Search Results (175)

This research proposes an approach based on a circular economy principle for the integral valorization of Sargassum from the Mexican Caribbean. The biomass was characterized through proximal and elemental analyses, and then an oxidative pretreatment was carried out to enhance a sequential processing scheme to extract sodium alginate and use the solid waste as a substrate for biogas production via anaerobic digestion. The oxidative pretreatment successfully reduces the recalcitrant content and the concentration of heavy metals. The sodium alginate extracted from treated biomass achieves a yield higher than 20%; the characterization of the polymer via nuclear magnetic resonance showed that the mannuronic-to-guluronic ratio was between 0.34 and 0.62, indicating the potential for its use for environmental and biomedical applications. The highest yield in methane production was 328 mL CH₄/g of volatile solids, with a purity of 90%, and was achieved using the waste from alginate extraction with an inoculum-to-substrate ratio of 1:1. The experimental data presented an excellent fit to a Gompertz model (R² > 0.99). The proposed valorization pathway improves the sustainability of Sargassum management, prioritizing the recovery of high-value compounds before energy production. This circular approach provides a framework for converting environmental challenges into opportunities in the Caribbean. Full article

Early-stage estimation of total biogas yield is useful for preliminary screening of anaerobic digestion substrates when detailed kinetic parameters, long-term reactor data and substrate-specific biochemical methane potential tests are not yet available. This study develops a compact Gradient Boosting Regression model for estimating total biogas yield from basic substrate and operating descriptors commonly reported in anaerobic digestion studies. A literature-informed reconstructed benchmark dataset containing 120 records from twelve organic substrate groups was used. The response variable was total biogas yield, expressed as mL g⁻¹ volatile solids (VS) added; methane yield and methane content were not used as interchangeable target variables. Seven input variables were considered: volatile solids content, total solids content, carbon-to-nitrogen ratio, residence time descriptor, digestion temperature, pH and organic loading rate. The model was evaluated using the coefficient of determination (R²), mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), five-fold cross-validation and residual diagnostics. On the test subset, the model achieved R² = 0.9885, MAE = 13.40 mL g⁻¹ VS, RMSE = 16.16 mL g⁻¹ VS and MAPE = 3.73%. The mean five-fold cross-validation score was R² = 0.9720 ± 0.0180, indicating stable interpolation performance within the investigated data domain. Feature-importance analysis identified C/N ratio as the dominant predictor, followed by volatile solids and total solids. However, residual diagnostics showed heteroscedasticity, and the low apparent importance of pH and temperature was attributed to their narrow ranges in the compiled dataset, rather than to biological irrelevance. The proposed model is therefore intended as an early-stage screening tool for total biogas yield estimation, not as a universal methane yield or design-level prediction model. Full article

This study, conducted in the Ecuadorian Andes, evaluated the anaerobic co-digestion of local crop residues (amaranth and quinoa) with llama, vicuña, and pig manure to analyze methane production kinetics. The raw materials were characterized by proximate, elemental, and structural analyses, and biogas volume and the CH₄ fraction were monitored daily. The Amaranth-vicuña and Amaranth-llama treatments reached 77.29 ± 5.63 and 64.62 ± 3.62 mL biogas/g VS and 36.20 ± 7.29 and 31.78 ± 3.62 mL CH₄/g VS, respectively; in contrast, Quinoa-vicuña and Quinoa-llama produced only 1.04 ± 0.25 and 0.24 ± 0.03 mL CH₄/g VS. Monod-model parameters were estimated using an apparent formulation based on the methane production rate, and the kinetic behavior was compared with first-order, modified Gompertz, and modified logistic models. In addition, artificial neural networks (ANNs) were evaluated to predict the methane production curve from substrate characterization. Network 44, with a 13-15-10-1 architecture, yielded an overall R² = 0.998, validation R² = 0.997, and validation MSE = 0.415. Ten-times repeated five-fold cross-validation of the same architecture yielded R² = 0.985 ± 0.007 and RMSE = 1.21 ± 0.28 mL CH₄/g VS, supporting its interpolation capability within the experimental domain, although this does not demonstrate extrapolation to new substrate combinations. Overall, the proposed approach combines interpretable kinetic parameters with ANN-based prediction, but external validation with independent datasets is still required. The reported yields correspond to the specific production achieved in a low-cost batch system operated at room temperature and should not be interpreted as standardized biochemical methane potential (BMP) values. Full article

