Atmospheric nitrate concentrations and isotope composition for samples collected in the marine boundary layer in 2006 and 2007

The comprehensive isotopic composition of atmospheric nitrate (i.e., the simultaneous measurement of all its stable isotope ratios: 15N/14N, 17O/16O and 18O/16O) has been determined for aerosol samples collected in the marine boundary layer (MBL) over the Atlantic Ocean from 65°S (Weddell Sea) to 79°N (Svalbard), along a ship-borne latitudinal transect. In nonpolar areas, the d15N of nitrate mostly deriving from anthropogenically emitted NOx is found to be significantly different (from 0 to 6 per mil) from nitrate sampled in locations influenced by natural NOx sources (-4 ± 2) per mil. The effects on d15N(NO3-) of different NOx sources and nitrate removal processes associated with its atmospheric transport are discussed. Measurements of the oxygen isotope anomaly (D17O = d17O - 0.52 × d18O) of nitrate suggest that nocturnal processes involving the nitrate radical play a major role in terms of NOx sinks. Different D17O between aerosol size fractions indicate different proportions between nitrate formation pathways as a function of the size and composition of the particles. Extremely low d15N values (down to -40 per mil) are found in air masses exposed to snow-covered areas, showing that snowpack emissions of NOx from upwind regions can have a significant impact on the local surface budget of reactive nitrogen, in conjunction with interactions with active halogen chemistry. The implications of the results are discussed in light of the potential use of the stable isotopic composition of nitrate to infer atmospherically relevant information from nitrate preserved in ice cores.

Anthropogenic aerosol emissions and rainfall decline in South-West Australia - accompanying model results in NetCDF format

It is commonly understood that the observed decline in precipitation in South-West Australia during the 20th century is caused by anthropogenic factors. Candidates therefore are changes to large-scale atmospheric circulations due to global warming, extensive deforestation and anthropogenic aerosol emissions - all of which are effective on different spatial and temporal scales. This contribution focusses on the role of rapidly rising aerosol emissions from anthropogenic sources in South-West Australia around 1970. An analysis of historical longterm rainfall data of the Bureau of Meteorology shows that South-West Australia as a whole experienced a gradual decline in precipitation over the 20th century. However, on smaller scales and for the particular example of the Perth catchment area, a sudden drop in precipitation around 1970 is apparent. Modelling experiments at a convection-resolving resolution of 3.3km using the Weather and Research Forecasting (WRF) model version 3.6.1 with the aerosol-aware Thompson-Eidhammer microphysics scheme are conducted for the period 1970-1974. A comparison of four runs with different prescribed aerosol emissions and without aerosol effects demonstrates that tripling the pre-1960s atmospheric CCN and IN concentrations can suppress precipitation by 2-9%, depending on the area and the season. This suggests that a combination of all three processes is required to account for the gradual decline in rainfall seen for greater South-West Australia and for the sudden drop observed in areas along the West Coast in the 1970s: changing atmospheric circulations, deforestation and anthropogenic aerosol emissions.

Aplicación de técnicas de inteligencia artificial a la predicción de contaminantes atmosféricos

