A procedure to evaluate environmental rehabilitation in limestone quarries

A procedure to evaluate mine rehabilitation practices during the operational phase was developed and validated. It is based on a comparison of actually observed or documented practices with internationally recommended best practices (BP). A set of 150 BP statements was derived from international guides in order to establish the benchmark. The statements are arranged in six rehabilitation programs under three categories: (1) planning (2) operational and (3) management, corresponding to the adoption of the plan-do-check-act management systems model to mine rehabilitation. The procedure consists of (i) performing technical inspections guided by a series of field forms containing BP statements; (ii) classifying evidences in five categories; and (iii) calculating conformity indexes and levels. For testing and calibration purposes, the procedure was applied to nine limestone quarries and conformity indexes were calculated for the rehabilitation programs in each quarry. Most quarries featured poor planning practices, operational practices reached high conformity levels in 50% of the cases and management practices scored moderate conformity. Despite all quarries being ISO 14001 certified, their management systems pay low attention to issues pertaining to land rehabilitation and biodiversity. The best results were achieved by a quarry whose expansion was recently submitted to the environmental impact assessment process, suggesting that public scrutiny may play a positive role in enhancing rehabilitation practices. Conformity indexes and levels can be used to chart the evolution of rehabilitation practices at regular intervals, to establish corporate goals and for communication with stakeholders. (C) 2010 Elsevier Ltd. All rights reserved.

Multi-Objective Optimization Design of Tanker Ships via a Genetic Algorithm

The cost of a new ship design heavily depends on the principal dimensions of the ship; however, dimensions minimization often conflicts with the minimum oil outflow (in the event of an accidental spill). This study demonstrates one rational methodology for selecting the optimal dimensions and coefficients of form of tankers via the use of a genetic algorithm. Therein, a multi-objective optimization problem was formulated by using two objective attributes in the evaluation of each design, specifically, total cost and mean oil outflow. In addition, a procedure that can be used to balance the designs in terms of weight and useful space is proposed. A genetic algorithm was implemented to search for optimal design parameters and to identify the nondominated Pareto frontier. At the end of this study, three real ships are used as case studies. [DOI:10.1115/1.4002740]

Application of Fluorescence to the Study of Crude Petroleum

Crude petroleum oils are complex mixtures of different compounds (mainly organic), which are obtained from an extensive range of different geological sources. The fluorescence of crude petroleum oils derives largely from the aromatic hydrocarbon fraction, and this fluorescence emission is strongly influenced by the chemical composition (e.g., fluorophore and quencher concentrations) and physical characteristics (e.g., viscosity and optical density) of the oil. The fluorescence spectroscopy (FS) is increasingly used in petroleum technology due the availability of better optical detection techniques, because FS offers high sensitivity, good diagnostic potential, and relatively simple instrumentation. In this work we analyzed crude petroleum at different dilution in Nujol, a transparent mineral oil. The main objective of this work was to verify the possibility to measure crude oil emission spectroscopic without use of volatile solvents. The mixtures of nujol with different -crude oil concentrations were measured with a 10 mm optical path cuvette thus simplifying the fluorescence spectroscopy signal detection. The emission spectra were obtained by exciting the samples with a 400 W Xenon lamp at 350 nm, 450 nm and 532 nm. The emissions of the samples were collected perpendicularly with the excitation axis.

Modeling the kinetics of the coalescence of water droplets in crude oil emulsions subject to an electric field, with the cellular automata technique

In this study, the concept of cellular automata is applied in an innovative way to simulate the separation of phases in a water/oil emulsion. The velocity of the water droplets is calculated by the balance of forces acting on a pair of droplets in a group, and cellular automata is used to simulate the whole group of droplets. Thus, it is possible to solve the problem stochastically and to show the sequence of collisions of droplets and coalescence phenomena. This methodology enables the calculation of the amount of water that can be separated from the emulsion under different operating conditions, thus enabling the process to be optimized. Comparisons between the results obtained from the developed model and the operational performance of an actual desalting unit are carried out. The accuracy observed shows that the developed model is a good representation of the actual process. (C) 2010 Published by Elsevier Ltd.

