Effects of Pyrolysis Temperature on Product Yields and Energy Recovery from Co-Feeding of Cotton Gin Trash, Cow Manure, and Microalgae: A Simulation Study

Exploitation of lignocellulosic-based biomass biorefinery: A critical review of renewable bioresource, sustainability and economic views

Urbanization has driven the demand for fossil fuels, however, the overly exploited resource has caused severe damage on environmental pollution. Biorefining using abundant lignocellulosic biomass is an emerging strategy to replace traditional fossil fuels. Value-added lignin biomass reduces the waste pollution in the environment and provides a green path of conversion to obtain renewable resources. The technology is designed to produce biofuels, biomaterials and value-added products from lignocellulosic biomass. In the biorefinery process, the pretreatment step is required to reduce the recalcitrant structure of lignocellulose biomass and improve the enzymatic digestion. There is still a gap in the full and deep understanding of the biorefinery process including the pretreatment process, thus it is necessary to provide optimized and adapted biorefinery solutions to cope with the conversion process in different biorefineries to further provide efficiency in industrial applications. Current research progress on value-added applications of lignocellulosic biomass still stagnates at the biofuel phase, and there is a lack of comprehensive discussion of emerging potential applications. This review article explores the advantages, disadvantages and properties of pretreatment methods including physical, chemical, physico-chemical and biological pretreatment methods. Value-added bioproducts produced from lignocellulosic biomass were comprehensively evaluated in terms of encompassing biochemical products , cosmetics, pharmaceuticals, potent functional materials from cellulose and lignin, waste management alternatives, multifunctional carbon materials and eco-friendly products. This review article critically identifies research-related to sustainability of lignocellulosic biomass to promote the development of green chemistry and to facilitate the refinement of high-value, environmentally-friendly materials. In addition, to align commercialized practice of lignocellulosic biomass application towards the 21st century, this paper provides a comprehensive analysis of lignocellulosic biomass biorefining and the utilization of biorefinery green technologies is further analyzed as being considered sustainable, including having potential benefits in terms of environmental, economic and social impacts. This facilitates sustainability options for biorefinery processes by providing policy makers with intuitive evaluation and guidance.

Nano Modifications of Biochar to Enhance Heavy Metal Adsorption from Wastewaters: A Review

Biochar (BC) is a carbon-rich material that can be obtained by thermal decomposition of agricultural solid waste under oxygen-limited conditions. It has received increasing attention as a cost-effective sorbent to treat metal-contaminated water due to attributes such as high porosity and the presence of various functional groups. The heavy metal (HM) sorption and removal capacity of BC can be enhanced by developing novel biochar nanohybrids (BNHs) that can be produced via surface modification of BC with nanomaterials. Loading of nanomaterials on the biochar surface can improve its physicochemical properties through alterations in the functional group profile, porosity, and availability of active sites on the BC surface which can enhance the HM adsorption ability. This manuscript provides information on preparation of nano-based biochar hybrids emanating from the type of modifying agent for the removal of different HM ions from wastewaters, and the underlying mechanisms have been discussed. Further, this compilation discusses published literature depicting the influence of different processes of preparation on the physicochemical properties and adsorption capacity of nanobiochar hybrids. The potential risks of BNHs have been reviewed to effectively avoid the possible harmful impacts on the environment, and future research directions have been proposed.

A comparative study of machine learning methods for bio-oil yield prediction - A genetic algorithm-based features selection

A novel genetic algorithm-based feature selection approach is incorporated and based on these features, four different ML methods were investigated. According to the findings, ML models could reliably predict bio-oil yield. The results showed that Random forest (RF) is preferred for bio-oil yield prediction (R2 ~ 0.98) and highly recommended when dealing with the complex correlation between variables and target. Multi-Linear regression model showed relatively poor generalization performance (R2 ~ 0.75). The partial dependence analysis was done for ML models to show the influence of each input variable on the target variable. Lastly, an easy-to-use software package was developed based on the RF model for the prediction of bio-oil yield. The current study offered new insights into the pyrolysis process of biomass and to improve bio-oil yield. It is an attempt to reduce the time-consuming and expensive experimental work for estimating the bio-oil yield of biomass during pyrolysis.

