Waste Gas Research Articles

Toward Sustainable Production: Emerging Trends in Iron and Steel Making

AbstractThe iron and steel industry is a significant contributor to greenhouse gas emissions, responsible for about 7–9 % of the total emissions. This paper examines sustainable production methods in the iron and steel industry, focusing on decarbonization strategies and energy integration. It covers a wide range of alternative reductants to replace the conventional use of coal. Moreover, the paper highlights the challenges and opportunities associated with each approach. Additionally, it discusses the design modifications for coal‐based sponge iron plants, aiming to reduce coal consumption and waste gas generation while ensuring economic viability. This study provides a roadmap for transitioning to environmentally friendly, technically feasible, and economically viable iron and steel manufacturing processes.

N2O deconstruction of polycyclooctene to generate carbonyl-functionalized macromonomers

Deconstruction of polyolefins into functionalized macromonomers presents a compelling strategy for polyolefin upcycling by creating macromonomers through dehydrogenation/depolymerization. We show that nitrous oxide (N2O), a greenhouse gas waste product from the production of nylon, mediates the deconstruction of polycyclooctene (PCOE) and generates carbonyl-functionalized macromonomers. Carbonyl incorporation and macromonomer molar mass were well controlled by reaction time, and subsequent hydrogenation readily removed residual carbon-carbon double bonds. We also demonstrated that the reaction could progress efficiently with substrates of moderate levels of unsaturation, closely mimicking partially dehydrogenated polyethylene. Such carbonyl-functionalized macromonomers could serve as feedstock for preparing vitrimers and other functional polymers.

Bimetallic sulfides CuInSe2 adsorbent for rapid elemental mercury uptake from coal-fired flue gas

Abstract Coal-fired power plants use coal as fuel, which will release a lot of mercury in the combustion process, directly threatening the ecological environment of the earth. In this study, a new adsorbent CuInSe2 with an active selenium site was prepared, which can effectively remove Hg0. The flower structure of the adsorbent with uniform distribution of selenium sites was confirmed by SEM characterization. Experimental results demonstrated that the adsorption efficiency was close to 99% at 80 ∼200°C, and the adsorption efficiency remained at a stable level of 92.39% even after continuous exposure for 6 hours. The equilibrium adsorption capacity was 18.64 mg/g. CuInSe2 has excellent resistance to SO2 and NO. In conclusion, CuInSe2 adsorbents possess significant potential for mercury removal, providing a new direction for the remediation of mercury pollution in various industrial waste gases using dual-metal selenide adsorbents.

Thermodynamic analysis of heat pump heating system based on flue gas waste heat recovery

Abstract A lot of waste heat has not been recycled from exhaust gas of gas-fired condensing boilers. By enhancing boiler’s thermal efficiency, condensation latent and heat sensible heat should be deeply utilized. This article uses a heat pump to recover the waste heat from boiler flue gas to improve the heating efficiency of the unit. Taking an example of boiler unit, to illustrate the function of the thermodynamic capability, this article create a new heating system by installing a flue gas condenser and a low-temperature economizer, and a thermodynamic model. The experimental results show that if gas is cooling from 130°C to90°C and coefficient of performance(Cop ) is set by 1.746, by setting a low-temperature economizer, 20.87MW can be obtained from waste heat, which decrease water consumption of desulfurization tower 28.792t / h; due to that the heat pump use the condenser, waste heat can be recovered to 10.10MW and condensed water can be recovered to13.654t / h. When heat network’s return water increases, Cop decreases, but efficiency will increases in network; when outlet water in condenser increases, Cop and network efficiency decrease, but heat pump system increases in efficiency.

Design, optimisation and evaluation of the S-CO2 Brayton cycle for marine low-speed engine flue gas

