An Analysis of CMAQ Gas Phase Dry Deposition over North America Through Grid-Scale and Land-Use Specific Diagnostics in the Context of AQMEII4

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.

2002-2017 anthropogenic emissions data for air quality modeling over the United States

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, PM_2.5 and constituent species, wet and dry deposition) for the Conterminous US at a 12 km horizontal grid spacing.

Wet nitrogen (N) deposition to urban Latin America: filling in the gaps with GEOS-Chem

In Latin America, atmospheric deposition is a major vector of nitrogen (N) input to urban systems. Yet, measurements of N deposition are sparse, precluding analysis of spatial patterns, temporal trends, and ecosystem impacts. Chemical transport models can be used to fill these gaps in the absence of dense measurements. Here, we evaluate the performance of a global 3-D chemical transport model in simulating spatial and interannual variation in wet inorganic N (NH₄-N + NO₃-N) deposition across urban areas in Latin America. Monthly wet and dry inorganic N deposition to Latin America were simulated for the period 2006-2010 using the GEOS-Chem Chemical Transport Model. Published estimates of observed wet or bulk inorganic N deposition measured between 2006-2010 were compiled for 16 urban areas and then compared with model output from GEOS-Chem. Observed mean annual inorganic N deposition to the urban study sites ranged from 5.7-14.2 kg ha^-1 yr^-1, with NH₄-N comprising 48-90% of the total. Results show that simulated N deposition was highly correlated with observed N deposition across sites (R² = 0.83, NMB = -50%). However, GEOS-Chem generally underestimated N deposition to urban areas in Latin America compared to observations. Underestimation due to bulk sampler dry deposition artifacts was considered and improved bias without improving correlation. In contrast to spatial variation, the model did not capture year-to-year variation well. Discrepancies between modeled and observed values exist, in part, because of uncertainties in Latin American N emissions inventories. Our findings indicate that even at coarse spatial resolution, GEOS-Chem can be used to simulate N deposition to urban Latin America, improving understanding of regional deposition patterns and potential ecological effects.

The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation

The Community Multiscale Air Quality (CMAQ) model version 5.3 (CMAQ53), released to the public in August 2019 and followed by version 5.3.1 (CMAQ531) in December 2019, contains numerous science updates, enhanced functionality, and improved computation efficiency relative to the previous version of the model, 5.2.1 (CMAQ521). Major science advances in the new model include a new aerosol module (AERO7) with significant updates to secondary organic aerosol (SOA) chemistry, updated chlorine chemistry, updated detailed bromine and iodine chemistry, updated simple halogen chemistry, the addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism, updated M3Dry bidirectional deposition model, and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model's hybrid vertical coordinate (HVC) was added to CMAQ53 and the Meteorology-Chemistry Interface Processor (MCIP) version 5.0 (MCIP50). Enhanced functionality in CMAQ53 includes the new Detailed Emissions Scaling, Isolation and Diagnostic (DESID) system for scaling incoming emissions to CMAQ and reading multiple gridded input emission files. Evaluation of CMAQ531 was performed by comparing monthly and seasonal mean daily 8 h average (MDA8) O₃ and daily PM_2.5 values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O₃, CMAQ531 has higher O₃ in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O₃ bias (2-4 ppbv monthly average). MDA8 O₃ is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O₃ from the lateral boundary conditions (BCs), which generally increases MDA8 O₃ bias in spring and fall ( 0.5 μg m^-3). For daily 24 h average PM_2.5, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter to CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons were also performed to isolate updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used. Transitioning from a hemispheric CMAQ (HCMAQ) version 5.2.1 simulation to a HCMAQ version 5.3 simulation to provide lateral BCs contributes to higher O₃ mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O₃ dry deposition to snow in CMAQ53) and lower O₃ mixing ratios in middle and lower latitudes year-round (due to reduced O₃ over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC resulted in consistently higher (1.0-1.5 ppbv) MDA8 O₃ mixing ratios and higher PM_2.5 concentrations (0.1-0.25 μg m^-3) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O₃ is generally higher with M3Dry outside of summer, while PM_2.5 is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to non-vegetated surfaces and land use with short vegetation (e.g., grasslands) between the two models. For ambient NH₃, STAGE has slightly higher concentrations and smaller bias in the winter, spring, and fall, while M3Dry has higher concentrations and smaller bias but larger error and lower correlation in the summer.

