Recycling of Trees Planted for Phytostabilization to Solid Fuel: Parametric Optimization Using the Response Surface Methodology and Genetic Algorithm

Abstract

Biomass resources are gaining attention to address environmental issues, ensure energy efficiency, and ensure longterm fuel sustainability. The use of biomass in its raw form is known to present a number of issues, including high shipping, storage, and handling costs. Hydrothermal carbonization (HTC), for example, can increase the physiochemical properties of biomass by converting it into a more carbonaceous solid hydrochar with enhanced physicochemical properties. This study investigated the optimum process conditions for the HTC of woody biomass (Searsia lancea). HTC was carried out at varying reaction temperatures (200−280 °C) and hold times (30−90 min). The response surface methodology (RSM) and genetic algorithm (GA) were used to optimize the process conditions. RSM proposed an optimum mass yield (MY) and calorific value (CV) of 56.5% and 25.8 MJ/kg at a 220 °C reaction temperature and 90 min of hold time. The GA proposed an MY and a CV of 47% and 26.7 MJ/kg, respectively, at 238 °C and 80 min. This study revealed a decrease in the hydrogen/carbon (28.6 and 35.1%) and oxygen/carbon (20 and 21.7%) ratios, indicating the coalification of the RSM-and GA-optimized hydrochars, respectively. By blending the optimized hydrochars with coal discard, the CV of the coal was increased by about 15.42 and 23.12% for RSM-and GA-optimized hydrochar blends, respectively, making them viable as an energy alternative.

Hydrothermal carbonization of sawdust for hydrochar production to prepare solid fuels

“…In the literature, design of experiment (DoE) methods have been used to optimize hydrochar yield obtained from HTC of different types of biomass and organic waste, among which RSM has been identified as the most commonly used optimization method. [23][24][25][26] Central composite design (CCD) and Box-Behnken design are the major types of techniques used in RSM for optimization. Although Box-Behnken design often has fewer design points than CCD and hence is less expensive and time-consuming to run with the same number of factors, Box-Behnken design can only run three levels for each factor, unlike CCD's five levels per factor, and it is also not capable of running all factors at their extreme settings.…”