Hydrothermal Carbonization of <i>Searsia lancea</i> Trees Grown on Mine Drainage: Processing Variables and Product Composition

Setsepu, Ramadimetja Lizah; Abdulsalam, Jibril; Weiersbye, Isabel; Bada, Samson

doi:10.1021/acsomega.1c02173

Cited by 11 publications

(6 citation statements)

References 34 publications

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“…The physicochemical results reported for the untreated biomass used in this study are similar to those reported by Setepu et al, 25 with the inherent moisture of 8.01%. The high moisture content in biomass could make it more liable to SPONCOM.…”

Section: Relationship Between the Physicochemical Properties Of Bioma...supporting

confidence: 89%

Inhibition of Spontaneous Combustion Characteristic of Biomass Treated with Imidazolium-Based Ionic Liquids Using Thermogravimetric Analysis

Matsobane,

Bada,

Genc

et al. 2023

ACS Omega

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Emim HSO 4 , and [Bmim + OAc − ] on the SPONCOM liability of Sersia lancea biomass sample harvested from the Vaal River Mine, South Africa. The results of the derivative thermogravimetric (DTG) analysis of this indigenous biomass showed that it is highly liable to SPONCOM prior to treatment with ILs. Following treatment with all three ILs, the DTG results showed that ILs can potentially inhibit the SPONCOM liability of biomass, with [Bmim + OAc − ] showing the best inhibitory effects. With [Bmim + OAc − ] (IL-C), the TGspc index of S. lancea biomass was reduced to 0.0207 from 0.1457%/°C min −1 , and the sample was classified as low reactive after treatment. This indicates that less oxygen was consumed by the treated samples with [Bmim + OAc − ] than by the untreated ones. From the textural properties of the IL-treated biomass, the mechanism responsible for the lower liability of the treated biomass was determined. This study establishes that biomass is very reactive, and it is important to understand its liability to SPONCOM, before being shipped as a fired or co-fired fuel across the Atlantic.

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Section: Relationship Between the Physicochemical Properties Of Bioma...supporting

confidence: 89%

Inhibition of Spontaneous Combustion Characteristic of Biomass Treated with Imidazolium-Based Ionic Liquids Using Thermogravimetric Analysis

Matsobane,

Bada,

Genc

et al. 2023

ACS Omega

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“…All the pellets produced at the two different blending ratios were subjected to proximate analysis, calorific value, and various mechanical tests. The results obtained from the combustion and chemical elemental composition of the pellet samples were reported previously (Setsepu et al, 2021).…”

Section: Hydrochar Production and Pelletizationmentioning

confidence: 63%

Effects of Searsia lancea hydrochar inclusion on the mechanical properties of hydrochar/discard coal pellets

Setsepu

Abdulsalam

Bada

2021

J. S. Afr. Inst. Min. Metall.

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The utilization of biomass as a solid fuel for co-firing has received great attention from boiler manufacturers as a clean coal technology (CCT) option. This research aimed to produce biocoal pellets, as a clean energy fuel, using hydrochar from trees planted to rehabilitate acid mine drainage (AMD) water and fine coal discards. The hydrochar was synthesized by hydrothermal carbonization of Searsia lancea harvested from AMD-contaminated land at a temperature of 280°C and a residence time of 90 minutes. It was blended with discard coal (-1 mm) at ratios of 25% and 50% hydrochar to produce different forms of solid pelletized biocoal (BC). The physicochemical and mechanical properties of each of the biocoal pellet blends were determined. The 100% hydrochar had the highest calorific value of 29.99 MJ/kg, while the raw discard coal had a calorific value of 16.73 MJ/kg. The ash content decreased from 42% in the discard coal to 25% in the blend of 50% coal and 50% hydrochar biocoal pellets. Biocoal pellets comprising 25% hydrochar and 75% discard coal (BC25HC/75COAL) displayed the best mechanical properties (compressive strength 3.06 MPa) of all the fuels, but the physicochemical properties were inferior to the BC50HC/50 COAL pellets. This research has demonstrated that hydrochar synthesized from a tree species planted for hydraulic control of AMD has the capability to act as a binder for improving the mechanical properties and energy characteristics of fine discard coal.

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“…MLR and PLSR are both linear regression models, where PLSR models are able to resolve the colinearity among the input variables and provide unbiased input-output relationships . On the contrary, MPR is nonlinear in nature and typically represents a second- or third-order polynomial regression model in the RRCC literature. − The outputs of MPR are further utilized for process optimization through response surface methodology. Among ML models, ANNs are black-box models that mimic biological neurons by attempting to replicate information transfer between biological neurons through electrical signals using mathematical functions. , ANN models have been highly successful in combining complex nonlinear input data to predict outputs .…”

Section: Methodsmentioning

confidence: 99%

A Critical Review of Data Science Applications in Resource Recovery and Carbon Capture from Organic Waste

Zaki,

Rowles,

Adjeroh

et al. 2023

ACS EST Eng.

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Municipal and agricultural organic waste can be treated to recover energy, nutrients, and carbon through resource recovery and carbon capture (RRCC) technologies such as anaerobic digestion, struvite precipitation, and pyrolysis. Data science could benefit such technologies by improving their efficiency through data-driven process modeling along with reducing environmental and economic burdens via life cycle assessment (LCA) and techno-economic analysis (TEA), respectively. We critically reviewed 616 peer-reviewed articles on the use of data science in RRCC published during 2002−2022. Although applications of machine learning (ML) methods have drastically increased over time for modeling RRCC technologies, the reviewed studies exhibited significant knowledge gaps at various model development stages. In terms of sustainability, an increasing number of studies included LCA with TEA to quantify both environmental and economic impacts of RRCC. Integration of ML methods with LCA and TEA has the potential to costeffectively investigate the trade-off between efficiency and sustainability of RRCC, although the literature lacked such integration of techniques. Therefore, we propose an integrated data science framework to inform efficient and sustainable RRCC from organic waste based on the review. Overall, the findings from this review can inform practitioners about the effective utilization of various data science methods for real-world implementation of RRCC technologies.

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Hydrothermal Carbonization of Searsia lancea Trees Grown on Mine Drainage: Processing Variables and Product Composition

Cited by 11 publications

References 34 publications

Inhibition of Spontaneous Combustion Characteristic of Biomass Treated with Imidazolium-Based Ionic Liquids Using Thermogravimetric Analysis

Inhibition of Spontaneous Combustion Characteristic of Biomass Treated with Imidazolium-Based Ionic Liquids Using Thermogravimetric Analysis

Effects of Searsia lancea hydrochar inclusion on the mechanical properties of hydrochar/discard coal pellets

A Critical Review of Data Science Applications in Resource Recovery and Carbon Capture from Organic Waste

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