Hazardous Materials Research Articles

Quantitative risk analysis of road transportation of hazardous materials in coastal areas

Given the complex climate conditions in coastal areas and their role as key transportation hubs for hazardous chemicals, this study proposes a method to quantitatively and comprehensively evaluate transportation risks. Initially, accident data were analyzed to identify risk factors from five aspects: human, vehicle, materials, environment, and management, based on system safety theory. Subsequently, a risk analysis model was developed using Decision-making Trial and Evaluation Laboratory, interpretive structural model theory, and Bayesian theory to quantitatively assess accident risk levels. The model was applied to a case involving a hazardous chemical accident on a cross-sea bridge, where Bayesian backward reasoning was used to analyze the sensitivity and importance of risk factors. This approach facilitated the key risk factors affecting the safety of hazardous chemical transportation systems. Notably, the study incorporated scenarios involving hazardous material transport vehicles crossing sea bridges into the risk assessment framework, offering valuable insights for management authorities. It also considered the impact of strong side winds-a factor often overlooked-in hazardous material transport. The validation process demonstrated that the method accurately quantifies the risk of hazardous chemical transportation and identifies the key factors influencing accident occurrence. The research highlights that strong gusts of wind significantly impact safety, and human factors are crucial in the overall risk system.

Online control parameter optimization design for multi-machine coordinated loading system of hazardous substances

To address the parameter instability issues in hazardous materials handling during multi-machine loading and unloading operations, we propose a Full-Scale Smart Parameter Optimization Control (FSPOC) system specifically designed for multi-machine coordination. This system leverages a novel fish scale prediction algorithm tailored for cooperative multi-machine environments. Initially, the fish scale prediction algorithm, inspired by bionic fish scales, is developed to predict future system behavior by analyzing historical data. Building on this algorithm, we introduce a disturbance cancellation control theorem and design a parameter optimization controller to enhance stability in high-dimensional nonlinear spaces. The FSPOC method is then applied to a multi-machine cooperative system, enabling online distributed parameter optimization for complex systems with multiple degrees of freedom. The effectiveness of the proposed method was validated through simulations, where it was compared with two other optimization techniques: Genetic Algorithm-based PID (GAPID) and Chaotic Atomic Search Algorithm-based PID (CHASO). The simulation results confirm the superiority of the FSPOC method.

Green synthesis of NiFe2O4 nanoparticles using Hyphaene thebaica: A facile route towards magnetic and photocatalytic application

Wastewaters from textile industries contribute to significant volumes of colored and hazardous material pollution. Photocatalytic degradation offers a method to reduce organic pollutants, such as dye-containing effluents effectively. Nickel Ferrite (NiFe2O4) receives the most attention in spinel ferrites since it has diverse applications in catalysis, sensor technology, spintronics, magnetocaloric refrigeration, high-density data storage devices, etc. We performed the green synthesis of NiFe2O4 nanoparticles by fruit extract of a gingerbread tree (Hyphaene thebaica). We characterized it with Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-ray diffraction (XRD), Fourier Transform Infrared spectroscopy (FTIR), and Raman spectroscopy. The XRD indicates the inverse-spinel structure of the F3dm space group with crystallite size measured as 30 nm. SEM and TEM revealed the spheroidal structure of NiFe2O4 NPs. The green synthesized NiFe2O4 has tetrahedral and octahedral stretching vibrations of Ni–O and Fe–O, as suggested by FTIR. Doublet-like peak behavior in the Raman spectrum indicated the presence of a mixed spinel structure. We studied magnetic behavior in two different modes, and magnetization measurements showed a soft ferromagnetic behavior with a saturation magnetization of 1.527 emu g−1. For photocatalytic potential, the degradation efficiency was 97 % after 90 min at adding 1 g/L of NiFe2O4 nano-catalyst, which shows the high catalytic activity of NiFe2O4 NPs under visible light conditions.

