Scrap Research Articles

Scrap Steel Recycling: A Carbon Emission Reduction Index for China

Accurately assessing carbon emissions from recycling scrap steel is essential for reducing emissions in the steel industry, especially in China, the world’s largest crude steel producer. In this study, a carbon emission reduction index was introduced to evaluate the effectiveness of recycling scrap steel in reducing emissions. The index considers the three processes used in scrap steel recycling: blast furnace ironmaking, converter steelmaking, and electric arc furnace steelmaking. This study developed an evaluation model using fuzzy analytic hierarchy process and iterative cluster analysis to determine the reduction of carbon emission. From a life cycle perspective, this study identified primary factors contributing to emissions, including fuel, raw materials, electric energy, and auxiliary materials. Then, the carbon emission reduction index for scrap recycling was developed by examining the production of one ton of steel and each additional ton of scrap steel, which can provide valuable insights into the environmental impact of scrap recycling. Finally, the study forecasts the future Carbon Emission Reduction Index for steel scrap recycling. The study indicates an increase in the carbon emission reduction index for scrap recycling prior to 2017, followed by a decrease about 11.8% from 2017 to 2018 and increases from 2018 to 2021. Finally, it dropped by 8.7% per cent in 2022. Similarly, the carbon emission reduction index for electric furnace steelmaking increased prior to 2019, then subsequently decreased. It is changing by ten per cent a year. Additionally, the scrap recycling index experienced a significant decrease of 90% in 2015, followed by a gradual increase until 2017 and then a consistent decrease every year thereafter. The index suddenly rose in 2021 and then decreased change for policy reasons. The forecast results suggest a gradual increase in the carbon emission reduction index per ton of steel scrap in the future. In conclusion, the practicable modeling methodology has the ability to assist government organizations and private enterprises in devising efficient green and low-carbon development tactics.

Evaluating the Effects of Metallic Waste on the Structural and Gamma-Ray Shielding Properties of Epoxy Composites.

The objective of the research is to develop novel materials that are both inexpensive and have a low density, while also being able to endure the transportation of γ-photons with low-to-medium energy levels. The outcome consisted of four epoxy resins that were strengthened with different quantities of heavy metallic waste. The density of the formed composites improved from 1.134 ± 0.022 g/cm3 to 1.560 ± 0.0312 g/cm3 when the waste content was raised from 0 to 40 weight percent. The theoretical investigation was determined using Monte Carlo (MCNP) simulation software, and the results of linear attenuation coefficient were justified experimentally in a low and medium energy range of 15-662 keV. The mass attenuation coefficient results in a low gamma energy range (15-122 keV) varied in between 3.175 and 0.159 cm2/g (for E-MW0 composite) and in between 8.212 and 0.164 cm2/g (for E-MW40 composite). The decrease in mass attenuation coefficient was detected in a medium gamma photon energy range (122-662 keV) with 0.123-0.082 cm2/g (for E-MW0 composite) and 0.121-0.080 cm2/g (for E-MW40 composite). The density of the enhanced composites influenced these parameters. As the metallic waste composition increased, the fabricated composites' half-value thickness decreased. At 15 keV, the half-value thickness decreased from 0.19 to 0.05 cm. At 59 keV, it fell from 2.70 to 1.41 cm. At 122 keV, it fell from 3.90 to 2.72 cm. At 662 keV, it fell from 7.45 to 5.56 cm. This decrease occurred as the heavy metal waste concentration increased from 0 to 40 wt.%. The study indicates that as metallic waste concentrations rise, there is a rise in the effective atomic number and a decline in the buildup factors.

