Development of chitosan packaging films with carvacrol and grape seed extract as antimicrobial and antioxidant agents

In order to produce packaging films with a broad spectrum of action on microorganisms, the effect of two antimicrobial (AM) to be included in the films, carvacrol and GSE were studied separately on different microorganisms. Carvacrol was more effective against the grampositive bacteria than against the gram-negative bacterium. GSE was not effective against yeast. Subsequently, a search for optimal combinations of carvacrol, GSE and the addition of chitosan (as a third component with film forming properties) was carried out. Response surface analysis showed several synergetic effects and three optimal AM combinations (OAMC) were obtained for each microorganism. The experimental validation confirmed that the optimal solutions found can successfully predict the response for each microorganism. The optimization of mixtures of the three components, but this time, using the same concentration for all microorganisms, was also studied to obtain an OAMC with wide spectrum of activity. The results of the response surface analysis showed several synergistic effects for all microorganisms. Three OAMC, OAMC-1, OAMC-2, OAMC-3, were found to be the optimal mixtures for all microorganisms. The radical scavenging activity (RSA) of the different agents was then compared with a standard antioxidant (AOX) BHT, at different concentrations; as also at the OAMC. The RSA increased in the following order: chitosanmodel for the release of GA based on Fick’s law successfully fitted the experimental data and GA diffusion coefficients, assumed to be Arrhenius temperature dependent were obtained for each film. This work will contribute to the development of environmentally friendly packaging films, resulting in improved food preservation and shelf-life extension.

Response curves of deterministic and probabilistic cellular automata in one and two dimensions

One of the most important problems in the theory of cellular automata (CA) is determining the proportion of cells in a specific state after a given number of time iterations. We approach this problem using patterns in preimage sets - that is, the set of blocks which iterate to the desired output. This allows us to construct a response curve - a relationship between the proportion of cells in state 1 after niterations as a function of the initial proportion. We derive response curve formulae for many two-dimensional deterministic CA rules with L-neighbourhood. For all remaining rules, we find experimental response curves. We also use preimage sets to classify surjective rules. In the last part of the thesis, we consider a special class of one-dimensional probabilistic CA rules. We find response surface formula for these rules and experimental response surfaces for all remaining rules.

