Intercomparison of C-14 Analysis of Carbonaceous Aerosols: Exercise 2009

Radiocarbon analysis of the carbonaceous aerosol allows an apportionment of fossil and non-fossil sources of airborne particulate matter (PM). A chemical separation of total carbon (TC) into its subfractions organic carbon (OC) and elemental carbon (EC) refines this powerful technique, as OC and EC originate from different sources and undergo different processes in the atmosphere. Although C-14 analysis of TC, EC, and OC has recently gained increasing attention, interlaboratory quality assurance measures have largely been missing, especially for the isolation of EC and OC. In this work, we present results from an intercomparison of 9 laboratories for C-14 analysis of carbonaceous aerosol samples on quartz fiber filters. Two ambient PM samples and 1 reference material (RM 8785) were provided with representative filter blanks. All laboratories performed C-14 determinations of TC and a subset of isolated EC and OC for isotopic measurement. In general, C-14 measurements of TC and OC agreed acceptably well between the laboratories, i.e. for TC within 0.015-0.025 (FC)-C-14 for the ambient filters and within 0.041 (FC)-C-14 for RM 8785. Due to inhomogeneous filter loading, RM 8785 demonstrated only limited applicability as a reference material for C-14 analysis of carbonaceous aerosols. C-14 analysis of EC revealed a large deviation between the laboratories of 28-79 as a consequence of different separation techniques. This result indicates a need for further discussion on optimal methods of EC isolation for C-14 analysis and a second stage of this intercomparison.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Long-term climate change commitment and reversibility: An EMIC Intercomparison

This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. Most EMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs for RCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination of CO2 emissions in all EMICs. Restoration of atmospheric CO2 from RCP to preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2.

Atmospheric CO₂, δ(O₂/N₂) and δ13CO2 measurements at Jungfraujoch, Switzerland: results from a flask sampling intercomparison program

We present results from an intercomparison program of CO2, δ(O2/N2) and δ13CO2 measurements from atmospheric flask samples. Flask samples are collected on a bi-weekly basis at the High Altitude Research Station Jungfraujoch in Switzerland for three European laboratories: the University of Bern, Switzerland, the University of Groningen, the Netherlands and the Max Planck Institute for Biogeochemistry in Jena, Germany. Almost 4 years of measurements of CO2, δ(O2/N2) and δ13CO2 are compared in this paper to assess the measurement compatibility of the three laboratories. While the average difference for the CO2 measurements between the laboratories in Bern and Jena meets the required compatibility goal as defined by the World Meteorological Organization, the standard deviation of the average differences between all laboratories is not within the required goal. However, the obtained annual trend and seasonalities are the same within their estimated uncertainties. For δ(O2/N2) significant differences are observed between the three laboratories. The comparison for δ13CO2 yields the least compatible results and the required goals are not met between the three laboratories. Our study shows the importance of regular intercomparison exercises to identify potential biases between laboratories and the need to improve the quality of atmospheric measurements.

First intercomparison study on the analysis of oxygenated polycyclic aromatic hydrocarbons (oxy-PAHs) and nitrogen heterocyclic polycyclic aromatic compounds (N-PACs) in contaminated soil

Oxygenated polycyclic aromatic hydrocarbons (oxy-PAHs) and nitrogen heterocyclic polycyclic aromatic compounds (N-PACs) are toxic, highly leachable and often abundant at sites that are also contaminated with PAHs. However, due to lack of regulations and standardized methods for their analysis, they are seldom included in monitoring and risk-assessment programs. This intercomparison study constitutes an important step in the harmonization of the analytical methods currently used, and may also be considered a first step towards the certification of reference materials for these compounds. The results showed that the participants were able to determine oxy-PAHs with accuracy similar to PAHs, with average determined mass fractions agreeing well with the known levels in a spiked soil and acceptable inter- and intra-laboratory precisions for all soils analyzed. For the N-PACs, the results were less satisfactory, and have to be improved by using analytical methods more specifically optimized for these compounds.

