Field crops can emit or store carbon depending on the season and cropping practices. A process-based modeling approach allowed us to predict the transfer pattern of the CO2 fluxes and energy balance between soil, vegetation, and atmosphere. In this study, the SURFATM-CO2 model was developed to simulate distinctly the CO2 exchanges between soil, plants, and the atmosphere. The model couples soil respiration, taking into account its temperature sensitivity, with photosynthesis and plant respiration process-based, taking into account the plant's CO2 compensation point. The SURFATM-CO2 process model was evaluated using field measurements obtained from a novel multiport profile system consisting of 4 vertical measurement heights to monitor the spatial and temporal variation of CO2, water, and temperature within and above the maize canopy in east Tennessee. The 5Hz frequency raw data were averaged into 15-minute runs and used as input for the SURFATM model. The model satisfactorily simulates the energy balance, and we are currently testing the model for the CO2 fluxes. The main objective of this study is to understand the exchanges of CO2 between the soil, vegetation and atmosphere compartments. The finding of the SURFATM-CO2 model will highlight the ability of the SURFATM-model to capture the canopy-atmosphere interaction as well as provide a base for model application in the studies of carbon dynamics, and cropland ecosystem management.

Ammonia ( N H 3 ) concentration and flux measurements made in 2016 in a mixed deciduous forest at the western North Carolina Coweeta Hydrologic Laboratory are analyzed using a multi-layer, one-dimensional column model with detailed canopy physics and bi-directional exchange. Simulations for April 26-30 and July 19-30 are presented to assess the model's ability to represent measured in-canopy N H 3 profiles and probe the processes that control bi-directional exchange with the canopy and forest floor. During dry canopy conditions, model simulations are found to well reproduce measured in-canopy profiles for both the April and July periods, given appropriate model inputs. Results from the model, and the shape of in-canopy N H 3 profiles, are sensitive to vertical turbulent mixing, the values of the input soil/litter emission potential, and the assumed litter resistance. N H 3 fluxes simulated above the forest canopy are very small (-25 to -5 ng m-2 s-1 in April and < 1 ng m-2 s-1 in July) with primarily deposition to the canopy during the April time period, but with mixed deposition/emission during July. The model also suggests that net deposition or emission of N H 3 can be a function of location within the canopy, depending on the difference between the air concentration and the effective canopy compensation point. However, during periods when the canopy is wet from overnight dew and drying rapidly, the model does a poor job of replicating in-canopy profiles, typically underestimating N H 3 concentrations, since the model does not account for the release of N H 3 from evaporating dew. Although available data during the field campaign are not sufficient to rule out other potential hypotheses, given that the model reasonably reproduces in-canopy profiles during dry canopy periods, but fails during periods of rapid drying, the results are suggestive that dew is playing a major role in N H 3 concentration changes observed in July during the field study. Additional studies and measurements are needed to determine the processes and environmental controls that affect N H 3 absorption and release from dew and to evaluate the importance of this process for modeling deposition and re-emission on the regional scale. Further questions that arise from our findings are whether the variation of N H 3 deposition or emission with location in the canopy is important from an ecological perspective and how in-canopy dynamics might be represented in regional-scale air quality models. Traditional big-leaf approaches of modeling N H 3 bi-directional exchange cannot account for in-canopy variation such as that presented here, and so multi-layer approaches may need to be developed for more nuanced estimates of N H 3 deposition to forest ecosystems.

Surfatm is a two-layer resistance model to compute the exchanges of heat, water vapour, ammonia, ozone, and pesticides between the atmosphere, the vegetation, and the soil in several ecosystems at the field scale. After briefly describing its functioning and functionalities, some application studies using the model are presented. Surfatm is a tool suitable for research, decision-making, and lecturing activities in environmental sciences, specifically on heat, water, and pollutant exchanges between the atmosphere and the biosphere.

UrbanNet data have been used to enhance the predictions of the Weather Research and Forecasting (WRF) model through observational nudging to improve temperature and wind predictions. HYSPLIT was utilized to understand the impact of using the observationally nudged WRF fields in dispersion modeling. The meteorological observations collected from the National Weather Service monitoring stations located at two major airports in Washington metropolitan area were also assimilated into WRF modeling. The results showed that observational nudging successfully adjusted WRF wind fields towards the observations and significantly reduced the forecast temperature bias at nighttime. The comparison of HYSPLIT simulations with and without the enhancement of the WRF model using UrbanNet and airport data showed significant differences in the pattern and direction of the dispersion plume especially during the early morning hours. Furthermore, ingesting the data from the closer airport to the downtown area in WRF provided HYSPLIT simulations very similar to the ones using UrbanNet data. This provides strong evidence that local data are essential to adjust weather prediction models routinely used to drive dispersion models. There was also evidence of increased mixing height when using local data collected in the downtown, mainly resulting from the increased surface heating in the city.

