Potential useful products from solid wastes

Golueke, Clarence G.; Dı́az, Luis F.

doi:10.1016/0734-242x(91)90071-e

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…Biogas can generate heat and electricity using microturbines, combustion engines, and combined heat and power plants. Digestate can also be used as a fertilizer to help soil grow [12,17]. Biogas and biofertilizer (digestate) are the two types of products produced by the anaerobic digestion process.Scientists have been redesigning and refining anaerobic digestion models for organic substances for over 40 years.…”

Section: Methanogenesismentioning

confidence: 99%

“…The materials (substrates) are then blended well for a specific retention time and heated for more extended periods at low temperatures, and the gas components are captured, isolated, and preserved. The digestate anaerobic digestion residue serve as a bio-fertilizer to enhance soil nutrients [12,13]. The anaerobic digestion process occurs in 5 consecutive phases.…”

Section: Introductionmentioning

confidence: 99%

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Data-Driven Circular Economy of Biowaste to Bioenergy with Conventional Prediction Modelling and Machine Learning

Matheri,

Sithole,

Mohamed

2023

Circ.Econ.Sust.

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Rapid population growth has not only increased energy demand, but waste generation that has increased and introduced emerging pollutants into waste streams, posing sanitary and environmental risks. The purpose of this research was to investigate waste to energy (anaerobic digestion-bioenergy process) on integrated waste management and digitalization of biomethane production as a data-driven circular economy model across the value chain of the carbon cycle (transition from take-make-dispose to use-make-return) through waste quantification, characterization, biomethane potential test (BMP) to prediction of the biomethane production. Anaerobic digestion experiment was conducted at a laboratory scale to analyze biomethane production from diverse substrates such as food waste, cow manure, sewage sludge, and chicken manure, with an average pH of 7.58. The experimental results obtained were then modelled and simulated with Modified Gompertz, Logistic, and Richards models and compared to machine learning simulation using Python with Gompertz, Logistics, and Richards models. Modified Logistic model was shown to be the best-fit curve, with a coefficient of determination (R2) > 0.9 validating the conventional mathematical modeling and simulation performance. During simulation with machine learning (Python), the experimental results obtained from the cow manure substrate provided the best fitting curve to the training curve compared to other substrates with the highest average of R2 as 1.0 for training, validation, and test data. Cow manure had the best validation performance at MSE (mean squared error) of 25.36 at epoch 1. Graphical Abstract

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Section: Methanogenesismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data-Driven Circular Economy of Biowaste to Bioenergy with Conventional Prediction Modelling and Machine Learning

Matheri,

Sithole,

Mohamed

2023

Circ.Econ.Sust.

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Ensuring Injection Safety during Measles Immunization Campaigns: More than Auto‐Disable Syringes and Safety Boxes

et al. 2003

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Measles immunization campaigns are effective elements of a comprehensive strategy for preventing measles cases and deaths. However, if immunizations are not properly administered or if immunization waste products are not safely managed, there is the potential to transmit bloodborne pathogens (e.g., human immunodeficiency virus and hepatitis B and hepatitis C). A safe injection can be defined as one that results in no harm to the recipient, the vaccinator, and the surrounding community. Proper equipment, such as the exclusive use of auto-disable syringes and safety boxes, is necessary, but these alone are not sufficient to ensure injection safety in immunization campaigns. Equally important are careful planning and managerial activities that include policy and strategy development, financing, budgeting, logistics, training, supervision, and monitoring. The key elements that must be in place to ensure injection safety in measles immunization campaigns are outlined.

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Potential useful products from solid wastes

Cited by 2 publications

References 3 publications

Data-Driven Circular Economy of Biowaste to Bioenergy with Conventional Prediction Modelling and Machine Learning

Data-Driven Circular Economy of Biowaste to Bioenergy with Conventional Prediction Modelling and Machine Learning

Ensuring Injection Safety during Measles Immunization Campaigns: More than Auto‐Disable Syringes and Safety Boxes

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