Energy-saving pretreatments affect pelagic Sargassum composition and DNA metabarcoding reveals the microbial community involved in methane yield.

Sargassum spp. flood the Caribbean coastline, causing damage to the local economy and environment. Anaerobic digestion (AD) has been proposed as an attractive option for turning macroalgae into valuable resources. Sargassum spp. has a complex composition that affects the microbial composition involved in AD which generates a low methane yield. This study aimed to improve the methane yield of pelagic Sargassum, using different energy-saving pretreatments and identifying the microbial community associated with methane production. We applied different energy-saving pretreatments to algal biomass and assessed the methane yield using a biomethane potential (BMP) test. The microbial communities involved in the AD of the best- and worst-performing methanogenic systems were analyzed by high-throughput sequencing. The results showed that pretreatment modified the content of inorganic compounds, fibers, and the C:N ratio, which had a strong positive correlation with BMP. The water washing pretreatment resulted in the best methane yield, with an increase of 38%. DNA metabarcoding analysis revealed that the bacterial genera Marinilabiliaceae_uncultured, DMER64, Treponema, and Hydrogenispora, as well as the archaea genera Methanosarcina, RumEn_M2, Bathyarchaeia, and Methanomassiliicocus, dominated the microbial community with a high methane yield. This study is the first to demonstrate the microbial community structure involved in the AD of Sargassum spp. The pretreatments presented in this study can help overcome the limitations associated with methane yield.

Removal of carbon and nitrogen in wastewater from a poultry processing plant in a photobioreactor cultivated with the microalga Chlorella vulgaris.

This study evaluates the removal of COD and nitrogen from poultry wastewater in photobioreactors. Cell growth, the effect of light intensity (3200, 9800, and 12000 lux) and air flow (1.6, 3.2, and 4.8 L min-1) as a source of CO2 in bold basal medium and wastewater with different concentrations of COD were evaluated. The growth kinetics were modeled by using the Gompertz model and logistic model for both culture media. COD removals of up to 95% were achieved, and poultry wastewater was found to be a viable growing medium for Chlorella vulgaris. Finally, the wastewater met Mexican standards, and biomass was obtained with products valued as lipids (3.2 g lipid/100 g biomass) and proteins (342.94 mg L-1). The culture was found to have a dilatory behavior, and the rheological models of Ostwald de Waele, Ostwald de Waele linealized and Herschel Bulkley were utilized, showing a laminar behavior.

Methane Production of Sargassum spp. Biomass from the Mexican Caribbean: Solid-Liquid Separation and Component Distribution.

In the last decade, Sargassum spp. seaweed species have caused massive flooding on the Caribbean Sea coasts. These seaweed species have a high content of recalcitrant compounds, such as insoluble fibers and polyphenols, which generate low methane yields in anaerobic digestion (AD). This study investigated the effect of solid-liquid separation of Sargassum biomass on biodegradability and methane yield. A biochemical methane potential (BMP) test was conducted with both fractions and raw biomass (RB). A mass balance was developed to assess the distribution of the components. The obtained liquid fraction (LF) showed high biodegradability and a high methane production rate, and it generated a methane yield of 159.7 ± 7.1 N L kg VS-1, a value that corresponds to approximately twice that achieved with RB and the solid fraction (SF). The component distribution analysis showed that about 90% of total solids (TS), volatile solids (VS), ash, carbon, and cellulose were retained in the SF. In conclusion, the LF had high biodegradability and methane yield. This suggests the potential for LFs of Sargassum biomass to be treated in large-scale high-load reactors; however, studies applied to SFs are needed because they retain a large amount of organic matter with low biodegradability.

Effects of Ornamental Plant Density and Mineral/Plastic Media on the Removal of Domestic Wastewater Pollutants by Home Wetlands Technology.