The need to anticipate high risk of exposure following the generation of a cloud of cold and dense gas beneath a forest canopy introduces a need to examine the processes facilitating exchange with the air above the canopy. It is the concentrations in this above-canopy air that are used to initialize many dispersion models and these concentrations are lower than would be expected if no canopy were present. In the lack of direct experimental studies of trans-canopy dilution in a forested environment, results from a variety of related experiments are used here to illustrate the complexity of the problem and to derive a first-order assessment of the extent of expected dilution. The focus is on the dense gas clouds following accidents involving liquid chlorine, ammonia and carbon dioxide. It is concluded that the dilution would result in above-canopy concentrations between 2% and 50% of average sub-canopy levels, depending on site-specific circumstances. It is also concluded that the relative importance of the various contributing processes is such that detailed incorporation of them in dispersion models would constitute an unjustified complexity unless definitive experimental observations are available. Instead, the consequences of the issues now considered might best be accommodated by reducing predicted downwind concentrations by a factor of about ten with a corresponding extension of the duration of the dispersion event.

Narragansett Bay, the largest estuary in New England, is a heavily urbanized watershed impacted by deposition and runoff. Nutrient budgets and local policy rely on deposition data from a 1990 study that did not include any direct observations of dry deposition of gaseous ammonia (NH 3(g) ) and particulate ammonium (p‐NH 4 + ) due to uncertainties in their flux direction and measurement difficulty. Recent work has shown that wet deposition of ammonium (NH 4 + ) to the Bay has increased by a factor of 6 over the past three decades, leading to a 2.5‐fold increase in wet nitrogen (N) deposition. This documented increase in wet deposition of NH 4 + is concurrent with managed nutrient reductions in urbanized estuaries but has potentially increased the impacts of atmospheric N deposition, including the dry deposition of NH 3(g) and p‐NH 4 + . However, the lack of NH 3(g) and p‐NH 4 + measurements hinders our interpretation of this important N source. For the first time over Narragansett Bay, and to our knowledge over open water, dry (particulate and gas phase) total ammonia (NH x = NH 3(g) + p‐NH 4 + ) and the bidirectional NH 3(g) flux were quantified using a relaxed eddy accumulation sampling technique. We find that dry deposition of NH x comprises 9.6% of total (wet + dry) N deposition. During the fall season, the dominant flux direction for NH 3(g) is upward, which also has implications for urban air quality. We estimate that NH 3(g) emitted from the Bay to the atmosphere makes up to 10% of the local NH 3(g) emission budget for fall.

This study presents an example of how outputs of operational and readily-available mesoscale numerical models can be adapted to initialize dispersion calculations within the urban surface roughness layer. Three years of urban meteorological observations from central Washington, DC, are compared against forecast outputs of the North American Mesoscale (NAM) model. NAM wind speed predictions underestimate the observations in light winds and overestimate the measurements in high winds. Average wind directions are consistent. However, an adjustment of the predicted direction of the plume by −20° is needed. The uncertainty associated with this adjustment is large in light NAM wind speed with no evident variation by season. The values of the standard deviation of the wind direction, σθ derived from NAM model outputs underestimate the observations by a small amount (about −1.5 to −2.5°). The results presented here indicate that mesoscale numerical model outputs can provide information adequate for dispersion calculations. However, levels of uncertainty associated with implementation of the suggested procedures increase with decreasing wind speed, causing considerable uncertainty in the implementation of adjustments as low wind speed conditions are approached. Results and recommendations reported here should not be extended to other numerical models or other cities without further testing.

Measurements of atmospheric ammonia (NH 3 ) concentrations and fluxes are limited in coastal regions in the eastern U.S. In this study, continuous and high temporal resolution measurements (5s) of atmospheric NH 3 concentrations were recorded using a cavity ring‐down spectrometer in a temperate tidal salt marsh at the St Jones Reserve (Dover, DE). Micrometeorological variables were measured using an eddy covariance system which is part of the AmeriFlux network (US‐StJ). Soil, plant, and water chemistry were also analyzed to characterize the sources and sinks of atmospheric NH 3 . A new analytical methodology was used to estimate the average ecosystem‐scale diurnal cycle of NH 3 fluxes by replicating the characteristics of a chamber experiment. This virtual chamber approach estimates positive surface fluxes in continuing strongly stable conditions when mixing with the air above is minimal. Our findings show that tidal water level may have a significant impact on NH 3 emissions from the marsh. The largest fluxes were observed at low tide when more soil was exposed. While it is expected that NH 3 fluxes will peak when the air temperature maximizes, high tide occurred concurrently with midday peaks in solar irradiance led to a decrease in NH 3 fluxes. Furthermore, soil, plant, and water chemistry measurements underpinning the NH 3 concentrations and fluxes lead us to conclude that this coastal wetland ecosystem can act as either a sink or a source of NH 3 . Such measurements provide novel data on which we can base reliable parameterizations to simulate NH 3 emissions from coastal salt marsh ecosystems using surface‐atmosphere transfer models.