Intercomparison of stratospheric ozone profiles for the assessment of the upgraded GROMOS radiometer at Bern

Since November 1994, the GROund-based Millimeter-wave Ozone Spectrometer (GROMOS) measures stratospheric and lower mesospheric ozone in Bern, Switzerland (47.95° N, 7.44° E). GROMOS is part of the Network for the Detection of Atmospheric Composition Change (NDACC). In July 2009, a Fast-Fourier-Transform spectrometer (FFTS) has been added as backend to GROMOS. The new FFTS and the original filter bench (FB) measured parallel for over two years. In October 2011, the FB has been turned off and the FFTS is now used to continue the ozone time series. For a consolidated ozone time series in the frame of NDACC, the quality of the stratospheric ozone profiles obtained with the FFTS has to be assessed. The FFTS results from July 2009 to December 2011 are compared to ozone profiles retrieved by the FB. FFTS and FB of the GROMOS microwave radiometer agree within 5% above 20 hPa. A later harmonization of both time series will be realized by taking the FFTS as benchmark for the FB. Ozone profiles from the FFTS are also compared to coinciding lidar measurements from the Observatoire Haute Provence (OHP), France. For the time period studied a maximum mean difference (lidar – GROMOS FFTS) of +3.8% at 3.1 hPa and a minimum mean difference of +1.4% at 8 hPa is found. Further, intercomparisons with ozone profiles from other independent instruments are performed: satellite measurements include MIPAS onboard ENVISAT, SABER onboard TIMED, MLS onboard EOS Aura and ACE-FTS onboard SCISAT-1. Additionally, ozonesondes launched from Payerne, Switzerland, are used in the lower stratosphere. Mean relative differences of GROMOS FFTS and these independent instruments are less than 10% between 50 and 0.1 hPa.

The diurnal variation in stratospheric ozone from the MACC reanalysis, the ERA-Interim reanalysis, WACCM and Earth observations: characteristics and intercomparison

In this study we compare the diurnal variation in stratospheric ozone derived from free-running simulations of the Whole Atmosphere Community Climate Model (WACCM) and from reanalysis data of the atmospheric service MACC (Monitoring Atmospheric Composition and Climate) which both use a similar stratospheric chemistry module. We find good agreement between WACCM and the MACC reanalysis for the diurnal ozone variation in the high-latitude summer stratosphere based on photochemistry. In addition, we consult the ozone data product of the ERA-Interim reanalysis. The ERA-Interim reanalysis ozone system with its long-term ozone parametrization can not capture these diurnal variations in the upper stratosphere that are due to photochemistry. The good dynamics representations, however, reflects well dynamically induced ozone variations in the lower stratosphere. For the high-latitude winter stratosphere we describe a novel feature of diurnal variation in ozone where changes of up to 46.6% (3.3 ppmv) occur in monthly mean data. For this effect good agreement between the ERA-Interim reanalysis and the MACC reanalysis suggest quite similar diurnal advection processes of ozone. The free-running WACCM model seriously underestimates the role of diurnal advection processes at the polar vortex at the two tested resolutions. The intercomparison of the MACC reanalysis and the ERA-Interim reanalysis demonstrates how global reanalyses can benefit from a chemical representation held by a chemical transport model. The MACC reanalysis provides an unprecedented description of the dynamics and photochemistry of the diurnal variation of stratospheric ozone which is of high interest for ozone trend analysis and research on atmospheric tides. We confirm the diurnal variation in ozone at 5 hPa by observations of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) experiment and selected sites of the Network for Detection of Atmospheric Composition Change (NDACC). The latter give valuable insight even to diurnal variation of ozone in the polar winter stratosphere.

Stability of the Atlantic meridional overturning circulation: A model intercomparison.

The evolution of the Atlantic Meridional Overturning Circulation (MOC) in 30 models of varying complexity is examined under four distinct Representative Concentration Pathways. The models include 25 Atmosphere-Ocean General Circulation Models (AOGCMs) or Earth System Models (ESMs) that submitted simulations in support of the 5th phase of the Coupled Model Intercomparison Project (CMIP5) and 5 Earth System Models of Intermediate Complexity (EMICs). While none of the models incorporated the additional effects of ice sheet melting, they all projected very similar behaviour during the 21st century. Over this period the strength of MOC reduced by a best estimate of 22% (18%–25%; 5%–95% confidence limits) for RCP2.6, 26% (23%–30%) for RCP4.5, 29% (23%–35%) for RCP6.0 and 40% (36%–44%) for RCP8.5. Two of the models eventually realized a slow shutdown of the MOC under RCP8.5, although no model exhibited an abrupt change of the MOC. Through analysis of the freshwater flux across 30°–32°S into the Atlantic, it was found that 40% of the CMIP5 models were in a bistable regime of the MOC for the duration of their RCP integrations. The results support previous assessments that it is very unlikely that the MOC will undergo an abrupt change to an off state as a consequence of global warming.