Improving the microbial production of biofuels through metabolic engineering

Les défis conjoints du changement climatique d'origine anthropique et la diminution des réserves de combustibles fossiles sont le moteur de recherche intense pour des sources d'énergie alternatives. Une avenue attrayante est d'utiliser un processus biologique pour produire un biocarburant. Parmi les différentes options en matière de biocarburants, le bio-hydrogène gazeux est un futur vecteur énergétique attrayant en raison de son efficacité potentiellement plus élevé de conversion de puissance utilisable, il est faible en génération inexistante de polluants et de haute densité d'énergie. Cependant, les faibles rendements et taux de production ont été les principaux obstacles à l'application pratique des technologies de bio-hydrogène. Des recherches intensives sur bio-hydrogène sont en cours, et dans les dernières années, plusieurs nouvelles approches ont été proposées et étudiées pour dépasser ces inconvénients. À cette fin, l'objectif principal de cette thèse était d'améliorer le rendement en hydrogène moléculaire avec un accent particulier sur l'ingénierie métabolique et l’utilisation de bioprocédés à variables indépendantes. Une de nos hypothèses était que la production d’hydrogène pourrait être améliorée et rendue plus économiquement viable par ingénierie métabolique de souches d’Escherichia coli producteurs d’hydrogène en utilisant le glucose ainsi que diverses autres sources de carbone, y compris les pentoses. Les effets du pH, de la température et de sources de carbone ont été étudiés. La production maximale d'hydrogène a été obtenue à partir de glucose, à un pH initial de 6.5 et une température de 35°C. Les études de cinétiques de croissance ont montré que la μmax était 0.0495 h-1 avec un Ks de 0.0274 g L-1 lorsque le glucose est la seule source de carbone en milieu minimal M9. .Parmi les nombreux sucres et les dérivés de sucres testés, les rendements les plus élevés d'hydrogène sont avec du fructose, sorbitol et D-glucose; 1.27, 1.46 et 1.51 mol H2 mol-1 de substrat, respectivement. En outre, pour obtenir les interactions entre les variables importantes et pour atteindre une production maximale d'hydrogène, un design 3K factoriel complet Box-Behnken et la méthodologie de réponse de surface (RSM) ont été employées pour la conception expérimentale et l'analyse de la souche d'Escherichia coli DJT135. Le rendement en hydrogène molaire maximale de 1.69 mol H2 mol-1 de glucose a été obtenu dans les conditions optimales de 75 mM de glucose, à 35°C et un pH de 6.5. Ainsi, la RSM avec un design Box-Behken était un outil statistique utile pour atteindre des rendements plus élevés d'hydrogène molaires par des organismes modifiés génétiquement. Ensuite, l'expression hétérologue de l’hydrogénases soluble [Ni-Fe] de Ralstonia eutropha H16 (l'hydrogénase SH) a tenté de démontrer que la mise en place d'une voie capable de dériver l'hydrogène à partir de NADH pourrait surpasser le rendement stoechiométrique en hydrogène.. L’expression a été démontrée par des tests in vitro de l'activité enzymatique. Par ailleurs, l'expression de SH a restaurée la croissance en anaérobie de souches mutantes pour adhE, normalement inhibées en raison de l'incapacité de réoxyder le NADH. La mesure de la production d'hydrogène in vivo a montré que plusieurs souches modifiées métaboliquement sont capables d'utiliser l'hydrogénase SH pour dériver deux moles d’hydrogène par mole de glucose consommé, proche du maximum théorique. Une autre stratégie a montré que le glycérol brut pourrait être converti en hydrogène par photofermentation utilisant Rhodopseudomonas palustris par photofermentation. Les effets de la source d'azote et de différentes concentrations de glycérol brut sur ce processus ont été évalués. À 20 mM de glycérol, 4 mM glutamate, 6.1 mol hydrogène / mole de glycérol brut ont été obtenus dans des conditions optimales, un rendement de 87% de la théorie, et significativement plus élevés que ce qui a été réalisé auparavant. En prolongement de cette étude, l'optimisation des paramètres a également été utilisée. Dans des conditions optimales, une intensité lumineuse de 175 W/m2, 30 mM glycérol et 4.5 mM de glutamate, 6.69 mol hydrogène / mole de glycérol brut ont été obtenus, soit un rendement de 96% de la valeur théorique. La détermination de l'activité de la nitrogénase et ses niveaux d'expression ont montré qu'il y avait relativement peu de variation de la quantité de nitrogénase avec le changement des variables alors que l'activité de la nitrogénase variait considérablement, avec une activité maximale (228 nmol de C2H4/ml/min) au point central optimal. Dans la dernière section, la production d'hydrogène à partir du glucose via la photofermentation en une seule étape a été examinée avec la bactérie photosynthétique Rhodobacter capsulatus JP91 (hup-). La méthodologie de surface de réponse avec Box-Behnken a été utilisée pour optimiser les variables expérimentales de façon indépendante, soit la concentration de glucose, la concentration du glutamate et l'intensité lumineuse, ainsi que d'examiner leurs effets interactifs pour la maximisation du rendement en hydrogène moléculaire. Dans des conditions optimales, avec une intensité lumineuse de 175 W/m2, 35 mM de glucose, et 4.5 mM de glutamate,, un rendement maximal d'hydrogène de 5.5 (± 0.15) mol hydrogène /mol glucose, et un maximum d'activité de la nitrogénase de 246 (± 3.5) nmol C2H4/ml/min ont été obtenus. L'analyse densitométrique de l'expression de la protéine-Fe nitrogenase dans les différentes conditions a montré une variation significative de l'expression protéique avec un maximum au point central optimisé. Même dans des conditions optimales pour la production d'hydrogène, une fraction significative de la protéine Fe a été trouvée dans l'état ADP-ribosylée, suggérant que d'autres améliorations des rendements pourraient être possibles. À cette fin, un mutant amtB dérivé de Rhodobacter capsulatus JP91 (hup-) a été créé en utilisant le vecteur de suicide pSUP202. Les résultats expérimentaux préliminaires montrent que la souche nouvellement conçue métaboliquement, R. capsulatus DG9, produit 8.2 (± 0.06) mol hydrogène / mole de glucose dans des conditions optimales de cultures discontinues (intensité lumineuse, 175 W/m2, 35 mM de glucose et 4.5 mM glutamate). Le statut d'ADP-ribosylation de la nitrogénase-protéine Fe a été obtenu par Western Blot pour la souche R. capsulatus DG9. En bref, la production d'hydrogène est limitée par une barrière métabolique. La principale barrière métabolique est due au manque d'outils moléculaires possibles pour atteindre ou dépasser le rendement stochiométrique en bio-hydrogène depuis les dernières décennies en utilisant les microbes. À cette fin, une nouvelle approche d’ingénierie métabolique semble très prometteuse pour surmonter cette contrainte vers l'industrialisation et s'assurer de la faisabilité de la technologie de la production d'hydrogène. Dans la présente étude, il a été démontré que l’ingénierie métabolique de bactéries anaérobiques facultatives (Escherichia coli) et de bactéries anaérobiques photosynthétiques (Rhodobacter capsulatus et Rhodopseudomonas palustris) peuvent produire de l'hydrogène en tant que produit majeur à travers le mode de fermentation par redirection métabolique vers la production d'énergie potentielle. D'autre part, la méthodologie de surface de réponse utilisée dans cette étude représente un outil potentiel pour optimiser la production d'hydrogène en générant des informations appropriées concernant la corrélation entre les variables et des producteurs de bio-de hydrogène modifiés par ingénierie métabolique. Ainsi, un outil d'optimisation des paramètres représente une nouvelle avenue pour faire un pont entre le laboratoire et la production d'hydrogène à l'échelle industrielle en fournissant un modèle mathématique potentiel pour intensifier la production de bio-hydrogène. Par conséquent, il a été clairement mis en évidence dans ce projet que l'effort combiné de l'ingénierie métabolique et la méthodologie de surface de réponse peut rendre la technologie de production de bio-hydrogène potentiellement possible vers sa commercialisation dans un avenir rapproché.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Studies on Advanced Oxidation Processes for the Removal of Acetamiprid from Wastewater

