Investigation of effects of varying model inputs on mercury deposition estimates in the Southwest US

The Community Multiscale Air Quality (CMAQ) model version 4.7.1 was used to simulate mercury wet and dry deposition for a domain covering the continental United States (US). The simulations used MM5-derived meteorological input fields and the US Environmental Protection Agency (EPA) Clear Air Mercury Rule (CAMR) emissions inventory. Using sensitivity simulations with different boundary conditions and tracer simulations, this investigation focuses on the contributions of boundary concentrations to deposited mercury in the Southwest (SW) US. Concentrations of oxidized mercury species along the boundaries of the domain, in particular the upper layers of the domain, can make significant contributions to the simulated wet and dry deposition of mercury in the SW US. In order to better understand the contributions of boundary conditions to deposition, inert tracer simulations were conducted to quantify the relative amount of an atmospheric constituent transported across the boundaries of the domain at various altitudes and to quantify the amount that reaches and potentially deposits to the land surface in the SW US. Simulations using alternate sets of boundary concentrations, including estimates from global models (Goddard Earth Observing System-Chem (GEOS-Chem) and the Global/Regional Atmospheric Heavy Metals (GRAHM) model), and alternate meteorological input fields (for different years) are analyzed in this paper. CMAQ dry deposition in the SW US is sensitive to differences in the atmospheric dynamics and atmospheric mercury chemistry parameterizations between the global models used for boundary conditions

Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments

While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH3) emissions which result from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-driven fertilizer applications to commercial cropland throughout the continental US. This information is coupled with a process-based air quality model to produce continental-scale NH3 emission estimates. Regional cropland NH3 emissions are driven by the timing and amount of inorganic NH3 fertilizer applied, soil processes, local meteorology, and ambient air concentrations. Initial fertilizer application often occurs when crops are planted. A state-level evaluation of EPIC-simulated, cumulative planted area compares well with similar USDA reported estimates. EPIC-annual, inorganic fertilizer application amounts also agree well with reported spatial patterns produced by others, but domain-wide the EPIC values are biased about 6% low. Preliminary application of the integrated fertilizer application and air quality modeling system produces a modified geospatial pattern of seasonal NH3 emissions that improves current simulations of observed atmospheric particle nitrate concentrations. This modeling framework provides a more dynamic, flexible, and spatially and temporally resolved estimate of NH3 emissions than previous factor-based NH3 inventories, and will facilitate evaluation of alternative nitrogen and air quality policy and adaptation strategies associated with future climate and land use changes

Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments

While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH<sub>3</sub>) emissions which result from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-driven fertilizer applications to commercial cropland throughout the continental US. This information is coupled with a process-based air quality model to produce continental-scale NH<sub>3</sub> emission estimates. Regional cropland NH<sub>3</sub> emissions are driven by the timing and amount of inorganic NH<sub>3</sub> fertilizer applied, soil processes, local meteorology, and ambient air concentrations. Initial fertilizer application often occurs when crops are planted. A state-level evaluation of EPIC-simulated, cumulative planted area compares well with similar USDA reported estimates. EPIC-annual, inorganic fertilizer application amounts also agree well with reported spatial patterns produced by others, but domain-wide the EPIC values are biased about 6% low. Preliminary application of the integrated fertilizer application and air quality modeling system produces a modified geospatial pattern of seasonal NH<sub>3</sub> emissions that improves current simulations of observed atmospheric particle nitrate concentrations. This modeling framework provides a more dynamic, flexible, and spatially and temporally resolved estimate of NH<sub>3</sub> emissions than previous factor-based NH<sub>3</sub> inventories, and will facilitate evaluation of alternative nitrogen and air quality policy and adaptation strategies associated with future climate and land use changes

Linking agricultural crop management and air quality models for regional to national-scale nitrogen assessments

While nitrogen (N) is an essential element for life, human population growth and demands for energy, transportation and food can lead to excess nitrogen in the environment. A modeling framework is described and implemented to promote a more integrated, process-based and system-level approach to the estimation of ammonia (NH<sub>3</sub>) emissions which result from the application of inorganic nitrogen fertilizers to agricultural soils in the United States. The United States Department of Agriculture (USDA) Environmental Policy Integrated Climate (EPIC) model is used to simulate plant demand-driven fertilizer applications to commercial cropland throughout the continental US. This information is coupled with a process-based air quality model to produce continental-scale NH<sub>3</sub> emission estimates. Regional cropland NH<sub>3</sub> emissions are driven by the timing and amount of inorganic NH<sub>3</sub> fertilizer applied, soil processes, local meteorology, and ambient air concentrations. Initial fertilizer application often occurs when crops are planted. A state-level evaluation of EPIC-simulated, cumulative planted area compares well with similar USDA reported estimates. EPIC-annual, inorganic fertilizer application amounts also agree well with reported spatial patterns produced by others, but domain-wide the EPIC values are biased about 6% low. Preliminary application of the integrated fertilizer application and air quality modeling system produces a modified geospatial pattern of seasonal NH<sub>3</sub> emissions that improves current simulations of observed atmospheric particle nitrate concentrations. This modeling framework provides a more dynamic, flexible, and spatially and temporally resolved estimate of NH<sub>3</sub> emissions than previous factor-based NH<sub>3</sub> inventories, and will facilitate evaluation of alternative nitrogen and air quality policy and adaptation strategies associated with future climate and land use changes

