Quantitative assessment on soil concentration of heavy metal-contaminated soil with various sample pretreatment techniques and detection methods

Remote sensing inversion on heavy metal content in salinized soil of Yellow River Delta based on Random Forest Regression-a case study of Gudao Town

To explore the potential of using the mineral alteration information extracted by remote sensing technology to indirectly estimate the heavy metal content of salinized soil, 23 sampling points were uniformly set up in the town of Gudao in the Yellow River Delta as the research area in 2022. The concentrations of seven heavy metals, Cr, Cu, Pb, Zn, As, Mn and Ni, at the sampling points were determined in laboratory tests. Spectral derivative indices, topographic factors, and mineral alteration information (iron staining, hydroxyl, and carbonate ions) were extracted and screened as modeling factors using Sentinel 2 imagery. An inverse model of heavy metal content was constructed using the random forest algorithm, and the model accuracy was evaluated using the cross-validation method. The results of the study show that: (1) Hydroxyl and carbonate ion alteration can be effectively used for the inversion of soil As and Ni content in this study area. Iron-stained alteration can be used as a modeling factor in the inversion of Cr, Cu, Pb, Zn, and Mn concentrations. (2) The inclusion of alteration information improves the accuracy of heavy metal content inversion. The Cu concentration was verified to be the best predictor, with an RMSE of 3.309, MAPE of 11.072%, and R2 of 0.904, followed by As, Ni, and Zn; the predictive value of Mn, Cr and Pb was average. (3) Based on the results of concentration inversion, the high concentration areas of As, Ni, and Mn are primarily distributed on both sides of the river and around lakes and ponds. The high-concentration areas of Zn were mainly distributed in the farmland areas on both sides of the river. Areas with high concentrations of Cu were mainly distributed in the eastern oil extraction area, both sides of the rivers, and around lakes.

Spatial variability of heavy metals concentrations in soil of auto-mechanic workshop clusters in Nsukka, Nigeria

The indiscriminate disposal of spent engine oils and other hazardous waste at auto mechanic workshops clusters in Nsukka, Enugu State, Nigeria is an environmental concern. This study examines the concentration of heavy metals in the soil inside the workshop cluster and in the unpolluted soil outside the workshop cluster at approximately 100 m. Ten sampling points were randomly selected from within the cluster and another ten from outside the cluster. Using a hand-held Global Positioning System, the coordinates of the selected points were established and used to create a digital map. Soil samples at depths of 0-30 cm and 30-60 cm, were analyzed for Cu, Fe, Zn, Pb, As and Cd using Spectrophotometer. Moisture content determination and particle size analysis were also done on the samples. Spatial variability of heavy metals concentrations of the studied site was also mapped with ArcGIS 10.2.2 using interpolation methods. Results showed that the soil ranged from sandy loam to sandy clay loam. Cadmium and Zinc had the lowest and highest concentration, respectively, in the studied area. Comparing the concentrations of heavy metals in soils within and outside the auto mechanic cluster revealed notable differences across various depths (0-30 cm and 30-60 cm). The analysis results for soil samples within the cluster exhibited concentration levels (mg/kg) ranging from 0.716-0.751 (Cu), 2.981-3.327 (Fe), 23.464-30.113 (Zn), 1.115-1.21 (Pb), 2.6-2.912 (As), and 0.133-0.365 (Cd) demonstrating a variation pattern in the order of Zn > Fe > As > Pb > Cu > Cd. Conversely, for soil samples outside the cluster, concentration levels (mg/kg) ranged from 0.611-0.618 (Cu), 2.233-2.516 (Fe), 12.841-15.736 (Zn), 0.887-0.903 (Pb), 1.669-1.911 (As), and 0.091-0.091 (Cd). To assess the disparity in heavy metal concentration levels between samples collected within and outside the clusters, ANOVA test was performed. The test showed significant difference in heavy metal concentrations between samples within and outside the auto mechanic cluster (p < 0.05), implying auto mechanic activities significantly impact heavy metal levels within the cluster compared to outside areas. The assessment of soil pollution utilized indices including the Geo-accumulation Index (Igeo), Contamination factor (Cf), and anthropogenic metal concentration (QoC). Zinc, Cadmium, and Arsenic showed the highest contamination factors, indicating significant soil contamination likely due to anthropogenic activities. The concentrations of the metals analyzed were within WHO permissible limits while the metals concentrations were also observed to decrease as depth was increased. Using ArcGIS 10.2.2, spatial maps showing heavy metal distribution were developed, with the Kriging method proving superior. This study suggests that heavy metal levels in the soil at the area be monitored on a regular basis.

Laser-induced graphene electrochemical sensor for quantitative detection of phytotoxic aluminum ions (Al3+) in soils extracts

Aluminum in its Al3+ form is a metal that inhibits plant growth, especially in acidic soils (pH < 5.5). Rapid and accurate quantitative detection of Al3+ in agricultural soils is critical for the timely implementation of remediation strategies. However, detecting metal ions requires time-consuming preparation of samples, using expensive instrumentation and non-portable spectroscopic techniques. As an alternative, electrochemical sensors offer a cost-effective and minimally invasive approach for in situ quantification of metal ions. Here, we developed and validated an electrochemical sensor based on bismuth-modified laser-induced graphene (LIG) electrodes for Al3+ quantitative detection in a range relevant to agriculture (1-300 ppm). Our results show a linear Al3+ detection range of 1.07-300 ppm with a variation coefficient of 5.3%, even in the presence of other metal ions (Pb2+, Cd2+, and Cu2+). The sensor offers a limit of detection (LOD) of 0.34 ppm and a limit of quantification (LOQ) of 1.07 ppm. We compared its accuracy for soil samples with pH < 4.8 to within 89-98% of spectroscopic methods (ICP-OES) and potentiometric titration. This technology's portability, easy to use, and cost-effectiveness make it a promising candidate for in situ quantification and remediation of Al3+ in agricultural soils and other complex matrices.

