Basic Oxygen Furnace Research Articles

Utilization of coalmine overburden-furnace slag and fly ash mixed cement-treated subbase/base course material for sustainable flexible pavements: mechanical performance and environmental impact.

The scarcity of conventional aggregates with tremendous growth in highway construction and the indiscriminate dumping of industrial waste materials in precious landfills has become a huge global concern. This study is aimed at utilizing wastes from various industries, including coalmine overburden (OB) dump, basic oxygen furnace (BOF) slag, and fly ash to produce suitable and sustainable cement-treated subbase/base course layers (CBSB/CTB) for flexible pavement construction. Response surface methodology was used to optimize the composition of the blended material considering unconfined compressive strength (UCS) and Poisson's ratio. Results demonstrated that 50% OB dump, 40% slag, 5% fly ash, and 5% cement achieved a 7-day UCS of 4.84MPa and Poisson's ratio of 0.25, in line with IRC:37-2018 guidelines. X-ray diffraction (XRD) and field emission scanning electron microscope (FESEM) analysis confirmed the presence of ettringite crystals, calcium-silicate-hydrate (C-S-H), and calcium-aluminosilicate-hydrate (C-A-S-H) gels which are the source of strength development in the blend. Further, a soaked California bearing ratio (CBR) of 136.08% and flexural strength of 2.06MPa after 7days and 28days of curing, respectively, demonstrates the overall strength of the stabilized waste. Approximately 4% weight loss was observed after wet-dry durability tests, indicating exceptional performance of the optimal blend in inclement weather conditions. Furthermore, the environmental impact of the blended material was studied through a leaching study. Fly ash had a high zinc (Zn) level, while BOF slag showed a rich concentrationof chromium (Cr), manganese (Mn), and iron (Fe) in the acid digestion test. In spite of this, the toxicity characteristics leaching procedure (TCLP) test indicated that the levels of heavy metals that leached from the stabilized material stayed considerably below the permissible limits set forth in Indian Standard, IS:10500 (2012). Finally, cost analysis showed a 51.6% reduction in construction cost with cement-treated industrial wastes instead of granular base/subbase made with conventional aggregates. The study recommends the suitability of the stabilized waste material as an alternate construction material for large-scale field applications, which could encourage the construction of flexible pavements that are environmentally benign, economical, and sustainable.

Soft sensor model for endpoint carbon content and temperature in BOF steelmaking based on just-in-time learning with multilayer structure preservation and sparse information enhancement

Ensuring precise prediction of the endpoint carbon content and temperature is paramount in controlling the endpoint of the basic oxygen furnace (BOF) steelmaking process. However, due to the frequent fluctuations in real-time blowing conditions, the conventional just-in-time learning soft sensor approach encounters challenges in effectively anticipating the blowing endpoint. To address these aforementioned issues, this research introduces a novel approach known as the pattern-oriented multilayer structure preservation and sparse information enhancement model (POMLSP-SIE). This approach involves dynamically generating a dataset with the same distribution based on the characteristics of the query sample pattern. It is combined with a multi-pathway dimension reduction model to preserve multi-view spatial geometry information while reducing data dimension. The low-dimensional embedding serves as dictionaries containing various hierarchical structural characteristics. Significant information within these dictionaries is sparsely represented to amplify its influence during the regression prediction process while diminishing the impact of less relevant information. This refinement aims to rectify the problem of static regression models being weak to adapt to changing working conditions, ultimately enhancing prediction performance. The effectiveness of the proposed method is substantiated through an experimental study utilising real converter steelmaking process data, thereby confirming its practical applicability.