This study presents a kinetic evaluation of anaerobic co-digestion of pulsed electric field (PEF)-pretreated corn stover using three models: the Modified Gompertz (MG), Logistic, and Reaction Curve (RC). The objective was to assess model performance and improve the interpretation of biogas production dynamics beyond cumulative biogas yield analysis. Experimental data were obtained from batch mesophilic digestion of fine and coarse corn stover fractions subjected to PEF pretreatment with applied voltages of 350 V and 1 kV. All models achieved high coefficients of determination (R² ≥ 0.97), indicating good agreement between experimental and modeled biogas production curves. However, error metrics and information criteria revealed clear differences in predictive performance. The MG model provided the closest agreement with experimentally determined biogas production potential (Bmax), whereas the Logistic model consistently underestimated both Bmax and the maximum biogas production rate (Rmax). The RC model yielded the lowest prediction errors and favorable information criteria values but showed greater sensitivity to the initial phase of biogas production, occasionally overestimating Bmax and Rmax. Moderate PEF pretreatment increased both Bmax and Rmax, particularly in the fine fractions, without substantially prolonging the lag phase. In contrast, pretreatment at the higher applied voltage resulted in more heterogeneous kinetic responses, including prolonged lag phases and increased variability of kinetic parameters. Full article

Anaerobic digestion (AD) is a common waste management method for producing renewable energy from biogas. However, animal manures typically have low C/N ratios, which can limit biogas recovery. This study aims to optimize biogas production through the co-digestion of goat manure (GM) with high-C/N lignocellulosic rice husk (RH) and sludge as the inoculum. Characterization of the substrate and inoculum revealed a low GM C/N ratio (GM = 21.3), whereas RH has a high-C/N (RH = 107.3). The volatile solids-to-total solids (VS/TS) ratios were around 82–85% for GM and RH. Batch experiments were conducted at different organic loading rates, with an inoculum-to-substrate ratio of 2:1 (mL:g), at 36 ± 1 °C for 65 days. This study investigates optimizing biomethane recovery by using serum-bottle biomethane potential (BMP) and compares kinetic performance and yields across different GM-to-RH ratios with the characteristics of the influent and effluent. The highest BMP values (mL CH₄/g_VS) occurred at 100% GM (245.1), followed by 90% GM (233.6) and 30% GM (232.5), indicating a strong synergy between GM and RH at specific mixing ratios. Kinetic modeling using both the modified Gompertz and first-order models effectively described digestion dynamics, allowing for estimation of potential lag phases and maximum production rates. These models aligned well with experimental data across substrates, aiding process design. Overall, the results show that strategic co-digestion of GM with RH can maximize methane recovery, with defined substrate ratios and a clear understanding of the kinetics essential for scale-up and sustainable biogas production. Full article

The aim of this study was to evaluate the effect of Sida hermaphrodita harvest timing on biomass composition, properties, and methane fermentation performance. In addition, an energy–economic assessment was performed for biomass obtained at different stages of the growing season. The economic assessment assumed CHP electrical and thermal efficiencies of 38% and 47%, electricity and heat prices of 0.18 and 0.05 EUR/kWh, respectively, month-specific agrotechnical costs, and OPEX equal to 30% of total energy revenue. The biomass exhibited clear seasonal changes, transitioning from a material with high bioavailability during the summer period to a structurally more recalcitrant substrate in the autumn and winter months, as indicated by increasing lignification and fibrous fraction contents. The highest CH₄ production yields, ranging from 300 to 320 mL/g VS, and maximum production rates of up to 33.5 mL/g VS·d were obtained between June and August. In December, the CH₄ yield decreased to 180 ± 9 mL/g VS, accompanied by a substantial deterioration in kinetic performance. Despite the relatively stable theoretical methane potential, which ranged from 405 to 430 mL/g VS, its conversion efficiency declined from 77.1% in the summer period to 41.9% in the winter period. Regression analysis confirmed the key influence of the C/N ratio and total solids content, with model fits reaching R² values of 0.74–0.80, while the structure of lignocellulosic complexes had a less pronounced but still relevant effect. The maximum CH₄ production per unit cultivation area, approaching 3380 m³/ha, was achieved in July–August, reflecting a balance between high specific methane yield and biomass productivity. At the same time, the results demonstrated that the maximum biomass yield did not translate into the highest energy and economic performance. The highest net economic return, 1789 ± 330 EUR/ha, was obtained in July, despite biomass yield being 13.6% higher in September. These findings indicate a seasonal decoupling between biomass yield and energy performance, highlight biomass quality as a critical determinant of anaerobic digestion efficiency, and support harvest-date optimization as a low-cost strategy for the practical use of S. hermaphrodita in agricultural biogas plants. Further long-term continuous and semi-continuous studies are required to validate process stability and performance under industrial operating conditions. Full article

