Systematic error in manometric measurement of biochemical methane potential: Sources and solutions

Fractional calculus as a generalized kinetic model for biochemical methane potential tests

This study presents a fractional calculus model as a generalized kinetic model for estimating the maximum methane yield and degradation kinetics in biomethane potential (BMP) assays, a key analytical method in anaerobic digestion research and application. The fractional model outperformed common first-order kinetic models by yielding superior data fitting and properly managing substrate heterogeneity. The fractional model showed robust performance in mono-digestion, co-digestion and pre-treatment BMP assays with or without presence of large tailing or sigmoidal patterns in the BMP curve. The main advantage of the fractional model over other models is its ability to capture the complexities of the methane production process without losing model accuracy. Assessment of the mathematical model revealed that for fractional orders greater than 0.8 the Mittag-Leffler sequence could be transformed into a more computationally efficient exponential function.

Growth Media Efficacy in Biochemical Methane Potential Assays

The Biochemical Methane Potential (BMP) assay is a vital tool for quantifying the amount of methane that specific biodegradable materials can generate in landfills and similar anaerobic environments. Applications of the protocol are extensive and while simple in design, the BMP assay can use anaerobic seed from many different types of sources to determine the methane potential from most biodegradable substrates. Many researchers use differing protocols for this assay, both including and excluding the use of synthetic growth medias, intended to provide vital nutrients and trace elements that facilitate methanogenesis and leave the substrate being tested as the only limiting factor in methane generation potential. The variety of previous approaches inspired this effort to determine the efficacy of adding synthetic growth media to BMP assays. The presented findings suggest the use of M-1 synthetic growth media, defined in this study, at a volumetric ratio of 10% active sludge: 90% M-1 media yielded optimal results in terms of gas yield and reduced variability.

Effect of Endogenous Methane Production: A Step Forward in the Validation of Biochemical Methane Potential (BMP) Tests

This work evaluates the influence of the inoculum type, the pre-consumption of the residual substrate and the ratio of blanks’ headspace volume to working volume (Hv Wv−1, 0.6 to 10) on Biochemical Methane Potential (BMP) measurements when methane is monitored by gas chromatography. Different inocula were tested: digested sewage sludge—DSS, granular sludge—GS and fresh dairy manure—DM. Microcrystalline cellulose was used as the substrate. BMP surpassed the maximum theoretical value (BMPmax = 414 L kg−1) when methane produced in the blanks was not discounted, showing that degassing cannot stand alone as an alternative to the procedure of discounting the inoculum’s background production. Still, when the residual substrate concentration is high (e.g., in DM), degassing is mandatory because methane produced from its digestion will conceal the methane produced from the substrate in the BMP determination. For inocula with a low residual substrate (e.g., GS), short degassing periods are recommended in order to avoid detrimental effects on methanogenic activity. For moderate residual substrate concentrations (e.g., DSS), BMP values closer to BMPmax (90–97%) were achieved after degassing and discounting the blanks with lower Hv Wv−1. For higher Hv ∙ Wv−1, less accurate quantification occurred, likely due to error propagation. Proper inoculum pre-incubation time and discounting the methane production from blanks with low Hv Wv−1 (adjusted according to the estimated background methane) are essential for accurate BMP determinations.

Impact of Operational Factors, Inoculum Origin, and Feedstock Preservation on the Biochemical Methane Potential

Anaerobic digestion for the valorization of organic wastes into biogas is gaining worldwide interest. Nonetheless, the sizing of the biogas plant units require knowledge of the quantity of feedstock, and their associated methane potentials, estimated widely by Biochemical Methane Potential (BMP) tests. Discrepancies exist among laboratories due to variability of protocols adopted and operational factors used. The aim of this study is to verify the influence of some operational factors (e.g., analysis frequency, trace elements and vitamins solution addition and flushing gas), feedstock conservation and the source of inoculum on BMP. Among the operational parameters tested on cellulose degradation, only the type of gas used for flushing headspace of BMP assays had shown a significant influence on methane yields from cellulose. Methane yields of 344 ± 6 NL CH₄ kg⁻¹ VS and 321 ± 10 NL CH₄ kg⁻¹ VS obtained from assays flushed with pure N₂ and N₂/CO₂ (60/40 v/v). The origin of inoculum (fed in co-digestion) only significantly affected the methane yields for straw, 253 ± 3 and 333 ± 3 NL CH₄ kg⁻¹ VS. Finally, freezing/thawing cycle effect depended of the substrate (tested on biowaste, manure, straw and WWTP sludge) with a possible effect of water content substrate.

Estimating the Methane Potential of Energy Crops: An Overview on Types of Data Sources and Their Limitations

As the anaerobic digestion of energy crops and crop residues becomes more widely applied for bioenergy production, planners and operators of biogas plants, and farmers who consider growing such crops, have a need for information on potential biogas and methane yields. A rich body of literature reports methane yields for a variety of such materials. These data have been obtained with different testing methods. This work elaborates an overview on the types of data source available and the methods that are commonly applied to determine the methane yield of an agricultural biomass, with a focus on European crops. Limitations regarding the transferability and generalisation of data are explored, and crop methane values presented across the literature are compared. Large variations were found for reported values, which can only partially be explained by the methods applied. Most notably, the intra-crop variation of methane yield (reported values for a single crop type) was higher than the inter-crop variation (variation between different crops). The pronounced differences in reported methane yields indicate that relying on results from individual assays of candidate materials is a high-risk approach for planning biogas operations, and the ranges of values such as those presented here are essential to provide a robust basis for estimation.

