The 2023 wildfires in Canada resulted in substantial emissions to air. In this work, we used predicted concentrations of hazardous air pollutants (HAPs), fine particulate matter (PM2.5), and ozone across the U.S. and Canada to estimate the potential impacts of 2023 Canadian wildfire smoke on human health. HAPs from Canadian wildfires were estimated to increase lifetime population-weighted cancer inhalation risk by 1-in-1 million (500 excess cancer cases) and noncancer risk by a hazard index (HI) of 0.05 across the domain. The additional risk from HAPs in smoke was predicted to exceed a cancer risk of 100-in-1 million for 1,300 people and a HI of 1.0 for 110,000 people, all in Canada. In addition, 360,000 people in Canada were predicted to experience an increase in annual-mean PM2.5 of at least 5 μg m-3. Nearly 63 million people, 76% of which were in the U.S., were predicted to experience an increase in seasonal maximum daily 8-hour average ozone greater than 1 ppb. In Canada, ozone and PM2.5 associated with the 2023 fires were estimated to result in over 3x more attributable deaths per year than wildfire smoke in years 2013 through 2018.

Abstract. The Surface Tiled Aerosol and Gaseous Exchange (STAGE) model was developed for estimating dry deposition and bidirectional exchange for field-scale applications and use within the CMAQ v5.3.2 regional scale model. The model was evaluated against micrometeorological flux measurements of NH3, HNO3, and SO2 at a managed grassland and NH3 in a cultivated corn (Zea Mays) field. When using field-scale observations for soil and vegetation NH3 compensation points, modelled fluxes for all species agreed well, within or near the reported measurement uncertainty. However, when using the CMAQ v5.3.2 values for NH3 emission potentials at the Duke Forest grassland site, the model estimated mean net deposition rate was 1.3 ng m-2 h-1 while the observed mean NH3 evasive flux was 8.4 ng m-2 h-1. Modelled NH3 concentration fields evaluated against Cross-Track Infrared Sounder (CrIS) satellite observations indicates a broad underestimation of NH3 concentrations by approximately 1 to 2 ppb in the U.S. Great Plains. The results from the grassland field data and indicates that there is likely an underestimation of the evasive NH3 flux in grassland sites due to the model's default tabular values of the vegetation/litter NH4+ concentrations. The STAGE's model sensitivity to soil and vegetation emission potentials indicates that regional scale model results for NH3 can be further improved with additional micrometeorological flux and vegetation and soil chemistry measurements over different land use types, soil types, and vegetation phenological stages.

Epidemiologic studies of ambient fine particulate matter (PM2.5) and ozone (O3) often use outdoor concentrations from central-site monitors or air quality model estimates as exposure surrogates, which can result in exposure errors. We previously developed an exposure model called TracMyAir, which is an iPhone application that determines seven tiers of individual-level exposure metrics for ambient PM2.5 and O3 using outdoor concentrations, home building characteristics, weather, time-activities. The exposure metrics with increasing information needs and complexity include: outdoor concentration (Cout, Tier 1), building infiltration factor (Finf, Tier 2), indoor concentration (Cin, Tier 3), time spent in microenvironments (ME) (TME, Tier 4), personal exposure factor (Fpex, Tier 5), exposure (E, Tier 6), and inhaled dose (D, Tier 7). In this study, we extended TracMyAir with two sets of additional features: (1) time-resolved exposures using smartphone geolocations with a ME classification model (MicroTrac) and official PM2.5 and O3 monitoring network, and (2) exposures based on low-cost outdoor PurpleAir (PA) PM2.5 monitoring network, non-ambient indoor PM2.5 using indoor-outdoor PA monitors, and inhaled dose based on physical activity data from smartphone and smartwatch. To demonstrate the two sets of extended features, we applied TracMyAir to estimate hourly PM2.5 and O3 exposure metrics for two corresponding panel studies with participants living in central North Carolina, USA. For Tier 4, the MicroTrac estimates were compared with 24-h diary data, and correctly classified the ME for 97 % of the daily time spent by the participants. Overall, the TracMyAir estimates showed considerable temporal and building-to-building variability of Finf, and Cin (Tiers 2–3), and person-to-person variability of Cout, TME, Fpex, E, and D (Tiers 1, 4–7). Our study demonstrates the capability of extending TracMyAir with air quality monitors, location-activity sensors, and models to determine fine-scale exposures, in support of epidemiologic studies and public health strategies to help reduce exposures to air pollutants.

