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

Biochemical methane potential database: A public platform

Diverse factors influence biogas production, such as material properties, testing conditions, reporting methods and other additional processing techniques. This complexity makes it difficult to compare biochemical methane potential (BMP) data, replicate experiments' results, and improve efficiencies associated with engineering applications. This study has taken preliminary attempts to build a sliced and structured BMP database, but optimizing the organization of data information and collecting more comprehensive and manually checked data information to cope with the increasing richness of the BMP test content. The first-generation BMP database contains 746 sets of data, covering 7 major substrate categories, including 187 key indicators and 26 supplementary indicators. It offers functions including data screening, comparing, uploading, and visual display of BMP data. The application of the database in comparing different types of substrates and additives is shown. In the future, the BMP database will be regularly upgraded to become more comprehensive.

Comparison of pyrochar, hydrochar and lignite as additive in anaerobic digestion and NH4+ adsorbent

The impact of pyrochar, hydrochar and lignite addition on anaerobic digestion of food waste was investigated with and without ammonia inhibition under batch conditions. Furthermore, ammonium adsorption capacities of the chars were investigated. To determine anaerobic degradation of char, reference samples containing inoculum and char were analyzed, indicating a significant degradation of hydrochar. Depending on the evaluation method, the increase in methane yield due to hydrochar addition varied between no statistically significant difference and +14 %. No significant impact due to the addition of 5 g/l pyrochar and lignite on AD was found. NH₄⁺ adsorption capacities showed a significantly higher net adsorption capacity of lignite (1.58mg_NH4⁺/g_L), compared to pyrochar (0.63mg_NH4⁺/g_PC). A negative NH₄⁺ adsorption capacity (-0.51 mg_NH4⁺/g_HC) was found for hydrochar. A high H/C-ratio, O/C-ratio and cation exchange capacity of hydrochar and lignite indicate many functional groups and low chemical stability, enabling an increased interaction between NH₄⁺ and char.

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.

Measurement of Biochemical Methane Potential of Heterogeneous Solid Substrates: Results of a Two-Phase French Inter-Laboratory Study

Biochemical methane potential (BMP) is essential to determine the production of methane for various substrates; literature shows important discrepancies for the same substrates. In this paper, a harmonized BMP protocol was developed and tested with two phases of BMP tests carried out by eleven French laboratories. Surprisingly, for the three same solid tested substrates (straw; raw mix and dried-shredded mix of potatoes, maize, beef meat and straw; and mayonnaise), the standard deviations of the repeatability and reproducibility inter-laboratory were not enhanced by the harmonized protocol (average of about 25% depending on the substrate), as compared to a previous step where all laboratories used their own protocols. Moreover, statistical analyses of all the results, after removal of the outliers (about 15% of all observations), did not highlight significant effect of the operational effect on BMP (stirring, automatic or manual gas quantification, use of trace metal, uses a bicarbonate buffer, inoculum to substrate ratio) at least for the tested ranges. On the other hand, the average intra-laboratory repeatability was low, about 7%, whatever the protocol, the substrate and the laboratory. It also appears that drying the SA substrate, which contained proteins, carbohydrates, lipids and fibers, does not impact its BMP.

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.