Biochemical methane potential (BMP) tests: Reducing test time by early parameter estimation

The Prevalence and Antibiotic-Resistant of Listeria monocytogenes in Livestock and Poultry Meat in China and the EU from 2001 to 2022: A Systematic Review and Meta-Analysis

To compare the prevalence and antibiotic resistance rate of Listeria monocytogenes in livestock and poultry (beef, pork and chicken) meat between China and the European Union (EU), a meta-analysis was conducted. Ninety-one out of 2156 articles in Chinese and English published between January 2001 and February 2022 were selected from four databases. The prevalence of L. monocytogenes in livestock and poultry (beef, pork and chicken) meat in China and Europe was 7.1% (3152/56,511, 95% CI: 5.8-8.6%) and 8.3% (2264/889,309, 95% CI: 5.9-11.0%), respectively. Moreover, a decreasing trend was observed in both regions over time. Regarding antibiotic resistance, for the resistance to 15 antibiotics, the pooled prevalence was 5.8% (95% CI: 3.1-9.1%). In both regions, the highest prevalence was found in oxacillin, ceftriaxone and tetracycline, and a large difference was reported between China and the EU in ceftriaxone (52.6% vs. 17.3%) and cefotaxime (7.0% vs. 0.0%). Based on the above, it remains a significant challenge to enforce good control measures against the meat-sourced L. monocytogenes both in China and in the EU.

Characterization of Biofilm Microbiome Formation Developed on Novel 3D-Printed Zeolite Biocarriers during Aerobic and Anaerobic Digestion Processes

Background: Aerobic or anaerobic digestion is involved in treating agricultural and municipal waste, and the addition of biocarriers has been proven to improve them further. We synthesized novel biocarriers utilizing zeolites and different inorganic binders and compared their efficiency with commercially available biocarriers in aerobic and anaerobic digestion systems. Methods: We examined BMP and several physicochemical parameters to characterize the efficiency of novel biocarriers on both systems. We also determined the SMP and EPS content of synthesized biofilm and measured the adherence and size of the forming biofilm. Finally, we characterized the samples by 16S rRNA sequencing to determine the crucial microbial communities involved. Results: Evaluating BMP results, ZSM-5 zeolite with bentonite binder emerged, whereas ZSM-5 zeolite with halloysite nanotubes binder stood out in the wastewater treatment experiment. Twice the relative frequencies of archaea were found on novel biocarriers after being placed in AD batch reactors, and >50% frequencies of Proteobacteria after being placed in WWT reactors, compared to commercial ones. Conclusions: The newly synthesized biocarriers were not only equally efficient with the commercially available ones, but some were even superior as they greatly enhanced aerobic or anaerobic digestion and showed strong biofilm formation and unique microbiome signatures.

Propionate-cultured sludge bioaugmentation to enhance methane production and micropollutant degradation in landfill leachate treatment

This research investigates the use of propionate-cultured sludge to enhance methane (CH₄) production and micropollutant biodegradation in biochemical methane potential (BMP) experiment treating landfill leachate. The experiments were carried out using non-acclimatized and acclimatized seed sludge with variable food to microorganism ratios of 1:1 and 1:2. Under the propionate-cultured sludge bioaugmentation, the concentrations of propionate-cultured sludge were varied between 10, 20, and 30 % (v/v). The acclimatized seed sludge exhibited high microbial abundance and diversity which promoted the CH₄ production and micropollutant biodegradation. The modified Gompertz model indicated that the optimal condition was the acclimatized seed sludge with 30% (v/v) propionate-cultured sludge, achieving the lag time (λ), maximum CH₄ production rate (R_max), and maximum CH₄ potential yield (P_max) of 0.57 day, 17.35 NmL/h, and 140.58 NmL/g COD. The research novelty lies in the use of propionate-cultured sludge bioaugmentation in landfill leachate treatment to enhance CH₄ production and micropollutant biodegradation.