Analysis of the melting process of carbon-bearing pellets in iron bath, slag bath and graphite crucible

Background With the increase in the amount of scrap steel in society, the proportion of electric furnace steelmaking is increasing year by year, especially in China. Due to the high Zn content, the electric furnace arc dust (EAFD) needs to be recovered by non-blast furnace process. Due to EAFD containing a large amount of zinc ferrite, it needs to be recovered by fire process. It is a promising process to melt the EAFD pellets to get the discount and zinc-rich secondary ash. Methods To clarify the melting behavior of pellets in the metallurgical process, the slag phase diagram and the effect of temperature and FeO on slag viscosity were calculated using FactSage, and the melting process of electric furnace arc dust (EAFD) pellets in a graphite crucible, iron bath, and slag bath were experimentally investigated. Results The experimental results show that the viscosity of the slag system decreases with increasing temperature and FeO content, and the effect of FeO on viscosity is greater. The viscosity decreased from 0.305 to 0.276 Pa·s when the FeO content in the slag was increased from 0 wt. % to 2 wt.% at 1773 K. The melting process of the EAFD pellets in an iron bath and graphite crucible was consistent, and after the formation of liquid-phase slag in the pellets, the liquid-phase slag was diffused to melt the pellets. Conclusions The iron bath improved the heat transfer conditions of the pellets, reducing the smelting time from 600 to 360 s. The slag bath promoted the slagging reaction of the contact part to change the pellet melting process and increase the pellet melting speed, and the EAFD pellets melted within 240 s in a slag bath.

GARBAGE COLLECTOR USING ARDUINO

The amount of Solid waste that is being produced through our everyday activities is huge and is getting unmanageable day by day. This is mainly due to increasing population leading to haphazard dumping and increasing transportation costs with already few cost-effective methods to treat the solid waste. According to an estimate in 2016, 277 million tons of solid waste is produced by India every year. It is also projected to increase to 387 million tons by 2030 and 543 million tons by 2050. The very first method involved in the Solid Waste Management is sorting of waste which simplifies the further procedure as to what to do with the waste i.e., should it be treated thermally, biologically or dumped. Improper segregation of solid waste and segregation at secondary levels of waste management is only going to delay the waste management process and sometimes even lead to inappropriate dumping. This project suggests a way to deal with segregation process so as to make the whole solid waste management easier and more efficient. Automatic Waste Segregation system provides a practical segregation process of solid waste into metal waste, dry waste and wet waste at the primary level right where the waste is being generated. An Automatic Waste Segregator with simpler mechanism than that of previous models is designed and a detailed methodology of the working of the segregation process is provided. Selection of the required equipment has been mentioned. This project aims at segregating the waste produced at the primary level and reducing the burden at secondary levels and cost of transportation of the waste. The results obtained after testing the Automatic Waste Segregator with wastes proved to be functional and can be comfortably relied upon to segregate the wastes.

Speciation of toxic metals in metal finishing filter cake by X-ray absorption spectroscopy

The speciation of Cr, Zn, Cu and Pb in two metal finishing filter cakes (TX and ST) was investigated by X-ray absorption spectroscopy (XAS) complemented by X-ray fluorescence (XRF) and X-ray diffraction (XRD). XRF showed that concentrations of Cr, Zn, Cu and Pb were 1.4%, 0.19%, 0.20% and 0.01%, respectively, in TX, and 12.6%, 3.3%, 1.3% and 0.21% in ST. No crystalline phases were detected in TX by XRD whereas ST was dominated by calcite. Cr and Fe K edge XAS showed Cr to be trivalent and octahedrally coordinated, co-precipitated with Fe as CrxFe1-x-(oxy)hydroxides in both filter cakes. Zn, P and Ca K edge XAS showed that 2ZnCO3∙3Zn(OH)2 and Zn3(PO4)2 were the dominant zinc-containing phases, with combined tetrahedral and octahedral coordination; Zn phases were slightly more crystalline in TX than ST. Pb L3 edge X-ray absorption near edge spectroscopy (XANES) found that Pb was likely adsorbed on amorphous SiO2. Cu, Si and S K edge XAS showed that all Cu was divalent, and the dominant copper phases were found to be Cu2Cl(OH)3, Cu(OH)2 and CuSO4·5H2O for ST, whereas Cu appeared to adsorb to amorphous SiO2 for TX, which contained much less Pb. Cr is thus immobilized in the filter cakes in a phase with low solubility at environmentally feasible pH values, whereas Zn, Cu and Pb could be released when the pH decreases below 8 or above 11. These findings are significant for the development of waste management regulations and/or metal recovery methods (e.g., hydro/pyrometallurgy).

