detection limit, and 6) insufficiently addressed by epidemiological studies. A new methodology to rank emerging pollutants is proposed here based on weighting multiple criteria. Some selected emerging issues are also discussed here and include the growing concern of ultrafine or nanoparticles, growing ammonia emissions (due to rapid expansion of the agriculture), increased methane/ethane/propane emissions (due to the expanding hydraulic fracturing in the oil and gas sector) and the growing transportation sector. Finally, the interaction between biological and anthropogenic pollution has been found to be a double threat for public health. Here, a multidisciplinary and critical overview of selected emerging pollutants and related critical issues is presented with a focus in Canada.Implications: This overview paper provides a selection methodology for emerging pollutants in the atmospheric environment. It also provides a critical discussion of some related issues. The ultimate objective is to inform about the need to 1) address emerging issues through adequate surface monitoring and modeling in order to inform the development of regulations, 2) reduce uncertainties by geographically mapping emerging pollutants (e.g., through data fusion, data assimilation of observations into air quality models) which can improve the scientific support of epidemiological studies and policies. This review also highlights some of the difficulties with the management of these emerging pollutants, and the need for an integrated approach.

A coupled stratospheric chemistry–meteorology model was developed by combining the Canadian operational weather prediction model Global Environmental Multiscale (GEM) with a comprehensive stratospheric photochemistry model from the Belgian Assimilation System for Chemical ObsErvations (BASCOE). The coupled model was called GEM-BACH for GEM-Belgian Atmospheric CHemistry. The coupling was made across a chemical interface that preserves time-splitting while being modular, allowing GEM to run with or without chemistry. An evaluation of the coupling was performed by comparing the coupled model, refreshed by meteorological analyses every 6 h, against the standard offline chemical transport model (CTM) approach. Results show that the dynamical meteorological consistency between meteorological analysis times far outweighs the error created by the jump resulting from the meteorological analysis increments at regular time intervals, irrespective of whether a 3D-Var or 4D-Var meteorological analysis is used. Arguments in favor of using the same horizontal resolution for chemistry, meteorology, and meteorological and chemical analysis increments are also presented. GEM-BACH forecasts refreshed by meteorological analyses every 6 h were compared against independent measurements of temperature, long-lived species, ozone and water vapor. The comparison showed a relatively good agreement throughout the stratosphere except for an upper-level warm temperature bias and an ozone deficit of nearly 15%. In particular, the coupled model simulation during an ozone hole event gives better ozone concentrations than a 4D-Var chemical assimilation at a lower resolution.

BACKGROUND:Individual and neighbourhood-scale socioeconomic characteristics modify associations between exposure to air pollution and mortality. The role of stress, which may integrate effects of social and environmental exposures on health, is unknown. We examined whether an individual's perspective on their own well-being, as assessed using self-rated measures of stress and health, modifies the pollutant-mortality relationship. METHODS:The Canadian Community Health Survey (CCHS)-mortality cohort includes respondents from surveys administered between 2001 and 2012 linked to vital statistics and postal codes from 1981 until 2016. Annual fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) exposure estimates were attached to a sample of cohort members aged 30-89 years (n = 398,300 respondents/3,848,400 person-years). We examined whether self-rated stress, distress, mental health, and general health modified associations between long-term exposure to each pollutant (three-year moving average with one-year lag) and non-accidental mortality using Cox survival models, adjusted for individual- (i.e. socioeconomic and behavioural) and neighbourhood-scale covariates. RESULTS:In fully-adjusted models, the relationship between exposure to pollutants and mortality was stronger among those with poor self-rated mental health, including a significant difference for NO2 (hazard ratio (HR) = 1.15, 95% CI 1.06-1.25 per IQR) compared to those with very good/excellent mental health (HR = 1.05, 95% CI 1.01-1.08; Cochran's Q = 4.01; p < 0.05). Poor self-rated health was similarly associated with higher pollutant-associated HRs, but only in unadjusted models. Stress and distress did not modify pollutant-mortality associations. CONCLUSIONS:Poor self-rated mental and general health were associated with increased mortality attributed to exposure to ambient pollutants.