Abstract Air pollution is a big threat and a phenomenon that has a specific impact on human health, in addition, changes that occur in the chemical composition of the atmosphere can change the weather and cause acid rain or ozone destruction. Those are phenomena of global importance. The World Health Organization (WHO) considerates air pollution as one of the most important global priorities. Salamanca, Gto., Mexico has been ranked as one of the most polluted cities in this country. The industry of the area led to a major economic development and rapid population growth in the second half of the twentieth century. The impact in the air quality is important and significant efforts have been made to measure the concentrations of pollutants. The main pollution sources are locally based plants in the chemical and power generation sectors. The registered concerning pollutants are Sulphur Dioxide (SO2) and particles on the order of ∼10 micrometers or less (PM10). The prediction in the concentration of those pollutants can be a powerful tool in order to take preventive measures such as the reduction of emissions and alerting the affected population. In this PhD thesis we propose a model to predict concentrations of pollutants SO2 and PM10 for each monitoring booth in the Atmospheric Monitoring Network Salamanca (REDMAS - for its spanish acronym). The proposed models consider the use of meteorological variables as factors influencing the concentration of pollutants. The information used along this work is the current real data from REDMAS. In the proposed model, Artificial Neural Networks (ANN) combined with clustering algorithms are used. The type of ANN used is the Multilayer Perceptron with a hidden layer, using separate structures for the prediction of each pollutant. The meteorological variables used for prediction were: Wind Direction (WD), wind speed (WS), Temperature (T) and relative humidity (RH). Clustering algorithms, K-means and Fuzzy C-means, are used to find relationships between air pollutants and weather variables under consideration, which are added as input of the RNA. Those relationships provide information to the ANN in order to obtain the prediction of the pollutants. The results of the model proposed in this work are compared with the results of a multivariate linear regression and multilayer perceptron neural network. The evaluation of the prediction is calculated with the mean absolute error, the root mean square error, the correlation coefficient and the index of agreement. The results show the importance of meteorological variables in the prediction of the concentration of the pollutants SO2 and PM10 in the city of Salamanca, Gto., Mexico. The results show that the proposed model perform better than multivariate linear regression and multilayer perceptron neural network. The models implemented for each monitoring booth have the ability to make predictions of air quality that can be used in a system of real-time forecasting and human health impact analysis. Among the main results of the development of this thesis we can cite: A model based on artificial neural network combined with clustering algorithms for prediction with a hour ahead of the concentration of each pollutant (SO2 and PM10) is proposed. A different model was designed for each pollutant and for each of the three monitoring booths of the REDMAS. A model to predict the average of pollutant concentration in the next 24 hours of pollutants SO2 and PM10 is proposed, based on artificial neural network combined with clustering algorithms. Model was designed for each booth of the REDMAS and each pollutant separately. Resumen La contaminación atmosférica es una amenaza aguda, constituye un fenómeno que tiene particular incidencia sobre la salud del hombre. Los cambios que se producen en la composición química de la atmósfera pueden cambiar el clima, producir lluvia ácida o destruir el ozono, fenómenos todos ellos de una gran importancia global. La Organización Mundial de la Salud (OMS) considera la contaminación atmosférica como una de las más importantes prioridades mundiales. Salamanca, Gto., México; ha sido catalogada como una de las ciudades más contaminadas en este país. La industria de la zona propició un importante desarrollo económico y un crecimiento acelerado de la población en la segunda mitad del siglo XX. Las afectaciones en el aire son graves y se han hecho importantes esfuerzos por medir las concentraciones de los contaminantes. Las principales fuentes de contaminación son fuentes fijas como industrias químicas y de generación eléctrica. Los contaminantes que se han registrado como preocupantes son el Bióxido de Azufre (SO2) y las Partículas Menores a 10 micrómetros (PM10). La predicción de las concentraciones de estos contaminantes puede ser una potente herramienta que permita tomar medidas preventivas como reducción de emisiones a la atmósfera y alertar a la población afectada. En la presente tesis doctoral se propone un modelo de predicción de concentraci ón de los contaminantes más críticos SO2 y PM10 para cada caseta de monitorización de la Red de Monitorización Atmosférica de Salamanca (REDMAS). Los modelos propuestos plantean el uso de las variables meteorol ógicas como factores que influyen en la concentración de los contaminantes. La información utilizada durante el desarrollo de este trabajo corresponde a datos reales obtenidos de la REDMAS. En el Modelo Propuesto (MP) se aplican Redes Neuronales Artificiales (RNA) combinadas con algoritmos de agrupamiento. La RNA utilizada es el Perceptrón Multicapa con una capa oculta, utilizando estructuras independientes para la predicción de cada contaminante. Las variables meteorológicas disponibles para realizar la predicción fueron: Dirección de Viento (DV), Velocidad de Viento (VV), Temperatura (T) y Humedad Relativa (HR). Los algoritmos de agrupamiento K-means y Fuzzy C-means son utilizados para encontrar relaciones existentes entre los contaminantes atmosféricos en estudio y las variables meteorológicas. Dichas relaciones aportan información a las RNA para obtener la predicción de los contaminantes, la cual es agregada como entrada de las RNA. Los resultados del modelo propuesto en este trabajo son comparados con los resultados de una Regresión Lineal Multivariable (RLM) y un Perceptrón Multicapa (MLP). La evaluación de la predicción se realiza con el Error Medio Absoluto, la Raíz del Error Cuadrático Medio, el coeficiente de correlación y el índice de acuerdo. Los resultados obtenidos muestran la importancia de las variables meteorológicas en la predicción de la concentración de los contaminantes SO2 y PM10 en la ciudad de Salamanca, Gto., México. Los resultados muestran que el MP predice mejor la concentración de los contaminantes SO2 y PM10 que los modelos RLM y MLP. Los modelos implementados para cada caseta de monitorizaci ón tienen la capacidad para realizar predicciones de calidad del aire, estos modelos pueden ser implementados en un sistema que permita realizar la predicción en tiempo real y analizar el impacto en la salud de la población. Entre los principales resultados obtenidos del desarrollo de esta tesis podemos citar: Se propone un modelo basado en una red neuronal artificial combinado con algoritmos de agrupamiento para la predicción con una hora de anticipaci ón de la concentración de cada contaminante (SO2 y PM10). Se diseñó un modelo diferente para cada contaminante y para cada una de las tres casetas de monitorización de la REDMAS. Se propone un modelo de predicción del promedio de la concentración de las próximas 24 horas de los contaminantes SO2 y PM10, basado en una red neuronal artificial combinado con algoritmos de agrupamiento. Se diseñó un modelo para cada caseta de monitorización de la REDMAS y para cada contaminante por separado.

