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In late June 2021 a heatwave of unprecedented magnitude impacted the Pacific Northwest (PNW) region of Canada and the United States. Many locations broke all-time maximum temperature records by more than 5°C, and the Canadian national temperature record was broken by 4.6°C, with the highest recorded temperature 49.6°C. Local records were broken by large margins, even when compared to local records broken during the infamous heatwaves in Europe 2003, and Russian in 2010. A region of high pressure that became stationary over the region (an atmospheric block) was the dominant cause of this heatwave; however, trajectory analysis finds that upstream diabatic heating played a key role in the magnitude of the temperature anomalies. Weather forecasts provided advanced notice of the event, while sub-seasonal forecasts showed an increased likelihood of a heat extreme with 10-20 day lead times, with an increased likelihood of a blocking event seen in forecasts initialized 3 weeks prior to the heatwave peak. The impacts of this event were catastrophic. We provide a summary of some of these impacts, including estimates of hundreds of attributable deaths across the PNW, mass-mortalities of marine life, reduced crop and fruit yields, river flooding from rapid snow and glacier melt, and a substantial increase in wildfires—the latter contributing to devastating landslides in the months following. These impacts provide examples we can learn from, and a vivid depiction of how climate change can be so devastating.

Purpose of Review Increasing wildfire size and severity across the western United States has created an environmental and social crisis that must be approached from a transdisciplinary perspective. Climate change and more than a century of fire exclusion and wildfire suppression have led to contemporary wildfires with more severe environmental impacts and human smoke exposure. Wildfires increase smoke exposure for broad swaths of the US population, though outdoor workers and socially disadvantaged groups with limited adaptive capacity can be disproportionally exposed. Exposure to wildfire smoke is associated with a range of health impacts in children and adults, including exacerbation of existing respiratory diseases such as asthma and chronic obstructive pulmonary disease, worse birth outcomes, and cardiovascular events. Seasonally dry forests in Washington, Oregon, and California can benefit from ecological restoration as a way to adapt forests to climate change and reduce smoke impacts on affected communities. Recent Findings Each wildfire season, large smoke events, and their adverse impacts on human health receive considerable attention from both the public and policymakers. The severity of recent wildfire seasons has state and federal governments outlining budgets and prioritizing policies to combat the worsening crisis. This surging attention provides an opportunity to outline the actions needed now to advance research and practice on conservation, economic, environmental justice, and public health interests, as well as the trade-offs that must be considered. Summary Scientists, planners, foresters and fire managers, fire safety, air quality, and public health practitioners must collaboratively work together. This article is the result of a series of transdisciplinary conversations to find common ground and subsequently provide a holistic view of how forest and fire management intersect with human health through the impacts of smoke and articulate the need for an integrated approach to both planning and practice.

This review addresses knowledge gaps in cannabis cultivation facility (CCF) air emissions by synthesizing the peer-reviewed and gray literature. Focus areas include compounds emitted, air quality indoors and outdoors, odor assessment, and the potential health effects of emitted compounds. Studies suggest that β-myrcene is a tracer candidate for CCF biogenic volatile organic compounds (BVOCs). Furthermore, β-myrcene, d-limonene, terpinolene, and α-pinene are often reported in air samples collected in and around CCF facilities. The BVOC emission strength per dry weight of plant is higher than most conventional agriculture crops. Nevertheless, reported total CCF BVOC emissions are lower compared with VOCs from other industries. Common descriptors of odors coming from CCFs include "skunky", "herbal", and "pungent". However, there are few peer-reviewed studies addressing the odor impacts of CCFs outdoors. Atmospheric modeling has been limited to back trajectory models of tracers and ozone impact assessment. Health effects of CCFs are mostly related to odor annoyance or occupational hazards. We identify 16 opportunities for future studies, including an emissions database by strain and stage of life (growing cycle) and odor-related setback guidelines. Exploration and implementation of key suggestions presented in this work may help regulators and the industry reduce the environmental footprint of CCF facilities.

Springtime road dust is a common air quality concern for northern latitudes communities. Traction material, brake wear, tire wear, and other particles entrained in snow during winter become re-suspended into the air as the snow melts. Characterization of within-season variability of road dust composition and weather conditions is critical to understanding its acute health impacts. Sixty 24-hour samples of PM10 were collected with a high-volume sampler at a near-road site in Prince George, British Columbia. Near-road samples were collected intermittently in winter and daily in spring. All samples were analyzed for 18 trace elements. We used data from a nearby regulatory monitor to estimate daily coarse fraction (PM10–2.5). Proportion of PM10–2.5 in PM10 was used to classify days as high or low road dust based on a threshold of 65% PM10–2.5. We identified clusters of near-road samples based on weather parameters and PM10 components using Bayesian profile regression (BPR). Twenty-one near-road PM10 samples were classified as high road dust days and 34 as low road dust days. Concentrations of total trace elements and specific trace elements were significantly higher on high road dust days (aluminum, chromium, iron, lead, tin, vanadium, and zinc). High road dust days also had low relative humidity and precipitation and higher temperature and air pressure. We identified five clusters of near-road PM10 mixtures that suggested an interaction between temperature and humidity for road dust impacts. Samples from a near-road site indicated days highly affected by springtime road dust are distinct from other days based on particulate mixtures and meteorological factors. Higher loading of trace element mixtures in PM10 on high road dust days has important implications for acute toxicity of road dust. Relationships between road dust and weather may facilitate further research into health effects of road dust as the climate changes. Implications: Non-tailpipe emissions driven by springtime road dust in northern latitude communities is increasing in importance for air pollution control and improving our understanding of the health effects of chemical mixtures from particulate matter exposure. High-volume samples from a near-road site indicated that days affected by springtime road dust are substantively different from other days with respect to particulate matter mixture composition and meteorological drivers. The high load of trace elements in PM10 on high road dust days has important implications for the acute toxicity of inhaled air and subsequent health effects. The complex relationships between road dust and weather identified in this study may facilitate further research on the health effects of chemical mixtures related to road dust while also highlighting potential changes in this unique form of air pollution as the climate changes.

