Effects of typical residuals on wooden waste pyrolysis: products and pollutants

Effects of typical residuals on wooden waste pyrolysis: products and pollutants | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of typical residuals on wooden waste pyrolysis: products and pollutants Qindong Chen, Xiyao Zhao, Jae-Hac Ko, Ning Wang, Qiyong Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9045066/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Bulky wastes disposal generates significant quantities of wooden waste mixed with residues such as cloth, foam, and leather, posing challenges for resource utilization. Pyrolysis offers better adaptability to impurities among thermal treatment technologies. However, the impact of residual impurities on product quality and pollutant emissions remains poorly quantified. This study systematically investigated the effects of residue content (0%, 5%, 10%, and 15%) on wooden waste fast pyrolysis at 550°C, analyzing products (bio-char, bio-oil, particulate matter-PM, and gases) and pollutants. Key results showed that biochar yield exceeded theoretical values, while PM yield decreased initially but rebounded at 15% residue content. Low residue content (5%) enhanced bio-oil quality, increasing phenolic compounds from 8.56% to 40.17% and reducing PM harmful components (e.g., acidic species fell to 3.51%). For gases, increasing the residue content from 0% to 15% lowered the CO/CO2 ratio in the gas from 5.42 to 2.48. However, residues introduced heavy metals like arsenic, exceeding safety limits by 3–7 times at 5–15% content. Overall, maintaining low residue content optimizes product usability and pollutant control, supporting pyrolysis for heterogeneous waste. Bulky waste residues fast pyrolysis pollutant emission pyrolysis products Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Bulky wastes have become pressing domestic waste issues. [ 1 , 2 ] Bulky wastes are large-sized and typically made of various materials, [ 3 ] such as wooden framework, leather, [ 4 ] flame retardant, [ 5 ] and foam. [ 6 ] The treatment of bulky wastes, apart from direct recycling, usually requires initial dismantling. During the dismantling process, high-value metals and relatively intact foam are separated for recycling, while other components—predominantly wooden waste mixed with residues such as cloth, foam, and leather—are usually crushed together and undergo subsequent treatment. [ 1 ] Disposal of the wooden waste (landfill or incineration) will not only increase the operational costs of bulky wastes processing facilities, but also not conducive to the resource utilization of the wooden components. Currently, thermal utilization technologies—such as combustion (distinct from waste incineration), pyrolysis, and gasification—are highly efficient methods for valorizing wooden waste. [ 7 ] However, residual impurities may impact their reaction process or utilization efficiency. Combustion and gasification are two approaches that require an oxidizing medium (e.g., air, water vapor), [ 8 ] mecessitating a mass transfer process from the exterior to the interior of the fuel. Residue materials like leather usually have low softening/melting points. [ 9 ] Upon softening/melting, they may encapsulate the woody fuel, hindering oxidant diffusion and reducing conversion efficiency. [ 10 ] Additionally, incomplete conversion of fuel can carry over significant amounts of particulate matter and tar, causing corrosion to downstream equipment. [ 11 , 12 ] Notably, in combustion-based power generation, entrained particulate matter can foul heat transfer surfaces, lowering heat transfer efficienc; [ 13 ] in gasification, tar increased gas cleanup costs. Consequently, when wooden waste from dismantling is used as biomass fuel, a low impurity content is generally required, which elevates the labor and operational costs of front-end treatment. Pyrolysis demonstrates a broader adaptability to feedstock heterogeneity than combustion or gasification. [ 14 ] Unlike those processes, pyrolysis operates without oxidizing agents, and mass transfer primarily occurs through internal-to-external diffusion within particles. [ 7 ] This reduces the impact of residue softening/melting on the conversion process. Furthermore, biomass pyrolysis typically occurs at lower temperatures (500–800°C), allowing the use of corrosion-resistant materials in reactor design. Therefore, pyrolysis is more suitable for resource utilization of heterogeneous feedstocks containing impurities. [ 15 ] The primary products of pyrolysis—biochar and bio-oil—offer potential for high-value applications. However, critical gaps remain in understanding: (1) How residual components in feed affect product quality, and (2) The quantitative impact of impurity content on both product characteristics and pollutant emissions (such as PM and heavy metals). These knowledge gaps impede process optimization and environmental risk assessment, constraining pyrolysis-based valorization of heterogeneous bulky waste. In this work, we quantitatively elucidated the dual effects of residue content on product quality and pollutant emissions from wooden waste pyrolysis. Bench-scale experiments were conducted to collect pyrolysis products and particulates. By integrating physical and chemical analyses of the products and particulate matter, we evaluated product usability under different impurity contents and quantified pollutant emission levels. The findings provided theoretical guidance for optimizing the resource utilization of wooden waste from the dismantled bulky waste. 2. Materials and Methods 2.1 Materials The sawdust and three main residual materials (leather, sponge, and textile) were collected from a bulky waste treatment plant in Shenzhen, China. These samples were obtained through multi - point sampling and then were crushed and blended. All sample dimensions are less than 5 mm. To facilitate analysis, the three residues in all mixed samples are present in a 1:1:1 ratio. Four types of samples with residue contents of 0%, 5%, 10%, and 15% were selected for experimental analysis. Among them, 15% represents the maximum residue content in the bulky waste treatment plant sampled. The essential properties of the samples are displayed in Table 1 . It was noticed that the collected leather samples were all nitrogen - free, indicating that they were synthetic leather. This suggests that the content of authentic leather in the waste furniture was extremely low. Table 1 Proximate and ultimate analysis of raw materials Sawdust Leather Sponge Textile Ultimate analysis (wt.%, ad) N 0.13 ± 0.01 - * 6.55 ± 0.08 - C 45.7 ± 0.27 41.17 ± 0.18 62.09 ± 0.16 84.92 ± 0.04 H 6.18 ± 0.04 4.5 ± 0.18 8.25 ± 0.40 14.32 ± 0.06 S - - - - O ** 32.39 ± 0.65 33.49 ± 0.31 22.81 ± 0.16 1.09 ± 0.04 Proximate analysis (wt.