Anaerobic digestion (AD) is an effective technology for sustainable waste management, renewable energy production and resource recovery within a circular economy. This study offers a systematic bibliometric review of global advances in AD research and assesses their relevance to Ghana. Using the PRISMA framework, the literature from 2011 to 2025 was sourced from the Scopus database and analysed through bibliometric and thematic methods. The review emphasises four key factors affecting AD performance: municipal solid waste as feedstock, pretreatment technologies, biochemical methane potential (BMP) assessment and process optimisation. Studies were included if they addressed any of these themes. Non-English publications, inaccessible full texts and papers lacking bibliographic metadata were excluded. After screening 3424 records, 61 studies were included in the systematic review. After metadata screening, 3374 of the 3424 retrieved records were retained for bibliometric analysis. Results show that municipal solid waste, food waste, agricultural residues and sewage sludge are promising sources for biogas generation. Pretreatment techniques, including thermal, chemical, mechanical and biological, significantly enhance substrate biodegradability and methane production. BMP assessment is a reliable way to gauge feedstock suitability and energy recovery potential. Optimising parameters like pH, temperature, organic loading, hydraulic retention time and co-digestion ratios improves process stability and biogas yield. The review highlights the increasing use of modelling and optimisation to boost digester performance and facilitate scale-up. In Ghana, abundant organic waste offers significant opportunities for biogas development. Employing advanced feedstock characterisation, pretreatment, BMP evaluation and optimisation can improve AD efficiency, support renewable energy, reduce waste disposal issues and promote Ghana’s shift toward a sustainable circular bioeconomy. Full article

Sub-Saharan Africa is rich in agricultural biomass, yet its biogas utilization is far below its potential. Most earlier studies failed to identify the nonlinear, multi-factor relationships that shape real national biogas yields and fully clarify this imbalance. This study constructs a 2007–2023 panel dataset for ten sub-Saharan African countries, merging agricultural output, socioeconomic, and infrastructure metrics. Gradient Boosting model and SHapley Additive exPlanations (SHAP) analysis are applied for empirical evaluation. SHAP analysis confirms that charcoal consumption yields the largest contribution to biogas production, with a mean absolute SHAP value of 1.018. The correlation between the two variables is negative under the threshold and becomes positive beyond this critical level. Urbanization has an inverted U-shaped correlation with biogas output, and the marginal contributions of predictors vary substantially across sampled countries. Instead, fragile supply chains, rural labor loss, and fierce competition in clean energy markets curb local biogas production. Forecasts show that regional biogas output will continue to fall until 2030. Targeted national policies matching each country’s core influencing factors are therefore urgently required. Full article

To improve the efficiency of AD for tetracycline-containing wastewater, this study systematically investigated the effects of ZVI and PAC on pollutant removal, VFA metabolism, biogas production, and sludge physicochemical characteristics. RSM was employed to optimize the co-dosing conditions of ZVI and PAC. The results suggested that ZVI and PAC could significantly facilitate COD degradation, and the optimal dosages for COD removal were 1000 mg/L ZVI and 2000 mg/L PAC with a removal efficiency of 61.03% and 56.9%, respectively. Both additives effectively accelerated the catabolism of typical VFAs, thereby mitigating the accumulation of intermediate metabolites that may cause AD system instability. In terms of biogas production, 1000 mg/L ZVI and 2000 mg/L PAC enhanced methane yield by 55.9% and 35.0% compared to the control group, with ZVI exhibiting a more prominent enhancement effect. Mechanistic analysis suggested that ZVI and PAC reinforced the AD process through multiple pathways: enhancing the electrical conductivity of the AD system, possibly facilitating the electron transfer pathways, and stimulating the secretion of EPSs by anaerobic microbes. RSM optimization yielded the optimal co-dosing parameters: 1000 mg/L ZVI and 1200 mg/L PAC. Under these conditions, the methane yield was increased by 71.18% relative to the control group, and the model validation accuracy reached 97.94%. This study provides a viable technical strategy and theoretical basis for enhancing the efficiency of anaerobic treatment of tetracycline-containing wastewater. Full article