Past work has shown that traffic patterns in the USA and resulting NOx emissions vary by day of week, with NOx emissions typically being higher on weekdays than weekends. This pattern of emissions leads to different levels of ozone on weekends versus weekdays and can be leveraged to understand how local ozone formation changes in response to NOx emission perturbations in different urban areas. Specifically, areas with lower NOx but higher ozone on the weekends (the weekend effect) can be characterized as NOx-saturated and areas with both lower NOx and ozone on weekends (the weekday effect) can be characterized as NOx-limited. In this analysis, we assess maximum daily 8 h average (MDA8) ozone weekend–weekday differences across 51 USA nonattainment areas using 18 years of observed and modeled data from 2002–2019, using the following two metrics: mean MDA8 ozone and percentage of days with MDA8 ozone > 70 ppb (parts per billion). In addition, we quantify the modeled and observed trends in these weekend–weekday differences across this period of substantial NOx emission reductions in the USA. The model assessment is carried out using U.S. Environmental Protection Agency (EPA)'s Air QUAlity TimE Series Project (EQUATES) Community Multiscale Air Quality (CMAQ) model dataset. We identify three types of MDA8 ozone trends occurring across the USA, namely transitioning chemical regime, disappearing weekday effect, and no trend. The transitioning chemical regime trend occurs in a subset of large urban areas that were NOx-saturated (i.e., volatile organic compound (VOC)-limited) at the beginning of the analysis period but transitioned to mixed chemical regimes or NOx-limited conditions by the end of the analysis period. Nine areas have strong transitioning chemical regime trends using both modeled and observed data and with both metrics indicating strong agreement that they are shifting to more NOx-limited conditions: Milwaukee, Houston, Phoenix, Denver, the Northern Wasatch Front, the Southern Wasatch Front, Las Vegas, Los Angeles – San Bernardino County, Los Angeles – South Coast, and San Diego. The disappearing weekday effect was identified for multiple rural and agricultural areas of California which were NOx-limited for the entire analysis period but appear to become less influenced by local day-of-week emission patterns in more recent years. Finally, we discuss a variety of reasons why there are no trends in certain areas including complex impacts of heterogeneous source mixes and stochastic impacts of meteorology. Overall, this assessment finds that the EQUATES modeling simulations indicate more NOx-saturated conditions than the observations but do a good job of capturing year-to-year changes in weekend–weekday MDA8 ozone patterns.

Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4) is focused on the diagnostic intercomparison and evaluation of deposition simulated by regional-scale air quality modeling systems and employs both grid and box modeling techniques to accomplish this goal. This study presents an analysis of CMAQv5.3.1 simulations that were performed in the context of AQMEII4 over a North American modeling domain. Results show that variability in the estimated dry deposition sink affected model performance and resulted from both differences in model process formulation and the representation of the underlying land use (LU). To gain mechanistic insights into model behavior, the study employs diagnostic variables defined for the AQMEII4 project, i.e., grid scale and land-use specific effective conductances and deposition fluxes for the major dry deposition pathways (stomatal, cuticular, lower canopy, and soil). Analysis of these variables indicates that there generally is a greater contribution to ozone dry deposition from the stomatal and cuticular pathways in the CMAQ M3DRY dry deposition scheme compared to CMAQ STAGE dry deposition scheme and that differences in LU classification schemes can have a pronounced impact on simulated fluxes.