%, ad) Ash 1.93 ± 0.01 10.36 ± 0.00 - 0.76 ± 0.00 Volatiles 82.47 ± 0.42 69.06 ± 0.06 99.4 ± 0.01 99.57 ± 0.01 Fixed carbon ** 15.6 ± 0.43 20.58 ± 0.06 - - * - indicates not detected ** calculated by difference: O = 100% – C – H – N – S – Ash Fixed carbon = 100% – Ash – Volatile 2.2 Experimental Setup The experiment used a vertical tubular furnace system for pyrolysis to collect bio-oil, bio-char, and particulate matter (PM), as well as to analyze gas product components. As illustrated in the schematic diagram (Figure S1), the apparatus comprised three functional modules: gas supply, pyrolysis reactor, and product collection/analysis. High-purity nitrogen gas (99.99% purity) was employed as the reaction atmosphere, with its flow rate precisely controlled at 400 mL·min − 1 via a mass flow meter. Prior to pyrolysis, the system was purged with nitrogen for 30 min to eliminate residual oxygen and establish an inert environment. The furnace was stabilized at 550°C before 3.0 ± 0.1 g of biomass samples was introduced on sample tray to into the reactor. The pyrolysis was maintained for 30 min under continuous nitrogen flow to ensure complete reaction and product collection. The system was configured with separate pathways for gas analysis and bio-oil/particulate matter collection, selectable via valves. (1) For gas analysis, condensable bio-oil vapors were first filtered out using an organic solvent (methanol: dichloromethane = 1:4, v/v) cooled in dry ice, followed by dehydration with anhydrous calcium chloride (CaCl 2 ). The cleaned gas was then sent to a gas analyzer (Gasboard-3100 P, Hubei Cubic-Ruiyi Instrument Co. Ltd., China) for composition measurement. (2) For bio-oil and PM collection, the aerosol stream passed through a 0.22 µm nylon membrane filter to capture PM, and the remaining vapor was condensed at liquid N₂ temperature (− 196°C) to trap all bio-oil. This two-channel design enabled simultaneous gas monitoring and phase-specific product collection without cross-interference. The bio-char remained in the quartz reactor. After cooling and weighing, the bio-char sample was collected and stored in amber glass bottles. Each experiment was conducted in duplicate to ensure reproducibility, with system performance confirmed by comparing bio-char yields from the two runs. 2.3 Characterization 2.3.1 Bio-char The bio-char yield ( Y BC ) was calculated gravimetrically: $${Y}_{BC}=\frac{{m}_{BC}}{{m}_{0}}\times100\%$$ 1 where m BC and m 0 represent the mass of bio-char and initial mass of feedstock, respectively. The physical characteristics of bio-char were examined via surface morphology and N₂ physical adsorption/desorption analyses. Surface morphology was observed by scanning electron microscopy (SEM-EDS, TM4000 plus, Hitachi, Japan), and energy-dispersive X-ray spectroscopy (EDS) provided quantitative insight into how residual materials affect structure. N₂ physical adsorption/desorption isotherms (ASAP 2020 Plus, Micromeritics, US) were used to determine the Brunauer-Emmentt-Teller (BET) specific surface area and pore size distribution, providing data to evaluate the utility of bio-char. The chemical composition of bio-char was characterized using Fourier-transform infrared spectroscopy (FTIR, IRTRACER-100, Shimadzu, Japan), Raman spectroscopy (Renishaw 287Q00, UK), and inductively coupled plasma mass spectrometry (ICP-MS, iCAP Qnova Series; Thermoscientific, US). FTIR and Raman spectroscopy primarily analyze the composition and variations of surface functional groups of bio-char under different residue contents. ICP-MS was employed to investigate the distribution characteristics of heavy metals in bio-char when leather waste is present during pyrolysis. 2.3.2 Bio-oil The bio-oil yield ( Y BO ) was directly calculated through gravimetric measurement: $${Y}_{BO}=\frac{{m}_{BO}}{{m}_{0}}\times100\%$$ 2 where m BO represents the mass of bio-oil. Bio-oil composition was characterized by gas chromatography-mass spectrometry (GCMS, 5977B GC/MSD, Agilent, US) equipped with an HP-5MS (30 m × 250 mm × 0.25µm) chromatographic column. Bio-oil samples were diluted with 30 mL of dichloromethane-methanol mixed solution (4:1, chromatographic grade) and then filtered through a 0.22 µm nylon membrane to remove potential particulate. GC-MS conditions included helium carrier gas (99.99% purity) at 1 mL·min − 1 , an electron ionization (EI) source at 70 eV a and mass scanning from 33–500 amu. A solvent delay of 4 min was set to avoid solvent peaks, and a post-run bake-out at 280°C for 2 min was applied to remove residual organics. The injector was at 250°C and the detector at 280°C. The oven program held at 50°C for 5 min, ramped 5°C·min − 1 to 200°C, then 15°C·min − 1 to 450°C, holding for 5 min. chromatographic and mass spectral integration were performed using dedicated software. Chromatogram integration and peak identification were performed with the NIST14 spectral library, accepting matches ≥ 70% and confirming by retention time. Identified compounds were categorized into functional groups (alcohols, aromatic hydrocarbons, phenols, alkanes, halogenated organics, nitrogen-containing compounds, aldehydes, ketones, alkenes, esters, ethers, and an “others” category for unidentified compounds) to elucidate bio-oil composition characteristics. 2.3.3 Particulate matter The yield of PM ( Y PM ) was calculated gravimetrically: $${Y}_{PM}=\frac{{m}_{PM}}{{m}_{0}}\times100\%$$ 3 where m PM represents the mass of PM. PM morphology was characterized by photography and SEM. Portions of the collection filter were gold-sputtered and examined via SEM for particle morphology. PM chemical composition was analyzed by GC-MS: the collected particulate matter was dissolved in dichloromethane–methanol (4:1) and then analyzed under the same GC-MS conditions as the bio-oil (subsection 2.3.2 ). 2.3.4 Gas components characteristic The gas yield ( Y gas ) was determined by difference: $${Y}_{gas}=100\%-{Y}_{BC}-{Y}_{BO}-{Y}_{PM}$$ 4 Gas composition was measured with a portable IR gas analyzer, detecting CO 2 , CO, CH 4 , and H 2 at 1-second intervals. By integrating the real-time release curves, the volume percentages of each gas were obtained. Combining these with their molecular weights allowed calculation of the mass distribution of the gaseous products. 3. Results and Discussion 3.1 Products analysis 3.1.1 Products distribution Figure 1 shows the pyrolysis product distributions of each sample (including the mixed sample), with gas yield determined by difference (with a comparison to theoretical values in Table S1). The product yields differed mainly in biochar, particulate matter (PM), and gases. The biochar yield significantly exceeded the theoretical value. The PM yield initially decreased but then increased at higher residue ratios, exceeding the theoretical prediction at 15% residue content. The total yield of char + PM increased with residue content, indicating more solid products at higher impurity levels. Low residue content helped to retain solid products and high- molecular-weight tar within the carbon structure. Additionally, residues had a higher average gas yield (37.44%) than sawdust (28.62%). higher residue fractions promoted gas-phase transport of macromolecular tar and biochar particles, leading to a rebound in PM formation at 15% residue. In terms of gas composition (Fig. 2 ), CO is the primary gaseous component. As the residue content increased from 0% to 5%, 10%, and 15%, the CO/CO 2 ratio in the gas dropped markedly (from 5.42 to 2.42, 2.83, and 2.48, respectively), and the CH 4 /CO 2 ratio also declined (from 3.08 to 1.61, 1.04, and 1.17, respectively). Overall, the total gas yield decreased with higher residue, indicating that reduced CO and CH 4 production drove the decline in gas output. Notably, the presence of residues did not increase the overall oxygen content of the feedstock (as the O/C ratio actually decreases), suggesting a synergistic effect that promoted additional CO 2 formation rather than simply introducing more oxygen. In other words, the addition of residues facilitated the conversion of the overall oxygen in the feedstock into CO 2 in the gas phase, which had a certain positive effect on controlling the oxygen content in liquid products. 