Comparison of Performances of Kinetic Models for Biomethane Production with Cheese Whey Mixtures


MANAV DEMİR N., Unal E.

WATER AIR AND SOIL POLLUTION, vol.233, no.8, 2022 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 233 Issue: 8
  • Publication Date: 2022
  • Doi Number: 10.1007/s11270-022-05817-0
  • Journal Name: WATER AIR AND SOIL POLLUTION
  • Journal Indexes: Science Citation Index Expanded, Scopus, ABI/INFORM, Agricultural & Environmental Science Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, Chimica, Compendex, EMBASE, Environment Index, Geobase, Greenfile, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Biogas, Cheese whey, Biochemical methane potential (BMP), Substrate mixture, ANAEROBIC CO-DIGESTION, ENHANCED METHANE PRODUCTION, BIOGAS PRODUCTION, WASTE, PRETREATMENT, SUBSTRATE, INOCULUM, BIOMASS, SLUDGE, MANURE

Abstract

This paper summarizes findings from a study in which the biochemical methane potential (BMP) of cheese whey was investigated. The cheese whey and mixtures of it with various co-substrates were used in anaerobic serum bottles for a period of about 90 days. The effects of inoculum were also investigated using granular anaerobic sludge from gum industry and anaerobic sludge from a municipal wastewater treatment plant. A total of 14 groups were set with two different inoculums and various substrate mixtures. The highest cumulative biogas and methane production were observed as 1229 mL and 790 mL, respectively, for a mixture of 50% whey, 33% slaughterhouse wastewater, and 17% cattle manure inoculated with granular anaerobic sludge. The highest BMP was obtained for whey (diluted to 13%) inoculated with anaerobic sludge as 360 mLCH(4)/gCOD(added). Methane percentages in headspace for all serum bottles were above 50%. Several kinetic models to predict biogas production were calibrated. Results showed that the first-order model and the transference function showed the best prediction performance for most of the serum bottles.