In intensive greenhouse agriculture, irrational fertilization practices can exacerbate carbon emissions and impair ecosystem service functions. To address this issue, biogas slurry and biochar were introduced as waste-derived substitutes for mineral fertilizer, and the effects of different fertilization strategies on the net ecosystem carbon balance (N_ECB) and ecosystem service value (ESV) of greenhouse tomato (Solanum lycopersicum L.) production systems over two growing seasons (spring–summer and autumn–winter) were systematically evaluated. When economic return was prioritized, the treatment with 25% biogas slurry substituting for mineral fertilizer (BS25) performed best, with ESVs of 641,606.83 and 629,987.37 CNY ha⁻¹ in the spring–summer and autumn–winter seasons, respectively; the treatment with 50% biogas slurry substitution (BS50) ranked second, and both treatments were significantly superior to the others (p < 0.05). When the objective was to enhance carbon sink capacity while maintaining high yield, the treatment with 75% biogas slurry combined with biochar substituting for mineral fertilizer (BS75 + C) showed the best overall performance, with N_ECB values of 6.30 and 6.34 t ha⁻¹ in the two respective seasons, while also demonstrating clear advantages in soil organic matter accumulation and atmospheric regulation. Based on the VIKOR model with AHP-CRITIC combined weighting, BS75 + C was identified as the optimal option. However, the most suitable fertilization strategy depends on management objectives: BS25 is recommended when maximizing short-term economic return is the primary goal, whereas BS75 + C is preferable for enhancing carbon sink capacity and ecological benefits. Considering both ecosystem service value and comprehensive performance, BS50 and BS75 + C are recommended as sustainable fertilization strategies for greenhouse tomato production. Full article

Silage additives enhance forage preservation and resource efficiency by reducing dry matter (DM) losses and limiting aerobic spoilage. This study evaluated crop-specific lactic acid bacteria (LAB) inoculants by comparing treated (T) silage with untreated (U) controls for maize and grass. Silage quality was assessed using nutritional, fermentation, and microbial indicators, alongside aerobic stability (ASTA) and biogas yield. Additionally, a carbon footprint (CF) assessment, based on primary data from a farm in northern Germany with background datasets, quantified the implications for the biogas-to-electricity pathway. Two scenarios were modelled, with Scenario II accounting for changes in soil organic carbon (SOC). LAB additives improved preservation, with DM losses decreased from 18.48% in untreated grass (UG) to 13.17% in treated grass (TG) and from 21.53% in untreated maize (UM) to 5.21% in treated maize (TM). ASTA increased to 223 h for TM and 218 h for TG, alongside a lower presence of yeasts and moulds. In Scenario I, CF decreased by 5.00% for TG (293.53 g CO₂-eq kWh_el⁻¹) and 6.89% for TM (229.05 g CO₂-eq kWh_el⁻¹). Under Scenario II (including SOC), TG showed a value of 135.43 g CO₂-eq kWh_el⁻¹, and TM 321.48 g CO₂-eq kWh_el⁻¹. Overall, the additive improved silage stability and reduced climate impacts. Full article

