SIMLA: Simulating particle dynamics in intense laser and other electromagnetic fields via classical and quantum electrodynamics

We present the Fortran program SIMLA, which is designed for the study of charged particle dynamics in laser and other background fields. The dynamics can be determined classically via the Lorentz force and Landau–Lifshitz equations or, alternatively, via the simulation of photon emission events determined by strong-field quantum-electrodynamics amplitudes and implemented using Monte-Carlo routines. Multiple background fields can be included in the simulation and, where applicable, the propagation direction, field type (plane wave, focussed paraxial, constant crossed, or constant magnetic), and time envelope of each can be independently specified.

Biofilm Complexity Controls Fine Particle Dynamics in Streams

Most models of riverine eco-hydrology and biogeochemistry rely upon bulk parameterization of fluxes. However, the transport and retention of carbon and nutrients in headwater streams is strongly influenced by biofilms (surface-attached microbial communities), which results in strong feedbacks between stream hydrodynamics and biogeochemistry. Mechanistic understanding of the interactions between streambed biofilms and nutrient dynamics is lacking. Here we present experimental results linking microscale observations of biofilm community structure to the deposition and resuspension of clay-sized mineral particles in streams. Biofilms were grown in identical 3 m recirculating flumes over periods of 14-50 days. Fluorescent particles were introduced to each flume, and their deposition was traced over 30 minutes. Particle resuspension from the biofilms was then observed under an increased stream flow, mimicking a flood event. We quantified particle fluxes using flow cytometry and epifluorescence microscopy. We directly observed particle adhesion to the biofilm using a confocal laser scanning microscope. 3-D Optical Coherence Tomography was used to determine biofilm roughness, areal coverage and void space in each flume. These measurements allow us to link biofilm complexity to particle retention during both baseflow and floodflow. The results suggest that increased biofilm complexity favors deposition and retention of fine particles in streams.

Using particle dispersal models to assist in the conservation and recovery of the overexploited native oyster (Ostrea edulis) in an enclosed sea lough

Oyster populations around the world have seen catastrophic decline which has been largely attributed to overexploitation, disease and pollution. While considerable effort and resources have been implemented into restoring these important environmental engineers, the success of oyster populations is often limited by poor understanding of site-specific dispersal patterns of propagules. Water-borne transport is a key factor controlling or regulating the dispersal of the larval stage of benthic marine invertebrates which have limited mobility. The distribution of the native oyster Ostrea edulis in Strangford Lough, Northern Ireland, together with their densities and population structure at subtidal and intertidal sites has been documented at irregular intervals between 1997 and 2013. This paper revisits this historical data and considers whether different prevailing environmental conditions can be used to explain the distribution, densities and population structure of O. edulis in Strangford Lough. The approach adopted involved comparing predictive 2D hydrodynamic models coupled with particle tracking to simulate the dispersal of oyster larvae with historical and recent field records of the distribution of both subtidal and intertidal, populations since 1995. Results from the models support the hypothesis that commercial stocks of O. edulis introduced into Strangford Lough in the 1990s resulted in the re-establishment of wild populations of oysters in the Northern Basin which in turn provided a potential source of propagules for subtidal populations. These results highlight that strategic site selection (while inadvertent in the case of the introduced population in 1995) for the re-introduction of important shellfish species can significantly accelerate their recovery and restoration.

Particle acceleration with laser and applications

The biological effectiveness of laser driven protons on cells at high dose rate in a single exposure has been studied. V79 cell lines were irradiated with laser driven protons.