Wildfire smoke is a rapidly growing threat to global cardiovascular health. We review the literature linking wildfire smoke exposures to cardiovascular effects. We find substantial evidence that short-term exposures are associated with key cardiovascular outcomes, including mortality, hospitalization, and acute coronary syndrome. Wildfire smoke exposures will continue to increase over the majority of Earth’s surface. For example, the United States alone has experienced a 5-fold increase in annual area burned since 1972, with 82 million individuals estimated to be exposed to wildfire smoke by midcentury. The associated rise in excess morbidity and mortality constitutes a growing global public health crisis. Fortunately, the effect of wildfire smoke on cardiovascular health is modifiable at the individual and population levels through specific interventions. Health systems therefore have an opportunity to help safeguard patients from smoke exposures. We provide a roadmap of evidence-based interventions to reduce risk and protect cardiovascular health. Key interventions include preparing health systems for smoke events; identifying and educating vulnerable patients; reducing outdoor activities; creating cleaner air environments; using air filtration devices and personal respirators; and aggressive management of chronic diseases and traditional risk factors. Further research is needed to test the efficacy of interventions on reducing cardiovascular outcomes.

There is increasing evidence that long-term exposure to fine particulate matter [PMWe aimed to evaluate the associations between daily and subdaily (hourly)Scores from 20 plays of an attention-oriented brain-training game were obtained for 10,228 adults in the United States (U.S.). We estimated daily and hourlyDaily and subdailyOur results indicate that

Exposure to biomass smoke has been associated with a wide range of acute and chronic health outcomes. Over the past decades, the frequency and intensity of wildfires has increased in many areas, resulting in longer smoke episodes with higher concentrations of fine particulate matter (PM

Smoke from burning biomass is an important source of fine particulate matter (PM2.5), but the health risks may not be fully captured by the Canadian Air Quality Health Index (AQHI). In May 2018, the province of British Columbia launched an evidence-based amendment (AQHI-Plus) to improve AQHI performance for wildfire smoke, but the AQHI-Plus was not developed or tested on data from the residential woodsmoke season. This study assesses how the AQHI and AQHI-Plus are associated with acute health outcomes during the cooler seasons of 2010-2017 in British Columbia, Canada. Monthly and daily patterns of temperature and PM2.5 concentrations were used to identify Local Health Areas (LHAs) that were impacted by residential woodsmoke. The effects of the AQHI and AQHI-Plus on five acute health outcomes (including non-accidental mortality, outpatient physician visits, and medical dispensations for cardiopulmonary conditions) were estimated using generalized linear mixed effect models with Poisson distributions adjusted for long- and short-term temperature trends. Values of the Akaike information criterion (AIC) were compared to evaluate whether the AQHI or AQHI-Plus was better fitted to each health outcome. Eleven LHAs were categorized as woodsmoke-impacted. In these LHAs, the AQHI and AQHI-Plus associations with acute health outcomes were sensitive to temperature adjustments. After temperature adjustments, the most consistent associations were observed for the two asthma-specific outcomes where the AQHI-Plus was better fitted than the AQHI. The improved performance of the AQHI-Plus for susceptible populations with asthma is consistent between communities impacted by residential woodsmoke and wildfire smoke. Implications: Canada's Air Quality Health Index (AQHI) is a three pollutant index used to communicate the short term health impact of degraded air quality. As fine particulate matter (PM2.5) is the lowest weighted pollutant in the AQHI, the index is poorly reflective of woodsmoke impacts. The present analysis found that an AQHI amendment developed for improved sensitivity to PM2.5 during wildfire seasons (AQHI-Plus) is also more predictive of acute asthma-related health outcomes in communities impacted by residential woodsmoke. The BC Ministry of Environment and Climate Change Strategy has piloted the AQHI-Plus year-round. Other jurisdictions should consider whether their air quality indices are reflective of the risks posed by woodsmoke.