Gas transport in firn: multiple-tracer characterisation and model intercomparison for NEEM, Northern Greenland

Air was sampled from the porous firn layer at the NEEM site in Northern Greenland. We use an ensemble of ten reference tracers of known atmospheric history to characterise the transport properties of the site. By analysing uncertainties in both data and the reference gas atmospheric histories, we can objectively assign weights to each of the gases used for the depth-diffusivity reconstruction. We define an objective root mean square criterion that is minimised in the model tuning procedure. Each tracer constrains the firn profile differently through its unique atmospheric history and free air diffusivity, making our multiple-tracer characterisation method a clear improvement over the commonly used single-tracer tuning. Six firn air transport models are tuned to the NEEM site; all models successfully reproduce the data within a 1σ Gaussian distribution. A comparison between two replicate boreholes drilled 64 m apart shows differences in measured mixing ratio profiles that exceed the experimental error. We find evidence that diffusivity does not vanish completely in the lock-in zone, as is commonly assumed. The ice age- gas age difference (1 age) at the firn-ice transition is calculated to be 182+3−9 yr. We further present the first intercomparison study of firn air models, where we introduce diagnostic scenarios designed to probe specific aspects of the model physics. Our results show that there are major differences in the way the models handle advective transport. Furthermore, diffusive fractionation of isotopes in the firn is poorly constrained by the models, which has consequences for attempts to reconstruct the isotopic composition of trace gases back in time using firn air and ice core records.

Real-time analysis of δ13C- and δD-CH4 in ambient air with laser spectroscopy: method development and first intercomparison results

In situ and simultaneous measurement of the three most abundant isotopologues of methane using mid-infrared laser absorption spectroscopy is demonstrated. A field-deployable, autonomous platform is realized by coupling a compact quantum cascade laser absorption spectrometer (QCLAS) to a preconcentration unit, called trace gas extractor (TREX). This unit enhances CH4 mole fractions by a factor of up to 500 above ambient levels and quantitatively separates interfering trace gases such as N2O and CO2. The analytical precision of the QCLAS isotope measurement on the preconcentrated (750 ppm, parts-per-million, µmole mole−1) methane is 0.1 and 0.5 ‰ for δ13C- and δD-CH4 at 10 min averaging time. Based on repeated measurements of compressed air during a 2-week intercomparison campaign, the repeatability of the TREX–QCLAS was determined to be 0.19 and 1.9 ‰ for δ13C and δD-CH4, respectively. In this intercomparison campaign the new in situ technique is compared to isotope-ratio mass spectrometry (IRMS) based on glass flask and bag sampling and real time CH4 isotope analysis by two commercially available laser spectrometers. Both laser-based analyzers were limited to methane mole fraction and δ13C-CH4 analysis, and only one of them, a cavity ring down spectrometer, was capable to deliver meaningful data for the isotopic composition. After correcting for scale offsets, the average difference between TREX–QCLAS data and bag/flask sampling–IRMS values are within the extended WMO compatibility goals of 0.2 and 5 ‰ for δ13C- and δD-CH4, respectively. This also displays the potential to improve the interlaboratory compatibility based on the analysis of a reference air sample with accurately determined isotopic composition.

Larcform 1 - single column model intercomparison of Arctic air formation, link to model results in NetCDF format

Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, not least because they lack or misrepresent physical processes that are specific to high latitudes. The Arctic boundary layer in winter has been observed to be in either a radiatively clear or cloudy state: The radiatively clear state is characterized by strong surface radiative cooling leading to the build-up of surface-based temperature inversions, whereas the cloudy state occurs when cloud liquid water is present in the atmospheric column, allowing little or no surface radiative cooling and leading to weaker and typically elevated temperature inversions. Many large-scale models have been shown to lack the cloudy state, and some do substantially underestimate stability in the clear state. We here present results from the first Lagrangian ARCtic air FORMation experiment (Larcform 1), a GASS (Global atmospheric system studies) single-column model intercomparison which reproduces these biases of large-scale models in an idealised setup.