How Different Are Manometric, Gravimetric, and Automated Volumetric BMP Results?

The objectives of this study were to: (1) quantify differences in biochemical methane potential (BMP) measured using three measurement methods, including two popular methods (a commercial automated system (AMPTS II) and manual manometric) and one newer method (gravimetric), and (2) assess the importance of the mixing position in the measurement sequence. Powdered microcrystalline cellulose was used as the substrate in simultaneous tests. All methods gave similar results (<8% difference in the mean BMP) and were reasonably accurate (recovery of 80–86% of the theoretical maximum BMP). Manometric BMP values were consistently lower than gravimetric by 4–5%. Precision was lower for the automated method (relative standard deviation (RSD) of about 7%) than for the manual methods (RSD about 1–3%). Mixing after biogas measurement resulted in 3% higher BMP for both manual methods than mixing before, due to the lower measured CH4 production from blanks. This effect may be linked to a fraction of CH4 that remains dissolved or even as attached bubbles, and suggests that mixing before measurement is preferable. The automated volumetric and gravimetric methods (mode 2) gave very similar mean BMP values (1% different). However, kinetic analysis showed that methane production was faster with the automated volumetric method. This could come from an error in the estimation of the CH4 production rate for the automated method, or an increase in the degradation rate due to better mixing. Both automatic volumetric and manual gravimetric measurements met current validation criteria for mean cellulose BMP, but the RSD from the automated system exceeded the limit.

Improving Inter-Laboratory Reproducibility in Measurement of Biochemical Methane Potential (BMP)

Biochemical methane potential (BMP) tests used to determine the ultimate methane yield of organic substrates are not sufficiently standardized to ensure reproducibility among laboratories. In this contribution, a standardized BMP protocol was tested in a large inter-laboratory project, and results were used to quantify sources of variability and to refine validation criteria designed to improve BMP reproducibility. Three sets of BMP tests were carried out by more than thirty laboratories from fourteen countries, using multiple measurement methods, resulting in more than 400 BMP values. Four complex but homogenous substrates were tested, and additionally, microcrystalline cellulose was used as a positive control. Inter-laboratory variability in reported BMP values was moderate. Relative standard deviation among laboratories (RSDR) was 7.5 to 24%, but relative range (RR) was 31 to 130%. Systematic biases were associated with both laboratories and tests within laboratories. Substrate volatile solids (VS) measurement and inoculum origin did not make major contributions to variability, but errors in data processing or data entry were important. There was evidence of negative biases in manual manometric and manual volumetric measurement methods. Still, much of the observed variation in BMP values was not clearly related to any of these factors and is probably the result of particular practices that vary among laboratories or even technicians. Based on analysis of calculated BMP values, a set of recommendations was developed, considering measurement, data processing, validation, and reporting. Recommended validation criteria are: (i) test duration at least 1% net 3 d, (ii) relative standard deviation for cellulose BMP not higher than 6%, and (iii) mean cellulose BMP between 340 and 395 NmLCH4 gVS−1. Evidence from this large dataset shows that following the recommendations—in particular, application of validation criteria—can substantially improve reproducibility, with RSDR < 8% and RR < 25% for all substrates. The cellulose BMP criterion was particularly important. Results show that is possible to measure very similar BMP values with different measurement methods, but to meet the recommended validation criteria, some laboratories must make changes to their BMP methods. To help improve the practice of BMP measurement, a new website with detailed, up-to-date guidance on BMP measurement and data processing was established.

Development and Validation of a Low-Cost Gas Density Method for Measuring Biochemical Methane Potential (BMP)

Accurate determination of biochemical methane potential (BMP) is important for both biogas research and practice. However, access to laboratory equipment limits the capacity of small laboratories or biogas plants to conduct reliable BMP assays, especially in low- and middle-income countries. This paper describes the development and validation of a new gas density-based method for measuring BMP (GD-BMP). In the GD-BMP method, biogas composition is determined from biogas density. Biogas density is based on bottle mass loss and biogas volume, and these can be accurately measured using only a standard laboratory scale, inexpensive syringes, and a simple manometer. Results from four experiments carried out in three different laboratories showed that the GD-BMP method is both accurate (no significant bias compared to gravimetric or volumetric methods with biogas analysis by gas chromatography) and precise (<3% relative standard deviation is possible). BMP values from the GD-BMP method were also comparable to those measured for the same substrates with an industry standard automated system (AMPTS II) in two independent laboratories (maximum difference 10%). Additionally, the GD-BMP method was shown to be accurate even in the presence of leakage by excluding leakage from mass loss measurements. The proposed GD-BMP method represents a significant breakthrough for both biogas research and the industry. With it, accurate BMP measurement is possible with only a minimal investment in supplies and equipment.