Ammonia Emissions in the United States, European Union, and China Derived by High-Resolution Inversion of Ammonium Wet Deposition Data: Interpretation with a New Agricultural Emissions Inventory (MASAGE_NH3)

We use the adjoint of a global 3-D chemical transport model (GEOS-Chem) to optimize ammonia $(NH_3)$ emissions in the U.S., European Union, and China by inversion of 2005–2008 network data for $NH^+_4$ wet deposition fluxes. Optimized emissions are derived on a 2° × 2.5° grid for individual months and years. Error characterization in the optimization includes model errors in precipitation. Annual optimized emissions are $2.8 Tg NH_3−N a^{−1}$ for the contiguous U.S., $3.1 Tg NH_3−N a^{−1}$ for the European Union, and $8.4 Tg NH_3−N a^{−1}$ for China. Comparisons to previous inventories for the U.S. and European Union show consistency $(\sim \pm 15$ in annual totals but some large spatial and seasonal differences. We develop a new global bottom-up inventory of $NH_3$ emissions (Magnitude And Seasonality of Agricultural Emissions model for NH3 (MASAGE_NH3)) to interpret the results of the adjoint optimization. MASAGE_NH3 provides information on the magnitude and seasonality of $NH_3$ emissions from individual crop and livestock sources on a 0.5° × 0.5° grid. We find that U.S. emissions peak in the spring in the Midwest due to corn fertilization and in the summer elsewhere due to manure. The seasonality of European emissions is more homogeneous with a well-defined maximum in spring associated with manure and mineral fertilizer application. There is some evidence for the effect of European regulations of $NH_3$ emissions, notably a large fall decrease in northern Europe. Emissions in China peak in summer because of the summertime application of fertilizer for double cropping.Engineering and Applied Science

Projections of Atmospheric Nitrogen Deposition to the Chesapeake Bay Watershed

Atmospheric deposition is among the largest pathways of nitrogen loading to the Chesapeake Bay Watershed (CBW). The interplay between future climate and emission changes in and around the CBW will likely shift the future nutrient deposition abundance and chemical regime (e.g., oxidized vs. reduced nitrogen). In this work, a Representative Concentration Pathway from the Community Earth System Model is dynamically downscaled using a recently updated Weather Research and Forecasting model that subsequently drives the Community Multiscale Air Quality model coupled to the agroeconomic Environmental Policy Integrated Climate model. The relative impacts of emission and climate changes on atmospheric nutrient deposition are explored for a recent historical period and a period centered on 2050. The projected regional emissions in Community Multiscale Air Quality reflect current federal and state regulations, which use baseline and projected emission years 2011 and 2040, respectively. The historical simulations of 2-m temperature (T2) and precipitation (PRECIP) have cool and dry biases, and temperature and PRECIP are projected to both increase. Ammonium wet deposition agrees well with observations, but nitrate wet deposition is underpredicted. Climate and deposition changes increase simulated future ammonium fertilizer application. In the CBW by 2050, these changes (along with widespread decreases in anthropogenic nitrogen oxide and sulfur oxide emissions, and relatively constant ammonia emissions) decrease total nitrogen deposition by 21%, decrease annual average oxidized nitrogen deposition by 44%, and increase reduced nitrogen deposition by 10%. These results emphasize the importance of decreased anthropogenic emissions on the control of future nitrogen loading to the Chesapeake Bay in a changing climate

Mechanistic representation of soil nitrogen emissions in the Community Multiscale Air Quality (CMAQ) model v 5.1

Soils are important sources of emissions of nitrogen-containing (N-containing) gases such as nitric oxide (NO), nitrous acid (HONO), nitrous oxide (N2O), and ammonia (NH3). However, most contemporary air quality models lack a mechanistic representation of the biogeochemical processes that form these gases. They typically use heavily parameterized equations to simulate emissions of NO independently from NH3 and do not quantify emissions of HONO or N2O. This study introduces a mechanistic, process-oriented representation of soil emissions of N species (NO, HONO, N2O, and NH3) that we have recently implemented in the Community Multiscale Air Quality (CMAQ) model. The mechanistic scheme accounts for biogeochemical processes for soil N transformations such as mineralization, volatilization, nitrification, and denitrification. The rates of these processes are influenced by soil parameters, meteorology, land use, and mineral N availability. We account for spatial heterogeneity in soil conditions and biome types by using a global dataset for soil carbon (C) and N across terrestrial ecosystems to estimate daily mineral N availability in nonagricultural soils, which was not accounted for in earlier parameterizations for soil NO. Our mechanistic scheme also uses daily year-specific fertilizer use estimates from the Environmental Policy Integrated Climate (EPIC v0509) agricultural model. A soil map with sub-grid biome definitions was used to represent conditions over the continental United States. CMAQ modeling for May and July 2011 shows improvement in model performance in simulated NO2 columns compared to Ozone Monitoring Instrument (OMI) satellite retrievals for regions where soils are the dominant source of NO emissions. We also assess how the new scheme affects model performance for NOx (NO+NO2), fine nitrate (NO3) particulate matter, and ozone observed by various ground-based monitoring networks. Soil NO emissions in the new mechanistic scheme tend to fall between the magnitudes of the previous parametric schemes and display much more spatial heterogeneity. The new mechanistic scheme also accounts for soil HONO, which had been ignored by parametric schemes.</p