The United States Environmental Protection Agency (US EPA) has developed a set of annual North American emissions data for multiple air pollutants across 18 broad source categories for 2002 through 2017. The sixteen new annual emissions inventories were developed using consistent input data and methods across all years. When a consistent method or tool was not available for a source category, emissions were estimated by scaling data from the EPA's 2017 National Emissions Inventory with scaling factors based on activity data and/or emissions control information. The emissions datasets are designed to support regional air quality modeling for a wide variety of human health and ecological applications. The data were developed to support simulations of the EPA's Community Multiscale Air Quality model but can also be used by other regional scale air quality models. The emissions data are one component of EPA's Air Quality Time Series Project which also includes air quality modeling inputs (meteorology, initial conditions, boundary conditions) and outputs (e.g., ozone, PM2.5 and constituent species, wet and dry deposition) for the Conterminous US at a 12 km horizontal grid spacing.

Extra figures showing area-specific observed and modeled ozone distributions, modeled NOX distributions, modeled formaldehyde distributions and trends in ∆ , ̅̅̅̅̅̅̅̅̅̅ Figure S-1.Door County, WI nonattianment area 2002-2019 May-Sep: observed (top left) and modeled (top center) MDA8 ozone distribution by day of week; modeled NOX (bottom left) and modeled formaldehyde (bottom center) distribution by day of week; observed and modeled trends in ∆ , ̅̅̅̅̅̅̅̅̅̅ (top right); modeled trends in WE-WD NOX and formaldehyde differences (bottom right).The distributions by day of the week are for the entire 18 years with each box representing the 25 th to 75 th percentile for that day of the week across all 18 years, the whiskers representing the 1.5 times the interquartile range, and the bold line inside the box representing the median.WE-WD differences (top and bottom right) are based on 5-year rolling periods.0.221 (0.198,0.25) p-val < 0.

Abstract. Past work has shown that traffic patterns in the US and resulting NOX emissions vary by day of week, with NOX emissions typically higher on weekdays than weekends. This pattern of emissions leads to different levels of ozone on weekends versus weekdays and can be leveraged to understand how local ozone formation changes in response to NOX emissions perturbations in different urban areas. Specifically, areas with lower NOX but higher ozone on the weekends (the weekend effect) can be characterized as NOX -saturated and areas with both lower NOX and ozone on weekends (the weekday effect) can be characterized as NOX-limited. In this analysis we assess ozone weekend-weekday differences across US nonattainment areas using 18 years of observed and modeled data from 2002–2019 using two metrics: mean ozone and percentage of days > 70 ppb. In addition, we quantify the modeled and observed trends in these weekend-weekday differences across this period of substantial NOX emissions reductions in the US. The model assessment is carried out using EPA’s Air QUAlity TimE Series Project (EQUATES) CMAQ dataset. We identify 3 types of ozone trends occuring across the US: disappearing weekend effect, disappearing weekday effect, and no trend. The disappearing weekend effect occurs in a subset of large urban areas that were NOX -saturated (i.e., VOC-limited) at the beginning of the analysis period but transitioned to mixed chemical regimes or NOX-limited conditions by the end of the analysis period. Nine areas have disappearing weekend effect trends in both datasets and with both metrics indicating strong agreement that they are shifting to more NOX-limited conditions: Milwaukee, Houston, Phoenix, Denver, Northern Wasatch Front, Southern Wasatch Front, Las Vegas, Los Angeles – San Bernardino County, Los Angeles – South Coast, and San Diego. The disappearing weekday effect was identified for multiple rural and agricultural areas of California which were NOX -limited for the entire analysis period but appear to become less influenced by local day of week emission patterns in more recent years. Finally, we discuss a variety of reasons why there are no statistically significant trends in certain areas including complex impacts of heterogeneous source mixes and stochastic impacts of meteorology. Overall, this assessment finds that the EQUATES modeling simulations indicate more NOX-saturated conditions than the observations but do a good job of capturing year-to-year changes in weekend-weekday ozone patterns.

The fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4) is conducting a diagnostic intercomparison and evaluation of deposition simulated by regional-scale air quality models over North America and Europe. In this study, we analyze annual AQMEII4 simulations performed with the Community Multiscale Air Quality Model (CMAQ) version 5.3.1 over North America. These simulations were configured with both the M3Dry and Surface Tiled Aerosol and Gas Exchange (STAGE) dry deposition schemes available in CMAQ. A comparison of observed and modeled concentrations and wet deposition fluxes shows that the AQMEII4 CMAQ simulations perform similarly to other contemporary regional-scale modeling studies. During summer, M3Dry has higher ozone (O3) deposition velocities (Vd) and lower mixing ratios than STAGE for much of the eastern U.S. while the reverse is the case over eastern Canada and along the West Coast. In contrast, during winter STAGE has higher O3 Vd and lower mixing ratios than M3Dry over most of the southern half of the modeling domain while the reverse is the case for much of the northern U.S. and southern Canada. Analysis of the diagnostic variables defined for the AQMEII4 project, i.e. grid-scale and land-use (LU) specific effective conductances and deposition fluxes for the major dry deposition pathways, reveals generally higher summertime stomatal and wintertime cuticular grid-scale effective conductances for M3Dry and generally higher soil grid-scale effective conductances (for both vegetated and bare soil) for STAGE in both summer and winter. On a domain-wide basis, the stomatal grid-scale effective conductances account for about half of the total O3 Vd during daytime hours in summer for both schemes. Employing LU-specific diagnostics, results show that daytime Vd varies by a factor of 2 between LU categories. Furthermore, M3Dry vs. STAGE differences are most pronounced for the stomatal and vegetated soil pathway for the forest LU categories, with M3Dry estimating larger effective conductances for the stomatal pathway and STAGE estimating larger effective conductances for the vegetated soil pathway for these LU categories. Annual domain total O3 deposition fluxes differ only slightly between M3Dry (74.4 Tg/year) and STAGE (76.2 Tg/yr), but pathway-specific fluxes to individual LU types can vary more substantially on both annual and seasonal scales which would affect estimates of O3 damages to sensitive vegetation. A comparison of two simulations differing only in their LU classification scheme shows that the differences in LU cause seasonal mean O3 mixing ratio differences on the order of 1 ppb across large portions of the domain, with the differences generally largest during summer and in areas characterized by the largest differences in the fractional coverages of the forest, planted/cultivated, and grassland LU categories. These differences are generally smaller than the M3Dry vs. STAGE differences outside the summer season but have a similar magnitude during summer. Results indicate that the deposition impacts of LU differences are caused both by differences in the fractional coverages and spatial distributions of different LU categories as well as the characterization of these categories through variables like surface roughness and vegetation fraction in look-up tables used in the land-surface model and deposition schemes. Overall, the analyses and results presented in this study illustrate how the diagnostic grid-scale and LU-specific dry deposition variables adopted for AQMEII4 can provide insights into similarities and differences between the CMAQ M3Dry and STAGE dry deposition schemes that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.

Chemical mechanisms describe how emissions of gases and particles evolve in the atmosphere and are used within chemical transport models to evaluate past, current, and future air quality. Thus, a chemical mechanism must provide robust and accurate 20 predictions of air pollutants if it is to be considered for use by regulatory bodies. In this work, we provide an initial evaluation of the Community Regional Atmospheric Chemical Multiphase Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone (O 3 ) across the Northeast U.S. during the summer of 2018 within the Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1

