Process Safety and Environmental Protection最新文献

The electrolytic manganese metal (EMM) industry faces significant environmental challenges, including substantial resource and energy consumption, severe pollution, and high CO₂ emissions. This study introduced a novel approach for developing collaborative strategies aimed at mitigating pollutants and CO₂ emissions. Through the implementation of life cycle carbon accounting and critical pollutant audits, a process enhancement program incorporating 17 advanced technologies was developed. Aligned with the principles of cleaner production, this project effectively mitigates the environmental burden at the source and offers viable solutions for addressing prominent emissions, such as manganese residue and acid fog. Furthermore, the marginal abatement cost curves demonstrate the economic practicality and applicability of these measures. This study provides a strategic blueprint for achieving sustainable green development in China’s EMM industry and offers valuable guidelines for formulating relevant environmental policies.

Industrial process data are closely related to production conditions and are essentially complex time series with high nonlinearity and dynamics. To solve the challenge of insufficient feature extraction of industrial process data, resulting in poor real-time monitoring of key quality variables, we propose an interpretable industrial soft sensor based on Graph Sampling and Aggregation Temporal Convolutional Network Improved by Multi-head Self-Attention (GraphSAGE-IMATCN) for predicting the trend of key quality variables in real time. Firstly, a three-dimensional data development strategy for batch processing is designed, and the maximum information coefficient (MIC) is introduced, and the threshold function is established by combining kernel density estimation to extract the characteristic variables with high quality correlation, and the explanatory and reliability of the model are enhanced by statistical methods. Secondly, a deep graph sampling aggregation (GraphSAGE) structure is designed for industrial big data, which aggregated features based on adjacent nodes and captured the context information of key nodes and serialized the extracted features to improve the computing speed of the model by combining the parallel computing advantages of the time convolutional network. Then, to overcome the data of different batch sizes and production scales, the residual structure of the Temporal Convolutional Network (TCN) is optimized by using Filter Response Normalization (FRN) to enhance the generalization and robustness of the model. Then, the multi-head self-attention mechanism (MHSA) is introduced to enhance the parallelism of the model, and the inference speed of the model is optimized to meet the key requirements of real-time performance for industrial process monitoring. Finally, the effectiveness of the proposed model is verified through experiments on the penicillin fermentation process and the debutanizer column.

The sodium roasting-water leaching process, the primary method for recycling valuable metals in spent FCC catalysts, has been industrialized and has good economic benefits. However, it also presents a significant challenge. Every ton of waste processed by the FCC catalyst will produce 0.75 tons of tailings, mainly containing silicon-aluminum-based substances, residual valuable metals, and other harmful components. These spent FCC catalyst tailings are listed as hazardous in the 'National List of Hazardous Wastes.' The need for harmless tailings disposal is crucial for its resource utilization and to mitigate its environmental impact. This study, which focuses on the resource characteristics of silicon-aluminum-based substances in spent FCC catalyst tailings, develops a method to shield harmful components and solve the resource utilization problem, which can significantly impact the waste management field. The research has laid a theoretical foundation for hazardous waste's harmless disposal and resource utilization.

The release control of organic dye pollutants has become a global issue, and improper disposal of red mud(RM) can also cause environmental pollution. In this paper, a novel composite material, RM-SC-HA, was prepared to adsorb MB (methylene blue) from dye wastewater by co-hydrothermal treatment using RM, sucrose, and humic acid as raw materials. RM-SC-HA is simple to prepare and has better adsorption of MB in dye wastewater. The results supported the proposed secondary (R² = 0.99) kinetic model, which states that chemisorption is the primary form of adsorption. The maximum amount of adsorption, which was achieved by Langmuir's isothermal model, was 417.12 mg/g. In addition, the adsorption mechanism can be attributed to the role of electrostatic interactions, hydrogen bonding, π-π stacking and void diffusion. When RM-SC-HA was used to treat simulated industrial wastewater samples, the removal rate was also maintained at a high level(About 90 %). In addition, RM-SC-HA has good magnetic properties and reusability. Its magnetic properties (saturation magnetization value of 2.49 emu/g) make it easy to separate from water under an applied magnetic field. The present study provides an efficient novel MB adsorbent and promotes the practical application of modified RM composites in water purification.