Dry Deposition of Ozone over Land: Processes, Measurement, and Modeling

Dry deposition of ozone is an important sink of ozone in near surface air. When dry deposition occurs through plant stomata, ozone can injure the plant, altering water and carbon cycling and reducing crop yields. Quantifying both stomatal and nonstomatal uptake accurately is relevant for understanding ozone's impact on human health as an air pollutant and on climate as a potent short-lived greenhouse gas and primary control on the removal of several reactive greenhouse gases and air pollutants. Robust ozone dry deposition estimates require knowledge of the relative importance of individual deposition pathways, but spatiotemporal variability in nonstomatal deposition is poorly understood. Here we integrate understanding of ozone deposition processes by synthesizing research from fields such as atmospheric chemistry, ecology, and meteorology. We critically review methods for measurements and modeling, highlighting the empiricism that underpins modeling and thus the interpretation of observations. Our unprecedented synthesis of knowledge on deposition pathways, particularly soil and leaf cuticles, reveals process understanding not yet included in widely-used models. If coordinated with short-term field intensives, laboratory studies, and mechanistic modeling, measurements from a few long-term sites would bridge the molecular to ecosystem scales necessary to establish the relative importance of individual deposition pathways and the extent to which they vary in space and time. Our recommended approaches seek to close knowledge gaps that currently limit quantifying the impact of ozone dry deposition on air quality, ecosystems, and climate.

A review of measurements of air-surface exchange of reactive nitrogen in natural ecosystems across North America

This review summarizes the state of the science of measurements of dry deposition of reactive nitrogen (Nr) compounds in North America, beginning with current understanding of the importance of dry deposition at the U.S. continental scale followed by a review of micrometeorological flux measurement methods. Measurements of Nr air-surface exchange in natural ecosystems of North America are then summarized, focusing on the U.S. and Canada. Drawing on this synthesis, research needed to address the incompleteness of dry deposition budgets, more fully characterize temporal and geographical variability of fluxes, and better understand air-surface exchange processes is identified. Our assessment points to several data and knowledge gaps that must be addressed to advance dry deposition budgets and air-surface exchange modeling for North American ecosystems. For example, recent studies of particulate (NO3-) and gaseous (NOx, HONO, peroxy nitrates) oxidized N fluxes challenge the fundamental framework of unidirectional flux from the atmosphere to the surface employed in most deposition models. Measurements in forest ecosystems document the importance of in-canopy chemical processes in regulating the net flux between the atmosphere and biosphere, which can result in net loss from the canopy. These results emphasize the need for studies to quantify within- and near-canopy sources and sinks of the full suite of components of the Nr chemical system under study (e.g., NOy or HNO3-NH3-NH4NO3). With respect to specific ecosystems and geographical locations, additional flux measurements are needed particularly in agricultural regions (NH3), coastal zones (NO3- and organic N), and arid ecosystems and along urban to rural gradients (NO2). Measurements that investigate non-stomatal exchange processes (e.g., deposition to wet surfaces) and the biogeochemical drivers of bidirectional exchange (e.g., NH3) are considered high priority. Establishment of long-term sites for process level measurements of reactive chemical fluxes should be viewed as a high priority long-term endeavor of the atmospheric chemistry and ecological communities.

Toward the improvement of total nitrogen deposition budgets in the United States

Frameworks for limiting ecosystem exposure to excess nutrients and acidity require accurate and complete deposition budgets of reactive nitrogen (Nr). While much progress has been made in developing total Nr deposition budgets for the U.S., current budgets remain limited by key data and knowledge gaps. Analysis of National Atmospheric Deposition Program Total Deposition (NADP/TDep) data illustrates several aspects of current Nr deposition that motivate additional research. Averaged across the continental U.S., dry deposition contributes slightly more (55%) to total deposition than wet deposition and is the dominant process (>90%) over broad areas of the Southwest and other arid regions of the West. Lack of dry deposition measurements imposes a reliance on models, resulting in a much higher degree of uncertainty relative to wet deposition which is routinely measured. As nitrogen oxide (NOx) emissions continue to decline, reduced forms of inorganic nitrogen (NHx = NH3 + NH4+) now contribute >50% of total Nr deposition over large areas of the U.S. Expanded monitoring and additional process-level research are needed to better understand NHx deposition, its contribution to total Nr deposition budgets, and the processes by which reduced N deposits to ecosystems. Urban and suburban areas are hotspots where routine monitoring of oxidized and reduced Nr deposition is needed. Finally, deposition budgets have incomplete information about the speciation of atmospheric nitrogen; monitoring networks do not capture important forms of Nr such as organic nitrogen. Building on these themes, we detail the state of the science of Nr deposition budgets in the U.S. and highlight research priorities to improve deposition budgets in terms of monitoring and flux measurements, leaf- to regional-scale modeling, source apportionment, and characterization of deposition trends and patterns.