Long-term trends in total inorganic nitrogen and sulfur deposition in the US from 1990 to 2010

Excess deposition (including both wet and dry deposition) of nitrogen and sulfur is detrimental to ecosystems. Recent studies have investigated the spatial patterns and temporal trends of nitrogen and sulfur wet deposition, but few studies have focused on dry deposition due to the scarcity of dry deposition measurements. Here, we use long-term model simulations from the coupled Weather Research and Forecasting and the Community Multiscale Air Quality (WRF-CMAQ) model covering the period from 1990 to 2010 to study changes in spatial distribution as well as temporal trends in total (TDEP), wet (WDEP), and dry deposition (DDEP) of total inorganic nitrogen (TIN) and sulfur (TS) in the United States (US). We first evaluate the model's performance in simulating WDEP over the US by comparing the model results with observational data from the US National Atmospheric Deposition Program. The coupled model generally underestimates the WDEP of both TIN (including both the oxidized nitrogen deposition, TNO3, and the reduced nitrogen deposition, NHx) and TS, with better performance in the eastern US than the western US. The underestimation of the wet deposition by the model is mainly caused by the coarse model grid resolution, missing lightning NOx emissions, and the poor temporal and spatial representation of NH3 emissions. TDEP of both TIN and TS shows significant decreases over the US, especially in the east, due to the large emission reductions that occurred in that region. The decreasing trends of TIN TDEP are caused by decreases in TNO3, and the increasing trends of TIN deposition over the Great Plains and Tropical Wet Forests (Southern Florida Coastal Plain) regions are caused by increases in NH3 emissions, although it should be noted that these increasing trends are not significant. TIN WDEP shows decreasing trends throughout the US, except for the Marine West Coast Forest region. TIN DDEP shows significant decreasing trends in the Eastern Temperate Forests, Northern Forests, Mediterranean California, and Marine West Coast Forest and significant increasing trends in the Tropical Wet Forests, Great Plains and Southern Semi-arid Highlands. For the other three regions (North American Deserts, Temperate Sierras, and Northwestern Forested Mountains), the decreasing or increasing trends are not significant. Both the WDEP and DDEP of TS have decreases across the US, with a larger decreasing trend in the DDEP than that in the WDEP. Across the US during the 1990–2010 period, DDEP of TIN accounts for 58–65 % of TDEP of TIN. TDEP of TIN over the US is dominated by deposition of TNO3 during the first decade, which then shifts to reduced nitrogen (NHx) dominance after 2003, resulting from a combination of NOx emission reductions and NH3 emission increases. The sulfur DDEP is usually higher than the sulfur WDEP until recent years, as the sulfur DDEP has a larger decreasing trend than WDEP

Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7

This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to observations and results from previous model versions in a series of simulations conducted to incrementally assess the effect of each change. The focus of this paper is on five major scientific upgrades: (a) updates to the heterogeneous N&lt;sub&gt;2&lt;/sub&gt;O&lt;sub&gt;5&lt;/sub&gt; parameterization, (b) improvement in the treatment of secondary organic aerosol (SOA), (c) inclusion of dynamic mass transfer for coarse-mode aerosol, (d) revisions to the cloud model, and (e) new options for the calculation of photolysis rates. Incremental test simulations over the eastern United States during January and August 2006 are evaluated to assess the model response to each scientific improvement, providing explanations of differences in results between v4.7 and previously released CMAQ model versions. Particulate sulfate predictions are improved across all monitoring networks during both seasons due to cloud module updates. Numerous updates to the SOA module improve the simulation of seasonal variability and decrease the bias in organic carbon predictions at urban sites in the winter. Bias in the total mass of fine particulate matter (PM&lt;sub&gt;2.5&lt;/sub&gt;) is dominated by overpredictions of unspeciated PM&lt;sub&gt;2.5&lt;/sub&gt; (PM&lt;sub&gt;other&lt;/sub&gt;) in the winter and by underpredictions of carbon in the summer. The CMAQv4.7 model results show slightly worse performance for ozone predictions. However, changes to the meteorological inputs are found to have a much greater impact on ozone predictions compared to changes to the CMAQ modules described here. Model updates had little effect on existing biases in wet deposition predictions