The reliability of clean renewable energy hinges on robust energy systems, with storage serving a critical function. This paper investigates the influence of various storage types and configurations on thermal performance, with a focus on optimal sizing for economic and environmental cost reduction. To achieve this objective, we simulate a solar cooling facility with varied configurations of hot/cold storage installations. This study employs an ANN methodology with a multi-layer perceptron approach to forecast unit performance for each configuration based on data generated during the simulation process. In the pursuit of the most efficient and high-performance network, a comprehensive investigation is conducted on the number of neurons, activation functions, and training algorithms. Subsequently, the optimization process, conducted through a genetic algorithm, determines the Pareto fronts representing the best solution sets. The comparison shows that a system design with double hot and cold storage tanks shows superior techno-economic-environmental performance. Among possible optimum solution sets, a point with this specification is selected; flow rate ratio, minimum flow ratio, cooling capacity ratio, cold storage ratio, and hot storage ratio of 1.2, 0.4, 0.91, 3.4, and 3.8, respectively. This configuration anticipates a levelized cost of cooling at 341 USD/MWhr, representing a 13 % reduction compared to the benchmark.

Chlorella biochar modified with boron and copper (B/Cu-BC) was created and used to break down the antibiotic metronidazole (MNZ) through peroxymonosulfate (PMS) activation. The physicochemical properties of B/Cu-BC were analyzed using SEM, BET, FTIR, XRD and XPS. The results showed that the modified Chlorella biochar, which included several oxygen-containing functional groups, exhibited a rise of 7.1 times in specific surface area and a rise of 8 times in pore volume compared to the unmodified variant. Under the optimal conditions, the B/Cu-BC+PMS system removed 86.6 % of MNZ in 90 min. The reaction mechanism of the system was confirmed by Quenching and electron paramagnetic resonance (EPR) experiments. The B/Cu-BC+PMS system was accompanied by SO₄•^-, •OH, •O₂^- and ¹O₂, in which •O₂^-was the main reactive oxygen species (ROS). The intermediates in the degradation process of MNZ were investigated using HPLC-MS, and two potential degradation pathways of MNZ were suggested. Finally, the toxicology of the intermediates from the MNZ degradation process was analyzed by toxicity estimation software tool. The bioconcentration coefficients and mutagenicity coefficients showed a significant decrease, indicating that the system could efficiently degrade the antibiotic MNZ in an environmentally friendly manner.

Metal-organic frameworks (MOFs) hold immense promise for low-temperature denitrification (de-NO_x) owing to their tunable pore size and active sites, nevertheless, their practical application is impeded by low yields. In this investigation, we introduce a synergistic modulated hydrothermal (SMHT) method designed to cooperatively control pre-cluster and solution pH using acetic acid and N, N-dimethylformamide, with the aim of enhancing MOFs yields. The TEOS&Mn-BTC-HY catalyst synthesized by the method of SMHT successfully increased the yield from 21 % of the input to 63 % compared with the TEOS&Mn-BTC catalyst synthesized by the hydrothermal method. Characterization analysis and performance testing reveal that the structure of TEOS&Mn-BTC-HY is minimally affected by the SMHT method, and its performance remains excellent. The de-NO_x efficiency remained above 90 % in the temperature range of 90–300 ℃, and even under challenging conditions such as 6 % H₂O or 100 ppm SO₂ at 150 ℃ for 10 h, the performance still exceeded 90 %. The designed SMHT process offers valuable insights for expanding MOFs production and further advancing the application of MOFs in the realm of de-NO_x.

Tetracycline antibiotics have attracted attention due to their difficulty in being degraded by the natural environment. In this work, 2D/3D mesoporous graphitic carbon nitride (mpg-C₃N₄)/ zinc oxide (ZnO) hollow nanocage (MCNZH) complexes with Z-scheme heterostructure were prepared for the photocatalytic degradation of tetracycline antibiotics. The catalysts were characterized by SEM, TEM, BET, XRD, FT-IR, EIS, etc. The degradation of tetracycline hydrochloride (40 mg L^–1) by MCNZH (1.2 g L^–1) can reach 92.08 %. Further, the energy band structure of the catalysts were calculated and the possible degradation mechanism was proposed. The results showed that ·OH^– and ·O₂^– were the main active species, and the internal electric field suppressed the compounding of photogenerated carriers. The catalysts exhibited broad-spectrum degradation of tetracycline antibiotics. Practical sample spiking experiments on soil and river water confirmed its practicability, which provide great significance for the application of the photocatalytic technology in the practical environmental purification.