Dynamic risk analysis of hazardous materials highway tunnel transportation based on fuzzy Bayesian network

Dynamic risk analysis of hazardous materials highway tunnel transportation based on fuzzy Bayesian network

A Blockchain-Based Access Control System for Secure and Efficient Hazardous Material Supply Chains

A Blockchain-Based Access Control System for Secure and Efficient Hazardous Material Supply Chains

Waste Symbiosis through the Synthesis of Highly Crystalline LTA and SOD Zeolites.

In recent years, the demand for natural and synthetic zeolites has surged due to their distinctive properties and myriad industrial applications. This research aims to synthesise crystalline zeolites by co-recycling two industrial wastes: salt slag (SS) and rice husk ash (RHA). Salt slag, a problematic by-product of secondary aluminium smelting, is classified as hazardous waste due to its reactive and leachable nature, though it is rich in aluminium. Conversely, RHA, an abundant and cost-effective by-product of the agro-food sector, boasts a high silicon content. These wastes were utilised as aluminium and silicon sources for synthesising various zeolites. This study examined the effects of temperature, ageing time, and sodium concentration on the formation of different zeolite phases and their crystallinity. Results indicated that increased Na+ concentration favoured sodalite (SOD) zeolite formation, whereas Linde type-A (LTA) zeolite formation was promoted at higher temperatures and extended ageing times. The formation range of the different zeolites was defined and supported by crystallographic, microstructural, and morphological analyses. Additionally, the thermal behaviour of the zeolites was investigated. This work underscores the potential to transform industrial waste, including hazardous materials like salt slag, into sustainable, high-value materials, fostering efficient waste co-recycling and promoting clean, sustainable industrial production through cross-sectoral industrial symbiosis.

An efficient One-Pot synthesis of NaOCl mediated pyrazolopyrimidine derivatives

The discovery and success of sildenafil, widely recognized as Viagra™, represented a major progress in the treatment of erectile dysfunction (ED). Numerous approaches for synthesis of the Pyrazolo[4,3-d]pyrimidine-7-one ring have reported in the literature. However, those methods have several drawbacks, including high temperatures, low yields, the use of hazardous materials, specific oxidation protocols, long reaction times, multiple reaction steps, and expensive catalysts. To overcome these limitations, we present a simple, catalyst-free, and cost-effective one-pot synthesis of pyrazolopyrimidine derivatives with a high yield and lower reaction time using the inorganic reagent i.e., sodium hypochlorite (NaOCl). The reaction uses easily available starting materials such as 4- amino-1-methyl-3-propylpyrazole-5-carboxamide and aldehyde derivatives under moderate conditions, providing a greener alternative to typical multi-step synthesis techniques. Detailed optimization studies to afford pyrazolopyrimidine derivatives (6a-6o) show that NaOCl is a strong oxidizing agent that promotes cyclization and functionalization processes. Structures of synthesized compounds were confirmed by 1H NMR,13C NMR and HR-MS techniques.

Analisis Putusan Pengadilan dalam Perkara Tindak Pidana Pencemaran Udara

Air pollution is one part of physical environmental pollution. Air pollution according to the Government Regulation on air pollution control is the entry or introduction of substances, energy, and/or other components into ambient air by human activities, so that the quality of ambient air decreases to a certain level that causes ambient air to be unable to fulfill its function. The research method used is to use a type of normative legal research method, by examining library materials or secondary data which include primary legal materials, secondary legal materials and tertiary legal materials using Decision Number 68/Pdt.G/LH/2022/PN Rap. The results of the study, namely the lawsuit was rejected by the Court and the impact was air pollution, namely respiratory disorders, cardiovascular disease, impaired fetal development, decreased lung function, and chronic diseases. Conclusion Air is very important because it provides oxygen and other gases that are essential for all life on earth. Air pollution or contamination is the introduction of other components into the air, either by human activities directly or indirectly or due to natural processes. The impacts of this pollution include respiratory disorders, cardiovascular disease, impaired fetal development, decreased lung function, and chronic diseases. Suggestions Palm oil mills need to adopt more effective pollution control technologies to reduce emissions of hazardous materials into the air. Local governments and environmental regulatory agencies must ensure that palm oil mills comply with all applicable environmental regulations and standards. Local communities must be empowered and educated about their rights and how to advocate for a healthy environment.