3.1.2 Bio-oil distribution From the total ion chromatograms (Fig. 3 ), the bio-oil compounds were predominantly distributed at low retention time ( RT ) positions. Generally, a smaller RT corresponds to lower molecular weight or shorter carbon chain length. [ 16 ] Compositionally, the presence of residues completely altered the characteristics of bio-oil. On one hand, the complexity of bio-oil increased. The characteristic product of sponge (C 8 H 8 ) was presented in the mixed sample, while the characteristic products of leather (C 8 H 17 Cl) and fabric (C 9 H 18 ) were not. It is worth noting that the leather-derived compound contains chlorine (C 8 H 17 Cl), however, no Cl-containing species were detected in the mixed-sample bio-oil, indicating that leather’s chlorine likely shifted into the gas or solid phase. This outcome might be unfavorable for gas utilization but is significant for environmental safety by preventing chlorinated compounds in the liquid fuel. As the residue content increased, bio-oil components associated with the textile (C 16 H 34 O and C 12 H 24 ) became evident in the products. On the other hand, at low residue content (5%), the variety of phenolic compounds greatly increased (from 8.56% to 40.17%), and the proportion of C8 and smaller molecules rose from 52.02% to 59.84%, resulting in a higher fraction of easily utilizable components in the bio-oil. As residue content increased further, the everage carbon chain length of bio-oil increased (C8 decreases to 42.27% and 36.14% in samples with 10% and 15% residue content, respectively), while phenolic content dropped sharply (reducing to 13.46% and 13.45%, respectively), thereby reducing utilization potential. 3.1.3 Bio-char properties The surface morphology and chemical structure of char samples with different residue contents were shown in Fig. 4 . (1) Physical structure Microscopy revealed increasingly compact structures, with pores becoming indistinct at 15% residue content. N 2 adsorption results indicated that the specific surface area initially increased and then decreased at higher residues. This suggests that trace amounts of residues (5%) may provide complementary and catalytic effects (via metal components), promoting volatile release and pore formation to increase surface area. However, excessive residues restricted mass transfer during wood pyrolysis, limiting volatile release and ultimately reducing the surface area. (2) Chemical structure FTIR spectra were largely similar for all chars, with only minor peak differences. Peaks at 3750 cm⁻¹ and 3000–3600 cm⁻¹ correspond to hydroxyl (–OH) groups. An intensified peak at 3750 cm⁻¹ in residue-containing samples indicated increased aromatic alcohols or substituted phenols, while the broad peak at 3000–3600 cm⁻¹ (hydroxyl from moisture) weakened, suggesting reduced hydrophilicity. Peaks at 1042 cm⁻¹ (C–O stretching) [ 17 ] and 628 cm⁻¹ (C–N stretching (Larkin, 2011)) diminished as residue content increased, indicating fewer oxygen/nitrogen functional groups on the bio-char surfaces—consistent with the earlier observation of oxygen being drawn off into CO 2 . Peaks at 1698 cm⁻¹ and 1577 cm⁻¹ (aromatic ring C = O stretching) [ 18 ] influence thermal/chemical stability, while peaks at 1414 cm⁻¹ and 1253 cm⁻¹ (aromatic substituents) affect surface reactivity. Residue content had no significant impact on these peaks, implying stable carbon structure and surface activity. Raman analysis showed that the G-band full-width-at-half-maximum (FWHM) increased with residue content, indicating lower graphitic crystallinity. Lower I D / I G ratios (compared to pure sawdust char) suggested fewer defects and a proportion of higher graphitic carbon. [ 19 ] Sample M-5 exhibited the lowest G-band FWHM and I D / I G , implying superior graphitization and structural stability. Its low I D / I (GR+VL+VR) ratio indicated that large aromatic rings structures (≥ 6 rings) were present mainly in amorphous carbon. [ 20 ] Samples M-10 and M-15 also had lower I D / I G than M-0, but higher G-band FWHM, suggesting higher graphitization but poorer crystallinity. Their carbon skeletons likely comprised smaller graphite crystallinities, which enhanced chemical stability but reduced mechanical strength (Gurtner et al., 2023; Junior et al., 2020). [ 21 , 22 ] Additionally, high I D / I (GR+VL+VR) ratios indicated more large aromatic rings attached to graphite structures, further reducing crystallinity. 3.2 Pollutants analysis 3.2.1 Particulate matter The PM from sawdust exhibited a dispersed, clustered morphology (Fig. 5 ). Chemically, the PM was predominantly composed of high-molecular-weight compounds of a relatively simple composition, mainly ethers, carboxylic acids, and esters (together 99.52%, contributing 12.29%, 30.68%, and 56.55%, respectively). This implied that the liquid-phase products and small molecular components in pure wood pyrolysis have low viscosity, preventing the entrapment of carbonaceous particles (e.g., soot (Richter and Howard, 2000)) from being trapped to form PM. The major identified component was C 24 H 38 O 4 (44.71%, including 42.44% Bis(2 - ethylhexyl) phthalate and 2.27% 1, 3 - Benzenedicarboxylic acid, bis(2 - ethylhexyl) ester). Acidic components in the PM tended to condense on cooler sections of pipelines or equipment, posing corrosive risks; notably, in pure sawdust PM the total acidic component content reached 30.68%, highlighting its critical role in system degradation. When the residue content was low (5%), no significant clusters were observed on the surface, and the proportion of small molecular components increased, leading to elevated compositional complexity (from 3 to 7 components, including phenols, aldehydes, carboxylic acids, sugars, ketones, alkanes, and esters, totaling 100.00%). The acidic component content dropped to 3.51%. As the residue content increased to 10% and 15%, the PM composition became even more complex. Aromatic hydrocarbons in the PM increased (reaching 3.99% at 15%) and alcohols emerged (6.60% at 15%). Multiple minor peaks categorized as "others" appeared (combined 9.03%), and the acidic content rebounded to 6.02% at 10% and 10.44% at 15%, respectively. In summary, low residue content significantly benefited PM control, both by reducing the PM yield and mitigating harmful component (e.g., acidic species). Under low residue conditions, most solid products remained as biochar rather than being entrained into vapor phase to form airborne particulates. 3.2.2 Heavy metal in bio-char As shown in Fig. 6 , heavy metal concentrations in residue-containing bio-char samples were significantly higher than those in pure sawdust for all metals except Cu. This confirms that the residues (especially leather) as the primary source of these metals in the char. Cr concentrations increased with residue content, though not proportionally. Other elements (Ni, As, Cd, Sb) peaked at 10% residue content (M-10), except Cd. According to China’s agricultural soil standard (GB15618-2018), arsenic (As) exceeded risk thresholds (control value: 10 mg/kg for pH > 7.5). The European Bio-char Certificate (EBC) agricultural limit for As is 1.3 mg/kg. Thus, even a small amount of residues introduced a significant As contamination risks. At 15% residue content (M-15), As level was ~ 3× the limit; at 5% (M-5), ~ 4×. Dilution could mitigate risks but reduce utilization efficiency. M-10 (7× the limit) posed the greatest challenges for cost-effective remediation. 