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Wildfire impacts on air quality and climate are expected to be exacerbated by climate change with the most pronounced impacts in the boreal biome. Despite the large geographic coverage, there is limited information on boreal forest wildfire emissions, particularly for organic compounds, which are critical inputs for air quality model predictions of downwind impacts. In this study, airborne measurements of 193 compounds from 15 instruments, including 173 non-methane organics compounds (NMOG), were used to provide the most detailed characterization, to date, of boreal forest wildfire emissions. Highly speciated measurements showed a large diversity of chemical classes highlighting the complexity of emissions. Using measurements of the total NMOG carbon (NMOG T), the Σ NMOG was found to be 50 % ± 3 % to 53 % ± 3 % of NMOG T , of which, the intermediate- and semi-volatile organic compounds (I/SVOCs) were estimated to account for 7 % to 10 %. These estimates of I/SVOC emission factors expand the volatility range of NMOG typically reported. Despite extensive speciation, a substantial portion of NMOG T remained unidentified (47 % ± 15 % to 50 % ± 15 %), with expected contributions from more highly-functionalized VOCs and I/SVOCs. The emission factors derived in this study improve wildfire chemical speciation profiles and are especially relevant for air quality modelling of boreal forest wildfires. These aircraft-derived emission estimates were further linked with those derived from satellite observations demonstrating their combined value in assessing variability in modelled emissions. These results contribute to the verification and improvement of models that are essential for reliable predictions of near-source and downwind pollution resulting from boreal forest wildfires. [ABSTRACT FROM AUTHOR]

We investigate the potential for aircraft-based top-down emission rate retrieval over- and under-estimation using a regional chemical transport model, the Global Environmental Multiscale-Modeling Air-Quality and CHemistry (GEM-MACH). In our investigations we consider the application of the mass-balance approach in the Top-down Emission Rate Retrieval Algorithm (TERRA). Aircraft-based mass-balance retrieval methodologies such as TERRA require relatively constant meteorological conditions and source emission rates to reliably estimate emission rates from aircraft observations. Avoiding cases where meteorology and emission rates change significantly is one means of reducing emissions retrieval uncertainty, and quantitative metrics that may be used for retrieval accuracy estimation are therefore desirable. Using these metrics has the potential to greatly improve emission rate retrieval accuracy. Here, we investigate the impact of meteorological variability on mass-balance emission rate retrieval accuracy by using model-simulated fields as a proxy for real-world chemical and meteorological fields, in which virtual aircraft sampling of the GEM-MACH output was used for top-down mass balance estimates. We also explore the impact of upwind emissions from nearby sources on the accuracy of the retrieved emission rates. This approach allows the state of the atmosphere used for top-down estimates to be characterized in time and 3D space; the input meteorology and emissions are "known", and thus potential means for improving emission rate retrievals and determining the factors affecting retrieval accuracy may be investigated. We found that emissions retrieval accuracy is correlated with three key quantitative criteria, evaluated a priori from forecasts and/or from observations during the sampling period: (1) changes to the atmospheric stability (described as the change in gradient Richardson number), (2) variations in the direction of transport, as a result of plume vertical motion and in the presence of vertical wind shear, and (3) the combined effect of the upwind-to-downwind concentration ratio and the upwind-to-downwind concentration standard deviations. We show here that cases where these criteria indicate high temporal variability and/or high upwind emissions can result in "storage-and-release" events within the sampled region (control volume), which decrease emission rate retrieval accuracy. Storage-and-release events may contribute the bulk of mass-balance emission rate retrieval under- and over-estimates, ranging in the tests carried out here from -25 % to 24 % of the known (input) emissions, with a median of -2 %. Our analysis also includes two cases with unsuitable meteorological conditions and/or significant upwind emissions to demonstrate conditions which may result in severe storage, which in turn cause emission rate under-estimates by the mass-balance approach. We also introduce a sampling strategy whereby the emission rate retrieval under- and over-estimates associated with storage-and-release are greatly reduced (to -14 % to +5 %, respectively, relative to the magnitude of the known emissions). We recommend repeat flights over a given facility and/or time-consecutive upwind and downwind (remote) vertical profiling of relevant fields (e.g., tracer concentrations) in order to measure and account for the factors associated with storage-and-release events, estimate the temporal trends in the evolution of the system during the flight/sampling time, and partially correct for the effects of meteorological variability and upwind emissions. [ABSTRACT FROM AUTHOR]

