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The behavior of biomass pyrolysis can be predicted by analyzing its characteristics. This study aimed to model the release of volatiles across various temperatures, biomass properties, and heating rates. Palm kernel shells were pyrolyzed at 433–773 K with a heating rate of 5 K·min−1 using volatile‐state kinetic modeling. The process began by calculating the biomass type number (NCT), which was used to determine volatile enhancement (VE), volatile release yield (YVY), product yield (Yi), and product mass fraction (yi). The kinetic parameters, including the activation energy for product formation (Eai), were derived through a fitting process.The results indicate a YVY of 70.77% within the devolatilization zone, corresponding to the degradation of cellulose and hemicellulose. The YVY increased with higher temperatures, lower NCT, and higher heating rates. The activation energy ranged from 155–185 kJ·mol⁻¹ for biocrude oil (BCO) and 149–186 kJ·mol⁻¹ for gas. The kinetic parameters from the volatile‐state kinetic model demonstrated errors below 0.2% in comparison with the experimental data, confirming the model's accuracy and reliability. [ABSTRACT FROM AUTHOR]

Volatile state mathematical models for quantifying the chemical components in volatile biomass pyrolysis products were developed. The component mass yield Yi rate depends linearly on its pseudo kinetic constant and the remaining mass yield. The mass fraction rate of each component was modeled from the derivation of its mass yield rate equation. A new mathematical model equation was successfully developed. The involved variables are: biomass number, temperature, heating rate, pre-exponential factor, and pseudo activation energy related to each component. The component mass fraction yi and the mass yield were predicted using this model within a temperature range. Available experimental pyrolysis data for beechwood and rice husk biomass were used to confirm the developed model. The volatile products were separated into biopyrolysis gas (BPG) and a bio-pyrolysis oil (BPO). Five components in the BPG and forty in the BPO were quantified. The pseudo activation energy for each pseudo chemical reaction for a specific component was modeled as a polynomial function of temperature. The component mass fraction and yield are quantifiable using this developed mathematical model equation within a temperature range. The predicted component mass fractions and yields agreed excellently with the available experimental data. [ABSTRACT FROM AUTHOR]

In order to reduce dependence on fossil resources, the use of biomass for chemical production purposes can be realized through thermal decomposition via the pyrolysis route. Recently, kinetic studies of biomass thermal decomposition have attracted much attention in research communities. The modeling widely relies on solid-state approach but the results give discrepancy between the average E a value from model-free and model-based approaches, 146.3 kJ mol−1 vs. 52.3 kJ mol−1. Apart from that, the obtained E a value can reach more than 200 kJ mol−1 which is similar to ammonia synthesis without catalyst and the phenomenon of increasing E a at the end of the decomposition process is also found. From the evidence, a transformation method using a volatile state approach is offered in this review to bridge the research gap. Starting with reformulating the conversion concept, calculating the biomass type number, predicting mass fraction and yield, and determining kinetic parameters. This approach has been employed for several types of biomass and has provided satisfactory results and performance of mass fraction and yield predictions of volatile products with RMSE below 0.05. The calculated E a is also lower than the solid-state approach. Moreover, the pattern of E a formed a second-order polynomial function where it initially intensifies until a certain conversion, then alleviates as it approaches the end of the decomposition process because the decomposition products have been formed. • A transformation method in kinetic parameters determination is proposed. • Volatile state approach uses single-step decomposition in the devolatilization zone. • This approach accurately predicts mass fraction and yield of each volatile product. • The activation energy is also obtained as the 2nd-order temperature function. • It initially increases and then declines as conversion and temperature progress. [ABSTRACT FROM AUTHOR]