Toward sustainability: Integrating experimental study and data-driven modeling for eco-friendly paver blocks containing plastic waste

Abstract Plastic waste (PW) poses a significant threat as a hazardous material, while the production of cement raises environmental concerns. It is imperative to urgently address and reduce both PW and cement usage in concrete products. Recently, several experimental studies have been performed to incorporate PW into paver blocks (PBs) as a substitute for cement. However, the experimental testing is not enough to optimize the use of waste plastic in pavers due to resource and time limitations. This study proposes an innovative approach, integrating experimental testing with machine learning to optimize PW ratios in PBs efficiently. Initially, experimental investigations are performed to examine the compressive strength (CS) of plastic sand paver blocks (PSPBs). Varied mix proportions of plastic and sand with different sizes of sand are employed. Moreover, to enhance the CS and meet the minimum requirements of ASTM C902-15 for light traffic, basalt fibers, a sustainable industrial material, are also utilized in the manufacturing process of environmentally friendly PSPB. The highest CS of 17.26 MPa is achieved by using the finest-size sand particles with a plastic-to-sand ratio of 30:70. Additionally, the inclusion of 0.5% basalt fiber, measuring 4 mm in length, yields further enhancement in outcome by significantly improving CS by 25.4% (21.65 MPa). Following that, an extensive experimental record is established, and multi-expression programming (MEP) is used to forecast the CS of PSPB. The model’s projected results are confirmed by using various statistical procedures and external validation methods. Furthermore, comprehensive parametric and sensitivity studies are conducted to assess the effectiveness of the MEP-based proposed models. The sensitivity analysis demonstrates that the size of the sand particles and the fiber content are the primary factors contributing to more than 50% of the CS in PSPB. The parametric analysis confirmed the model’s accuracy by demonstrating a comparable pattern to the experimental results. Furthermore, the results indicate that the proposed MEP-based formulation exhibits high precision with an R 2 of 0.89 and possesses a strong ability to predict. The study also provides a graphical user interface to increase the significance of ML in the practical application of handling waste management. The main aim of this research is to enhance the reuse of PW to promote sustainability and economic benefits, particularly in producing green environments with integration of machine learning and experimental investigations.

Robustness of higher‐order network pertinent to first‐ and higher‐order dependency

AbstractRobustness of higher‐order network (HON) with dependency is different from first‐order network (FON), as the attack orders and the number of iterations are totally different. To measure the robustness of HON with dependency, this study proposed new attack strategies on node and edge failure through measuring the size of the giant component and global efficiency. And two real‐world systems of hazardous materials transportation accident causation system and Chinese high‐speed railway system with different network size were empirically studied. Results show that HON is more fragile to robustness attacks than FON. The number of attack iterations is uncertain in HON, which depends on the attack strategies and the network structure. Meanwhile, nodes and edges with high dependency have greater impacts on network robustness, providing valuable insights into capturing critical information. This study may be helpful to design the robust system, improve the system's reliability and serve as a valuable reference for future exploration of HONs robustness.

Penyuluhan Keamanan Pangan pada Ibu Rumah Tangga di RT 05 RW 06 Kelurahan Bandar Kidul Kota Kediri

Two important factors in preventing foodborne illness are food hygiene and sanitation. These efforts can reduce the risk of bacterial contamination of food. Some examples of hazardous materials in food are plastics, metals, borax, formalin, insecticides, and banned food additives such as benzoic acid, ascorbic acid, lactic acid, and citric acid. The objective of this outreach is to increase knowledge about food safety and how to manage it. The method of counseling to the general public includes coordination with the head of the RT, providing materials, giving pre- and post-tests, and evaluating activities carried out at the RT head's house on June 1, 2024 at 16.00-17.30. The results of this activity were an increase in pre and post-test scores on questions regarding storage temperature and the main purpose of food storage, from 50 to 70 and 95 to 100. The conclusion of this counseling is that there is an increase in housewives' knowledge about food safety on a household scale. Suggestions for further counseling are to increase the number of targets so that more housewives understand the importance of household-scale food safety.

