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Enhancing Solid Fuel Properties of Sawdust Torrefaction using a Rotary Drum Reactor
(2026-07-01)
Sripha, Yutthana
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Phengpom, Tinnapob
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Kaewpengkrow, Prangtip Rittichote
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Thianpong, Chinaruk
This study investigated the physicochemical properties of torrefied sawdust obtained from the industry using a rotary drum reactor. Sawdust samples were torrefied at 220, 250, and 280 °C for 15, 30, and 45 min under a nitrogen atmosphere. Proximate analysis was conducted to determine the moisture, volatile, fixed carbon, and ash contents. The volatile content of the torrefied sawdust ranged from 69.05 to 88.06 wt.%. The results suggested that the chemical energies of solid fuels are stored in volatile matter and fixed carbon, both of which have a higher reactivity during carbonization. Characterization of functional groups was conducted using an FTIR spectrophotometer, and the higher heating value (HHV) of the torrefied sawdust was also investigated. The HHV increased from 15.36 MJ/kg to 21.13 MJ/kg, with the highest HHV achieved at 280°C for 45 min. Moreover, the torrefaction at 250 °C for 30 min gave a biofuel with more than 80% energy density, which allowed us to classify this biofuel as lignite. Therefore, torrefaction is a promising pretreatment technique that can improve the energy quality and combustion properties.
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Performance Assessment of Co-Gasification Process for Syngas Production Using Multi-Biomass Feedstocks
(2026-06-15)
Wiranarongkorn, Kunlanan
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Detchusananard, Thanaphorn
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Piroonlerkgul, Pakorn
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Im-orb, Karittha
The investigation focused on alternative energy production from biomass residuals, predominantly located in Northern Thailand, for year-round utilization. The biomass gasification model was created in Aspen Plus. The cassava stalk served as a foundational biomass for blending with additional materials. Increased equivalent ratio (ER) increased syngas yield, while higher gasifying temperatures decreased it. The total energy demand rose with increasing ER, whereas it decreased with higher gasifying temperatures. The gasification process may transition from exothermic to endothermic when the ER exceeds 0.25. The effect of mixing ratio of 1) cassava stalk and 2) rice straw, or 3) cane stalks, or 4) corn stalk at 1:0, 4:1, 3:2, and 2:3 on the gasification performance was investigated. The maximum syngas yield of all mixture cases at each gasifying temperature was achieved at mixing ratio of 2:3 and ER of 0.3. This study discovered blending cassava stalk with seasonal leftovers like rice straw, cane stalks, and corn stalks in a 2:3 ratio generated outstanding syngas year-round in Thailand. For the blended biomass feed rate of 10 kg/h, the maximum syngas yield of 0.356 kmol/h was achieved for the mixture of cassava stalk and rice straw at a gasifying temperature of 900°C.
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NIR Spectroscopy for Non-Destructive Prediction of Greenhouse Gas Emissions and Global Warming Potential by Biomass Combustion
(2026-05-01)
Sirisomboon, Panmanas
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Gyawali, Prakash
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Posom, Jetsada
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Lapcharoensuk, Ravipat
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Shrestha, Bim Prasad
Greenhouse gas (GHG) emissions from biomass combustion include carbon dioxide (CO<inf>2</inf>), methane (CH<inf>4</inf>) and nitrous oxide (N<inf>2</inf>O), which cause climate change and global warming. By measuring GHG emissions by biomass combustion, a potent protocol for the calculation of global warming potential (GWP), which is how much the global temperature has risen due to combustion processes, can be achieved, contributing to determining the mean reduction in global temperature rise and fostering a transition towards more sustainable energy systems. Additionally, warning can be given of the GHG and GWP risks associated with different species of biomass. This review includes the GHG emissions and GWP of biomass combustion and their measurement and estimation directly through biomass sample combustion, using unmanned aerial vehicles (UAVs) and satellite measurements of radiation interacting with atmospheric gases, or satellite-derived data and calculations according to IPCC guidelines. In addition, the relationship of lignocellulosic compounds and elements in biomass to HHV and GHG emissions is described. The key mechanism of molecular vibration of hydrogen bonds in biomass caused by NIR radiation related to GHG emissions is revealed and recorded regarding the possibility of using NIR spectroscopy for the prediction of GHG emissions and GWP. Calculation examples for sugarcane bagasse and other biomass species are shown. The comparative advantages and limitations of NIR spectroscopy with respect to other methods are included. These factors lead to elucidation of the possibility of using NIR spectroscopy for non-destructive prediction of GHG emissions. In this review, the feasibility of using NIR spectroscopy to evaluate GHG emissions, GWP and emission factors (EFs) as an alternative to IPCC estimation methods related to climate change by biomass combustion is confirmed. NIR spectroscopy is a novel methodology for predicting GHG emissions and GWP directly from intact chip or powder biomass spectral data without explicit gas measurement. This article records the essential spectroscopic knowledge of biomass polymer valorization that is of value in polymer science.
