A circular economy approach for olive oil industry: From olive pomace to microalgal biomass

In this work olive pomace was used to recover high added value compounds and produce biogas by anaerobic digestion. Moreover, in order to satisfy the circular economy concept, the digestate from the latter process was used as medium for the microalga Chlorella vulgaris growth

Tools for Optimization of Biomass-to-Energy Conversion Processes

Biomasses are renewable sources used in energy conversion processes to obtain diverse products through different technologies. The production chain, which involves delivery, logistics, pre-treatment, storage and conversion as general components, can be costly and uncertain due to inherent variability. Optimization methods are widely applied for modeling the biomass supply chain (BSC) for energy processes. In this qualitative review, the main aspects and global trends of using geographic information systems (GISs), linear programming (LP) and neural networks to optimize the BSC are presented. Modeling objectives and factors considered in studies published in the last 25 years are reviewed, enabling a broad overview of the BSC to support decisions at strategic, tactical and operational levels. Combined techniques have been used for different purposes: GISs for spatial analyses of biomass; neural networks for higher heating value (HHV) correlations; and linear programming and its variations for achieving objectives in general, such as costs and emissions reduction. This study reinforces the progress evidenced in the literature and envisions the increasing inclusion of socio-environmental criteria as a challenge in future modeling efforts

Doxycycline degradation by the oxidative Fenton process

Doxycycline is a broad-spectrum tetracycline occurring in domestic, industrial and rural effluents, whose main drawback is the increasing emergence of resistant bacteria. This antibiotic could be degraded by the so-called Fenton process, consisting in the oxidation of organic pollutants by oxygen peroxide (H2O2) in the presence of Fe2+. Experiments were performed according to an experimental Rotational Central Composite Design to investigate the influence of temperature (0 \u2013 40.0\ub0C), H2O2 concentration (100 \u2013 900 mg/L) and Fe2+ concentration (5 \u2013 120 mg/L) on residual doxycycline and total organic carbon concentrations. Whereas the final residual doxycycline concentration ranged from 0 to 55.8 mg/L, the oxidation process proved unable to reduce the total organic carbon by more than 30%. The best operating conditions were concentrations of H2O2 and Fe2+ of 611 and 25 mg/L, respectively, and temperature of 35.0\ub0C, but the analysis of variance revealed that only the first variable exerted a statistically-significant effect on the residual doxycycline concentration. These results suggest possible application of this process in the treatment of doxycycline-containing effluents and may be used as starting basis to treat tetracycline-contaminated effluents

Trattamento di inquinanti emergenti in acque da digestione anaerobica di liquami suinicoli mediante microalghe

I liquami suinicoli post digestione anaerobica, ancora ricchi in ammonio, possono causare fenomeni di eutrofizzazione delle acque. Inoltre, per l\u2019eccessivo uso di antibiotici negli allevamenti, significative quantit\ue0 non metabolizzate di questi farmaci possono essere ritrovate nei liquami e quindi nelle acque dopo trattamento anaerobico. Crescendo in modo eterotrofico, le microalghe potrebbero offrire diversi vantaggi, essendo in grado di usare il carbonio organico cos\uec come nutrienti inorganici quali azoto e fosforo presenti nelle acque di scarico. Lo scopo di questa ricerca \ue8 stato quello di valutare l\u2019effetto di inquinati emergenti aggiunti al digestato da liquami suinicoli sulla crescita della microalga Chlorella vulgaris. A tale scopo C. vulgaris \ue8 stata fatta crescere in terreno con differenti quantit\ue0 di digestato al fine di ottenere concentrazioni iniziali di azoto ammoniacale pari a 60, 120 e 170 mgN/L. A fini comparativi, colture addizionali sono state eseguite sia in acqua arricchita con ammonio puro alle stesse concentrazioni sopra riportate, sia nel terreno classico di crescita per questa microalga (Bold Basal Medium). Alla coltura con 60 mgN/L di ammonio da liquami, dopo il raggiungimento della fase stazionaria sono stati aggiunti 14.0 mg/L di Micospectone, consistente in una miscela al 33.3 e 66.6% degli antibiotici Lincomicina e Spectinomicina. Studi preliminari hanno evidenziato che concentrazioni superiori di antibiotico (56-112 mg/L) possono portare ad un\u2019inibizione della crescita microalgale. La concentrazione della biomassa microalgale \ue8 stata quantificata giornalmente per via spettrofotometrica ad una lunghezza d\u2019onda pari a 625 nm, mentre quelle di ammonio totale e di fosfati periodicamente. La biomassa fresca ed essiccata al termine della crescita \ue8 stata osservata mediante microscopia ottica ed elettronica a scansione. In presenza di digestato e antibiotico, C. vulgaris ha raggiunto concentrazioni finali di circa 1.3 g di biomassa secca per litro di terreno. L\u2019ammonio \ue8 stato rimosso efficacemente con velocit\ue0 di rimozione pari a 5.6 and 3.4 mgN/Lgiorno partendo rispettivamente da concentrazioni iniziali di ammonio di 60 e 120 mgN/L, mentre concentrazioni superiori di ammonio (170 mgN/L) hanno comportato inibizione sia della crescita sia della sua propria rimozione

