Ofélia de Queiroz Fernandes Araújo

Optimization of a sequencing batch reactor for biological nitrogen removal

An optimal operating mode for a sequencing batch reactor was determined via a model-based optimization. Synthetic wastewater containing mainly organic matter (as glucose) and nitrogen (as ammonium chloride) was treated without any addition of an external carbon source to accomplish denitrification step. A simplified model was used to describe process dynamics, comprised of six ordinary differential equations and an empirical correlation for oxygen consumption rate. Batch cycle time was the chosen objective function to be minimized for a fixed volume of waste to be treated. Furthermore, as SBR operation is divided in two major phases - aerobic and anoxic, to achieve total pollutants removal within minimum time, these phases can be repeatedly alternated. To ensure availability of organic matter necessary for denitrification, these two phases were combined with feed steps. Different feed strategies were tested using one, two or three feed steps. A successive quadratic programming algorithm was used, and maximum values for final COD, nitrate and ammonium concentrations, as well as maximum feed pump flow rate were some the process constraints. One step feed strategy was indicated by the optimization leading to a batch cycle time of 5h.

A methodology for screening of microalgae as a decision making tool for energy and green chemical process applications

The increasing interest for biotechnological use of microalgae demands a methodology for selection of species suitable to support the development of technologies based on the use of such non-conventional renewable raw material, i.e., green industrial applications. The vast and expanding collection of experimental data on both cell growth and biomass composition available in the literature can be used to reduce the cost of the experimental investigations required to support process engineering and optimization. Selecting the appropriate organism requires extracting useful information from such data, a cumbersome task since various multidisciplinary factors must be considered. This paper presents a computer-aided methodology for selecting appropriate algal species given an energy or green chemical process application employing microalgae as a renewable raw material. The approach is “system oriented”, based on biomass composition and chemical processing of the biomass downstream of the CO2 biofixation and harvesting operations. Quantitative performance results are supported by professional process simulation. Besides comparison of a set of species performances, the proposed methodology also allows the discrimination among distinct algal compositions resulting from different growth conditions for a given species. Furthermore, three categories of screening metrics are proposed to be maximized by the decision making procedure in order to elicit the relevant information. To demonstrate the potential of the proposed methodology, a databank of both biochemical and elemental compositions of microalgal biomass was used in three green applications: Assessment of biomass heating value; production of syngas by gasification of the biomass; and production of Bio-H2. Within the accuracy of the databank employed to illustrate the procedure, the methodology selected Botryococcus braunii and Isochrysis galbana as potential promising candidates, for the three examined applications.

Effects of CO2 enrichment and nutrients supply intermittency on batch cultures of Isochrysis galbana.

Aiming at enhanced performance to increase economic feasibility of microalgae based processes, Isochrysis galbana was grown in three modes of cultivation: batch, intermittent fed batch and semi-continuous. The batch mode was conducted under two regimes of aeration: conventional aeration and CO2 enriched aeration (5% v/v in air). Increased biomass productivity without significant impact on lipid accumulation was observed for CO2 enriched aeration relatively to cultivation aerated with air only. The intermittent fed batch cultivation policy was proven to be useful for lipid accumulation, increasing the lipid content by 19.8%. However, the semi-continuous mode resulted in higher productivity due to increased biomass concentration; the biomass productivity reached 0.51 g/(Ld). Fluorescence measurements were performed; the calculated low electron transport rate showed the need to increase the irradiance. The results showed that I. galbana can be grown in semi-continuous condition at high levels of biomass productivity.

Dynamic simulation of flash drums using rigorous physical property calculations

The dynamics of flash drums is simulated using a formulation adequate for phase modeling with equations of state (EOS). The energy and mass balances are written as differential equations for the internal energy and the number of moles of each species. The algebraic equations of the model, solved at each time step, are those of a flash with specified internal energy, volume and mole numbers (UVN flash). A new aspect of our dynamic simulations is the use of direct iterations in phase volumes (instead of pressure) for solving the algebraic equations. It was also found that an iterative procedure previously suggested in the literature for UVN flashes becomes unreliable close to phase boundaries and a new alternative is proposed. Another unusual aspect of this work is that the model expressions, including the physical properties and their analytical derivatives, were quickly implemented using computer algebra.

State observers for a biological wastewater nitrogen removal process in a sequential batch reactor

Biological removal of nitrogen is a two-step process: aerobic autotrophic microorganisms oxidize ammoniacal nitrogen to nitrate, and the nitrate is further reduced to elementary nitrogen by heterotrophic microorganisms under anoxic condition with concomitant organic carbon removal. Several state variables are involved which render process monitoring a demanding task, as in most biotechnological processes, measurement of primary variables such as microorganism, carbon and nitrogen concentrations is either difficult or expensive. An alternative is to use a process model of reduced order for on-line inference of state variables based on secondary process measurements, e.g. pH and redox potential. In this work, two modeling approaches were investigated: a generic reduced order model based on the generally accepted IAWQ No. 1 Model [M. Henze, C.P.L., Grady, W., Gujer, G.V.R., Marais, T., Matsuo, Water Res. 21 (5) (1987) 505-515]-generic model (GM), and a reduced order model specially validated with the data acquired from a benchscale sequential batch reactor (SBR) specific model (SM). Model inaccuracies and measurement errors were compensated for with a Kalman filter structure to develop two state observers: one built with GM, the generic observer (GO), and another based on SM, the specific observer (SO). State variables estimated by GM, SM, GO and SO were compared to experimental data from the SBR unit. GM gave the worst performance while SM predictions presented some model to data mismatch. GO and SO, on the other hand, were both in very good agreement with experimental data showing that filters add robustness against model errors, which reduces the modeling effort while assuring adequate inference of process variables.