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.

An upper atmospheric probe for auroral effects

An electrically floating bare tether in LEO orbit may serve as upper atmospheric probe. Ambient ions bombard the negatively biased tether and liberate secondary electrons, which accelerate through the same voltage to form a magnetically guided planar e-beam resulting in auroral effects at the E-layer. This beam is free from the S/C charging and plasma interaction problems of standard e-beams. The energy flux is weak but varies accross the large beam cross section, allowing continuous observation from the S/C. A brightness scan of line-integrated emissions, that mix emitting altitudes and tether points originating the electrons, is analysed. The tether is magnetically dragged at nighttime operation, when power supply and plasma contactor at the S/C are off for electrical floating; power and contactor are on at daytime for partial current reversal, resulting in thrust. System requirements for keeping average orbital height are discussed.

The application of inverse-dispersion and gradient methods to estimate ammonia emissions from a penguin colony.

Penguin colonies represent some of the most concentrated sources of ammonia emissions to the atmosphere in the world. The ammonia emitted into the atmosphere can have a large influence on the nitrogen cycling of ecosystems near the colonies. However, despite the ecological importance of the emissions, no measurements of ammonia emissions from penguin colonies have been made. The objective of this work was to determine the ammonia emission rate of a penguin colony using inverse-dispersion modelling and gradient methods. We measured meteorological variables and mean atmospheric concentrations of ammonia at seven locations near a colony of Adélie penguins in Antarctica to provide input data for inverse-dispersion modelling. Three different atmospheric dispersion models (ADMS, LADD and a Lagrangian stochastic model) were used to provide a robust emission estimate. The Lagrangian stochastic model was applied both in ‘forwards’ and ‘backwards’ mode to compare the difference between the two approaches. In addition, the aerodynamic gradient method was applied using vertical profiles of mean ammonia concentrations measured near the centre of the colony. The emission estimates derived from the simulations of the three dispersion models and the aerodynamic gradient method agreed quite well, giving a mean emission of 1.1 g ammonia per breeding pair per day (95% confidence interval: 0.4–2.5 g ammonia per breeding pair per day). This emission rate represents a volatilisation of 1.9% of the estimated nitrogen excretion of the penguins, which agrees well with that estimated from a temperature-dependent bioenergetics model. We found that, in this study, the Lagrangian stochastic model seemed to give more reliable emission estimates in ‘forwards’ mode than in ‘backwards’ mode due to the assumptions made.

How lowering speed limits in an urban highway affects traffics performance and emissions: the case of Madrid M-30 ring-road

The city of Madrid keeps not meeting the GHG and air pollutant limits set by the European legislation. A broad range of strategies have being taken into account to reduce both types of emissions; however traffic management meas ures are usually consigned to the sidelines. In 2004, Madrid City Council launched a plan to re-design its inner ring-road supported by a socioeconomic study that evaluated the environmental and operational benefits of the project. For safety reasons the planned speed limit for the tunnel section was finally reduced from 90km/h to 70km/h. Using a Macroscopic Traffic Model and the European Air Pollutant and Emissions Inventory Guidebook (EMEP/EEA), this paper examines the environmental and traffic performance consequences of this decision. Results support the thesis that reduced speed limits leads to GHG and air pollution reductions in the area affected by the measure without substantially altering traffic performance. The implementation of the new speed limit policy brings about a 15% and 16% reduction in both CO2 and NOx emissions respectively. Emissions’ reduction during off-peak hours is larger than during peak hours.