Previous research has associated snowfall with risk of myocardial infarction (MI). Most studies have been conducted in regions with harsh winters; it remains unclear whether snowfall is associated with risk of MI in regions with milder or more varied climates. A case-crossover design was used to investigate the association between snowfall and death from MI in British Columbia, Canada. Deaths from MI among British Columbia residents between October 15 and March 31 from 2009 to 2017 were identified. The day of each death from MI was treated as the case day, and each case day was matched to control days drawn from the same day of the week during the same month. Daily snowfall amount was assigned to case and control days at the residential address, using weather stations within 15 km of the residence and 100 m in elevation. In total, 3,300 MI case days were matched to 10,441 control days. Compared with days that had no snowfall, odds of death from MI increased 34% (95% confidence interval: 0%, 80%) on days with heavy snowfall (≥5 cm). In stratified analysis of deaths from MI as a function of both maximum temperature and snowfall, risk was significantly increased on snowfall days when the temperature was warmer.

Climate change is an increasingly important public health issue, reflected in morbidity and mortality outcomes during extreme heat events. At the same time, the harms of social isolation with respect to a wide range of health outcomes are becoming better understood. Given that older adults are at higher risk during hot weather and at higher risk of social isolation, they are among those at highest risk for adverse impacts of extreme heat events. While specific strategies to reduce heat exposure have been described in the literature and promoted in public health practice, these may not be readily available to socially isolated older adults. As such, it is crucial to identify key approaches to address risk due to social isolation in the aging population, and to acknowledge their limitations and barriers. Interventions rooted in social connection, a concept widely applied in interventions for public health and social well-being, should be applied as a tool for adaptation to extreme heat events.RéSUMé: Le changement climatique est un problème de santé publique de plus en plus important, qui se reflète dans les résultats de la morbidité et de la mortalité lors des épisodes de chaleur extrême. Au même temps, les mals de l'isolement social en ce qui concerne un large éventail de résultats pour la santé sont de mieux en mieux compris. Étant donné que les personnes âgées sont plus à risque durant les temps chaud et à risque d'isolement social, elles font partie des personnes les plus exposées aux effets négatifs d'événements de chaleur extrême. Bien que des stratégies spécifiques pour réduire l'exposition à la chaleur aient été décrites dans la littérature et promues dans la pratique de la santé publique, elles peuvent ne pas être facilement accessibles aux personnes âgées socialement isolées. Comme tel, il est essentiel d'identifier les approches clés pour réduire les risques dus à l'isolement social de la population vieillissante et de reconnaître leurs limites et obstacles. Les interventions enracinées dans la connexion sociale, un concept largement appliqué dans les interventions pour la santé publique et le bien-être social, devraient être appliquées comme un outil d'adaptation aux événements de chaleur extreme.

In late June to early July 2021 a heatwave of unprecedented magnitude impacted the Pacific Northwest region, lands colonially named British Columbia (BC) and Alberta (AB) in Canada, and Washington (WA) and Oregon (OR) in the United States. Many locations broke all-time maximum daily temperature records by more than 5°C. The standing Canadian national temperature record was broken on three consecutive days, at multiple locations, with the highest temperature of 49.6°C recorded, 4.6°C higher than the previous Canadian record. Weather forecasts provided advanced notice of the severity of the event, while sub-seasonal forecasts showed substantially increased likelihood of atmospheric blocking and high temperatures with 10-day lead times, and some skill out to 18 days. The impacts of this event were catastrophic. Estimates indicate at least 900 attributable deaths occurred across BC, WA and OR, likely the deadliest weather event in Canadian1 history. The heat contributed to mass-mortalities of marine life, reduced crop and fruit yields, river flooding from rapid snow and glacier melt, and a rapid increase in wildfires—the latter contributing to devastating landslides in the months following.

Attributing individual deaths to extreme heat events (EHE) in Canada and elsewhere is important for understanding the risk factors, protective interventions, and burden of mortality associated with climate change. However, there is currently no single mechanism for identifying individual deaths due to EHE and different agencies have taken different approaches, including (1) vital statistics coding based on medical certificates of death, (2) probabilistic methods, and (3) enhanced surveillance. The 2018 EHE in Montréal provides an excellent case study to compare EHE deaths identified by these different approaches. There were 353 deaths recorded in the vital statistics data over an 8-day period, of which 102 were potentially attributed to the EHE by at least one approach and 251 were not attributed by any approach. Only nine of the 102 deaths were attributed to the EHE by all three approaches, 23 were attributed by two approaches, and 70 were attributed by only one approach. Given that there were approximately 50 excess deaths during the EHE, it remains unclear exactly which of the total 353 deaths should be attributed to the extreme temperatures. These results highlight the need for a more systematic and cooperative approach to EHE mortality in Canada, which will continue to increase as the climate changes.RéSUMé: L’attribution des décès individuels aux épisodes de chaleur accablante (ECA) au Canada et ailleurs est importante pour comprendre les facteurs de risque, les interventions de protection et le fardeau de la mortalité associés aux changements climatiques. Cependant, il n’existe actuellement aucun mécanisme unique pour identifier les décès individuels dus à l’ECA et différentes agences ont adopté différentes approches, notamment (1) le codage des statistiques de l’état civil basé sur les certificats médicaux de décès, (2) des méthodes probabilistes et (3) une surveillance renforcée. L’ECA 2018 à Montréal fournit une excellente étude de cas pour comparer les décès ECA identifiés par ces différentes approches. Il y a eu 353 décès enregistrés dans les données des statistiques de l’état civil sur une période de 8 jours, dont 102 ont été potentiellement attribués à l’ECA par au moins une approche et 251 n’ont été attribués par aucune approche. Seuls neuf des 102 décès ont été attribués à l’ECA par les trois approches, 23 ont été attribués par deux approches et 70 ont été attribués par une seule approche. Étant donné qu’il y a eu environ 50 décès supplémentaires pendant l’ECA, on ne sait pas exactement lequel des 353 décès au total doit être attribué aux températures extrêmes. Ces résultats soulignent la nécessité d’une approche plus systématique et coopérative de la mortalité ECA au Canada, qui continuera d’augmenter à mesure que le climat change.