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Valorizing Red Seaweed Spent Biomass into Reducing Sugars for β-Carotene Production by Rhodotorula paludigena
(2026-05-01)
Kongsinkaew, Chatchol
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Tangsattayatithan, Chutipol
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Chittapun, Supenya
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Phiphatbunyabhorn, Parivat
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Laemthong, Tunyaboon
Seaweed bioactive extraction generates de-extracted residual solids that remain carbohydrate-rich but are often underutilized. This study developed an integrated valorization route for Gracilaria fisheri spent biomass to produce fermentable sugars for β-carotene production by Rhodotorula paludigena CM33. Reducing sugar production was optimized using response surface methodology (Box–Behnken design) by varying reaction time, sulfuric acid concentration, and biomass loading at 90 °C. The predicted optimum (47.39 min, 2.50% (w/v) H<inf>2</inf>SO<inf>4</inf>, and 7.13% (w/v) biomass) yielded 22.41 g/L reducing sugars and was validated experimentally at 22.22 ± 0.19 g/L, indicating that the model reliably predicted reducing sugar production. The optimized condition was scaled up in a 22 L bioreactor with sequential acid hydrolysis followed by enzyme-assisted hydrolysis, increasing reducing sugars from ~30 to ~40 g/L. FTIR and SEM analyses indicated progressive modification of the carbohydrate matrix across processing stages. Batch cultivation of R. paludigena on the hydrolysate showed that ammonium sulfate supplementation significantly increased biomass, whereas β-carotene titers were not significantly different. Repeated-batch operation on non-supplemented hydrolysate sustained production over four cycles with β-carotene titers of 13.75–17.27 mg/L, demonstrating the operational feasibility of the hydrolysate-based system. Overall, this work demonstrates a practical seaweed biorefinery approach to upgrade G. fisheri spent biomass into sugars and carotenoid-rich yeast biomass.
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Sustainable Valorization of Salak Peel Waste: Regeneration of Biochar for Lead Removal from Wastewater
(2026-01-01)
Buakhiao, Phruektinai
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Chungcharoen, Thatchapol
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Jamkamon, Aud
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Limmun, Warunee
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Thungsotanon, Dithaporn
This study evaluates the effects of pyrolysis temperature (600°C and 800°C, denoted as SP600 and SP800) and regeneration reagents on lead (Pb²⁺) adsorption performance of biochar derived from salak peels. Moreover, the lead removal efficiency and adsorption efficiency after several regeneration cycles under appropriate conditions were also investigated. The results indicate that increasing the pyrolysis temperature significantly enhances lead removal efficiency and adsorption capacity, with biochar pyrolyzed at 800°C and loaded with lead (SP800Pb) exhibiting the highest initial lead adsorption performance. However, upon regeneration using hydrochloric acid (HCl) and sodium nitrate (NaNO₃) at various concentrations, SP600Pb demonstrated higher lead removal performance than SP800Pb across all conditions. Specifically, SP600Pb regenerated by 0.1M HCl exhibited the highest lead desorption efficiency and removal efficiency. Furthermore, after five consecutive adsorption-regeneration cycles, the biochar regenerated by 0.1M HCl (SP600RPb) exhibited a suitable removal efficiency of 83.91 ± 0.10 and a desorption efficiency of 148.73 ± 0.13. The observed desorption efficiency exceeding 100 was attributed to the accumulated release of Pb²⁺ ions during successive regeneration cycles, which indicates enhanced ion-exchange dynamics over time. Therefore, biochar pyrolyzed at 600°C and regenerated using 0.1M HCl is appropriate for the reuse of biochar in lead adsorption, promoting sustainable resource application, cost reduction, and waste minimization in production processes.