Urban trees and atmospheric pollutants in big cities: Effects in Madrid

Una investigación sobre la mejora de la contaminación del aire (CA) por medio de arbolado urbano se realizó en Madrid, una ciudad con casi 4 M de habitantes, 2,8 M de vehículos y casi 3 M de árboles de mantenimiento público. La mayoría de los árboles estaban en dos bosques periurbanos. Los 650.000 restantes era pies de alineación y parques. Los taxones estudiados fueron Platanus orientalis (97.205 árboles), Ulmus sp. (70.557), Pinus pinea (49.038), Aesculus hippocastanum (22.266), Cedrus sp. (13.678) y Quercus ilex (1.650), de calles y parques. Muestras foliares se analizaron en diferentes épocas del año, así como datos de contaminación por PM10 de 28 estaciones de medición de la contaminación durante 30 años, y también la intensidad del tráfico (IMD) en 2.660 calles. La acumulación de metales pesados (MP) sobre hojas y dentro de estas se estimó en relación con la CA y del suelo y la IMD del tráfico. La concentración media de Ba, Cd, Cr, Cu, Mn, Ni, Pb y Zn en suelo (materia seca) alcanzó: 489,5, 0,7, 49,4, 60,9, 460,9, 12,8, 155,9 y 190,3 mg kg-1 respectivamente. Los árboles urbanos, particularmente coníferas (debido a la mayor CA en invierno) contribuyen significativamente a mejorar la CA sobre todo en calles con alta IMD. La capacidad de las seis sp. para capturar partículas de polvo en su superficies foliares está relacionada con la IMD del tráfico y se estimó en 16,8 kg/año de MP tóxicos. Pb y Zn resultaron ser buenos marcadores antrópicos en la ciudad en relación con el tráfico, que fue la principal fuente de contaminación en los árboles y suelos de Madrid. Las especies de árboles variaron en función de su capacidad para capturar partículas (dependiendo de las propiedades de sus superficies foliares) y acumular los MP absorbidos de los suelos. Las concentraciones foliares de Pb y Zn estuvieron por encima de los límites establecidos en diferentes sitios de la ciudad. La microlocalización de Zn mediante microscópico mostró la translocación al xilema y floema. Se detectaron puntos de contaminación puntual de Cu and Cr en antiguos polígonos industriales y la distribución espacial de los MP en los suelos de Madrid mostró que en incluso en zonas interiores del El Retiro había ciertos niveles elevados de [Pb] en suelo, tal vez por el emplazamiento la Real Fábrica de Porcelana en la misma zona hace 200 años. Distintas áreas del centro de la ciudad también alcanzaron niveles altos de [Pb] en suelo. Según los resultados, el empleo de una combinación de Pinus pinea con un estrato intermedio de Ulmus sp. y Cedrus sp. puede ser la mejor recomendación como filtro verde eficiente. El efecto del ozono (O3) sobre el arbolado en Madrid fue también objeto de este estudio. A pesar de la reducción de precursores aplicada en muchos países industrializados, O3 sigue siendo la principal causa de CA en el hemisferio norte, con el aumento de [O3] de fondo. Las mayores [O3] se alcanzaron en regiones mediterráneas, donde el efecto sobre la vegetación natural es compensado por el xeromorfismo y la baja conductancia estomática en respuesta los episodios de sequía estival característicos de este clima. Durante una campaña de monitoreo, se identificaron daños abióticos en hojas de encina parecidos a los de O3 que estaban plantadas en una franja de césped con riego del centro de Madrid. Dada la poca evidencia disponible de los síntomas de O3 en frondosas perennifolias, se hizo un estudio que trató de 1) confirman el diagnóstico de daño de O3, 2) investigar el grado de los síntomas en encinas y 3) analizar los factores ambientales que contribuyeron a los daños por O3, en particular en lo relacionado con el riego. Se analizaron los marcadores macro y micromorfológicos de estrés por O3, utilizando las mencionadas encinas a modo de parcela experimental. Los síntomas consistieron en punteado intercostal del haz, que aumentó con la edad. Además de un punteado subyacente, donde las células superiores del mesófilo mostraron reacciones características de daños por O3. Las células próximas a las zonas dañadas, presentaron marcadores adicionales de estrés oxidativo. Estos marcadores morfológicos y micromorfológicos de estrés por O3 fueron similares a otras frondosas caducifolias con daños por O3. Sin embargo, en nuestro caso el punteado fue evidente con AOT40 de 21 ppm•h, asociada a riego. Análisis posteriores mostraron que los árboles con riego aumentaron su conductancia estomática, con aumento de senescencia, manteniéndose sin