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.

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

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

Fluorescent Biological Aerosol Particles in Coastal Canada and the Link to Atmospheric Ice Nuclei

Bioaerosols are a subgroup of atmospheric aerosols and are often linked to the spread of human, animal and plant diseases. Bioaerosols also may play an indirect effect on environmental processes, including the formation of precipitation and alteration of the global climate through their role as nuclei for cloud droplet formation. Several types of biological organisms (e.g., fungi and bacteria) have been shown to be effective ice nuclei (IN) and cloud condensation nuclei (CCN). During 21 days in August 2013 we participated in a collaborative international campaign at a rural, coastal site near the village of Ucluelet on the west coast of Vancouver Island, British Columbia, Canada. The experiments were conducted as part of the NETCARE project (the NETwork on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments), in part to examine cloud nuclei properties of marine aerosol. The study was conducted from a mobile trailer located approximately 100 m from the coast. A suite of aerosol instrumentation was operated for approximately one month. Key instruments utilized as a part of this thesis include the wideband integrated bioaerosol sensor (WIBS-4A) and the multiple orifice uniform deposition impactor (MOUDI) coupled with an off-line droplet freezing technique (DFT) for the measurement of ice nucleation activity of particles in immersion mode. The WIBS measures the concentration and properties of individual fluorescent particles suspended in the air, which can serve as a proxy for airborne biological particle content. Particles shown to be fluorescent by the WIBS instrument were divided into seven categories based on the pattern of fluorescence each particle exhibited in the three fluorescent channels. Results of the WIBS analysis show that the fluorescent particle concentration in the region correlated well with IN number. The fluorescent particle concentration correlated well with the number of particles shown to be ice active as a function of both particle size and freezing temperature. Correlations involving marine aerosols and marine biological activity indicate that the majority of IN measured at the coastal site likely are not from have marine sources.

Halogen deposition in polar snow and ice

The atmospheric chemistry of iodine and bromine in polar regions is of interest due to the key role of halogens in many atmospheric processes, particularly tropospheric ozone destruction. Bromine is emitted from the open ocean but is enriched above first-year sea ice during springtime bromine explosion events, whereas iodine is emitted from biological communities hosted by sea ice. It has been previously demonstrated that bromine and iodine are present in Antarctic ice over glacial-interglacial cycles. Here we investigate seasonal variability of bromine and iodine in polar snow and ice, to evaluate their emission, transport and deposition in Antarctica and the Arctic and better understand potential links to sea ice. We find that bromine enrichment (relative to sea salt content) and iodine concentrations in polar ice do vary seasonally in Arctic snow and Antarctic ice and we relate such variability to satellite-based observations of tropospheric halogen concentrations. Peaks of bromine enrichment in Arctic snow and Antarctic ice occur in spring and summer, when sunlight is present. Iodine concentrations are largest in winter Antarctic ice strata, contrary to contemporary observations of summer maxima in iodine emissions.

Adsorption Calorimetry for Energy Conversion Technologies: Applications in Organic Photovoltaics, Catalysis, and Atomic Layer Deposition

Thesis (Ph.D.)--University of Washington, 2016-07

Peat Bog Ecosystems: Atmospheric pollution

Peatlands can be damaged by deposition of pollutants from the atmosphere – often termed ‘ acid rain ’ . This results from the release of sulphur and nitrogen pollutants into the atmosphere . Originally associated with the Industrial Revolution, ‘acid rain’ was first described by Robert Angus Smith, a Manchester chemist of the 1800s , whose obser vations were made in close proximity to the peatlands of the South Pennines. Sulphur dioxide (SO 2 ) pollution, which is mainly emitted from coal burning power stations, peaked in the 1970s and has since decreased by over 90% due to emission controls and ch anges in energy supply. N itrogen ous air pollutants have decreased less . N itrogen oxide (NO x ) emissions , which are mainly from vehicle s , have decreased by two thirds since their peak in 1990 , but the decrease in ammonia ( NH 3 ) emissions , which are mainly from intensive livestock farming, is much less certain and may be only about 20%.