Five configurations of the S-CO2 Brayton cycle (SCBC) were constructed for flue gas waste heat recovery (WHR) of the marine low-speed engine HHM-6EX340EF on the EBSILON platform using the bench test data to save energy, reduce emissions and the efficient operation of ocean-going vessels. Experimental data from Sandia National Laboratories (SNL) was utilised to validate the accuracy of the model and the effect of Brayton cycle parameters on flue gas WHR for different configurations was analysed. The parameters of the SCRBC (S-CO2 recompression Brayton cycle) were optimised by combining the Neural Network Fitting (NNF) model, Multi-objective optimisation algorithms, and multi-criteria decision-making methods. Finally, the thermodynamic analysis of the low-speed engine was comprehensively evaluated by comparing five configurations of SCSBC (S-CO2 simple Brayton cycle), SCCBC (S-CO2 recuperative Brayton cycle), SCHBC (S-CO2 reheating Brayton cycle), SCIBC (S-CO2 intercooling Brayton cycle), and SCRBC. The optimised SCIBC configuration had the highest net recuperated work of 195.76 kW and the highest Brayton cycle efficiency of 20.13 %. The engine efficiency was improved by 0.82 %, 1.45 %, 1.78 %, 1.86 % and 1.68 %, the BSFC was decreased by 3.20 g/kW·h, 5.56 g/kW·h, 6.82 g/kW·h, 7.04 g/kW·h, and 6.43 g/kW·h, and the output power increased by 86.90 kW, 153.33 kW, 195.76 kW, 189.36 kW, and 178.14 kW, respectively. The maximum exergy loss of the cooler was 162.67 kW with an exergy loss efficiency of 14.54 % in the SCSBC configuration. Optimising the flue gas heat exchanger and cooler will further enhance the efficiency and reduce emissions. Research on the parameter and configuration optimisation of the SCBC for marine low-speed diesel engines can be extended to other low-speed engines.

Obtaining high H2-rich syngas yield and carbon conversion efficiency from biomass gasification: From characterization to process optimization using machine learning with experimental validation

Gasification, among the other thermochemical processes, stands as a promising method for sustainable waste management while generating valuable H2-rich syngas. In the last few years, there has been a significant surge in the adoption of machine learning (ML) techniques for modelling biomass as well as gasification and pyrolysis of waste. The present study unveiled the supremacy of Gaussian Process Regression (GPR) algorithm as compared to other ML models, in predicting syngas yield [Ysyn (Nm3/kg of biomass)] and carbon conversion efficiency[ηCarbon(%)] respectively, with a high prediction accuracy of R2 > 0.9 in both the cases. The necessary datasets were collected from experimental trials, at reaction conditions of temperature (T): 550–1000 °C, air flow rate (AFR): 0.02–0.04 L/min, and reaction time of 2 h, in a two-stage fixed bed reactor, which were identified on the Basis of thermodynamic as well as stoichiometric analysis. Additionally, the models were employed in Bayesian optimization within a weighted multi-objective framework to obtain the optimal operational parameters, focusing on maximizing both yield and conversion simultaneously. Finally, this result was validated experimentally to check the sanctity of the data-driven optimization.

Recent Advances in Superabsorbent Hydrogels Derived from Agro Waste Materials for Sustainable Agriculture: A Review.

Superabsorbent hydrogels made from agro waste materials have the potential to promote sustainable agriculture and environmental sustainability. These hydrogels not only help reduce water consumption and increase crop yields but also contribute to minimizing waste and lowering greenhouse gas emissions. Recent research on superabsorbent hydrogels derived from agro wastes has focused on the preparation of hydrogels based on natural polymers isolated from agro wastes, such as cellulose, hemicellulose, and lignin. This review provides an in-depth examination of hydrogels developed from raw agro waste materials and natural polymers extracted from agro wastes, highlighting that these studies start with raw wastes as the main materials. The utilization strategies for specific types of agro wastes are comprehensively described. This review outlines different methods utilized in the production of these hydrogels, including physical cross-linking techniques such as dissolution-regeneration and freeze-thawing, as well as chemical cross-linking methods involving various cross-linking agents and graft polymerization techniques such as free radical polymerization, microwave-assisted polymerization, and γ radiation graft polymerization. Specifically, this review explores the applications of agro waste-based superabsorbent hydrogels in enhancing soil properties such as water retention and slow-release of fertilizers for sustainable agriculture.

Encounter Barrier Factor Biogas as Renewable Energy

The existence of an anaerobic bioreactor that produces biogas can provide two benefits. First, it can produce sustainable energy. Second, it helps reduce greenhouse gas emissions and waste. Based on these two advantages, obstacles to its implementation must be overcome to realize regional energy security. The research method used is descriptive-quantitative and enriched by descriptive-qualitative by FGD, through in-depth interviews, direct observation of the field, and interviews of related parties. This research is to find the source of the problem for the gap that occurs between the real condition of biogas potential that is utilized and wasted as emissions. Based on the results of this study, there are three main obstacles that need to be optimized. The first is the difficulty of raw materials because most of them are imported. The second challenge is the price difference because the power purchase agreement was calculated before the new law came out. And third, the lack of government support. Based on these three constraints, the optimization strategy carried out is: first, facilitate regulations in the ease of procurement of supporting materials. Second, the government regulates and straightens regulations related to price differences. Third, central and local governments should actively support development by increasing training, education, and capacity building for policymaking and analysis in the field of new and renewable energy.