The aim of this study is to analyze the synergy between environmental factors (pollutant, allergenic birch pollen, weather) and its relationship with asthma hospitalization in Montreal, Canada. The data is stratified into weather types and the study restricted to spring season to limit the impact of multiple confounders. Results shows that the daily count of asthma hospitalization (spring 2006–2008) in situation of warm fronts or trowals (daily average of 3.78 counts, CI 95% 2.95–4.61) was much higher ( p < 0.001) than in other situations (2.49 counts, CI 95% 2.37–2.71). Moreover, the explained variance of asthma hospitalization due to air pollution rises from about less than 7% (in the case of no stratification) to about 28% ( R = 0.53, p < 0.05 with stratification). Statistical tests for interaction and overall results point towards a synergy between environmental factors which exacerbates asthma. A new concept named frontal asthma is proposed to explain several results found here and in the open literature.

We examine data assimilation coupling between meteorology and chemistry in the stratosphere from both weak and strong coupling strategies. The study was performed with the Canadian operational weather prediction Global Environmental Multiscale (GEM) model coupled online with the photochemical stratospheric chemistry model developed at the Belgian Institute for Space Aeronomy, described in Part I. Here, the Canadian Meteorological Centre’s operational variational assimilation system was extended to include errors of chemical variables and cross-covariances between meteorological and chemical variables in a 3D-Var configuration, and we added the adjoint of tracer advection in the 4D-Var configuration. Our results show that the assimilation of limb sounding observations from the MIPAS instrument on board Envisat can be used to anchor the AMSU-A radiance bias correction scheme. Additionally, the added value of limb sounding temperature observations on meteorology and transport is shown to be significant. Weak coupling data assimilation with ozone–radiation interaction is shown to give comparable results on meteorology whether a simplified linearized or comprehensive ozone chemistry scheme is used. Strong coupling data assimilation, using static error cross-covariances between ozone and temperature in a 3D-Var context, produced inconclusive results with the approximations we used. We have also conducted the assimilation of long-lived species observations using 4D-Var to infer winds. Our results showed the added value of assimilating several long-lived species, and an improvement in the zonal wind in the Tropics within the troposphere and lower stratosphere. 4D-Var assimilation also induced a correction of zonal wind in the surf zone and a temperature bias in the lower tropical stratosphere.

Environment and Climate Change Canada’s ADAGIO project (Atmospheric Deposition Analysis Generated by Optimal Interpolation using Observations) produces maps of wet, dry and total annual deposition of oxidized and reduced nitrogen (N) and sulphur (S) and ozone in Canada and the United States by combining in an optimal way observed and modeled data. Optimal interpolation methods are used to provide the best objective analyses of seasonally-averaged surface concentrations of gaseous, particulate, and precipitation species predicted by Environment and Climate Change Canada’s in-line regional air quality model GEM-MACH (Global Environmental Multiscale model—Modelling Air quality and Chemistry) based on the difference between the modeled and measured values at network observation sites. The resulting objective analyses (OA) for gas and particulate species concentration fields are then combined with effective deposition velocities from GEM-MACH to calculate dry deposition. Concentrations of precipitation ions are combined with precipitation amounts from the Canadian Precipitation Analysis (CaPA), in which all available precipitation data sets are used to adjust precipitation amounts predicted by GEM, to calculate wet deposition. Results from the 2010 development year are compared with previously-generated wet deposition kriging maps, results from the USEPA’s Total Deposition (TDEP) method, and surface measurements not used in the analysis where available. It was found that the biggest sources of uncertainties are the dry deposition velocities and error statistics (weight matrix used to produce OA). Therefore, more work is needed to reduce these uncertainties.

