Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools

Abstract

Steroid estrogens namely 17-estradiol (E2) and 17-ethinylestradiol (EE2) and antibiotics including sulfamethoxazole (SMX) are pharmaceutically active compounds (PhAC) of emerging concern due to their environmental and human health impacts even at ppb range concentrations. These compounds usually flow to wastewater treatment plants (WWTP) and are released to the aquatic systems due to inefficient removal in conventional biological systems. In this work, a sequencing batch reactor (SBR) with aerobic granular sludge (AGS) was operated in the presence of E2, EE2 and SMX. SVI5, SVI30/SVI5 ratio, VSS, and TSS of mature AGS (in absence of PhAC), as well as in the presence of PhAC (0.221mgL-1 of E2, 0.278mgL-1 of EE2 and 0.290mgL-1 of SMX), were successfully predicted with multilinear regression (MLR) using morphological and structural parameters of floccular and granular fractions of AGS obtained from quantitative image analysis (QIA). Good prediction models were obtained for the SVI5 (R2 of 0.976), floccular VSS (R2 of 0.949) and TSS (R2 of 0.934), granular VSS (R2 of 0.930) and TSS (R2 of 0.916), SVI30/SVI5 ratio (R2 of 0.917) and density (R2 of 0.889). These results emphasize the usefulness of this methodology for monitoring dysfunctions in AGS in the presence of the studied PhAC.