Sustainable waste-to-hydrogen energy conversion through face mask waste gasification integrated with steam methane reformer and water-gas shift reactor

The burgeoning environmental crisis and the urgent need for sustainable energy solutions underscore the importance of innovative waste-to-energy conversion technologies. This study aims to an efficient utilize of face mask waste for a novel energy system to address waste management and energy production simultaneously by introducing an integrated system comprising a gasifier reactor, steam methane reformer, and water-gas shift reactor, designed to convert face mask waste into a hydrogen-rich syngas. The gasifier reactor initiates the process with a hydrogen flow rate of 2.352 mol/h, which is subsequently enriched to 5.405 mol/h in the steam methane reformer and further to 6.132 mol/h in the water-gas shift reactor, marking a cumulative increase of 160%. Methane content, initially at 2.017 mol/h, is reduced by 38.4% post-reforming and remains stable through the water-gas shift reaction. Carbon monoxide sees a significant reduction from 0.8558 mol/h to 0.1817 mol/h, a decrease of 78.8%. The findings of this study have profound implications for the energy sector, demonstrating the potential of the integrated system to not only mitigate waste but also to produce clean energy efficiently. The substantial increase in hydrogen content across the reactors highlights the system's capability to support the burgeoning hydrogen economy, while the management of carbon oxides aligns with environmental sustainability goals. The value of this study lies in its contribution to the advancement of waste-to-energy technologies and its role in shaping future energy policies and practices.

A machine learning approach to classifying sustainability practices in hotel management

Advancing sustainable efforts in hotels, especially small and medium-sized enterprises (SMEs), is important for addressing environmental and social impacts and promoting long-term viability in the hospitality industry. This paper uses machine learning techniques to classify sustainable practices in SMEs. Analyzing data from Booking.com’s “Travel Sustainable Level” section, which includes 30 sustainability measures across five categories (waste, water, energy and greenhouse gases, nature, and destination and community), this study examines 19 factors affecting hotel sustainability. Non-linear machine learning models identify significant features: performance, star rating, size, group membership, and coastal location. These findings are validated through a model introducing ‘Levels of Commitment to Sustainability, “categorizing hotels based on their adherence to these measures”. Variables were more distinctly differentiated by commitment levels than Booking.com levels. Post-hoc analysis and expert interviews reveal insights into the least adopted sustainability measures and their perceived costs and benefits. This study introduces a novel classification approach for hotel sustainability, providing essential insights for effective sustainable hotel management. It highlights key factors influencing sustainability and emphasizes the significance of these factors for developing targeted strategies. Furthermore, this research contributes to a broader understanding of sustainability in hospitality, demonstrating the applicability of machine learning in evaluating sustainable practices.

Data-driven interpretation, comparison and optimization of hydrogen production from supercritical water gasification of biomass and polymer waste: Applying ensemble and differential evolution in machine learning algorithms

Supercritical water gasification (SCWG) has been utilized for producing hydrogen from organic wastes, which is associated with sustainable development. Nevertheless, identifying the optimal SCWG conditions and appropriate catalysts for diverse waste materials to yield hydrogen-rich syngas is consistently a laborious and costly endeavor. The current research presents a comprehensive framework that combines machine learning models (Decision Tree, Ensembled Learning Tree, Support Vector Machine, and Gradient Boost Regression) with Differential Evolution Optimization (DEO) to predict and optimize hydrogen production from Supercritical Water Gasification (SCWG) using 24 different biomass characteristics and process parameters.The findings indicate that ELA-DEO emerges as the preferred method for forecasting hydrogen yield (R2test = 0.95, RMSETest = 0.091), demonstrating its effectiveness in handling intricate variable-target relationships. Conversely, Support Vector Machine (SVM) displayed weaker performance with an R2Test of 0.73 and RMSETest of 0.116. In the SHAP feature importance analysis, temperature, catalyst amount, catalyst type, hydrogen and oxygen were highlighted as important parameters affecting the process. In addition, by fine-tuning the machine learning hyperparameters, the DEO optimization method was used to maximize the production of H2. The optimized ELA-DEO model was used to identify the ideal features and conditions applicable to our experimental setup. Based on these findings, a recommended biomass table was finally formulated, which was validated by the ELA-DEO model. According to our laboratory results, Dunaliella salina produced 12 mmol of hydrogen with a 35% selectivity. Black liquor with 3% (wt) wood has the capacity to produce 17.21 mmol of hydrogen. Also, when crude glycerol was reacted with RuCl3, 18.7 mmol of hydrogen were generated. However, Dunaliella salina produced a 64% mole fraction of total gas output, which matched the maximum value predicted by our ELA-DEO models.