An Intercomparison of Modelling Approaches for Simulating the Atmospheric Dispersion of Ammonia Emitted by Agricultural Sources

RESUMEN La dispersión del amoniaco (NH3) emitido por fuentes agrícolas en medias distancias, y su posterior deposición en el suelo y la vegetación, pueden llevar a la degradación de ecosistemas vulnerables y a la acidificación de los suelos. La deposición de NH3 suele ser mayor junto a la fuente emisora, por lo que los impactos negativos de dichas emisiones son generalmente mayores en esas zonas. Bajo la legislación comunitaria, varios estados miembros emplean modelos de dispersión inversa para estimar los impactos de las emisiones en las proximidades de las zonas naturales de especial conservación. Una revisión reciente de métodos para evaluar impactos de NH3 en distancias medias recomendaba la comparación de diferentes modelos para identificar diferencias importantes entre los métodos empleados por los distintos países de la UE. En base a esta recomendación, esta tesis doctoral compara y evalúa las predicciones de las concentraciones atmosféricas de NH3 de varios modelos bajo condiciones, tanto reales como hipotéticas, que plantean un potencial impacto sobre ecosistemas (incluidos aquellos bajo condiciones de clima Mediterráneo). En este sentido, se procedió además a la comparación y evaluación de varias técnicas de modelización inversa para inferir emisiones de NH3. Finalmente, se ha desarrollado un modelo matemático simple para calcular las concentraciones de NH3 y la velocidad de deposición de NH3 en ecosistemas vulnerables cercanos a una fuente emisora. La comparativa de modelos supuso la evaluación de cuatro modelos de dispersión (ADMS 4.1; AERMOD v07026; OPS-st v3.0.3 y LADD v2010) en un amplio rango de casos hipotéticos (dispersión de NH3 procedente de distintos tipos de fuentes agrícolas de emisión). La menor diferencia entre las concentraciones medias estimadas por los distintos modelos se obtuvo para escenarios simples. La convergencia entre las predicciones de los modelos fue mínima para el escenario relativo a la dispersión de NH3 procedente de un establo ventilado mecánicamente. En este caso, el modelo ADMS predijo concentraciones significativamente menores que los otros modelos. Una explicación de estas diferencias podríamos encontrarla en la interacción de diferentes “penachos” y “capas límite” durante el proceso de parametrización. Los cuatro modelos de dispersión fueron empleados para dos casos reales de dispersión de NH3: una granja de cerdos en Falster (Dinamarca) y otra en Carolina del Norte (EEUU). Las concentraciones medias anuales estimadas por los modelos fueron similares para el caso americano (emisión de granjas ventiladas de forma natural y balsa de purines). La comparación de las predicciones de los modelos con concentraciones medias anuales medidas in situ, así como la aplicación de los criterios establecidos para la aceptación estadística de los modelos, permitió concluir que los cuatro modelos se comportaron aceptablemente para este escenario. No ocurrió lo mismo en el caso danés (nave ventilada mecánicamente), en donde el modelo LADD no dio buenos resultados debido a la ausencia de procesos de “sobreelevacion de penacho” (plume-rise). Los modelos de dispersión dan a menudo pobres resultados en condiciones de baja velocidad de viento debido a que la teoría de dispersión en la que se basan no es aplicable en estas condiciones. En situaciones de frecuente descenso en la velocidad del viento, la actual guía de modelización propone usar un modelo que sea eficaz bajo dichas condiciones, máxime cuando se realice una valoración que tenga como objeto establecer una política de regularización. Esto puede no ser siempre posible debido a datos meteorológicos insuficientes, en cuyo caso la única opción sería utilizar un modelo más común, como la versión avanzada de los modelos Gausianos ADMS o AERMOD. Con el objetivo de evaluar la idoneidad de estos modelos para condiciones de bajas velocidades de viento, ambos modelos fueron utilizados en un caso con condiciones Mediterráneas. Lo que supone sucesivos periodos de baja velocidad del viento. El estudio se centró en la dispersión de NH3 procedente de una granja de cerdos en Segovia (España central). Para ello la concentración de NH3 media mensual fue medida en 21 localizaciones en torno a la granja. Se realizaron también medidas de concentración de alta resolución en una única localización durante una campaña de una semana. En este caso, se evaluaron dos estrategias para mejorar la respuesta del modelo ante bajas velocidades del viento. La primera se basó en “no zero wind” (NZW), que sustituyó periodos de calma con el mínimo límite de velocidad del viento y “accumulated calm emissions” (ACE), que forzaban al modelo a calcular las emisiones totales en un periodo de calma y la