An intercomparison of models used to simulate the short range atmospheric dispersion and deposition of agricultural ammonia emissions

Ammonia (NH3) emitted into the atmosphere from agricultural sources can have an impact on nearby sensitive ecosystems either through elevated ambient concentrations or dry/wet deposition to vegetation and soil surfaces. Environmental impact assessments are often carried out using short-range atmospheric dispersion models to estimate mean annual atmospheric concentrations and total annual deposition of NH3 at the ecosystem location. A range of different atmospheric dispersion models are used for these assessments depending on the location and experience of the assessors and have not, until now, been compared for these types of assessments. This poster compares and validates concentration predictions of four commonly used models (ADMS v4.11, AERMOD v070262, LADD3 and OPS-st4,5) for dispersion from agricultural sources using hypothetical and real case studie

Improving the spatial resolution of air-quality modelling at a European scale – development and evaluation of the Air Quality Re-gridder Model (AQR v1.1)

Currently, atmospheric chemistry and transport models (ACTMs) used to assess impacts of air quality, applied at a European scale, lack the spatial resolution necessary to simulate fine-scale spatial variability. This spatial variability is especially important for assessing the impacts to human health or ecosystems of short-lived pollutants, such as nitrogen dioxide (NO2) or ammonia (NH3). In order to simulate this spatial variability, the Air Quality Re-gridder (AQR) model has been developed to estimate the spatial distributions (at a spatial resolution of 1  ×  1 km2) of annual mean atmospheric concentrations within the grid squares of an ACTM (in this case with a spatial resolution of 50  ×  50 km2). This is done as a post-processing step by combining the coarse-resolution ACTM concentrations with high-spatial-resolution emission data and simple parameterisations of atmospheric dispersion. The AQR model was tested for two European sub-domains (the Netherlands and central Scotland) and evaluated using NO2 and NH3 concentration data from monitoring networks within each domain. A statistical comparison of the performance of the two models shows that AQR gives a substantial improvement on the predictions of the ACTM, reducing both mean model error (from 61 to 41 % for NO2 and from 42 to 27 % for NH3) and increasing the spatial correlation (r) with the measured concentrations (from 0.0 to 0.39 for NO2 and from 0.74 to 0.84 for NH3). This improvement was greatest for monitoring locations close to pollutant sources. Although the model ideally requires high-spatial-resolution emission data, which are not available for the whole of Europe, the use of a Europe-wide emission dataset with a lower spatial resolution also gave an improvement on the ACTM predictions for the two test domains. The AQR model provides an easy-to-use and robust method to estimate sub-grid variability that can potentially be extended to different timescales and pollutants

Measurement and modelling of ammonia emissions from an anaerobic digestion plant

Anaerobic digestion (AD) is becoming increasingly popular for treating organic waste. The methane produced can be burned to generate electricity, and the digestate, which is rich in mineral nitrogen, can be used as a fertiliser. The storage and processing of large volumes of organic wastes through AD has been identified as a significant source of NH3 emissions, however only one study has previously quantified the totality NH3 emissions that arise in situ at an AD plant. In this study the emissions from an AD plant was estimated through the integration of supportive methodologies involving passive and continuous air NH3 sampling, atmospheric dispersion modelling and the application of published emission factors (EFs) and empirical models within the literature. Two dispersion models (ADMS and a Lagrangian stochastic model) were applied to produce robust emission estimates. The Lagrangian stochastic model (Windtrax) was used for inverse dispersion modelling to back-calculate the total emission rate from the point of continuous measurement. Back-calculated emission rates and literature EFs were applied to the ADMS model to make predictions of air NH3 concentrations. Predicted concentrations were verified against weekly passive (CEH ALPHA) NH3 measurements, where measured concentrations were well described by the numerical model framework using the emission rate estimated by inverse dispersion modelling. EFs that were applied from the literature required adjustment to fit the measured concentrations, however after sensible adjustment an excellent match of observed and predicted concentrations was achieved. Total emissions from the AD plant was estimated to be 16.8 μg s-1 ± 1.8 mg s-1. This is significantly higher than the back-calculated estimate (10.3 ± 1.1 mgs-1), due to a more realistic treatment of the source area. The storage of solid digestate and the aerobic treatment of liquid effluents were the most significant sources of NH3. The representativeness of the existing EF estimated for AD plants is evaluated through application to the present case study and comparing with NH3 measurements and estimated emission rates. The existing AD EF considerably overestimated observed concentrations by an average factor of 54. The applicability of calculated EFs to other AD plants is discussed

Improving the low-wind performance of the AERMOD atmospheric dispersion model for predicting short-range impacts of livestock ammonia emissions.