Synergistic Utilization of Basic Oxygen Furnace Slag and Coal Gangue: Modified Slag and Metal Extraction

Synergistic Utilization of Basic Oxygen Furnace Slag and Coal Gangue: Modified Slag and Metal Extraction

Bioleaching of Industrial Metallic Steel Waste by Mixed Cultures of Thermoacidophilic Archaea

Different mixed cultures of extremely thermoacidophilic microorganisms were used for bioleaching of metalliferous industrial dust waste derived from the basic oxygen furnace (BOF) steelmaking process. Such mixed cultures can extract various metals from multi-metallic BOF-dust waste, improving the metal dissolution and bioleaching performance in frames of metal recycling processes to assist circular economies and waste management. The results of the investigation showed that mixed cultures of thermoacidophilic archaea of the order Sulfolobales (Acidianus spp., Sulfolobus spp., and Metallosphaera sedula) during their growth in laboratory glass bioreactors provided a superior bioleaching system to Acidianus manzaensis alone. Depending on the composition of mixed thermoacidophilic cultures, extraction of various metals from BOF-dust could be achieved. Among the three different types of mixed cultures tested, the mixed culture system of A. manzaensis, A. brierleyi, and S. acidocaldarius was most effective for extraction of major elements (Fe, Ca, Zn, Mn, and Al). The mixed culture of A. manzaensis, A. brierleyi, and M. sedula showed high performance for bioleaching of most of the minor elements (Cu, Ni, Pb, Co, Mo, and Sr). The efficient ability of mixed cultures to colonise the mineral matrix of the metal waste product was observed via scanning electron microscopy, while their metal extraction capacities were analysed by inductively coupled plasma mass spectrometry. These investigations will promote the further design of microbial consortia in order to break down the solid matrix and efficiently extract metals from metalliferous waste materials.

Decarbonization pathways analysis and recommendations in the green steel supply chain of a typical steel end user-automotive industry

China's automotive industry, the world's largest producer and consumer, has reached a crucial stage in its transition from rapid expansion to high-quality and low-carbon development. Considering the decarbonization of the whole automotive industry, in addition to reducing the CO2 emissions from fuel supply and exhaust pipes, which account for 65–80 % of the total value chain CO2 emissions, the automotive industry should also accelerate the decarbonization of raw materials, which contribute to 18–22 % of these CO2 emissions. Many automotive manufacturers are collaborating with steel producers on green steel initiatives due to the high CO2 emissions from steel production, the integrated nature of the steel supply chain, and the need for early planning in low-carbon steel production routes transformation. To clarify the carbon emission characteristic of the automotive steel supply chain, this research establishes a mathematical method for calculating cradle-to-gate carbon footprint of automotive steel product based on BF (Blast furnace)-BOF (Basic oxygen furnace), Scrap-EAF (Electric arc furnace), and DRI (Direct reduced iron)-EAF steel production routes. The cradle-to-gate carbon footprints of BF-BOF, Scrap-EAF, and DRI-EAF steel production routes are 1711.84 kgCO2/t-sp (steel product), 916.39 kgCO2/t-sp, and 2738.53 kgCO2/t-sp. A projection of CO2 emissions in automotive steel supply chain from 2020 to 2060 has been investigated, taking into account production structure adjustment, scrap recycling, and low-carbon electricity adoption, as well as the demand for automotive steel products. Projections from 2020 to 2060 indicate that the CO2 emission intensity of the automotive steel supply chain will decrease by 28.25 % by 2030 and 93.99 % by 2060, with total emissions dropping by 28.47 % and 96.92 %, respectively. This research identifies effective decarbonization measures in the automotive steel supply chain, including internal and end-of-life (EOL) steel scrap recycling, which offer significant CO2 emissions reduction without increased costs, demonstrating high cost-effectiveness. In a word, this research provides a technical framework and data foundation for decarbonizing the automotive steel supply chain.

Crystallization behavior of BOF slag during the cooling process towards leaching for CO2 sequestration