In the stable conditions prevailing at night, concentrations of emitted gases (e.g., radon [Rn], carbon dioxide [CO2](,) methane [CH4](,) ammonia [NH3], and nitrous oxide [N2O]) build up at the surface, with intermittent interruptions due to the passage of packets of turbulence. The applicability of conventional experimental methods is then questionable. Here, a statistical approach is proposed, in which micrometeorological field data are used to replicate the likely characteristics of a chamber experiment, yielding estimates of surface fluxes at the surface itself with reduced requirement for adequate fetch. Application of the virtual chamber methodology to two recent field studies is explored: (a) a study of nocturnal CO2 emission from a farmland area in Ohio in 2015; and (b) an investigation of NH3 effluxes from a crop previously treated with urea ammonium nitrate (UAN) in Illinois in 2014. For both datasets, the virtual chamber approach yields results in general agreement with eddy covariance (EC) data.

........................................................................................................................................................ 3 List of Figures ............................................................................................................................................... 5 List of Tables ................................................................................................................................................ 8 1.0 Introduction ............................................................................................................................................. 9 2.0 Hoover Station Design .......................................................................................................................... 12 2.1 Instrumentation ................................................................................................................................. 12 2.2 Data Acquisition and communications ............................................................................................. 13 2.3 Data processing and archiving .......................................................................................................... 13 3.0 Observations ......................................................................................................................................... 14 3.1 Mean observations ............................................................................................................................ 14 3.1.1 Wind Speed ................................................................................................................................ 14 3.1.2 Wind Direction ........................................................................................................................... 15 3.1.3 Ambient Temperature ................................................................................................................ 15 3.2 Turbulence observations ................................................................................................................... 15 3.2.1 Horizontal and vertical velocity variances ................................................................................. 16 3.2.2 Shear Stress ................................................................................................................................ 17 3.2.3 Sensible Heat Flux ..................................................................................................................... 17 4.0 Data Evaluation ..................................................................................................................................... 17 4.1 Mean Wind and Temperature ........................................................................................................... 17 4.2 Turbulence Statistics ......................................................................................................................... 18 5.0 Summary ............................................................................................................................................... 20 6.0 Acknowledgements ............................................................................................................................... 21 7.0 References ............................................................................................................................................. 22

Agriculture is the main source of ammonia (NH3) emissions in the atmosphere. NH3 is precursor to secondary fine particulate matter, which is of concern for its impacts on health and visibility. There are a limited number of field measurements of NH3 emissions from fertilizer application in the US, and this limits our understanding of the importance of individual NH3 source and sink processes in controlling timing and magnitude of NH3 emissions. In this study, a new parameterization of the effect of urease inhibitor on NH3 emissions from urea based fertilizer was developed on the basis of experimental results found in the literature. This parameterization was combined with an existing operational parameterization of soil and stomatal emission potentials (Gamma(g), Gamma(s)) and was implemented in a surface-atmosphere transfer model for NH3 (SURFATM-NH3) in order to evaluate the bi-directional fluxes of NH3 at the field scale. The model was evaluated with field measurements obtained by the flux-gradient (FG) and relaxed eddy accumulation (REA) methods in a fertilized corn field in central Illinois. By integrating the effect of urease inhibitor, the timing of the highest NH3 emission peak was successfully predicted and its magnitude was close to that measured (predicted 2106 ng m(-2) s(-1), measured by FG 2312 +/- 582 ng m(-2) s(-1)). Based on the model results, urease inhibitor has a considerable effect on the dynamics and order of magnitude of NH3 fluxes. Furthermore, the model simulated the inhibiting action of N-(n-butyl) thiophosphoric (nBTPT) and suggests that it can reduce NH3 volatilization by 32%. The model also successfully predicted environmental parameters, such as soil temperature. Finally, this new version of SURFATM-NH3 is a valuable tool to estimate the NH3 bi-directional fluxes at the field scale, which describes dynamic modeling of Gamma(s) and Gamma(g) by taking into account the effect of urease inhibitor which is commonly used in the US to improve the efficiency of urea fertilizers.

