Co-pyrolysis of sewage sludge and waste tobacco stem: Gas products analysis, pyrolysis kinetics, artificial neural network modeling, and synergistic effects

Co-pyrolysis behavior of sewage sludge and coal slurry: Pyrolysis characteristics, interaction mechanisms, and gas emissions

The co-pyrolysis behaviors of sewage sludge (SS) and coal slurry (CS), including pyrolysis characteristics, kinetics, interactions, and gas emissions, were investigated using the thermogravimetric-mass spectrometry method. The interaction mechanism was revealed by investigating the effect of the pretreatment method on the interaction. The results showed that the addition of SS improved the comprehensive pyrolysis performance of CS. Artificial neural networks were applicable for predicting the co-pyrolysis process, with the optimal model being a 3 × 5 × 7 model. The synergistic effect occurs at 410-609 °C, and 50% CS addition resulted in a reduction of the maximum weight loss peak temperature by 12.3 °C, along with a reduction of the apparent activation energy by 19.2 kJ/mol. For the whole co-pyrolysis process, the most significant synergistic effect was exhibited at CS ratios of 50% and 60%. The synergistic effect was mainly caused by SS volatiles-CS char and SS minerals-CS char interactions. Co-pyrolysis promoted the release of CH3+, CH4, H2O, and CO2 but suppressed the release of H2, NH3, NO, and SO2. The releases of NO and SO2 were 7.3% and 5.8% lower than the theoretical values, respectively. Co-pyrolysis of SS and CS in a mixture of 5:5 or 6:4 is recommended for synergistic effects.

Co-pyrolysis behaviors, kinetics, and thermodynamics of sludge, lignite and biomass through fixed-bed reactor experiments and thermogravimetric analysis

Co-pyrolysis behaviors, kinetics, and thermodynamic parameters of petrochemical sludge (PS), lignite (HL), and pine wood (PW) were investigated via fixed-bed reactor experiments and thermogravimetric analysis. Fixed-bed experiments showed H2 and CO2 were main gases from PS, HL, and blends, CO from PW and PS, and CO and CH4 from PS and HL. Thermal analysis indicated that ternary blends' de-volatilization had two parts dominated by PW and HL, respectively. The comprehensive de-volatilization index increased from 7.0 × 10-7 to 3.3 × 10-6 %2/(min2·°C3) as PW ratio rose from 20 % to 40 %. Effects of heating rates on pyrolysis properties, kinetics, and thermodynamics were studied using thermal analysis data. Characteristic indices increased, and activation energies decreased with HL or PW mixing; minimum activation energy was 147.2 kJ/mol for PS and HL blend. Blending lignite and biomass improved pyrolysis indices of petrochemical sludge and reduced activation energy and thermodynamic parameters, benefiting sludge disposal.

Prediction of the impact of tobacco waste hydrothermal products on compost microbial growth using hyperspectral imaging combined with machine learning

The insufficient understanding of the impact of hydrothermal products on the growth characteristics of compost microorganisms presents a significant challenge to the broader implementation of hydrothermal coupled composting for tobacco waste. Traditional biochemical detection methods are labor-intensive and time-consuming, highlighting the need for faster and more accurate alternatives. This study investigated the effects of hydrothermal treatment on tobacco straw products and their influence on compost microorganism growth, using hyperspectral imaging (HSI) technology and machine learning algorithms. Sixty-one tobacco straw samples were analyzed with a hyperspectral camera, and image processing was used to extract average spectra from regions of interest (ROI). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied to assess four key variables: nicotine content, total humic acid content, Penicillium chrysogenum H/C ratio, and Bacillus subtilis OD600 ratio. The effects of hydrothermal treatment on compost were classified as promoting, inhibiting, or neutral regarding microbial growth. The Competitive Adaptive Reweighted Sampling (CARS) method identified the most influential wavelengths in the 900-1700 nm spectral range. The Random Forest (RF) model outperformed SVM, KNN, and XGBoost models in predicting microbial growth responses, achieving R c = 0.957, RMSE = 3.584. Key wavelengths were identified at 1096 nm, 1101 nm, 1163 nm, 1335 nm, and 1421 nm. The results indicate that hyperspectral imaging combined with machine learning can accurately predict changes in the chemical composition of tobacco straws and their effects on microbial activity. This method provides an innovative and effective means of improving the resource usage of tobacco straws in composting, enhancing sustainable waste management procedures.

Biochar from Co-Pyrolyzed Municipal Sewage Sludge (MSS): Part 1: Evaluating Types of Co-Substrates and Co-Pyrolysis Conditions

With the increasing production of municipal sewage sludge (MSS) worldwide, the development of efficient and sustainable strategies for its management is crucial. Pyrolysis of MSS offers several benefits, including volume reduction, pathogen elimination, and energy recovery through the production of biochar, syngas, and bio-oil. However, the process can be limited by the composition of the MSS, which can affect the quality of the biochar. Co-pyrolysis has emerged as a promising solution for the sustainable management of MSS, reducing the toxicity of biochar and improving its physical and chemical properties to expand its potential applications. This review discusses the status of MSS as a feedstock for biochar production. It describes the types and properties of various co-substrates grouped according to European biochar certification requirements, including those from forestry and wood processing, agriculture, food processing residues, recycling, anaerobic digestion, and other sources. In addition, the review addresses the optimization of co-pyrolysis conditions, including the type of furnace, mixing ratio of MSS and co-substrate, co-pyrolysis temperature, residence time, heating rate, type of inert gas, and flow rate. This overview shows the potential of different biomass types for the upgrading of MSS biochar and provides a basis for research into new co-substrates. This approach not only mitigates the environmental impact of MSS but also contributes to the wider goal of achieving a circular economy in MSS management.