The importance of the industrialization of Brazilian shale when faced with the world energy scenario

This article discusses the importance of the industrialization of Brazilian shale based on factors such as: security of the national energy system security, global oil geopoliticsl, resources available, production costs, oil prices, environmental impacts and the national oil reserves. The study shows that the industrialization of shale always arises when issues such as peak oil or its geopolitics appear as factors that raise the price of oil to unrealistic levels. The article concludes that in the Brazilian case, shale oil may be classified as a strategic resource, economically viable, currently in development by the success of the retorting technology for extraction of shale oil and the price of crude oil. The article presents the conclusion that shale may be the driving factor for the formation of a technology park in Sao Mateus do Sul, due to the city`s economic dependence on Petrosix.

A mechanistic kinetic model for phenol degradation by the Fenton process

The objective of this paper is to develop and validate a mechanistic model for the degradation of phenol by the Fenton process. Experiments were performed in semi-batch operation, in which phenol, catechol and hydroquinone concentrations were measured. Using the methodology described in Pontes and Pinto [R.F.F. Pontes, J.M. Pinto, Analysis of integrated kinetic and flow models for anaerobic digesters, Chemical Engineering journal 122 (1-2) (2006) 65-80], a stoichiometric model was first developed, with 53 reactions and 26 compounds, followed by the corresponding kinetic model. Sensitivity analysis was performed to determine the most influential kinetic parameters of the model that were estimated with the obtained experimental results. The adjusted model was used to analyze the impact of the initial concentration and flow rate of reactants on the efficiency of the Fenton process to degrade phenol. Moreover, the model was applied to evaluate the treatment cost of wastewater contaminated with phenol in order to meet environmental standards. (C) 2009 Elsevier B.V. All rights reserved.

Coalescence of Water Droplets in Crude Oil Emulsions: Analytical Solution

In petroleum refineries, water is used in desalting units to remove the salt contained in crude oil. Typically, 7% of the volume of hot crude oil is water, forming a water-and-oil emulsion. The emulsion flows between two electrodes and is subjected to an electric field. The electrical forces promote the coalescence of small droplets of water dispersed in crude oil, and these form bigger droplets. This paper calculates the forces acting on the droplets, highlighting particularly the mechanisms proposed for droplet-droplet coalescence under the influence of an applied electric field. Moreover, a model is developed in order to calculate the displacement speed of the droplets and the time between droplet collisions. Thus, it is possible to simulate and optimize the process by changing the operational variables (temperature, electrical field, and water quantity). The main advantage of this study is to show that it is feasible to increase the volume of water recycled in desalting processes, thus reducing the use of freshwater and the generation of liquid effluents in refineries.

Optimal synthesis of anaerobic digester networks

The objective of this paper is to develop a mathematical model for the synthesis of anaerobic digester networks based on the optimization of a superstructure that relies on a non-linear programming formulation. The proposed model contains the kinetic and hydraulic equations developed by Pontes and Pinto [Chemical Engineering journal 122 (2006) 65-80] for two types of digesters, namely UASB (Upflow Anaerobic Sludge Blanket) and EGSB (Expanded Granular Sludge Bed) reactors. The objective function minimizes the overall sum of the reactor volumes. The optimization results show that a recycle stream is only effective in case of a reactor with short-circuit, such as the UASB reactor. Sensitivity analysis was performed in the one and two-digester network superstructures, for the following parameters: UASB reactor short-circuit fraction and the EGSB reactor maximum organic load, and the corresponding results vary considerably in terms of digester volumes. Scenarios for three and four-digester network superstructures were optimized and compared with the results from fewer digesters. (C) 2009 Elsevier B.V. All rights reserved.

