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Worsening wildfire seasons in recent years are reversing decadal progress on the reduction of harmful air pollutants in the US, particularly in Western states. Measurements of the contributions of wildfire smoke to ambient air pollutants, such as fine particulate matter (PM2.5), at fine resolution scales would be valuable to public health research on climate vulnerable populations and compound climate risks. We estimate the influence of wildfire smoke emissions on daily PM2.5 at fine-resolution, 3 km, for California 2011–2020, using a geostatistical modeled ambient PM2.5 estimate and wildfire smoke plume data from NOAA Hazard Mapping System. Additionally, we compare this product with the US Environmental Protection Agency (EPA) daily and annual standards for PM2.5 exposure. Our results show wildfires significantly influence PM2.5 in California and nearly all exceedances of the daily US EPA PM2.5 standard were influenced by wildfire smoke, while annual exceedances were increasingly attributed to wildfire smoke influence in recent years. This wildfire-influenced PM2.5 product can be applied to public health research to better understand source-specific air pollution impacts and assess the combination of multiple climate hazard risks. [ABSTRACT FROM AUTHOR]

An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NOx) and their spatial distribution can enable policymakers to focus their control efforts. In this study we used low-cost sensors (LCSs) to increase the spatial resolution of an existing NO2 monitoring network in addition to VOC sampling to better understand summer ozone formation in Maricopa County, Arizona, and observed that afternoon O3 values at the downwind sites were significantly correlated, ~0.27, to the morning NO2 × rate values at the urban sites. Additionally, we looked at the impact of wildfire smoke on ozone exceedances and compared non-smoke days to smoke days. The average O3 on smoke days was approximately 20% higher than on non-smoke days, however, the average NO2 concentration multiplied by estimated photolysis rate (NO2 × rate) values were only 2% higher on smoke days. Finally, we evaluated the ozone sensitivity of the region by calculating HCHO/NO2 ratios using three different datasets: ground, satellite, and model. Although the satellite dataset produced higher HCHO/NO2 ratios than the other datasets, when the proper regime thresholds are applied the three datasets consistently show transition and VOC-limited O3 production regimes over the Phoenix metro area. This suggests a need to implement more VOC emission controls in order to reach O3 attainment in the county. [ABSTRACT FROM AUTHOR]

Wildfire activity is increasing around the world, concurrent with climate change, and mitigation strategies for protecting vulnerable populations are desperately needed. Because inhaled particles are deleterious to respiratory health, particularly among older adults with co-morbidities, we engaged maintenance personnel working in long term care facilities located in the Western US. Our objective was to identify opportunities to build resilience during wildfire smoke events. We implemented a virtual workshop that addressed wildfire smoke health impacts as well as strategies to assess and maintain indoor air quality. A total of 24 maintenance personnel attended the virtual workshop and 14 participated in a quantitative survey. Workshop attendees found value in the material and there was enthusiasm for educational resources and enhancing indoor air quality. Four months later, four maintenance staff participated in a follow-up interview. Our qualitative assessment revealed the following themes: awareness and prioritization, application of knowledge, barriers, and educational resources. Access to real-time actionable air quality data was a consistent feature across these themes. Maintenance personnel could play a key role in a facility's ability to prepare for and respond to wildfire smoke events, and this study highlights potential challenges and opportunities to involving them in resilience building strategies. [ABSTRACT FROM AUTHOR]

Sub-micron particles are ubiquitous in the indoor environment, especially during wildfire smoke episodes, and have a higher impact on human health than larger particles. Conventional fibrous air filters installed in heating, ventilation, and air conditioning (HVAC) systems play an important role in controlling indoor air quality by removing various air pollutants, including particulate matter (PM). However, it is evident that the removal efficiency of wildfire smoke PM and its effect on filter performance is significantly under-studied. This study delves into the size-specific removal efficiency of pine needle smoke, a representative of wildfire smoke and emissions. We test an array of filter media with minimum efficiency reporting values (MERV) spanning 11–15. Both size-resolved particle number concentrations and mass concentrations were measured using an Optical Particle Sizer (OPS, TSI, Inc.) and a Scanning Mobility Particle Sizer (SMPS, TSI, Inc.). Furthermore, we characterize the filter media morphology and smoke particles deposited on filter fibers using Scanning Electron Microscopy (SEM) to gain insights into the interaction dynamics of these particles. Our findings add to the comprehension of the relationship between MERV designations and smoke removal efficiency. Such insight can inform standards and guidelines and equip decision-makers with the knowledge needed to initiate measures for mitigating the impact of air pollution, specifically on the indoor environment. [ABSTRACT FROM AUTHOR]

