PM2.5-bound oxygenated PAHs, nitro-PAHs and parent-PAHs from the atmosphere of a Chinese megacity: seasonal variation, sources and cancer risk assessment

Polycyclic aromatic compounds (PACs) in air particulate matter contribute considerably to the health risk of air pollution. The objectives of this study were to assess the occurrence and variation in concentrations and sources of PM2.5-bound PACs [Oxygenated PAHs (OPAHs), nitro-PAHs and parent-PAHs] sampled from the atmosphere of a typical Chinese megacity (Xi'an), to study the influence of meteorological conditions on PACs and to estimate the lifetime excess cancer risk to the residents of Xi'an (from inhalation of PM2.5-bound PACs). To achieve these objectives, we sampled 24-h PM2.5 aerosols (once in every 6 days, from 5 July 2008 to 8 August 2009) from the atmosphere of Xi'an and measured the concentrations of PACs in them. The PM2.5-bound concentrations of Σcarbonyl-OPAHs, ∑ hydroxyl + carboxyl-OPAHs, Σnitro-PAHs and Σalkyl + parent-PAHs ranged between 5–22, 0.2–13, 0.3–7, and 7–387 ng m− 3, respectively, being markedly higher than in most western cities. This represented a range of 0.01–0.4% and 0.002–0.06% of the mass of organic C in PM2.5 and the total mass of PM2.5, respectively. The sums of the concentrations of each compound group had winter-to-summer ratios ranging from 3 to 8 and most individual OPAHs and nitro-PAHs had higher concentrations in winter than in summer, suggesting a dominant influence of emissions from household heating and winter meteorological conditions. Ambient temperature, air pressure, and wind speed explained a large part of the temporal variation in PACs concentrations. The lifetime excess cancer risk from inhalation (attributable to selected PAHs and nitro-PAHs) was six fold higher in winter (averaging 1450 persons per million residents of Xi'an) than in summer. Our results call for the development of emission control measures.

Understanding the performance of the FLake model over two African Great Lakes

The ability of the one-dimensional lake model FLake to represent the mixolimnion temperatures for tropical conditions was tested for three locations in East Africa: Lake Kivu and Lake Tanganyika's northern and southern basins. Meteorological observations from surrounding automatic weather stations were corrected and used to drive FLake, whereas a comprehensive set of water temperature profiles served to evaluate the model at each site. Careful forcing data correction and model configuration made it possible to reproduce the observed mixed layer seasonality at Lake Kivu and Lake Tanganyika (northern and southern basins), with correct representation of both the mixed layer depth and water temperatures. At Lake Kivu, mixolimnion temperatures predicted by FLake were found to be sensitive both to minimal variations in the external parameters and to small changes in the meteorological driving data, in particular wind velocity. In each case, small modifications may lead to a regime switch, from the correctly represented seasonal mixed layer deepening to either completely mixed or permanently stratified conditions from similar to 10 m downwards. In contrast, model temperatures were found to be robust close to the surface, with acceptable predictions of near-surface water temperatures even when the seasonal mixing regime is not reproduced. FLake can thus be a suitable tool to parameterise tropical lake water surface temperatures within atmospheric prediction models. Finally, FLake was used to attribute the seasonal mixing cycle at Lake Kivu to variations in the near-surface meteorological conditions. It was found that the annual mixing down to 60m during the main dry season is primarily due to enhanced lake evaporation and secondarily to the decreased incoming long wave radiation, both causing a significant heat loss from the lake surface and associated mixolimnion cooling.