Wildfire smoke exposure is associated with a range of acute health outcomes, which can be more severe in individuals with underlying health conditions. Currently, there is limited information on the susceptibility of healthcare facilities to smoke infiltration. As part of a larger study to address this gap, a rehabilitation facility in Vancouver, Canada was outfitted with one outdoor and seven indoor low-cost fine particulate matter (PM2.5) sensors in Air Quality Eggs (EGG) during the summer of 2020. Raw measurements were calibrated using temperature, relative humidity, and dew point derived from the EGG data. The infiltration coefficient was quantified using a distributed lag model. Indoor concentrations during the smoke episode were elevated throughout the building, though non-uniformly. After censoring indoor-only peaks, the average infiltration coefficient (range) during typical days was 0.32 (0.22–0.39), compared with 0.37 (0.31–0.47) during the smoke episode, a 19% increase on average. Indoor PM2.5 concentrations quickly reflected outdoor conditions during and after the smoke episode. It is unclear whether these results will be generalizable to other years due to COVID-related changes to building operations, but some of the safety protocols may offer valuable lessons for future wildfire seasons. For example, points of building entry and exit were reduced from eight to two during the pandemic, which likely helped to protect the building from wildfire smoke infiltration. Overall, these results demonstrate the utility of indoor low-cost sensors in understanding the impacts of extreme smoke events on facilities where highly susceptible individuals are present. Furthermore, they highlight the need to employ interventions that enhance indoor air quality in such facilities during smoke events.

British Columbia, Canada, was impacted by a record-setting heat dome in early summer 2021. Most households in greater Vancouver do not have air conditioning, and there was a 440% increase in community deaths during the event. Readily available data were analyzed to inform modifications to the public health response during subsequent events in summer 2021 and to guide further research.The 434 community deaths from 27 June through 02 July 2021 (heat dome deaths) were compared with all 1,367 community deaths that occurred in the same region from 19 June through 09 July of 2013-2020 (typical weather deaths). Conditional logistic regression was used to examine the effects of age, sex, neighborhood deprivation, and the surrounding environment. Data available from homes with and without air conditioning were also used to illustrate the indoor temperatures differences.A combined index of material and social deprivation was most predictive of heat dome risk, with an adjusted odds ratio of 2.88 [1.85, 4.49] for the most deprived category. Heat dome deaths also had lower greenness within 100 m than typical weather deaths. Indoor temperatures in one illustrative home without air conditioning ranged between 30°C and 40°C.Risk of death during the heat dome was associated with deprivation, lower neighborhood greenness, older age, and sex. High indoor temperatures likely played an important role. Public health response should focus on highly deprived neighborhoods with low air conditioning prevalence during extreme heat events. Promotion of urban greenspace must continue as the climate changes.

BACKGROUND AND AIM: A growing body of evidence indicates that exposure to air pollution affects cognitive performance; however, few studies have assessed this in the context of repeated measures wi...

BACKGROUND AND AIM: There is increasing evidence that air pollution exposure adversely impacts cognitive health. While wildfire smoke is a pollutant of growing concern, there is little evidence to ...

Wildfire smoke exposure is associated with a range of acute health outcomes, which can be more severe in individuals with underlying health conditions. Currently, there is limited information on the susceptibility of healthcare facilities to smoke infiltration. As part of a larger study to address this gap, a rehabilitation facility in Vancouver, Canada was outfitted with one outdoor and seven indoor low-cost fine particulate matter (PM2.5) sensors in Air Quality Eggs (EGG) during the summer of 2020. Raw measurements were calibrated using temperature, relative humidity, and dew point derived from the EGG data. The infiltration coefficient was quantified using a distributed lag model. Indoor concentrations during the smoke episode were elevated throughout the building, though non-uniformly. After censoring indoor-only peaks, the average infiltration coefficient (range) during typical days was 0.32 (0.22–0.39), compared with 0.37 (0.31–0.47) during the smoke episode, a 19% increase on average. Indoor PM2.5 concentrations quickly reflected outdoor conditions during and after the smoke episode. It is unclear whether these results will be generalizable to other years due to COVID-related changes to building operations, but some of the safety protocols may offer valuable lessons for future wildfire seasons. For example, points of building entry and exit were reduced from eight to two during the pandemic, which likely helped to protect the building from wildfire smoke infiltration. Overall, these results demonstrate the utility of indoor low-cost sensors in understanding the impacts of extreme smoke events on facilities where highly susceptible individuals are present. Furthermore, they highlight the need to employ interventions that enhance indoor air quality in such facilities during smoke events.