Predicting Thermoelectric Power Plants Diesel/Heavy Fuel Oil Engine Fuel Consumption Using Univariate Forecasting and XGBoost Machine Learning Models

Monitoring and controlling thermoelectric power plants (TPPs) operational parameters have become essential to ensure system reliability, especially in emergencies. Due to system complexity, operating parameters control is often performed based on technical know-how and simplified analytical models that can result in limited observations. An alternative to this task is using time series forecasting methods that seek to generalize system characteristics based on past information. However, the analysis of these techniques on large diesel/HFO engines used in Brazilian power plants under the dispatch regime has not yet been well-explored. Therefore, given the complex characteristics of engine fuel consumption during power generation, this work aimed to investigate patterns generalization abilities when linear and nonlinear univariate forecasting models are used on a representative database related to an engine-driven generator used in a TPP located in Pernambuco, Brazil. Fuel consumption predictions based on artificial neural networks were directly compared to XGBoost regressor adaptation to perform this task as an alternative with lower computational cost. AR and ARIMA linear models were applied as a benchmark, and the PSO optimizer was used as an alternative during model adjustment. In summary, it was possible to observe that AR and ARIMA-PSO had similar performances in operations and lower error distributions during full-load power output with normal error frequency distribution of −0.03 ± 3.55 and 0.03 ± 3.78 kg/h, respectively. Despite their similarities, ARIMA-PSO achieved better adherence in capturing load adjustment periods. On the other hand, the nonlinear approaches NAR and XGBoost showed significantly better performance, achieving mean absolute error reductions of 42.37% and 30.30%, respectively, when compared with the best linear model. XGBoost modeling was 8.7 times computationally faster than NAR during training. The nonlinear models were better at capturing disturbances related to fuel consumption ramp, shut-down, and sudden fluctuations steps, despite being inferior in forecasting at full-load, especially XGBoost due to its high sensitivity with slight fuel consumption variations

A Novel Remaining Useful Estimation Model to Assist Asset Renewal Decisions Applied to the Brazilian Electric Sector

Assets deteriorate over time, as well as being covered, corroded, or becoming old in less obvious ways. Maintenance can extend the remaining useful life (RUL) of an asset system, but sooner or later it must surely be replaced. In this study, we propose a new RUL estimation methodology to assist in decision making for the maintenance and replacement of assets from prioritizing equipment in a renovation plan. Our methodology uses advanced data analysis techniques that consider multiple competing criteria with the goal of maximizing values of the asset throughout its life cycle, while considering the rules of remuneration and service quality of the current regulation, as well as the values at risk according to the decisions and actions taken. Experimental results with real datasets show the efficiency of the proposed approach. Finally, this work also presents the development of an analytical tool to optimize asset renewal decisions applying the RUL estimation methodology proposed and its application to the Brazilian electric sector