A Measurement-Model Fusion Approach for Improved Wet Deposition Maps and Trends

Air quality models provide spatial fields of wet deposition (WD) and dry deposition that explicitly account for the transport and transformation of emissions from thousands of sources. However, many sources of uncertainty in the air quality model including errors in emissions and meteorological inputs (particularly precipitation) and incomplete descriptions of the chemical and physical processes governing deposition can lead to bias and error in the simulation of WD. We present an approach to bias correct Community Multiscale Air Quality model output over the contiguous United States using observation-based gridded precipitation data generated by the Parameter-elevation Regressions on Independent Slopes Model and WD observations at the National Atmospheric Deposition Program National Trends Network sites. A cross-validation analysis shows that the adjusted annual accumulated WD for NO3 -, NH4 +, and SO4 2- from 2002 to 2012 has less bias and higher correlation with observed values than the base model output without adjustment. Temporal trends in observed WD are captured well by the adjusted model simulations across the entire contiguous United States. Consistent with previous trend analyses, WD NO3 - and SO4 2- are shown to decrease during this period in the eastern half of the United States, particularly in the Northeast, while remaining nearly constant in the West. Trends in WD of NH4 + are more spatially and temporally heterogeneous, with some positive trends in the Great Plains and Central Valley of CA and slightly negative trends in the south.

The impact of air pollutant deposition on solar energy system efficiency: An approach to estimate PV soiling effects with the Community Multiscale Air Quality (CMAQ) model

Deposition and accumulation of aerosol particles on photovoltaics (PV) panels, which is commonly referred to as "soiling of PV panels," impacts the performance of the PV energy system. It is desirable to estimate the soiling effect at different locations and times for modeling the PV system performance and devising cost-effective mitigation. This study presents an approach to estimate the soiling effect by utilizing particulate matter (PM) dry deposition estimates from air quality model simulations. The Community Multiscale Air Quality (CMAQ) modeling system used in this study was developed by the U.S. Environmental Protection Agency (U.S. EPA) for air quality assessments, rule-making, and research. Three deposition estimates based on different surface roughness length parameters assumed in CMAQ were used to illustrate the soling effect in different land-use types. The results were analyzed for three locations in the U.S. for year 2011. One urban and one suburban location in Colorado were selected because there have been field measurements of particle deposition on solar panels and analysis on the consequent soiling effect performed at these locations. The third location is a coastal city in Texas, the City of Brownsville. These three locations have distinct ambient environments. CMAQ underestimates particle deposition by 40% to 80% when compared to the field measurements at the two sites in Colorado due to the underestimations in both the ambient PM₁₀ concentration and deposition velocity. The estimated panel transmittance sensitivity due to the deposited particles is higher than the sensitivity obtained from the measurements in Colorado. The final soiling effect, which is transmittance loss, is estimated as 3.17 ± 4.20% for the Texas site, 0.45 ± 0.33%, and 0.31 ± 0.25% for the Colorado sites. Although the numbers are lower compared to the measurements in Colorado, the results are comparable with the soiling effects observed in U.S.

Spatial variation of modelled total, dry and wet nitrogen deposition to forests at global scale

Forests are an important biome that covers about one third of the global land surface and provides important ecosystem services. Since atmospheric deposition of nitrogen (N) can have both beneficial and deleterious effects, it is important to quantify the amount of N deposition to forest ecosystems. Measurements of N deposition to the numerous forest biomes across the globe are scarce, so chemical transport models are often used to provide estimates of atmospheric N inputs to these ecosystems. We provide an overview of approaches used to calculate N deposition in commonly used chemical transport models. The Task Force on Hemispheric Transport of Air Pollution (HTAP2) study intercompared N deposition values from a number of global chemical transport models. Using a multi-model mean calculated from the HTAP2 deposition values, we map N deposition to global forests to examine spatial variations in total, dry and wet deposition. Highest total N deposition occurs in eastern and southern China, Japan, Eastern U.S. and Europe while the highest dry deposition occurs in tropical forests. The European Monitoring and Evaluation Program (EMEP) model predicts grid-average deposition, but also produces deposition by land use type allowing us to compare deposition specifically to forests with the grid-average value. We found that, for this study, differences between the grid-average and forest specific could be as much as a factor of two and up to more than a factor of five in extreme cases. This suggests that consideration should be given to using forest-specific deposition for input to ecosystem assessments such as critical loads determinations.