Chemical mechanisms describe how emissions of gases and particles evolve in the atmosphere and are used within chemical transport models to evaluate past, current, and future air quality. Thus, a chemical mechanism must provide robust and accurate predictions of air pollutants if it is to be considered for use by regulatory bodies. In this work, we provide an initial evaluation of the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMMv1.0) by assessing CRACMMv1.0 predictions of surface ozone (O3) across the northeastern US during the summer of 2018 within the Community Multiscale Air Quality (CMAQ) modeling system. CRACMMv1.0 O3 predictions of hourly and maximum daily 8 h average (MDA8) ozone were lower than those estimated by the Regional Atmospheric Chemistry Mechanism with aerosol module 6 (RACM2_ae6), which better matched surface network observations in the northeastern US (RACM2_ae6 mean bias of +4.2 ppb for all hours and +4.3 ppb for MDA8; CRACMMv1.0 mean bias of +2.1 ppb for all hours and +2.7 ppb for MDA8). Box model calculations combined with results from CMAQ emission reduction simulations indicated a high sensitivity of O3 to compounds with biogenic sources. In addition, these calculations indicated the differences between CRACMMv1.0 and RACM2_ae6 O3 predictions were largely explained by updates to the inorganic rate constants (reflecting the latest assessment values) and by updates to the representation of monoterpene chemistry. Updates to other reactive organic carbon systems between RACM2_ae6 and CRACMMv1.0 also affected ozone predictions and their sensitivity to emissions. Specifically, CRACMMv1.0 benzene, toluene, and xylene chemistry led to efficient NOx cycling such that CRACMMv1.0 predicted controlling aromatics reduces ozone without rural O3 disbenefits. In contrast, semivolatile and intermediate-volatility alkanes introduced in CRACMMv1.0 acted to suppress O3 formation across the regional background through the sequestration of nitrogen oxides (NOx) in organic nitrates. Overall, these analyses showed that the CRACMMv1.0 mechanism within the CMAQ model was able to reasonably simulate ozone concentrations in the northeastern US during the summer of 2018 with similar magnitude and diurnal variation as the current operational Carbon Bond (CB6r3_ae7) mechanism and good model performance compared to recent modeling studies in the literature.

We examined the impact of dimethylsulfide (DMS) emissions on sulfate concentrations over the continental U.S. by using the Community Multiscale Air Quality (CMAQ) model version 5.4 and performing annual simulations without and with DMS emissions for 2018. DMS emissions enhance sulfate not only over seawater but also over land, although to a lesser extent. On an annual basis, the inclusion of DMS emissions increase sulfate concentrations by 36% over seawater and 9% over land. The largest impacts over land occur in California, Oregon, Washington, and Florida, where the annual mean sulfate concentrations increase by ~25%. The increase in sulfate causes a decrease in nitrate concentration due to limited ammonia concentration, especially over seawater, and an increase in ammonium concentration with a net effect of increased inorganic particles. The largest sulfate enhancement occurs near the surface (over seawater), and the enhancement decreases with altitude, diminishing to 10–20% at an altitude of ~5 km. Seasonally, the largest enhancement in sulfate over seawater occurs in summer, and the lowest in winter. In contrast, the largest enhancements over land occur in spring and fall due to higher wind speeds that can transport more sulfate from seawater into land.

Data fusion can be applied to air quality data to create improved air quality estimates. Data fusion methods have previously been applied to major particulate and gas species, with little focus on trace metal particulate species. The data fusion method presented here, improves temporal and spatial correlations for ten pollutants (Al, Ca, Mn, Si, Fe, Ti, K, Mg, Cl, Na) across the continental United States at a 12km resolution for 2006. Temporal correlations (R2) between the fused products and observations ranged between 0.86-0.97 for all pollutants and spatial correlation ranged between 0.12-0.86. Spatial-temporal cross validation R2 values ranged from 0.40 - 0.64 for Al, Ca, Mg, Cl, and Na. The accuracy of the estimates for Fe, Si, K, Mn, and Ti was lower, with an R2 ranging from 0.01 – 0.18; however, these metrics were larger than the correlation between the observations and the estimates from the original CMAQ simulation.