Assessment of the performance of 3m 3500 organic vapor monitors over extended sampling durations

The purpose of this study was to assess the accuracy and precision of airborne volatile organic compound (VOC) concentrations measured using passive air samplers (3M 3500 organic vapor monitors) over extended sampling durations (9 and 15 days). A total of forty-five organic vapor monitor samples were collected at a State of Texas air monitoring site during two different sampling periods (July/August and November 2008). The results of this study indicate that for most of the tested compounds, there was no significant difference between long-term (9 or 15 days) sample concentrations and the means of parallel consecutive short-term (3 days) sample concentrations. Biases of 9 or 15-day measurements vs. consecutive 3-day measurements showed considerable variability. Those compounds that had percent bias values of <10% are suggested as acceptable for long-term sampling (9 and 15 days). Of the twenty-one compounds examined, 10 compounds are classified as acceptable for long-term sampling; these include m,p-xylene, 1,2,4-trimethylbenzene, n-hexane, ethylbenzene, benzene, toluene, o-xylene, d-limonene, dimethylpentane and methyl tertbutyl ether. The ratio of sampling procedure variability relative to variability within days was approximately 1.89 for both sampling periods for the 3-day vs. 9-day comparisons and approximately 2.19 for both sampling periods for the 3-day vs. 15-day comparisons. Considerably higher concentrations of most VOCs were measured during the November sampling period compared to the July/August period. These differences may be a result of varying meteorological conditions during these two time periods, e.g., the differences in wind direction, and wind speed. Further studies are suggested to further evaluate the accuracy and precision of 3M 3500 organic vapor monitors over extended sampling durations. ^

Water stable oxygen isotope records from six Antarctic ice core sites for the present and last interglacial periods

We compare the present and last interglacial periods as recorded in Antarctic water stable isotope records now available at various temporal resolutions from six East Antarctic ice cores: Vostok, Taylor Dome, EPICA Dome C (EDC), EPICA Dronning Maud Land (EDML), Dome Fuji and the recent TALDICE ice core from Talos Dome. We first review the different modern site characteristics in terms of ice flow, meteorological conditions, precipitation intermittency and moisture origin, as depicted by meteorological data, atmospheric reanalyses and Lagrangian moisture source diagnostics. These different factors can indeed alter the relationships between temperature and water stable isotopes. Using five records with sufficient resolution on the EDC3 age scale, common features are quantified through principal component analyses. Consistent with instrumental records and atmospheric model results, the ice core data depict rather coherent and homogenous patterns in East Antarctica during the last two interglacials. Across the East Antarctic plateau, regional differences, with respect to the common East Antarctic signal, appear to have similar patterns during the current and last interglacials. We identify two abrupt shifts in isotopic records during the glacial inception at TALDICE and EDML, likely caused by regional sea ice expansion. These regional differences are discussed in terms of moisture origin and in terms of past changes in local elevation histories, which are compared to ice sheet model results. Our results suggest that elevation changes may contribute significantly to inter-site differences. These elevation changes may be underestimated by current ice sheet models

Radiance, irradiance, and remote sensing reflectance during the North Sea Coast Harmful Algal Bloom (NORCOHAB II) HEINCKE cruise HE302

In this study four data quality flags are presented for automated and unmanned above-water hyperspectral optical measurements collected underway in the North Sea, The Minch, Irish Sea and Celtic Sea in April/May 2009. Coincident to these optical measurements a DualDome D12 (Mobotix, Germany) camera system was used to capture sea surface and sky images. The first three flags are based on meteorological conditions, to select erroneous incoming solar irradiance (ES) taken during dusk, dawn, before significant incoming solar radiation could be detected or under rainfall. Furthermore, the relative azimuthal angle of the optical sensors to the sun is used to identify possible sunglint free sea surface zones. A total of 629 spectra remained after applying the meteorological masks (first three flags). Based on this dataset, a fourth flag for sunglint was generated by analysing and evaluating water leaving radiance (LW) and remote sensing reflectance (RRS) spectral behaviour in the presence and absence of sunglint salient in the simultaneously available sea surface images. Spectra conditions satisfying "mean LW (700-950 nm) < 2 mW/m**2/nm/Sr" or alternatively "minimum RRS (700-950 nm) < 0.010/Sr", mask the most measurements affected by sunglint, providing efficient flagging of sunglint in automated quality control. It is confirmed that valid optical measurements can be performed 0° <= theta <= 360° although 90° <= theta <= 135° is recommended.