siguiente hora de no-calma. Debido a las importantes incertidumbres en los datos de entrada del modelo (inputs) (tasa de emisión de NH3, velocidad de salida de la fuente, parámetros de la capa límite, etc.), se utilizó el mismo caso para evaluar la incertidumbre en la predicción del modelo y valorar como dicha incertidumbre puede ser considerada en evaluaciones del modelo. Un modelo dinámico de emisión, modificado para el caso de clima Mediterráneo, fue empleado para estimar la variabilidad temporal en las emisiones de NH3. Así mismo, se realizó una comparativa utilizando las emisiones dinámicas y la tasa constante de emisión. La incertidumbre predicha asociada a la incertidumbre de los inputs fue de 67-98% del valor medio para el modelo ADMS y entre 53-83% del valor medio para AERMOD. La mayoría de esta incertidumbre se debió a la incertidumbre del ratio de emisión en la fuente (50%), seguida por la de las condiciones meteorológicas (10-20%) y aquella asociada a las velocidades de salida (5-10%). El modelo AERMOD predijo mayores concentraciones que ADMS y existieron más simulaciones que alcanzaron los criterios de aceptabilidad cuando se compararon las predicciones con las concentraciones medias anuales medidas. Sin embargo, las predicciones del modelo ADMS se correlacionaron espacialmente mejor con las mediciones. El uso de valores dinámicos de emisión estimados mejoró el comportamiento de ADMS, haciendo empeorar el de AERMOD. La aplicación de estrategias destinadas a mejorar el comportamiento de este último tuvo efectos contradictorios similares. Con el objeto de comparar distintas técnicas de modelización inversa, varios modelos (ADMS, LADD y WindTrax) fueron empleados para un caso no agrícola, una colonia de pingüinos en la Antártida. Este caso fue empleado para el estudio debido a que suponía la oportunidad de obtener el primer factor de emisión experimental para una colonia de pingüinos antárticos. Además las condiciones eran propicias desde el punto de vista de la casi total ausencia de concentraciones ambiente (background). Tras el trabajo de modelización existió una concordancia suficiente entre las estimaciones obtenidas por los tres modelos. De este modo se pudo definir un factor de emisión de para la colonia de 1.23 g NH3 por pareja criadora por día (con un rango de incertidumbre de 0.8-2.54 g NH3 por pareja criadora por día). Posteriores aplicaciones de técnicas de modelización inversa para casos agrícolas mostraron también un buen compromiso estadístico entre las emisiones estimadas por los distintos modelos. Con todo ello, es posible concluir que la modelización inversa es una técnica robusta para estimar tasas de emisión de NH3. Modelos de selección (screening) permiten obtener una rápida y aproximada estimación de los impactos medioambientales, siendo una herramienta útil para evaluaciones de impactos en tanto que permite eliminar casos que presentan un riesgo potencial de daño bajo. De esta forma, lo recursos del modelo pueden Resumen (Castellano) destinarse a casos en donde la posibilidad de daño es mayor. El modelo de Cálculo Simple de los Límites de Impacto de Amoniaco (SCAIL) se desarrolló para obtener una estimación de la concentración media de NH3 y de la tasa de deposición seca asociadas a una fuente agrícola. Está técnica de selección, basada en el modelo LADD, fue evaluada y calibrada con diferentes bases de datos y, finalmente, validada utilizando medidas independientes de concentraciones realizadas cerca de las fuentes. En general SCAIL dio buenos resultados de acuerdo a los criterios estadísticos establecidos. Este trabajo ha permitido definir situaciones en las que las concentraciones predichas por modelos de dispersión son similares, frente a otras en las que las predicciones difieren notablemente entre modelos. Algunos modelos nos están diseñados para simular determinados escenarios en tanto que no incluyen procesos relevantes o están más allá de los límites de su aplicabilidad. Un ejemplo es el modelo LADD que no es aplicable en fuentes con velocidad de salida significativa debido a que no incluye una parametrización de sobreelevacion del penacho. La evaluación de un esquema simple combinando la sobreelevacion del penacho y una turbulencia aumentada en la fuente mejoró el comportamiento del modelo. Sin embargo más pruebas son necesarias para avanzar en este sentido. Incluso modelos que son aplicables y que incluyen los procesos relevantes no siempre dan similares predicciones. Siendo las razones de esto aún desconocidas. Por ejemplo, AERMOD predice mayores concentraciones que ADMS para dispersión de NH3 procedente de naves de ganado ventiladas mecánicamente. Existe evidencia que sugiere que el modelo ADMS infraestima concentraciones en estas situaciones debido a un elevado límite de velocidad de viento. Por el contrario, existen