Worsening wildfire seasons in recent years are reversing decadal progress on the reduction of harmful air pollutants in the US, particularly in Western states. Measurements of the contributions of wildfire smoke to ambient air pollutants, such as fine particulate matter (PM2.5), at fine resolution scales would be valuable to public health research on climate vulnerable populations and compound climate risks. We estimate the influence of wildfire smoke emissions on daily PM2.5 at fine-resolution, 3 km, for California 2011–2020, using a geostatistical modeled ambient PM2.5 estimate and wildfire smoke plume data from NOAA Hazard Mapping System. Additionally, we compare this product with the US Environmental Protection Agency (EPA) daily and annual standards for PM2.5 exposure. Our results show wildfires significantly influence PM2.5 in California and nearly all exceedances of the daily US EPA PM2.5 standard were influenced by wildfire smoke, while annual exceedances were increasingly attributed to wildfire smoke influence in recent years. This wildfire-influenced PM2.5 product can be applied to public health research to better understand source-specific air pollution impacts and assess the combination of multiple climate hazard risks.

An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NOx) and their spatial distribution can enable policymakers to focus their control efforts. In this study we used low-cost sensors (LCSs) to increase the spatial resolution of an existing NO2 monitoring network in addition to VOC sampling to better understand summer ozone formation in Maricopa County, Arizona, and observed that afternoon O3 values at the downwind sites were significantly correlated, ~0.27, to the morning NO2 × rate values at the urban sites. Additionally, we looked at the impact of wildfire smoke on ozone exceedances and compared non-smoke days to smoke days. The average O3 on smoke days was approximately 20% higher than on non-smoke days, however, the average NO2 concentration multiplied by estimated photolysis rate (NO2 × rate) values were only 2% higher on smoke days. Finally, we evaluated the ozone sensitivity of the region by calculating HCHO/NO2 ratios using three different datasets: ground, satellite, and model. Although the satellite dataset produced higher HCHO/NO2 ratios than the other datasets, when the proper regime thresholds are applied the three datasets consistently show transition and VOC-limited O3 production regimes over the Phoenix metro area. This suggests a need to implement more VOC emission controls in order to reach O3 attainment in the county.

Wildfire activity is increasing around the world, concurrent with climate change, and mitigation strategies for protecting vulnerable populations are desperately needed. Because inhaled particles are deleterious to respiratory health, particularly among older adults with co-morbidities, we engaged maintenance personnel working in long term care facilities located in the Western US. Our objective was to identify opportunities to build resilience during wildfire smoke events. We implemented a virtual workshop that addressed wildfire smoke health impacts as well as strategies to assess and maintain indoor air quality. A total of 24 maintenance personnel attended the virtual workshop and 14 participated in a quantitative survey. Workshop attendees found value in the material and there was enthusiasm for educational resources and enhancing indoor air quality. Four months later, four maintenance staff participated in a follow-up interview. Our qualitative assessment revealed the following themes: awareness and prioritization, application of knowledge, barriers, and educational resources. Access to real-time actionable air quality data was a consistent feature across these themes. Maintenance personnel could play a key role in a facility’s ability to prepare for and respond to wildfire smoke events, and this study highlights potential challenges and opportunities to involving them in resilience building strategies.

Sub-micron particles are ubiquitous in the indoor environment, especially during wildfire smoke episodes, and have a higher impact on human health than larger particles. Conventional fibrous air filters installed in heating, ventilation, and air conditioning (HVAC) systems play an important role in controlling indoor air quality by removing various air pollutants, including particulate matter (PM). However, it is evident that the removal efficiency of wildfire smoke PM and its effect on filter performance is significantly under-studied. This study delves into the size-specific removal efficiency of pine needle smoke, a representative of wildfire smoke and emissions. We test an array of filter media with minimum efficiency reporting values (MERV) spanning 11–15. Both size-resolved particle number concentrations and mass concentrations were measured using an Optical Particle Sizer (OPS, TSI, Inc.) and a Scanning Mobility Particle Sizer (SMPS, TSI, Inc.). Furthermore, we characterize the filter media morphology and smoke particles deposited on filter fibers using Scanning Electron Microscopy (SEM) to gain insights into the interaction dynamics of these particles. Our findings add to the comprehension of the relationship between MERV designations and smoke removal efficiency. Such insight can inform standards and guidelines and equip decision-makers with the knowledge needed to initiate measures for mitigating the impact of air pollution, specifically on the indoor environment.

