New Bidirectional Ammonia Flux Model in an Air Quality Model Coupled With an Agricultural Model

Modeling the Oxygen Isotope Anomaly (Δ17O) of Reactive Nitrogen in the Community Multiscale Air Quality Model: Insights into Nitrogen Oxide Chemistry in the Northeastern United States

Atmospheric nitrate, including nitric acid (HNO3), particulate nitrate (pNO3), and organic nitrate (RONO2), is a key atmosphere component with implications for air quality, nutrient deposition, and climate. However, accurately representing atmospheric nitrate concentrations within atmospheric chemistry models is a persistent challenge. A contributing factor to this challenge is the intricate chemical transformations involving HNO3 formation, which can be difficult for models to replicate. Here, we present a novel model framework that utilizes the oxygen stable isotope anomaly (Δ17O) to quantitatively depict ozone (O3) involvement in precursor nitrogen oxidesN O x = N O + N O 2 photochemical cycling and HNO3 formation. This framework has been integrated into the US EPA Community Multiscale Air Quality (CMAQ) modeling system to facilitate a comprehensive assessment of NO x oxidation and HNO3 formation. In application across the northeastern US, the model Δ17O compares well with recently conducted diurnal Δ17O(NO2) and spatiotemporal Δ17O(HNO3) observations, with a root mean square error between model and observations of 2.6 ‰ for Δ17O(HNO3). The model indicates the major formation pathways of annual HNO3 production within the northeastern US are NO+OH (46 %), N2O5 hydrolysis (34 %), and organic nitrate hydrolysis (12 %). This model can evaluate NO x chemistry in CMAQ in future air quality and deposition studies involving reactive nitrogen.

Impacts assessment of nitrification inhibitors on U.S. agricultural emissions of reactive nitrogen gases

Fertilizer-intensive agriculture leads to emissions of reactive nitrogen (Nr), posing threats to climate via nitrous oxide (N2O) and to air quality and human health via nitric oxide (NO) and ammonia (NH3) that form ozone and particulate matter (PM) downwind. Adding nitrification inhibitors (NIs) to fertilizers can mitigate N2O and NO emissions but may stimulate NH3 emissions. Quantifying the net effects of these trade-offs requires spatially resolving changes in emissions and associated impacts. We introduce an assessment framework to quantify such trade-off effects. It deploys an agroecosystem model with enhanced capabilities to predict emissions of Nr with or without the use of NIs, and a social cost of greenhouse gas to monetize the impacts of N2O on climate. The framework also incorporates reduced-complexity air quality and health models to monetize associated impacts of NO and NH3 emissions on human health downwind via ozone and PM. Evaluation of our model against available field measurements showed that it captured the direction of emission changes but underestimated reductions in N2O and overestimated increases in NH3 emissions. The model estimated that, averaged over applicable U.S. agricultural soils, NIs could reduce N2O and NO emissions by an average of 11% and 16%, respectively, while stimulating NH3 emissions by 87%. Impacts are largest in regions with moderate soil temperatures and occur mostly within two to three months of N fertilizer and NI application. An alternative estimate of NI-induced emission changes was obtained by multiplying the baseline emissions from the agroecosystem model by the reported relative changes in Nr emissions suggested from a global meta-analysis: -44% for N2O, -24% for NO and +20% for NH3. Monetized assessments indicate that on an annual scale, NI-induced harms from increased NH3 emissions outweigh (8.5-33.8 times) the benefits of reducing NO and N2O emissions in all agricultural regions, according to model-based estimates. Even under meta-analysis-based estimates, NI-induced damages exceed benefits by a factor of 1.1-4. Our study highlights the importance of considering multiple pollutants when assessing NIs, and underscores the need to mitigate NH3 emissions. Further field studies are needed to evaluate the robustness of multi-pollutant assessments.