evidencias de que AERMOD sobreestima concentraciones debido a sobreestimaciones a bajas Resumen (Castellano) velocidades de viento. Sin embrago, una modificación simple del pre-procesador meteorológico parece mejorar notablemente el comportamiento del modelo. Es de gran importancia que estas diferencias entre las predicciones de los modelos sean consideradas en los procesos de evaluación regulada por los organismos competentes. Esto puede ser realizado mediante la aplicación del modelo más útil para cada caso o, mejor aún, mediante modelos múltiples o híbridos. ABSTRACT Short-range atmospheric dispersion of ammonia (NH3) emitted by agricultural sources and its subsequent deposition to soil and vegetation can lead to the degradation of sensitive ecosystems and acidification of the soil. Atmospheric concentrations and dry deposition rates of NH3 are generally highest near the emission source and so environmental impacts to sensitive ecosystems are often largest at these locations. Under European legislation, several member states use short-range atmospheric dispersion models to estimate the impact of ammonia emissions on nearby designated nature conservation sites. A recent review of assessment methods for short-range impacts of NH3 recommended an intercomparison of the different models to identify whether there are notable differences to the assessment approaches used in different European countries. Based on this recommendation, this thesis compares and evaluates the atmospheric concentration predictions of several models used in these impact assessments for various real and hypothetical scenarios, including Mediterranean meteorological conditions. In addition, various inverse dispersion modelling techniques for the estimation of NH3 emissions rates are also compared and evaluated and a simple screening model to calculate the NH3 concentration and dry deposition rate at a sensitive ecosystem located close to an NH3 source was developed. The model intercomparison evaluated four atmospheric dispersion models (ADMS 4.1; AERMOD v07026; OPS-st v3.0.3 and LADD v2010) for a range of hypothetical case studies representing the atmospheric dispersion from several agricultural NH3 source types. The best agreement between the mean annual concentration predictions of the models was found for simple scenarios with area and volume sources. The agreement between the predictions of the models was worst for the scenario representing the dispersion from a mechanically ventilated livestock house, for which ADMS predicted significantly smaller concentrations than the other models. The reason for these differences appears to be due to the interaction of different plume-rise and boundary layer parameterisations. All four dispersion models were applied to two real case studies of dispersion of NH3 from pig farms in Falster (Denmark) and North Carolina (USA). The mean annual concentration predictions of the models were similar for the USA case study (emissions from naturally ventilated pig houses and a slurry lagoon). The comparison of model predictions with mean annual measured concentrations and the application of established statistical model acceptability criteria concluded that all four models performed acceptably for this case study. This was not the case for the Danish case study (mechanically ventilated pig house) for which the LADD model did not perform acceptably due to the lack of plume-rise processes in the model. Regulatory dispersion models often perform poorly in low wind speed conditions due to the model dispersion theory being inapplicable at low wind speeds. For situations with frequent low wind speed periods, current modelling guidance for regulatory assessments is to use a model that can handle these conditions in an acceptable way. This may not always be possible due to insufficient meteorological data and so the only option may be to carry out the assessment using a more common regulatory model, such as the advanced Gaussian models ADMS or AERMOD. In order to assess the suitability of these models for low wind conditions, they were applied to a Mediterranean case study that included many periods of low wind speed. The case study was the dispersion of NH3 emitted by a pig farm in Segovia, Central Spain, for which mean monthly atmospheric NH3 concentration measurements were made at 21 locations surrounding the farm as well as high-temporal-resolution concentration measurements at one location during a one-week campaign. Two strategies to improve the model performance for low wind speed conditions were tested. These were ‘no zero wind’ (NZW), which replaced calm periods with the minimum threshold wind speed of the model and ‘accumulated calm emissions’ (ACE), which forced the model to emit the total emissions during a calm period during the first subsequent non-calm hour. Due