Short-range impacts to sensitive ecosystems as a result of ammonia emitted by livestock farms are often assessed using atmospheric dispersion modelling systems such as AERMOD. These assessments evaluate mean annual atmospheric concentrations of ammonia and nitrogen deposition rates at the ecosystem location for comparison with ecosystem damage thresholds. However, predictions of mean annual atmospheric concentrations can be dominated by periods of stable night-time conditions, which can contribute significantly to mean concentrations. AERMOD has been demonstrated to overestimate concentrations in certain stable low-wind conditions and so the model could potentially overestimate the short-range impacts of livestock ammonia emissions. This paper tests several modifications to the parameterisation of AERMOD (v12345) that aim to improve model predictions in low-wind conditions. The modifications are first described and then are applied to three pig farm case studies in the USA, Denmark and Spain to assess whether the modifications improve long-term mean ammonia concentration predictions through improved model performance. For these three case studies, most of the modifications tested improved model performance as a result of reducing the long-term mean concentration predictions, with the largest effect for low- or ground-level sources (e.g. slurry lagoons or naturally ventilated housing)

Suitability and uncertainty of two models for the simulation of ammonia dispersion from a pig farm located in an area with frequent calm conditions

We used two atmospheric dispersion models (ADMS and AERMOD) to simulate the short-range dispersion of ammonia emitted by two pig farms to assess their suitability in situations with frequent calm meteorological conditions. Simulations were carried out both using constant and temporally-varying emission rates to evaluate the effect on the model predictions. Monthly and annual mean concentrations predicted by the models at locations within one kilometre of the farms were compared with measured values. AERMOD predicted higher concentrations than ADMS (by a factor of 6–7, on average) and predicted the atmospheric concentrations more accurately for both the monthly and annual simulations. The differences between the concentrations predicted by the two models were mainly the result of different calm wind speed thresholds used by the models. The use of temporally-varying emission rates improved the performance of both models for the monthly and annual simulations with respect to the constant emission simulations. A Monte Carlo uncertainty analysis based on the inputs judged to be the most uncertain for the selected case study estimated a prediction uncertainty of ± a factor of two for both models with most of this due to uncertainty in emission rates

Measurement of methane emissions from confined sources using the inverse dispersion method

