Identification of Critical Problems in Biochemical Methane Potential (BMP) Tests From Methane Production Curves

Konrad Koch,Sören Weinrich,Sergi Astals,Sasha D Hafner

doi:10.3389/fenvs.2019.00178

Abstract

Biochemical methane potential (BMP) tests are routinely conducted in academia and industry to determine the methane potential of a given substrate. Although many guidelines have been proposed to standardize BMP tests, results published in the peer-reviewed literature show that critical flaws in experimental design or execution are still common. Therefore, a powerful but simple method for evaluating the quality of BMP measurements is proposed in this work: the specific methane production (SMP) curve from any BMP trial should have a similar shape for most substrates, and significant deviation from this typical response is usually associated with a lack of reliability in resulting BMP estimates. In this study, some common experimental mistakes were reproduced to demonstrate this concept and establish relationships between flaws in experiments, SMP curves, and BMP values. The studied flaws were inoculum storage (2 weeks and at different temperatures), inoculum dilution with water (no dilution to 1:2 dilution), and inoculum-to-substrate ratio (from 2.00 to 0.05). Common kinetic models were used to better assess SMP curves. All flaws exhibited an impact on the SMP curves, but excessive dilution and extremely low inoculum-to-substrate ratio had the largest impacts on both SMP curves and BMP. In the most extreme case (ISR of 0.05), there was a clear lag phase of more than 10 days, and the resulting BMP was 15% lower than for the reference case. Together these results demonstrate the utility of the proposed method. The ultimate goal of this research is to help less experienced researchers identify and address problems in their experimental procedure, ultimately contributing to more accurate BMP measurements. The general approach is both simple and useful, and should always be part of a quality check for BMP tests.

Highlights

Measurement of biochemical methane potential (BMP) of organic substrates is important for research (Ariunbaatar et al, 2016; Yeshanew et al, 2016; Benn and Zitomer, 2018; Hafner et al, 2018; Filer et al, 2019) and biogas plant management (Koch et al, 2016; Gandiglio et al, 2017; Lippert et al, 2018)
The main motivation for this study is to present a method that can help researchers with less experience recognize problems in BMP tests based on the specific methane production (SMP) curve (Figure 1)
Complete model predictions along with parameter estimates of all applied models are available in the Supplementary Material

Summary

Introduction

Measurement of biochemical methane potential (BMP) of organic substrates is important for research (Ariunbaatar et al, 2016; Yeshanew et al, 2016; Benn and Zitomer, 2018; Hafner et al, 2018; Filer et al, 2019) and biogas plant management (Koch et al, 2016; Gandiglio et al, 2017; Lippert et al, 2018). All of them provide more or less detailed information of how to design and conduct BMP tests, and two of them defined criteria to validate the obtained results (VDLUFA, 2011; Holliger et al, 2016) These validation criteria are either based on relative standard deviations among the replicates to guarantee high intra-laboratory reproducibility, or define a range for the methane yield of a positive control (i.e., microcrystalline cellulose). While it is hard to predict the methane potential of an unknown substrate, in the present study it is hypothesized that the SMP curve should have a similar shape for most substrates Significant deviation from this typical response usually indicates problems that need to be corrected in order to obtain reliable results. The guideline presents only hypothetical idealized curves and not actual measurements and it is not clear what might cause each response

Objectives

Methods

Results