A series of wildfires in northern Quebec, early July 2002, and in southern Quebec, late May 2010, resulted in severe air pollution downwind. Downwind exposures were investigated to estimate the impact on outdoor and indoor environments. The plumes derived from the wildfires resulted in an increase of over 10 ppbv ozone (O3) concentrations in both major cities and rural areas, while O3 enhancement was not observed at locations adjacent to wildfire burning areas. Temporal trend in PM2.5 concentration showed a peak of 105.5 μg/m3 on July 7, 2002, while on May 31, 2010 the peak was 151.1 μg/m3 in Boston downwind. PM2.5 speciation showed similar trends between the episodes, along with spikes in the PM2.5/PM10 ratio, and in the concentrations of Black Carbon, ΔC (i.e., UV absorbing compounds minus Black Carbon), Organic Carbon (OC), potassium, and chlorine. OC was the most dominant constituent of the PM2.5 mass in the wildfires. The dominant specific carbon fractions include OC fraction 3, pyrolysis carbon, and EC fraction 1, likely due to pyrolysis of structural components of wood. Indoor PM2.5 peaks at two houses corresponded well with the ambient PM2.5 peak, along with the elemental composition, which could indicate an impact of wildfires on indoor air pollution exposure.

The United States (US) Environmental Protection Agency (EPA)\'s SPECIATE database contains speciated particulate matter (PM) and volatile organic compound (VOC) emissions profiles. Emissions profiles from anthropogenic combustion, industry, wildfires, and agricultural sources among others are key inputs for creating chemically-resolved emissions inventories for air quality modeling. While the database and its use for air quality modeling are routinely updated and evaluated, this work sets out to systematically prioritize future improvements and communicate speciation data needs to the research community. We first identify the most prominent profiles (PM and VOC) used in the EPA\'s 2014 emissions modeling platform based on PM mass and VOC mass and reactivity. It is important to note that the on-road profiles were excluded from this analysis since speciation for these profiles is computed internally in the MOVES model. We then investigate these profiles further for quality and to determine whether they were being appropriately matched to source types while also considering regional variability of speciated pollutants. We then applied a quantitative needs assessment ranking system which rates the profile based on age, appropriateness (i.e. is the profile being used appropriately), prevalence in the EPA modeling platform and the quality of the reference. Our analysis shows that the highest ranked profiles (e.g. profile assignments with the highest priority for updates) include PM2.5 profiles for fires (prescribed, agricultural and wild) and VOC profiles for crude oil storage tanks and residential wood combustion of pine wood. Top ranked profiles may indicate either that there are problems with the currently available source testing or that current mappings of profiles to source categories within EPA\'s modeling platform need improvement. Through this process, we have identified 29 emissions sourcecategories that would benefit from updated mapping. Many of these mapping mismatches are due to lack of emissions testing for appropriate source categories. In addition, we conclude that new source emissions testing would be especially beneficial for residential wood combustion, nonroad gasoline exhaust and nonroad diesel equipment.

Research efforts to better characterize the differential toxicity of PM2.5 (particles with aerodynamic diameters less than or equal to 2.5 μm) speciation are often hindered by the sparse or non-existent coverage of ground monitors. The Multi-angle Imaging SpectroRadiometer (MISR) aboard NASA\'s Terra satellite is one of few satellite aerosol sensors providing information of aerosol shape, size and extinction globally for a long and continuous period that can be used to estimate PM2.5 speciation concentrations since year 2000. Currently, MISR only provides a 17.6 km product for its entire mission with global coverage every 9 days, a bit too coarse for air pollution health effects research and to capture local spatial variability of PM2.5 speciation. In this study, generalized additive models (GAMs) were developed using MISR prototype 4.4 km-resolution aerosol data with meteorological variables and geographical indicators, to predict ground-level concentrations of PM2.5 sulfate, nitrate, organic carbon (OC) and elemental carbon (EC) in Southern California between 2001 and 2015 at the daily level. The GAMs are able to explain 66%, 62%, 55% and 58% of the daily variability in PM2.5 sulfate, nitrate, OC and EC concentrations during the whole study period, respectively. Predicted concentrations capture large regional patterns as well as fine gradients of the four PM2.5 species in urban areas of Los Angeles and other counties, as well as in the Central Valley. This study is the first attempt to use MISR prototype 4.4 km-resolution AOD (aerosol optical depth) components data to predict PM2.5 sulfate, nitrate, OC and EC concentrations at the sub-regional scale. In spite of its low temporal sampling frequency, our analysis suggests that the MISR 4.4 km fractional AODs provide a promising way to capture the spatial hotspots and long-term temporal trends of PM2.5 speciation, understand the effectiveness of air quality controls, and allow our estimated PM2.5 speciation data to be linked with common spatial units such as census tract or zip code in epidemiological studies. This modeling strategy needs to be validated in other regions when more MISR 4.4 km data becoming available in the future.