Bokashi fermentation of brewery's spent grains positively affects larval performance of the black soldier fly Hermetia illucens while reducing gaseous nitrogen losses

Digestion of waste feedstocks by larvae of the black soldier fly Hermetia illucens (Diptera: Stratiomyidae) (BSF) results in proteins for animal feed and organic fertilizer with a reduced environmental footprint, but it can still have negative environmental effects through greenhouse gas (GHG) and ammonia (NH3) emissions. Both biomass conversion by BSF larvae and associated GHG and NH3 emissions can depend on substrate properties that may be optimized through microbial inoculation pre-treatments, such as bokashi fermentation. Here, we quantified the effects of bokashi fermentation of brewery's spent grains on BSF rearing metrics and associated GHG and NH3 emissions at benchtop scale. We found that bokashi fermentation increased larval biomass by 40% and shortened development time by over two days on average, compared with unfermented spent grains. In line with increased larval growth, CO2 emissions in BSF larvae treatments were 31.0 and 79.0% higher in the bokashi fermented spent grains and Gainesville substrates, respectively, compared to the unfermented spent grains. Adding BSF larvae to the spent grains increased cumulative N2O emissions up to 64.0 mg N2O kg substratedry-1 but there were essentially no N2O emissions when larvae were added to fermented spent grains. Bokashi fermentation also reduced NH3 fluxes from the volatilization of substrate nitrogen in the BSF larvae treatment by 83.7-85.8% during days 7 and 9, possibly by increasing N assimilation by larvae or by reducing the transformation of substrate NH4+ to NH3. Therefore, bokashi fermentation may be applied to improve performance of BSF larvae on a common industrial waste stream and reduce associated emissions.

Anthropogenic Secondary Organic Aerosol and Ozone Production from Asphalt-Related Emissions

Liquid asphalt is a petroleum-derived substance commonly used in construction activities. Recent work has identified lower volatility, reactive organic carbon from asphalt as an overlooked source of secondary organic aerosol (SOA) precursor emissions. Here, we leverage potential emission estimates and usage data to construct a bottom-up inventory of asphalt-related emissions in the United States. In 2018, we estimate that hot-mix, warm-mix, emulsified, cutback, and roofing asphalt generated ~380 Gg (317 Gg - 447 Gg) of organic compound emissions. The impacts of these emissions on anthropogenic SOA and ozone throughout the contiguous United States are estimated using photochemical modeling. In several major cities, asphalt-related emissions can increase modeled summertime SOA, on average, by 0.1 - 0.2 μg m-3 (2-4% of SOA) and may reach up to 0.5 μg m-3 at noontime on select days. The influence of asphalt-related emissions on modeled ozone are generally small (~0.1 ppb). We estimate that asphalt paving-related emissions are half of what they were nearly 50 years ago, largely due to the concerted efforts to reduce emissions from cutback asphalts. If on-road mobile emissions continue their multidecadal decline, contributions of urban SOA from evaporative and non-road mobile sources will continue to grow in relative importance.

Dry Deposition Methods Based on Turbulence Kinetic Energy: Part 1. Evaluation of Various Resistances and Sensitivity Studies Using a Single-Point Model

Different functions are used to account for turbulence strength in the atmospheric boundary layer for different stability regimes. These functions are one of the sources for differences among different atmospheric models' predictions and associated biases. Also, turbulence strength is underrepresented in some of the resistance formulations. To address these issues with dry deposition, firstly we take advantage of three-dimensional (3-D) turbulence information in estimating resistances by proposing and validating a 3-D turbulence velocity scale that is relevant for different stability regimes of boundary layer. Secondly, we hypothesize and validate that friction velocity measured by 3-D sonic anemometer can be effectively replaced by the new turbulence velocity scale multiplied by the von Karman constant. Finally, we (1) present a set of resistance formulations for ozone (O3) based on the 3-D turbulence velocity scale; (2) intercompare estimations of such resistances with those obtained using existing formulations; and, (3) evaluate simulated O3 fluxes using a single-point dry deposition model against long-term observations of O3 fluxes at the Harvard Forest (MA) site. Results indicate that the new resistance formulations work very well in simulating surface latent heat and O3 fluxes when compared to respective existing formulations and measurements at a decadal time scale. Findings from this research may help to improve the capability of dry deposition schemes for better estimation of dry deposition fluxes and create opportunities for the development of a community dry deposition model for use in regional/global air quality models.

Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate

Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NO_x), ammonia (NH₃), and nitrous oxide (N₂O). The propensity of NO_x and NH₃ to generate ozone and fine particulate matter and associated impacts on health are highly variable, whereas the climate impacts of long-lived N₂O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially resolved monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the Nr emissions from fertilized soils across the contiguous United States. We then apply a reduced-form air pollution health effect model to assess air quality impacts from NO_x and NH₃ and a social cost of N₂O to assess the climate impacts. Assuming an $8.2 million value of a statistical life and a $13,100/ton social cost of N₂O, the air quality impacts are a factor of ∼7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.