Current air quality models usually underestimate the concentration of ambient air sulfate, but the cause of this underestimation remains unclear. One reason for the underestimation is that the sulfate formation mechanism in the models is incomplete, and does not adequately consider the impact of the synergistic effects of high concentrations of multiple pollutants on sulfate formation. In this work, the roles of gaseous NO 2 , NH 3 and solution ionic strength in the formation of sulfate in the aqueous phase were quantitatively investigated using a glass reactor and a 30 m3 smog chamber, separately. The results showed that sulfate formation was enhanced to different degrees in the presence of gas-phase NO 2 , NH 3 and their coexistence as solutes in both liquid solution and aerosol water. NH 3 enhances the aqueous oxidation of SO 2 by NO 2 mainly by accelerating the uptake of SO 2 through increased solubility. More importantly, we found that high ionic strength in aerosol water could significantly accelerate the aqueous oxidation of SO 2 , resulting in unexpectedly high S(VI) formation rates. We estimate that under severe haze conditions, heterogeneous oxidation of SO 2 by NO 2 on aerosols may be much shorter than that through gas phase oxidation by OH, aided by high ionic strengths in aerosols. Considering the existence of complex air pollution conditions with high concentrations of NO 2 , NH 3 and aerosol water, as expected in typical urban and suburban settings, the sulfate formation mechanisms revealed in the present work should be incorporated into air quality models to improve the prediction of sulfate concentrations. Image 1 • Aqueous SO 4 2− formation could be greatly enhanced with the presence of NO 2 and NH 3. • Higher reaction rate constants were observed duo to the higher ionic strengths. • Relationship between reaction rate constant and ionic strengths was obtained. Much higher reaction rate constants (k) between NO 2 and SO 2 were observed in aerosol water compared to bulk waterdue to higher ionic strengths (I); Relationship between k and I was obtained. [ABSTRACT FROM AUTHOR]

This study assesses the impact of revised volatile organic compound (VOC) and organic aerosol (OA) emissions estimates in the GEM-MACH (Global Environmental Multiscale--Modelling Air Quality and CHemistry) chemical transport model (CTM) on air quality model predictions of organic species for the Athabasca oil sands (OS) region in Northern Alberta, Canada. The first emissions data set that was evaluated (base-case run) makes use of regulatoryreported VOC and particulate matter emissions data for the large oil sands mining facilities. The second emissions data set (sensitivity run) uses total facility emissions and speciation profiles derived from box-flight aircraft observations around specific facilities. Large increases in some VOC and OA emissions in the revised-emissions data set for four large oil sands mining facilities and decreases for others were found to improve the modeled VOC and OA concentration maxima in facility plumes, as shown with the 99th percentile statistic and illustrated by case studies. The results show that the VOC emission speciation profile from each oil sand facility is unique and different from standard petrochemicalrefinery emission speciation profiles used for other regions in North America. A significant increase in the correlation coefficient is reported for the long-chain alkane predictions against observations when using the revised emissions based on aircraft observations. For some facilities, larger longchain alkane emissions resulted in higher secondary organic aerosol (SOA) production, which improved OA predictions in those plumes. Overall, the use of the revised-emissions data resulted in an improvement of the model mean OA bias; however, a decrease in the OA correlation coefficient and a remaining negative bias suggests the need for further improvements to model OA emissions and formation processes. The weight of evidence suggests that the top-down emission estimation technique helps to better constrain the fugitive organic emissions in the oil sands region, which are a challenge to estimate given the size and complexity of the oil sands operations and the number of steps in the process chain from bitumen extraction to refined oil product. This work shows that the top-down emissions estimation technique may help to constrain bottom-up emission inventories in other industrial regions of the world with large sources of VOCs and OA. [ABSTRACT FROM AUTHOR]