Self-Healing Concrete: Concepts, Energy Saving and Sustainability

The production of cement accounts for 5 to 7% of carbon dioxide emissions in the world, and its broad-scale use contributes to climate imbalance. As a solution, biotechnology enables the cultivation of bacteria and fungi for the synthesis of calcium carbonate as one of the main constituents of cement. Through biomineralization, which is the initial driving force for the synthesis of compounds compatible with concrete, and crystallization, these compounds can be delivered to cracks in concrete. Microencapsulation is a method that serves as a clock to determine when crystallization is needed, which is assisted by control factors such as pH and aeration. The present review addresses possibilities of working with bioconcrete, describing the composition of Portland cement, analysis methods, deterioration, as well as environmental and energetic benefits of using such an alternative material. A discussion on carbon credits is also offered. The contents of this paper could strengthen the prospects for the use of self-healing concrete as a way to meet the high demand for concrete, contributing to the building of a sustainable society

Influence of milk type and addition of passion fruit peel powder on fermentation kinetics, texture profile and bacterial viability in probiotic yoghurts

AbstractThe effect of the addition of passion fruit peel powder (PFPP) on the fermentation kinetics and texture parameters, post-acidification and bacteria counts of probiotic yoghurts made with two milk types were evaluated during 28 days of storage at 4 °C. Milks were fermented by Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus (CY340), and one strain of probiotic bacteria: Lactobacillus acidophilus (L10 and NCFM), Bifidobacterium animalis subsp. lactis (Bl04 and HN019). The addition of PFPP reduced significantly fermentation time of skim milk co-fermented by the strains L10, NCFM and HN019. At the end of 28-day shelf-life, counts of B. lactis Bl04 were about 1 Log CFU mL–1 higher in whole yoghurt fermented with PFPP regarding its control but, in general, the addition of PFPP had less influence on counts than the milk type itself. The titratable acidity in yoghurts with PFPP was significantly higher than in their respective controls, and in skim yoghurts higher than in the whole ones. The PFPP increased firmness, consistency (except for the NCFM strain of L. acidophilus) and cohesiveness of all skim yoghurts. The results point out the suitability of using passion fruit by-product in the formulation of both skim and whole probiotic yoghurts

Use of Hydrogen as Fuel: A Trend of the 21st Century

The unbridled use of fossil fuels is a serious problem that has become increasingly evident over the years. As such fuels contribute considerably to environmental pollution, there is a need to find new, sustainable sources of energy with low emissions of greenhouse gases. Climate change poses a substantial challenge for the scientific community. Thus, the use of renewable energy through technologies that offer maximum efficiency with minimal pollution and carbon emissions has become a major goal. Technology related to the use of hydrogen as a fuel is one of the most promising solutions for future systems of clean energy. The aim of the present review was to provide an overview of elements related to the potential use of hydrogen as an alternative energy source, considering its specific chemical and physical characteristics as well as prospects for an in-crease in the participation of hydrogen fuel in the world energy matrix

Mapping of Alternative Oilseeds from the Brazilian Caatinga and Assessment of Catalytic Pathways toward Biofuels Production

Biofuels are increasingly important renewable resources in the world's energy matrix that have challenged the scientific community as well as small and large farmers to develop alternatives to fossil fuels in order to achieve the aims of energy transition. In particular, Brazil's proven competitiveness in agribusiness together with its rich biodiversity put the country in a key position in the biofuels market. The semiarid Caatinga of northeastern Brazil, an exclusive biome rich in many oilseed species suitable for potential energy purposes, is of particular interest in this field. Nowadays, soybeans are the main feedstock used for the production of biodiesel, but, due to the increasing demand for biofuels, the search for alternative sources of oil from tropical flora with high productivity is crucial. Under this premise, this systematic review focuses on mapping Caatinga's vegetable oil crops that could be used as alternative raw materials for biofuels' production in Brazil, in addition to traditional soybeans and sugarcane. To gain more detailed insight into these matrices, their main properties, including oil content, fatty acid profile and physicochemical properties, are discussed. Moreover, an overview is provided of processes to synthesize different types of biofuels, particularly biodiesel and aviation biokerosene, including the routes employing homogeneous, enzymatic and mainly heterogeneous catalysts. Finally, future prospects and challenges for renewable biofuels and the Caatinga biome are addressed