Ice and snow measurements during Nathaniel B. Palmer cruise NBP0709 (SIMBA experiment)

The Sea Ice Mass Balance in the Antarctic (SIMBA) experiment was conducted from the RVIB N.B. Palmer in September and October 2007 in the Bellingshausen Sea in an area recently experiencing considerable changes in both climate and sea ice cover. Snow and ice properties were observed at 3 short-term stations and a 27-day drift station (Ice Station Belgica, ISB) during the winter-spring transition. Repeat measurements were performed on sea ice and snow cover at 5 ISB sites, each having different physical characteristics, with mean ice (snow) thicknesses varying from 0.6 m (0.1 m) to 2.3 m (0.7 m). Ice cores retrieved every five days from 2 sites and measured for physical, biological, and chemical properties. Three ice mass-balance buoys (IMBs) provided continuous records of snow and ice thickness and temperature. Meteorological conditions changed from warm fronts with high winds and precipitation followed by cold and calm periods through four cycles during ISB. The snow cover regulated temperature flux and controlled the physical regime in which sea ice morphology changed. Level thin ice areas had little snow accumulation and experienced greater thermal fluctuations resulting in brine salinity and volume changes, and winter maximum thermodynamic growth of ~0.6 m in this region. Flooding and snow-ice formation occurred during cold spells in ice and snow of intermediate thickness. In contrast, little snow-ice formed in flooded areas with thicker ice and snow cover, instead nearly isothermal, highly permeable ice persisted. In spring, short-lived cold air episodes did not effectively penetrate the sea ice nor overcome the effect of ocean heat flux, thus favoring net ice thinning from bottom melt over ice thickening from snow-ice growth, in all cases. These warm ice conditions were consistent with regional remote sensing observations of earlier ice breakup and a shorter sea ice season, more recently observed in the Bellingshausen Sea.

Sediments in arctic sea ice - entrainment, characterization and quantification

Sediments in Arctic sea ice are important for erosion and redistribution and consequently a factor for the sediment budget of the Arctic Ocean. The processes leading to the incorporation of sediments into the ice are not understood in detail yet. In the present study, experiments on the incorporation of sediments were therefore conducted in ice tanks of The Hamburg Ship Model Basin (HSVA) in winter 1996/1997, These experiments showed that on average 75 % of the artificial sea-ice sediments were located in the brine-channel system. The sediments were scavenged from the water column by frazil ice. Sediments functioning as a nucleus for the formation of frazil ice were less important for the incorporation. Filtration in grease ice during relatively calm hydrodynamic conditions was probably an effective process to enrich sediments in the ice. Wave fields did not play an important role for the incorporation of sediments into the artificial sea ice. During the expedition TRANSDRIFT III (TDIII, October 1995), different types of natural, newly-formed sea ice (grease ice, nilas and young ice) were sampled in the inner Laptev Sea at the time of freeze-up. The incorporation of sediments took place during calm meteorological conditions then. The characteristics of the clay mineral assemblages of these sedirnents served as references for sea-ice sediments which were sampled from first-year drift ice in the outer Laptev Sea and the adjacent Arctic Ocean during the POLARSTERN expedition ARK-XI/1 (July-September 1995). Based on the clay mineral assemblages, probable incorporation areas for the sedirnents in first-year drift ice could be statistically reconstructed in the inner Laptev Sea (eastern, central, and Western Laptev Sea) as well as in adjacent regions. Comparing the amounts of particulate organic carbon (POC) in sea-ice sediments and in surface sediments from the shelves of potential incorporation areas often reveals higher values in sea-ice sediments (TDIII: 3.6 %DM; ARK-XI/1: 2.3 %DM). This enrichment of POC is probably due to the incorporation process into the sea ice, as could be deducted from maceral analysis and Rock-Eval pyrolysis. Both methods were applied in the present study to particulate organic material (POM) from sea-ice sediments for the first time. It was shown that the POM of the sea-ice sediments from the Laptev Sea and the adjacent Arctic Ocean was dominated by reworked, strongly fragmented, allochthonous (terrigenous) material. This terrigenous component accounted for more than 75 % of all counted macerals. The autochthonous (marine) component was also strongly fragmented, and higher in the sediments from newly-formed sea ice (24 % of all counted macerals) as compared to first-year drift ice (17 % of all counted macerals). Average hydroge indices confirmed this pattern and were in the transition zone between kerogen types II and III (TDIII: 275 mg KW/g POC; ARK-XI/1: 200 mg KW/g POC). The sediment loads quantified in natural sea ice (TDIII: 33.6 mg/l, ARK-XI/1: 49.0 mg/l) indicated that sea-ice sediments are an important factor for the sediment budget in the Laptev Sea. In particular during the incorporation phase in autumn and early winter, about 12 % of the sediment load imported annually by rivers into the Laptev Sea can be incorporated into sea ice and redistributed during calm meteorological conditions. Single entrainment events can incorporate about 35 % of the river input into the sea ice (ca. 9 x 10**6 t) and export it via the Transpolar Drift from the Eurasian shelf to the Fram Strait.