Investigation of the evolved pyrolytic products and energy potential of Bagasse: experimental, kinetic, thermodynamic and boosted regression trees analysis

This study explored bagasse's energy potential grown using treated industrial wastewater through various analyses, experimental, kinetic, thermodynamic, and machine learning boosted regression tree methods. Thermogravimetry was employed to determine thermal degradation characteristics, varying the heating rate from 10 to 30 °C/min. The primary pyrolysis products from bagasse are H2, CH4, H2O, CO2, and hydrocarbons. Kinetic parameters were estimated using three model-free methods, yielding activation energies of approximately 245.98 kJ mol-1, 247.58 kJ mol-1, and 244.69 kJ mol-1. Thermodynamic parameters demonstrated the feasibility and reactivity of pyrolysis with ΔH ≈ 240.72 kJ mol-1, ΔG ≈ 162.87 kJ mol-1, and ΔS ≈ 165.35 J mol-1 K-1. The distribution of activation energy was analyzed using the multiple distributed activation energy model. Lastly, boosted regression trees predicted thermal degradation successfully, with an R2 of 0.9943. Therefore, bagasse's potential as an eco-friendly alternative to fossil fuels promotes waste utilization and carbon footprint reduction.

Effects of adding steel slag on humification and characteristics of bacterial community during phosphate-amended composting of municipal sludge

This study aimed to investigate the effects of different proportions (0%, 5%, 7.5%, and 10%) of steel slag (SS) on humification and bacterial community characteristics during phosphate-amended composting of municipal sludge. Compared with adding KH2PO4 alone, co-adding SS significantly promoted the temperature, pH, nitrification, and critical enzyme activities (polyphenol oxidase, cellulase, laccase); especially organic matter (OM) degradation rate (25.5%) and humification degree (1.8) were highest in the 5%-SS treatment. Excitation-emission matrix-parallel factor confirmed that co-adding SS could promote the conversion of protein-like substances or microbial by-products into humic-like substances. Furthermore, adding 5%-SS significantly improved the relative abundances of Actinobacteria, Firmicutes and the genes related to carbohydrate and amino acid metabolism, and enhanced the interactions of bacterial community in stability and complexity. The partial least squares path model indicated that OM was the primary factor affecting humification. These results provided a promising strategy to optimize composting of municipal sludge via SS.

Machine learning for municipal sludge recycling by thermochemical conversion towards sustainability

The sustainable disposal of high-moisture municipal sludge (MS) has received increasing attention. Thermochemical conversion technologies can be used to recycle MS into liquid/gas bio-fuel and value-added solid products. In this review, we compared energy recovery potential of common thermochemical technologies (i.e., incineration, pyrolysis, hydrothermal conversion) for MS disposal via statistical methods, which indicated that hydrothermal conversion had a great potential in achieving energy recovery from MS. The application of machine learning (ML) in MS recycling was discussed to decipher complex relationships among MS components, process parameters and physicochemical reactions. Comprehensive ML models should be developed considering successive reaction processes of thermochemical conversion in future studies. Furthermore, challenges and prospects were proposed to improve effectiveness of ML for energizing thermochemical conversion of MS regarding data collection and preprocessing, model optimization and interpretability. This review sheds light on mechanism exploration of MS thermochemical recycling by ML, and provide practical guidance for MS recycling.

Mild and Efficient One-Step Synthesis of Nitrogen-Doped Multistage Porous Carbon for High-Performance Supercapacitors

Biomass-derived carbon materials have broad application prospects in energy storage, but still face problems such as complex synthesis paths and the massive use of corrosive activators. In this study, we proposed a mild and efficient pathway to prepare nitrogen-doped porous carbon material (N-YAC) using one-step pyrolysis with solid K2CO3, tobacco straw, and melamine. The optimized material (N-YAC0.5) was not only enriched with nitrogen, but also exhibited a high specific surface area (2367 m2/g) and a reasonable pore size distribution (46.49% mesopores). When utilized in electrodes, N-YAC0.5 exhibited an excellent capacitance performance (338 F/g at 1 A/g) in the three-electrode system, and benefitted from a high mesopore distribution that maintained a capacitance of 85.2% (288 F/g) at high current densities (20 A/g). Furthermore, the composed symmetric capacitor achieved an energy density of 14.78 Wh/kg at a power density of 400 W/kg. In summary, our work provides a novel and eco-friendly approach for converting biomass into high-performance energy-storage materials.