Evaluation of asphalt film thickness and heavy metal leaching of oxidizing slag used as an aggregate material in dense-graded asphalt concrete.

Electric-arc-furnace (EAF) steelmaking uses scrap iron and steel as raw materials. Scrap iron and steel originate from complex sources and may contain heavy metal components which can leach into the environment over time due to wear-and-tear. A by-product of the EAF steelmaking process is oxidizing slag, and approximately 1.2 million metric tons is produced every year in Taiwan alone. This study investigated substitution of natural aggregates with oxidizing slag in dense-graded asphalt concrete. We evaluated the water resistance and asphalt film thickness of the oxidizing slag substituted asphalt concrete and further explored the performance of oxidizing slag as paving material. We determined the dissolved and total amounts of heavy metals in the oxidizing slag, comparing these results with current regulatory controls to assess the environmental compatibility of the oxidizing slag. We found that due to the complicated sources of oxidizing slag, the basic properties should be analyzed on a batch-to-batch basis. Furthermore, we recommend trial mixing before upscaling the production of oxidizing slag substituted dense-graded asphalt concrete to confirm the mixing time required to achieve uniformity. The results also show that in comparison to natural aggregates used in asphalt concrete, oxidizing slag exhibits superior performance in terms of increased asphalt film thickness and improved water resistance. Furthermore, oxidizing slag as an aggregate material was associated with decreased heavy metal leaching and reduced environmental pollution. The results of the toxicity characteristic leaching procedure (TCLP) met regulatory requirements. However, the microwave-assisted aqua-regia digestion procedure showed heavy metal concentrations exceeding the monitoring standards for food crops. Considering environmental compatibility, it is recommended that controlling the total amount of heavy metals in oxidizing slag should be included in regulatory requirements. Furthermore, we should prohibit the use of materials such as oxidizing slag and other steel furnace slag in the roadways adjacent to edible crop farmlands.

Effect of activator type and Pozzocrete waste on the mechanical and microstructural properties of eco-friendly geopolymer incorporating electric arc furnace slag

ABSTRACT The precursor type and activator are two primary factors that significantly affect the properties of geopolymers. Most of the previous studies used byproduct materials such as fly ash (FA) and slag as geopolymer precursors, while too limited studies used electric arc furnace slag (EAFS) for this purpose. The EAFS is a type of steel slag, which can be produced when scrap steel is melted. The preliminary usage of EAFS as a precursor in the geopolymer system has not been sufficiently highlighted. To make this come true, the current procedure employed EAFS as a precursor material for the geopolymeric system. Due to superior properties, EAFS was partially replaced with 10–50 wt% pozzocrete (Pz). Two different types of alkaline activators, NaOH and Na2CO3, were used to activate EAFS slurries supported by Pz. The results indicated that the optimal ratio of Pz to be replaced by EAFS to achieve the target properties varies according to the type of activator. The inclusion of 10% Pz exhibited maximum compressive strength when Na2CO3 was used, whilst 50% Pz exhibited maximum compressive strength when NaOH was used. The coexistence between N-A-S-H from Pz and C-(A)-S-H gel from EAFS is the main reason for the enhanced strength.

Matrix effect correction in active neutron interrogation for residual fissile mass assessment in radioactive waste drums