Characterisation of gas and particle emissions from wildfires

Os incêndios florestais são uma importante fonte de emissão de compostos gasosos e de aerossóis. Em Portugal, onde a maioria dos incêndios ocorre no norte e centro do país, os incêndios destroem todos os anos milhares de hectares, com importantes perdas em termos económicos, de vidas humanas e qualidade ambiental. As emissões podem alterar consideravelmente a química da atmosfera, degradar a qualidade do ar e alterar o clima. Contudo, a informação sobre as caraterísticas das emissões dos incêndios florestais nos países do Mediterrâneo é limitada. Tanto a nível nacional como internacional, existe um interesse crescente na elaboração de inventários de emissões e de regulamentos sobre as emissões de carbono para a atmosfera. Do ponto de vista atmosférico da monitorização atmosférica, os incêndios são considerados um desafio, dada a sua variabilidade temporal e espacial, sendo de esperar um aumento da sua frequência, dimensão e severidade, e também porque as estimativas de emissões dependem das caraterísticas dos biocombustíveis e da fase de combustão. O objetivo deste estudo foi quantificar e caraterizar as emissões de gases e aerossóis de alguns dos mais representativos incêndios florestais que ocorreram no centro de Portugal nos verões de 2009 e de 2010. Efetuou-se a colheita de amostras de gases e de duas frações de partículas (PM2.5 e PM2.5-10) nas plumas de fumo em sacos Tedlar e em filtros de quartzo acoplados a um amostrador de elevado volume, respetivamente. Os hidrocarbonetos totais (THC) e óxidos de carbono (CO e CO2) nas amostras gasosas foram analisados em instrumentos automáticos de ionização de chama e detetores não dispersivos de infravermelhos, respetivamente. Para algumas amostras, foram também quantificados alguns compostos de carbonilo após reamostragem do gás dos sacos Tedlar em cartuchos de sílica gel revestidos com 2,4-dinitrofenilhidrazina (DNPH), seguida de análise por cromatografia líquida de alta resolução. Nas partículas, analisou-se o carbono orgânico e elementar (técnica termo-óptica), iões solúveis em água (cromatografia iónica) e elementos (espectrometria de massa com plasma acoplado por indução ou análise instrumental por ativação com neutrões). A especiação orgânica foi obtida por cromatografia gasosa acoplada a espectrometria de massa após extração com recurso a vários solventes e separação dos extratos orgânicos em diversas classes de diferentes polaridades através do fracionamento com sílica gel. Os fatores de emissão do CO e do CO2 situaram-se nas gamas 52-482 e 822-1690 g kg-1 (base seca), mostrando, respetivamente, correlação negativa e positiva com a eficiência de combustão. Os fatores de emissão dos THC apresentaram valores mais elevados durante a fase de combustão latente sem chama, oscilando entre 0.33 e 334 g kg-1 (base seca). O composto orgânico volátil oxigenado mais abundante foi o acetaldeído com fatores de emissão que variaram desde 1.0 até 3.2 g kg-1 (base seca), seguido pelo formaldeído e o propionaldeído. Observou-se que as emissões destes compostos são promovidas durante a fase de combustão latente sem chama. Os fatores de emissão de PM2.5 e PM10 registaram valores entre 0.50-68 e 0.86-72 g kg-1 (base seca), respetivamente. A emissão de partículas finas e grosseiras é também promovida em condições de combustão lenta. As PM2.5 representaram cerca de 90% da massa de partículas PM10. A fração carbonosa das partículas amostradas em qualquer dos incêndios foi claramente dominada pelo carbono orgânico. Foi obtida uma ampla gama de rácios entre o carbono orgânico e o carbono elementar, dependendo das condições de combustão. Contudo, todos os rácios refletiram uma maior proporção de carbono orgânico em relação ao carbono elementar, típica das emissões de queima de biomassa. Os iões solúveis em água obtidos nas partículas da pluma de fumo contribuíram com valores até 3.9% da massa de partículas PM2.5 e 2.8% da massa de partículas de PM2.5-10. O potássio contribuiu com valores até 15 g mg-1 PM2.5 e 22 g mg-1 PM2.5-10, embora em massa absoluta estivesse maioritariamente presente nas partículas finas. Os rácios entre potássio e carbono elementar e entre potássio e carbono orgânico obtidos nas partículas da pluma de fumo enquadram-se na gama de valores relatados na literatura para emissões de queima de biomassa. Os elementos detetados nas amostras representaram, em média, valores até 1.2% e 12% da massa de PM2.5 e PM2.5-10, respetivamente. Partículas resultantes de uma combustão mais completa (valores elevados de CO2 e baixos de CO) foram caraterizadas por um elevado teor de constituintes inorgânicos e um menor conteúdo de matéria orgânica. Observou-se que a matéria orgânica particulada é composta principalmente por componentes fenólicos e produtos derivados, séries de compostos homólogos (alcanos, alcenos, ácidos alcanóicos e alcanóis), açúcares, biomarcadores esteróides e terpenóides, e hidrocarbonetos aromáticos policíclicos. O reteno, um biomarcador das emissões da queima de coníferas, foi o hidrocarboneto aromático dominante nas amostras das plumas de fumo amostradas durante a campanha que decorreu em 2009, devido ao predomínio de amostras colhidas em incêndios em florestas de pinheiros. O principal açúcar anidro, e sempre um dos compostos mais abundantes, foi o levoglucosano. O rácio levoglucosano/OC obtido nas partículas das plumas de fumo, em média, registaram valores desde 5.8 a 23 mg g-1 OC. Os rácios levoglucosano/manosano e levoglucosano/(manosano+galactosano) revelaram o predomínio de amostras provenientes da queima de coníferas. Tendo em conta que a estimativa das emissões dos incêndios florestais requer um conhecimento de fatores de emissão apropriados para cada biocombustível, a base de dados abrangente obtida neste estudo é potencialmente útil para atualizar os inventários de emissões. Tem vindo a ser observado que a fase de combustão latente sem chama, a qual pode ocorrer simultaneamente com a fase de chama e durar várias horas ou dias, pode contribuir para uma quantidade considerável de poluentes atmosféricos, pelo que os fatores de emissão correspondentes devem ser considerados no cálculo das emissões globais de incêndios florestais. Devido à falta de informação detalhada sobre perfis químicos de emissão, a base de dados obtida neste estudo pode também ser útil para a aplicação de modelos no recetor no sul da Europa.