This work addresses the crystallization behavior and microstructure feature of the molten basic oxygen furnace (BOF) slag during a slow cooling process. The aim is to provide a reference for the modification of BOF slag for subsequent leaching of Ca as part of CO2 sequestration. Integrated analysis of XRD, SEM-EDS, and thermodynamic calculations suggest a crystallization behavior of BOF slag during the cooling process. RO phases ((Mg, Fe, Mn) O) was the equilibrium phase at a high temperature of around 1600 °C, followed at lower temperatures by the formation of Ca3SiO5 (C3S) and α-Ca2SiO4 (α-C2S). The Ca2Fe2O5 (C2F) phase forms during the latter stages of melt solidification. On the basis of the combined analysis of the leaching test results and crystallographic analysis, a future direction of modification of BOF slag is suggested that enriches Ca into the C2S and hinders the formation of C2F. However, inhibiting the generation of C2F by adjusting the cooling process alone is difficult since its crystallization rate is fast. The phase of C2F was observed in XRD and SEM even if the BOF slag was quenched from 1600 °C. Furthermore, the chemical characterization and morphological evolution of the crystalline phase of molten BOF slag during the slow cooling process was observed.

Performance Assessment of Basic Oxygen Furnace Slag (BOFS) as an Ice-Melting Abrasive Material

Abrasives play a crucial role in surface blasting, especially in cold climates, where snow and ice significantly challenge transportation infrastructure and road safety. The main purpose of this research is to address the critical need for effective and sustainable winter maintenance techniques. This study examined the possibilities of Basic Oxygen Furnace Slag (BOFS) as a substitute (an abrasive substance) for conventional aggregates in ice-melting applications. Thus, this research assessed the physical properties of BOFS, such as absorption capacity, tested at -5°C, and aggregate angularity test, and designed for evaluation of the surface texture, friction, and percentage of fractured faces in uncompacted voids (SSD%) of the aggregates. Moreover, the potential use of a blend of BOFS with de-icing salts, specifically sodium chloride (NaCl) and calcium chloride (CaCl2), was investigated as an effective ice-melting agent. For this purpose, three tests were carried out: the petri dish test according to SHRP H-205.1, the polishing ice melting test using a modified ASTM C 944 (rotational cutter), and the surface temperature measurement test. By assessing the performance of BOFS, our goal was to justify its efficacy, offering a practical alternative for regions experiencing severe winter conditions. Eventually, the findings from this study assert that BOFS can be used for surface blasting, indicating its potential as a substitute for traditional abrasives.

A Robust Static Model of Basic Oxygen Furnace for Analyzing Emerging Steelmaking Scenarios

A robust static model, which incorporates emerging steelmaking scenarios in terms of solid charge mix with the given hot metal in basic oxygen furnace process, is developed. It employs mass and enthalpy balances to comprehend nonequilibrium conditions, considering four key empirical parameters: iron loss, post‐combustion ratio, heat loss, and undissolved lime content in slag, which are fine‐tuned using plant data through a multivariate approach, ensuring the reliability. The model is validated in a basic oxygen furnace (BOF) shop using data from over 4000 heats, achieving a strike rate of ≈77% for input lime prediction within ±1 ton and ≈80% for input oxygen prediction within ±600 Nm3. Model implementation in BOF shop provides valuable guidance to the operators, resulting in the reduction of average oxygen and lime consumption by 139 Nm3 and 652 kg heat−1, respectively. The model also enables the determination of the maximum scrap utilization of ≈16% for 0.8% silicon and ≈14% for 0.6% silicon in hot metal, respectively. The model aids in calculating the maximum tap temperature for varying hot metal silicon and iron ore addition. Overall, the model optimizes primary steelmaking, enhancing efficiency, reducing resource consumption, and offering insights into alternative iron sources like direct reduced iron.

Mathematical Modeling on the Multiphase Flow during Top–Bottom Combined Blowing Basic Oxygen Furnace Steelmaking Process

A 3D mathematical model on the multiphase flow and splashing phenomenon in a 210 t Basic oxygen furnace converter is established. The turbulent multiphase flow of the molten steel, slag, and oxygen is simulated by the combined realizable k−ε model and volume of fluid model. The trajectory of argon bubbles and the interaction between the molten steel and argon is simulated by the two‐way coupled Lagrangian discrete phase model. Effects of the lance height and bottom‐blowing gas flow rate on the multiphase flow and splashing phenomenon are investigated. The results indicated that the cavity depth is decreased from 0.45 to 0.36 m when the lance height increases from 1700 to 2300 mm. The cavity depth is not significantly affected by the bottom‐blowing argon flow rate with the 44 000 m3 h−1 top‐blowing oxygen flow rate and 1700 mm lance height. The increased lance height resulted in a decrease in splashing. When the oxygen lance height increases from 1700 to 2300 mm, the amount of the splashed molten steel decreases from 3774.3 to 1953.0 kg.