Atmospheric deposition of nitrogen (N) and sulfur (S) compounds from human activity has greatly declined in the United States (US) over the past several decades in response to emission controls set by the Clean Air Act. While many observational studies have investigated spatial and temporal trends of atmospheric deposition, modeling assessments can provide useful information over areas with sparse measurements, although they usually have larger horizontal resolutions and are limited by input data availability. In this analysis, we evaluate wet, dry, and total N and S deposition from multiyear simulations within the contiguous US (CONUS). Community Multiscale Air Quality (CMAQ) model estimates from the EPA's (Environmental Protection Agency) Air QUAlity TimE Series (EQUATES) project contain important model updates to atmospheric deposition algorithms compared to previous model data, including the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model which contains land-use-specific resistance parameterization and land-use-specific deposition estimates needed to estimate the differential impacts of N deposition to different land use types. First, we evaluate model estimates of wet deposition and ambient concentrations, finding underestimates of SO4, NO3, and NH4 wet deposition compared to National Atmospheric Deposition Program observations and underestimates of NH4 and SO4 and overestimates of SO2 and TNO3 (HNO3+NO3) compared to the Clean Air Status and Trends Network (CASTNET) ambient concentrations. Second, a measurement–model fusion approach employing a precipitation and bias correction to wet-deposition estimates is found to reduce model bias and improve correlations compared to the unadjusted model values. Model agreement of wet deposition is poor over parts of the West and Northern Rockies, due to errors in precipitation estimates caused by complex terrain and uncertainty in emissions at the relatively coarse 12 km grid resolution used in this study. Next, we assess modeled N and S deposition trends across climatologically consistent regions in the CONUS. Total deposition of N and S in the eastern US is larger than the western US with a steeper decreasing trend from 2002–2017; i.e., total N declined at a rate of approximately −0.30 kg N ha−1 yr−1 in the Northeast and Southeast and by −0.02 kg N ha−1 yr−1 in the Northwest and Southwest. Widespread increases in reduced N deposition across the Upper Midwest, Northern Rockies, and West indicate evolving atmospheric composition due to increased precipitation amounts over some areas, growing agricultural emissions, and regional NOx/SOx emission reductions shifting gas–aerosol partitioning; these increases in reduced N deposition are generally masked by the larger decreasing oxidized N trend. We find larger average declining trends of total N and S deposition between 2002–2009 than 2010–2017, suggesting a slowdown of the rate of decline likely in response to smaller emission reductions. Finally, we document changes in the modeled total N and S deposition budgets. The average annual total N deposition budget over the CONUS decreases from 7.8 in 2002 to 6.3 kg N ha−1 yr−1 in 2017 due to declines in oxidized N deposition from NOx emission controls. Across the CONUS during the 2002–2017 time period, the average contribution of dry deposition to the total N deposition budget drops from 60 % to 52 %, whereas wet deposition dominates the S budget rising from 45 % to 68 %. Our analysis extends upon the literature documenting the growing contribution of reduced N to the total deposition budget, particularly in the Upper Midwest and Northern Rockies, and documents a slowdown of the declining oxidized N deposition trend, which may have consequences on vegetation diversity and productivity.

Dry deposition of atmospheric aerosols in large-scale models is a critical, but highly uncertain, sink process with a strong dependence on particle size, meteorological conditions, and land surface properties. This study investigates the particle dry deposition scheme implemented in the standard Community Multiscale Air Quality (CMAQ) model v5.2.1, characterizes its underlying parameterized components with comparison to a similar scheme in a contemporary regional-scale model, and proposes two updated schemes that are then evaluated with available ambient particle deposition velocity (Vd) measurements. Both updated schemes reduce the surprisingly strong dependence of deposition velocity on the aerosol mode width, with one scheme further introducing a dependence on vegetation coverage that is broadly consistent with variability in observations between vegetated and non-vegetated surfaces. Compared to the base scheme, the updated scheme with vegetation dependence increases Vd for submicron particles and decreases it for larger particles by an average of 37% and -66%, respectively. This scheme performs statistically better than the base scheme, reducing fractional biases by 56%-97% for vegetated land-use types and has roughly equivalent performance over water. The base and updated schemes are tested with three annual CMAQ (v5.2.1) simulations for the year 2011; predicted ambient aerosol concentrations are evaluated with routine monitoring network observations and predicted dry deposition fluxes are evaluated with data from the Clean Air Status and Trends Network (CASTNET). The updated scheme with vegetation dependence reduces negative fractional biases for PM10 by 41% and positive fractional biases for PM2.5 organic carbon by 15%. This scheme has been incorporated into the most recent publicly accessible versions of CMAQ (v5.3 and beyond) to replace the scheme used in previous versions of CMAQ (v4.5 through v5.2.1).