Green Wearable Sensors and Antennas for Bio-Medicine, Green Internet of Things, Energy Harvesting, and Communication Systems.

This paper presents innovations in green electronic and computing technologies. The importance and the status of the main subjects in green electronic and computing technologies are presented in this paper. In the last semicentennial, the planet suffered from rapid changes in climate. The planet is suffering from increasingly wild storms, hurricanes, typhoons, hard droughts, increases in seawater height, floods, seawater acidification, decreases in groundwater reserves, and increases in global temperatures. These climate changes may be irreversible if companies, organizations, governments, and individuals do not act daily and rapidly to save the planet. Unfortunately, the continuous growth in the number of computing devices, cellular devices, smartphones, and other smart devices over the last fifty years has resulted in a rapid increase in climate change. It is severely crucial to design energy-efficient "green" technologies and devices. Toxic waste from computing and cellular devices is rapidly filling up landfills and increasing air and water pollution. This electronic waste contains hazardous and toxic materials that pollute the environment and affect our health. Green computing and electronic engineering are employed to address this climate disaster. The development of green materials, green energy, waste, and recycling are the major objectives in innovation and research in green computing and electronics technologies. Energy-harvesting technologies can be used to produce and store green energy. Wearable active sensors and metamaterial antennas with circular split ring resonators (CSSRs) containing energy-harvesting units are presented in this paper. The measured bandwidth of the matched sensor is around 65% for VSWR, which is better than 3:1. The sensor gain is 14.1 dB at 2.62 GHz. A wideband 0.4 GHz to 6.4 GHz slot antenna with an RF energy-harvesting unit is presented in this paper. The Skyworks Schottky diode, SMS-7630, was used as the rectifier diode in the harvesting unit. If we transmit 20 dBm of RF power from a transmitting antenna that is located 0.2 m from the harvesting slot antenna at 2.4 GHz, the output voltage at the output port of the harvesting unit will be around 1 V. The power conversion efficiency of the metamaterial antenna dipole with metallic strips is around 75%. Wearable sensors with energy-harvesting units provide efficient, low-cost healthcare services that contribute to a green environment and minimize energy consumption. The measurement process and setups of wearable sensors are presented in this paper.

Origami-based multifunctional sensing platform for sustainable detection of hazardous magnetic materials

Anthropogenic magnetite (AM) nanoparticles have been identified in the human brain and circulatory system, potentially linked to neurodegenerative and cardiovascular diseases. Specifically, AM and other magnetic nanocontaminants from industrial emissions and brake wear are hazardous components of particulate matter. Such contamination enriches urban soils with magnetite and other magnetic nanocontaminants, which can be absorbed by plants like rice and consequently enter the human body indirectly. Developing accurate and robust AM-sensing platforms is crucial, especially in areas where magnetic contamination threatens ecosystems and human health. Innovative materials, such as magnetoactive smart materials, are essential for creating sensors with specific, wireless, and adjustable magnetic properties for efficient detection and monitoring of soil contamination. This study presents an origami-based multifunctional sensing platform for sustainable detection of magnetic environmental contamination. Utilizing paper as its substrate for low-cost AM sensing, the device incorporates two wax/NdFeB magnets, four hydrophilic channels, and a hydrophilic analysis area, enclosed by hydrophobic wax. Through comprehensive analysis techniques including energy-dispersive X-ray spectroscopy, vibrating sample magnetometry, infrared spectroscopy, and photographic color changes, the device exhibited a detection limit below 156 μg. The platform's versatility, affordability, sustainability, and capacity for multi-analysis indicate promising prospects for developing economically equitable, user-friendly, mechanically robust, and flexible magnetic contamination sensing devices. These devices eliminate the need for complex machinery while delivering rapid, accurate, and precise results tailored to diverse environmental needs, thus promoting sustainable and safe societies.