Evaluation and Intercomparison of Five North American Dry Deposition Algorithms at a Mixed Forest Site

To quantify differences between dry deposition algorithms commonly used in North America, five models were selected to calculate dry deposition velocity (V _d) for O₃ and SO₂ over a temperate mixed forest in southern Ontario, Canada, where a 5-year flux database had previously been developed. The models performed better in summer than in winter with correlation coefficients for hourly V _d between models and measurements being approximately 0.6 and 0.3, respectively. Differences in mean V _d values between models were on the order of a factor of 2 in both summer and winter. All models produced lower V _d values than the measurements of O₃ in summer and SO₂ in summer and winter, although the measured V _d may be biased. There was not a consistent tendency in the models to overpredict or underpredict for O₃ in winter. Several models produced magnitudes of the diel variation of V _d (O₃) comparable to the measurements, while all models produced slightly smaller diel variations than the measurements of V _d (SO₂) in summer. A few models produced larger diel variations than the measurements of V _d for O₃ and SO₂ in winter. Model differences were mainly due to different surface resistance parameterizations for stomatal and nonstomatal uptake pathways, while differences in aerodynamic and quasi-laminar resistances played only a minor role. It is recommended to use ensemble modeling results for ecosystem impact assessment studies, which provides mean values of all the used models and thus can avoid too much overestimations or underestimations.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O₃) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM_2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O₃ mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM_2.5 bias (PM_2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O₃ and PM_2.5 on average in January and July. Overall, the seasonal variation in simulated PM_2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM_2.5 concentrations decrease in the winter (when PM_2.5 is generally overestimated by CMAQ) and increase in the summer (when PM_2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O₃ mean bias, as O₃ tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O₃ is low); however, O₃ correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO _x (NO + NO₂), VOC and SO _x (SO₂ + SO₄) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O₃ due to large, widespread reductions in observed emissions.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O₃) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM_2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O₃ mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM_2.5 bias (PM_2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O₃ and PM_2.5 on average in January and July. Overall, the seasonal variation in simulated PM_2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM_2.5 concentrations decrease in the winter (when PM_2.5 is generally overestimated by CMAQ) and increase in the summer (when PM_2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O₃ mean bias, as O₃ tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O₃ is low); however, O₃ correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO _x (NO + NO₂), VOC and SO _x (SO₂ + SO₄) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O₃ due to large, widespread reductions in observed emissions.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O₃) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM_2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O₃ mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM_2.5 bias (PM_2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O₃ and PM_2.5 on average in January and July. Overall, the seasonal variation in simulated PM_2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM_2.5 concentrations decrease in the winter (when PM_2.5 is generally overestimated by CMAQ) and increase in the summer (when PM_2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O₃ mean bias, as O₃ tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O₃ is low); however, O₃ correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO _x (NO + NO₂), VOC and SO _x (SO₂ + SO₄) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O₃ due to large, widespread reductions in observed emissions.

Description and evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.1

The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2.5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM2.5 bias (PM2.5 is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O3 and PM2.5 on average in January and July. Overall, the seasonal variation in simulated PM2.5 generally improves in CMAQv5.1 (when considering all model updates), as simulated PM2.5 concentrations decrease in the winter (when PM2.5 is generally overestimated by CMAQ) and increase in the summer (when PM2.5 is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O3 mean bias, as O3 tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O3 is low); however, O3 correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO x (NO + NO2), VOC and SO x (SO2 + SO4) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O3 due to large, widespread reductions in observed emissions.