Advancing the performance characteristics of rubber asphalt mixtures through the integration of Basic Oxygen Furnace (BOF) slag: A focus on static and dynamic mechanical enhancements.

To investigate the advantageous effects of incorporating industrial solid waste basic oxygen furnace (BOF) slag on the mechanical characteristics of warm-mixed rubber asphalt (WMRA) and hot-mixed rubber asphalt (HMRA) mixture, varying proportions of BOF slag were substituted for limestone coarse aggregates (0%, 25%, 50%, and 75%). Additionally, a 1.5% dosage of Sasobit warm-mixed modifier was introduced to prepare the rubber asphalt. Subsequent to preparation, both static mechanical tests (including Marshall and indirect tensile tests) and dynamic mechanical tests (including dynamic creep and elastic modulus tests) were conducted to evaluate the influence of BOF slag on the mechanical behavior of WMRA and HMRA mixtures across different substitution levels. Following testing, a two-way analysis of variance (ANOVA) was employed to dissect the impact of BOF slag content and Sasobit warm-mixed modifier on the static and dynamic mechanical properties of the rubber asphalt mixtures. The findings reveal that BOF slag exhibits commendable engineering aggregate properties, enabling substantial substitution of coarse aggregates in both HMRA and WMRA mixtures. As the proportion of BOF slag increases, it enhances the resistance of asphalt mixtures to permanent deformation and cracking under static and dynamic loading conditions, while broadening the range of elastic deformation for both WMRA and HMRA mixtures subjected to repeated loading. Moreover, a synergistic enhancement in the resistance of rubber asphalt mixtures to dynamic load-induced deformation is observed when employing both BOF slag and Sasobit warm-mixed modifier. The findings offer valuable insights for enhancing the performance of WMRA and HMRA mixtures, as well as broadening the utilization of BOF slag and waste rubber.

Thermal activation of basic oxygen furnace slag as a heterogeneous catalyst in transesterification: Characterization and catalytic activity studies

The valorization of industrial by-products has garnered significant attention in recent years due to its potential to enhance sustainability and economic efficiency within various sectors. Basic Oxygen Furnace slag (BOF-S), a by-product generated in the steelmaking process characterized by its complex composition, presents an opportunity for waste management and resource recovery. This study investigates the potential of BOF-S as a catalyst in converting waste cooking oil to biodiesel via the transesterification reaction. To improve its efficiency, BOF-S was calcined at 850 °C (BOF-S 850), and 1000 °C (BOF-S 1000), for 5 h. The BOF-S was characterized using XRF, N2 sorption, XRD, TGA-DSC, SEM-EDS and FTIR. The characterization techniques showed that the BOF-S 850 had superior characteristics as a catalyst: rough surface, increased pore size and more active basic sites compared to the BOF-S and the BOF-S 1000 slag samples. The transesterification reaction was conducted at a methanol: oil ratio of 20:1, a catalyst loading of 20 wt %, a reaction time of 12 h, a reaction temperature of 60 °C, and a stirring speed of 750 rpm. The findings established that the BOF-S 850 was the best catalyst, with a 90.77 % biodiesel yield and was able to sustain a maximum of two transesterification cycle runs.