Wastewater treatment (WWT) is a priority around the world; conventional treatments are not widely used in rural areas owing to the high operating and maintenance costs. In Mexico, for instance, only 40% of wastewater is treated. One sustainable option for WWT is through the use of constructed wetlands (CWs) technology, which may remove pollutants using cells filled with porous material and vegetation that works as a natural filter. Knowing the optimal material and density of plants used per square meter in CWs would allow improving their WWT effect. In this study, the effect of material media (plastic/mineral) and plant density on the removal of organic/inorganic pollutants was evaluated. Low (three plants), medium (six plants) and high (nine plants) densities were compared in a surface area of 0.3 m2 of ornamental plants (Alpinia purpurata, Canna hybrids and Hedychium coronarium) used in polycultures at the mesocosm level of household wetlands, planted on the two different substrates. Regarding the removal of contaminants, no significant differences were found between substrates (p ≥ 0.05), indicating the use of plastic residues (reusable) is an economical option compared to typical mineral materials. However, differences (p = 0.001) in removal of pollutants were found between different plant densities. For both substrates, the high density planted CWs were able to remove COD in a range of 86-90%, PO4-P 22-33%, NH4-N in 84-90%, NO3-N 25-28% and NO2-N 38-42%. At medium density, removals of 79-81%, 26-32, 80-82%, 24-26%, and 39-41%, were observed, whereas in CWs with low density, the detected removals were 65-68%, 20-26%, 79-80%, 24-26% and 31-40%, respectively. These results revealed that higher COD and ammonia were removed at high plant density than at medium or low densities. Other pollutants were removed similarly in all plant densities (22-42%), indicating the necessity of hybrid CWs to increase the elimination of PO4-P, NO3-N and NO2-N. Moreover, high density favored 10 to 20% more the removal of pollutants than other plant densities. In addition, in cells with high density of plants and smaller planting distance, the development of new plant shoots was limited. Thus, it is suggested that the appropriate distance for this type of polyculture plants should be from 40 to 50 cm in expansion to real-scale systems in order to take advantage of the harvesting of species in these and allow species of greater foliage, favoring its growth and new shoots with the appropriate distance to compensate, in the short time, the removal of nutrients.

Analysis of the behavior for operation parameters in the anaerobic digestion process with thermal pretreatment, using fuzzy logic.

This article presents a study that identifies the variables with greatest impact on the biogas and methane production over a process with thermal pretreatment, to accelerate anaerobic digestion process in sewage sludge in a water treatment plant, for a poultry processing factory, by using fuzzy logic. The designed fuzzy logic model includes 688 inference rules, with a correlation of 99.3% between prediction data against experimental data, for the biogas variable; and 97% for the methane variable. The predictions of the fuzzy logic model were analyzed with response surface models, and it is concluded that the temperature and operating time variables are mutually determining in the biogas and methane production. Likewise, this research provides a methodology for the design of an expert decision support system that allows to evaluate and optimize a mesophilic anaerobic digestion process through a previous thermal treatment in order to improve the yields of biogas and methane in the treatment of effluent sludge from agroindustry. These results propose to diffuse logic as a reliable tool to make comparisons, and predictions for operation variables management on the treatment of residual sludge with thermal pretreatment on anaerobic digestion.

Mitigation of greenhouse gases (CO2) generated in the anaerobic digestion of physicochemical sludges using airlift photobioreactors operated with Chlorella spp.

The aim of this study was to evaluate the mitigation of greenhouse gasses generated in the anaerobic digestion process of physicochemical sludges by evaluating the effect of CO2 supply and light intensity requirements on the growth of microalga Chlorella spp. and measuring the consumption of CO2. The best conditions at a laboratory scale were performed in an airlift photobioreactor (PBR) at pilot-scale plant (26 L) during 60 days with a CO2 supply of 2% v v-1 from an electric generator coupled to an anaerobic digestion of physicochemical sludge process. The maximum %CO2 consumed was 91.92% which was reached in the seventh supply cycle and biomass production was 2.18 g L-1. The results obtained showed that airlift-type PBRs are a suitable complement for anaerobic digestion of physicochemical sludge technologies in order to reduce emissions of greenhouse gases produced during the combustion of biogas.

Evaluation of Wastewater Treatment by Microcosms of Vertical Subsurface Wetlands in Partially Saturated Conditions Planted with Ornamental Plants and Filled with Mineral and Plastic Substrates.

