A longitudinal dataset of reactor adaptation and operation during semicontinuous anaerobic digestion of black liquor
Description
This dataset was generated by the G-AQUA research group (Sustainable Environmental Management and Advanced Water and Waste Treatment) at Universidad Politécnica de Madrid (UPM), Spain. It contains 125 days of longitudinal monitoring data from two parallel semicontinuous anaerobic digesters treating real black liquor (RBL) and synthetic black liquor (SBL) under mesophilic conditions. The experimental campaign followed an adaptive operational strategy in which organic loading rate (OLR), hydraulic retention time (HRT), and co-substrate composition evolved according to reactor performance. The dataset includes operational variables, process monitoring parameters, and laboratory analyses, including biogas production, methane content, pH, electrical conductivity, COD fractions, total carbon, total nitrogen, and volatile fatty acids (VFAs). Three sequential co-substrates were evaluated throughout the study: ethanol, glycerol, and cheese whey. In addition to process measurements, the dataset documents the operational decisions associated with maintaining stable anaerobic digestion of a highly recalcitrant lignin-rich industrial wastewater. The dataset is intended to support exploratory data analysis, process monitoring, soft-sensor development, machine learning, hybrid modelling, and decision-support applications in anaerobic digestion systems.