Exposure to ozone and fine particle (PM2.5) air pollution results in premature death. These pollutants are predominantly secondary in nature and can form from nitrogen oxides (NOX), sulfur oxides (SOX), and volatile organic compounds (VOCs). Predicted health benefits for emission reduction scenarios often incompletely account for VOCs as precursors as well as the secondary organic aerosol (SOA) component of PM2.5. Here, we show that anthropogenic VOC emission reductions are more than twice as effective as equivalent fractional reductions of SOX or NOX at reducing air pollution-associated cardiorespiratory mortality in the United States. A 25% reduction in anthropogenic VOC emissions from 2016 levels is predicted to avoid 13,000 premature deaths per year, and most (85%) of the VOC-reduction benefits result from reduced SOA with the remainder from ozone. While NOX (-5.7 ± 0.2 % yr-1) and SOX (-12 ± 1 % yr-1) emissions have declined precipitously across the U.S. since 2002, anthropogenic VOC emissions (-1.8 ± 0.3 % yr-1) and concentrations of non-methane organic carbon (-2.4 ± 1.0 % yr-1) have changed less. This work indicates preferentially controlling VOCs could yield significant benefits to human health.

Air quality modeling for research and regulatory applications often involves executing many emissions sensitivity cases to quantify impacts of hypothetical scenarios, estimate source contributions, or quantify uncertainties. Despite the prevalence of this task, conventional approaches for perturbing emissions in chemical transport models like the Community Multiscale Air Quality (CMAQ) model require extensive offline creation and finalization of alternative emissions input files. This workflow is often time-consuming, error-prone, inconsistent among model users, difficult to document, and dependent on increased hard disk resources. The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module, a component of CMAQv5.3 and beyond, addresses these limitations by performing these modifications online during the air quality simulation. Further, the model contains an Emission Control Interface which allows users to prescribe both simple and highly complex emissions scaling operations with control over individual or multiple chemical species, emissions sources, and spatial areas of interest. DESID further enhances the transparency of its operations with extensive error-checking and optional gridded output of processed emission fields. These new features are of high value to many air quality applications including routine perturbation studies, atmospheric chemistry research, and coupling with external models (e.g., energy system models, reduced-form models).

Atmospheric nitrogen oxide and nitrogen dioxide (NO + NO2, together termed as NOX) estimates from annual photochemical simulations for years 2002-2016 are compared to surface network measurements of NOX and total gas-phase-oxidized reactive nitrogen (NOY) to evaluate the Community Multiscale Air Quality (CMAQ) modeling system performance by U.S. region, season, and time of day. In addition, aircraft measurements from 2011 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality are used to evaluate how emissions, chemical mechanism, and measurement uncertainty each contribute to the overall model performance. We show distinct seasonal and time-of-day patterns in NOX performance. Summertime NOX is overpredicted with bimodal peaks in bias during early morning and evening hours and persisting overnight. The summertime morning NOX bias dropped from between 28% and 57% for earlier years (2002-2012) to between -2% and 7% for later years (2013-2016). Summer daytime NOX tends to be unbiased or underpredicted. In winter, the evening NOX overpredictions remain, but NOX is unbiased or underpredicted overnight, in the morning, and during the day. NOX overpredictions are most pronounced in the Midwestern and Southern United States with Western regions having more of a tendency toward model underpredictions of NOX. Modeled NOX performance has improved substantially over time, reflecting updates to the emission inputs and the CMAQ air quality model. Model performance improvements are largest for years simulated with CMAQv5.1 or later and for emission inventory years 2014 and later, coinciding with reduced onroad NOX emissions from vehicles with newer emission control technologies and improved treatment of chemistry, deposition, and vertical mixing in CMAQ. Our findings suggest that emissions temporalization of specific mobile source sectors have a small impact on model performance, while chemistry updates improve predictions of NOY but do not improve summertime NOX bias in the Baltimore/DC area. Sensitivity runs performed for different locations across the country suggest that the improvement in summer NOX performance can be attributed to updates in vertical mixing incorporated in CMAQv5.1.