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Light-Emitting Diode Illumination Enhances Biomass, Pigment, and Lipid Production in Halotolerant Cyanobacterium Aphanothece halophytica
(2025-06-01)
Thongtha, Sitthichai
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Kittiwongwattana, Chokchai
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Incharoensakdi, Aran
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Phunpruch, Saranya
Light characteristics, including spectrum and intensity, significantly impact cyanobacterial biomass production, pigment biosynthesis, and cellular metabolism, influencing the composition of various biochemical compounds. This study aimed to investigate the effects of light-emitting diode (LED) illumination on biomass, pigment, and lipid production in the unicellular halotolerant cyanobacterium Aphanothece halophytica, cultivated in a suitable natural seawater (SNSW) medium. The results revealed that LED light outperformed fluorescent light, with blue LED light, particularly at an intensity of 60 μmol photons m−2 s−1, significantly enhancing growth, pigment synthesis, and lipid accumulation. This resulted in a maximum cell density of 68.96 ± 1.52 × 106 cells mL−1, a specific growth rate of 0.302 ± 0.002 day−1, and a lipid productivity of 56.81 ± 0.75 mg L−1 day−1. White LED light produced lipids suitable for biodiesel, whereas blue, green, and red LEDs promoted the accumulation of polyunsaturated fatty acids (PUFAs), beneficial for food supplements. These findings highlight the potential of LED-based cultivation strategies for optimizing biomass and biochemical compound production in A. halophytica.
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Enhancing Biomass and Lipid Production in Messastrum gracile Using Inorganic Carbon Substrates and Alternative Solvents for Lipid Extraction
(2025-03-01)
Pan-utai, Wanida
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Pornpukdeewattana, Soisuda
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Inrung, Wilasinee
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Thurakit, Theera
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Srinophakun, Penjit
Microalgae show promise as a biomass and bioproduct for applications in various industries. The cultivation of microalgae plays a crucial role in optimizing biomass yield and bioproduct accumulation. The provision of inorganic carbon substrates substantially enhances microalgal growth and lipid biosynthesis, resulting in marked increases in the production of biofuels and other bioproducts. This study examined biomass and lipid accumulation in Messastrum gracile IFRPD 1061 under inorganic stress conditions, previously unreported. M. gracile IFRPD 1061 was subjected to varying conditions of inorganic carbon substrates, 1–3 g·L−1 sodium carbonate and bicarbonate concentration, to enhance biomass and lipid accumulation. Optimal productivity levels were observed with sodium bicarbonate addition of 3 g·L−1 and 1 g·L−1 for biomass and lipids, resulting in productivities of 392.64 and 53.57 mg·L−1·d−1, respectively. Results underlined the effectiveness of sodium carbonate and bicarbonate as inorganic carbon sources for stimulating microalgal growth and enhancing the production of high-value products. The extraction of lipids from freeze-dried biomass of M. gracile IFRPD 1061 demonstrated optimal yield using methanol/hexane solvents compared with the control experiments. Lipid extraction yields using methanol/hexane were 42.18% and 46.81% from oven-dried and freeze-dried biomass, respectively. Lipids extracted from oven-dried M. gracile IFRPD 1061 using methanol/hexane/chloroform solvents indicated the potential of methanol/hexane as a solvent for lipid extraction from dry microalgal biomass using an ultrasonic-assisted technique. This study contributes valuable insights into maximizing biofuel and bioproduct production from microalgae, highlighting A. gracilis as a promising candidate for industrial applications.
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PHYSICOCHEMICAL CHARACTERIZATION AND EFFECTS OF FLY ASH GENERATED FROM BIOCHAR BRIQUETTES ON THE GROWTH OF CHINESE CELERY CABBAGE (BRASSICA RAPA SUBSP. PEKINENSIS)
(2025-01-01)
Suwankamnoed, S.
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Meksiriporn, B.
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Sripana, N.
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Sutjaritvorakul, T.
Agricultural waste biomass is considered a valuable source of eco-friendly renewable energy. Generally, biomass is processed through pyrolysis and is compressed to form biochar briquettes. After combustion, the remaining ash is the incombustible material that can be used in agriculture. The aim of this research is to investigate the physicochemical properties of fly ash derived from biochar briquettes and to evaluate its effect on the growth of Chinese celery cabbage (Brassica rapa subsp. pekinensis). Fly ash was analyzed using a scanning electron microscopy (SEM) equipped with an energy dispersive X-ray spectroscopy (EDS) and X-ray diffractometer (XRD). The results exhibited the major elements were carbon (C, 59.31%), oxygen (O, 24.48%) with additional elements including potassium (K), silicon (Si), aluminum (Al), and calcium (Ca). The XRD pattern confirmed the presence of silica (SiO<inf>2</inf>), calcite (CaCO<inf>3</inf>) and hydroxyapatite (Ca<inf>10</inf>(PO<inf>4</inf>)<inf>6</inf>(OH)<inf>2</inf>). Seedlings of the tested plants were grown in pots containing varying concentrations of local soil and biochar briquette ash (soil:ash, v/v), with treatments including 100% soil (control, T1), 80:20 (T2), 60:40 (T3), and 40:60 (T4). Growth parameters improved significantly with 40% ash (T3), while 60% ash (T4) had adverse effects. These results indicated that biochar briquette ash can be effectively used as an ash-based fertilizer.