This study presents an integrated optimization framework for enhancing biogas and methane production through anaerobic digestion, addressing the challenge of identifying optimal operating conditions across multiple interacting parameters. Biochemical methane potential tests were conducted to evaluate the individual effects of four critical operational parameters: temperature, mixing regime, inoculum-to-substrate (I-S) ratio, and chemical oxygen demand load (COD-L). Experimental findings confirmed that thermophilic conditions, mixing once a day, I-S ratio of 1:2, and moderate COD loading consistently delivered the most favorable biogas and methane yields. Kinetic modeling, including the Modified Gompertz and Logistic models, showed strong predictive agreement with experimental data (R² > 0.90), reliably capturing production dynamics across all tested conditions. Polynomial response surface methodology further identified COD-L as the dominant driver of methane yield, with optimal operating conditions falling within moderate temperature and COD-L ranges. This revealed significant nonlinear interactions between parameters. Building on these findings, the Crayfish Optimization algorithm successfully determined global optimal conditions, achieving a maximum biogas production of 0.371 Nm³/kg.VS. These results highlight how combining experimental investigation with predictive modeling and metaheuristic optimization creates a powerful decision-support framework for improving the efficiency and stability of anaerobic digestion systems. Full article

Anaerobic digestion of municipal wastewater sludge is often limited by slow hydrolysis rates. This study evaluated the effects of ozone pretreatment on methane production during mesophilic batch digestion. Ozone was applied at 0–10% for 30–90 s, with inoculum-to-substrate ratios of 1.0–2.0. Methane production was monitored using the AMPTS II system. The maximum methane yield (736 NmL CH₄ g⁻¹ VS; 1381 NmL total) was obtained at 10% ozone for 30 s and I/S = 1.5. Kinetic modelling showed enhanced methane production rates and reduced lag phases, with the Gompertz and Logistic models providing the best fit. Full article

This study assessed the long-term energy self-sufficiency and operational dynamics of a full-scale wastewater treatment plant over the period 2015–2023, with particular emphasis on biogas-driven energy recovery and time-dependent process interactions. The relationship between biogas production and electricity and heat generation was evaluated alongside the influence of different sludge streams on system performance using cross-correlation analysis. The results demonstrated a high level of energy recovery, with biogas-derived electricity covering, on average, 60% of the plant’s demand and reaching a maximum of 74% annually. A very strong correlation was observed between annual biogas production and electricity generation (r = 0.94), confirming the direct energetic coupling of both processes. Monthly analyses further indicated strong consistency between biogas yield and both electricity and heat production (r = 0.55–0.91 and r = 0.86, respectively). Cross-correlation analysis identified Thickened Waste Activated Sludge and Primary Sludge as important process drivers, with statistically significant delayed effects at 10–20 days. In contrast, recirculation-related streams exhibited negligible influence on system dynamics. Statistical analysis revealed that most heavy metals, including Cd, Cr, Ni, and Hg, exhibited high variability (Coefficient Variability > 40%), which can directly impact the stability of methane production. These results indicate that wastewater treatment plants’ energy performance is governed by delayed process responses linked to sludge residence time, highlighting the need for predictive models incorporating at least two weeks of historical operational data. In addition, physicochemical analysis of sewage sludge confirmed generally stable nutrient content, despite variability in biological parameters and heavy metal concentrations. Overall, the study demonstrates that integrating long-term operational datasets with time-lag analysis provides valuable insights for optimizing energy recovery and supporting circular economy strategies in wastewater treatment plants. Full article

Two-Stage Anaerobic Digesters (TSADs) have emerged as an effective strategy for improving the stability and efficiency of biogas production from high-strength substrates such as food waste. The separation of acidogenic and methanogenic phases enables better environmental control for distinct microbial communities, thereby enhancing methane yield and reducing process instability. This study investigates the dynamics of microbial populations of acidogens, acetogens, and methanogens in a TSAD using an extended Anaerobic Digester Model No. 1 framework incorporating stage-specific microbial growth kinetics. Simulation scenarios were performed across a range of operational parameters, including OLR (1–8 kg VS/m³ day), pH (5.0–8.0), temperature (35 °C and 45 °C), and HRT (10–30 days). The results demonstrate that balanced microbial population dynamics and syntrophic interactions strongly influence methane production and overall digester performance. Optimal methane yields were achieved within an OLR range of 3.5–4.5 kg VS/m³ day under mesophilic conditions. Elevated loading rates led to VFA accumulation and pH decline, resulting in the inhibition of methanogenic populations and reduced methane output. Preliminary parametric analysis suggests that the acetoclastic methanogen growth rate and ammonia inhibition constants are influential parameters affecting system performance. The findings highlight the importance of integrating microbial population dynamics into AD models to enhance predictive accuracy and support the development of intelligent control strategies for sustainable waste-to-energy systems. Full article