Pollution of water with pesticides has become a threat to the man, material and environment. The pesticides released to the environment reach the water bodies through run off. Industrial wastewater from pesticide manufacturing industries contains pesticides at higher concentration and hence a major source of water pollution. Pesticides create a lot of health and environmental hazards which include diseases like cancer, liver and kidney disorders, reproductive disorders, fatal death, birth defects etc. Conventional wastewater treatment plants based on biological treatment are not efficient to remove these compounds to the desired level. Most of the pesticides are phyto-toxic i.e., they kill the microorganism responsible for the degradation and are recalcitrant in nature. Advanced oxidation process (AOP) is a class of oxidation techniques where hydroxyl radicals are employed for oxidation of pollutants. AOPs have the ability to totally mineralise the organic pollutants to CO2 and water. Different methods are employed for the generation of hydroxyl radicals in AOP systems. Acetamiprid is a neonicotinoid insecticide widely used to control sucking type insects on crops such as leafy vegetables, citrus fruits, pome fruits, grapes, cotton, ornamental flowers. It is now recommended as a substitute for organophosphorous pesticides. Since its use is increasing, its presence is increasingly found in the environment. It has high water solubility and is not easily biodegradable. It has the potential to pollute surface and ground waters. Here, the use of AOPs for the removal of acetamiprid from wastewater has been investigated. Five methods were selected for the study based on literature survey and preliminary experiments conducted. Fenton process, UV treatment, UV/ H2O2 process, photo-Fenton and photocatalysis using TiO2 were selected for study. Undoped TiO2 and TiO2 doped with Cu and Fe were prepared by sol-gel method. Characterisation of the prepared catalysts was done by X-ray diffraction, scanning electron microscope, differential thermal analysis and thermogravimetric analysis. Influence of major operating parameters on the removal of acetamiprid has been investigated. All the experiments were designed using central compoiste design (CCD) of response surface methodology (RSM). Model equations were developed for Fenton, UV/ H2O2, photo-Fenton and photocatalysis for predicting acetamiprid removal and total organic carbon (TOC) removal for different operating conditions. Quality of the models were analysed by statistical methods. Experimental validations were also done to confirm the quality of the models. Optimum conditions obtained by experiment were verified with that obtained using response optimiser. Fenton Process is the simplest and oldest AOP where hydrogen peroxide and iron are employed for the generation of hydroxyl radicals. Influence of H2O2 and Fe2+ on the acetamiprid removal and TOC removal by Fenton process were investigated and it was found that removal increases with increase in H2O2 and Fe2+ concentration. At an initial concentration of 50 mg/L acetamiprid, 200 mg/L H2O2 and 20 mg/L Fe2+ at pH 3 was found to be optimum for acetamiprid removal. For UV treatment effect of pH was studied and it was found that pH has not much effect on the removal rate. Addition of H2O2 to UV process increased the removal rate because of the hydroxyl radical formation due to photolyis of H2O2. An H2O2 concentration of 110 mg/L at pH 6 was found to be optimum for acetamiprid removal. With photo-Fenton drastic reduction in the treatment time was observed with 10 times reduction in the amount of reagents required. H2O2 concentration of 20 mg/L and Fe2+ concentration of 2 mg/L was found to be optimum at pH 3. With TiO2 photocatalysis improvement in the removal rate was noticed compared to UV treatment. Effect of Cu and Fe doping on the photocatalytic activity under UV light was studied and it was observed that Cu doping enhanced the removal rate slightly while Fe doping has decreased the removal rate. Maximum acetamiprid removal was observed for an optimum catalyst loading of 1000 mg/L and Cu concentration of 1 wt%. It was noticed that mineralisation efficiency of the processes is low compared to acetamiprid removal efficiency. This may be due to the presence of stable intermediate compounds formed during degradation Kinetic studies were conducted for all the treatment processes and it was found that all processes follow pseudo-first order kinetics. Kinetic constants were found out from the experimental data for all the processes and half lives were calculated. The rate of reaction was in the order, photo- Fenton>UV/ H2O2>Fenton> TiO2 photocatalysis>UV. Operating cost was calculated for the processes and it was found that photo-Fenton removes the acetamiprid at lowest operating cost in lesser time. A kinetic model was developed for photo-Fenton process using the elementary reaction data and mass balance equations for the species involved in the process. Variation of acetamiprid concentration with time for different H2O2 and Fe2+ concentration at pH 3 can be found out using this model. The model was validated by comparing the simulated concentration profiles with that obtained from experiments. This study established the viability of the selected AOPs for the removal of acetamiprid from wastewater. Of the studied AOPs photo- Fenton gives the highest removal efficiency with lowest operating cost within shortest time.