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Near-Infrared Spectroscopy Modeling of Combustion Characteristics in Chip and Ground Biomass from Fast-Growing Trees and Agricultural Residue
(2024-03-01)
Shrestha, Bijendra
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Posom, Jetsada
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Pornchaloempong, Pimpen
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Sirisomboon, Panmanas
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Shrestha, Bim Prasad
This study focuses on the investigation and comparison of combustion characteristic parameters and combustion performance indices between fast-growing trees and agricultural residues as biomass sources. The investigation is conducted through direct combustion in an air environment using a thermogravimetric analyzer (TGA). Additionally, partial least squares regression (PLSR)-based models were developed to assess combustion performance indices via near-infrared spectroscopy (NIRS), serving as a non-destructive alternative method. The results obtained through the TGA reveal that, specifically, fast-growing trees display higher average ignition temperature (227 °C) and burnout temperature (521 °C) in comparison to agricultural residues, which exhibit the values of 218 °C and 515 °C, respectively. Therefore, fast-growing trees are comparatively difficult to ignite, but sustain combustion over extended periods, yielding higher temperatures. However, despite fast-growing trees having a high ignition index (D<inf>i</inf>) and burnout index (D<inf>f</inf>), the comprehensive combustion performance (S<inf>i</inf>) and flammability index (C<inf>i</inf>) of agricultural residue are higher, indicating the latter possess enhanced thermal and combustion reactivity, coupled with improved combustion stability. Five distinct PLSR-based models were developed using 115 biomass samples for both chip and ground forms, spanning the wavenumber range of 3595–12,489 cm−1. The optimal model was selected by evaluating the coefficients of determination in the prediction set (R2<inf>P</inf>), root mean square error of prediction (RMSEP), and RPD values. The results suggest that the proposed model for D<inf>f</inf>, obtained through GA-PLSR using the first derivative (D1), and S<inf>i</inf>, achieved through full-PLSR with MSC, both in ground biomass, is usable for most applications, including research. The model yielded, respectively, an R2<inf>P</inf>, RMSEP, and RPD, which are 0.8426, 0.4968 wt.% min⁻4, and 2.5; and 0.8808, 0.1566 wt.%2 min⁻2 °C⁻3, and 3.1. The remaining models (D<inf>i</inf> in chip and ground, D<inf>f</inf>, and S<inf>i</inf> in chip, and C<inf>i</inf> in chip and ground biomass) are primarily applicable only for rough screening purposes. However, including more representative samples and exploring a more suitable machine learning algorithm are essential for updating the model to achieve a better nondestructive assessment of biomass combustion behavior.
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NIR Spectroscopy as an Alternative to Thermogravimetric Analyzer for Biomass Proximate Analysis: Comparison of Chip and Ground Biomass Models
(2024-02-01)
Shrestha, Bijendra
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Posom, Jetsada
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Sirisomboon, Panmanas
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Shrestha, Bim Prasad
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Pornchaloempong, Pimpen
This study investigates the non-destructive analysis of proximate parameters (moisture content, MC; volatile matter, VM; fixed carbon, FC; ash content) in various chipped and ground biomass using a combination of destructive thermogravimetric analysis (TGA) and non-destructive near-infrared spectroscopy (NIRS) with partial least squares regression (PLSR). The thermogravimetric method determines proximate analysis data through TG and DTG curves, tracking biomass mass loss over time or temperature. NIRS scans chipped biomass in diffuse reflectance, and ground biomass in transflectance mode, covering the wavenumber range from 3595 to 12,489 cm−1. PLSR-based models (Full-PLSR, GA-PLSR, SPA-PLSR, MP PLSR 5-range method, and MP PLSR 3-range method) are developed and evaluated based on R2P, RMSEP, and RPD. MC and FC models for chip biomass exhibit satisfactory performance, making them cautiously applicable in various applications, including research. Optimal models for MC and FC in chip biomass, constructed using GA-PLSR with the second derivative and Full-PLSR with a constant offset, yield high R2P values (0.8654 and 0.8773), low RMSEP values (0.85% and 2.12%), and high RPD values (2.9 and 3.0), indicating applicative capabilities. Other parameters such as MC and FC in ground biomass, as well as VM and ash content in both chip and ground biomass, are found suitable for rough screening. Model sensitivity, assessed by calculating LOQ, indicates high sensitivity for VM in both chip and ground biomass and FC in chip biomass, as the calculated LOQ value is lower than the minimum reference values used during model development. However, for the remaining parameters, LOQ values surpass the established minimum reference value, suggesting limitations in predicting samples below the calibration range. Continuous model enhancement incorporating an ample number of representative biomass samples and consistent validation with unknown samples are imperative for ensuring accurate predictions.

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