Estimation of the main air pollutants from different biomasses under combustion atmospheres by artificial neural networks.

The production of biofuels to be used as bioenergy under combustion processes generates some gaseous emissions (CO, CO2, NOx, SOx, and other pollutants), affecting living organisms and requiring careful assessments. However, obtaining such information experimentally for data evaluation is costly and time-consuming and its in situ obtaining for regional biomasses (e.g., those from Northeast Brazil (NEB) is still a major challenge. This paper reports on the application of artificial neural networks (ANNs) for the prediction of the main air pollutants (CO, CO2, NO, and SO2) produced during the direct biomass combustion (N2/O2:80/20%) with the use of ultimate analysis (carbon, hydrogen, nitrogen, sulfur, and oxygen). 116 worldwide biomasses were used as input data, which is a relevant alternative to overcome the lack of experimental resources in NEB and obtain such information. Cross-validation was conducted with k-fold to optimize the ANNs and performance was analyzed with the use of statistical errors for accuracy assessments. The results showed an acceptable statistical performance for all architectures of ANNs, with 0.001-12.41% MAPE, 0.001-5.82 mg Nm-3 MAE, and 0.03-52.30 mg Nm-3 RMSE, highlighting the high precision of the emissions studied. On average, the differences between predicted and real values for CO, CO2, NO, and SO2 emissions from NEB biomasses were approximately 0.01%, 10-6%, 0.14%, and 0.05%, respectively. Pearson coefficient provided consistent results of concentration of the ultimate analysis in relation to the emissions studied and effectiveness of the test set in the developed models.

Investigation of the combustion process of fish scales from Northeast Brazil in a drop tube furnace (DTF).

The waste generated by the global fishing industry, such as fish scales, is mostly considered useless and discarded in a disorderly and/or unplanned way in inappropriate places, posing serious risks to both the environment and human health. This study proposes the use of fish scales in combustion processes as an alternative for such residues and to avoid their exposure in urban areas. Combustion experiments were conducted in a drop tube furnace (DTF), and the factors temperature, residence time, and sample particle size were investigated. The main atmospheric pollutants (CO, NO, CO2, and SO2) and the residues generated from the combustion processes were characterized by FTIR, EDS and ICP-OES analyses, and SEM images. The samples showed better performance at 1100 °C and 500 -ms residence time, when the burnout reached 96%, and particle size greater than 300-µm and 300-ms residence time led to the worst combustion performance (24.45% burnout), with the highest CO and NO peaks, indicating incomplete combustion of the fish scales. The analysis of the residues revealed total decomposition of the organic matter at temperatures above 700 °C and formation of hydroxyapatite. According to the DTF results, the use of fish scales in firing processes is a viable treatment of the residues, generating energy and avoiding environmental problems caused by inadequate disposal.

Potential application of fish scales as feedstock in thermochemical processes for the clean energy generation.

The replacement of fossil fuels by renewable sources has been discussed globally, because fossil fuels account for a large portion of the pollutant emissions into the atmosphere. Several cities along the Brazilian coast produce a variety of fish types, generating a large amount of waste, including viscera and fish scales, which are already used in several industrial processes. However, these cities still face a large environmental problem, i.e., residue disposal from commercial establishments, e.g., fishmongers, which are often discarded in a disordered and/or unplanned manner in inappropriate places. Within this scenario, the energy utilization of an animal biomass supplied by a fishery in the city of São Luís was investigated, submitting samples to combustion (synthetic air) and pyrolysis (100% N2) processes for the bioenergy generation. Physicochemical properties from fish scales were evaluated by proximate and ultimate analyzes, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-Ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and inductively coupled plasma - optical emission spectroscopy (ICP-OES). The thermal behavior of samples was evaluated by thermogravimetry/derivative thermogravimetry (TG/DTG), differential thermal analysis (DTA) and calorimetry (HHV/LHV). It was verified that the fish scales have carbon and oxygen the major elements, and insignificant amounts of sulfur and heavy metals (lead, copper, chromium, lithium, zinc). This material also presented a large amorphous region (89%), in addition to the presence of collagen fibers and hydroxyapatite crystals. The thermal and physicochemical characteristics of this material were evaluated and compare it to other biomasses already in use, predicting its use for the bioenergy generation.