The oil sands (OS) of Alberta, Canada, which are classified as unconventional oil, are the third-largest oil reserves in the world. We describe here a 6-year effort to improve the emissions data used for air quality (AQ) modeling of the roughly 100 km×100 km oil extraction and processing industrial complex operating in the Athabasca Oil Sands Region (AOSR) of northeastern Alberta. This paper reviews the national, provincial, and sub-provincial emissions inventories that were available during the three phases of the study, supplemented by hourly SO2 and NOx emissions and stack characteristics for larger point sources measured by a continuous emission monitoring system (CEMS), as well as daily reports of SO2 from one AOSR facility for a 1-week period during a 2013 field campaign when the facility experienced upset conditions. Next it describes the creation of several detailed hybrid emissions inventories and the generation of model-ready emissions input files for the Global Environmental Multiscale-Modelling Air quality and CHemistry (GEM-MACH) AQ modeling system that were used during the 2013 field study and for various postcampaign GEM-MACH sensitivity studies, in particular for a high-resolution model domain with 2.5 km grid spacing covering much of western Canada and centered over the AOSR. Lastly, it compares inventory-based bottom-up emissions with aircraft-observation-based top-down emissions estimates. Results show that emissions values obtained from different data sources can differ significantly, such as a possible 10-fold difference in PM2.5 emissions and approximately 40 and 20% differences for total VOC (volatile organic compound) and SO2 emissions. A novel emissions-processing approach was also employed to allocate emissions spatially within six large AOSR mining facilities in order to address the urban-scale spatial extent of the facilities and the highresolution 2.5 km model grid. Gridded facility- and processspecific spatial surrogate fields that were generated using spatial information from GIS (geographic information system) shapefiles and satellite images were used to allocate non-smokestack emissions for each facility to multiple grid cells instead of treating these emissions as point sources and allocating them to a single grid cell as is normally done. Facility- and process-specific temporal profiles and VOC speciation profiles were also developed. The pre-2013 vegetation and land-use databases normally used to estimate biogenic emissions and meteorological surface properties were modified to account for the rapid change in land use in the study area due to marked, year-by-year changes in surface mining activities, including the 2013 opening of a new mine. Lastly, mercury emissions data were also processed in addition to the seven criteria-air-contaminant (CAC) species (NOx , VOC, SO2, NH3, CO, PM2.5, and PM10) to support AOSR mercury modeling activities. Six GEM-MACH modeling papers in this special issue used some of these new sets of emissions and land-use input files. [ABSTRACT FROM AUTHOR]

We evaluate four high-resolution model simulations of pollutant emissions, chemical transformation, and downwind transport for the Athabasca oil sands using the Global Environmental Multiscale -- Modelling Air-quality and Chemistry (GEM-MACH) model, and compare model results with surface monitoring network and aircraft observations of multiple pollutants, for simulations spanning a time period corresponding to an aircraft measurement campaign in the summer of 2013. We have focussed here on the impact of different representations of the model's aerosol size distribution and plume-rise parameterization on model results. The use of a more finely resolved representation of the aerosol size distribution was found to have a significant impact on model performance, reducing the magnitude of the original surface PM2.5 negative biases 32%, from 2.62 to - 1.72 µg m-3. We compared model predictions of SO2, NO2, and speciated particulate matter concentrations from simulations employing the commonly used Briggs (1984) plume-rise algorithms to redistribute emissions from large stacks, with stack plume observations. As in our companion paper (Gordon et al., 2017), we found that Briggs algorithms based on estimates of atmospheric stability at the stack height resulted in under-predictions of plume rise, with 116 out of 176 test cases falling below the model : observation 1 : 2 line, 59 cases falling within a factor of 2 of the observed plume heights, and an average model plume height of 289m compared to an average observed plume height of 822 m. We used a high-resolution meteorological model to confirm the presence of significant horizontal heterogeneity in the local meteorological conditions driving plume rise. Using these simulated meteorological conditions at the stack locations, we found that a layered buoyancy approach for estimating plume rise in stable to neutral atmospheres, coupled with the assumption of free rise in convectively unstable atmospheres, resulted in much better model performance relative to observations (124 out of 176 cases falling within a factor of 2 of the observed plume height, with 69 of these cases above and 55 of these cases below the 1 : 1 line and within a factor of 2 of observed values). This is in contrast to our companion paper, wherein this layered approach (driven by meteorological observations not co-located with the stacks) showed a relatively modest impact on predicted plume heights. Persistent issues with over-fumigation of plumes in the model were linked to a more rapid decrease in simulated temperature with increasing height than was observed. This in turn may have led to overestimates of near-surface diffusivity, resulting in excessive fumigation. [ABSTRACT FROM AUTHOR]

