Synergistic Co-Digestion of Microalgae and Primary Sludge to Enhance Methane Yield from Temperature-Phased Anaerobic Digestion

Effect of pretreated and anaerobically digested microalgae on the chemical and biochemical properties of soil and wheat grown on fluvisol

In this study, the effects of the potential application of digestate as an agricultural fertiliser obtained from anaerobically digested microalgae treated by three pretreatment methods, namely alkaline hydrogen peroxide (AHP), high temperature and pressure (HTP), and hydrodynamic cavitation (HC) on some properties of soil, and wheat growth and yield were investigated. For this purpose, pretreated and anaerobically digested microalgae digestates alone or together with diammonium phosphate (DAP) as a chemical fertiliser were applied to soil for wheat growth. The highest dosage of AHP pretreated digestate combined with a half dose of DAP applied to soil was rich in nutrients as 0.25%N and 7.19 mg kg-1 compared to all groups. The properties of the soils were enhanced by applying the highest dosage (0.06 g kg-1) of microalgae digestate combined with a half dose of DAP. 0.02 g kg-1 dosage of HC pretreated digestate combined with a half dose of DAP also greatly improved nitrogen use efficiency indices by up to 104%. The soils' enzyme activities increased in wheat growth experiments by applying either raw or pretreated microalgae digestates. The soils' β-glycosidase, alkaline phosphatase, and urease enzyme activities increased to 1.38 mg pNP g-1 soil, 4.91 mg pNP g-1 soil, and 2.27 mg NH4-N 100 g-1 soil respectively by the application of highest dosage of HC pretreated digestate. The digestates did not have a toxic effect on wheat growth, it was determined that applied pretreatment processes did not cause significant changes in wheat plant height or wet and dry weight.

Identification of factors affecting removal of antibiotic resistance genes in full-scale anaerobic digesters treating organic solid wastes

Efficiencies of removing antibiotic resistance genes (ARGs) and intI1 were explored using eight full-scale anaerobic digesters. The digesters demonstrated different characteristics on the basis of substrate types (food waste, manure or sludge); configuration (single or two-stage); temperature (psychrophilic, mesophilic or thermophilic); hydraulic retention time (HRT) (9.7-44 days); and operation mode (continuous stirred tank reactor or plug flow reactor). Digesters' configuration or operating parameters showed a greater effect on abundance of ARGs than the type of input substrate. Redundancy analysis (RDA) accounted for 85.2% of the total variances and digesters with the same configuration and operational conditions showed similar performance for removal of ARGs. The highest efficiencies of removing ARGs (99.99%) were observed in two-stage thermophilic digesters with relatively long HRTs (32 days). The lowest removal efficiency (97.93%) was observed in single-stage mesophilic with relatively short HRTs (9.7 days), likely due to vertical and horizontal gene transfer.

Effect of type of coagulants on removal efficiency and removal mechanisms of antibiotic resistance genes in anaerobic digestion of primary sludge produced via a chemically enhanced primary treatment process

The potential impact of the trivalent coagulant cations on the removal mechanisms, removal efficiencies and removal patterns of antibiotic resistance genes (ARGs) during anaerobic digestion (AD) of chemically enhanced primary treatment sludge (CEPTS) was investigated using polyaluminium chloride (PACl), ferric chloride (FeCl₃) and mixed FeCl₃-PACl. The removal efficiency of 23 ARGs and intI1 improved to 72.1% in AD of primary sludge with 100 mg/L FeCl₃ and was lowest (only 54.4 %) in AD of primary sludge with 25 mg/L PACl. The removal of ARGs in AD of CEPTS with addition of single or mixed types of Al-based coagulant began to increase rapidly at the onset of batch operation. On the other hand, both the rapid increase in the removal efficiency of ARGs in AD with FeCl₃ and the maximum removal efficiency were attained later than in the other ADs.

Effects of biological pretreatments of microalgae on hydrolysis, biomethane potential and microbial community

Parameters of temperature-phased anaerobic digestion (TPAD) were varied to study their effects on hydrolysis, biomethane potential (BMP), and microbial diversity of microalgae biodegradation. Anaerobic pretreatments at 85 °C demonstrated the release of soluble carbohydrate and protein molecules under low microbial metabolic activity. However, at 55 °C, anaerobic pretreatments showed superior performance in methane yield, nutrient release, and volatile fatty acids (VFAs) production due to dominant Clostridium. Furthermore, the highest destruction of volatile solids (VS) was observed during aerobic pretreatments at 55 °C under the influence of various quantities of these genera - Luteimonas, Symbiobacterium, Soehngenia, Thermobacillus, and Ureibacillus. Statistical analysis revealed that hydrolysis and BMP were not correlated. However, soluble nitrogen and phosphorous showed strong correlation with methane (r = 0.623 and 0.948, respectively) under thermo-anaerobic pretreatment, while VS removal and concentrations of acetic and butyric acids and lipids were positively correlated with each other under thermo-aerobic pretreatment.

Rapid Biochemical Methane Potential Evaluation of Anaerobic Co-Digestion Feedstocks Based on Near Infrared Spectroscopy and Chemometrics

Biochemical methane potential (BMP) of anaerobic co-digestion (co-AD) feedstocks is an essential basis for optimizing ratios of materials. Given the time-consuming shortage of conventional BMP tests, a rapid estimated method was proposed for BMP of co-AD—with straw and feces as feedstocks—based on near infrared spectroscopy (NIRS) combined with chemometrics. Partial least squares with several variable selection algorithms were used for establishing calibration models. Variable selection methods were constructed by the genetic simulated annealing algorithm (GSA) combined with interval partial least squares (iPLS), synergy iPLS, backward iPLS, and competitive adaptive reweighted sampling (CARS), respectively. By comparing the modeling performances of characteristic wavelengths selected by different algorithms, it was found that the model constructed using 57 characteristic wavelengths selected by CARS-GSA had the best prediction accuracy. For the validation set, the determination coefficient, root mean square error and relative root mean square error of the CARS-GSA model were 0.984, 6.293 and 2.600, respectively. The result shows that the NIRS regression model—constructed with characteristic wavelengths, selected by CARS-GSA—can meet actual detection requirements. Based on a large number of samples collected, the method proposed in this study can realize the rapid and accurate determination of the BMP for co-AD raw materials in biogas engineering.