Material Flow Analysis-Based Sustainability Assessment for Circular Economy Scenarios of Urban Building Stock of Vienna

Urban buildings consume raw material and energy, and they produce waste and greenhouse gasses. Sustainable urban development strategies aim to reduce these. Using the case study of buildings in Vienna, this article evaluates the impact of a defined urban development pathway on the heating energy demand, greenhouse gas emissions, and total material requirement of buildings in Vienna for 2021–2050. Furthermore, the impact of recycling to reduce the total material requirement and to increase the circular material use rate is evaluated. The results show that the heating energy demand can be reduced to meet the targets of Vienna’s sustainable development strategy. The same does not count for greenhouse gas emissions. To meet the targets for the latter, the renovation of old buildings by thermal insulation should be expanded and heating systems substituted. With respect to the total material requirement, the recycling of demolition waste from buildings in Vienna to produce secondary raw materials for buildings in Vienna can help to achieve the reduction targets of Vienna’s sustainable development strategy so that in the year 2050, the material footprint is only 44% of the value of the year 2019. Since there is a contradiction between the total material requirement and the circular material use rate, the latter has to be discussed for its use as a circular economy indicator, since the aim of circular economy is not to produce as much recycling materials as possible, but to reduce resource consumption to a sustainable level.

Experimental study on heat storage characteristics of an air-sand moving bed heat exchanger

The air-sand moving bed heat exchanger, designed for storing fluctuating medium-temperature gas waste heat, offers significant potential for energy conservation and carbon reduction in industrial settings. However, its operational characteristics are insufficiently explored. This study investigates the heat storage process involving direct contact and cross-flow of air and quartz sand within a rectangular heat exchanger chamber. Comprehensive analyses were conducted to explore flow resistance characteristics, temperature response, and heat storage performance. Results indicate that pressure drop increases with higher air velocity and temperature, and lower air pressure, particle diameter. The relative discrepancy between fitted pressure drops and experimental data is below 10%. The primary heat transfer zone exists during particle descent. As the air-particle mass flow ratio increases, the descent rate of this zone along the airflow direction slows. Additionally, higher air temperatures elevate the optimal air-particle mass flow ratio. With inlet temperatures for air and particles set at 350 °C and 30 °C respectively, and a mass flow ratio of 0.81, an exergy efficiency of 58.93% and a power density of 600.64 kW·m−3 are achieved. These findings offer crucial insights for air-sand moving bed heat exchangers for medium-temperature gas waste heat recovery.

Modeling & experimental studies on enhancement of H2S conversion using catalytic membrane reactor for hydrogen production