A Study of Single Stage Semi‐Dry Anaerobic Digestion of Organic Fraction of Municipal Solid Waste

Solid waste generation is a natural consequence of human activity and is increasing along with population growth, urbanization and industrialization. Improper disposal of the huge amount of solid waste seriously affects the environment and contributes to climate change by the release of greenhouse gases. Practicing anaerobic digestion (AD) for the organic fraction of municipal solid waste (OFMSW) can reduce emissions to environment and thereby alleviate the environmental problems together with production of biogas, an energy source, and digestate, a soil amendment. The amenability of substrate for biogasification varies from substrate to substrate and different environmental and operating conditions such as pH, temperature, type and quality of substrate, mixing, retention time etc. Therefore, the purpose of this research work is to develop feasible semi-dry anaerobic digestion process for the treatment of OFMSW from Kerala, India for potential energy recovery and sustainable waste management. This study was carried out in three phases in order to reach the research purpose. In the first phase, batch study of anaerobic digestion of OFMSW was carried out for 100 days at 32°C (mesophilic digestion) for varying substrate concentrations. The aim of this study was to obtain the optimal conditions for biogas production using response surface methodology (RSM). The parameters studied were initial pH, substrate concentration and total organic carbon (TOC). The experimental results showed that the linear model terms of initial pH and substrate concentration and the quadratic model terms of the substrate concentration and TOC had significant individual effect (p < 0.05) on biogas yield. However, there was no interactive effect between these variables (p > 0.05). The optimum conditions for maximizing the biogas yield were a substrate concentration of 99 g/l, an initial pH of 6.5 and TOC of 20.32 g/l. AD of OFMSW with optimized substrate concentration of 99 g/l [Total Solid (TS)-10.5%] is a semi-dry digestion system .Under the optimized condition, the maximum biogas yield was 53.4 L/kg VS (volatile solid).. In the second phase, semi-dry anaerobic digestion of organic solid wastes was conducted for 45 days in a lab-scale batch experiment for substrate concentration of 100 g/l (TS-11.2%) for investigating the start-up performances under thermophilic condition (50°C). The performance of the reactor was evaluated by measuring the daily biogas production and calculating the degradation of total solids and the total volatile solids. The biogas yield at the end of the digestion was 52.9 L/kg VS for the substrate concentration of 100 g/l. About 66.7% of volatile solid degradation was obtained during the digestion. A first order model based on the availability of substrate as the limiting factor was used to perform the kinetic studies of batch anaerobic digestion system. The value of reaction rate constant, k, obtained was 0.0249 day-1. A laboratory bench scale reactor with a capacity of 36.8 litres was designed and fabricated to carry out the continuous anaerobic digestion of OFMSW in the third phase. The purpose of this study was to evaluate the performance of the digester at total solid concentration of 12% (semi-dry) under mesophlic condition (32°C). The digester was operated with different organic loading rates (OLRs) and constant retention time. The performance of the reactor was evaluated using parameters such as pH, volatile fatty acid (VFA), alkalinity, chemical oxygen demand (COD), TOC and ammonia-N as well as biogas yield. During the reactor’s start-up period, the process is stable and there is no inhibition occurred and the average biogas production was 14.7 L/day. The reactor was fed in continuous mode with different OLRs (3.1,4.2 and 5.65 kg VS/m3/d) at constant retention time of 30 days. The highest volatile solid degradation of 65.9%, with specific biogas production of 368 L/kg VS fed was achieved with OLR of 3.1 kg VS/m3/d. Modelling and simulation of anaerobic digestion of OFMSW in continuous operation is done using adapted Anaerobic Digestion Model No 1 (ADM1).The proposed model, which has 34 dynamic state variables, considers both biochemical and physicochemical processes and contains several inhibition factors including three gas components. The number of processes considered is 28. The model is implemented in Matlab® version 7.11.0.584(R2010b). The model based on adapted ADM1 was tested to simulate the behaviour of a bioreactor for the mesophilic anaerobic digestion of OFMSW at OLR of 3.1 kg VS/m3/d. ADM1 showed acceptable simulating results.