Greenhouse gas (GHG) emissions are reported in annual national inventories. Globally, the main anthropogenic sources of methane (CH4) are fossil fuel burning, agriculture, landfills, and waste management. The main source of CH4 from agriculture is enteric fermentation in the digestive tract of ruminants and a minor source are emissions from manure management. In 2019, the Swiss Federal council decided that Switzerland must reduce its GHG emission to net-zero until 2050. To reach this goal, the agricultural sector is obliged to contribute to the emission reduction. However, emissions from the agriculture and waste sector imply large uncertainties as, among other reasons, the availability of data based on real-world studies is limited. Several investigations showed that measurements from laboratory- or pilot-scale experiments do often not comply with real-world conditions. For studies under real-world conditions, different measurement approaches are available. One of the most promising methods is the inverse dispersion method (IDM) that was applied in this thesis to measure CH 4 emissions from livestock production and the waste management sector in order to evaluate the method for complex source configurations and to specify emission factors of these sources. For the IDM, a backward Lagrangian stochastic (bLS) model in combination with concentration measurements up- and downwind of the source using open-path tunable diode laser spectrometers (GasFinders) were employed. GasFinders are simple to use, flexible in their application, and relatively cost-effective measuring devices. However, several challenges were faced and overcome throughout the thesis. The precision of the employed GasFinder model was about 10 times lower than the manufacturer stated, which necessitated adaptation in the measurement setup. Additionally, an intercomparison before or after each measurement campaign was necessary to correct the offset and span between the employed GasFinders. In the first two studies presented in this thesis, experiments were conducted to evaluate the IDM. In a third study, experiments were conducted to assess the handling of complex source configurations with the IDM. The emissions determined in the third study were used as a basis for emission factors of Swiss biogas plants (BGPs) and wastewater treatment plants (WWTPs). In the first study, a known and predefined amount of CH 4 was released by an artificial source in a barn that mimics a dairy housing. For concentration measurements, GasFinders with a path length ii Thesis summary of 110 m were placed in downwind direction of the barn at a distance of 50 m, 100 m, 150 m, and 200 m. At the first three distances, an ultrasonic anemometer was placed in the middle of the GasFinder path length for executing turbulence measurements. Upwind of the barn, an additional GasFinder and an ultrasonic anemometer were installed. The main objective was to test the ideal measurement fetch for the IDM. The results of this experiment are included in the method section, where the conditions and the setup of an IDM measurement campaign are outlined. A release rate of 140 norm litres min -1 was chosen to achieve sufficient concentration enhancement at the GasFinder locations. The mean recovery rates of the experiment were between 0.55 – 0.76. In the second study, CH4 emission measurements from a naturally ventilated dairy housing were conducted in two measurement campaigns. During part of the campaign duration, emissions were also measured inside the housing with the inhouse tracer ratio method (iTRM). This allowed comparing the IDM with the iTRM, which was considered as a reference method for naturally ventilated livestock housings. For simultaneous emission intervals, the average IDM emissions were lower by 1 % and 8 % compared to the iTRM measurements, which was within the uncertainty of either of the two methods. Additionally, an uncertainty analysis for the IDM showed that measurement campaigns of at least 10 consecutive days are necessary to acquire reliable emission data. The third study addressed the handling of complex source configurations with the IDM. Emissions from four agricultural BGPs and two WWTPs in Switzerland were measured. The average BGP CH 4 emission varied between 0.39 kg h -1 and 2.22 kg h-1, which was less than 5 % of the plant’s CH4 production. The average CH4 emissions for the two WWTPs were 166 g population-equivalent-1 y -1 and 381 g population-equivalent-1 y -1, respectively. The BGPs often had livestock housings nearby that needed to be discriminated from the plant emission. It was demonstrated how the plant emission can be corrected for the nearby CH4 sources, which confounded the GasFinder measurements. Further, it was demonstrated how to combine multiple GasFinder measurements to a single line concentration for the bLS modelling. WWTPs are complex sources as they consist of multiple sub-sources with different emission strengths spread over a large area. Three different calculation approaches with different degree of details are presented for the combination of the individual sources in the bLS modelling: (i) A polygon over the entire WWTP area as a single source. (ii) All potential sources within the WWTP have a uniform emission density. (iii) Based on literature data, relative weighting of the individual sources is carried out. The maximum difference in emission between the most complex approach (iii) and the simplest approach (i) was 42 %. It could be shown that for large source areas (> 10,000 m2), approach (iii) is the preferred option, whereas for the measured BGPs the simple polygon approach (i) was sufficient. The recovery rate of the IDM from the release experiment (study 1) was below 1 and somewhat lower than previous studies with a similar experimental setting have shown. I was not able to conclusively identify the reasons for this result, which contrasts with the outcome of study 2 at the naturally ventilated dairy housing with a high consistency between the IDM and the iTRM used as a reference. Therefore, I suggest repeating the release experiment with an adapted setting and additionally roughly mapping the emission plume by a drone or a high-precision handheld sensor to monitor the dispersion of the plume. The field measurements at the WWTPs and the BGPs based on iii the chosen approach of source combination yielded data that are in the expected range according to current state of knowledge. The presented PhD thesis supports the aptitude of the IDM to measure emissions from complex sources like farms, BGPs, or WWTPs. Such measurements contribute to increasing the accuracy of national GHG inventories. Nevertheless, I suggest further investigations to better assess the accuracy of the IDM under complex conditions

Applications of computational modelling to ammonia dispersion from agricultural sources.