Monitoring Mercury Deposition: A Key Tool to Understanding the Link Between Emissions and Effects

Illinois State Water Survey/National Atmospheric Deposition Program

Growth and characterization of III-V compound semiconductor nanostructures by metalorganic chemical vapor deposition

Planar <110> GaAs nanowires and quantum dots grown by atmospheric MOCVD have been introduced to non-standard growth conditions such as incorporating Zn and growing them on free-standing suspended films and on 10° off-cut substrates. Zn doped nanowires exhibited periodic notching along the axis of the wire that is dependent on Zn/Ga gas phase molar ratios. Planar nanowires grown on suspended thin films give insight into the mobility of the seed particle and change in growth direction. Nanowires that were grown on the off-cut sample exhibit anti-parallel growth direction changes. Quantum dots are grown on suspended thin films and show preferential growth at certain temperatures. Envisioned nanowire applications include twin-plane superlattices, axial pn-junctions, nanowire lasers, and the modulation of nanowire growth direction against an impeding barrier and varying substrate conditions.

Atmospheric mercury concentrations observed at ground-based monitoring sites globally distributed in the framework of the GMOS network

Long-term monitoring of data of ambient mercury (Hg) on a global scale to assess its emission, transport, atmospheric chemistry, and deposition processes is vital to understanding the impact of Hg pollution on the environment. The Global Mercury Observation System (GMOS) project was funded by the European Commission (http://www.gmos.eu) and started in November 2010 with the overall goal to develop a coordinated global observing system to monitor Hg on a global scale, including a large network of ground-based monitoring stations, ad hoc periodic oceanographic cruises and measurement flights in the lower and upper troposphere as well as in the lower stratosphere. To date, more than 40 ground-based monitoring sites constitute the global network covering many regions where little to no observational data were available before GMOS. This work presents atmospheric Hg concentrations recorded worldwide in the framework of the GMOS project (2010–2015), analyzing Hg measurement results in terms of temporal trends, seasonality and comparability within the network. Major findings highlighted in this paper include a clear gradient of Hg concentrations between the Northern and Southern hemispheres, confirming that the gradient observed is mostly driven by local and regional sources, which can be anthropogenic, natural or a combination of both.

Non-Equilibrium Atmospheric Plasma As A Novel Route To Nanomaterial Synthesis And Processing For Biomedical Applications

Since last century, the rising interest of value-added and advanced functional materials has spurred a ceaseless development in terms of industrial processes and applications. Among the emerging technologies, thanks to their unique features and versatility in terms of supported processes, non-equilibrium plasma discharges appear as a key solvent-free, high-throughput and cost-efficient technique. Nevertheless, applied research studies are needed with the aim of addressing plasma potentialities optimizing devices and processes for future industrial applications. In this framework, the aim of this dissertation is to report on the activities carried out and the results achieved concerning the development and optimization of plasma techniques for nanomaterial synthesis and processing to be applied in the biomedical field. In the first section, the design and investigation of a plasma assisted process for the production of silver (Ag) nanostructured multilayer coatings exhibiting anti-biofilm and anti-clot properties is described. With the aim on enabling in-situ and on-demand deposition of Ag nanoparticles (NPs), the optimization of a continuous in-flight aerosol process for particle synthesis is reported. The stability and promising biological performances of deposited coatings spurred further investigation through in-vitro and in-vivo tests which results are reported and discussed. With the aim of addressing the unanswered questions and tuning NPs functionalities, the second section concerns the study of silver containing droplet conversion in a flow-through plasma reactor. The presented results, obtained combining different analysis techniques, support a formation mechanism based on droplet to particle conversion driven by plasma induced precursor reduction. Finally, the third section deals with the development of a simulative and experimental approach used to investigate the in-situ droplet evaporation inside the plasma discharge addressing the main contributions to liquid evaporation in the perspective of process industrial scale up.