• The volatile state approach to describe biomass pyrolysis behavior is offered. • The kinetic parameters were determined using volatile state KAS and FWO methods. • Activation energy intensifies and then decreases as the temperature escalation. • The value of yield of volatile released (Y VY) is always lower than conversion (α). • This approach contributes to revealing the nature of biomass pyrolysis in logical. The determination of kinetic parameters of lignocellulosic biomass pyrolysis has been widely investigated through a solid-state approach using Kissinger-Akahira-Sunose (KAS) and Flynn-Wall-Ozawa (FWO) methods. Unfortunately, the result of activation energy continues to escalate along with temperature and conversion which contradict the behavior of biomass pyrolysis kinetic. Hence, this study offers a new approach to overcoming those problems, namely volatile state approach. The calculation was conducted by modifying solid-state KAS and FWO leading to volatile state KAS and FWO. The calculation for conversion in this approach starts from 0% and ends at not 100%. The data from Anca-Couce et al. were utilized and they were then plotted and calculated following volatile state KAS and FWO methods to acquire kinetic parameters. The difference in activation energy between the volatile state and solid-state was finally compared. Following the results, the activation energy obtained from volatile state KAS and FWO methods initially has an increasing value but then lessens as the pyrolysis temperature and conversion progress. This is in line with the involved activation energy should decrease at higher conversion. Therefore, the findings conclude that the volatile state approach contributes to revealing the nature of biomass pyrolysis with more logical and reasonable results. [Display omitted] [ABSTRACT FROM AUTHOR]

The green products from biomass pyrolysis open the way for the development and application of alternative fuels and chemicals. Until now, the pyrolysis kinetic studies are derived from solid-state approach (based on biomass as a reactant) which still faced drawbacks. A new approach, namely volatile state approach, is then developed with the volatile products as the main basis or reference to predict the mass fraction and yield as well as to determine the kinetic parameters from oil palm shell pyrolysis. The predicted results were then validated with the semi-batch pyrolysis experimental study. The oil palm shell has a biomass type number (N CT) of 9.57, volatile matter (Y VM) of 71.90%-wt, and was pyrolyzed at 300 °C, 350 °C, 400 °C, 450 °C, and 500 °C. From the experiment, as many as 95 compounds in bio-crude oil (BCO) were successfully produced which contain 72.79%-wt water and 27.21%-wt organic compounds. According to the characterization of 15 BCO components, they were classified into carbohydrates, fatty acids, phenol, aromatics, and water. Furthermore, the activation energy of products formation revealed a temperature dependence as a second-order polynomial function. Ultimately, this approach shows its satisfying capability to predict each BCO component mass fraction and yield which closely fits the experimental results. [Display omitted] • Biomass pyrolysis kinetic studies from solid-state approach still faced drawbacks. • Volatile state approach use the volatile products as the main basis for calculation. • Predicted mass fraction and yield of volatile products close to the experiment data. • Activation energy of volatile products are a second-order temperature function. [ABSTRACT FROM AUTHOR]

The investigation of natural rubber pyrolysis holds substantial significance for the advancement of renewable hydrocarbon chemical production. Given its composition of almost 100% volatile matter and nearly zero fixed carbon content, natural rubber as a renewable chemical source offers a promising route for bio-hydrocarbon producers. Remarkably, natural rubber pyrolysis behavior and kinetic mechanism still have received limited attention. This study, hence, aims to characterize and model natural rubber pyrolysis, which offers a better understanding of the pyrolysis phenomenon. The modeling employs a novel methodology, the volatile state approach, as the basis for kinetic investigation to comprehensively predict the mass composition and yield, as well as determine kinetic parameters. The pyrolysis was investigated under variations of temperature conditions in laboratory-scale of semi-batch thermogravimetry apparatus. The kinetic parameters were obtained from the combination of Arrhenius equation and volatile state Kissinger-Akahira-Sunose (KAS) method. The result reports that the pyrolysis of natural rubber presents excellent potential for producing a range of valuable products, including both liquid and gas products as bio-hydrocarbon (CH 4 , C 2 H 4 , C 2 H 6 , C 3 H 6 , C 3 H 8 , C 4 H 10 , and C 5 H 12) and non-hydrocarbon (CO 2 , CO, and H 2). Moreover, the activation energy of each gas component is obtained as temperature dependence while still adhering to the mass conservation principle. Notably, the volatile state kinetic modeling is valuable for enhancing the understanding of natural rubber pyrolysis, providing kinetic parameters for pyrolysis optimization and prediction of the composition and yield of each gas product, closely aligned to the experimental data. [Display omitted] • Natural rubber has nearly 100% volatile matter making it special than other biomass. • Its pyrolysis is aimed at producing liquid and bio-hydrocarbon gas (C 1 -C 5). • Kinetic modelling of natural rubber pyrolysis utilizes volatile state KAS approach. • The composition and yield of C 1 -C 5 gas products closely aligned to experimental data. • Activation energy of product formation is 2nd-order polynomial temperature function. [ABSTRACT FROM AUTHOR]