Imperial Users onl

Heterogeneity of atmospheric ammonia at the landscape scale and consequences for environmental impact assessment

We examined the consequences of the spatial heterogeneity of atmospheric ammonia (NH3) by measuring and modelling NH3 concentrations and deposition at 25 m grid resolution for a rural landscape containing intensive poultry farming, agricultural grassland, woodland and moorland. The emission pattern gave rise to a high spatial variability of modelled mean annual NH3 concentrations and dry deposition. Largest impacts were predicted for woodland patches located within the agricultural area, while larger moorland areas were at low risk, due to atmospheric dispersion, prevailing wind direction and low NH3 background. These high resolution spatial details are lost in national scale estimates at 1 km resolution due to less detailed emission input maps. The results demonstrate how the spatial arrangement of sources and sinks is critical to defining the NH3 risk to semi-natural ecosystems. These spatial relationships provide the foundation for local spatial planning approaches to reduce environmental impacts of atmospheric NH3

Integrated Environmental Modelling Framework for Cumulative Effects Assessment

Global warming and population growth have resulted in an increase in the intensity of natural and anthropogenic stressors. Investigating the complex nature of environmental problems requires the integration of different environmental processes across major components of the environment, including water, climate, ecology, air, and land. Cumulative effects assessment (CEA) not only includes analyzing and modeling environmental changes, but also supports planning alternatives that promote environmental monitoring and management. Disjointed and narrowly focused environmental management approaches have proved dissatisfactory. The adoption of integrated modelling approaches has sparked interests in the development of frameworks which may be used to investigate the processes of individual environmental component and the ways they interact with each other. Integrated modelling systems and frameworks are often the only way to take into account the important environmental processes and interactions, relevant spatial and temporal scales, and feedback mechanisms of complex systems for CEA. This book examines the ways in which interactions and relationships between environmental components are understood, paying special attention to climate, land, water quantity and quality, and both anthropogenic and natural stressors. It reviews modelling approaches for each component and reviews existing integrated modelling systems for CEA. Finally, it proposes an integrated modelling framework and provides perspectives on future research avenues for cumulative effects assessment

The nitrate aerosol field over Europe: simulations with an atmospheric chemistry-transport model of intermediate complexity

International audienceNitrate is an important component of fine aerosols in Europe. We present a model simulation for the year 1995 in which we account for the formation of the ammonium nitrate, a semi volatile component. For this purpose, LOTOS, a chemistry-transport model of intermediate complexity, was extended with a thermodynamic equilibrium module and additional relevant processes to account for aerosol formation and deposition. Our earlier analysis of data on (ammonium) nitrate in Europe was used for model evaluation. During winter, fall and especially spring high nitrate levels are projected over north western, central and eastern Europe. During winter nitrate concentrations are highest in the Po valley, Italy. This is in accordance with the field that was constructed from the data. In winter nitric acid, the precursor for aerosol nitrate, is formed through heterogeneous reactions on the surface of aerosols. Appreciable ammonium nitrate concentrations in summer are limited to those areas with high ammonia emissions, e.g. The Netherlands, since high ammonia concentrations are necessary to stabilise this aerosol component at high temperatures. Averaged over all stations the model reproduces the measured concentrations for NO3, SO4, NH4, TNO3, TNH4 and SO2 within 20%. The daily variation is captured well, albeit that the model does not always represents the amplitude of single events. The model underestimates wet deposition which was attributed to the crude representation of cloud processes. The treatment of ammonia was found to be the major source for uncertainties in the model representation of secondary aerosols. Also, inclusion of sea salt is necessary to properly assess the nitrate and nitric acid levels in marine areas. Over Europe the annual forcing by nitrate is calculated to be 25% of that by sulphate. In summer nitrate is found to be regionally important, e.g. in The Netherlands, where the forcing of nitrate and sulphate are calculated to be equal. In winter, spring and fall the nitrate forcing over Europe is about half that by sulphate. Over north western Europe and the alpine region the forcing by nitrate was calculated to be similar to that of sulphate. Overall, nitrate forcing is significant and should be taken into account to estimate the impact of regional climate change in Europe