4. Conclusion This study highlighted the significant influence of residual materials on pyrolysis products and pollutants from wooden waste. Key findings are summarized as follows: (1) Impact of residual components on product quality. Residual components dose-dependently modulate pyrolysis product quality. At 5% content, bio-oil phenolics increased from 8.56% to 40.17% and light fractions (≤ C8) from 52.02% to 59.84%; bio-char surface area peaked at low residues then declined, while the CO/CO 2 ratio decreased from 5.42 to 2.48 as residues rose from 0% to 15%. However, benefits reversed above 5% residue, reducing phenolics to ~ 13.5% and diminishing fuel utility. (2) Quantitative impact on pollutant emissions. Impurity content governs pollutant emissions through threshold effects. Particulate matter yield followed a U-shaped trajectory, decreasing initially but rebounding at 15% residue. Acidic PM components dropped to 3.51% at 5% residue but surged to 10.44% at 15%. Critically, residual leather introduced arsenic contamination, exceeding China's agricultural soil standard (10 mg/kg) by 4-fold at 5% residue and the European Bio-char Certificate limit (1.3 mg/kg) by an order of magnitude, mandating stringent residue control. Further research can explore the effects of other residual materials, such as metals and composite waste, and investigate synergistic interactions under different pyrolysis conditions. Additionally, the long-term stability and bioavailability of heavy metals in bio-char need to be assessed to address potential ecological and health risks. Declarations Funding Declaration This research was funded by the Ministry of Education (MOE) and the Jeju Special Self-Governing Province, Republic of Korea. (2025-RISE-17-001). Acknowledgement This research was supported by the Regional Innovation System & Education (RISE) program through the Jeju RISE center. The authors would like to acknowledge the staff and postgraduate students at Shenzhen Engineering Laboratory for Eco-efficient Recycled Materials. 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School","correspondingAuthor":false,"prefix":"","firstName":"Xiyao","middleName":"","lastName":"Zhao","suffix":""},{"id":603754076,"identity":"82d4512f-94c2-4ad1-9c34-ffc892c1b40a","order_by":2,"name":"Jae-Hac Ko","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Jae-Hac","middleName":"","lastName":"Ko","suffix":""},{"id":603754078,"identity":"9c3266a8-dff0-4807-aa5d-24f64d4d6c6f","order_by":3,"name":"Ning Wang","email":"","orcid":"","institution":"Chinese Academy of Tropical Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Wang","suffix":""},{"id":603754080,"identity":"2413e469-ec16-42ea-bcbc-42d393ed6bbe","order_by":4,"name":"Qiyong Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYDACZijNz8AGZR0gVotkA9FaYMDgALFa+I7zGD4u+HU4cfPttjTJH38Y5PhuJDB+LsCjRfIwj7HxzL60xG13jh2T5uFhMJa8kcAsPQOfew7zmEnz9tgkbruR3ibNIMGQuOFGAhszD2EtEombZ6S3Sf4wYKgnTgvPD5vEDRJpxyR4EhgSDAhpkTzMVmzM25BmPOPOsWRrngMShjPPPGyWxqeF7/zhjY95/hyW7Z/dZnjzxx8beb7jyQc/49PCcIDDgIGxDciQAHNBJGMDPg1ALewPGBj+wLWMglEwCkbBKMAEAJHtS0wURoFCAAAAAElFTkSuQmCC","orcid":"","institution":"Peking University Shenzhen Graduate School","correspondingAuthor":true,"prefix":"","firstName":"Qiyong","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2026-03-06 02:08:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9045066/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9045066/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108460286,"identity":"4f9f76a4-dcca-4711-aa96-2f6848e003a4","added_by":"auto","created_at":"2026-05-05 00:39:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":211423,"visible":true,"origin":"","legend":"\u003cp\u003ePyrolysis product distribution\u0026nbsp;\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9045066/v1/a1781a19b2cdb0cae3a6b437.png"},{"id":108460281,"identity":"e54c3784-b2a2-49bd-8e06-3237fc2c0169","added_by":"auto","created_at":"2026-05-05 00:39:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":152139,"visible":true,"origin":"","legend":"\u003cp\u003eReal-time gas release curves of pyrolysis with different residue contents\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9045066/v1/d0ad077f7ac293b755b1b7ac.png"},{"id":108460282,"identity":"169b19f1-4668-4541-9848-981eb9870f9a","added_by":"auto","created_at":"2026-05-05 00:39:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":118065,"visible":true,"origin":"","legend":"\u003cp\u003eTotal ion chromatograms (a) and component classification (b) of bio-oil with different residue contents\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9045066/v1/3389f9ef31d46fd1442233b9.png"},{"id":108460284,"identity":"61e12cdf-ccab-4e8a-b804-8f2abf90e30e","added_by":"auto","created_at":"2026-05-05 00:39:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":441798,"visible":true,"origin":"","legend":"\u003cp\u003eSurface morphology (a)~(d), and chemical structure (e) FTIR and (f) Raman area ratio, for char samples with different residue contents\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9045066/v1/f47d0d6dc4d4ee0030e41605.png"},{"id":108460283,"identity":"6abfbe0e-8db4-4a6e-b395-6efe94916a41","added_by":"auto","created_at":"2026-05-05 00:39:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1835853,"visible":true,"origin":"","legend":"\u003cp\u003ePM characterization. (GC-MS spectra, SEM, product photograph)\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9045066/v1/517aae3c4ef162021089f464.png"},{"id":108460285,"identity":"3cf562c3-c456-4889-b710-b47ab937909f","added_by":"auto","created_at":"2026-05-05 00:39:59","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":762786,"visible":true,"origin":"","legend":"\u003cp\u003eHeavy metal concentrations in residue-containing bio-char\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9045066/v1/ce83af0ba03b66c868331302.png"},{"id":108803832,"identity":"2d3f0e4b-400e-4464-aba4-1c314f20cc1e","added_by":"auto","created_at":"2026-05-08 15:08:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3689565,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9045066/v1/6a17783c-f7bf-41eb-9d15-89f408723922.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of typical residuals on wooden waste pyrolysis: products and pollutants","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBulky wastes have become pressing domestic waste issues.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e Bulky wastes are large-sized and typically made of various materials,\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e such as wooden framework, leather,\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e flame retardant,\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e and foam.\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e The treatment of bulky wastes, apart from direct recycling, usually requires initial dismantling. During the dismantling process, high-value metals and relatively intact foam are separated for recycling, while other components\u0026mdash;predominantly wooden waste mixed with residues such as cloth, foam, and leather\u0026mdash;are usually crushed together and undergo subsequent treatment.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e Disposal of the wooden waste (landfill or incineration) will not only increase the operational costs of bulky wastes processing facilities, but also not conducive to the resource utilization of the wooden components.\u003c/p\u003e \u003cp\u003eCurrently, thermal utilization technologies\u0026mdash;such as combustion (distinct from waste incineration), pyrolysis, and gasification\u0026mdash;are highly efficient methods for valorizing wooden waste.\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e However, residual impurities may impact their reaction process or utilization efficiency. Combustion and gasification are two approaches that require an oxidizing medium (e.g., air, water vapor),\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e mecessitating a mass transfer process from the exterior to the interior of the fuel. Residue materials like leather usually have low softening/melting points.