Feasibility study on using red mud as a viscosity-modifying agent for self-compacting concrete

Red mud (RM) is a hazardous waste material generated during the alkaline leaching of bauxite in the Bayer process. The feasibility of using RM as a viscosity-modifying agent (VMA) for self-compacting concrete (SCC) was proposed in this study. In addition, RM paste, cement paste, RM-blended paste, SCC that containing RM as VMA were prepared, and those fresh properties were investigated with emphasis. The results show that compared to cement paste, the RM paste exhibited excellent water retention. In the RM-blended cement paste with equivalent fluidity, an increase in RM dosage led to a notable decrease in bleeding rate, accompanied by an increase in yield stress and plastic viscosity. Similarly, in the SCC (containing RM as VMA) with equivalent slump-flow, the segregation rate decreased significantly (17.12 % of segregation for SCC that without RM, and 6.88 % of segregation for SCC that with 12 wt% RM), while yield stress and plastic viscosity increased with higher RM dosages, demonstrating a linear relationship. These findings highlight the feasibility of achieving SCC with high slump-flow and non-segregation by using RM as VMA, and the fresh properties of prepared SCC can be effectively controlled. Meanwhile, the findings of this study offer a novel approach to utilize RM and provide valuable guidance for the application of RM used as VMA.

Weak interaction induced selective separation of V/Mo/Co from spent hydrodesulfurization catalyst leaching solution: Mechanism and strategy

Spent hydrodesulfurization catalysts contain more than 10 ∼ 25 wt% V, Mo and Co, which are not only hazardous materials, but also can be considered as valuable secondary resources. The complete separation of these complex critical metals by solvent extraction still needs to be improved. Here, a selective extraction route for the separation of V/Mo/Co is proposed based on the weak interaction differences between extractants and metal, which is realized by theoretical calculation and experimental verification. This process does not require pretreatment of N1923 and Cyanex272 (C272), thus reduced the consume of acid and base as well as generation of waste water. With the preliminary results of V/Mo, Co/Mo, and V/Co separation, the weak interaction between extractants and metal molecules was revealed by quantum chemical calculations quantitatively. The molecular charge distribution, surface electrostatic potential distribution (ESP) and the average local ionization energy (ALIE) shows the priority reactivity of the metal molecules as: H6V10O28 > H2Mo4O13 > H4V4O12 > H3VO4 > H2MoO4. The independent gradient model based on Hirshfeld partition (IGMH) show differences in the weak interaction forces as: N1923-V>C272-Mo > C272-V>N1923-Mo > C272-Co. The selective separation process of V/Mo/Co was designed with the guide of above results. The combined recovery of the three metals V, Mo and Co amounted to 83.88 %, 87.08 %, and 99.01 %, respectively. The whole route reduces 3.92 t sulfuric acid and 7.83 t sodium hydroxide per solid, and reduces 1.99 t carbon emissions compared to the conventional route.

Multi-deformable interpenetrating network thermosensitive hydrogel fluorescent device for real-time and visual detection of nitrite

Functionalized thermosensitive hydrogel materials exhibit excellent properties for the fabrication of sensing devices that enable real-time visual detection of food safety duo to their good plasticity and powerful loading capacity. Here, a ratiometric fluorescent device based on an interpenetrating network (IPN) thermosensitive hydrogel was designed to embed functionalized Au nanoclusters (Au NCs) and Blue Carbon dots (BCDs) composites in a multi-network structure to build a sensitive hazardous material nitrite (NO2-) chemsensor. The hydrogel was utilized poloxamer 407 (P407), lignin and cellulose to form stable IPN structure, which resulted in complementation and synergy, thereby strengthening its porous network structure. The combination of fluorescent nanoprobes with the porous network structure has the potential to enhance stable fluorescence signals and improve sensing sensitivity. Moreover, the thermosensitive liquid-solid transition characteristics of the hydrogel facilitate its preparation into diverse sensing devices following curing at room temperature. The hydrogel device, when combined with a smartphone system, converted image information into data information, thereby enabling the accurate quantification of NO2- with a detection limit of 9.38 nM in 2 s. The designed multi-functional hydrogel device is capable of real-time differentiation of NO2- dosage with the naked eye, offering a high-contrast, rapid-response sensing methodology for visual assessment of food freshness. This research contributes to the expansion of hydrogel materials applications and the detection of hazardous materials in food safety.