PM and material decay: analysis of dry depositions on horizontal and vertical surrogate surfaces through a Deposition Box system

Airborne Particulate Matter (PM), can get removed from the atmosphere through wet and dry mechanisms, and physically/chemically interact with materials and induce premature decay. The effect of dry depositions is a complex issue, especially for outdoor materials, because of the difficulties to collect atmospheric deposits repeatable in terms of mass and homogeneously distributed on the entire investigated substrate. In this work, to overcome these problems by eliminating the variability induced by outdoor removal mechanisms (e.g. winds and rainfalls), a new sampling system called ‘Deposition Box’, was used for PM sampling. Four surrogate materials (Cellulose Acetate, Regenerated Cellulose, Cellulose Nitrate and Aluminum) with different surfaces features were exposed in the urban-marine site of Rimini (Italy), in vertical and horizontal orientations. Homogeneous and reproducible PM deposits were obtained and different analytical techniques (IC, AAS, TOC, VP-SEM-EDX, Vis-Spectrophotometry) were employed to characterize their mass, dimension and composition. Results allowed to discriminate the mechanisms responsible of the dry deposition of atmospheric particles on surfaces with different nature and orientation and to determine which chemical species, and in which amount, tend to preferentially deposit on them. This work demonstrated that “Deposition Box” can represent an affordable tool to study dry deposition fluxes on materials and results obtained will be fundamental in order to extend this kind of exposure to actual building and heritage materials, to investigate the PM contribution in their decay.

Study and implementation of control strategies for polymerization processes assisted by atmospheric pressure plasma jets

In recent years, polymerization processes assisted by atmospheric pressure plasma jets (APPJs) have received increasing attention in numerous industrially relevant sectors since they allow to coat complex 3D substrates without requiring expensive vacuum systems. Therefore, advancing the comprehension of these processes has become a high priority topic of research. This PhD dissertation is focused on the study and the implementation of control strategies for a polymerization process assisted by an atmospheric pressure single electrode plasma jet. In the first section, a study of the validity of the Yasuda parameter (W/FM) as controlling parameter in the polymerization process assisted by the plasma jet and an aerosolized fluorinated silane precursor is proposed. The surface characterization of coatings deposited under different W/FM values reveals the presence of two very well-known deposition domains, thus suggesting the validity of W/FM as controlling parameter. In addition, the key role of the Yasuda parameter in the process is further demonstrated since coatings deposited under the same W/FM exhibit similar properties, regardless of how W/FM is obtained. In the second section, the development of a methodology for measuring the energy of reactions in the polymerization process assisted by the plasma jet and vaporized hexamethyldisiloxane is presented. The values of energy per precursor molecule are calculated through the identification and resolution of a proper equivalent electrical circuit. To validate the methodology, these energy values are correlated to the bond energies in the precursor molecule and to the properties of deposited thin films. It is shown that the precursor fragmentation in the discharge and the coating characteristics can be successfully explained according to the obtained values of energy per molecule. Through a detailed discussion of the limits and the potentialities of both the control strategies, this dissertation provides useful insights into the control of polymerization processes assisted by APPJs.

Historic and modern alloys: atmospheric corrosion and development of accelerated ageing methodologies

The atmospheric corrosion of modern and historic alloys used in cultural heritage has been investigated by applying specific accelerated ageing methods. Three main research lines were carried out, involving different materials. In the first part, the atmospheric corrosion of a modern Cu-3Si-1Mn bronze was investigated through accelerated ageing tests simulating outdoor runoff conditions. The corrosion processes were evaluated through different analyses, and the results obtained were compared to those of a traditional quaternary bronze. The second line was carried out to characterise historic aluminium alloys used in aeronautics to develop and apply innovative protection strategies for their conservation. Historic wrecks were identified and characterised through micro and macroscale observations. Moreover, accelerated ageing tests were performed on both historic and modern alloys to compare their behaviour and select the best modern substrate to be used for the development of effective coatings. The third research line aimed to develop accelerate sampling and ageing methods to investigate the role of particulate matter (PM) in the atmospheric corrosion of bronzes and metals in general. The first approach consisted in the fine-tuning of an efficient accelerated method for ambient PM sampling on bronze specimens followed by their accelerated ageing, in order to establish a correlation between the PM and the substrate’s corrosion. After the accelerated ageing of the specimens, the corrosion was evaluated by surface characterisation and correlated to the PM features. The second approach consisted in the development of a synthetic PM formulation and of an artificial deposition method, which was performed by spraying mixtures containing the main PM inorganic fractions on a G-85 bronze with an airbrush. The deposition efficiency was assessed, and the effect of synthetic PM on the bronze corrosion was evaluated. The results were compared to those obtained by ambient PM deposition.