A coupled stratospheric chemistry-meteorology model was developed by combining the Canadian operational weather prediction model Global Environmental Multiscale (GEM) with a comprehensive stratospheric photochemistry model from the Belgian Assimilation System for Chemical ObsErvations (BASCOE). The coupled model was called GEM-BACH for GEM-Belgian Atmospheric CHemistry. The coupling was made across a chemical interface that preserves time splitting while being modular, allowing GEM to run with or without chemistry. An evaluation of the coupling was performed by comparing the coupled model, refreshed by meteorological analyses every 6 hours, against the standard offline chemical transport model (CTM) approach. Results show that the dynamical meteorological consistency between meteorological analysis times far outweighs the error created by the jump resulting from the meteorological analysis increments at regular time intervals, irrespective whether a 3D-Var or 4D-Var meteorological analysis is used. GEM-BACH forecast refreshed by meteorological analyses every 6 hours were compared against independent measurements of temperature, long-lived species, ozone and water vapor. The comparison showed a relatively good agreement throughout the stratosphere except for an upper-level warm temperature bias and an ozone deficit of nearly 15%. Arguments in favor of using the same horizontal resolution for chemistry, meteorology, and meteorological analysis increments are also presented. In particular, the coupled model simulation during an ozone hole event gives better ozone concentrations than a 4D-Var chemical assimilation at a lower resolution.

RationaleThere is growing evidence that air pollution may contribute to the development of childhood asthma and other allergic diseases. In this follow-up of the Toronto Child Health Evaluation Questionnaire (T-CHEQ) study, we examined associations between early life exposures to air pollution and incidence of asthma, allergic rhinitis and eczema from birth through adolescence.Methods1286 T-CHEQ participants were followed from birth until outcome (March 31, 2016) or loss to follow-up, with a mean of 17 years of follow-up. Concentrations of nitrogen dioxide (NO2), ozone (O3) and particulate matter with a 50% cut-off aerodynamic diameter of 2.5 µm (PM2.5) from January 1, 1999 to December 31, 2012 were assigned to participants based on their postal codes at birth using ground observations, chemical/meteorological models, remote sensing and land-use regression models. Study outcomes included incidence of physician-diagnosed asthma, allergic rhinitis and eczema. Cox proportional hazard regression models were used to estimate hazard ratios per interquartile range of exposures and outcomes, adjusting for potential confounders.ResultsHazard ratios of 1.17 (95% CI 1.05–1.31) for asthma and 1.07 (95% CI 0.99–1.15) for eczema were observed for total oxidants (O3and NO2) at birth. No significant increase in risk was found for PM2.5.ConclusionsExposures to oxidant air pollutants (O3and NO2) but not PM2.5were associated with an increased risk of incident asthma and eczema in children. This suggests that improving air quality may contribute to the prevention of asthma and other allergic disease in childhood and adolescence.

ObjectivesTo estimate the proportion of the Canadian population that is more susceptible to adverse effects of ozone (O3) and fine particle (PM2.5) air pollution exposure and how this varies by health region alongside ambient concentrations of O3 and PM2.5.MethodsUsing data from the census, the Canadian Community Health Survey, vital statistics and published literature, we generated cross-sectional estimates for 2014 of the proportions of the Canadian population considered more susceptible due to age, chronic disease, pregnancy, outdoor work, socio-economic status, and diet. We also estimated 2010–2012 average concentrations of O3 and PM2.5. Analyses were conducted nationally and for 110 health regions.ResultsRestrictive criteria (age < 10 or ≥ 75; asthma, chronic obstructive pulmonary disease, heart disease, or diabetes; pregnancy) suggested that approximately one third of the Canadian population is more susceptible, while inclusive criteria (restrictive plus age 10–19 and 65–74, outdoor work, less than high school education, low vitamin C intake) increased this proportion to approximately two thirds. Across health regions, estimates ranged from 24.4% to 41.2% (restrictive) and 61.2% to 87.0% (inclusive). Ten health regions were in the highest quartile of both population susceptibility and O3 or PM2.5 concentrations, all of which were outside major urban centres.ConclusionsA substantial proportion of the Canadian population exhibits at least one risk factor that increases their susceptibility to adverse effects of O3 and PM2.5 exposure. Both risk communication and management interventions need to be increasingly targeted to regions outside large urban centres in the highest quartiles of both susceptibility and exposure.RésuméObjectifsEstimer la proportion de la population canadienne qui est plus susceptible aux effets indésirables de l’exposition à la pollution de l’air par l’ozone (O3) et les particules fines (PM2,5), ainsi que les variations de cette proportion selon la région sanitaire et les concentrations ambiantes d’O3 et de PM2,5.MéthodeÀ l’aide des données du recensement, de l’Enquête sur la santé dans les collectivités canadiennes, des statistiques de l’état civil et des travaux publiés, nous avons généré des estimations transversales, pour l’année 2014, des proportions de la population canadienne jugées plus susceptibles aux effets de la pollution de l’air en raison de l’âge, des maladies chroniques, de la grossesse, du travail en plein air, du statut socioéconomique et du régime alimentaire. Nous avons aussi estimé les concentrations moyennes d’O3 et de PM2,5 en 2010-2012. Des analyses ont été menées pour l’ensemble du pays et pour 110 régions sanitaires.RésultatsSelon les critères restrictifs (< 10 ans ou ≥ 75 ans; asthme, maladie pulmonaire obstructive chronique, cardiopathie ou diabète; grossesse), environ le tiers de la population canadienne est plus susceptible aux effets de la pollution de l’air, tandis que les critères inclusifs (critères restrictifs plus : 10 à 19 ans et 65 à 74 ans; travail en plein air; niveau de scolarité inférieur au diplôme d’études secondaires; faible apport en vitamine C) gonflent cette proportion à environ les deux tiers. Dans les régions sanitaires, les estimations ont varié entre 24,4 % et 41,2 % (critères restrictifs) et entre 61,2 % et 87 % (critères inclusifs). Dix régions sanitaires se classaient dans le quartile supérieur tant pour la susceptibilité de leur population que pour les concentrations d’O3 ou de PM2,5; toutes étaient situées hors des grands centres urbains.ConclusionsUne proportion considérable de la population canadienne présente au moins un facteur de risque qui augmente sa susceptibilité aux effets indésirables de l’exposition à l’O3 et aux PM2,5. La communication des risques et les interventions de gestion doivent être de plus en plus ciblées sur les régions hors des grands centres urbains qui se classent dans les quartiles supérieurs pour la susceptibilité et l’exposition.

Les pollutions anthropique et biologique ont toutes les deux un impact négatif sur la santé humaine. L’analyse de deux métriques (fédérale et provinciale) basées sur des indices de qualité de l’air couramment utilisés dans la province de Québec (Canada) montre un lien statistique significatif avec un indicateur de santé respiratoire évalué pour différentes régions de la province. Mais lorsqu’elle est combinée avec la pollution biologique au printemps (exprimée par les taux simulés d’émission régionale de pollen de Betula), cette corrélation devient plus élevée : R2 passe alors de valeurs inférieures à 0,5 à environ 0,76 (p < 0,0001). On explique ici cette augmentation par le phénomène de synergie entre la pollution anthropique et le pollen de Betula. Cette synergie est décrite dans la littérature, entre autres, par le concept de polluen (polluant + pollen), une combinaison présentant plus de risque pour la santé respiratoire que la pollution anthropique ou le pollen pris séparément. Les résultats de l’étude présentée ici suggèrent que la synergie entre la pollution anthropique et biologique doit être prise en compte. Ainsi, les indices de qualité de l’air actuels devraient intégrer la notion de pollution biologique pour mieux représenter le risque total pour la santé respiratoire des populations, que ce soit au Canada, en France ou ailleurs.