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.

Levels, sources and seasonality of coarse particles (PM10-PM2.5) in three European capitals e implications for particulate pollution control

Coarse particles of aerodynamic diameter between 2.5 and 10 mm (PMc) are produced by a range of natural (windblown dust and sea sprays) and anthropogenic processes (non-exhaust vehicle emissions, industrial, agriculture, construction and quarrying activities). Although current ambient air quality regulations focus on PM2.5 and PM10, coarse particles are of interest from a public health point of view as they have been associated with certain mortality and morbidity outcomes. In this paper, an analysis of coarse particle levels in three European capitals (London, Madrid and Athens) is presented and discussed. For all three cities we analysed data from both traffic and urban background monitoring sites. The results showed that the levels of coarse particles present significant seasonal, weekly and daily variability. Their wind driven and non-wind driven resuspension as well as their roadside increment due to traffic were estimated. Both the local meteorological conditions and the air mass history indicating long-range atmospheric transport of particles of natural origin are significant parameters that influence the levels of coarse particles in the three cities especially during episodic events.

Atmospheric modelling of tritium forms transport: review of capabilities and R&D needs for the assessment of fusion facilities environmental impact

One of the key scrutiny issues of new coming energy era would be the environmental impact of fusion facilities managing one kg of tritium. The potential change of committed dose regulatory limits together with the implementation of nuclear design principles (As Low as Reasonably achievable - ALARA -, Defense in Depth -D-i-D-) for fusion facilities could strongly impact on the cost of deployment of coming fusion technology. Accurate modeling of environmental tritium transport forms (HT, HTO) for the assessment of fusion facility dosimetric impact in Accidental case appears as of major interest. This paper considers different short-term releases of tritium forms (HT and HTO) to the atmosphere from a potential fusion reactor located in the Mediterranean Basin. This work models in detail the dispersion of tritium forms and dosimetric impact of selected environmental patterns both inland and in-sea using real topography and forecast meteorological data-fields (ECMWF/FLEXPART). We explore specific values of this ratio in different levels and we examine the influence of meteorological conditions in the HTO behavior for 24 hours. For this purpose we have used a tool which consists on a coupled Lagrangian ECMWF/FLEXPART model useful to follow real time releases of tritium at 10, 30 and 60 meters together with hourly observations of wind (and in some cases precipitations) to provide a short-range approximation of tritium cloud behavior. We have assessed inhalation doses. And also HTO/HT ratios in a representative set of cases during winter 2010 and spring 2011 for the 3 air levels.