Adsorption of atrazine and 2,4-D pesticides on alternative biochars from cedar bark sawdust (Cedrella fissilis).

Bark residues of the forest species Cedrela fissilis were physically and chemically modified with zinc chloride (ZnCl2) as an activating agent. The two modified materials were analyzed as adsorbents in removing atrazine and 2,4-D herbicides from effluents. Firstly, the precursor material and the modified ones were characterized by different techniques to identify the structural changes that occurred in the surfaces. Through TGA, it was observed that both modified materials have thermal stability close to each other and are highly superior to the precursor. X-ray diffractions proved that the amorphous structure was not altered, the three materials being highly heterogeneous and irregular. The micrographs showed that the treatments brought new spaces and cavities on the surface, especially for the material carbonized with ZnCl2. The pHPZC of the modified materials was close to 7.5. The physically modified material had a surface area of 47.31 m2 g-1 and pore volume of 0.0095 cm3 g-1, whereas the carbonized material had a surface area of 98.12 m2 g-1 and pore volume of 0.0099 cm3 g-1. Initial tests indicated that none of the adsorbents were efficient in removing 2,4-D. However, they showed good potential for removing atrazine. The Koble-Corrigan isothermal model best fits the experimental data, with a maximum capacity of 3.44 mg g-1 and 2.70 mg g-1 for physically modified and with ZnCl2, respectively. The kinetic studies showed that the system tends to enter into equilibrium after 120 min, presenting good statistical indicators to the linear driving force model (LDF). The surface diffusion coefficients were 2.18×10-9 and 2.37×10-9 cm2 s-1 for atrazine adsorption on the physically and chemically modified materials. These results showed that the application of residues from the processing of cedar bark is promising. However, new future studies must be carried out to improve the porous development of the material and obtain greater adsorption capacities.

An approach to assess and identify polymers in the health-care waste of a Brazilian university hospital.

This work presents the health-care waste (HCW) management and an approach to assess and identify polymers in a General Surgery Unit - Internment Service (GSU) of a Brazilian university hospital, to estimate the main polymers presenting in medical devices that are consumed during a year, discarded either as infecting (Group A) or as scarifying residue (Group E). Among the waste produced from the medical devices, 3.14 ton (98.79%) were composed of polymers (63.06% of plastics and 35.73% elastomers) while around 0.03 ton (1.21%) by metals. The proposed approach is composed of 4 steps: (1) Collecting data about consumed medical devices to be categorized into the residues Groups (A and E); (2) Identifying the polymeric composition with information provided by suppliers; (3) Characterizing the polymer functional groups by Fourier-Transform Infrared Spectroscopy (FTIR) and (4) Determining the polymer melting point by Differential Scanning Calorimetry (DSC). According to the results, the analyzed HCW was composed mainly of polypropylene (80.88%), high-density polyethylene (5.28%), polystyrene (4.51%), and cellulose (3.58%), from a total of 11 different polymers.

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016.

Modeling the microbial growth and temperature profile in a fixed-bed bioreactor.

Aiming to scale up and apply control and optimization strategies, currently is required the development of accurate plant models to forecast the process nonlinear dynamics. In this work, a mathematical model to predict the growth of the Kluyveromyces marxianus and temperature profile in a fixed-bed bioreactor for solid-state fermentation using sugarcane bagasse as substrate was built up. A parameter estimation technique was performed to fit the mathematical model to the experimental data. The estimated parameters and the model fitness were evaluated with statistical analyses. The results have shown the estimated parameters significance, with 95 % confidence intervals, and the good quality of process model to reproduce the experimental data.

Optimization of enzymatic hydrolysis of cassava to obtain fermentable sugars.

This work evaluates the enzymatic hydrolysis of starch from cassava using pectinase, α-amylase, and amyloglucosidase. A central composite rotational design (CCRD) was carried out to evaluate the effects of amyloglucosidase, pectinase, reaction time, and solid to liquid ratio. All the experiments were carried out in a bioreactor with working volume of 2 L. Approximately 98% efficiency hydrolysis was obtained, resulting in a concentration of total reducing sugar released of 160 g/L. It was concluded that pectinase improved the hydrolysis of starch from cassava. Reaction time was found to be significant until 7 h of reaction. A solid to liquid ratio of 1.0 was considered suitable for hydrolysis of starch from cassava. Amyloglucosidase was a significant variable in the process: after its addition to the reaction media, a 30%-50% increase in the amount of total reducing sugar released was observed. At optimal conditions the maximum productivity obtained was 22.9 g/(L·h).