The current knowledge about the role terrestrial ornamental plants play in constructed wetlands (CWs) has scarcely been evaluated. Likewise, little attention has been given towards the use of new support or fill media for subsurface flow CWs, which may result in the reduction of costs when implemented on a large scale. This study evaluated, during nine months, the effect of three terrestrial ornamental plants and two substrates on the elimination of pollutants in wastewaters by using fill-and-drain vertical subsurface flow CWs (FD-CWs). Sixteen microcosms were used, nine filled with polyethylene terephthalate (PET) and nine with porous river stone (PRS). For each type of substrate, duplicates of microcosms were used, utilizing Anthurium sp., Zantedeschia aethiopica, and Spathiphyllum wallisii as vegetation and two other CWs without vegetation as controls. The environmental conditions, number of flowers, and height of the plants were registered. The results revealed that both substrates in the FD-CWs were efficient in removing pollutants. The average removal of pollutants in systems with vegetation revealed a positive effect on the reduction of the biochemical oxygen demand (55⁻70%), nitrates (28⁻44%), phosphates (25⁻45%), and fecal coliforms (52⁻65%). Meanwhile, in units without vegetation, the reduction of pollutants was nearly 40⁻50% less than in those with vegetation. The use of PET as a filling substrate in CWs did not affect the growth and/or the flowering of the species; therefore, its use combined with the species studied in CWs may be replicated in villages with similar wastewater problems. This may represent a reduction in implementation costs when utilizing PET recycled wastes and PRS as substrates in these systems in comparison with the typical substrates used in CWs. More studies are needed to better understand the interactions among these novel support media and the commercial terrestrial ornamental plants.

Intelligent Spectroscopy System Used for Physicochemical Variables Estimation in Sugar Cane Soils.

The current condition of soils is a major area of interest due to the lack of certainty in their physicochemical properties, which can guarantee the quality and the production of a specific crop. Additionally, methodologies to improve land management must be implemented in order to address the consequences of many environmental issues. To date, many techniques have been implemented to improve the accuracy-and more recently the speed-of analysis, in order to obtain results while in the field. Among those, Near Infrared (NIR) spectroscopy has been widely used to achieve the objectives mentioned above. Nevertheless, it requires particular knowledge, and the cost might be high for farmers who own the fields and crops. Thus, the present work uses a system that implements capacitance spectroscopy plus artificial intelligence algorithms to estimate the physicochemical variables of soil used to grow sugar cane. The device uses the frequency response of the soil to determine its magnitude and phase values, which are used by artificial intelligence algorithms that are capable of estimating the soil properties. The obtained results show errors below 8% in the estimation of the variables compared to the analysis results of the soil in laboratories. Additionally, it is a portable system, with low cost, that is easy to use and could be implemented to test other types of soils after evaluating the necessary algorithms or proposing alternatives to restore soil properties.

Use of artificial neuronal networks for prediction of the control parameters in the process of anaerobic digestion with thermal pretreatment.

This article focuses on the analysis of the behavior patterns of the variables involved in the anaerobic digestion process. The objective is to predict the impact factor and the behavior pattern of the variables, i.e., temperature, pH, volatile solids (VS), total solids, volumetric load, and hydraulic residence time, considering that these are the control variables for the conservation of the different groups of anaerobic microorganisms. To conduct the research, samples of physicochemical sludge were taken from a water treatment plant in a poultry processing factory, and, then, the substrate was characterized, and a thermal pretreatment was used to accelerate the hydrolysis process. The anaerobic digestion process was analyzed in order to obtain experimental data of the control variables and observe their impact on the production of biogas. The results showed that the thermal pre-hydrolysis applied at 90°C for 90 min accelerated the hydrolysis phase, allowing a significant 52% increase in the volume of methane produced. An artificial neural network was developed, and it was trained with the database obtained by monitoring the anaerobic digestion process. The results obtained from the artificial neural network showed that there is an adjustment between the real values and the prediction of validation based on 60 samples with a 96.4% coefficient of determination, and it was observed that the variables with the major impact on the process were the loading rate and VS, with impact factors of 36% and 23%, respectively.

Development of energy efficient mixing strategies in egg-shaped anaerobic reactors through 3D CFD simulation.