Wildland fires are diminishing air quality on a seasonal and regional basis, raising concerns about respiratory health risks to the public and occupational groups. This American Thoracic Society (ATS) workshop was convened in 2019 to meet the growing health threat of wildland fire smoke. The workshop brought together a multidisciplinary group of 19 experts, including wildland fire managers, public health officials, epidemiologists, toxicologists, and pediatric and adult pulmonologists. The workshop examined the following four major topics: 1) the science of wildland fire incidence and fire management, 2) the respiratory and cardiovascular health effects of wildland fire smoke exposure, 3) communication strategies to address these health risks, and 4) actions to address wildland fire health impacts. Through formal presentations followed by group discussion, workshop participants identified top priorities for fire management, research, communication, and public policy to address health risks of wildland fires. The workshop concluded that short-term exposure to wildland smoke causes acute respiratory health effects, especially among those with asthma and chronic obstructive pulmonary disease. Research is needed to understand long-term health effects of repeated smoke exposures across fire seasons for children, adults, and highly exposed occupational groups (especially firefighters). Other research priorities include fire data collection and modeling, toxicology of different fire fuel sources, and the efficacy of health protective measures to prevent respiratory effects of smoke exposure. The workshop committee recommends a unified federal response to the growing problem of wildland fires, including investment in fire behavior and smoke air quality modeling, research on the health impacts of smoke, and development of robust clinical and public health communication tools.

OBJECTIVE: Wildfire smoke is an important source of air pollution associated with a range of cardiopulmonary health conditions. The Air Quality Health Index (AQHI) is the most widely used tool in Canada to communicate with the public about air pollution, but it may not adequately reflect health risks from wildfire smoke. The objective of this study was to evaluate the ability of the AQHI and four alternate AQHI-Plus amendments to predict adverse population health effects from wildfire smoke. METHODS: The maximum 1-h values of the AQHI and the four amendments were calculated for each 48-h period of the wildfire seasons from 2010 to 2017 for 32 health units in British Columbia. Generalized Poisson models were used to estimate the association between these values and daily counts of five health outcomes: all-cause mortality; physician visits for all circulatory causes; visits for all respiratory causes, including asthma; asthma-specific visits; and dispensations of salbutamol sulfate (i.e., Ventolin®). Model fit was evaluated with the Akaike information criterion. RESULTS: The AQHI and the four amendments were all associated with all five health outcomes. The AQHI exhibited best fit to the all-cause mortality and circulatory physician visits during all wildfire seasons, while the 1-h PM(2.5)Only AQHI-Plus exhibited best fit to the asthma-related outcomes during all wildfire seasons. CONCLUSION: Individuals with common respiratory conditions such as asthma and chronic obstructive pulmonary disease are particularly susceptible to wildfire smoke. As such, the 1-h PM(2.5)Only AQHI-Plus amendment was recommended for communicating about potential health effects of air quality during wildfire seasons in BC. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.17269/s41997-019-00237-w) contains supplementary material, which is available to authorized users.

Background Indoor and outdoor fine particulate matter (PM2.5) are both leading risk factors for death and disease, but making indoor measurements is often infeasible for large study populations. Methods We developed models to predict indoor PM2.5 concentrations for pregnant women who were part of a randomized controlled trial of portable air cleaners in Ulaanbaatar, Mongolia. We used multiple linear regression (MLR) and random forest regression (RFR) to model indoor PM2.5 concentrations with 447 independent 7-day PM2.5 measurements and 87 potential predictor variables obtained from outdoor monitoring data, questionnaires, home assessments, and geographic data sets. We also developed blended models that combined the MLR and RFR approaches. All models were evaluated in a 10-fold cross-validation. Results The predictors in the MLR model were season, outdoor PM2.5 concentration, the number of air cleaners deployed, and the density of gers (traditional felt-lined yurts) surrounding the apartments. MLR and RFR had similar performance in cross-validation (R2 = 50.2%, R2 = 48.9% respectively). The blended MLR model that included RFR predictions had the best performance (cross validation R2 = 81.5%). Intervention status alone explained only 6.0% of the variation in indoor PM2.5 concentrations. Conclusions We predicted a moderate amount of variation in indoor PM2.5 concentrations using easily obtained predictor variables and the models explained substantially more variation than intervention status alone. While RFR shows promise for modelling indoor concentrations, our results highlight the importance of out-of-sample validation when evaluating model performance. We also demonstrate the improved performance of blended MLR/RFR models in predicting indoor air pollution.