Metallic waste in the form of shells and nozzles remains following the reprocessing of spent fuel at La Hague plant (France). Before the final disposal, drums containing the waste are transported to the compaction facility where its volume is reduced by a factor of 5. With the objective of controlling the criticality/safety levels, an active neutron interrogation system at the entrance of the facility is used to assess the residual fissile mass remaining in the waste, which relies on prompt fission neutron detection (known as the differential die-away technique, DDA). The measured signal is proportionally linked to the fissile mass by a calibration coefficient. However, two effects can produce an inaccurate prediction. The number of induced fissions for the same fissile mass varies according to the waste matrix composition, particularly the neutron slow-down and absorption ratio. Secondly, the presence of fissile clusters can impact the neutron interrogation due to an increase in self-shielding effect. This work presents a matrix effect correction method based on the use of internal flux monitors (sensitive to the neutron absorption ratio) and the transmission signal (sensitive to the slow-down ratio). It relies on a numerical model of the whole measurement cell developed with the Monte-Carlo N-Particle transport (MCNP) code. The calibration coefficient of 72 different matrices, representative of the waste produced at La Hague, were simulated and a statistical model using a multilinear regression was then established. This simulated-based approach provides a more robust and comprehensive estimation of the residual fissile mass without impacting accuracy thanks to the flux monitors and the transmission signals.

Exploring the Aesthetic and Functional Aspects of Recycled Furniture in Promoting Sustainable Development: An Applied Approach for Interior Design Students

This study aimed to explore the sustainable aesthetic and functional dimensions of environmental waste in the context of interior design applications by students. Employing both descriptive and applied methodologies, a series of artistic works derived from environmental waste, specifically metal and wood, were conceptualized and executed by art education students. These works, totaling 11 artistic models in interior design, underwent chemical treatment as part of the process. An evaluation card, assessed by arbitrators, was utilized to gauge the standards of aesthetic and functional sustainability inherent in the artworks. Technical data were collected and subsequently analyzed using SPSS software, which facilitated the calculation of arithmetic averages, standard deviations, and t-tests to ascertain the extent to which sustainability standards were met within the aesthetic and functional dimensions of the works. The study findings indicated that the average response scores for the aesthetic and functional dimensions, pertaining to the achievement of sustainability for wood and metal waste, were notably high. This underscores the potential of producing artful works suitable for interior design applications within the spaces of the College of Education. With an average score of 3.984, students exhibited positive engagement with the aesthetic and functional aspects of their artistic products, indicative of their considerable ethical significance. This augurs well for the feasibility of attaining sustainability through the recycling of wood and metal waste. Furthermore, this research underscores the necessity of integrating aesthetic, environmental, and social values in achieving sustainable aesthetic and functional environmental values within the interior design curriculum. This integration demands a comprehensive understanding of user expectations, technological advancements, and the cultural background, customs, and traditions of both users and society at large.

Multi-class waste segregation using computer vision and robotic arm

Waste segregation is an essential aspect of a smoothly functioning waste management system. Usually, various recyclable waste types are disposed of together at the source, and this brings in the necessity to segregate them into their categories. Dry waste needs to be separated into its own categories to ensure that the proper procedures are implemented to treat and process it, which leads to an overall increased recycling rate and reduced landfill impact. Paper, plastics, metals, and glass are just a few examples of the many dry waste materials that can be recycled or recovered to create new goods or energy. Over the past years, much research has been conducted to devise effective and productive ways to achieve proper segregation for the waste that is being produced at an ever-increasing rate. This article introduces a multi-class garbage segregation system employing the YOLOv5 object detection model. Our final prototype demonstrates the capability of classifying dry waste categories and segregating them into their respective bins using a 3D-printed robotic arm. Within our controlled test environment, the system correctly segregated waste classes, mainly paper, plastic, metal, and glass, eight out of 10 times successfully. By integrating the principles of artificial intelligence and robotics, our approach simplifies and optimizes the traditional waste segregation process.

Classification of e-waste using machine learning-assisted laser-induced breakdown spectroscopy.

Waste management and the economy are intertwined in various ways. Adopting sustainable waste management techniques can contribute to economic growth and resource conservation. Artificial intelligence (AI)-based classification is very crucial for rapid and contactless classification of metals in electronic waste (e-waste) management. In the present research work, five types of aluminium alloys, because of their extensive use in structural, electrical and thermotechnical functions in the electronics industry, were taken. Laser-induced breakdown spectroscopy (LIBS), a spectral identifier technique, was employed in conjunction with machine learning (ML) classification models of AI. Principal component analysis (PCA), an unsupervised ML classifier, was found incapable to differentiate LIBS data of alloys. Supervised ML classifier was then trained (for 10-fold cross-validation) on randomly selected 80% and tested on 20% spectral data of each alloy to assess classification capacity of each. In most of the tested variants of K nearest neighbour (kNN) the resulting accuracy was lower than 30% but kNN ensembled with random subspace method showed improved accuracy up to 98%. This study revealed that an AI-based LIBS system can classify e-waste alloys rather effectively in a non-contactless mode and could potentially be connected with robotic systems, hence, minimizing manual labour.