Volatile Chemical Product Enhancements to Criteria Pollutants in the United States

Volatile chemical products (VCPs) are a significant source of reactive organic carbon emissions in the United States with a substantial fraction (>20% by mass) serving as secondary organic aerosol (SOA) precursors. Here, we incorporate a new nationwide VCP inventory into the Community Multiscale Air Quality (CMAQ) model with VCP-specific updates to better model air quality impacts. Model results indicate that VCPs mostly enhance anthropogenic SOA in densely populated areas with population-weighted annual average SOA increasing 15-30% in Southern California and New York City due to VCP emissions (contribution of 0.2-0.5 μg m^-3). Annually, VCP emissions enhance total population-weighted PM_2.5 by ∼5% in California, ∼3% in New York, New Jersey, and Connecticut, and 1-2% in most other states. While the maximum daily 8 h ozone enhancements from VCP emissions are more modest, their influence can cause a several ppb increase on select days in major cities. Printing Inks, Cleaning Products, and Paints and Coatings product use categories contribute ∼75% to the modeled VCP-derived SOA and Cleaning Products, Paints and Coatings, and Personal Care Products contribute ∼81% to the modeled VCP-derived ozone. Overall, VCPs enhance multiple criteria pollutants throughout the United States with the largest impacts in urban cores.

4D-Var Inversion of European NH3 Emissions Using CrIS NH3 Measurements and GEOS-Chem Adjoint With Bi-Directional and Uni-Directional Flux Schemes

We conduct the first 4D-Var inversion of NH₃ accounting for NH₃ bi-directional flux, using CrIS satellite NH₃ observations over Europe in 2016. We find posterior NH₃ emissions peak more in springtime than prior emissions at continental to national scales, and annually they are generally smaller than the prior emissions over central Europe, but larger over most of the rest of Europe. Annual posterior anthropogenic NH₃ emissions for 25 European Union members (EU25) are 25% higher than the prior emissions and very close (<2% difference) to other inventories. Our posterior annual anthropogenic emissions for EU25, the UK, the Netherlands, and Switzerland are generally 10%-20% smaller than when treating NH₃ fluxes as uni-directional emissions, while the monthly regional difference can be up to 34% (Switzerland in July). Compared to monthly mean in-situ observations, our posterior NH₃ emissions from both schemes generally improve the magnitude and seasonality of simulated surface NH₃ and bulk NH _x wet deposition throughout most of Europe, whereas evaluation against hourly measurements at a background site shows the bi-directional scheme better captures observed diurnal variability of surface NH₃. This contrast highlights the need for accurately simulating diurnal variability of NH₃ in assimilation of sun-synchronous observations and also the potential value of future geostationary satellite observations. Overall, our top-down ammonia emissions can help to examine the effectiveness of air pollution control policies to facilitate future air pollution management, as well as helping us understand the uncertainty in top-down NH₃ emissions estimates associated with treatment of NH₃ surface exchange.

Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16

A new dynamical core, known as the Finite-Volume Cubed-Sphere (FV3) and developed at both NASA and NOAA, is used in NOAA's Global Forecast System (GFS) and in limited-area models for regional weather and air quality applications. NOAA has also upgraded the operational FV3GFS to version 16 (GFSv16), which includes a number of significant developmental advances to the model configuration, data assimilation, and underlying model physics, particularly for atmospheric composition to weather feedback. Concurrent with the GFSv16 upgrade, we couple the GFSv16 with the Community Multiscale Air Quality (CMAQ) model to form an advanced version of the National Air Quality Forecasting Capability (NAQFC) that will continue to protect human and ecosystem health in the US. Here we describe the development of the FV3GFSv16 coupling with a "state-of-the-science" CMAQ model version 5.3.1. The GFS-CMAQ coupling is made possible by the seminal version of the NOAA-EPA Atmosphere-Chemistry Coupler (NACC), which became a major piece of the next operational NAQFC system (i.e., NACC-CMAQ) on 20 July 2021. NACC-CMAQ has a number of scientific advancements that include satellite-based data acquisition technology to improve land cover and soil characteristics and inline wildfire smoke and dust predictions that are vital to predictions of fine particulate matter (PM_2.5) concentrations during hazardous events affecting society, ecosystems, and human health. The GFS-driven NACC-CMAQ model has significantly different meteorological and chemical predictions compared to the previous operational NAQFC, where evaluation of NACC-CMAQ shows generally improved near-surface ozone and PM_2.5 predictions and diurnal patterns, both of which are extended to a 72 h (3 d) forecast with this system.