Objectives To 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. Methods Using 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. Results Restrictive criteria (age

Supplemental Digital Content is available in the text., Background: Ambulance data provide a useful source of population-based and spatiotemporally resolved information for assessing health impacts of air pollution in nonhospital settings. We used the clinical records of paramedics to quantify associations between particulate matter (PM2.5) and diabetic, cardiovascular, and respiratory conditions commonly managed by those responding to calls for emergency ambulance services. Methods: We evaluated 394,217 paramedic assessments from three states in Southeastern Australia (population 13.2 million) and daily PM2.5 concentrations modeled at 5 km resolution from 2009 to 2014. We used a time-stratified, case-crossover analysis adjusted for daily meteorology to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for each clinical outcome per 10 µg/m3 increase in daily PM2.5 at lags from 0 to 2 days. Results: Increased PM2.5 was associated with increased odds of paramedic assessments of hypoglycemia (OR = 1.07; 95% CI = 1.02, 1.12, lag 0), arrhythmia (OR = 1.05; 95% CI = 1.02, 1.09, lag 0), heart failure (OR = 1.07; 95% CI = 1.02, 1.12, lag 1), faint (OR = 1.09; 95% CI = 1.04–1.13, lag 0), asthma (OR = 1.06; 95% CI = 1.01, 1.11, lag 1), chronic obstructive pulmonary disease (OR = 1.07; 95% CI = 1.01, 1.13, lag 1), and croup (OR = 1.09; 95% CI = 1.02, 1.17). We did not identify associations with cerebrovascular outcomes. Conclusions: Ambulance data enable the evaluation of important clinical syndromes that are often initially managed in nonhospital settings. Daily PM2.5 was associated with hypoglycemia, faint, and croup in addition to the respiratory and cardiovascular outcomes that are better established.

Residential wood burning is a major source of fine particulate matter (PMMobile monitoring was conducted with a nephelometer and multi-wavelength aethalometer, capable of identifying woodsmoke PMFixed site measurements of BFollowing the successful implementation of the mobile CANAW method, training materials were created and tested with lay volunteers along with an online mapping application. Volunteers were able to effectively operate the equipment, collect valuable data on woodsmoke concentrations, and map spatial patterns across their communities using the application. The CANAW method is a valuable option for advancing cost-effective data collection for residential woodsmoke in otherwise unmonitored communities, and to add spatial context to existing monitoring networks.

As we enter the wildfire season in the northern hemisphere, the potential for a dangerous interaction between SARS-CoV-2 and smoke pollution should be recognized and acknowledged. This is challenging because the public health threat of COVID-19 is immediate and clear, whereas the public health threat of wildfire smoke seems distant and uncertain in comparison. However, we must start preparing now to effectively manage the combination of public health threats that we may face in the months ahead. (Am J Public Health. Published online ahead of print June 18, 2020: e1-e3. doi:10.2105/AJPH.2020.305744).

Background: Exposure to fine particulate matter (PM2.5) during wildfire seasons has been associated with adverse health outcomes. Previous studies have focused on daily exposure, but PM2.5 levels in smoke events can vary considerably within 1 d. Objectives: We aimed to assess the immediate and lagged relationship between sub-daily exposure to PM2.5 and acute health outcomes during wildfire seasons in British Columbia. Methods: We used a time-stratified case-crossover study design to evaluate the association between modeled hourly PM2.5 and ambulance dispatches during wildfire seasons from 2010 to 2015. Distributed lag nonlinear models were used to estimate the lag-specific and cumulative odds ratios (ORs) at lags from 1 to 48 h. We examined the relationship for all dispatches and dispatches related to respiratory, circulatory, and diabetic conditions, identified by codes for ambulance dispatch (AD), paramedic assessment (PA) or hospital diagnosis (HD). Results: Increased respiratory health outcomes were observed within 1 h of exposure to a 10-μg/m3 increase in PM2.5. The 48-h cumulative OR [95% confidence interval (CI)] was 1.038 (1.009, 1.067) for the AD code Breathing Problems and 1.098 (1.013, 1.189) for PA code Asthma/COPD. The point estimates were elevated within 1 h for the PA code for Myocardial Infarction and HD codes for Ischemic Heart Disease, which had 24-h cumulative ORs of 1.104 (0.915, 1.331) and 1.069 (0.983, 1.162), respectively. The odds of Diabetic AD and PA codes increased over time to a cumulative 24-h OR of 1.075 (1.001, 1.153) and 1.104 (1.015, 1.202) respectively. Conclusions: We found increased PM2.5 during wildfire seasons was associated with some respiratory and cardiovascular outcomes within 1 h following exposure, and its association with diabetic outcomes increased over time. Cumulative effects were consistent with those reported elsewhere in the literature. These results warrant further investigation and may have implications for the appropriate time scale of public health actions. https://doi.org/10.1289/EHP5792

Smoke from wildfires contains many air pollutants of concern and epidemiological studies have identified associations between exposure to wildfire smoke PM