Estimates of potential harmful effects on ecosystems in the Canadian provinces of Alberta and Saskatchewan due to acidifying deposition were calculated, using a 1-year simulation of a high-resolution implementation of the Global Environmental Multiscale-Modelling Air-quality and Chemistry (GEM-MACH) model, and estimates of aquatic and terrestrial ecosystem critical loads. The model simulation was evaluated against two different sources of deposition data: total deposition in precipitation and total deposition to snowpack in the vicinity of the Athabasca oil sands. The model captured much of the variability of observed ions in wet deposition in precipitation (observed versus model sulfur, nitrogen and base cation R2 values of 0.90, 0.76 and 0.72, respectively), while being biased high for sulfur deposition, and low for nitrogen and base cations (slopes 2.2, 0.89 and 0.40, respectively). Aircraft-based estimates of fugitive dust emissions, shown to be a factor of 10 higher than reported to national emissions inventories (Zhang et al., 2018), were used to estimate the impact of increased levels of fugitive dust on model results. Model comparisons to open snowpack observations were shown to be biased high, but in reasonable agreement for sulfur deposition when observations were corrected to account for throughfall in needleleaf forests. The model–observation relationships for precipitation deposition data, along with the expected effects of increased (unreported) base cation emissions, were used to provide a simple observation-based correction to model deposition fields. Base cation deposition was estimated using published observations of base cation fractions in surface-collected particles (Wang et al., 2015).Both original and observation-corrected model estimates of sulfur, nitrogen, and base cation deposition were used in conjunction with critical load data created using the NEG-ECP (2001) and CLRTAP (2017) methods for calculating critical loads, using variations on the Simple Mass Balance model for terrestrial ecosystems, and the Steady State Water Chemistry and First-order Acidity Balance models for aquatic ecosystems. Potential ecosystem damage was predicted within each of the regions represented by the ecosystem critical load datasets used here, using a combination of 2011 and 2013 emissions inventories. The spatial extent of the regions in exceedance of critical loads varied between 1 × 104 and 3.3 × 105 km2, for the more conservative observation-corrected estimates of deposition, with the variation dependent on the ecosystem and critical load calculation methodology. The larger estimates (for aquatic ecosystems) represent a substantial fraction of the area of the provinces examined.Base cation deposition was shown to be sufficiently high in the region to have a neutralizing effect on acidifying deposition, and the use of the aircraft and precipitation observation-based corrections to base cation deposition resulted in reasonable agreement with snowpack data collected in the oil sands area. However, critical load exceedances calculated using both observations and observation-corrected deposition suggest that the neutralization effect is limited in spatial extent, decreasing rapidly with distance from emissions sources, due to the rapid deposition of emitted primary dust particles as a function of their size. We strongly recommend the use of observation-based correction of model-simulated deposition in estimating critical load exceedances, in future work.

Background: Diabetes is infrequently coded as the primary cause of death but may contribute to cardiovascular disease (CVD) mortality in response to fine particulate matter (PM 2.5 ) exposure. We analyzed all contributing causes of death to examine susceptibility of diabetics to CVD mortality from long-term exposure. Methods: We linked a subset of the 2001 Canadian Census Health and Environment Cohort (CanCHEC) with 10 years of follow-up to all causes of death listed on death certificates. We used survival models to examine the association between CVD deaths (n = 123,500) and exposure to PM 2.5 among deaths that co-occurred with diabetes (n = 20,600) on the death certificate. More detailed information on behavioral covariates and diabetes status at baseline available in the Canadian Community Health Survey (CCHS)-mortality cohort (n = 12,400 CVD deaths, with 2,800 diabetes deaths) complemented the CanCHEC analysis. Results: Among CanCHEC subjects, comention of diabetes on the death certificate increased the magnitude of association between CVD mortality and PM 2.5 (HR = 1.51 [1.39–1.65] per 10 μg/m 3 ) versus all CVD deaths (HR = 1.25 [1.21–1.29]) or CVD deaths without diabetes (HR = 1.20 [1.16–1.25]). Among CCHS subjects, diabetics who used insulin or medication (included as proxies for severity) had higher HR estimates for CVD deaths from PM 2.5 (HR = 1.51 [1.08–2.12]) relative to the CVD death estimate for all respondents (HR = 1.31 [1.16–1.47]). Conclusions: Mention of diabetes on the death certificate resulted in higher magnitude associations between PM 2.5 and CVD mortality, specifically among those who manage their diabetes with insulin or medication. Analyses restricted to the primary cause of death likely underestimate the role of diabetes in air pollution–related mortality. See video abstract at, http://links.lww.com/EDE/B408.