Porous silicon optical cavity structure applied to high sensitivity organic solvent sensor

The present work reports the thermal annealing process, the number of layer and electrochemical process effect in the optical response quality of Bragg and microcavity devices that were applied as organic solvent sensors. These devices have been obtained by using porous silicon (PS) technology. The optical characterization of the Bragg reflector, before annealing, showed a broad photonic band-gap structure with blue shifted and narrowed after annealing process. The electrochemical process used to obtain the PS-based device imposes the limit in the number of layers because of the chemical dissolution effect. The interface roughness minimizations in the devices have been achieved by using the double electrochemical cell setup. The microcavity devices showed to have a good sensibility for organic solvent detection. The thermal annealed device showed better sensibility feature and this result was attributed to passivation of the surface devices. (c) 2007 Elsevier Ltd. All rights reserved.

Generation of self-similar Gaussian time series by means of the DWT and DWPT variance maps

Due to the several kinds of services that use the Internet and data networks infra-structures, the present networks are characterized by the diversity of types of traffic that have statistical properties as complex temporal correlation and non-gaussian distribution. The networks complex temporal correlation may be characterized by the Short Range Dependence (SRD) and the Long Range Dependence - (LRD). Models as the fGN (Fractional Gaussian Noise) may capture the LRD but not the SRD. This work presents two methods for traffic generation that synthesize approximate realizations of the self-similar fGN with SRD random process. The first one employs the IDWT (Inverse Discrete Wavelet Transform) and the second the IDWPT (Inverse Discrete Wavelet Packet Transform). It has been developed the variance map concept that allows to associate the LRD and SRD behaviors directly to the wavelet transform coefficients. The developed methods are extremely flexible and allow the generation of Gaussian time series with complex statistical behaviors.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

MORTADELLA SAUSAGE PRODUCED WITH SOYBEAN OIL INSTEAD OF PORK FAT

This study examines the effects of partially or completely replacing pork backfat with soybean oil in mortadella production. Mortadella sausages of various formulations showed no differences (P > 0.05) in any of the technological and physico-chemical parameters evaluated (process yield, shear force, pH, water activity and proximate composition). When compared to products made with pork backfat, those made with vegetable oil had a higher unsaturated fatty acid content (P <= 0.05) and a similar cholesterol content (P > 0.05). Products made with vegetable oil scored lower (P <= 0.05) than those made with pork fat on all of the evaluated sensory attributes (colour, odour, flavour, texture and overall acceptability).

Emerging Threats and Opportunities for Large-Scale Ecological Restoration in the Atlantic Forest of Brazil

Over the past 150 years, Brazil has played a pioneering role in developing environmental policies and pursuing forest conservation and ecological restoration of degraded ecosystems. In particular, the Brazilian Forest Act, first drafted in 1934, has been fundamental in reducing deforestation and engaging private land owners in forest restoration initiatives. At the time of writing (December 2010), however, a proposal for major revision of the Brazilian Forest Act is under intense debate in the National Assembly, and we are deeply concerned about the outcome. On the basis of the analysis of detailed vegetation and hydrographic maps, we estimate that the proposed changes may reduce the total amount of potential areas for restoration in the Atlantic Forest by approximately 6 million hectares. As a radically different policy model, we present the Atlantic Forest Restoration Pact (AFRP), which is a group of more than 160 members that represents one of the most important and ambitious ecological restoration programs in the world. The AFRP aims to restore 15 million hectares of degraded lands in the Brazilian Atlantic Forest biome by 2050 and increase the current forest cover of the biome from 17% to at least 30%. We argue that not only should Brazilian lawmakers refrain from revising the existing Forest Law, but also greatly step up investments in the science, business, and practice of ecological restoration throughout the country, including the Atlantic Forest. The AFRP provides a template that could be adapted to other forest biomes in Brazil and to other megadiversity countries around the world.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.