Towards green steel-energy and CO2 assessment of low carbon steelmaking via hydrogen based shaft furnace direct reduction process

Under current stringent climate policies, the iron and steel industry, as a major contributor to industrial CO2 emissions, urgently needs the development of low-carbon metallurgical technologies. This work focuses on the hydrogen-based shaft furnace process, which can utilize green energy to significantly reduce CO2 emissions. This work combines the hydrogen-based shaft furnace CFD model, regression equations, and Aspen Plus model to develop a multi-gas source DR (Direct Reduction) plant model. This combination significantly reduces computation time while maintaining predictive accuracy. The transformation from COG (Coke Oven Gas)-DR to H2-DR plant was studied, showing that the top gas circulation process greatly reduces the net carbon input of the entire DR plant. However, the energy consumption of electrolytic hydrogen production limits the transformation of COG-DR plant to H2-DR plant. The process CO2 emissions depend largely on electrical energy footprint. Under traditional electrical energy footprint, the CO2 emissions of H2-DR-EAF (Electric Arc Furnace) route are about four times those of the COG-DR-EAF route. Only when using green source energy does the H2-DR-EAF route achieve the lowest CO2 emissions among all routes, at 344 kg/tls, which is 79 % lower than that of the BF (Blast Furnace)-BOF (Basic Oxygen Furnace) route.

Microstructure and residual strength properties of engineered geopolymer composites (EGC) subjected to high temperatures

This study investigates the effects of high temperature on the microstructure and residual compressive strength properties of engineered geopolymer composites (EGC). The importance of this study focusses on the performance and durability of EGC, aiming towards sustainable construction practices. The proposed study fills the knowledge gap by the use of steel fibers (SF) as primary reinforcement in EGC, specifically involving a combination of Fly Ash (FA), Basic Oxygen Furnace (BOF) slag, and Iron Ore Tailings (IOT). The residual properties of EGC under high-temperature conditions were assessed by preparing cube specimens (50 mm) involving FA and BOF slag as primary precursors, with IOT as a partial replacement to conventional fine aggregate (M-sand) and brass-coated SF as discrete reinforcement. The specimens were exposed to temperatures up to 1000 °C in a muffle furnace in six different levels: 25, 200, 400, 600, 800, and 1000 °C. Post-exposure, the specimens were ambient cured prior to testing of pore structure distribution, residual strength properties, and microstructural characteristics involving scanning electron microscopy (SEM) analysis. The experimental findings show that, despite various combinations of precursors, IOT and SF, no explosive deterioration or spalling occurred in EGC mixes at any level of exposure. Also, as the exposure temperature increased, the compressive strength decreased while the strain capacity enhanced, denoting an increase in the stiffness of the EGC mixes. Notably, the SF maintained its structural integrity even at 1000 °C, which was consistent with the observed microstructural behavior. This indicates the proposed EGC exhibits excellent resistance to elevated temperatures and enhanced strain-hardening capacity. Overall, this research provides valuable insights into the residual properties and microstructural characteristics of FA: BOF: IOT-based EGC, highlighting its potential as a sustainable and fire-resistant building material. The outcomes contribute significantly to the existing knowledge on EGC and its application in environments exposed to high temperatures.

Incorporating composition into life cycle assessment of steel grades

Steel is a vital material in modern industries due to its versatility and remarkable properties. In a world that is increasingly concerned about the environment, it is necessary to incorporate good practices that help reduce the environmental impact of our economies. An important aspect is evaluating the environmental impact of materials throughout their life cycle. However, calculating this impact using generic databases can be challenging, as they may lack the necessary specificity. To obtain more accurate environmental impact calculations, it is essential to consider the composition of the materials. Each steel grade, for example, can vary in the content of alloying elements, which influences its environmental impact. Therefore, particularising calculations based on compositions is essential for making informed and sustainable material selection decisions. This article presents a calculation methodology to establish a Life Cycle Inventory of steel, emphasising the specific composition and using datasets of steel production in a Basic Oxygen Furnace (BOF) developed by ecoinvent as reference. The methodology presented seeks to allow the systematic calculation of the environmental impact of any steel considering its composition, contribute to the incorporation of environmental criteria in the selection of materials, and quantify the content of critical raw materials according to the latest report published by the European Union. Likewise, a case study is included, in which the composition's influence on the environmental impact of 10 steel grades widely used in induction cooktops has been analysed.

The Application of Converter Sludge and Slag to Produce Ecological Cement Mortars.