to large uncertainties in the model input data (NH3 emission rates, source exit velocities, boundary layer parameters), the case study was also used to assess model prediction uncertainty and assess how this uncertainty can be taken into account in model evaluations. A dynamic emission model modified for the Mediterranean climate was used to estimate the temporal variability in NH3 emission rates and a comparison was made between the simulations using the dynamic emissions and a constant emission rate. Prediction uncertainty due to model input uncertainty was 67-98% of the mean value for ADMS and between 53-83% of the mean value for AERMOD. Most of this uncertainty was due to source emission rate uncertainty (~50%), followed by uncertainty in the meteorological conditions (~10-20%) and uncertainty in exit velocities (~5-10%). AERMOD predicted higher concentrations than ADMS and more of the simulations met the model acceptability criteria when compared with the annual mean measured concentrations. However, the ADMS predictions were better correlated spatially with the measurements. The use of dynamic emission estimates improved the performance of ADMS but worsened the performance of AERMOD and the application of strategies to improved model performance had similar contradictory effects. In order to compare different inverse modelling techniques, several models (ADMS, LADD and WindTrax) were applied to a non-agricultural case study of a penguin colony in Antarctica. This case study was used since it gave the opportunity to provide the first experimentally-derived emission factor for an Antarctic penguin colony and also had the advantage of negligible background concentrations. There was sufficient agreement between the emission estimates obtained from the three models to define an emission factor for the penguin colony (1.23 g NH3 per breeding pair per day with an uncertainty range of 0.8-2.54 g NH3 per breeding pair per day). This emission estimate compared favourably to the value obtained using a simple micrometeorological technique (aerodynamic gradient) of 0.98 g ammonia per breeding pair per day (95% confidence interval: 0.2-2.4 g ammonia per breeding pair per day). Further application of the inverse modelling techniques for a range of agricultural case studies also demonstrated good agreement between the emission estimates. It is concluded, therefore, that inverse dispersion modelling is a robust technique for estimating NH3 emission rates. Screening models that can provide a quick and approximate estimate of environmental impacts are a useful tool for impact assessments because they can be used to filter out cases that potentially have a minimal environmental impact allowing resources to be focussed on more potentially damaging cases. The Simple Calculation of Ammonia Impact Limits (SCAIL) model was developed as a screening model to provide an estimate of the mean NH3 concentration and dry deposition rate downwind of an agricultural source. This screening tool, based on the LADD model, was evaluated and calibrated with several experimental datasets and then validated using independent concentration measurements made near sources. Overall SCAIL performed acceptably according to established statistical criteria. This work has identified situations where the concentration predictions of dispersion models are similar and other situations where the predictions are significantly different. Some models are simply not designed to simulate certain scenarios since they do not include the relevant processes or are beyond the limits of their applicability. An example is the LADD model that is not applicable to sources with significant exit velocity since the model does not include a plume-rise parameterisation. The testing of a simple scheme combining a momentum-driven plume rise and increased turbulence at the source improved model performance, but more testing is required. Even models that are applicable and include the relevant process do not always give similar predictions and the reasons for this need to be investigated. AERMOD for example predicts higher concentrations than ADMS for dispersion from mechanically ventilated livestock housing. There is evidence to suggest that ADMS underestimates concentrations in these situations due to a high wind speed threshold. Conversely, there is also evidence that AERMOD overestimates concentrations in these situations due to overestimation at low wind speeds. However, a simple modification to the meteorological pre-processor appears to improve the performance of the model. It is important that these differences between the predictions of these models are taken into account in regulatory assessments. This can be done by applying the most suitable model for the assessment in question or, better still, using multiple or hybrid models.