Forest fire smoke is a growing public health concern as more intense and frequent fires are expected under climate change. Remote sensing is a promising tool for exposure assessment, but its utility for health studies is limited because most products measure pollutants in the total column of the atmosphere, and not the surface concentrations most relevant to population health. Information about the vertical distribution of smoke is vital for addressing this limitation. The CALIPSO satellite can provide such information but it cannot cover all smoke events due to its narrow ground track. In this study, we developed a random forests model to predict the minimum height of the smoke layer observed by CALIPSO at high temporal and spatial resolution, using information about fire activity in the vicinity, geographic location, and meteorological conditions. These pieces of information are typically available in near-real-time, ensuring that the resulting model can be easily operationalized. A total of 15,617 CALIPSO data blocks were identified as impacted by smoke within the province of British Columbia, Canada from 2006 to 2015, and 52.1% had smoke within the boundary layer, where the population might be exposed. The final model explained 82.1% of the variance in the observations with a root mean squared error of 560 m. The most important variables in the model were wind patterns, the month of smoke observation, and fire intensity within 500 km. Predictions from this model can be 1) directly applied to smoke detection from the existing remote sensing products to provide another dimension of information; 2) incorporated into statistical smoke models with inputs from remote sensing products; or 3) used to inform estimates of vertical dispersion in deterministic smoke models. These potential applications are expected to improve the assessment of ground-level population exposure to forest fire smoke.

Various aspects of land use regression (LUR) models for volatile organic compounds (VOCs) were systematically reviewed. Sixteen studies were identified published between 2002 and 2017. Of these, six were conducted in Canada, five in the USA, two in Spain, and one each in Germany, Italy, and Iran. They were developed for 14 different individual VOCs or groupings: benzene; toluene; ethylbenzene; m -xylene; p -xylene; ( m / p )-xylene; o -xylene; total BTEX; 1,3-butadiene; formaldehyde; n -hexane; total hydro carbons; styrene; and acrolein. The models were based on measurements ranging from 22 sites in El Paso (USA) to 179 sites in Tehran (Iran). Only four studies in Rome (Italy), Sabadell (Spain), Tehran, and Windsor (Canada) met the Cocheo's criterion of having at least one passive sampler per 3.4 km 2 of study area. The range of R 2 values across all models was from 0.26 for 1,3-butadiene in Dallas (USA) to 0.93 for benzene in El Paso. The average R 2 values among two or more studies of the same VOCs were as follows: benzene (0.70); toluene (0.60); ethylbenzene (0.66); ( m / p )-xylene (0.65); o -xylene (0.61); total BTEX (0.66); 1,3-butadiene (0.46); and formaldehyde (0.56). The common spatial predictors of studied VOC concentrations were dominated by traffic-related variables, but they also included proximity to ports in the USA, number of chimneys in Canada, altitude in Spain, northern latitudes in Italy, and proximity to sewage treatment plants and to gas filling stores in Iran. For the traffic-related variables, the review suggests that large buffers, up to 5,000 m, should be considered in large cities. Although most studies reported logical directions of association for predictors, some reported inconsistent results. Some studies included log-transformed predictors while others divided one variable by another. Only six studies provided the p-values of predictors. Future work may incorporate chemistry-transport models, satellite observations, meteorological variables, particularly temperature, consider specific sources of aromatic vs aliphatic compounds, or may develop hybrid models. Currently, only one national model has been developed for Canada, and there are no global LUR models for VOCs. Overall, studies from outside North America and Europe are critically needed to describe the wide range of exposures experienced by different populations.

Background Natural spaces can provide psychological benefits to individuals, but population-level epidemiologic studies have produced conflicting results. Refining current exposure-assessment methods is necessary to advance our understanding of population health and to guide the design of health-promoting urban forms. Objectives The aim of this study was to develop a comprehensive Natural Space Index that robustly models potential exposure based on the presence, form, accessibility, and quality of multiple forms of greenspace (e.g., parks and street trees) and bluespace (e.g., oceans and lakes). Material and methods The index was developed for greater Vancouver, Canada. Greenness presence was derived from remote sensing (NDVI/EVI); forms were extracted from municipal and private databases; and accessibility was based on restrictions such as private ownership. Quality appraisals were conducted for 200 randomly sampled parks using the Public Open Space Desktop Appraisal Tool (POSDAT). Integrating these measures in GIS, exposure was assessed for 60,242 postal codes using 100- to 1,600-m buffers based on hypothesized pathways to mental health. A single index was then derived using principal component analysis (PCA). Results Comparing NDVI with alternate approaches for assessing natural space resulted in widely divergent results, with quintile rankings shifting for 22–88% of postal codes, depending on the measure. Overall park quality was fairly low (mean of 15 on a scale of 0–45), with no significant difference seen by neighborhood-level household income. The final PCA identified three main sets of variables, with the first two components explaining 68% of the total variance. The first component was dominated by the percentages of public and private greenspace and bluespace and public greenspace within 250 m, while the second component was driven by lack of access to bluespace within 1 km. Conclusions Many current approaches to modeling natural space may misclassify exposures and have limited specificity. The Natural Space Index represents a novel approach at a regional scale with application to urban planning and policy-making.