Integrated management of residues from tomato production: Recovery of value-added compounds and biogas production in the biorefinery context

The biorefinery approach must be boosted in the management of agro-residues in the future. The present study aims to investigate the valorization of tomato production residues, namely rotten tomato (unfit for consumption - RT), green tomato (GT), and tomato branches (TB). The assessment involves the recovery of value-added compounds through the extraction process followed by biogas production through anaerobic digestion. A thorough characterization of the three residues (RT, GT, and TB) was carried out, including the identification of volatile compounds by solid-phase microextraction (SPME) and gas chromatography/mass spectrometry (GC/MS). The volatiles analysis revealed the presence of flavor enhancer compounds and molecules with insecticidal properties. A solid-liquid extraction with ethanol allowed the recovery of value-added compounds in the extracts, in particular phenolic compounds, β-carotene, and lycopene, which contributed to the antioxidant activity. RT and TB extracts were found to be richer in total phenolic compounds (~27 mg GAE/g_db dry basis) and exhibited higher antioxidant activity (IC₅₀ = 0.911 and 0.745 mg/mL). The tomato branches extract had the highest concentration of carotenoids with 37.23 and 3.08 mg/kg_db of β-carotene and lycopene, respectively. The biochemical methane potential (BMP) was assessed in sealed reactors operating in anaerobic conditions for all the raw (RT, GT, and TB) and extracted substrates waste (RTe, GTe, and TBe). While the BMP of RT and GT was in the range of 232-285 mL CH₄/g VS, a lower value of 141 mL CH₄/g VS was obtained for TB. The methane production for each pair of raw and extracted substrates (RT/RTe, GT/GTe, and TB/TBe) was considered statistically similar at a 95 % confidence level. Overall, the value-added compounds recovery through ethanolic extraction did not compromise the methane production of the materials.

Estimation of Energy Recovery Potential from Primary Residues of Four Municipal Wastewater Treatment Plants

Wastewater treatment plants have been traditionally developed for the aerobic degradation of effluent organic matter, and are associated with high energy consumption. The adoption of sustainable development targets favors the utilization of every available energy source, and the current work aims at the identification of biomethane potential from non-conventional sources derived from municipal wastewater treatment processes. Byproducts derived from the primary treatment process stage were collected from four sewage treatment plants in Greece with great variation in design capacity and servicing areas with wide human activities, affecting the quality of the influents and the corresponding primary wastes. The samples were characterized for the determination of their solids and fats content, as well as the concentration of leached organic matter and nutrients, and were subjected to anaerobic digestion treatment for the measurement of their biomethane production potential according to standardized procedures. All samples exhibited potential for biogas utilization, with screenings collected from a treatment plant receiving wastewater from an area with combined rural and agro-industrial activities presenting the highest potential. Nevertheless, these samples had a methanogens doubling time of around 1.3 days, while screenings from a high-capacity unit proved to have a methanogens doubling time of less than 1 day. On the other hand, floatings from grit chambers presented the smallest potential for energy utilization. Nevertheless, these wastes can be utilized for energy production, potentially in secondary sludge co-digestion units, converting a treatment plant from an energy demanding to a zero energy or even a power production process.

Batch Anaerobic Co-Digestion and Biochemical Methane Potential Analysis of Goat Manure and Food Waste

The improper management of goat manure from concentrated goat feeding operations and food waste leads to the emission of greenhouse gasses and water pollution in the US. The wastes were collected from the International Goat Research Center and a dining facility at Prairie View A&M University. The biochemical methane potential of these two substrates in mono and co-digestion at varied proportions was determined in triplicates and processes were evaluated using two nonlinear regression models. The experiments were conducted at 36 ± 1 °C with an inoculum to substrate ratio of 2.0. The biomethane was measured by water displacement method (pH 10:30), absorbing carbon dioxide. The cumulative yields in goat manure and food waste mono-digestions were 169.7 and 206.0 mL/gVS, respectively. Among co-digestion, 60% goat manure achieved the highest biomethane yields of 380.5 mL/gVS. The biodegradabilities of 33.5 and 65.7% were observed in goat manure and food waste mono-digestions, while 97.4% were observed in the co-digestion having 60% goat manure. The modified Gompertz model is an excellent fit in simulating the anaerobic digestion of food waste and goat manure substrates. These findings provide useful insights into the co-digestion of these substrates.