Technical note: AQMEII4 Activity 1: evaluation of wet and dry deposition schemes as an integral part of regional-scale air quality models

We present in this technical note the research protocol for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This research initiative is divided into two activities, collectively having three goals: (i) to define the current state of the science with respect to representations of wet and especially dry deposition in regional models, (ii) to quantify the extent to which different dry deposition parameterizations influence retrospective air pollutant concentration and flux predictions, and (iii) to identify, through the use of a common set of detailed diagnostics, sensitivity simulations, model evaluation, and reduction of input uncertainty, the specific causes for the current range of these predictions. Activity 1 is dedicated to the diagnostic evaluation of wet and dry deposition processes in regional air quality models (described in this paper), and Activity 2 to the evaluation of dry deposition point models against ozone flux measurements at multiple towers with multiyear observations (to be described in future submissions as part of the special issue on AQMEII4). The scope of this paper is to present the scientific protocols for Activity 1, as well as to summarize the technical information associated with the different dry deposition approaches used by the participating research groups of AQMEII4. In addition to describing all common aspects and data used for this multi-model evaluation activity, most importantly, we present the strategy devised to allow a common process-level comparison of dry deposition obtained from models using sometimes very different dry deposition schemes. The strategy is based on adding detailed diagnostics to the algorithms used in the dry deposition modules of existing regional air quality models, in particular archiving diagnostics specific to land use-land cover (LULC) and creating standardized LULC categories to facilitate cross-comparison of LULC-specific dry deposition parameters and processes, as well as archiving effective conductance and effective flux as means for comparing the relative influence of different pathways towards the net or total dry deposition. This new approach, along with an analysis of precipitation and wet deposition fields, will provide an unprecedented process-oriented comparison of deposition in regional air quality models. Examples of how specific dry deposition schemes used in participating models have been reduced to the common set of comparable diagnostics defined for AQMEII4 are also presented.

Evaluation of the offline-coupled GFSv15-FV3-CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States

As a candidate for the next-generation National Air Quality Forecast Capability (NAQFC), the meteorological forecast from the Global Forecast System with the new Finite Volume Cube-Sphere dynamical core (GFS-FV3) will be applied to drive the chemical evolution of gases and particles described by the Community Multiscale Air Quality modeling system. CMAQv5.0.2, a historical version of CMAQ, has been coupled with the North American Mesoscale Forecast System (NAM) model in the current operational NAQFC. An experimental version of the NAQFC based on the offline-coupled GFS-FV3 version 15 with CMAQv5.0.2 modeling system (GFSv15-CMAQv5.0.2) has been developed by the National Oceanic and Atmospheric Administration (NOAA) to provide real-time air quality forecasts over the contiguous United States (CONUS) since 2018. In this work, comprehensive region-specific, time-specific, and categorical evaluations are conducted for meteorological and chemical forecasts from the offline-coupled GFSv15-CMAQv5.0.2 for the year 2019. The forecast system shows good overall performance in forecasting meteorological variables with the annual mean biases of -0.2 °C for temperature at 2 m, 0.4% for relative humidity at 2 m, and 0.4 m s-1 for wind speed at 10 m compared to the METeorological Aerodrome Reports (METAR) dataset. Larger biases occur in seasonal and monthly mean forecasts, particularly in spring. Although the monthly accumulated precipitation forecasts show generally consistent spatial distributions with those from the remote-sensing and ensemble datasets, moderate-to-large biases exist in hourly precipitation forecasts compared to the Clean Air Status and Trends Network (CASTNET) and METAR. While the forecast system performs well in forecasting ozone (O3) throughout the year and fine particles with a diameter of 2.5 μm or less (PM2.5) for warm months (May-September), it significantly overpredicts annual mean concentrations of PM2.5. This is due mainly to the high predicted concentrations of fine fugitive and coarse-mode particle components. Underpredictions in the southeastern US and California during summer are attributed to missing sources and mechanisms of secondary organic aerosol formation from biogenic volatile organic compounds (VOCs) and semivolatile or intermediate-volatility organic compounds. This work demonstrates the ability of FV3-based GFS in driving the air quality forecasting. It identifies possible underlying causes for systematic region- and time-specific model biases, which will provide a scientific basis for further development of the next-generation NAQFC.