\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e Upon softening/melting, they may encapsulate the woody fuel, hindering oxidant diffusion and reducing conversion efficiency.\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e Additionally, incomplete conversion of fuel can carry over significant amounts of particulate matter and tar, causing corrosion to downstream equipment.\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e Notably, in combustion-based power generation, entrained particulate matter can foul heat transfer surfaces, lowering heat transfer efficienc;\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e in gasification, tar increased gas cleanup costs. Consequently, when wooden waste from dismantling is used as biomass fuel, a low impurity content is generally required, which elevates the labor and operational costs of front-end treatment.\u003c/p\u003e \u003cp\u003ePyrolysis demonstrates a broader adaptability to feedstock heterogeneity than combustion or gasification.\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e Unlike those processes, pyrolysis operates without oxidizing agents, and mass transfer primarily occurs through internal-to-external diffusion within particles.\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e This reduces the impact of residue softening/melting on the conversion process. Furthermore, biomass pyrolysis typically occurs at lower temperatures (500\u0026ndash;800\u0026deg;C), allowing the use of corrosion-resistant materials in reactor design. Therefore, pyrolysis is more suitable for resource utilization of heterogeneous feedstocks containing impurities.\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e The primary products of pyrolysis\u0026mdash;biochar and bio-oil\u0026mdash;offer potential for high-value applications. However, critical gaps remain in understanding: (1) How residual components in feed affect product quality, and (2) The quantitative impact of impurity content on both product characteristics and pollutant emissions (such as PM and heavy metals). These knowledge gaps impede process optimization and environmental risk assessment, constraining pyrolysis-based valorization of heterogeneous bulky waste.\u003c/p\u003e \u003cp\u003eIn this work, we quantitatively elucidated the dual effects of residue content on product quality and pollutant emissions from wooden waste pyrolysis. Bench-scale experiments were conducted to collect pyrolysis products and particulates. By integrating physical and chemical analyses of the products and particulate matter, we evaluated product usability under different impurity contents and quantified pollutant emission levels. The findings provided theoretical guidance for optimizing the resource utilization of wooden waste from the dismantled bulky waste.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Materials\u003c/h2\u003e \u003cp\u003eThe sawdust and three main residual materials (leather, sponge, and textile) were collected from a bulky waste treatment plant in Shenzhen, China. These samples were obtained through multi - point sampling and then were crushed and blended. All sample dimensions are less than 5 mm. To facilitate analysis, the three residues in all mixed samples are present in a 1:1:1 ratio. Four types of samples with residue contents of 0%, 5%, 10%, and 15% were selected for experimental analysis. Among them, 15% represents the maximum residue content in the bulky waste treatment plant sampled. The essential properties of the samples are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. It was noticed that the collected leather samples were all nitrogen - free, indicating that they were synthetic leather. This suggests that the content of authentic leather in the waste furniture was extremely low.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProximate and ultimate analysis of raw materials\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSawdust\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLeather\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSponge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTextile\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUltimate analysis (wt.%, ad)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProximate analysis (wt.%, ad)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolatiles\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFixed carbon\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e*\u003c/sup\u003e- indicates not detected\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e**\u003c/sup\u003ecalculated by difference:\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eO\u0026thinsp;=\u0026thinsp;100% \u0026ndash; C \u0026ndash; H \u0026ndash; N \u0026ndash; S \u0026ndash; Ash\u003c/p\u003e \u003cp\u003eFixed carbon\u0026thinsp;=\u0026thinsp;100% \u0026ndash; Ash \u0026ndash; Volatile\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Experimental Setup\u003c/h2\u003e \u003cp\u003eThe experiment used a vertical tubular furnace system for pyrolysis to collect bio-oil, bio-char, and particulate matter (PM), as well as to analyze gas product components. As illustrated in the schematic diagram (Figure S1), the apparatus comprised three functional modules: gas supply, pyrolysis reactor, and product collection/analysis. High-purity nitrogen gas (99.99% purity) was employed as the reaction atmosphere, with its flow rate precisely controlled at 400 mL\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e via a mass flow meter. Prior to pyrolysis, the system was purged with nitrogen for 30 min to eliminate residual oxygen and establish an inert environment. The furnace was stabilized at 550\u0026deg;C before 3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 g of biomass samples was introduced on sample tray to into the reactor. The pyrolysis was maintained for 30 min under continuous nitrogen flow to ensure complete reaction and product collection.\u003c/p\u003e \u003cp\u003eThe system was configured with separate pathways for gas analysis and bio-oil/particulate matter collection, selectable via valves. (1) For gas analysis, condensable bio-oil vapors were first filtered out using an organic solvent (methanol: dichloromethane\u0026thinsp;=\u0026thinsp;1:4, v/v) cooled in dry ice, followed by dehydration with anhydrous calcium chloride (CaCl\u003csub\u003e2\u003c/sub\u003e). The cleaned gas was then sent to a gas analyzer (Gasboard-3100 P, Hubei Cubic-Ruiyi Instrument Co. Ltd., China) for composition measurement. (2) For bio-oil and PM collection, the aerosol stream passed through a 0.22 \u0026micro;m nylon membrane filter to capture PM, and the remaining vapor was condensed at liquid N₂ temperature (\u0026minus;\u0026thinsp;196\u0026deg;C) to trap all bio-oil. This two-channel design enabled simultaneous gas monitoring and phase-specific product collection without cross-interference.\u003c/p\u003e \u003cp\u003eThe bio-char remained in the quartz reactor. After cooling and weighing, the bio-char sample was collected and stored in amber glass bottles. Each experiment was conducted in duplicate to ensure reproducibility, with system performance confirmed by comparing bio-char yields from the two runs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Characterization\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 Bio-char\u003c/h2\u003e \u003cp\u003eThe bio-char yield (\u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003eBC\u003c/em\u003e\u003c/sub\u003e) was calculated gravimetrically:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$${Y}_{BC}=\\frac{{m}_{BC}}{{m}_{0}}\\times100\\%$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003em\u003c/em\u003e\u003csub\u003e\u003cem\u003eBC\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003em\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e represent the mass of bio-char and initial mass of feedstock, respectively.