Biochemical methane potential prediction for mixed feedstocks of straw and manure in anaerobic co-digestion

To rapidly estimate the biochemical methane potential (BMP) of feedstocks, different multivariate regression models were established between BMP and the physicochemical indexes or near-infrared spectroscopy (NIRS). Mixed fermentation feedstocks of corn stover and livestock manure were rapidly detected BMP in anaerobic co-digestion (co-AD). The results showed that the predicted accuracy of NIRS model based on characteristic wavelengths selected by multiple competitive adaptive reweighted sampling outperformed all regression models based on the physicochemical indexes. For the NIRS regression model, coefficient of determination, root mean squares error, relative root mean squares error, mean relative error and residual predictive deviation of the validation set were 0.982, 6.599, 2.713%, 2.333% and 7.605. The results reveal that the predicted accuracy of NIRS model is very high, and meet the requirements of rapid prediction of BMP for co-AD feedstocks in practical biogas engineering.

Rapid Biochemical Methane Potential Evaluation of Anaerobic Co-Digestion Feedstocks Based on Near Infrared Spectroscopy and Chemometrics

Biochemical methane potential (BMP) of anaerobic co-digestion (co-AD) feedstocks is an essential basis for optimizing ratios of materials. Given the time-consuming shortage of conventional BMP tests, a rapid estimated method was proposed for BMP of co-AD—with straw and feces as feedstocks—based on near infrared spectroscopy (NIRS) combined with chemometrics. Partial least squares with several variable selection algorithms were used for establishing calibration models. Variable selection methods were constructed by the genetic simulated annealing algorithm (GSA) combined with interval partial least squares (iPLS), synergy iPLS, backward iPLS, and competitive adaptive reweighted sampling (CARS), respectively. By comparing the modeling performances of characteristic wavelengths selected by different algorithms, it was found that the model constructed using 57 characteristic wavelengths selected by CARS-GSA had the best prediction accuracy. For the validation set, the determination coefficient, root mean square error and relative root mean square error of the CARS-GSA model were 0.984, 6.293 and 2.600, respectively. The result shows that the NIRS regression model—constructed with characteristic wavelengths, selected by CARS-GSA—can meet actual detection requirements. Based on a large number of samples collected, the method proposed in this study can realize the rapid and accurate determination of the BMP for co-AD raw materials in biogas engineering.

Comparative analysis of prediction models for methane potential based on spent edible fungus substrate

In this study, ten spent edible fungus (SEF) with different compositional features were used for the maximum methanogenic potential (P₀) evaluation, and the prediction models including regression and kinetics based on this were developed separately. The results showed that the regression model with more chemical components had a good correlation with the P₀, and at least three chemical compositions could reach the threshold of sensitivity. The Cone model showed the best fitting effect on P₀ in all kinetic models, which had higher R-square (>0.994) and lower error (1.004-5.672%). Meanwhile, the minimum digestive testing time (14 days) was determined by the evaluation of sensitivity via statistical indicators. It is concluded that the determination of the prediction model of P₀ should be evaluated with the combination of statistical indicators and specific requirements.

Biogas Potential of the Side Streams Obtained in a Novel Phenolic Extraction System from Olive Mill Solid Waste

The olive oil production is an important industrial sector in many Mediterranean areas, but it is currently struggled by the necessity of a proper valorisation of the olive mill solid waste or alperujo. The alperujo is the main by-product generated during the two-phase olive oil extraction, accounting for up to 80% of the initial olive mass. The alperujo is a source of valuable compounds, such as the pomace olive oil or highly interesting phenolic compounds. In the present research, a novel biorefinery approach has been used for phenolic compounds recovery. However, the extraction of these valuables compounds generates different exhausted phases with high organic matter content that are required to be managed. This study consists of the evaluation of the anaerobic biodegradability of the different fractions obtained in a novel biorefinery approach for the integral valorisation of alperujo. The results show that the different phases obtained during the biorefinery of the alperujo can be effectively subjected to anaerobic digestion and no inhibition processes were detected. The highest methane yield coefficients were obtained for the phases obtained after a two-months storages, i.e., suspended solids and liquid phase free of suspended solids, which generated 366 ± 7 mL CH₄/g VS and 358 ± 6 mL CH₄/g VS, respectively. The phenol extraction process reduced the methane yield coefficient around 25% due to the retention of biodegradable compounds during the extraction process. Regardless of this drop, the anaerobic digestion is a suitable technology for the stabilization of the different generated residual phases, whereas the high market price of the extracted phenols can largely compensate the slight decrease in the methane generation.