Extremophiles and their expanding biotechnological applications.

Microbial life is not restricted to any particular setting. Over the past several decades, it has been evident that microbial populations can exist in a wide range of environments, including those with extremes in temperature, pressure, salinity, and pH. Bacteria and Archaea are the two most reported types of microbes that can sustain in extreme environments, such as hot springs, ice caves, acid drainage, and salt marshes. Some can even grow in toxic waste, organic solvents, and heavy metals. These microbes are called extremophiles. There exist certain microorganisms that are found capable of thriving in two or more extreme physiological conditions simultaneously, and are regarded as polyextremophiles. Extremophiles possess several physiological and molecular adaptations including production of extremolytes, ice nucleating proteins, pigments, extremozymes and exopolysaccharides. These metabolites are used in many biotechnological industries for making biofuels, developing new medicines, food additives, cryoprotective agents etc. Further, the study of extremophiles holds great significance in astrobiology. The current review summarizes the diversity of microorganisms inhabiting challenging environments and the biotechnological and therapeutic applications of the active metabolites obtained as a response to stress conditions. Bioprospection of extremophiles provides a progressive direction with significant enhancement in economy. Moreover, the introduction to omics approach including whole genome sequencing, single cell genomics, proteomics, metagenomics etc., has made it possible to find many unique microbial communities that could be otherwise difficult to cultivate using traditional methods. These findings might be capable enough to state that discovery of extremophiles can bring evolution to biotechnology.

Artikel Review: “Kondisi Terkini Kualitas Air Sungai Di Daerah Istimewa Yogyakarta”

Domestic waste and heavy metals are common problems found in river water. Household activities around the river contribute domestic waste to the river. Also, due to industrial activities in the last few centuries caused heavy metal pollution. This article discusses the quality of Bogowonto, Winongo, Code, Gajah Wong, Opak, Belik and Bedog rivers for the analysis of domestic waste parameter values, while the heavy metal content for Bogowonto and Code river was excluded. The analysis method is purposive sampling and composite sample. The rescent research result on the observation of various parameters showed a fairly high waste content for domestic waste with BOD (Biochemical Oxygen Demand) parameters,while the highest pollution content for heavy metal waste is lead and iron.

Utilization and Experimental Use of Stainless Steel Metal Scrap Machinery Waste, St-40 Iron, Copper and Aluminum to Reduce Co, Hc, Co2 Elements in Vehicle Exhaust

Air pollution due to motor vehicle exhaust emissions is increased. Polluted air harms human health dan the environment. Consequently, it is essential to make a sustained effort to reduce air pollution. The purpose of this research is to investigate the effect of adding aluminum scrap to the exhaust system of a motor vehicle on gas emissions composition. The motor vehicle exhaust system was modified to accommodate aluminum scrap placement. A gas analyzer was utilized to observe exhaust gas composition, such as carbon dioxide, hydrocarbon, and carbon monoxide. Aluminum scrap with different masses was wrapped around the exhaust's inner tube in 50 gr, 70 gr and 90 gr. The engine speed was maintained at 500 rpm throughout the testing process. It was found that the temperature of the outer exhaust tube is in a range of 40 degrees Celsius to 50 degrees Celsius. The results revealed that the most appropriate amount of aluminum scrap was 90 gr n to reduce carbon monoxide, hydrocarbon, and carbon dioxide in an exhausts gas. The surprising outcome was 76.78 % of carbon monoxide content declined, and furthermore hydrocarbon, and carbon dioxide content were deteriorated by 61.63% and 78.37%, respectively.

