Kinetics of Solid Waste Biodegradation in Laboratory Lysimeters

Solid waste biodegradation kinetics determine the time it takes to achieve stabilization of solid waste in landfills. This paper reports the results of a laboratory scale investigation aimed at evaluating the effect of different enhancement techniques on solid waste biodegradation kinetics. The experiments were carried out in a group of five lysimeters. The effect of temperature and leachate recirculation was investigated. Total Volatile Solids (TVS) and fiber content under controlled conditions of temperature and moisture were monitored for a period of nine months. The experiments were carried out under both mesophilic and thermophilic conditions. The moisture of solid waste was controlled through the process of leachate recirculation. The results of kinetic analysis showed that solid waste degradation follows first order kinetics. The optimal conditions for solid waste biodegradation were found to be mesophilic temperature of about 38oC and moisture content of about 65%. It was concluded that leachate recirculation enhanced the biodegradation process over the whole studied range of moisture content, while the temperature influence was the maximum during mesophilic stage. The biodegradation under thermophilic conditions was decelerated as compared to control lysimiter. The results obtained by this study may be applied to a real scale bioreactor landfill

Modeling and optimization of biogas production from a waste digester using artificial neural network and genetic algorithm

Artificial neural networks (ANNs) and genetic algorithms (GA) are considered among the latest tools that are used to solve complicated problems that cannot be solved by conventional solutions. The present study utilizes the ANN and GA as tools for simulating and optimizing of biogas production process from the digester of Russaifah biogas plant in Jordan. Operational data of the plant for a period of 177 days were collected and employed in the analysis. The study considered the effect of digester operational parameters, such as temperature (T), total solids (TS), total volatile solids (TVS), and pH on the biogas yield. A multi-layer ANN model with two hidden layers was trained to simulate the digester operation and to predict the methane production. The performance of the ANN model is verified and demonstrated the effectiveness of the model to predict the methane production accurately with correlation coefficient of 0.87. The developed ANN model was used with genetic algorithm to optimize the methane size. The optimal amount of methane was converged to be 77%, which is greater than the maximum value obtained from the plant records of 70.1%. The operational conditions that resulted in the optimal methane production were determined as temperature at 36 °C, TS 6.6%, TVS 52.8% and pH 6.4

Municipal solid waste management in refugee hosting communities: Analysis of a case study in northern Jordan

The Syrian civil war, which broke out in 2011, caused the displacement of more than one million refugees to Jordan. Most of them settled in the Northern Govenorates of Jordan. Due to this, the local services and infrastructures of the hosting communities, in particular the solid waste management (SWM), were put under great pressure. The aim of this study is to evaluate how the off-camp refugees impacted the SWM in the Greater Irbid Municipality (GIM; in the Irbid Governorate), both quantitatively and qualitatively. Data and results obtained from the studies carried out before the Syrian crisis are compared with data collected by the authors in 2016 using similar or comparable methodologies. Moreover, local citizen perceptions of and satisfaction with the solid waste (SW) service level were assessed. A deterioration of the SWM in GIM between 2011 and 2016 was observed in terms of service performance indicators (e.g., an increase of SW collection and transportation costs by 2.5 times and of fines for improper SW disposal by 2.2 times) and of citizens’ views (a decline in SWM quality was felt by 59% of the respondents). An attempt to cope with this situation has been made in recent years with international donors mobilizing efforts and resources to enable municipalities to meet the growing demand in basic SW services. There is however, still much to be done

Assessment of Vegetation Cover Using Normalized Difference Vegetation Index Based on Satellite Images: Case Study from Ajloun in Northern Jordan

In this study, the vegetation cover in the Ajloun forest reserve was assessed using moderate spatial resolution satellite images. It was possible to construct maps of the Normalized Difference Vegetation Index (NDVI) for the study area, during the period 2000–2018 using the special QGIS software. Statistical analysis of the minimum NDVI values indicated an increasing trend in the vegetative cover of the study area, where NDVI values were increased from 0.05 to 0.18 during the period 2000–2018. Using satellite images in assessing the vegetation cover is a robust method that saves time and efforts. The results allow conducting a predictive analysis of the dynamics of the state of forest ecosystems based on actual data and will be useful as a tool for decision-makers to make informed decisions for inventory, remote control of logging, assessment of the consequences of fires, forest pathological monitoring, and scientific research. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG