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Processes
Special Issues
Prediction and Monitoring of Biomass Properties for Energy Applications
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Prediction and Monitoring of Biomass Properties for Energy Applications

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Environmental and Green Processes".

Deadline for manuscript submissions: closed (22 October 2021) | Viewed by 14015

Special Issue Editors

Dr. Andrea Pizzi

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Guest Editor
Department of Agricultural, Food and Environmental Sciences, Università Politecnica delle Marche, Via Brecce Bianche, I-60131 Ancona, Italy
Interests: biomass quality; bioenergy; biofuel; residues; environmental impact; multivariate analysis; infrared spectroscopy; circular economy; quality assessment; biomass characterization; fast measurements; combustion emission factors
Dr. Giuseppe Toscano

E-Mail Website
Guest Editor
Dipartimento di Scienze Agrarie, Alimentari e Ambientali, Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy
Interests: biomass quality; bioenergy; biofuel; sustainability assessment; residues; biosystem engineering; life cycle assessment; standardization; circular economy; environmental impact; wood processing; food processing; renewable energy; energy conversion
Special Issues, Collections and Topics in MDPI journals
Dr. Daniele Duca

E-Mail Website
Guest Editor
Department of Agricultural, Food and Environmental Sciences, Università Politecnica delle Marche, Via Brecce Bianche 10, 60131 Ancona, Italy
Interests: biomass quality; bioenergy; biofuel; sustainability assessment; residues; biosystem engineering; life cycle assessment; standardization; circular economy; environmental impact; wood processing; food processing; renewable energy; energy conversion
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Knowledge of biomass quality is increasingly a key factor in the bioenergy sector, mainly for the consideration of the increase in the typologies of residual raw materials used for biofuel production and feeding power and heating systems.

The information on the type of biomass and its physical, chemical, and energy properties are essential especially for operators called to make decisions to solve logistical, technical, and economical issues.

For practical reasons, the data should be available in a short time, at relatively low cost, and at any time and point of the supply chain, from the origin of the raw material up to the use in the final energy conversion system.

To address this need, research has been stimulated in promoting new solutions to measure the quality of biomass and biofuels through predictive modeling, innovations in analytical techniques, and tools and management strategies for monitoring biomass.

This Special Issue will collect research articles or comprehensive reviews focused on the aforementioned topics.

Subjects welcomed are listed below:

  • Evaluation of biomass feedstock and biofuels properties used in real scale energy applications
  • Quality prediction models, statistics, and surveys on biomass properties
  • Relationships between biomass properties and biofuel production
  • Innovative methods and tools for the assessment of biomass feedstocks and biofuel quality assessment
  • Methods for quality control management in the bioenergy chain

Dr. Andrea Pizzi
Assoc. Prof. Dr. Giuseppe Toscano
Prof. Dr. Daniele Duca
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Biofuel
  • Quality assessment
  • Woodchip
  • Pellet 
  • Bioenergy
  • Predictive model
  • Biomass characterization

Published Papers (5 papers)

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Research

12 pages, 3000 KiB  
Article
A Low-Cost System for Moisture Content Detection of Bagasse upon a Conveyor Belt with Multispectral Image and Various Machine Learning Methods
by Natrapee Nakawajana, Patchara Lerdwattanakitti, Wanphut Saechua, Jetsada Posom, Khwantri Saengprachatanarug and Seree Wongpichet
Processes 2021, 9(5), 777; https://doi.org/10.3390/pr9050777 - 28 Apr 2021
Cited by 5 | Viewed by 2278
Abstract
This research aimed to propose an online system based on multispectral images for the real-time estimation of the moisture content (MC) of sugarcane bagasse. The system consisted of a conveyor belt, four halogen bulbs, and a multispectral camera. The MC models were developed [...] Read more.
This research aimed to propose an online system based on multispectral images for the real-time estimation of the moisture content (MC) of sugarcane bagasse. The system consisted of a conveyor belt, four halogen bulbs, and a multispectral camera. The MC models were developed using machine learning algorithms, i.e., multiple linear regression (MLR), principal component regression (PCR), artificial neural network (ANN), PCA-ANN, Gaussian process regression (GPR), PCA-GPR, random forest regression (RFR), and PCA-GPR. The models were developed using 150 samples (calibration set) meanwhile the remaining 50 samples were applied as a validation set. The comparison of all developed models showed that the PCA-RFR model achieved better detection with a higher accuracy of MC prediction. The PCA-RFR model showed the best results which were a coefficient of determination of prediction (r2) of 0.72, root mean square error of prediction (RMSEP) of 11.82 wt%, and a ratio of the standard error of prediction to standard deviation (RPD) of 1.85. The results show that this technique was very useful for MC rapid screening of the sugarcane bagasse. Full article
(This article belongs to the Special Issue Prediction and Monitoring of Biomass Properties for Energy Applications)
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11 pages, 2627 KiB  
Article
Revealing of Supercritical Water Gasification Process of Lignin by Reactive Force Field Molecular Dynamics Simulations
by Veerapandian Ponnuchamy, Jakub Sandak and Anna Sandak
Processes 2021, 9(4), 714; https://doi.org/10.3390/pr9040714 - 18 Apr 2021
Cited by 10 | Viewed by 2923
Abstract
Gasification with supercritical water is an efficient process that can be used for the valorization of biomass. Lignin is the second most abundant biopolymer in biomass and its conversion is fundamental for future energy and value-added chemicals. In this paper, the supercritical water [...] Read more.
Gasification with supercritical water is an efficient process that can be used for the valorization of biomass. Lignin is the second most abundant biopolymer in biomass and its conversion is fundamental for future energy and value-added chemicals. In this paper, the supercritical water gasification process of lignin by employing reactive force field molecular dynamics simulations (ReaxFF MD) was investigated. Guaiacyl glycerol-β-guaiacyl ether (GGE) was considered as a lignin model to evaluate the reaction mechanism and identify the components at different temperatures from 1000 K to 5000 K. The obtained results revealed that the reactions and breaking of the lignin model started at 2000 K. At the primary stage of the reaction at 2000 K the β-O-4 bond tends to break into several compounds, forming mainly guaiacol and 1,3-benzodioxole. In particular, 1,3-benzodioxole undergoes dissociation and forms cyclopentene-based ketones. Afterward, dealkylation reaction occurred through hydroxyl radicals of water to form methanol, formaldehyde and methane. Above 2500 K, H2, CO and CO2 are predominantly formed in which water molecules contributed hydrogen and oxygen for their formation. Understanding the detailed reactive mechanism of lignin’s gasification is important for efficient energy conversion of biomass. Full article
(This article belongs to the Special Issue Prediction and Monitoring of Biomass Properties for Energy Applications)
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14 pages, 3255 KiB  
Article
Wood Fuel Procurement to Bioenergy Facilities: Analysis of Moisture Content Variability and Optimal Sampling Strategy
by Elena Leoni, Manuela Mancini, Giovanni Aminti and Gianni Picchi
Processes 2021, 9(2), 359; https://doi.org/10.3390/pr9020359 - 15 Feb 2021
Cited by 7 | Viewed by 1969
Abstract
Moisture content is the most relevant quality parameter for wood fuels. Effective and fast determination of moisture of incoming feedstock is essential in the management of bioenergy facilities. The availability of fast and reliable moisture meters based on innovative technologies simplifies this task. [...] Read more.