cambios sus características xeromórficas foliares. Estos hallazgos ponen de relieve el papel primordial de la disponibilidad de agua frente a las características xeromórficas a la hora de manifestarse los síntomas en las células por daños de O3 en encina. ABSTRACT Research about air pollution mitigation by urban trees was conducted in Madrid (Spain), a southern European city with almost 4 M inhabitants, 2.8 M daily vehicles and 3 M trees under public maintenance. Most trees were located in two urban forests, while 650'000 trees along urban streets and in parks. The urban taxa included Platanus orientalis (97'205 trees), Ulmus sp. (70’557), Pinus pinea (49'038), Aesculus hippocastanum (22’266), Cedrus sp. (13'678 and Quercus ilex (1'650) along streets and parks. Leave samples were analysed sequentially in different seasons, PM10 data from 28 air monitoring stations during 30 years and traffic density estimated from 2’660 streets. Heavy metal (HM) accumulation on the leaf surface and within leaves was estimated per tree related to air and soil pollution, and traffic intensity. Mean concentration of Ba, Cd, Cr, Cu, Mn, Ni, Pb and Zn in topsoil samples (dry mass) amounted in Madrid: 489.5, 0.7, 49.4, 60.9, 460.9, 12.8, 155.9 and 190.3 mg kg-1 respectively. Urban trees, particularly conifers (due to higher pollution in winter) contributed significantly to alleviate air pollution especially near to high ADT roads. The capacity of the six urban street trees species to capture air-born dust on the foliage surface as related to traffic intensity was estimated to 16.8 kg of noxious metals from exhausts per year. Pb and Zn pointed to be tracers of anthropic activity in the city with vehicle traffic as the main source of diffuse pollution on trees and soils. Tree species differed by their capacity to capture air-borne dust (by different leaf surface properties) and to allocate HM from soils. Pb and Zn concentrations in the foliage were above limits in different urban sites and microscopic Zn revelation showed translocation in xylem and phloem tissue. Punctual contamination in soils by Cu and Cr was identified in former industrial areas and spatial trace element mapping showed for central Retiro Park certain high values of [Pb] in soils even related to a Royal pottery 200 years ago. Different areas in the city centre also reached high levels [Pb] in soils. According to the results, a combination of Pinus pinea with understorey Ulmus sp. and Cedrus sp. layers can be recommended for the best air filter efficiency. The effects of ozone (O3) on trees in different areas of Madrid were also part of this study. Despite abatement programs of precursors implemented in many industrialized countries, ozone remained the main air pollutant throughout the northern hemisphere with background [O3] increasing. Some of the highest ozone concentrations were measured in regions with a Mediterranean climate but the effect on the natural vegetation is alleviated by low stomatal uptake and frequent leaf xeromorphy in response to summer drought episodes characteristic of this climate. During a bioindication survey, abiotic O3-like injury was identified in foliage. Trees were growing on an irrigated lawn strip in the centre of Madrid. Given the little structural evidence available for O3 symptoms in broadleaved evergreen species, a study was undertaken in 2007 with the following objectives 1) confirm the diagnosis, 2) investigate the extent of symptoms in holm oaks growing in Madrid and 3) analyse the environmental factors contributing to O3 injury, particularly, the site water supply. Therefore, macro- and micromorphological markers of O3 stress were analysed, using the aforementioned lawn strip as an intensive study site. Symptoms consisted of adaxial and intercostal stippling increasing with leaf age. Underlying stippling, cells in the upper mesophyll showed HR-like reactions typical of ozone stress. The surrounding cells showed further oxidative stress markers. These morphological and micromorphological markers of ozone stress were similar to those recorded in deciduous broadleaved species. However, stippling became obvious already at an AOT40 of 21 ppm•h and was primarily found at irrigated sites. Subsequent analyses showed that irrigated trees had their stomatal conductance increased and leaf life-span reduced whereas their leaf xeromorphy remained unchanged. These findings suggest a central role of water availability versus leaf xeromorphy for ozone symptom expression by cell injury in holm oak.

