Multi-task prediction and optimization of hydrochar properties from high-moisture municipal solid waste: Application of machine learning on waste-to-resource

2021 ◽  
Vol 278 ◽  
pp. 123928 ◽  
Author(s):  
Jie Li ◽  
Xinzhe Zhu ◽  
Yinan Li ◽  
Yen Wah Tong ◽  
Yong Sik Ok ◽  
...  
Fuel ◽  
2021 ◽  
Vol 283 ◽  
pp. 118906
Author(s):  
Cansu Birgen ◽  
Elisa Magnanelli ◽  
Per Carlsson ◽  
Øyvind Skreiberg ◽  
Jostein Mosby ◽  
...  

2020 ◽  
Vol 46 (1) ◽  
pp. 77-86
Author(s):  
Victor Emery David ◽  
Jiang Wenchao ◽  
Daniel Mmereki

The ineffective management of household solid waste (HSW) in most developing cities in Africa including Monrovia has become a major issue threatening the environment and public health. In response to these waste challenges, developed countries have embarked upon major environmental reforms, and have made advances in best practices and sustainable management of their Municipal Solid Waste (MSW). However, in most developing countries like Liberia, such environmental reforms have not been initiated and therefore the situation has become compounded; this is due to several factors impeding the development of a sustainable municipal solid waste system. This study, therefore, aims to critically analyze the influencing factors of solid waste management; the characteristics of household waste and suggest management solutions for effective and sustainable management.<br/> Results from the analysis of data, using The Ordinary Least Square Regression (OLS) method estimates the average household waste per capita generation as 0.76kg/capita/day. Regarding the composition of the waste stream, the results show that 67% of the waste sampled from Monrovia is biodegradable and mostly comprised of high wet weight and high moisture content kitchen waste. On the other hand, the remaining percentage is mostly non-degradable but recyclable materials such as glass ceramics and metals. This suggests that due to the high moisture content in the waste, samples are suitable for composting and other mechanical and biological management options. Using the stratified sampling method, 300 households were chosen. Multiple regressions were conducted to determine the relationship between waste generation and socio-economic factors and these showed that the effect of income, household size and the environmental concern on HSW generation is statistically significant at a 1% significance. However, further findings revealed a negative relationship between income and HSW generation at a 1% level of significance. These findings provide new insight regarding the role of socio-economic characteristics affecting the generation of household waste in Monrovia.


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