Abstract: The Pacific 2001 Air Quality Study was undertaken to characterize the physical and chemical properties of particulate matter in the Lower Fraser Valley (LFV) airshed of British Columbia. Aerosol transport in the LFV was observed to occur through several regional scale mechanisms, including seabreeze–landbreeze flows, upslope–downslope flows and north–south valley flows. Enhanced aerosol concentrations were observed in the eastern portion of the LFV, the north–south tributary valleys and the Gulf/San Juan islands convergence zone. Particle composition was found to vary according to proximity to emission sources relative to surface flows. Approximately half of the particle mass was comprised of organic carbon, with the rest being inorganic species. Sodium nitrate was an important component of the coarse particle fraction, while ammonium sulphate was concentrated in the fine fraction. A broad suite of organic substances were detected, and both anthropogenic and biogenic sources were found to contribute to secondary organic aerosol formation. Particle formation and growth was observed to occur via nucleation, condensation and coagulation. In general, the western part of the LFV airshed was dominated by combustion-related compounds, sea salt chemistry and organics (both anthropogenic and biogenic), while the eastern part of the airshed was dominated by NH3 chemistry and biogenic organics. The extent of processing of air masses was found to increase in a west to east direction, although the occasional accumulation of photochemically aged pollutants in the Gulf/San Juan islands convergence zone was observed to reverse this gradient. NH3 was found not to be a limiting species in the formation of fine mode inorganic aerosols, suggesting that NH3 emission reductions would have to be substantial in order to confer a significant improvement in PM and visibility. This coupled with the non-linear relationships between NO x , VOC and secondary particulates, suggests that PM and visibility improvement in the LFV would most likely require concurrent reductions in NH3, SO x , NO x and VOC emissions. [Copyright &y& Elsevier]

The Pacific 2001 Air Quality Study was a major program on ambient particulate matter carried out in the Lower Fraser Valley. This paper provides an overview of the study and gives accounts of the measurements in each major components of the field measurement program, including ground sites specifically targeted on traffic emissions, urban mixing, urban to rural transition, biogenic emissions from forest, and a mixture of urban and forest, and an airborne measurement program to link the ground based components. A summary of major findings is given in the paper, along with a general background for the papers in this issue. [Copyright &y& Elsevier]

Abstract: The data management and archiving activities of the Pacific 2001 Air Quality Study were handled by the Pacific 2001 Data Centre which was run by the National Atmospheric Chemistry (NAtChem) Database and Analysis Facility of Environment Canada. To ensure that the Pacific 2001 Air Quality Study data were archived in a common way, the NARSTO Data Exchange Standard (DES) was used as the mandatory format for the data files, partially because it allowed for the inclusion of metadata within the data files and partially because it provided the necessary flexibility for handling the many measurement types used in the study. Described in detail in the paper, the DES is now readily available to the scientific community. After each DES data file was submitted to the Data Centre, a read-and-verify program was run to check its conformity to the DES and to detect incorrect and problematic data. The errors detected by the read-and-verify program were automatically documented and an error report was sent to the data originators for data correction and resubmission. Statistical summaries and data plots were created for all data files and subsequently sent to the data originators for review and further error detection. Of the 125 data files submitted to the Data Centre, only 5 were error-free upon first submission. A test of 17 randomly selected files determined that all but two required at least four iterations of the submission–error checking–resubmission cycle in order to produce final error-free files. It was therefore concluded that both data originators and data centres alike should assume that errors exist in all submitted data files until proven differently by a set of automated error-checking programs. It was also concluded that data visualization plots and statistical summaries are highly effective tools for detecting errors in data files. Metadata associated with the measurement data were documented in Quality Assurance Project Plans that were archived in the Data Centre with the DES data files. [Copyright &y& Elsevier]