The response of reworked aerosols to climate through estimation of inter-particle forces

This paper describes the first use of inter-particle force measurement in reworked aerosols to better understand the mechanics of dust deflation and its consequent ecological ramifications. Dust is likely to carry hydrocarbons and micro-organisms including human pathogens and cultured microbes and thereby is a threat to plants, animals and human. Present-day global aerosol emissions are substantially greater than in 1850; however, the projected influx rates are highly disputable. This uncertainty, in part, has roots in the lack of understanding of deflation mechanisms. A growing body of literature shows that whether carbon emission continues to increase, plant transpiration drops and soil water retention enhances, allowing more greenery to grow and less dust to flux. On the other hand, a small but important body of geochemistry literature shows that increasing emission and global temperature leads to extreme climates, decalcification of surface soils containing soluble carbonate polymorphs and hence a greater chance of deflation. The consistency of loosely packed reworked silt provides background data against which the resistance of dust’s bonding components (carbonates and water) can be compared. The use of macro-scale phenomenological approaches to measure dust consistency is trivial. Instead, consistency can be measured in terms of inter-particle stress state. This paper describes a semi-empirical parametrisation of the inter-particle cohesion forces in terms of the balance of contact-level forces at the instant of particle motion. We put forward the hypothesis that the loss of Ca2+-based pedogenic salts is responsible for much of the dust influx and surficial drying pays a less significant role.

Determination of Alternaria spp. Habitats Using 7-Day Volumetric Spore Trap, Hybrid Single Particle Lagrangian Integrated Trajectory Model and Geographic Information System

There are many species among the Alternaria genus, which hosts on economically important crops causing significant yield losses. Less attention has been paid to fungi hosting on plants constituting substantial components of pastures and meadows. Alternaria spp. spores are also recognised as important allergens. A 7-day volumetric spore trap was used to monitor the concentration of airborne fungal spores. Air samples were collected in Worcester, England (2006–2010). Days with a high spore count were then selected. The longest episode that occurred within a five year study was chosen for modelling. Two source maps presenting distribution of crops under rotation and pastures in the UK were produced. Back trajectories were calculated using the HYSPLIT model. In ArcGIS clusters of trajectories were studied in connection with source maps by including the height above ground level and the speed of the air masses. During the episode no evidence for a long distance transport from the continent of Alternaria spp. spores was detected. The overall direction of the air masses fell within the range from South-West to North. The back trajectories indicated that the most important sources of Alternaria spp. spores were located in the West Midlands of England.

Particle swarm optimization based approaches to vehicle-to-grid scheduling

This paper addresses the problem of energy resources management using modern metaheuristics approaches, namely Particle Swarm Optimization (PSO), New Particle Swarm Optimization (NPSO) and Evolutionary Particle Swarm Optimization (EPSO). The addressed problem in this research paper is intended for aggregators’ use operating in a smart grid context, dealing with Distributed Generation (DG), and gridable vehicles intelligently managed on a multi-period basis according to its users’ profiles and requirements. The aggregator can also purchase additional energy from external suppliers. The paper includes a case study considering a 30 kV distribution network with one substation, 180 buses and 90 load points. The distribution network in the case study considers intense penetration of DG, including 116 units from several technologies, and one external supplier. A scenario of 6000 EVs for the given network is simulated during 24 periods, corresponding to one day. The results of the application of the PSO approaches to this case study are discussed deep in the paper.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.