Moisture content is the most relevant quality parameter for wood fuels. Effective and fast determination of moisture of incoming feedstock is essential in the management of bioenergy facilities. The availability of fast and reliable moisture meters based on innovative technologies simplifies this task. However, in Mediterranean conditions the inherent variability of wood fuels calls for a careful sampling strategy if representative results are required while facing acceptable analytic costs. The present study is aimed at measuring the fuel heterogeneity and defining accordingly the appropriate number of samples to be analyzed in order to get reliable moisture-content results. A total of 70 truckloads (about 2270 t of woodchips) were sampled during commercial operations in two different seasons. Five samples were collected from each load and measured with standard method and magnetic resonance gauge. Results show that the variability of moisture content is influenced by mixing of species and storage of biomass. Heterogeneity can vary greatly also within single truckloads, to the point that three samples are needed to achieve about 90% of estimates within the desired precision limits. In the case of larger lots, such as barge or ship loads, 20 samples can provide sufficient precision in most scenarios. Full article
(This article belongs to the Special Issue Prediction and Monitoring of Biomass Properties for Energy Applications)
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18 pages, 5991 KiB  
Article
Rapid Quality Control of Woodchip Parameters Using a Hand-Held Near Infrared Spectrophotometer
by Elena Leoni, Manuela Mancini, Daniele Duca and Giuseppe Toscano
Processes 2020, 8(11), 1413; https://doi.org/10.3390/pr8111413 - 05 Nov 2020
Cited by 14 | Viewed by 2058
Abstract
Near infrared spectroscopy is a non-invasive and rapid technique to support the analysis of solid biofuels such as woodchip, which is considered as a suitable alternative for energy production, according to European goals for fossil fuel reduction. Chemical and physical properties of the [...] Read more.
Near infrared spectroscopy is a non-invasive and rapid technique to support the analysis of solid biofuels such as woodchip, which is considered as a suitable alternative for energy production, according to European goals for fossil fuel reduction. Chemical and physical properties of the woodchip influence combustion performance, so the most discriminant parameters such as moisture and ash content and gross calorific value were constantly monitored. The aim of this study was the development of prediction models for these three parameters with the use of a hand-held NIR spectrometer. Laboratory analyses were carried out to evaluate the quality of several Italian samples from a power plant, and PLS regression models were developed to test prediction accuracy. Moreover, the most relevant wavelengths were investigated to discriminate chemical compounds influence. Prediction models demonstrated the capacity of handheld MicroNIR instrument to be considered a practical tool for solid biofuel quality assessment. As a consequence, NIR spectroscopy improved real-time analysis and made it suitable for practical and industrial applications, as supported by the recent Italian standard UNI/TS 11765. Full article
(This article belongs to the Special Issue Prediction and Monitoring of Biomass Properties for Energy Applications)
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20 pages, 4731 KiB  
Article
Hydrothermal Carbonization of Olive Tree Pruning as a Sustainable Way for Improving Biomass Energy Potential: Effect of Reaction Parameters on Fuel Properties
by Judith González-Arias, Marta Elena Sánchez, Elia Judith Martínez, Camila Covalski, Ana Alonso-Simón, Rubén González and Jorge Cara-Jiménez
Processes 2020, 8(10), 1201; https://doi.org/10.3390/pr8101201 - 23 Sep 2020
Cited by 43 | Viewed by 3979
Abstract
Hydrothermal carbonization (HTC) allows the conversion of organic waste into a solid product called hydrochar with improved fuel properties. Olive tree pruning biomass (OTP), a very abundant residue in Mediterranean countries, was treated by HTC to obtain a solid fuel similar to coal [...] Read more.
Hydrothermal carbonization (HTC) allows the conversion of organic waste into a solid product called hydrochar with improved fuel properties. Olive tree pruning biomass (OTP), a very abundant residue in Mediterranean countries, was treated by HTC to obtain a solid fuel similar to coal that could be used in co-combustion processes. Three different reaction temperatures (220, 250, and 280 °C) and reaction times (3, 6, and 9 h) were selected. The hydrochars obtained were extensively analyzed to study their behavior as fuel (i.e., ultimate, proximate, fiber and thermogravimetric analysis, Fourier-transform infrared spectroscopy (FTIR), activation energy, and combustion performance). The concentrations of cellulose, hemicellulose, and lignin in the samples depict a clear and consistent trend with the chemical reactions carried out in this treatment. Regarding O/C and H/C ratios and HHV, the hydrochars generated at more severe conditions are similar to lignite coal, reaching values of HHV up to 29.6 MJ kg−1. The higher stability of the solid is reflected by the increase of the activation energy (≈60 kJ mol−1), and ignition temperatures close to 400 °C. With this, HTC is a proper thermal treatment for the management of raw OTP biomass and its further conversion into a solid biofuel. Full article
(This article belongs to the Special Issue Prediction and Monitoring of Biomass Properties for Energy Applications)
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