Abstract. Quantification of the emission rates of various gases from soils at night remains a challenge, confronting climate science (in the case of CO2 and CH4) and agriculture science (for NH3 and N2O, among others). In the stable conditions prevailing at night, concentrations of such emitted gases build up at the surface during the night, with intermittent interruptions commonly attributed to the passage of packets of turbulence. The utility of conventional micrometeorological experimental methods in such circumstances is questionable, and chamber methods have been developed to meet the challenge. Here, a statistical approach is proposed, in which micrometeorological field data are used to replicate the likely characteristics of a chamber experiment, yielding estimates of surface fluxes at the surface itself and not at some height above it. The methodology proposed is developmental at this time, with details intended to correspond to the use of both closed and vented chambers. Its application to three recent field studies is explored: (1) a study of nocturnal CO2 emission from two test areas (one previously tilled and the other not) in Ohio in 2015; (2) a similar experiment conducted in Zimbabwe in 2013 (one area previously tilled and a second left fallow), and (3) an investigation of NH3 effluxes from a crop previously treated with urea ammonium nitrate (UAN), in Illinois in 2014. There are few measurements with which to compare the results presented here, however the values obtained are within the range of available field data.

Studies of NH3 flux over agricultural ecosystems in the USA are limited by low temporal resolution (typically hours or days) and sparse spatial coverage, with no studies over corn in the Midwest USA. We report on NH3 flux measurements over a corn canopy in Central Illinois, USA, using the relaxed eddy accumulation (REA) and flux gradient (FG) methods, providing measurements at 4 h and 0.5 h intervals, respectively. The REA and FG systems were operated for the duration of the 2014 corn-growing season. Flux-footprint analysis was used to select data from both systems, resulting in 82 concurrent measurements. Mean NH3 flux of concurrent measurements was 205 +/- 300 ng m(-2) s(-1) from REA and 110 +/- 256 ng m(-2) s(-1) from FG for all concurrent samples. Results from both methods were not significantly different at a 95% confidence level for all concurrent measurements. The FG system resolved NH3 emission peaks at 0.5 h averaging time that were otherwise un-observed with 4 h REA averaging. Two early-season peak emission periods were identified (DOY 130-132 and 140-143), where the timing and intensity of such emissions were attributed to a combination of urease inhibitor, applied as a field management decision, and localized soil temperature and precipitation. Given the dependence of NH3 fluxes on multiple parameters, this study further highlights the need for increased spatial coverage and high temporal resolution (e.g., < 1 h) of measurements to better understand the impact of agricultural NH3 emissions on air quality and the global nitrogen cycle. Such measurements are also needed for evaluation of models describing surface-atmosphere exchange of NH3.

Volatilization from plant foliage is known to have a great contribution to pesticide emission to the atmosphere. However, its estimation is still difficult because of our poor understanding of processes occurring at the leaf surface. A compartmental approach for dissipation processes of pesticides applied on the leaf surface was developed on the base of experimental study performed under controlled conditions using laboratory volatilization chamber. This approach was combined with physicochemical properties of pesticides and was implemented in SURFATM-Pesticides model in order to predict pesticide volatilization from plants in a more mechanistic way. The new version of SURFATM-Pesticide model takes into account the effect of formulation on volatilization and leaf penetration. The model was evaluated in terms of 3 pesticides applied on plants at the field scale (chlorothalonil, fenpropidin and parathion) which display a wide range of volatilization rates. The comparison of modeled volatilization fluxes with measured ones shows an overall good agreement for the three tested compounds. Furthermore the model confirms the considerable effect of the formulation on the rate of the decline in volatilization fluxes especially for systemic products. However, due to the lack of published information on the substances in the formulations, factors accounting for the effect of formulation are described empirically. A sensitivity analysis shows that in addition to vapor pressure, the octanol-water partition coefficient represents important physicochemical properties of pesticides affecting pesticide volatilization from plants. Finally the new version of SURFATM-Pesticides is a prospecting tool for key processes involved in the description of pesticide volatilization from plants.

Estimation of pesticide volatilization from plants is difficult because of our poor understanding of foliar penetration by pesticides, which governs the amount of pesticide available for volatilization from the leaf surface. The description of foliar penetration is still incomplete because experimental measurements of this complex process are difficult. In this study, the dynamics of leaf penetration of C-chlorothalonil and C-epoxiconazole applied to wheat leaves were measured in a volatilization chamber, which allowed us to simultaneously measure pesticide volatilization. Fungicide penetration into leaves was characterized using a well-defined sequential extraction procedure distinguishing pesticide fractions residing at different foliar compartments; this enabled us to accurately measure the penetration rate constant into the leaves. The effect of pesticide formulation was also examined by comparing formulated and pure epoxiconazole. We observed a strong effect of formulation on leaf penetration in the case of a systemic product. Furthermore, the penetration rate constant of formulated epoxiconazole was almost three times that of pure epoxiconazole (0.47 ± 0.20 and 0.17 ± 0.07, respectively). Our experimental results showed high recovery rates of the radioactivity applied within the range of 90.5 to 105.2%. Moreover, our results confirm that pesticide physicochemical properties are key factors in understanding leaf penetration of pesticide and its volatilization. This study provides important and useful parameters for mechanistic models describing volatilization of fungicides applied to plants, which are scarce in the literature.