Ammonia Dry Deposition in an Alpine Ecosystem Traced to Agricultural Emission Hotpots

Elevated reactive nitrogen (N_r) deposition is a concern for alpine ecosystems, and dry NH₃ deposition is a key contributor. Understanding how emission hotspots impact downwind ecosystems through dry NH₃ deposition provides opportunities for effective mitigation. However, direct NH₃ flux measurements with sufficient temporal resolution to quantify such events are rare. Here, we measured NH₃ fluxes at Rocky Mountain National Park (RMNP) during two summers and analyzed transport events from upwind agricultural and urban sources in northeastern Colorado. We deployed open-path NH₃ sensors on a mobile laboratory and an eddy covariance tower to measure NH₃ concentrations and fluxes. Our spatial sampling illustrated an upslope event that transported NH₃ emissions from the hotspot to RMNP. Observed NH₃ deposition was significantly higher when backtrajectories passed through only the agricultural region (7.9 ng m^-2 s^-1) versus only the urban area (1.0 ng m^-2 s^-1) and both urban and agricultural areas (2.7 ng m^-2 s^-1). Cumulative NH₃ fluxes were calculated using observed, bidirectional modeled, and gap-filled fluxes. More than 40% of the total dry NH₃ deposition occurred when air masses were traced back to agricultural source regions. More generally, we identified that 10 (25) more national parks in the U.S. are within 100 (200) km of an NH₃ hotspot, and more observations are needed to quantify the impacts of these hotspots on dry NH₃ deposition in these regions.

Establishing the Suitability of the Model for Prediction Across Scales for Global Retrospective Air Quality Modeling

The U.S. EPA is leveraging recent advances in meteorological modeling to construct an air quality modeling system to allow consistency from global to local scales. The Model for Prediction Across Scales-Atmosphere (MPAS-A or MPAS) has been developed by the National Center for Atmospheric Research (NCAR) as a global complement to the Weather Research and Forecasting model (WRF). Patterned after a regional coupled system with WRF, the Community Multiscale Air Quality (CMAQ) modeling system has been coupled within MPAS to explore global-to-local chemical transport modeling. Several options were implemented into MPAS for retrospective applications. Nudging-based data assimilation was added to support continuous simulations of past weather to minimize error growth that exists with a weather forecast configuration. The Pleim-Xiu land-surface model, the Asymmetric Convective Model 2 boundary layer scheme, and the Pleim surface layer scheme were added as the preferred options for retrospective air quality applications with WRF. Annual simulations were conducted using this EPA-enhanced MPAS configuration on two different mesh structures and compared against WRF. MPAS generally compares well with WRF over the conterminous United States. Errors in MPAS surface meteorology are comparable to WRF throughout the year. Precipitation statistics indicate MPAS performs slightly better than WRF. Solar radiation in MPAS is higher than WRF and measurements, suggesting fewer clouds in MPAS than WRF. Upper-air meteorology is well-simulated by MPAS, but errors are slightly higher than WRF. These comparisons lend confidence to use MPAS for retrospective air quality modeling and suggest ways it can be further improved in the future.

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.

The contribution of wildland fire emissions to deposition in the U S: implications for tree growth and survival in the Northwest

Ecosystems require access to key nutrients like nitrogen (N) and sulfur (S) to sustain growth and healthy function. However, excessive deposition can also damage ecosystems through nutrient imbalances, leading to changes in productivity and shifts in ecosystem structure. While wildland fires are a known source of atmospheric N and S, little has been done to examine the implications of wildland fire deposition for vulnerable ecosystems. We combine wildland fire emission estimates, atmospheric chemistry modeling, and forest inventory data to (a) quantify the contribution of wildland fire emissions to N and S deposition across the U S, and (b) assess the subsequent impacts on tree growth and survival rates in areas where impacts are likely meaningful based on the relative contribution of fire to total deposition. We estimate that wildland fires contributed 0.2 kg N ha-1 yr-1 and 0.04 kg S ha-1 yr-1 on average across the U S during 2008-2012, with maxima up to 1.4 kg N ha-1 yr-1 and 0.6 kg S ha-1 yr-1 in the Northwest representing over ~30% of total deposition in some areas. Based on these fluxes, exceedances of S critical loads as a result of wildland fires are minimal, but exceedances for N may affect the survival and growth rates of 16 tree species across 4.2 million hectares, with the most concentrated impacts occurring in Oregon, northern California, and Idaho. Understanding the broader environmental impacts of wildland fires in the U S will inform future decision making related to both fire management and ecosystem services conservation.