\u003c/p\u003e \u003cp\u003eThe physical characteristics of bio-char were examined via surface morphology and N₂ physical adsorption/desorption analyses. Surface morphology was observed by scanning electron microscopy (SEM-EDS, TM4000 plus, Hitachi, Japan), and energy-dispersive X-ray spectroscopy (EDS) provided quantitative insight into how residual materials affect structure. N₂ physical adsorption/desorption isotherms (ASAP 2020 Plus, Micromeritics, US) were used to determine the Brunauer-Emmentt-Teller (BET) specific surface area and pore size distribution, providing data to evaluate the utility of bio-char.\u003c/p\u003e \u003cp\u003eThe chemical composition of bio-char was characterized using Fourier-transform infrared spectroscopy (FTIR, IRTRACER-100, Shimadzu, Japan), Raman spectroscopy (Renishaw 287Q00, UK), and inductively coupled plasma mass spectrometry (ICP-MS, iCAP Qnova Series; Thermoscientific, US). FTIR and Raman spectroscopy primarily analyze the composition and variations of surface functional groups of bio-char under different residue contents. ICP-MS was employed to investigate the distribution characteristics of heavy metals in bio-char when leather waste is present during pyrolysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Bio-oil\u003c/h2\u003e \u003cp\u003eThe bio-oil yield (\u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003eBO\u003c/em\u003e\u003c/sub\u003e) was directly calculated through gravimetric measurement:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$${Y}_{BO}=\\frac{{m}_{BO}}{{m}_{0}}\\times100\\%$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003em\u003c/em\u003e\u003csub\u003e\u003cem\u003eBO\u003c/em\u003e\u003c/sub\u003e represents the mass of bio-oil.\u003c/p\u003e \u003cp\u003eBio-oil composition was characterized by gas chromatography-mass spectrometry (GCMS, 5977B GC/MSD, Agilent, US) equipped with an HP-5MS (30 m \u0026times; 250 mm \u0026times; 0.25\u0026micro;m) chromatographic column. Bio-oil samples were diluted with 30 mL of dichloromethane-methanol mixed solution (4:1, chromatographic grade) and then filtered through a 0.22 \u0026micro;m nylon membrane to remove potential particulate. GC-MS conditions included helium carrier gas (99.99% purity) at 1 mL\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, an electron ionization (EI) source at 70 eV a and mass scanning from 33\u0026ndash;500 amu. A solvent delay of 4 min was set to avoid solvent peaks, and a post-run bake-out at 280\u0026deg;C for 2 min was applied to remove residual organics. The injector was at 250\u0026deg;C and the detector at 280\u0026deg;C. The oven program held at 50\u0026deg;C for 5 min, ramped 5\u0026deg;C\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 200\u0026deg;C, then 15\u0026deg;C\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 450\u0026deg;C, holding for 5 min. chromatographic and mass spectral integration were performed using dedicated software. Chromatogram integration and peak identification were performed with the NIST14 spectral library, accepting matches\u0026thinsp;\u0026ge;\u0026thinsp;70% and confirming by retention time. Identified compounds were categorized into functional groups (alcohols, aromatic hydrocarbons, phenols, alkanes, halogenated organics, nitrogen-containing compounds, aldehydes, ketones, alkenes, esters, ethers, and an \u0026ldquo;others\u0026rdquo; category for unidentified compounds) to elucidate bio-oil composition characteristics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3 Particulate matter\u003c/h2\u003e \u003cp\u003eThe yield of PM (\u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003ePM\u003c/em\u003e\u003c/sub\u003e) was calculated gravimetrically:\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$${Y}_{PM}=\\frac{{m}_{PM}}{{m}_{0}}\\times100\\%$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003em\u003c/em\u003e\u003csub\u003e\u003cem\u003ePM\u003c/em\u003e\u003c/sub\u003e represents the mass of PM.\u003c/p\u003e \u003cp\u003ePM morphology was characterized by photography and SEM. Portions of the collection filter were gold-sputtered and examined via SEM for particle morphology. PM chemical composition was analyzed by GC-MS: the collected particulate matter was dissolved in dichloromethane\u0026ndash;methanol (4:1) and then analyzed under the same GC-MS conditions as the bio-oil (subsection \u003cspan refid=\"Sec7\" class=\"InternalRef\"\u003e2.3.2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.4 Gas components characteristic\u003c/h2\u003e \u003cp\u003eThe gas yield (\u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003egas\u003c/em\u003e\u003c/sub\u003e) was determined by difference:\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$${Y}_{gas}=100\\%-{Y}_{BC}-{Y}_{BO}-{Y}_{PM}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eGas composition was measured with a portable IR gas analyzer, detecting CO\u003csub\u003e2\u003c/sub\u003e, CO, CH\u003csub\u003e4\u003c/sub\u003e, and H\u003csub\u003e2\u003c/sub\u003e at 1-second intervals. By integrating the real-time release curves, the volume percentages of each gas were obtained. Combining these with their molecular weights allowed calculation of the mass distribution of the gaseous products.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Products analysis\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Products distribution\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the pyrolysis product distributions of each sample (including the mixed sample), with gas yield determined by difference (with a comparison to theoretical values in Table S1). The product yields differed mainly in biochar, particulate matter (PM), and gases. The biochar yield significantly exceeded the theoretical value. The PM yield initially decreased but then increased at higher residue ratios, exceeding the theoretical prediction at 15% residue content. The total yield of char\u0026thinsp;+\u0026thinsp;PM increased with residue content, indicating more solid products at higher impurity levels. Low residue content helped to retain solid products and high- molecular-weight tar within the carbon structure. Additionally, residues had a higher average gas yield (37.44%) than sawdust (28.62%). higher residue fractions promoted gas-phase transport of macromolecular tar and biochar particles, leading to a rebound in PM formation at 15% residue.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn terms of gas composition (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), CO is the primary gaseous component. As the residue content increased from 0% to 5%, 10%, and 15%, the CO/CO\u003csub\u003e2\u003c/sub\u003e ratio in the gas dropped markedly (from 5.42 to 2.42, 2.83, and 2.48, respectively), and the CH\u003csub\u003e4\u003c/sub\u003e/CO\u003csub\u003e2\u003c/sub\u003e ratio also declined (from 3.08 to 1.61, 1.04, and 1.17, respectively). Overall, the total gas yield decreased with higher residue, indicating that reduced CO and CH\u003csub\u003e4\u003c/sub\u003e production drove the decline in gas output. Notably, the presence of residues did not increase the overall oxygen content of the feedstock (as the O/C ratio actually decreases), suggesting a synergistic effect that promoted additional CO\u003csub\u003e2\u003c/sub\u003e formation rather than simply introducing more oxygen. In other words, the addition of residues facilitated the conversion of the overall oxygen in the feedstock into CO\u003csub\u003e2\u003c/sub\u003e in the gas phase, which had a certain positive effect on controlling the oxygen content in liquid products.