Assessment of a fast method to predict the biochemical methane potential based on biodegradable COD obtained by fractionation respirometric tests

The biochemical methane potential test (BMP) is the most common analytical technique to predict the performance of anaerobic digesters. However, this assay is time-consuming (from 20 to over than 100 days) and consequently impractical when it is necessary to obtain a quick result. Several methods are available for faster BMP prediction but, unfortunately, there is still a lack of a clear alternative. Current aerobic tests underestimate the BMP of substrates since they only detect the easily biodegradable COD. In this context, the potential of COD fractionation respirometric assays, which allow the determination of the particulate slowly biodegradable fraction, was evaluated here as an alternative to early predict the BMP of substrates. Seven different origin waste streams were tested and the anaerobically biodegraded organic matter (COD_met) was compared with the different COD fractions. When considering adapted microorganisms, the appropriate operational conditions and the required biodegradation time, the differences between the COD_met, determined through BMP tests, and the biodegradable COD (COD_b) obtained by respirometry, were not significant (COD_met (57.8026 ± 21.2875) and COD_b (55.6491 ± 21.3417), t (5) = 0.189, p = 0.853). Therefore, results suggest that the BMP of a substrate might be early predicted from its COD_b in only few hours. This methodology was validated by the performance of an inter-laboratory studyconsidering four additional substrates.

Impact of Storage Conditions on the Methanogenic Activity of Anaerobic Digestion Inocula

The impact of storage temperature (4, 22 and 37 °C) and storage time (7, 14 and 21 days) on anaerobic digestion inocula was investigated through specific methanogenic activity assays. Experimental results showed that methanogenic activity decreased over time with storage, regardless of storage temperature. However, the rate at which the methanogenic activity decreased was two and five times slower at 4 °C than at 22 and 37 °C, respectively. The inoculum stored at 4 °C and room temperature (22 °C) maintained methanogenic activity close to that of fresh inoculum for 14 days (<10% difference). However, a storage temperature of 4 °C is preferred because of the slower decrease in activity with lengthier storage time. From this research, it was concluded that inoculum storage time should generally be kept to a minimum, but that storage at 4 °C could help maintain methanogenic activity for longer.

Temperature regulations impose positive influence on the biomethane potential versus digesting modes treating agricultural residues

Temperature regulations (mesophilic/thermophilic) and digesting modes (mono-/co-digestion) play key roles in the biomethane potential of anaerobic digestion, but limited research focus on the synergetic effects on microbial interconnections of the biomethane process. In this study, the pineapple and maize residues under different operations were monitored by batch biogas assays and 16S high-throughput sequencing to explore: 1) biomethane potential regarding different operations, 2) microbial communities in different treated reactors, and 3) significant factors determine microbial distribution. Results showed that the co-digestion had higher methanogenic abundance and biomethane production (~3300 mL_n) versus mono-digestion under mesophilic condition. To the thermophilic condition, the co-digestion had less methanogenic abundance but more biomethane production (~5000 mL_n). Statistical evidence uncovered that the Clostridiaceae and Thermoanaerobacteraceae dominated pathways linked closely with methanogenesis which may contribute the more biomethane production in the thermophilic condition. This study demonstrated the temperature regulations drove rare taxa as major contributors for biomethane production.

