Co-hydrothermal carbonization of food waste-woody sawdust blend: Interaction effects on the hydrochar properties and nutrients characteristics

2020 ◽  
Vol 316 ◽  
pp. 123900 ◽  
Author(s):  
Tengfei Wang ◽  
Buchun Si ◽  
Zhengjun Gong ◽  
Yunbo Zhai ◽  
Mingfeng Cao ◽  
...  
Keyword(s):  
Food Waste ◽  
Hydrothermal Carbonization ◽  
Interaction Effects

scholarly journals Lead Removal by Hydrochar from Hydrothermal Carbonization of Food Waste

2021 ◽  
Vol 801 (1) ◽  
pp. 012002
Author(s):  
Thi Hoang Tuyen Do ◽  
Thai-Hoang Le ◽  
Thi Phuong Thuy Pham
Keyword(s):  
Food Waste ◽  
Hydrothermal Carbonization ◽  
Lead Removal

scholarly journals Transformation of Sulfur during Co-Hydrothermal Carbonization of Coal Waste and Food Waste

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2271
Author(s):  
Pretom Saha ◽  
Nepu Saha ◽  
Shanta Mazumder ◽  
M. Toufiq Reza
Keyword(s):  
Food Waste ◽  
Hydrothermal Carbonization ◽  
Fuel Properties ◽  
Organic Sulfur ◽  
Coal Waste ◽  
Total Sulfur ◽  
Transformation Mechanism ◽  
Wet Chemical ◽  
The Difference ◽  
Sulfur Transformation

Co-hydrothermal carbonization (Co-HTC) is an emerging technology for processing multiple waste streams together to improve their fuel properties in the solid product, known as hydrochar, compared to the hydrothermal carbonization (HTC) of those individual streams. Sulfur is considered one of the most toxic contaminants in solid fuel and the combustion of this sulfur results in the emission of SOx. It was reported in the literature that, besides the fuel properties, Co-HTC reduced the total sulfur content in the hydrochar phase significantly. However, the transformation of different forms of sulfur has not yet been studied. Therefore, this study investigated the transformation of different forms of sulfur under the Co-HTC treatment. In the study, the Co-HTC of food waste (FW) and two types of coal wastes (middle bottom (CW1) and 4 top (CW2)) were conducted at 180 °C, 230 °C and 280 °C for 30 min. Different forms of sulfur were measured by using elemental analysis (total sulfur), and a wet chemical method (sulfate sulfur and pyritic sulfur). The organic sulfur was measured by the difference method. The results showed that a maximum of 49% and 65% decrease in total sulfur was achieved for CW1FW and CW2FW, respectively, at 230 °C. Similar to the total sulfur, the organic sulfur was also decreased about 85% and 75% for CW1FW and CW2FW, respectively. Based on these results, a sulfur transformation mechanism under Co-HTC treatment was proposed.

Hydrothermal carbonization of food waste and associated packaging materials for energy source generation

2013 ◽  
Vol 33 (11) ◽  
pp. 2478-2492 ◽  
Author(s):  
Liang Li ◽  
Ryan Diederick ◽  
Joseph R.V. Flora ◽  
Nicole D. Berge
Keyword(s):  
Energy Source ◽  
Food Waste ◽  
Hydrothermal Carbonization ◽  
Packaging Materials

A Study on the Adsorption of Heavy Metal with Food Waste Bio-char using Hydrothermal Carbonization (HTC)

2016 ◽  
Vol 33 (2) ◽  
pp. 137-144
Author(s):  
Wonduck Chung ◽  
◽  
Minah Oh ◽  
Woori Cho ◽  
Seong-Kyu Park ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Food Waste ◽  
Hydrothermal Carbonization

Influence of temperature on nitrogen fate during hydrothermal carbonization of food waste

2018 ◽  
Vol 247 ◽  
pp. 182-189 ◽  
Author(s):  
Tengfei Wang ◽  
Yunbo Zhai ◽  
Yun Zhu ◽  
Chuan Peng ◽  
Bibo Xu ◽  
...  
Keyword(s):  
Food Waste ◽  
Hydrothermal Carbonization ◽  
Influence Of Temperature ◽  
Nitrogen Fate ◽  
Influence Of Temperature On

scholarly journals Hydrochars as Emerging Biofuels: Recent Advances and Application of Artificial Neural Networks for the Prediction of Heating Values

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4572
Author(s):  
Ioannis O. Vardiambasis ◽  
Theodoros N. Kapetanakis ◽  
Christos D. Nikolopoulos ◽  
Trinh Kieu Trang ◽  
Toshiki Tsubota ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Sewage Sludge ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Food Waste ◽  
Hydrothermal Carbonization ◽  
Mean Square ◽  
Artificial Neural

In this study, the growing scientific field of alternative biofuels was examined, with respect to hydrochars produced from renewable biomasses. Hydrochars are the solid products of hydrothermal carbonization (HTC) and their properties depend on the initial biomass and the temperature and duration of treatment. The basic (Scopus) and advanced (Citespace) analysis of literature showed that this is a dynamic research area, with several sub-fields of intense activity. The focus of researchers on sewage sludge and food waste as hydrochar precursors was highlighted and reviewed. It was established that hydrochars have improved behavior as fuels compared to these feedstocks. Food waste can be particularly useful in co-hydrothermal carbonization with ash-rich materials. In the case of sewage sludge, simultaneous P recovery from the HTC wastewater may add more value to the process. For both feedstocks, results from large-scale HTC are practically non-existent. Following the review, related data from the years 2014–2020 were retrieved and fitted into four different artificial neural networks (ANNs). Based on the elemental content, HTC temperature and time (as inputs), the higher heating values (HHVs) and yields (as outputs) could be successfully predicted, regardless of original biomass used for hydrochar production. ANN3 (based on C, O, H content, and HTC temperature) showed the optimum HHV predicting performance (R2 0.917, root mean square error 1.124), however, hydrochars’ HHVs could also be satisfactorily predicted by the C content alone (ANN1, R2 0.897, root mean square error 1.289).

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