This work describes a 3D computational fluid dynamic model, which characterizes the hydrodynamic behavior of a mixing strategy applied to egg-shaped reactors that lack a mechanical stirring device. The model is based on Navier-Stokes and material balance equations without a chemical reaction. To describe the behavior of mixing, initial water feed flows of 6, 7.5 and 9 mL s(-1) were used. An experimental validation was subsequently carried out using a pulse technique, with NaCl as a tracer. The residence time distributions were quantitatively determined. Then, the degradation process of the wastewater sludge was characterized by studying the time dependence of the dynamic viscosity, the concentration of volatile solids and the density of wastewater sludge. The data resulting were introduced into the validated model, and five feed flows from 9 to 13 mL s(-1), the best performance found was with feed flow of 11 mL s(-1).

Improved anaerobic digestion of a thermally pretreated mixture of physicochemical sludge; broiler excreta and sugar cane wastes (SCW): Effect on organic matter solubilization, biodegradability and bioenergy production.

Thermal pretreatment effect of a mixture of organic wastes (physicochemical sludge, excreta of broiler chickens and sugarcane wastes (SCW)) in the solubilization and biodegradability organic matter as well as bioenergy production by anaerobic digestion was evaluated. Two different mixtures of physicochemical sludge, excreta of broiler chickens and SCW (70%, 15%, 15% and 60%, 20%, 20% of VS, respectively) were treated at different temperatures (80 °C, 85 °C and 90 °C) and contact time (30, 60 and 90 min). Results indicate that, organic matter solubilization degree increased from 1.14 to 6.56%; subsequently, in the anaerobic digestion process, an increase of 50% in the volatile solids removal and 10% in biogas production was observed, while, retention time decreased from 23 up to 9 days. The results obtained were similar to pilot-scale. In both experimental scales it showed that the synergy produced by the simultaneous anaerobic digestion of different substrates could increase bioenergy production up to 1.3 L bio g(-1) VS removed and 0.82 L CH4 g(-1) VS removed. The treatment conditions presented in this study allow for large residue quantities to be treated and large bioenergy quantities to be produced (10% higher than during conventional treatment) without increasing the anaerobic digester volume.

Effect of low temperature thermal pre-treatment on the solubilization of organic matter, pathogen inactivation and mesophilic anaerobic digestion of poultry sludge.

Treatment of poultry industry effluents produces wastewater sludge with high levels of organic compounds and pathogenic microorganisms. In this research, the thermal pre-treatment of poultry slaughterhouse sludge (PSS) was evaluated for low temperatures in combination with different exposure times as a pre-hydrolysis strategy to improve the anaerobic digestion process. Organic compounds solubilization and inactivation of pathogenic microorganisms were evaluated after treatment at 70, 80 or 90°C for 30, 60 or 90 min. The results showed that 90°C and 90 min were the most efficient conditions for solubilization of the organic compounds (10%). In addition, the bacteria populations and the more resistant structures, such as helminth eggs (HE), were completely inactivated. Finally, the thermal pre-treatment applied to the sludge increased methane yield by 52% and reduced hydraulic retention time (HRT) by 52%.

Simplified interval observer scheme: a new approach for fault diagnosis in instruments.

There are different schemes based on observers to detect and isolate faults in dynamic processes. In the case of fault diagnosis in instruments (FDI) there are different diagnosis schemes based on the number of observers: the Simplified Observer Scheme (SOS) only requires one observer, uses all the inputs and only one output, detecting faults in one detector; the Dedicated Observer Scheme (DOS), which again uses all the inputs and just one output, but this time there is a bank of observers capable of locating multiple faults in sensors, and the Generalized Observer Scheme (GOS) which involves a reduced bank of observers, where each observer uses all the inputs and m-1 outputs, and allows the localization of unique faults. This work proposes a new scheme named Simplified Interval Observer SIOS-FDI, which does not requires the measurement of any input and just with just one output allows the detection of unique faults in sensors and because it does not require any input, it simplifies in an important way the diagnosis of faults in processes in which it is difficult to measure all the inputs, as in the case of biologic reactors.