The IWA Anaerobic Digestion Model No 1 (ADM1).

By Damien J. Batstone, J. Keller, I. Angelidaki, S. Kalyuzhnyi, S. Pavlostathis, A. Rozzi, W. Sanders, H. Siegrist, V. Vavilin. Water Science and Technology, 2002

2,010 citations recorded by the source corpus.

Subfields: Building and Construction, Molecular Biology, Pollution

View Paper: https://www.semanticscholar.org/paper/756e3ac325f0e6d1b747ed4c1fc484908ef70326

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. An-Ping Zeng
2. Saket Navlakha

In Pollution

1. Xavier Flores-Alsina
2. D. Puyol
3. Jorge Rodríguez
4. Damien J. Batstone

Citations in the corpus

• Tree-based automated machine learning to predict biogas production for anaerobic co-digestion of organic waste (2021, background): “24 Also, the complicated microbial and physicochemical process of AD substantially affects the prediction accuracy of mechanistic models.”
• Mathematical modelling of anaerobic digestion processes: applications and future needs (2015, methodology): “2.2 Liquid mixed digesters Anaerobic sludge digestion was original focus of kinetic modelling of anaerobic processes (Gossett and Belser 1982; Pavlostathis and Gossett 1986) as well as a key focus for the ADM1 and similar models (Batstone et al. 2002; Siegrist et al. 2002).”
• Biosystems analysis and engineering of microbial consortia for industrial biotechnology (2010, methodology): “It is aimed at direct and simple implementation in full-scale plants and should assist transfer from research to industry [81].”
• Renewable Power-to-Gas: A technological and economic review (2016, background): “Lastly, the methane is produced by aceticlastic methanogenesis (depletion of acetate) and hydrogenotrophic methanogenesis (CO2 reduction with H2) [102,103].”