Navigating E-Waste Disposal: Formal Practices among Residents of Bukit Sentosa, Rawang, Selangor

Electronic waste (e-waste) contains harmful materials that require specialized end-of-life handling. This study aims to analyse formal e-waste disposal practices among residents in Bukit Sentosa, Rawang, Selangor. Employing a quantitative research approach, data were collected from 367 respondents residing in Bukit Sentosa to examine the relationship between knowledge, awareness, and attitudes towards e-waste disposal practices. Spearman's correlation test revealed positive correlations between knowledge, attitudes, and awareness, and formal e-waste disposal practices. These findings indicate that improved knowledge, attitudes, and awareness lead to more responsible disposal behaviours, including increased recycling, reduced waste production, and proper disposal of hazardous materials, thereby mitigating environmental pollution. The findings suggest to enhanced public awareness and education can foster better e-waste management practices among urban households. Furthermore, the results highlight the potential for collaboration between policymakers, government agencies, local authorities, and NGOs, contributing to the development of more comprehensive and effective waste management regulations.

A learning optimization for resilience enhancement of risk-informed traffic control system with hazardous materials transportation under uncertainty

A learning optimization is proposed to enhance overall resilience of interdependent traffic systems with hazardous materials (hazmat) transportation under uncertainty. To this end, three interconnected systems are proposed against traffic dynamics and congestion in a complex environment of regular traffic and hazmat carriers incurred with time-varying travel cost. In order to increase control resilience against traffic instability, a reinforcement learning hazmat network is proposed. In order to efficiently improve computation resilience against disruption of risk uncertainty, a resilience-aware learning optimization is proposed to obtain optimal solutions. In order to demonstrate computational performance of proposed approach, numerical experiments are performed at a real-world city under various kinds of traffic conditions. Computational comparisons are numerically made with stochastic and robust optimization at large-scale traffic control systems. As it reported, the proposed learning-based optimization can better greatly enhance overall traffic system resilience, control resilience and computation resilience compared to other models under mixed risk of hazmat transportation and uncertain demand.

Non-invasive detection of hazardous materials with a thermal-to-epithermal neutron station: a feasibility study towards practical application

The growing scale of the devastation that even a single terrorist attack can cause requires more effective methods for the detection of hazardous materials. In particular, there are no solutions for effectively monitoring threats at sea, both for the off-shore infrastructure and ports. Currently, state-of-the-art detection methods determine the density distribution and the shapes of tested subjects but only allow for a limited degree of substance identification. This work aims to present a feasibility study of the possible usage of several methods available on the thermal-to-epithermal neutron station, VESUVIO, at the ISIS neutron and muon spallation source, UK, for the detection of hazardous materials. To this end, we present the results of a series of experiments performed concurrently employing neutron transmission and Compton scattering using melamine, a commonly used explosive surrogate, in order to determine its signal characteristics and limits of detection and quantitation. The experiments are supported by first-principles modelling, providing detailed scrutiny of the material structure and the nuclear dynamics behind the neutron scattering observables.

(Invited) Exploitation of Advanced Materials and Process for Sustainable Perovskite Solar Cells

All solid-state solar cells based on organometal trihalide perovskite absorbers have already achieved distinguished power conversion efficiency (PCE) to 26.1% and further improvements are expected up to 27%. Now, the research on perovskite solar cells (PSCs) has been moving toward commercialization. To facilitate commercialization of these great solar cells, some technical issues such as long-term stability, large scale fabrication process, Pb-related hazardous materials, and environmentally-burdened toxic solvent-based process need to be solved.This talk is dealing with our recent efforts to facilitate commercialization of perovskite solar cells. For examples, we introduce a recycling technology of perovskite solar cells, which covers the regeneration process of Pb contained perovskite layer as well as recycling process of Au electrodes and transparent conducting oxide glass [1, 2]. Also, novel strategies for recycling toxic solvents such as DFM, used in fabricating PSCs are introduced, which is critical to realize close loop recycling process of PSCs. Finally, recent studies for achieving high efficiency PSC using ecofriendly solvent are demonstrated.