Organic/metallic component analysis of lignocellulosic biomass: A thermochemical-perspective-based study on rice and bamboo waste

Thermochemical treatment is significantly impacted by the physiochemical properties of lignocellulosic biomass. Traditional characterization methods lack granularity, requiring advanced analytical techniques for comprehensive biomass characterization. This study analyzed elemental composition and their distribution in untreated rice husk, rice straw, and bamboo chips at micron and sub-micron scales. Results reveal significant variations in composition and spatial distribution of metallic components among agro-residues. Thermogravimetric analysis shows divergent decomposition patterns, while spectroscopic analysis indicates structural complexities and distinct silica content. Surface mapping illustrates prevalent silica and alkali metals on rice husk and rice straw. Atomic force microscopy depicts distinctive surface morphologies, with rice straw exhibiting heightened roughness due to silica bodies. Inductively coupled plasma-mass-spectrometry identified the abundance of alkali and alkaline earth metals in rice waste. Time-of-flight secondary ion mass spectrometry elucidates elemental spatial localization, affirming heterogeneous distribution across rice waste and homogenous distribution across bamboo waste. This study bridges the gap between biomass composition and optimized thermochemical conversion outcomes.

Rapid Identification and Classification of Metal Waste by Laser-Induced Breakdown Spectroscopy

Rapid Identification and Classification of Metal Waste by Laser-Induced Breakdown Spectroscopy

WaveSegNet: An Efficient Method for Scrap Steel Segmentation Utilizing Wavelet Transform and Multiscale Focusing

Scrap steel represents a sustainable and recyclable resource, instrumental in diminishing carbon footprints and facilitating the eco-friendly evolution of the steel sector. However, current scrap steel recycling faces a series of challenges, such as high labor intensity and occupational risks for inspectors, complex and diverse sources of scrap steel, varying types of materials, and difficulties in quantifying and standardizing manual visual inspection and rating. Specifically, we propose WaveSegNet, which is based on wavelet transform and a multiscale focusing structure for scrap steel segmentation. Firstly, we utilize wavelet transform to process images and extract features at different frequencies to capture details and structural information in the images. Secondly, we introduce a mechanism of multiscale focusing to further enhance the accuracy of segmentation by extracting and perceiving features at different scales. Through experiments conducted on the public Cityscapes dataset and scrap steel datasets, we have found that WaveSegNet consistently demonstrates superior performance, achieving the highest scores on the mIoU metric. Particularly notable is its performance on the real-world scrap steel dataset, where it outperforms other segmentation algorithms with an average increase of 3.98% in mIoU(SS), reaching 69.8%, and a significant boost of nearly 5.98% in mIoU(MS), achieving 74.8%. These results underscore WaveSegNet’s exceptional capabilities in processing scrap steel images. Additionally, on the publicly available Cityscapes dataset, WaveSegNet shows notable performance enhancements compared with the next best model, Segformer. Moreover, with its modest parameters and computational demands (34.1 M and 322 GFLOPs), WaveSegNet proves to be an ideal choice for resource-constrained environments, demonstrating high computational efficiency and broad applicability. These experimental results attest to the immense potential of WaveSegNet in intelligent scrap steel rating and provide a new solution for the scrap steel recycling industry. These experimental results attest to the immense potential of WaveSegNet in intelligent scrap steel rating and provide a new solution for the scrap steel recycling industry.

A comparative study on the effectiveness of pollutants control measures adopted in the steel industry to reduce workplace and environmental exposure: a case study

