With the rapid development of industrialization, the problem of concentration determination based on the copper production process has been widely concerned, and the accurate determination of high-concentration copper ions (Cu²⁺) is of great significance for enterprise production, resource utilization, and pollution prevention. The characteristics of different spectrophotometric methods for the determination of Cu²⁺ are discussed, and it is found that these methods are suitable for the determination of trace or low concentration of Cu²⁺ (0.5 μg/L–5 mg/L), whereas for the determination of high Cu²⁺ concentration pre-treatments such as dilution, complexation, and coloring are required. In this study, a method based on ultraviolet-visible spectroscopy (UV-Vis) combined with partial least squares regression analysis (PLS) was proposed for the determination of high copper ions (>100 mg/L), which performs rapid and accurate determination of high Cu²⁺ concentration by preprocessing and feature extraction of UV-Vis spectral data, followed by model construction with PLS analysis, which is easy to operate and applicable to a wide range of concentrations. The correlation coefficient (R²), mean relative error (MRE), and root mean square error (RMSECV) of the model prediction of Cu²⁺ concentrations were 0.99946, 0.006343, and 11.237 mg/L, respectively, indicating that the accuracy of the model prediction is very high. This study not only provides an efficient method for the precise determination of high Cu²⁺ concentration but also enables the simultaneous determination of Cu²⁺, Co²⁺, and Ni²⁺ ions, which provides a new technical means for environmental monitoring and pollution prevention.

Due to the fast material reaction in zinc hydrometallurgy, the traditional national standard photometric method cannot capture the characteristic information of target substances in real time. Herein, a nitrogen protection device is built based on ultraviolet spectrophotometry, supplemented by a programmable logic controller (PLC), to form an automatic control system for the direct detection of target substances (SO₄²⁻, Pb²⁺ and S²⁻) in zinc hydrometallurgy. The baseline straightness comparison results show that the nitrogen atmosphere can effectively improve the stability of the instrument. Furthermore, the detection sensitivity of SO₄²⁻, Pb²⁺ and S²⁻ under the nitrogen atmosphere is higher than that of the air atmosphere, manifesting in sensitivity increases of 16.23%, 18.05% and 17.91%, respectively. Additionally, devices based on PLC systems show advantages over manual control both in states feedback and information backtrack. Moreover, the regulation time and nitrogen consumption during the regulation process are reduced by 80% and 75%, respectively, which effectively reduces the test cost and improves the equipment utilization rate (from four cycles per day to six cycles per day). The device can meet the requirements of different target substances and different process conditions by changing the electronic control parts and air source, so it has great application potential in the automatic direct measurement of target substances in zinc hydrometallurgy.

Heavy particulate matter (PM) pollution and high energy consumption are the bottlenecks of hydrometallurgy, especially in the electrolysis process. Therefore, an urgent need is to explore PM reduction methods with production performance co-benefits. This study presents three PM reduction methods based on controlling operating parameters, i.e., lowering electrolyte temperature, H₂SO₄ concentration, and current density of the cathode. The optimized conditions were also investigated using the response surface methodology to balance the PM reduction effect and Zn production. The results showed that lowering electrolyte temperature is the most efficient, with an 89.0% reduction in the PM generation flux (GF_PM). Reducing H₂SO₄ concentration led to the minimum side effects on the current efficiency of Zn deposition (CE_Zn) or power consumption (PC). With the premise of non-deteriorating CE_Zn and PC, GF_PM can be reduced by 86.3% at the optimal condition (electrolyte temperature = 295 K, H₂SO₄ = 110 g/L, current density = 373 A/m²). In addition, the reduction mechanism was elucidated by comprehensively analyzing bubble characteristics, electrochemical reactions, and surface tension. Results showed that lower electrolyte temperature inhibited the oxygen evolution reaction (OER) and compressed gas volume. Lower H₂SO₄ concentration inhibited the hydrogen evolution reaction (HER) and reduced electrolyte surface tension. Lower current density inhibited both OER and HER by decreasing the reaction current. The inhibited gas evolutions reduced the microbubbles’ number and size, thereby reducing GF_PM. These results may provide energy-efficient PM reduction methods and theoretical hints of exploring cleaner PM reduction approaches for industrial electrolysis.