The paper presents an analysis of the effective use of a mixture of steel sludge (S1) and slag (S2) from the converter process of steel production for the production of cement mortars. Metallurgical waste used in the research, which is currently deposited in waste landfills and heaps near plants, posing a threat to groundwater (possibility of leaching metal ions present in the waste), was used as a substitute for natural sand in the range of 0-20% by weight of cement (each). The obtained test results and their numerical analysis made it possible to determine the conditions for replacing part of the sand in cement mortars with a mixture of sludge and slag from a basic oxygen furnace (BOF) and to determine the effects of such modification. For the numerical analysis, a full quadratic Response Surface Model (RSM) was utilized for two controlled factors. This model was subsequently optimized through backward stepwise regression, ensuring the inclusion of only statistically significant components and verifying the consistency of residual distribution with the normal distribution (tested via Ryan-Joiner's test, p > 0.1). The designated material models are helpful in designing ecological cement mortars using difficult-to-recycle waste (i.e., sludge and converter slag), which is important for a circular economy. Mortars modified with a mixture of metallurgical waste (up to 20% each) are characterized by a slightly lower consistency, compressive and flexural strength, and water absorption. However, they show a lower decrease in mechanical strength after the freezing-thawing process (frost resistance) compared to control mortars. Mortars modified with metallurgical waste do not have a negative impact on the environment in terms of leaching heavy metal ions. The use of a mixture of sludge and steel slag in the amount of 40% (slag/sludge in a 20/20 ratio) allows you to save 200 kg of sand when producing 1 m3 of cement mortar (cost reduction by approx. EUR 5.1/Mg) and will also reduce the costs of the environmental fee for depositing waste.

Comparison Between Empirical Strategies for Predicting Endpoint Phosphorus Content in BOF Steelmaking Process

Dephosphorization is a reaction of important role in steelmaking process, and the correct adequacy of endpoint phosphorus content would improve the quality and productivity of steel in basic oxygen furnace (BOF) processing. Aiming to meet the required steel specifications and reduce process time, two different empirical strategies were established for predicting the endpoint phosphorus content in BOF steelmaking process: linear regression and neural network. Eight variables that affect the endpoint phosphorus content (selected as output) were determined as the input variables of the models. The performances of predictions were evaluated simultaneously with the sensitivity analysis of the model to variations in the values of its input variables. Sensitivity analysis is essential as it reveals the impact of input variables on results, although it is often neglected due to its complexity and the need for multiple simulations. Integrating sensitivity analysis with prediction techniques allows for identifying key variables and making decisions. Both empirical models are suitable and reliable for decision making in the process and can be used as tools for predicting the endpoint phosphorus content, where the neural network has higher accuracy. The sensitivity analysis showed that the two variables that most affect the response of the empirical models were the percentage of oxygen volume of oxygen blown until the sub-lance in relation to the estimated total volume, and the phosphorus concentration in the sub-lance.

Dynamic Soft Sensor Model for Endpoint Carbon Content and Temperature in BOF Steelmaking Based on Adaptive Feature Matching Variational Autoencoder

The key to endpoint control in basic oxygen furnace (BOF) steelmaking lies in accurately predicting the endpoint carbon content and temperature. However, BOF steelmaking data are complex and change distribution due to variations in raw material batches, process adjustments, and equipment conditions, leading to concept drift and affecting model performance. In order to resolve these problems, this paper proposes a dynamic soft sensor model based on an adaptive feature matching variational autoencoder (VAE-AFM). Firstly, this paper innovatively proposes an adaptive feature matching (AFM) method. This method utilizes the maximum mean discrepancy to calculate the values of the marginal and conditional distributions. Based on the discrepancy between these two values, a dynamic adjustment algorithm is designed to adaptively assign different weights to the two distributions. This approach dynamically and quantitatively evaluates and adjusts the relative importance of different distributions in the domain adaptation process, thereby enhancing the effectiveness of cross-domain data alignment. Secondly, a variational autoencoder (VAE) is employed to process the data, as the VAE model can capture the complex data structures and latent features in the steelmaking process. Finally, the features extracted by the VAE are processed with the adaptive feature matching method, thereby constructing the VAE-AFM dynamic soft sensor model. Experimental studies on actual BOF steelmaking data validate the efficacy of the offered approach, offering a reliable solution to the challenges of high complexity and concept drift in BOF steelmaking data.