Ammonia emission abatement does not fully control reduced forms of nitrogen deposition

Human activities and population growth have increased the natural burden of reactive nitrogen (N) in the environment. Excessive N deposition on Earth's surface leads to adverse feedbacks on ecosystems and humans. Similar to that of air pollution, emission control is recognized as an efficient means to control acid deposition. Control of nitrogen oxides (NOx = NO + NO2) emissions has led to reduction in deposition of oxidized nitrogen (NOy, the sum of all oxidized nitrogen species, except nitrous oxide [N2O]). Reduced forms of nitrogen (NHx = ammonia [NH3] + ammonium [NH4+]) deposition have, otherwise, increased, offsetting the benefit of reduction in NOy deposition. Stringent control of NH3 emissions is being considered. In this study, we assess the response of N deposition to N emission control on continental regions. We show that significant reduction of NHx deposition is unlikely to be achieved at the early stages of implementing NH3 emission abatement. Per-unit NH3 emission abatement is shown to result in only 60-80% reduction in NHx deposition, which is significantly lower than the demonstrated 80-120% benefit of controlling NOx emissions on NOy deposition. This 60-80% effectiveness of NHx deposition reduction per unit NH3 emission abatement reflects, in part, the effects of simultaneous reductions in NOx and SO2 emissions.

An Integrated Agriculture, Atmosphere, and Hydrology Modeling System for Ecosystem Assessments

We present a regional-scale integrated modeling system (IMS) that includes Environmental Policy Integrated Climate (EPIC), Weather Research and Forecast (WRF), Community Multiscale Air Quality (CMAQ), and Soil and Water Assessment Tool (SWAT) models. The centerpiece of the IMS is the Fertilizer Emission Scenario Tool for CMAQ (FEST-C), which includes a Java-based interface and EPIC adapted to regional applications along with built-in database and tools. The SWAT integration capability is a key enhanced feature in the current release of FEST-C v1.4. For integrated modeling demonstration and evaluation, FEST-C EPIC is simulated over three individual years with WRF/CMAQ weather and N deposition. Simulated yearly changes in water and N budgets along with yields for two major crops (corn grain and soybean) match those inferred from intuitive physical reasoning and survey data given different-year weather conditions. Yearlong air quality simulations with an improved bidirectional ammonia flux modeling approach directly using EPIC-simulated soil properties including NH₃ content helps reduce biases of simulated gas-phase NH₃ and NH₄ ⁺ wet deposition over the growing season. Integrated hydrology and water quality simulations applied to the Mississippi River Basin show that estimated monthly streamflow and dissolved N near the outlet to the Gulf of Mexico display similar seasonal patterns as observed. Limitations and issues in different parts of the integrated multimedia simulations are identified and discussed to target areas for future improvements.

PLAIN LANGUAGE SUMMARY

Computer modeling tools with land-water-air processes are important for understanding nutrient cycling and its negative impacts on air and water quality. We have developed an integrated modeling system that includes agriculture, atmosphere, and hydrology components. The centerpiece of the system is a computer system that includes an agricultural ecosystem model and tools used to connect different modeling components. The agricultural system can conduct simulations for 42 types of grassland and cropland with the influence of site, soil, and management information along with weather and nitrogen deposition from the atmosphere component. An air quality computer model then uses information from the agricultural model, such as how much ammonia is in the soil, to predict how much ammonia gets in the air. Then, the watershed hydrology and water quality model uses the information from the agricultural and atmospheric models to understand the influence of agriculture and atmosphere on water quality. The paper demonstrates and evaluates the integrated modeling system on issues mainly related to N cycling. The system performs reasonably well in comparison with survey and observation data given the configured modeling constraints. The paper also identifies and discusses the advantages and limitations in each part of the system for future applications and improvements.