Background Harmful algal blooms produce paralytic shellfish toxins that accumulate in the tissues of filter feeding shellfish. Ingestion of these toxic shellfish can cause a serious and potentially fatal condition known as paralytic shellfish poisoning (PSP). The coast of British Columbia is routinely monitored for shellfish toxicity, and this study uses data from the monitoring program to identify spatiotemporal patterns in shellfish toxicity events and their relationships with environmental variables. Methods The dinoflagellate genus Alexandrium produces the most potent paralytic shellfish toxin, saxitoxin (STX). Data on all STX measurements were obtained from 49 different shellfish monitoring sites along the coast of British Columbia for 2002–2012, and monthly toxicity events were identified. We performed hierarchical cluster analysis to group sites that had events in similar areas with similar timing. Machine learning techniques were used to model the complex relationships between toxicity events and environmental variables in each group. Results The Strait of Georgia and the west coast of Vancouver Island had unique toxicity regimes. Out of the seven environmental variables used, toxicity in each cluster could be described by multivariable models including monthly sea surface temperature, air temperature, sea surface salinity, freshwater discharge, upwelling, and photosynthetically active radiation. The sea surface salinity and freshwater discharge variables produced the strongest univariate models for both geographic areas. Conclusions Applying these methods in coastal regions could allow for the prediction of shellfish toxicity events by environmental conditions. This has the potential to optimize biotoxin monitoring, improve public health surveillance, and engage the shellfish industry in helping to reduce the risk of PSP.

Background Mobile air temperature monitoring is a promising method to better understand temperature distributions at fine spatial resolutions across urban areas. The study objectives were to collect microscale measurements for evaluate different data sources used to assess heat exposure in greater Vancouver, Canada. Methods Mobile air temperature monitoring was conducted on foot at least twice for each of 20 routes. First, the mobile data were compared with 1-minute measurements from the nearest fixed site. Second, the mobile data from runs corresponding with Landsat overpass days were compared with satellite-derived land surface temperature (LST). Third, the mobile data were compared with estimates from a previously developed heat map for the region. Results Mobile measurements were typically higher and more variable than simultaneous fixed site measurements. Correlations between mobile measurements and LST were weak and highly variable (r 2 = 0.04–0.38). The z-score differentials between mobile measurements and the heat map suggested that spatial variability in temperatures is captured by the heat map. Conclusion Microscale measurements confirm that fixed sites do not characterize the variability in thermal conditions within nearby streetscapes. Microscale monitoring of air temperatures is a valuable tool for temporally and spatially evaluating other high resolution temperature data within small areas.

There is limited evidence for short-term association between mortality and ambient air pollution in the Middle East and no study has evaluated exposure windows of about a month prior to death. We investigated all-cause non-accidental daily mortality and its association with fine particulate matter (PM; 2.5; ), nitrogen dioxide (NO; 2; ), and the Air Quality Index (AQI) from March 2011 through March 2014 in the megacity of Tehran, Iran. Generalized additive quasi-Poisson models were used within a distributed lag linear modeling framework to estimate the cumulative effects of PM; 2.5; , NO; 2; , and the AQI up to a lag of 45 days. We further conducted multi-pollutant models and also stratified the analyses by sex, age group, and season. The relative risk (95% confidence interval (CI)) for all seasons, both sexes and all ages at lag 0 for PM; 2.5; , NO; 2; , and AQI were 1.004 (1.001, 1.007), 1.003 (0.999, 1.007), and 1.004 (1.001, 1.007), respectively, per inter-quartile range (IQR) increment (18.8 μg/m; 3; for PM; 2.5; , 12.6 ppb for NO; 2; , and 31.5 for AQI). In multi-pollutant models, the PM; 2.5; associations were almost independent from NO; 2; . However, the RRs for NO; 2; were slightly attenuated after adjustment for PM; 2.5; but they were still largely independent from PM; 2.5; . The cumulative relative risks (95% CI) per IQR increment reached maximum during the cooler months, including: 1.13 (1.06, 1.20) for PM; 2.5; at lag 0-31 (for females, all ages); 1.17 (1.10, 1.25) for NO; 2; at lag 0-45 (for males, all ages); and 1.13 (1.07, 1.20) for the AQI at lag 0-30 (for females, all ages). Generally, the RRs were slightly larger for NO; 2; than PM; 2.5; and AQI. We found somewhat larger RRs in females, age group >65 years of age, and in cooler months. In summary, positive associations were found in most models. This is the first study to report short-term associations between all-cause non-accidental mortality and ambient PM; 2.5; and NO; 2; in Iran.

This paper outlines a latent process model for forecasting multiple health outcomes arising from a common environmental exposure. Traditionally, surveillance models in environmental health do not link health outcome measures, such as morbidity or mortality counts, to measures of exposure, such as air pollution. Moreover, different measures of health outcomes are treated as independent, while it is known that they are correlated with one another over time as they arise in part from a common underlying exposure. We propose modelling an environmental exposure as a latent process, and we describe the implementation of such a model within a hierarchical Bayesian framework and its efficient computation using integrated nested Laplace approximations. Through a simulation study, we compare distinct univariate models for each health outcome with a bivariate approach. The bivariate model outperforms the univariate models in bias and coverage of parameter estimation, in forecast accuracy and in computational efficiency. The methods are illustrated with a case study using healthcare utilization and air pollution data from British Columbia, Canada, 2003-2011, where seasonal wildfires produce high levels of air pollution, significantly impacting population health. Copyright © 2016 John Wiley & Sons, Ltd.