Benefits and drawbacks of food and dairy waste co-digestion at a high organic loading rate: A Moosburg WWTP case study

Anaerobic co-digestion (AcoD) is a key technology in reframing organic waste as a viable energy source. A lack of documented experience on full-scale AcoD at wastewater treatment plants (WWTPs) has created a bottleneck in AcoD implementation, which is further tightened by the focus of existing AcoD studies being on low co-substrate loading (<50%) and the obtainable benefits. This study aims to fill this gap by investigating the drawbacks and benefits of high-ratio co-substrate dosing of food and dairy wastes at the Moosburg WWTP (Germany) from 2014 to 2017. The Moosburg WWTP co-digests sewage sludge, food waste, and dairy wastes at a 35:47:18 ratio by volatile solids (organic loading rate (OLR) of 3.0 kg_VS/(m³·day)). During the study period, this high co-substrate dosing increased the methane potential by 300 ± 50%. The corresponding high methane yield significantly increased the on-site electricity production, resulting in energy neutrality in 2014-2015. The corresponding economic gain from gate fees was 48,000 ± 5,000 € per year. The observed drawbacks included solids accumulation inside the digester (5 m³/month), high nitrogen backload (65% increase from co-substrate addition), reduced retention time (loss of 1.18 days/year from solids accumulation), and reduced dewaterability. The high nitrogen content in the centrate is treated by sequential batch reactors (SBRs), using lactose as the carbon source for denitrification. This study presents an alternative approach for determining gate fees based on the economic gains from inherent methane content, which identified waste milk, lactose and grease trap sludge as the most profitable co-substrates.

Correlations between biochemical composition and biogas production during anaerobic digestion of microalgae and cyanobacteria isolated from different sources of Turkey

Twenty one species of microalgae and Cyanobacteria were isolated from different ecosystems in Turkey to investigate the relation between biochemical methane potential (BMP) and biochemical characterization. Since the highest dry weight (X), specific growth rate (µ) and maximum productivity (P_max) were obtained from the five species, identification of species and BMP tests with the composition analyzes were examined. BMP values were determined 308, 293, 242, 229 and 230 mLCH₄/gVS for Desertifilum tharense, Phormidium animale, Chlorella sp., Anabeana variabilis and Chlorophyta uncultured. The Pearson correlation and principal component analysis (PCA) were applied to extract and clarify the correlation between composition of species and their methane production. Pearson correlation shows that glucose, Kjeldahl nitrogen and chlorophyll are highly and positively correlated with BMP. PCA revealed that Chlorella sp., Chlorophyta uncultured and Desertifilum tharense were placed against Phormidium animale distinguished by its extreme and different profile because of Kjeldahl nitrogen and glucose content.

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

This work focused on identification and quantification of systematic sources of error in manometric measurement of biochemical methane potential (BMP). Error was determined by comparison to gravimetric measurements and direct measurement of leakage. One out of three types of septa leaked above 1 bar (gauge) headspace pressure, losing 25 to 30% of biogas produced. But manometric BMP showed a negative bias even in the absence of leakage. Maximum error was 24% from 160 mL bottles with 40 mL of headspace (headspace fraction of 0.25). Error decreased with increasing headspace fraction, and was small (3%) for a headspace fraction of 0.75, showing that a high headspace volume is the best approach for minimizing error. Relative error in CH₄ production measurement increased with headspace pressure as well, but controlling pressure alone is not sufficient for minimizing error. Calculations showed that observed error may be due to volatilization of CH₄ during venting as well as inaccurate headspace volume determination, although these sources do not completely explain the magnitude of error observed. Measurement of biogas composition before and after venting showed that CO₂ volatilization can occur, but is probably a minor source of error. Calculations showed that error in estimation of ambient pressure or headspace temperature had only minor effects (<3%). Gravimetric measurements, which were unaffected by leakage and insensitive to error in estimation of headspace pressure, temperature or volume, can provide a simple check on manometric results, or a complete replacement.

Biochemical Methane Potential (BMP) Assay Method for Anaerobic Digestion Research

Biochemical methane potential (BMP) tests are widely used for characterizing a substrate’s influence on the anaerobic digestion process. As of 2018, there continues to be a lack of standardization of units and techniques, which impacts the comparability and validity of BMP results. However, BMP methods continue to evolve, and key aspects are studied to further eliminate systematic errors. This paper aims to update these key aspects with the latest research progress both to introduce the importance of each variable to those new to BMP measurements and to show the complexity required to design an accurate BMP test.

