With the acceleration of industrial modernization and urbanization, soil heavy metal pollution caused by human activities has become an increasingly severe environmental challenge that cannot be ignored around the world. Under normal circumstances, heavy metals are not easily dissolved in water in soil and are not easily degraded by microorganisms in the soil. Excessive accumulation of heavy metals in the soil will produce toxicity to plants and affect their normal growth and development. At the same time, heavy metal pollution may also pollute groundwater, affect the quality of drinking water and the health of aquatic ecosystems, and pose a threat to biodiversity, soil health and human health. National standards for soil Cu element analysis include flame atomic absorption spectrophotometry and wavelength dispersive X-ray fluorescence spectrometry. Although these methods offer high detection accuracy, they involve complex sample preparation and require advanced equipment, which limits the ability to analyze different metal elements anytime and anywhere. The aim of this study is to develop an efficient and sensitive method for detecting Cu in soil. By using chelating resin as enrichment matrix, the interference of other elements in soil can be reduced. The sensitivity of heavy metal detection is improved by using spatially constrained enhancement mechanism. This study hopes to significantly improve the detection ability of laser-induced breakdown spectroscopy (LIBS) to Cu in soil by combining spatially constrained LIBS with resin enrichment pretreatment technology, and provide an effective method for the treatment of soil heavy metal pollution.

In this study, resin enrichment technique and spatially constrained LIBS analysis method are combined. First, a specific type of chelating resin with high selectivity and strong adsorption capacity for Cu element is screened to maximize the enrichment of Cu ions in soil samples and effectively eliminate the interference of other elements. Second, the key experimental parameters are optimized by LIBS to determine the optimal experimental conditions and reduce the impact of unknown factors on the accuracy and detection sensitivity of the calibration model. Then, the influence mechanism of spatial constraint on the formation, expansion and spectral characteristics of LIBS plasma is deeply analyzed, and a customized spatial constraint device suitable for soil Cu element detection is designed and manufactured. Through comparative testing of different design schemes, the optimal device that can significantly improve the strength and stability of LIBS signal is selected. In the next step, the optimized LIBS experimental conditions and space constraint device are used to conduct quantitative analysis of Cu elements in enriched soil samples, and a stable and reliable calibration model is established to ensure the accuracy and repeatability of measurement results. In addition, the optimized method is applied to real soil samples to evaluate its stability and applicability under complex environmental conditions.

The spatially constrained LIBS technique combined with the resin enrichment method achieves remarkable results in improving the detection performance of Cu elements in soil. This method reduces the potential interference of other unknown elements on the detection results (Fig.3), and also realizes a double leap in detection sensitivity and quantitative analysis accuracy by introducing a spatial constraint mechanism. When no spatial constraint is applied, the linear correlation coefficients of Cu I 324.75 nm and 327.39 nm lines are 0.977 and 0.981, respectively, showing a good linear relationship. However, after the introduction of spatial constraint optimization, the linear correlation coefficients of these two key spectral lines jump to 0.986 (Fig.11), marking a significant improvement in detection accuracy. At the same time, the detection limit (LOD) of Cu element also decreases significantly, from the original 1.368 mg/kg and 1.062 mg/kg to the optimized 0.807 mg/kg and 0.617 mg/kg, respectively (Table 1). In addition, in the practical application verification, the recovery rates of GBW7451 and GBW7456 standard samples are tested, and the results show that the recovery rates are stable in the range of 96.43% to 98.66% and 93.40% to 104.58%, respectively, which proves the high accuracy and repeatability of the technology in the actual soil sample detection (Table 2).

In this paper, chelating resin is used as the matrix material and the LIBS combined with space constraint is used to realize the high-precision quantitative analysis of Cu in soil. By optimizing experimental parameters and data processing, an accurate relationship model between Cu mass fraction and LIBS signal intensity is established. The LOD values of Cu element in soil samples are 0.807 mg/kg and 0.617 mg/kg (far less than the predicted value of soil risk), and the determination coefficients are 0.986. It has a lower detection limit and a higher correlation coefficient. In this study, the detection sensitivity of Cu in soil and the accuracy of quantitative analysis are effectively improved through the method of spatially constrained LIBS combined with resin enrichment, which provides a new and effective way for soil heavy metal pollution monitoring. Future studies can further explore the application potential of this method in other heavy metal elements and different types of soil, further promoting the widespread use and development of LIBS technology in environmental science.