Machine learning approach for determining and optimizing influential factors of biogas production from lignocellulosic biomass.

Machine learning (ML) was used to predict specific methane yields (SMY) with a dataset of 14 features from lignocellulosic biomass (LB) characteristics and operating conditions of completely mixed reactors under continuous feeding mode. The random forest (RF) model was best suited for predicting SMY with a coefficient of determination (R) of 0.85 and root mean square error (RMSE) of 0.

Removal of Hydrogen Sulfide from Swine-Waste Biogas on a Pilot Scale Using Immobilized CM1.

Hydrogen sulfide (H2S) is a toxic and corrosive component that commonly occurs in biogas. In this study, H2S removal from swine-waste biogas using sulfur-oxidizing Paracoccus versutus CM1 immobilized in porous glass (PG) and polyurethane foam (PUF) biofilters was investigated. Bacterial compositions in the biofilters were also determined using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE).

Biogas production from high solids digestion of Pennisetum purpureum x Pennisetum typhoideum: Suitable conditions and microbial communities.

Effects of organic loading rates (OLRs), temperatures and effluent recirculation rates on biogas production from Giant Juncao Grass (GJG) using pilot-scale semi-continuously fed CSTRs were investigated. Thermophilic reactors could be stably operated at OLR up to 5.0 kg VS m d, while damaged process stability was detected in mesophilic reactors at OLR of 4.

Holistic determination of suitable conditions for biogas production from Pennisetum purpureum x Pennisetum americanum liquor in anaerobic baffled reactor.

Holistic approach had been undertaken to determine the suitable conditions for biogas production from Pennisetum purpureum x Pennisetum americanum (Napier Pak Chong1) liquor using the anaerobic baffled reactor (ABR). Effects of factors, i.e.

Fate of estrogens during the biological treatment of synthetic wastewater in a nitrite-accumulating sequencing batch reactor.

The fate of estrone (El), 17beta-estradiol (E2), and 17alpha-ethynylestradiol (EE2) was investigated in two nitrite-accumulating sequencing batch reactors operating under strictly aerobic (SBR1) conditions at different sludge ages (SRT, 1.7 to 17.1 d) and anoxic/anaerobic/aerobic (SBR2) conditions with different phases and durations of redox conditions, using a modified GC-MS analytical method for estrogen detection to ng/L concentrations.