Análisis de sensibilidad para un modelo de medición de percepción de marca basado en simulación computacional por agentes

Se presenta el análisis de sensibilidad de un modelo de percepción de marca y ajuste de la inversión en marketing desarrollado en el Laboratorio de Simulación de la Universidad del Rosario. Este trabajo de grado consta de una introducción al tema de análisis de sensibilidad y su complementario el análisis de incertidumbre. Se pasa a mostrar ambos análisis usando un ejemplo simple de aplicación del modelo mediante la aplicación exhaustiva y rigurosa de los pasos descritos en la primera parte. Luego se hace una discusión de la problemática de medición de magnitudes que prueba ser el factor más complejo de la aplicación del modelo en el contexto práctico y finalmente se dan conclusiones sobre los resultados de los análisis.

Spatio-temporal surface soil heat flux estimates from satellite data: results for the AMMA experiment at the Fakara (Niger) supersite

This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

Modelling climate impact on floods with ensemble climate projections

The evidence provided by modelled assessments of future climate impact on flooding is fundamental to water resources and flood risk decision making. Impact models usually rely on climate projections from global and regional climate models (GCM/RCMs). However, challenges in representing precipitation events at catchment-scale resolution mean that decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs. Here the impacts on projected high flows of differing ensemble approaches and application of Model Output Statistics to RCM precipitation are evaluated while assessing climate change impact on flood hazard in the Upper Severn catchment in the UK. Various ensemble projections are used together with the HBV hydrological model with direct forcing and also compared to a response surface technique. We consider an ensemble of single-model RCM projections from the current UK Climate Projections (UKCP09); multi-model ensemble RCM projections from the European Union's FP6 ‘ENSEMBLES’ project; and a joint probability distribution of precipitation and temperature from a GCM-based perturbed physics ensemble. The ensemble distribution of results show that flood hazard in the Upper Severn is likely to increase compared to present conditions, but the study highlights the differences between the results from different ensemble methods and the strong assumptions made in using Model Output Statistics to produce the estimates of future river discharge. The results underline the challenges in using the current generation of RCMs for local climate impact studies on flooding. Copyright © 2012 Royal Meteorological Society

Deriving global flood hazard maps of fluvial floods through a physical model cascade

Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979–2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25×25 km grid, which is then reprojected onto a 1×1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25×25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.