Modeling the Current and Future Roles of Particulate Organic Nitrates in the Southeastern United States

Organic nitrates are an important aerosol constituent in locations where biogenic hydrocarbon emissions mix with anthropogenic NOx sources. While regional and global chemical transport models may include a representation of organic aerosol from monoterpene reactions with nitrate radicals (the primary source of particle-phase organic nitrates in the Southeast United States), secondary organic aerosol (SOA) models can underestimate yields. Furthermore, SOA parametrizations do not explicitly take into account organic nitrate compounds produced in the gas phase. In this work, we developed a coupled gas and aerosol system to describe the formation and subsequent aerosol-phase partitioning of organic nitrates from isoprene and monoterpenes with a focus on the Southeast United States. The concentrations of organic aerosol and gas-phase organic nitrates were improved when particulate organic nitrates were assumed to undergo rapid (τ = 3 h) pseudohydrolysis resulting in nitric acid and nonvolatile secondary organic aerosol. In addition, up to 60% of less oxidized-oxygenated organic aerosol (LO-OOA) could be accounted for via organic nitrate mediated chemistry during the Southern Oxidants and Aerosol Study (SOAS). A 25% reduction in nitrogen oxide (NO + NO2) emissions was predicted to cause a 9% reduction in organic aerosol for June 2013 SOAS conditions at Centreville, Alabama.

Sensitivity of continental United States atmospheric budgets of oxidized and reduced nitrogen to dry deposition parametrizations

Reactive nitrogen (Nr) is removed by surface fluxes (air-surface exchange) and wet deposition. The chemistry and physics of the atmosphere result in a complicated system in which competing chemical sources and sinks exist and impact that removal. Therefore, uncertainties are best examined with complete regional chemical transport models that simulate these feedbacks. We analysed several uncertainties in regional air quality model resistance analogue representations of air-surface exchange for unidirectional and bi-directional fluxes and their effect on the continental Nr budget. Model sensitivity tests of key parameters in dry deposition formulations showed that uncertainty estimates of continental total nitrogen deposition are surprisingly small, 5 per cent or less, owing to feedbacks in the chemistry and rebalancing among removal pathways. The largest uncertainties (5%) occur with the change from a unidirectional to a bi-directional NH3 formulation followed by uncertainties in bi-directional compensation points (1-4%) and unidirectional aerodynamic resistance (2%). Uncertainties have a greater effect at the local scale. Between unidirectional and bi-directional formulations, single grid cell changes can be up to 50 per cent, whereas 84 per cent of the cells have changes less than 30 per cent. For uncertainties within either formulation, single grid cell change can be up to 20 per cent, but for 90 per cent of the cells changes are less than 10 per cent.

Application of watershed deposition tool to estimate from CMAQ simulations the atmospheric deposition of nitrogen to Tampa Bay and its watershed

The US. Environmental Protection Agency (EPA) has developed the Watershed Deposition Tool (WDT) to calculate from the Community Multiscale Air Quality (CMAQ) model output the nitrogen, sulfur and mercury deposition rates to watersheds and their sub-basins. The CMAQ model simulates from first principles the transport, transformation, and removal of atmospheric pollutants. We applied WDT to estimate the atmospheric deposition of reactive nitrogen (N) to Tampa Bay and its watershed. For 2002 and within the boundaries of Tampa Bay's watershed, modeled atmospheric deposition rates averaged 13.3 kg N ha(-1) yr(-1) and ranged from 6.24 kg N ha(-1) yr(-1) at the bay's boundary with Gulf of Mexico to 21.4 kg N ha(-1) yr(-1) near Tampa's urban core, based on a 12-km x 12-km grid cell size. CMAQ-predicted loading rates were 1,080 metric tons N yr(-1) to Tampa Bay and 8,280 metric tons N yr(-1) to the land portion of its watershed. If we assume a watershed-to-bay transfer rate of 18% for indirect loading, our estimates of the 2002 direct and indirect loading rates to Tampa Bay were 1,080 metric tons N and 1,490 metric tons N, respectively, for an atmospheric loading of 2,570 metric tons N or 71% of the total N loading to Tampa Bay. To evaluate the potential impact of the US. EPA Clean Air Interstate Rule (CAIR, replaced with Cross-State Air Pollution Rule), Tier 2 Vehicle and Gasoline Sulfur Rules, Heavy Duty Highway Rule, and Non-Road Diesel Rule, we compared CMAQ outputs between 2020 and 2002 simulations, with only the emissions inventories changed. The CMAQ-projected change in atmospheric loading rates between these emissions inventories was 857 metric tons N to Tampa Bay, or about 24% of the 2002 loading of 3,640 metric tons N to Tampa Bay from all sources.

IMPLICATIONS

Air quality modeling reveals that atmospheric deposition of reactive nitrogen (N) contributes a significant fraction to Tampa Bay's total N loading from external sources. Regulatory drivers that lower nitrogen oxide emissions from power plants and motor vehicles are important to bay management strategies, which seek to improve water quality through N load reduction.