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Bio-oil distribution\u003c/h2\u003e \u003cp\u003eFrom the total ion chromatograms (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the bio-oil compounds were predominantly distributed at low retention time (\u003cem\u003eRT\u003c/em\u003e) positions. Generally, a smaller \u003cem\u003eRT\u003c/em\u003e corresponds to lower molecular weight or shorter carbon chain length.\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e Compositionally, the presence of residues completely altered the characteristics of bio-oil. On one hand, the complexity of bio-oil increased. The characteristic product of sponge (C\u003csub\u003e8\u003c/sub\u003eH\u003csub\u003e8\u003c/sub\u003e) was presented in the mixed sample, while the characteristic products of leather (C\u003csub\u003e8\u003c/sub\u003eH\u003csub\u003e17\u003c/sub\u003eCl) and fabric (C\u003csub\u003e9\u003c/sub\u003eH\u003csub\u003e18\u003c/sub\u003e) were not. It is worth noting that the leather-derived compound contains chlorine (C\u003csub\u003e8\u003c/sub\u003eH\u003csub\u003e17\u003c/sub\u003eCl), however, no Cl-containing species were detected in the mixed-sample bio-oil, indicating that leather\u0026rsquo;s chlorine likely shifted into the gas or solid phase. This outcome might be unfavorable for gas utilization but is significant for environmental safety by preventing chlorinated compounds in the liquid fuel. As the residue content increased, bio-oil components associated with the textile (C\u003csub\u003e16\u003c/sub\u003eH\u003csub\u003e34\u003c/sub\u003eO and C\u003csub\u003e12\u003c/sub\u003eH\u003csub\u003e24\u003c/sub\u003e) became evident in the products.\u003c/p\u003e \u003cp\u003eOn the other hand, at low residue content (5%), the variety of phenolic compounds greatly increased (from 8.56% to 40.17%), and the proportion of C8 and smaller molecules rose from 52.02% to 59.84%, resulting in a higher fraction of easily utilizable components in the bio-oil. As residue content increased further, the everage carbon chain length of bio-oil increased (C8 decreases to 42.27% and 36.14% in samples with 10% and 15% residue content, respectively), while phenolic content dropped sharply (reducing to 13.46% and 13.45%, respectively), thereby reducing utilization potential.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Bio-char properties\u003c/h2\u003e \u003cp\u003eThe surface morphology and chemical structure of char samples with different residue contents were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e(1) Physical structure\u003c/p\u003e \u003cp\u003eMicroscopy revealed increasingly compact structures, with pores becoming indistinct at 15% residue content. N\u003csub\u003e2\u003c/sub\u003e adsorption results indicated that the specific surface area initially increased and then decreased at higher residues. This suggests that trace amounts of residues (5%) may provide complementary and catalytic effects (via metal components), promoting volatile release and pore formation to increase surface area. However, excessive residues restricted mass transfer during wood pyrolysis, limiting volatile release and ultimately reducing the surface area.\u003c/p\u003e \u003cp\u003e(2) Chemical structure\u003c/p\u003e \u003cp\u003eFTIR spectra were largely similar for all chars, with only minor peak differences. Peaks at 3750 cm⁻\u0026sup1; and 3000\u0026ndash;3600 cm⁻\u0026sup1; correspond to hydroxyl (\u0026ndash;OH) groups. An intensified peak at 3750 cm⁻\u0026sup1; in residue-containing samples indicated increased aromatic alcohols or substituted phenols, while the broad peak at 3000\u0026ndash;3600 cm⁻\u0026sup1; (hydroxyl from moisture) weakened, suggesting reduced hydrophilicity. Peaks at 1042 cm⁻\u0026sup1; (C\u0026ndash;O stretching)\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e and 628 cm⁻\u0026sup1; (C\u0026ndash;N stretching (Larkin, 2011)) diminished as residue content increased, indicating fewer oxygen/nitrogen functional groups on the bio-char surfaces\u0026mdash;consistent with the earlier observation of oxygen being drawn off into CO\u003csub\u003e2\u003c/sub\u003e. Peaks at 1698 cm⁻\u0026sup1; and 1577 cm⁻\u0026sup1; (aromatic ring C\u0026thinsp;=\u0026thinsp;O stretching)\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e influence thermal/chemical stability, while peaks at 1414 cm⁻\u0026sup1; and 1253 cm⁻\u0026sup1; (aromatic substituents) affect surface reactivity. Residue content had no significant impact on these peaks, implying stable carbon structure and surface activity.\u003c/p\u003e \u003cp\u003eRaman analysis showed that the G-band full-width-at-half-maximum (FWHM) increased with residue content, indicating lower graphitic crystallinity. Lower \u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e/\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e ratios (compared to pure sawdust char) suggested fewer defects and a proportion of higher graphitic carbon.\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e Sample M-5 exhibited the lowest G-band FWHM and \u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e/\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e, implying superior graphitization and structural stability. Its low \u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e/\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003e(GR+VL+VR)\u003c/em\u003e\u003c/sub\u003e ratio indicated that large aromatic rings structures (\u0026ge;\u0026thinsp;6 rings) were present mainly in amorphous carbon.\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e Samples M-10 and M-15 also had lower \u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e/\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e than M-0, but higher G-band FWHM, suggesting higher graphitization but poorer crystallinity. Their carbon skeletons likely comprised smaller graphite crystallinities, which enhanced chemical stability but reduced mechanical strength (Gurtner et al., 2023; Junior et al., 2020).\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e Additionally, high \u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eD\u003c/em\u003e\u003c/sub\u003e/\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003e(GR+VL+VR)\u003c/em\u003e\u003c/sub\u003e ratios indicated more large aromatic rings attached to graphite structures, further reducing crystallinity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Pollutants analysis\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Particulate matter\u003c/h2\u003e \u003cp\u003eThe PM from sawdust exhibited a dispersed, clustered morphology (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Chemically, the PM was predominantly composed of high-molecular-weight compounds of a relatively simple composition, mainly ethers, carboxylic acids, and esters (together 99.52%, contributing 12.29%, 30.68%, and 56.55%, respectively). This implied that the liquid-phase products and small molecular components in pure wood pyrolysis have low viscosity, preventing the entrapment of carbonaceous particles (e.g., soot (Richter and Howard, 2000)) from being trapped to form PM. The major identified component was C\u003csub\u003e24\u003c/sub\u003eH\u003csub\u003e38\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e (44.71%, including 42.44% Bis(2 - ethylhexyl) phthalate and 2.27% 1, 3 - Benzenedicarboxylic acid, bis(2 - ethylhexyl) ester). Acidic components in the PM tended to condense on cooler sections of pipelines or equipment, posing corrosive risks; notably, in pure sawdust PM the total acidic component content reached 30.68%, highlighting its critical role in system degradation.