A comparison of methods for early prediction of anaerobic biogas potential on biologically treated municipal solid waste

Anaerobic gas production tests, generically Biochemical Methane Potential (BMP) or Biogas Potential (BP) tests, are often used to assess biodegradability, though long duration limits their utility. This research investigated whether simple modelling approaches could provide a reliable earlier prediction of total biogas production. Data were assessed from a non-automated biogas test on a large number of both fresh and processed municipal solid waste (MSW) samples, sourced from a mechanical biological treatment (MBT) plant. Non-linear models of biogas production curves were useful in identifying a suitable test endpoint, supporting a test duration of 50 days. Biogas production at 50 days (B₅₀) was predicted using the first 14 days of test data, using (a) linear correlation, (b) a new linearisation process, and (c) non-linear kinetic models. Prediction errors were quantified as relative root mean squared error of prediction (rRMSEP), and bias. Predictions from most models were improved by removing the initial exponential increase phase. Linear correlation gave the most precise and accurate predictions at 14 days (rRMSEP = 2.8%, bias under 0.05%) and allowed acceptable prediction (rRMSEP <10%) both at 8 days, and at 6 days using separate correlations for each sample type. Of the other predictions, the new linearisation process gave the lowest rRMSEP (10.6%) at 14 days. More complex non-linear models conferred no advantage in prediction of B₅₀. These results demonstrate that early prediction of anaerobic gas production is possible for a well-optimised test, using only basic equipment and without recourse to external data sources or complex mathematical modelling.

Development of statistical predictive models for estimating the methane yield of Italian municipal sludges from chemical composition: a preliminary study

The biochemical methane potential (BMP) of primary and biological sludge varies in a wide range, mostly depending on location, sewer characteristics, wastewater treatment plant design and operating conditions. BMP tests are useful to verify the performance of a full scale digester, but they are not yet a common procedure in the operation of most Italian facilities because of cost and test duration. Changes in the composition of sewage sludge can lead to a high variation of biogas production. Aimed at developing BMP predictive models based on low cost and fast analyses, this study investigated the chemical composition of 20 sludge samples by means of principal component and multiple linear regression analyses. Three preliminary predictive models were developed based on soluble organic nitrogen, volatile solids, carbohydrates, proteins, lipids and an operational parameter, the sludge retention time: the explained variance and the standard errors of prediction of BMP are in the range 77-81% and 21-34 NmL_CH4·g_VS ^-1, respectively. Models were evaluated on five additional samples: errors ranged 2-15% for four samples and about 54% for one sample, collected from a peculiar facility. Further data and variables describing the operation mode of the waterline would certainly improve the reliability and robustness of the models.

Comparative analysis of methods and models for predicting biochemical methane potential of various organic substrates

Biochemical methane potential (BMP) corresponds to the maximum methane production at anaerobic digestion infinite time and is a key parameter to evaluate the suitability of substrates to obtain biogas. The main objective of this work is to explore the data available in the literature for ten categories of substrates to compare and develop new methods and mathematical models able to predict BMP. Indeed, experimental procedure is time-consuming, laborious and costly, and the development of methods or models based on properties easily assessed may be very helpful at industrial scale. In this study, three substrates (banana waste, tomato waste and winery wastewater) were tested and compared with >150 results from the literature. The analysis involved four methods (Met_I to Met_IV) and five models developed by multivariate regression (Mod_I to Mod_V). Met_I is related to elemental analysis; Met_II with the organic fraction composition; Met_III is associated with chemical oxygen demand (COD); Met_IV is based on NIR spectra. Regression models are combinations by grouping single variables: C, H, O, N (Mod_I); hemicellulose, lignin (LG), acid detergent fibre (ADF) (Mod_II); volatile solids (VS), COD (Mod_III); proteins (PT), carbohydrates (CRB), lipids (LP) (Mod_IV); and CRB, LP, PT, LG, ADF (Mod_V). The results showed that no significant correlation can be found between BMP and single common properties (e.g. VS or C/N ratio). However, good results may be achieved with models developed by multivariate regression (R² from 0.93 to 0.98, and R²_adj from 0.91 to 0.96). The prediction of BMP based on Met_IV, which is based on NIR spectroscopy combined with a multivariate regression model, revealed to be a promising method for both data from literature as well as for substrates analyzed in the present work.