Cultivation of Spirulina maxima in medium supplemented with sugarcane vinasse

The feasibility of sugarcane vinasse as supplement in growth medium of Spirulina maxima was investigated. The cell was cultivated under autotrophic (no vinasse, 70 μmol photons m(-2) s(-1)), heterotrophic (no light, culture medium supplemented with vinasse at 0.1% v/v and 1.0% v/v) and mixotrophic conditions (70 μmol photons m(-2) s(-1), vinasse at 0.1% v/v and 1.0% v/v). These preliminary results suggested a cyclic two-stage cultivation - CTSC, with autotrophic condition during light phase of the photoperiod (12 h, 70-200 μmol photons m(-2) s(-1)) and heterotrophic condition during dark phase (12h, 3.0% v/v vinasse). The adopted CTSC strategy consisted in three cycles with 75% withdrawal of suspension and reposition of medium containing 3.0% v/v vinasse, separated by autotrophic rest periods of few days between cycles. Results show an increase of biomass concentration between 0.495 g L(-1) and 0.609 g L(-1) at the 7th day of each cycle and high protein content (between 74.3% and 77.3% w/w).

Assessment of the impact of salinity and irradiance on the combined carbon dioxide sequestration and carotenoids production by Dunaliella salina: A mathematical model

Current anthropogenic activities have been causing a significant increase in the atmospheric concentration of CO2 over the past 60 years. To mitigate the consequent global warming problem, efficient technological solutions, based on economical and technical grounds, are required. In this work, microalgae are studied as important biological systems of CO2 fixation into organic compounds through photosynthesis. These microorganisms are potential sources of a wide variety of interesting chemical compounds, which can be used for commercial purposes, reducing the cost of CO2 capture and sequestration. Specifically, Dunaliella salina culture was studied aiming at the impact evaluation of operational conditions over cellular growth and carotenoid production associated with the CO2 sequestration on focus. The main experimental parameters investigated were salinity and irradiance conditions. The experimental results supported the development of a descriptive mathematical model of the process. Based on the proposed model, a sensitivity analysis was carried out to investigate the operational conditions that maximize CO2 consumption and carotenoid production, in order to guide further development of technological routes for CO2 capture through microalgae. A preliminary cost estimation of CO2 sequestration combined to carotenoids production for a 200 MW power plant is presented, based on the growth rates achieved in this study. Biotechnol. Bioeng. 2009;102: 425–435.

Electrical stimulation of saccharomyces cerevisiae cultures

Modulation of cell endogenous membrane potential by an external electrical field influences the structure and function of membrane compartments, proteins and lipid bi-layer. In this work, the effects of applied potential on Saccharomyces cerevisiae growth were characterized through simple yet conclusive experiments. Cell growth time profile and cell division were investigated as macroscopic response to the electrical stimulation. Control experiments were conducted under identical conditions except for the absence of applied potential. Through comparative analysis, electrical stimulation was verified to alter cell cycle as smaller sized population was observed, suggesting that a synchrony in cell division was promoted. Power spectral analysis was employed to sustain synchrony enhancement, and mathematical modeling was conducted for determining kinetic growth changes. Monod type kinetic parameters for growth were determined by non-linear regression. The affinity constant (namely kS) presented a dependence on applied potential suggesting changes on transport across cell membrane. Electrochemically promoted stress was also verified to inhibit growth as well as to induce changes on cell viability.

An age-structured population balance model for microbial dynamics

This work presents an age-structured population balance model (ASPBM) for a bioprocess in a continuous stirred-tank fermentor. It relates the macroscopic properties and dynamic behavior of biomass to the operational parameters and microscopic properties of cells. Population dynamics is governed by two time- and age-dependent density functions for living and dead cells, accounting for the influence of substrate and dissolved oxygen concentrations on cell division, aging and death processes. The ASPBM described biomass and substrate oscillations in aerobic continuous cultures as experimentally observed. It is noteworthy that a small data set consisting of nonsegregated measurements was sufficient to adjust a complex segregated mathematical model.

A KINETIC MODEL FOR THE FIRST STAGE OF PYGAS UPGRADING

Pyrolysis gasoline - PYGAS - is an intermediate boiling product of naphtha steam cracking with a high octane number and high aromatic/unsaturated contents. Due to stabilization concerns, PYGAS must be hydrotreated in two stages. The first stage uses a mild trickle-bed conversion for removing extremely reactive species (styrene, dienes and olefins) prior to the more severe second stage where sulfured and remaining olefins are hydrogenated in gas phase. This work addresses the reaction network and two-phase kinetic model for the first stage of PYGAS upgrading. Nonlinear estimation was used for model tuning with kinetic data obtained in bench-scale trickle-bed hydrogenation with a commercial Pd/Al2O3 catalyst. On-line sampling experiments were designed to study the influence of variables - temperature and spatial velocity - on the conversion of styrene, dienes and olefins.