\u003c/p\u003e \u003cp\u003eWhen the residue content was low (5%), no significant clusters were observed on the surface, and the proportion of small molecular components increased, leading to elevated compositional complexity (from 3 to 7 components, including phenols, aldehydes, carboxylic acids, sugars, ketones, alkanes, and esters, totaling 100.00%). The acidic component content dropped to 3.51%. As the residue content increased to 10% and 15%, the PM composition became even more complex. Aromatic hydrocarbons in the PM increased (reaching 3.99% at 15%) and alcohols emerged (6.60% at 15%). Multiple minor peaks categorized as \"others\" appeared (combined 9.03%), and the acidic content rebounded to 6.02% at 10% and 10.44% at 15%, respectively.\u003c/p\u003e \u003cp\u003eIn summary, low residue content significantly benefited PM control, both by reducing the PM yield and mitigating harmful component (e.g., acidic species). Under low residue conditions, most solid products remained as biochar rather than being entrained into vapor phase to form airborne particulates.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Heavy metal in bio-char\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, heavy metal concentrations in residue-containing bio-char samples were significantly higher than those in pure sawdust for all metals except Cu. This confirms that the residues (especially leather) as the primary source of these metals in the char. Cr concentrations increased with residue content, though not proportionally. Other elements (Ni, As, Cd, Sb) peaked at 10% residue content (M-10), except Cd.\u003c/p\u003e \u003cp\u003eAccording to China\u0026rsquo;s agricultural soil standard (GB15618-2018), arsenic (As) exceeded risk thresholds (control value: 10 mg/kg for pH\u0026thinsp;\u0026gt;\u0026thinsp;7.5). The European Bio-char Certificate (EBC) agricultural limit for As is 1.3 mg/kg. Thus, even a small amount of residues introduced a significant As contamination risks. At 15% residue content (M-15), As level was ~\u0026thinsp;3\u0026times; the limit; at 5% (M-5), ~\u0026thinsp;4\u0026times;. Dilution could mitigate risks but reduce utilization efficiency. M-10 (7\u0026times; the limit) posed the greatest challenges for cost-effective remediation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThis study highlighted the significant influence of residual materials on pyrolysis products and pollutants from wooden waste. Key findings are summarized as follows:\u003c/p\u003e \u003cp\u003e(1) Impact of residual components on product quality. Residual components dose-dependently modulate pyrolysis product quality. At 5% content, bio-oil phenolics increased from 8.56% to 40.17% and light fractions (\u0026le;\u0026thinsp;C8) from 52.02% to 59.84%; bio-char surface area peaked at low residues then declined, while the CO/CO\u003csub\u003e2\u003c/sub\u003e ratio decreased from 5.42 to 2.48 as residues rose from 0% to 15%. However, benefits reversed above 5% residue, reducing phenolics to ~\u0026thinsp;13.5% and diminishing fuel utility.\u003c/p\u003e \u003cp\u003e(2) Quantitative impact on pollutant emissions. Impurity content governs pollutant emissions through threshold effects. Particulate matter yield followed a U-shaped trajectory, decreasing initially but rebounding at 15% residue. Acidic PM components dropped to 3.51% at 5% residue but surged to 10.44% at 15%. Critically, residual leather introduced arsenic contamination, exceeding China's agricultural soil standard (10 mg/kg) by 4-fold at 5% residue and the European Bio-char Certificate limit (1.3 mg/kg) by an order of magnitude, mandating stringent residue control.\u003c/p\u003e \u003cp\u003eFurther research can explore the effects of other residual materials, such as metals and composite waste, and investigate synergistic interactions under different pyrolysis conditions. Additionally, the long-term stability and bioavailability of heavy metals in bio-char need to be assessed to address potential ecological and health risks.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding Declaration\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Ministry of Education (MOE) and the Jeju Special Self-Governing Province, Republic of Korea. (2025-RISE-17-001).\u003c/p\u003e\n\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; This research was supported by the Regional Innovation System \u0026amp; Education (RISE) program through the Jeju RISE center. The authors would like to acknowledge the staff and postgraduate students at Shenzhen Engineering Laboratory for Eco-efficient Recycled Materials.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTerazono A, Oguchi M, Akiyama H, Tomozawa H, Hagiwara T, Nakayama J (2024) Ignition and fire-related incidents caused by lithium-ion batteries in waste treatment facilities in Japan and countermeasures. Resour Conserv Recy 202:107398. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://doi.org/10.1016/j.resconrec.2023.107398\u003c/span\u003e\u003cspan address=\"10.1016/j.resconrec.2023.107398\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong N, Lu H, Yang X, Wang J, Yue D (2022) Spatial characteristics and multifactorial driving analysis of fly-tipping bulky waste in Beijing based on the random forest model. 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Elsevier, US\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bulky waste, residues, fast pyrolysis, pollutant emission, pyrolysis products","lastPublishedDoi":"10.21203/rs.3.rs-9045066/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9045066/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBulky wastes disposal generates significant quantities of wooden waste mixed with residues such as cloth, foam, and leather, posing challenges for resource utilization. Pyrolysis offers better adaptability to impurities among thermal treatment technologies. However, the impact of residual impurities on product quality and pollutant emissions remains poorly quantified. This study systematically investigated the effects of residue content (0%, 5%, 10%, and 15%) on wooden waste fast pyrolysis at 550\u0026deg;C, analyzing products (bio-char, bio-oil, particulate matter-PM, and gases) and pollutants. Key results showed that biochar yield exceeded theoretical values, while PM yield decreased initially but rebounded at 15% residue content. Low residue content (5%) enhanced bio-oil quality, increasing phenolic compounds from 8.56% to 40.17% and reducing PM harmful components (e.g., acidic species fell to 3.51%). For gases, increasing the residue content from 0% to 15% lowered the CO/CO2 ratio in the gas from 5.42 to 2.48. However, residues introduced heavy metals like arsenic, exceeding safety limits by 3\u0026ndash;7 times at 5\u0026ndash;15% content. Overall, maintaining low residue content optimizes product usability and pollutant control, supporting pyrolysis for heterogeneous waste.\u003c/p\u003e","manuscriptTitle":"Effects of typical residuals on wooden waste pyrolysis: products and pollutants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-05 00:39:31","doi":"10.21203/rs.3.rs-9045066/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"686455cf-d127-4253-81d4-e944cd8c0b5e","owner":[],"postedDate":"May 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T00:39:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-05 00:39:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9045066","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9045066","identity":"rs-9045066","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}