A method for high value-added utilization of BOF slag: Towards slag recycling and phosphorus recovery

Basic oxygen furnace (BOF) slag is a bulk solid waste generated in steelmaking process, containing large amounts of valuable components. However, its utilization ratio is not high in China, resulting in serious environmental pollution and resource waste. To realize the high value-added utilization of BOF slag, selective leaching was adopted to separate the P-bearing dicalcium silicate from slag. The leaching ratios of Si and P were much higher than those of Fe and Mn. The oxidized BOF slag exhibited a superior leaching of P. 85.6 % of P and 68.0 % of Si was separated from BOF slag while the leaching ratio of Fe was negligible in the HCl solution at pH 3. Almost all the dicalcium silicate was removed by leaching whereas the dicalcium ferrite remained. The tailing containing 46.1 % Fe2O3 and 32.9 % CaO can be reused as a steelmaking feedstock. The leachate was treated to extract phosphates by chemical precipitation. Approximately 98 % of phosphate ions was precipitated in the leachate when the pH increased to 8. Some silica gel was removed from the precipitate via alkaline wash and a phosphate containing 28.4 % P2O5 was recovered, which could be used as a phosphorus fertilizer. This study provided a method for BOF slag recycling in steelmaking process and phosphorus recovery.

Evaluating the efficacy of biogeochemical cover system in mitigating landfill gas emissions: A large-scale laboratory simulation.

Municipal solid waste (MSW) landfills are a significant source of methane (CH4) emissions in the United States, contributing to global warming. Current landfill gas (LFG) management methods, like the landfill cover system and LFG collection system, do not entirely prevent LFG release. Biocovers have the potential to reduce CH4 emissions through microbial oxidation. However, LFG also contains carbon dioxide (CO2) and trace hydrogen sulfide (H2S) depending on waste composition, temperature, moisture content, and age of waste. An innovative biogeochemical cover (BGCC) was developed to tackle these concerns. This cover comprises a biochar-based biocover layer overlaid with a basic oxygen furnace (BOF) steel slag layer. The biochar-based biocover layer oxidizes CH4 emissions, while the BOF slag layer reduces CO2 and H2S through carbonation and sulfidation reaction mechanisms. The BGCC system's field performance remains unexamined. Therefore, a large-scale tank setup simulating near-field conditions was developed to evaluate the BGCC system's ability to mitigate CH4, CO2, and H2S from LFG simultaneously. Synthetic LFG was passed through the BGCC in five distinct phases, each designed to simulate the varying gas compositions and flux rates typical of MSW landfill. Gas profiles along the depth were monitored during each phase, and gas removal efficiency was measured. After testing, biocover and BOF slag samples were extracted to analyze physico-chemical properties. Batch tests were also conducted on samples extracted from the biocover and BOF slag layers to determine potential CH4 oxidation rates and residual CO2 sequestration capacity. The results showed that the BGCC system's CH4 removal efficiency decreased with higher CH4 flux rates, achieving its highest removal (74.7-79.7%) at moderate influx rates (23.9-25.5g CH4/m2-day) and reducing to its lowest removal (27.4%) at the highest influx rate (57.5g CH4/m2-day). Complete H2S removal occurred during Phase 3 in the biocover layer of BGCC system. CH4 oxidation rates were highest near the upper (277.9µg CH4/g-day) and lowest in the deeper region of the biocover layer. In the tank experiment, CO2 breakthrough occurred after 156days due to drying of the BOF slag layer, with an average residual carbonation capacity of 46 gCO2/kg slag after moisture adjustment. Overall, the BGCC system effectively mitigated LFG emissions, including CH4, CO2, and H2S, at moderate flux rates, showing promise as a comprehensive solution for LFG management.

Attenuation of sound signals in foams for the basic oxygen furnace using physical modelling techniques

Attenuation of sound signals in foams for the basic oxygen furnace using physical modelling techniques