Co-digestion of solid waste: Towards a simple model to predict methane production

Correlations and impact of anaerobic digestion operating parameters on the start-up duration: Database construction for robust start-up guidelines

Anaerobic digestion (AD) has become a popular technique for organic waste management while offering economic and environmental advantages. As AD becomes increasingly prevalent worldwide, research efforts are primarily focused on optimizing its processes. During the operation of AD systems, the occurrence of unstable events is inevitable. So far, numerous conclusions have been drawn from full and lab-scale studies regarding the driving factors of start-up perturbations. However, the lack of standardized practices reported in start-up studies raises concerns about the comparability and reliability of obtained data. This study aims to develop a knowledge database and investigate the possibility of applying machine learning techniques on experimentation-extracted data to assist start-up planning and monitoring. Thus, a standardized database referencing 75 cases of start-up of one-stage wet continuously-stirred tank reactors (CSTR) processing agricultural, industrial, or municipal organic effluent in mono-digestion from 31 studies was constructed. 10 % of the total observations included in this database concern failed start-up experiments. Then, correlations between the parameters and their impacts on the start-up duration were studied using multivariate analysis and a model-based ranking methodology. Insights into trends of choices were highlighted through the correlation analysis of the database. As such, scenarios favoring short start-up duration were found to involve relatively low retention times (average initial and final hydraulic retention times, (HRTi) and (HRTf) of 26.25 and 20.6 days, respectively), high mean organic loading rates (average OLRmean of 5.24 g VS·d-1·L -1) and the processing of highly fermentable substrates (average feed volatile solids (VSfeed) of 81.35 g L-1). The model-based ranking of AD parameters demonstrated that the HRTf, the VSfeed, and the target temperature (Tf) have the strongest impact on the start-up duration, receiving the highest relative scores among the evaluated AD parameters. The database could serve as a reference for comparison purposes of future start-up studies allowing the identification of factors that should be closely controlled.

Quantitative assessment of exposure to fecal contamination in urban environment across nine cities in low-income and lower-middle-income countries and a city in the United States

BACKGROUND

During 2014 to 2019, the SaniPath Exposure Assessment Tool, a standardized set of methods to evaluate risk of exposure to fecal contamination in the urban environment through multiple exposure pathways, was deployed in 45 neighborhoods in ten cities, including Accra and Kumasi, Ghana; Vellore, India; Maputo, Mozambique; Siem Reap, Cambodia; Atlanta, United States; Dhaka, Bangladesh; Lusaka, Zambia; Kampala, Uganda; Dakar, Senegal.

OBJECTIVE

Assess and compare risk of exposure to fecal contamination via multiple pathways in ten cities.

METHODS

In total, 4053 environmental samples, 4586 household surveys, 128 community surveys, and 124 school surveys were collected. E. coli concentrations were measured in environmental samples as an indicator of fecal contamination magnitude. Bayesian methods were used to estimate the distributions of fecal contamination concentration and contact frequency. Exposure to fecal contamination was estimated by the Monte Carlo method. The contamination levels of ten environmental compartments, frequency of contact with those compartments for adults and children, and estimated exposure to fecal contamination through any of the surveyed environmental pathways were compared across cities and neighborhoods.

RESULTS

Distribution of fecal contamination in the environment and human contact behavior varied by city. Universally, food pathways were the most common dominant route of exposure to fecal contamination across cities in low-income and lower-middle-income countries. Risks of fecal exposure via water pathways, such as open drains, flood water, and municipal drinking water, were site-specific and often limited to smaller geographic areas (i.e., neighborhoods) instead of larger areas (i.e., cities).

CONCLUSIONS

Knowledge of the relative contribution to fecal exposure from multiple pathways, and the environmental contamination level and frequency of contact for those "dominant pathways" could provide guidance for Water, Sanitation, and Hygiene (WASH) programming and investments and enable local governments and municipalities to improve intervention strategies to reduce the risk of exposure to fecal contamination.

A review on anaerobic digestion with focus on the role of biomass co-digestion, modelling and optimisation on biogas production and enhancement

The status, recent trends and future perspectives in modelling and optimisation of anaerobic co-digestion is investigated. Areas that can be focused on and those which need further research towards enhancing biogas production are pointed out. Co-digestion, modelling and optimisation of anaerobic digestion as well as techno-economic aspects are reviewed in this paper. It was noted that co-digestion requires more research into a variety of bio-resources and their specific blend proportions. Modelling and optimisation of co-digestion with substrate seasonal fluctuations has not been addressed in previous studies. Controlling key process factors including temperature, pH, and carbon to nitrogen ratio is critical in improving biogas yield. Biogas hybridisation is yet to be explored in depth. The majority of researches are focused on mono-digestion, feedstock co-digestion, modelling, and optimisation of anaerobic digestion needs significant further investigations. A multi-objective approach taking all technical and economic parameters in the modelling and optimization is essential.

Modelization of anaerobic processes during co-digestion of slowly biodegradable substrates

The influence of the soluble substrates over the anaerobic processes has been extensively investigated, but little is known about the effects of particulate substrate. The biodegradation of these substrates starts with the hydrolytic step, this process is slower than the other ones involved in the biodegradation of particulate substrates and usually becomes the rate-limiting step. This study investigate the effect of the initial total solids (TS) concentration on the anaerobic co-digestion of two slowly biodegradable organic substrates. The wastes mixtures were prepared at different dilutions in the range from 10% to 28% TS. From these experiments it was observed that as TS concentration increased, the methane production decreased. These results were modelled and it was observed that neither hydrolysis nor fermentation stages controlled the methane production rate. Being a substrate inhibition event experienced at the methanogenic stage the responsible of the lower methane production when operating at high TS concentrations.

Existing Empirical Kinetic Models in Biochemical Methane Potential (BMP) Testing, Their Selection and Numerical Solution

Biochemical Methane Potential (BMP) tests are a crucial part of feasibility studies to estimate energy recovery opportunities from organic wastes and wastewater. Despite the large number of publications dedicated to BMP testing and numerous attempts to standardize procedures, there is no “one size fits all” mathematical model to describe biomethane formation kinetic precisely. Importantly, the kinetics models are utilized for treatability estimation and modeling processes for the purpose of scale-up. A numerical computation approach is a widely used method to determine model coefficients, as a replacement for the previously used linearization approach. However, it requires more information for each model and some range of coefficients to iterate through. This study considers existing empirical models used to describe biomethane formation process in BMP testing, clarifies model nomenclature, presents equations usable for numerical computation of kinetic parameters as piece-wise defined functions, defines the limits for model coefficients, and collects and analyzes criteria to evaluate and compare model goodness of fit.

Modeling the anaerobic co-digestion of solid waste: From batch to semi-continuous simulation

The main purpose of this study was to validate the use of a simple model for forecasting methane production in co-digestion reactors run semi-continuously using substrate data acquired in batch mode. Firstly, seven solid substrates were characterized individually in successive batches to assess their Biochemical Methane Potential (BMP) and kinetic parameters. Afterwards, eight mixtures of two, three or five substrates were processed in semi-continuous mode at an organic loading rate of 1 g VS L^-1 d^-1. The experimental methane production was always greater than that calculated from the BMP of each substrate. This result suggested that, endogenous activity needs to be taken into consideration in order to predict total methane production accurately. Near equivalence between experimental and modeled methane production was found after integration in the model of the endogenous activity. The results confirmed the possibility for use of substrate batch data (BMP and kinetics) to predict methane production in semi-continuous operations.