Application of a Supervised Learning Machine for Accurate Prognostication of Hydrogen Contents of Bio-Oil

This paper deals with modeling hydrogen contents of bio-oil (H-BO) as a function of pyrolysis conditions and biomass compositions of feedstock. The support vector machine algorithm optimized by the grey wolf optimization method has been used in modeling this end. Comprehensive data for this purpose were aggregated from previous sources and reports. The results of various analyses showed that this algorithm has a high ability to predict actual results. The calculated values of R2, MRE (%), MSE, and RMSE were obtained as 0.973, 1.98, 0.0568, and 0.241, respectively. According to the results of various analyses, the high performance of this model in predicting the output values was proved. Also, by comparing this model with the previously proposed models in terms of accuracy, it was observed that this model had a better performance. This algorithm can be a good alternative to costly and time-consuming laboratory data.

Lab-Scale Study of Temperature and Duration Effects on Carbonized Solid Fuels Properties Produced from Municipal Solid Waste Components

In work, data from carbonization of the eight main municipal solid waste components (carton, fabric, kitchen waste, paper, plastic, rubber, paper/aluminum/polyethylene (PAP/AL/PE) composite packaging pack, wood) carbonized at 300–500 °C for 20–60 min were used to build regression models to predict the biochar properties (proximate and ultimate analysis) for particular components. These models were then combined in general models that predict the properties of char made from mixed waste components depending on pyrolysis temperature, residence time, and share of municipal solid waste components. Next, the general models were compared with experimental data (two mixtures made from the above-mentioned components carbonized at the same conditions). The comparison showed that most of the proposed general models had a determination coefficient (R²) over 0.6, and the best prediction was found for the prediction of biochar mass yield (R² = 0.9). All models were implemented into a spreadsheet to provide a simple tool to determine the potential of carbonization of municipal solid waste/refuse solid fuel based on a local mix of major components.

Biological and thermochemical conversion of human solid waste to soil amendments

Biological and thermochemical sanitization of source-separated human solid waste (HSW) are effective technologies for unsewered communities. While both methods are capable of fecal pathogen sterilization, the agronomically-beneficial properties of waste sanitized between methods remains unclear. Therefore, this study compared recovery and quality of soil amendments produced by compostation, torrefaction, and pyrolysis of HSW, established their financial value, and quantified tradeoffs between product value and conversion efficiency. Temperature and associated mass losses significantly affected the physical and chemical properties of thermochemically-treated HSW. Thermophilic composting, a biological sanitation method practiced in informal settlements in Nairobi, Kenya, produced an amendment that contained between 16 and 858-fold more plant-available nitrogen (N; 214.5 mg N/kg) than HSW pyrolyzed between 300 and 700 °C (0.2-15.2 mg N/kg). Conversely, HSW pyrolyzed at 600 °C had four-fold higher plant-available phosphorus (P; 3117 mg P/kg) and five-fold higher plant-available potassium (K; 7403 mg K/kg) than composted HSW (716 mg P/kg and 1462 mg K/kg). Wide variation between international fertilizer prices on the low end and regional East African prices on the high end resulted in broad-spaced quantiles for the value of agronomic components in HSW amendments. Phosphorus and K comprised a disproportionate amount of the value, 52-87%, compared to plant-available N, which contributed less than 2%. The total value of treated HSW, summed across all agronomic components per unit weight amendment, was greatest for thermochemically-treated HSW at 600 °C, averaging 220 USD/Mg, more than four-fold that of composted HSW, 53 USD/Mg. In contrast, torrefaction provided the highest monetary value per unit weight feedstock, 144 USD/Mg, as low heating temperatures engender minimal mass loss and higher nutrient densities per unit weight feedstock, compared to composted or pyrolyzed HSW. When benchmarked against total N, P, and K of eight commonly-applied organic amendments, including sewage-sludge (Milorganite), compost, and alfalfa meal, HSW pyrolyzed at 700 °C was of greatest value per unit weight of amendment, 365 USD/Mg, compared to 89 USD/Mg for composted HSW, and contained 2.9% total N (0.5 mg available N/kg), 3.1% total P (7640 mg available P/kg), 3.5% total K (17,671 mg available K/kg).