Abstract Acidic gases such as H2S and CO2 are generated in the refineries during coal gasification. These pollutant gases need to be treated before releasing to the atmosphere. Conventionally, H2S gas is treated by Claus process in which H2S is converted to elemental S and H2O, in presence of O2 at ∼1,200 K. In the present energy scenarios, hydrogen has got importance as a source of clean fuel for industrial application. The H2S generated in the refineries can be a potential precursor of hydrogen. If this hydrogen can be obtained by thermal decomposition of H2S, that can increase the overall economic value of the H2S containing streams and the produced hydrogen can be used for hydrocracking and hydro-treating in refineries, as well as to synthesize value-added products for chemical industries. However, H2S thermal decomposition is an endothermic and equilibrium limited reaction (equilibrium conversion is only ∼15 % at 1,000 K), requiring a very high temperature (∼1,500 K) to achieve even a conversion of greater than 40 %. Packed Bed Catalytic Membrane Reactor (PBCMR) for thermal decomposition of H2S can be a potential technology augmentation and process intensification to increase this equilibrium conversion. In this work, modeling and experimental studies of H2S thermal decomposition using in-house designed & developed PBCMR have been carried out. The modeling studies were validated with experimental data. Clay-alumina ceramic tubular membrane (L: 250 mm; OD: 12 mm; thickness: 2 mm) was fabricated using extrusion process having an average membrane pore size of ∼1 μm and with a porosity of ∼20 %. Pt (2 %) coated alumina extrudes were used as catalyst to accelerate the reaction kinetics. Experimental studies showed that H2S to hydrogen conversion of ∼90 % is achieved using PBCMR at ∼1,523 K, compared to only ∼40 % conversion in a conventional packed bed tubular reactor (without membrane). Modelling studies were carried out to study the influence of operating parameters such as, reactor wall temperature, feed temperature, pressure and feed velocity. Studies showed that reactor wall temperature is having the most dominant effect on H2S conversion, which is confirmed by experimental findings. The studies offer useful insights into the application of PBCMR technology for management of waste gas stream containing H2S and recovery of hydrogen.

Assessing the impact of green patents on pollution reduction: A micro-level study of Chinese industrial firms

As global warming and environmental degradation escalate, policymakers worldwide increasingly advocate for the development of green patents. However, there is ongoing debate regarding the effectiveness of green patents in actual pollution reduction. Some studies suggest that firms may engage in green patenting activities to align with government and market expectations rather than achieving substantive breakthroughs in pollution reduction. In light of this, it is crucial to examine the impact of green patents on pollution reduction. This study employs a PSM-DID model to analyze the impact of green patents on pollution emission intensity using plant-level data from Chinese industrial firms. The results demonstrate that with an average increase of 1% in the number of green patents, the industrial waste gas emission intensity and industrial wastewater discharge intensity decreased by 4.74% and 8.68%, respectively. Furthermore, pollution treatment facilities were found to be more effective than green patents during the sample period. On average, the contribution of waste gas treatment facilities and wastewater treatment facilities in pollution reduction is 3.33% and 9.79% higher than that of green patents. These findings suggest that firms should adopt a balanced approach when making decisions on pollution reduction. Further analysis shows that the pollution reduction effect of green patents is partly at the expense of the total factor productivity of firms. This trade-off highlights the need for policy interventions to support firms in integrating green technologies without compromising productivity. This study underscores the emphasizes of transitioning from end-of-pipe pollution control to green production processes to achieve sustainable development in China.

The “6th R” of sustainability: Repurposing operating room waste for community benefit

BackgroundOperating rooms contribute greatly to hospital waste and greenhouse gas production. Efforts to “green the operating room” have focused on the 5R's of sustainability: reduce, reuse, recycle, rethink, and research. We propose a “6th R” —repurposing— as simple yet effective means of addressing operating room waste. MethodsClean, non-reusable surgical supplies were collected from a satellite facility of a children's hospital during a six-week pilot program. Materials were catalogued and repurposed throughout the community. The potential financial benefits were estimated based upon the value of repurposed goods and savings from reduced waste disposal. ResultsOver 960 items were collected during the 6-week pilot. Materials ranging from plastic trays to surgical towels were donated to organizations throughout the community. Approximate retail value of repurposed items was over $1200. When extrapolated to the entire hospital system, these repurposing efforts could account for over $50,000 in donations and $1300 in operational savings over a calendar year. ConclusionsRepurposing unused surgical items provide environmental, societal, and financial benefits, all while promoting more sustainable healthcare systems.

Introduction, Types, Properties, and Applications of Switchable Solvents: A Review