The Joint UK Land Environment Simulator (JULES), model description – part 1: energy and water fluxes

This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

An urban parameterization for a global climate model. Part I: Formulation and evaluation for two cities

Urbanization, the expansion of built-up areas, is an important yet less-studied aspect of land use/land cover change in climate science. To date, most global climate models used to evaluate effects of land use/land cover change on climate do not include an urban parameterization. Here, the authors describe the formulation and evaluation of a parameterization of urban areas that is incorporated into the Community Land Model, the land surface component of the Community Climate System Model. The model is designed to be simple enough to be compatible with structural and computational constraints of a land surface model coupled to a global climate model yet complex enough to explore physically based processes known to be important in determining urban climatology. The city representation is based upon the “urban canyon” concept, which consists of roofs, sunlit and shaded walls, and canyon floor. The canyon floor is divided into pervious (e.g., residential lawns, parks) and impervious (e.g., roads, parking lots, sidewalks) fractions. Trapping of longwave radiation by canyon surfaces and solar radiation absorption and reflection is determined by accounting for multiple reflections. Separate energy balances and surface temperatures are determined for each canyon facet. A one-dimensional heat conduction equation is solved numerically for a 10-layer column to determine conduction fluxes into and out of canyon surfaces. Model performance is evaluated against measured fluxes and temperatures from two urban sites. Results indicate the model does a reasonable job of simulating the energy balance of cities.

The Met Office unified model global atmosphere 4.0 and JULES global land 4.0 configurations

We describe Global Atmosphere 4.0 (GA4.0) and Global Land 4.0 (GL4.0): configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) community land surface model developed for use in global and regional climate research and weather prediction activities. GA4.0 and GL4.0 are based on the previous GA3.0 and GL3.0 configurations, with the inclusion of developments made by the Met Office and its collaborators during its annual development cycle. This paper provides a comprehensive technical and scientific description of GA4.0 and GL4.0 as well as details of how these differ from their predecessors. We also present the results of some initial evaluations of their performance. Overall, performance is comparable with that of GA3.0/GL3.0; the updated configurations include improvements to the science of several parametrisation schemes, however, and will form a baseline for further ongoing development.

Detection of solar dimming and brightening effects on Northern Hemisphere river flow

Anthropogenic aerosols in the atmosphere have the potential to affect regional-scale land hydrology through solar dimming. Increased aerosol loading may have reduced historical surface evaporation over some locations, but the magnitude and extent of this effect is uncertain. Any reduction in evaporation due to historical solar dimming may have resulted in an increase in river flow. Here we formally detect and quantify the historical effect of changing aerosol concentrations, via solar radiation, on observed river flow over the heavily industrialized, northern extra-tropics. We use a state-of-the-art estimate of twentieth century surface meteorology as input data for a detailed land surface model, and show that the simulations capture the observed strong inter-annual variability in runoff in response to climatic fluctuations. Using statistical techniques, we identify a detectable aerosol signal in the observed river flow both over the combined region, and over individual river basins in Europe and North America. We estimate that solar dimming due to rising aerosol concentrations in the atmosphere around 1980 led to an increase in river runoff by up to 25% in the most heavily polluted regions in Europe. We propose that, conversely, these regions may experience reduced freshwater availability in the future, as air quality improvements are set to lower aerosol loading and solar dimming.

Meteorological forcing data for urban outdoor thermal comfort models from a coupled convective boundary layer and surface energy balance scheme

Site-specific meteorological forcing appropriate for applications such as urban outdoor thermal comfort simulations can be obtained using a newly coupled scheme that combines a simple slab convective boundary layer (CBL) model and urban land surface model (ULSM) (here two ULSMs are considered). The former simulates daytime CBL height, air temperature and humidity, and the latter estimates urban surface energy and water balance fluxes accounting for changes in land surface cover. The coupled models are tested at a suburban site and two rural sites, one irrigated and one unirrigated grass, in Sacramento, U.S.A. All the variables modelled compare well to measurements (e.g. coefficient of determination = 0.97 and root mean square error = 1.5 °C for air temperature). The current version is applicable to daytime conditions and needs initial state conditions for the CBL model in the appropriate range to obtain the required performance. The coupled model allows routine observations from distant sites (e.g. rural, airport) to be used to predict air temperature and relative humidity in an urban area of interest. This simple model, which can be rapidly applied, could provide urban data for applications such as air quality forecasting and building energy modelling, in addition to outdoor thermal comfort.