Evaluation of traditional and machine learning approaches for modeling volatile fatty acid concentrations in anaerobic digestion of sludge: potential and challenges.

This study evaluates models for predicting volatile fatty acid (VFA) concentrations in sludge processing, ranging from classical statistical methods (Gaussian and Surge) to diverse machine learning algorithms (MLAs) such as Decision Tree, XGBoost, CatBoost, LightGBM, Multiple linear regression (MLR), Support vector regression (SVR), AdaBoost, and GradientBoosting. Anaerobic bio-methane potential tests were carried out using domestic wastewater treatment primary and secondary sludge. The tests were monitored over 40 days for variations in pH and VFA concentrations under different experimental conditions.

The influence of various chemical oxygen demands on microbial fuel cells performance using leachate as a substrate.

Microbial fuel cells (MFCs), hailed as a promising technology, hold the potential to combat various wastewater pollutants while simultaneously converting their chemical energy into electricity through biocatalysts. This study explores the applicability of a dual compartment MFC (DC-MFC) under varying conditions, targeting the removal of chemical oxygen demand (COD) from landfill leachate and electricity generation. In this setup, anaerobic sludge from a wastewater treatment plant serves as the inoculum in the anode compartment of the MFC, with a Nafion117 membrane acting as the separator between MFC units.

The effect of ammonia concentration on the treatment of bio electrochemical leachate using MFCs technology.

Microbial fuel cells (MFCs) have garnered attention in bio-electrochemical leachate treatment systems. The most common forms of inorganic ammonia nitrogen are ammonium ([Formula: see text]) and free ammonia. Anaerobic digestion can be inhibited in both direct (changes in environmental conditions, such as fluctuations in temperature or pH, can indirectly hinder microbial activity and the efficiency of the digestion process) and indirect (inadequate nutrient levels, or other conditions that indirectly compromise the microbial community's ability to carry out anaerobic digestion effectively) ways by both kinds.

Utilization of microbial fuel cells as a dual approach for landfill leachate treatment and power production: a review.

Landfill leachate, which is a complicated organic sewage water, presents substantial dangers to human health and the environment if not properly handled. Electrochemical technology has arisen as a promising strategy for effectively mitigating contaminants in landfill leachate. In this comprehensive review, we explore various theoretical and practical aspects of methods for treating landfill leachate.

Smart waste bin monitoring using IoT for sustainable biomedical waste management.

Suboptimal management of healthcare waste poses a significant concern that can be effectively tackled by implementing Internet of Things (IoT) solutions to enhance trash monitoring and disposal processes. The potential utilisation of the Internet of Things (IoT) in addressing the requirements associated with biomedical waste management within the Kaduna area was examined. The study included a selection of ten hospitals, chosen based on the criterion of having access to wireless Internet connectivity.

Optimizing total ammonia-nitrogen concentration for enhanced microbial fuel cell performance in landfill leachate treatment: a bibliometric analysis and future directions.

Untreated landfill leachate can harm the environment and human health due to its organic debris, heavy metals, and nitrogen molecules like ammonia. Microbial fuel cells (MFCs) have emerged as a promising technology for treating landfill leachate and generating energy. However, high concentrations of total ammonia-nitrogen (TAN), which includes both ammonia and the ammonium ion, can impede MFC performance.

A comprehensive review of demand side management in distributed grids based on real estate perspectives.

A major challenge in renewable energy planning and integration with existing systems is the management of intermittence of the resources and customer demand uncertainties that are attributed to climates. In emerging distributed grids, state-of-the-art optimization techniques were used for cost and reliability objectives. In the existing literature, power dispatch and demand side management schemes were implemented for various techno-economic objectives.

Waste management practices in developing countries: a socio-economic perspective.

Growing populations, expanding economies, industrialisation, and urbanisation pose a problem for waste management in developing countries. Their waste management methods, on the other hand, are not as efficient as they could be. Most developing countries' current waste management practices do not fully conform to developed countries' best practices for meeting socioeconomic goals.