On strategies for reducing greenhouse gas emissions

Equity is of fundamental concern in the quest for international cooperation to stabilize greenhouse gas concentrations by the reduction of emissions. By modeling the carbon cycle, we estimate the global CO2 emissions that would be required to stabilize the atmospheric concentration of CO2 at levels ranging from 450 to 1,000 ppm. These are compared, on both an absolute and a per-capita basis, to scenarios for emissions from the developed and developing worlds generated by socio-economic models under the assumption that actions to mitigate greenhouse gas emissions are not taken. Need and equity have provided strong arguments for developing countries to request that the developed world takes the lead in controlling its emissions, while permitting the developing countries in the meantime to use primarily fossil fuels for their development. Even with major and early control of CO2 emissions by the developed world, limiting concentration to 450 ppm implies that the developing world also would need to control its emissions within decades, given that we expect developing world emissions would otherwise double over this time. Scenarios leading to CO2 concentrations of 550 ppm exhibit a reduction of the developed world's per-capita emission by about 50% over the next 50 years. Even for the higher stabilization levels considered, the developing world would not be able to use fossil fuels for their development in the manner that the developed world has used them.

Aspectos técnicos e ambientais da incineração de resíduos sólidos urbanos: considerações sobre a proposta para São Paulo

A tecnologia de incineração no gerenciamento de resíduos sólidos urbanos é empregada de maneira intensa em diversos países do mundo. No Brasil, além da sua utilização eventual em resíduos de serviços de saúde, há uma proposta para implantação de duas usinas de grande porte visando ao tratamento térmico de resíduos sólidos domiciliares na cidade de São Paulo. Através de uma revisão bibliográfica sobre o tema, são apresentados os principais parâmetros técnicos e ambientais desta tecnologia, entre eles os mecanismos de combustão e de formação de poluentes, os tipos de equipamentos empregados, as formas de manejo e disposição de cinzas e escórias e os métodos de controle e redução de emissões atmosféricas como gases ácidos, material particulado e metais pesados. Também é feita uma revisão do atual conhecimento técnico-científico sobre dioxinas e furanos relativamente à incineração de resíduos sólidos urbanos. A partir desta base teórica pesquisada e da análise dos Estudos de Impacto Ambiental e dos Relatórios de Impacto Ambiental das usinas de incineração de Santo Amaro e Sapopemba, conclui-se que tais incineradores, na forma como são propostos, não apresentam o nível tecnológico necessário para atender às normas de operação e emissão de poluentes vigentes em países onde há legislação regulando esta atividade.

Atmospheric PM and volatile organic compounds released from Mediterranean shrubland wildfires

Wildfires produce a significant release of gases and particles affecting climate and air quality. In the Mediterranean region, shrublands significantly contribute to burned areas and may show specific emission profiles. Our objective was to depict and quantify the primary-derived aerosols and precursors of secondary particulate species released during shrubland experimental fires, in which fire-line intensity values were equivalent to those of moderate shrubland wildfires, by using a number of different methodologies for the characterization of organic and inorganic compounds in both gas-phase and particulate-phase. Emissions of PM mass, particle number concentrations and organic and inorganic PMx components during flaming and smouldering phases were characterized in a field shrubland fire experiment. Our results revealed a clear prevalence of K+ and SO42- as inorganic ions released during the flaming-smouldering processes, accounting for 68 to 80% of the inorganic soluble fraction. During the residual-smouldering phases, in addition to K+ and SO42-, Ca2+ was found in significant amounts probably due the predominance of re-suspension processes (ashes and soil dust) over other emission sources during this stage. Concerning organic markers, the chromatograms were dominated by phenols, n-alkanals and n-alkanones, as well as by alcohol biomarkers in all the PMx fractions investigated. Levoglucosan was the most abundant degradation compound with maximum emission factors between 182 and 261 mg kg-1 in PM2.5 and PM10 respectively. However, levoglucosan was also observed in significant amounts in the gas-phase. The most representative organic volatile constituents in the smoke samples were alcohols, carbonyls, acids, monocyclic and bicyclic arenes, isoprenoids and alkanes compounds. The emission factors obtained in this study may contribute to the validation and improvement of national and international emission inventories of this intricate and diffuse emission source.

Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling

Atmospheric inverse modelling has the potential to provide observation-based estimates of greenhouse gas emissions at the country scale, thereby allowing for an independent validation of national emission inventories. Here, we present a regional-scale inverse modelling study to quantify the emissions of methane (CH₄) from Switzerland, making use of the newly established CarboCount-CH measurement network and a high-resolution Lagrangian transport model. In our reference inversion, prior emissions were taken from the "bottom-up" Swiss Greenhouse Gas Inventory (SGHGI) as published by the Swiss Federal Office for the Environment in 2014 for the year 2012. Overall we estimate national CH₄ emissions to be 196 ± 18 Gg yr⁻¹ for the year 2013 (1σ uncertainty). This result is in close agreement with the recently revised SGHGI estimate of 206 ± 33 Gg yr⁻¹ as reported in 2015 for the year 2012. Results from sensitivity inversions using alternative prior emissions, uncertainty covariance settings, large-scale background mole fractions, two different inverse algorithms (Bayesian and extended Kalman filter), and two different transport models confirm the robustness and independent character of our estimate. According to the latest SGHGI estimate the main CH₄ source categories in Switzerland are agriculture (78 %), waste handling (15 %) and natural gas distribution and combustion (6 %). The spatial distribution and seasonal variability of our posterior emissions suggest an overestimation of agricultural CH₄ emissions by 10 to 20 % in the most recent SGHGI, which is likely due to an overestimation of emissions from manure handling. Urban areas do not appear as emission hotspots in our posterior results, suggesting that leakages from natural gas distribution are only a minor source of CH₄ in Switzerland. This is consistent with rather low emissions of 8.4 Gg yr⁻¹ reported by the SGHGI but inconsistent with the much higher value of 32 Gg yr⁻¹ implied by the EDGARv4.2 inventory for this sector. Increased CH₄ emissions (up to 30 % compared to the prior) were deduced for the north-eastern parts of Switzerland. This feature was common to most sensitivity inversions, which is a strong indicator that it is a real feature and not an artefact of the transport model and the inversion system. However, it was not possible to assign an unambiguous source process to the region. The observations of the CarboCount-CH network provided invaluable and independent information for the validation of the national bottom-up inventory. Similar systems need to be sustained to provide independent monitoring of future climate agreements.

Historic records of organic compounds from a high Alpine glacier: influences of biomass burning, anthropogenic emissions, and dust transport

Historic records of α-dicarbonyls (glyoxal, methylglyoxal), carboxylic acids (C6–C12 dicarboxylic acids, pinic acid, p-hydroxybenzoic acid, phthalic acid, 4-methylphthalic acid), and ions (oxalate, formate, calcium) were determined with annual resolution in an ice core from Grenzgletscher in the southern Swiss Alps, covering the time period from 1942 to 1993. Chemical analysis of the organic compounds was conducted using ultra-high-performance liquid chromatography (UHPLC) coupled to electrospray ionization high-resolution mass spectrometry (ESI-HRMS) for dicarbonyls and long-chain carboxylic acids and ion chromatography for short-chain carboxylates. Long-term records of the carboxylic acids and dicarbonyls, as well as their source apportionment, are reported for western Europe. This is the first study comprising long-term trends of dicarbonyls and long-chain dicarboxylic acids (C6–C12) in Alpine precipitation. Source assignment of the organic species present in the ice core was performed using principal component analysis. Our results suggest biomass burning, anthropogenic emissions, and transport of mineral dust to be the main parameters influencing the concentration of organic compounds. Ice core records of several highly correlated compounds (e.g., p-hydroxybenzoic acid, pinic acid, pimelic, and suberic acids) can be related to the forest fire history in southern Switzerland. P-hydroxybenzoic acid was found to be the best organic fire tracer in the study area, revealing the highest correlation with the burned area from fires. Historical records of methylglyoxal, phthalic acid, and dicarboxylic acids adipic acid, sebacic acid, and dodecanedioic acid are comparable with that of anthropogenic emissions of volatile organic compounds (VOCs). The small organic acids, oxalic acid and formic acid, are both highly correlated with calcium, suggesting their records to be affected by changing mineral dust transport to the drilling site.

Emissions of greenhouse gases in the United States 1985-1990

Mode of access: Internet.