AbstractSwitchable solvents (SS) are a class of liquids with the unique ability to significantly alter their physical properties in response to external stimuli such as changes in temperature or the introduction or removal of CO2 gas. This reversible behaviour allows them to return to their original state with minimal changes, making them highly advantageous for various applications. A notable example of a switchable solvent is waste carbon dioxide gas, which is non‐toxic, non‐flammable, and cost‐effective. The versatility of switchable solvents extends to their polarity and physical states, which can be modified through molecular adjustments, opening new pathways for research and industrial applications. This review provides a comprehensive overview of switchable solvents, including their classification, history, properties, and applications, with a particular focus on their role in green chemistry. The types of switchable solvents discussed include Switchable‐Polarity Solvents (SPS), Switchable‐Hydrophilicity Solvents (SHS), and Switchable Water. Each type is examined in terms of synthesis, chemical properties, and development. The desirable properties of switchable solvents, such as their efficiency and recyclability, make them suitable alternatives to traditional solvents in various fields. Their applications range from water treatment and oil extraction to cleaning solid particles and recovering residual motor oil. Additionally, switchable solvents have proven effective as reaction media and in recovering polystyrene from foam. This paper also highlights the environmental benefits of switchable solvents, emphasizing their role in reducing the ecological impact of chemical processes. The potential for future developments in this field is significant, with ongoing research aimed at enhancing their performance and expanding their applications. By providing a detailed analysis of switchable solvents, this review aims to support researchers and industry professionals in developing more sustainable and efficient chemical processes.

Impact of Cu content on the activity of TiO2-based catalysts for toluene oxidation

Toluene is one of the most toxic contaminants in industrial waste gases, it can enter the body through the respiratory system and skin. Long-term exposure to it can lead to skin inflammation and neurasthenia, and even cause lesions in organs. Over the years, catalytic oxidation technology has been extensively employed to the remove of toluene, and oxides, especially copper oxide, is considered to be an effective catalyst technology and has been extensively studied. In this work, we introduced CuO as an active species to investigate the impact of Cu content in TiO2@CuO (TC-x, x=1, 2, 3, and 5) catalyst on the activity, reusability, and stability of toluene oxidation. The result demonstrated that the addition of Cu species, facilitating the generation of active oxygen obviously reduced the complete oxidation temperature of toluene. Among them, TC-3 catalyst exhibited the highest activity (T50 = 234 ℃, T90 = 289 ℃, and T100 = 310 ℃, with Ctoluene=1000 ppm, WHSV=20,000 mL/ (g h)), great reusability, and stability for toluene degradation. According to the in-situ DRIFTS, the ultimate degradation products of toluene were CO2 and H2O, which were clean and free of secondary pollution.

Can Turkey Be A Hub For Closed-Loop Systems In the Textile Industry for the EU?

The global textile industry, valued at $414 million, confronts substantial environmental challenges, contributing to waste, pollution, and greenhouse gases. This paper examines Turkey's potential to drive sustainability in textiles, exploring circular systems that minimize waste and promote eco-friendly practices. The paper consists of seven parts. After introduction, in the second part the importance of sustainability and circularity in textile industry is explained. Third part examines the Turkey as a major textile player, and the challenges of textile recycling industry. Overwhelming obstacles like insufficient recycling infrastructure require industry initiatives, government regulations, and technological innovations. Following parts explains the main limitations of the textile recycling in EU and questions if Turkey, with its production capabilities and recycling expertise, could be a key ally for EU to solve the obstacles of current textile recycling challenges. Recommendation and Conclusion parts offer a road map for Turkey to enhance its capabilities to become a key ally for EU, exemplifying a transformative shift towards a sustainable textile industry.

Optimization of hydrogen-rich syngas from coal and sewage sludge co-gasification in supercritical water

Supercritical water gasification (SCWG) of coal and biomass waste complies with the structure of energy consumption and the targets for carbon peaking and carbon neutrality. In this work, the optimal blending ratio and thermochemical transformation characteristics of coal and sewage sludge (SS) co-gasification were explored experimentally at various temperatures (500–660 °C), residence time (0–40 min), feedstock concentrations (5–15 %), and catalyst utilization. The demethylation and dehydroxylation of intermediate products (aliphatic compounds, monocyclic aromatic hydrocarbons (MAHs)) improve the gasification performance under favorable experiment conditions (high temperature, long residence time, low feedstock concentration, and addition of catalysts). The optimal gasification results are an H2 yield of 38.36 mol/Kg and a 118.81 % increase of CGE (cold gas efficiency) in K2CO3-catalyzed gasification compared to the absence of the catalyst. Subsequently, the co-gasification mechanism of coal and SS was determined by the analysis of the three-phase product. Ultimately, a regression model was first established to obtain the practical optimization mechanism and yield prediction of hydrogen-rich syngas through response surface plots and regression equations. As verified in multiple experiments under varying situations, the regression model’s fitting accuracy yields an average relative error of 5.53 %.