Our understanding of the environmental and occupational health implications of pollutants emitted in steel production is still lacking, despite the considerable amount of research devoted to this topic. Given the significance of steel recycling and the need to reduce greenhouse gas emissions, many steel factories are adopting electric arc furnace (EAF) technology. The use of a technological system designed for the capture of pollutants emitted through EAF steel production is highly ecological because of its utilization of iron scrap and low investment cost. Despite this, the main issue with the EAF is the environmental impact it poses, specifically the release of pollutants into the air, such as dust and organic substances, chlorinated dioxins and furans, dioxin-like polychlorinated biphenyls and brominated dioxins and furans. As a result, workers in this field have a considerable rate of morbidity. The main challenge for EAFs is to optimize the capture of powders produced during the techno-logical process, both from the EAF and the workplace. A state-of-the art solution for managing pollutants in modern steel manufacturing is highlighted in this paper, featuring a method used in Romania that employs the Best Available Techniques (BAT) reference document for iron and steel production to directly collect pollutants from the EAF. The system included a cylindrical fitting, a heat exchanger to cool the gases and a hood to collect contaminants. In comparison to other ventilation options, this equipment boasts lower investment and lower operational costs because of its effective and minimal air flow. Through the use of cutting-edge technology and progressive strategies, we can move closer toward our objective of a workplace free from injuries in the steel industry.

Innovative deep decontamination of radioactive solid surfaces using microemulsions of deep eutectic solvents in supercritical carbon dioxide

Radioactive solid wastes resulting from the application of nuclear energy pose a risk to the environment, yet traditional decontamination methods generate many secondary wastes. Thus, sustainability-driven innovations are receiving increasing attention to achieve eco-friendly decontamination methods characterized by minimizing secondary waste generation. Here, we proposed a sustainable and pioneering approach to decontaminate radioactive solid wastes using microemulsions of deep eutectic solvents (DESs) in supercritical carbon dioxide (SC-CO2). We also determined the optimal ratios of the additives as follows: prepared DESs with a molar ratio of choline chloride (ChCl) to p-toluenesulfonic acid monohydrate (ptsa) of 1:2, and nonyl phenol polyoxyethylene ether (NP-10) to ChCl:ptsa DESs in a molar ratio of 0.8. Remarkably, after optimization of the decontamination process in terms of pressure, temperature and cleaning time, the radioactivity on the sample surface can be reduced to a level that is reusable in the nuclear field. Detailed analyses provided insights into the intermolecular interactions within the DESs. And the decontamination mechanisms involved the spontaneous evolution of microemulsions with ChCl:ptsa as the core to facilitate the solvation and removal of radioactive contaminants. Additionally, repeated cleaning was proved to be effective for ultra-deep decontamination, with the radioactivity on the sample surface reaching a clearance level and a decontamination efficiency of 99.8%. The DESs-in-CO2 systems successfully decontaminated various materials and simulated radionuclides, even real radioactive metal wastes from the nuclear industry. It was notable that the DESs-in-CO2 systems achieved decontamination efficiencies of more than 95.0% for radioactive contaminants on these solid surfaces. Overall, this innovative approach provided a green alternative to conventional radioactive solids decontamination, meeting the need for sustainable development of nuclear energy.

Iron scrap derived nano zero-valent iron/biochar activated persulfate for p-arsanilic acid decontamination with coexisting microplastics

P-arsanilic acid (AA) has received widespread attention because of its conversion to more toxic inorganic arsenic compounds (arsenate and arsenite) in the natural ecosystems. Its removal process and mechanisms with co-existence of microplastics remain unkown. In this study, biochar loaded with nano zero-valent iron (nZVI) particles (ISBC) was prepared by using iron scrap obtained from a steel works and wood chips collected from a wood processing plant. The advanced oxidation system of sodium persulfate (PDS) activated by ISBC was applied for AA degradation and inorganic arsenic control in aqueous media. More than 99% of the AA was completely degraded by the ISBC/PDS system, and the As(III) on AA was almost completely oxidized to As(V) and finally removed by ISBC. HCO3− inhibited the removal of AA by the ISBC/PDS system, while Cl− had a dual effect that showing inhibition at low concentrations yet promotion at high concentrations. The effect of microplastics on the degradation of AA by the ISBC/PDS system was further investigated due to the potential for combined microplastic and organic arsenic contamination in rural/remote areas. Microplastics were found to have little effect on AA degradation in the ISBC/PDS system, while affect the transport of inorganic arsenic generated from AA degradation. Overall, this study provides new insights and methods for efficient removal of p-arsanilic acid from water with coexisting microplastics.