To understand the health effects of wildfire smoke, it is important to accurately assess smoke exposure over space and time. Particulate matter (PM) is a predominant pollutant in wildfire smoke. In this study, we develop land-use regression (LUR) models to investigate the impact that a cluster of wildfires in the northwest USA had on the level of PM in southern Alberta (Canada), in the summer of 2015. Univariate aerosol optical depth (AOD) and multivariate AOD-LUR models were used to estimate the level of PM2.5 in urban and rural areas. For epidemiological studies, it is also important to distinguish between wildfire-related PM2.5 and PM2.5 originating from other sources. We therefore subdivided the study period into three sub-periods: (1) Pre-fire, (2) during-fire, and (3) post-fire. We then developed separate models for each sub-period. With this approach, we were able to identify different predictors significantly associated with smoke-related PM2.5 verses PM2.5 of different origin. Leave-one-out cross-validation (LOOCV) was used to evaluate the models' performance. Our results indicate that model predictors and model performance are highly related to the level of PM2.5, and the pollution source. The predictive ability of both uni- and multi-variate models were higher in the during-fire period than in the pre- and post-fire periods. [ABSTRACT FROM AUTHOR]

FireWork is an on-line, one-way coupled meteorology-chemistry model based on near-real-time wildfire emissions. It was developed by Environment and Climate Change Canada to deliver operational real-time forecasts of biomass-burning pollutants, in particular fine particulate matter (PM2.5), over North America. Such forecasts provide guidance for early air quality alerts that could reduce air pollution exposure and protect human health. A multi-year (2013-2016) analysis of FireWork forecasts over a five-month period (May to September) was conducted. This work used an archive of FireWork outputs to quantify wildfire contributions to total PM2.5 surface concentrations across North America. Different concentration thresholds (0.2 to 28 μg/m³) and averaging periods (24 h to five months) were considered. Analysis suggested that, on average over the fire season, 76% of Canadians and 69% of Americans were affected by seasonal wildfire-related PM2.5 concentrations above 0.2 μg/m³. These effects were particularly pronounced in July and August. Futhermore, the analysis showed that fire emissions contributed more than 1 μg/m³ of daily average PM2.5 concentrations on more than 30% of days in the western USA and northwestern Canada during the fire season. [ABSTRACT FROM AUTHOR]

To understand the health effects of wildfire smoke, it is important to accurately assess smoke exposure over space and time. Particulate matter (PM) is a predominant pollutant in wildfire smoke. In this study, we develop land-use regression (LUR) models to investigate the impact that a cluster of wildfires in the northwest USA had on the level of PM in southern Alberta (Canada), in the summer of 2015. Univariate aerosol optical depth (AOD) and multivariate AOD-LUR models were used to estimate the level of PM2.5 in urban and rural areas. For epidemiological studies, it is also important to distinguish between wildfire-related PM2.5 and PM2.5 originating from other sources. We therefore subdivided the study period into three sub-periods: (1) Pre-fire, (2) during-fire, and (3) post-fire. We then developed separate models for each sub-period. With this approach, we were able to identify different predictors significantly associated with smoke-related PM2.5 verses PM2.5 of different origin. Leave-one-out cross-validation (LOOCV) was used to evaluate the models’ performance. Our results indicate that model predictors and model performance are highly related to the level of PM2.5, and the pollution source. The predictive ability of both uni- and multi-variate models were higher in the during-fire period than in the pre- and post-fire periods.

FireWork is an on-line, one-way coupled meteorology–chemistry model based on near-real-time wildfire emissions. It was developed by Environment and Climate Change Canada to deliver operational real-time forecasts of biomass-burning pollutants, in particular fine particulate matter (PM2.5), over North America. Such forecasts provide guidance for early air quality alerts that could reduce air pollution exposure and protect human health. A multi-year (2013–2016) analysis of FireWork forecasts over a five-month period (May to September) was conducted. This work used an archive of FireWork outputs to quantify wildfire contributions to total PM2.5 surface concentrations across North America. Different concentration thresholds (0.2 to 28 µg/m3) and averaging periods (24 h to five months) were considered. Analysis suggested that, on average over the fire season, 76% of Canadians and 69% of Americans were affected by seasonal wildfire-related PM2.5 concentrations above 0.2 µg/m3. These effects were particularly pronounced in July and August. Futhermore, the analysis showed that fire emissions contributed more than 1 µg/m3 of daily average PM2.5 concentrations on more than 30% of days in the western USA and northwestern Canada during the fire season.