Toxic effects of atmospheric deposition in mining areas on wheat seedlings

Storage and transportation of coal, as well as operation of coal-fired power plants, produce amounts of metallic exhaust that may lead to different atmospheric environment in the overlapped areas of farmland and coal resource (OAFCR) environment. To investigate the effects of different atmospheric environment in the OAFCR region (north of Xuzhou) on wheat seedlings (AK-58), a box experiment was conducted and compared to an area far from the OAFCR (south of Xuzhou). The study revealed that (1) compared to the southern suburb of Xuzhou, the fresh and dry weight, activities of photosynthetic enzymes and POD of wheat seedlings in the OAFCR reduced obviously. (2) Significantly higher levels of Cr, Cd, Pb, Zn, and Cu were found in the shoots and roots of wheat seedlings in the OAFCR, with lower transfer factor for heavy metals (except Cd and As) in comparison to those in the southern suburb. And the bioconcentration factors of heavy metals (except As) in wheat seedlings in the OAFCR were significantly higher. (3) Nearly 90% of heavy metals (Pb, Cu, Cd, Zn, and Cr) absorbed by wheat were stored in cell walls and soluble fractions, with significantly higher contents of Cu and Cr in wheat seedlings' cell walls and higher contents of Pb, Zn, and Cd in soluble components found in the OAFCR. Our results showed that atmospheric deposition in the mining area has a certain toxic effect on wheat seedlings, and this study provides a theoretical basis for OAFCR crop toxicity management.

A machine learning strategy-incorporated BiFeO3/Ti3C2 MXene electrochemical platform for simple, rapid detection of Pb2+ with high sensitivity

The electrochemical technique has been increasingly used for the detection of heavy metal ions in the water system. However, the process for determining the optimum experimental conditions was cumbersome, time-consuming, and unsynchronized, resulting in unsatisfactory detection efficiency. Herein, a new machine learning (ML) strategy combined with BiFeO3/Ti3C2 MXene (BiFeO3/MXene) was used to fabricate a simple but efficient electrochemical Pb2+ sensor. The interconnected BiFeO3/MXene composites prepared by a hydrothermal method possessed an interconnected conductive framework, abundant active sites, and a large surface area, which gave them excellent electronic conductivity and high accumulation of Pb2+. Meanwhile, ML methods such as back-propagation artificial neural network (BPANN) and genetic algorithm (GA) combined with orthogonal experimental design (OED) were used to optimize sensor parameters such as the pH of the supporting electrolyte, the BiFeO3/MXene content, deposition potential, and deposition time. Compared with OED and the one factor at a time (OFAT) methods, the OED-ML method greatly simplified the experimental procedures and improved the electrochemical detection performance. The developed sensor showed superior detection performance for Pb2+ with a detection limit of 0.0001 μg L-1 using the OED-ML method, which was much lower than that of the OED and OFAT methods (0.0003 μg L-1). In addition, the sensor showed good repeatability, reproducibility, stability, and interference capability. The feasibility of the method was verified by detecting Pb2+ in lake samples with recoveries ranging from 98.79% to 101.3%. To our knowledge, the ML strategy was introduced for the first time in an electrochemical sensor for Pb2+ detection, which proved the feasibility and practicality of ML.

Open acid dissolution-Ammonia solution extraction-ICP OES rapid determination of 7 trace metal elements in soil

To overcome the corrosion of hydrofluoric acid on the ICP OES injection system in the acid dissolution system, this paper makes some improvements based on the traditional open digestion. The improved method does not require the complete removal of hydrofluoric acid. After appropriate digestion of the sample with a mixed acid, the solution can be transferred to a colorimetric tube containing ammonium hydroxide solution to give the final volume for analysis. In this paper, two-point standard curves are plotted using soil standards and process blanks, which is not only convenient but also overcomes the interference of the matrix effect. Through continuous experiments, the preferred ratio of mixed acid is 3 mL nitric acid + 5 mL hydrofluoric acid, and the concentration of ammonia solution is 0.5%. The spectral lines of the measured elements V (292.4), Cr (283.5), Co (228.6), Ni (231.6), Cu (324.7), Zn (213.8) and Pb (220.3) were determined. The method quantification limits of the seven measured elements V, Cr, Co, Ni, Cu, Zn and Pb were 0.909, 4.32, 0.269, 0.261, 0.968, 3.69 and 2.64 μg g-1, respectively, and the precision was 3.5%, 5.2%, 4.8%, 2.4%, 6.1% and 4.5%, respectively. After processing six national standard materials according to the experimental method, the measured values of each measured element were basically in agreement with the certified values, indicating that this method is fully feasible for the measurement of V, Cr, Co, Ni, Cu, Zn and Pb in soil. This method greatly improves the efficiency of pretreatment and is particularly suitable for analysing large batches of samples.

In-situ growth of porous rod-like tungsten oxide for electrochemical determination of cupric ion

Preconcentration can effectively enhance the detection performance of electrodes in the electrochemical detection of heavy metal ions, but it also presents challenges for real-time monitoring. Several attempts have been made to optimize preconcentration by improving the adsorption capacity or detection mechanism of the electrode. The valence transfer of tungsten oxide between W5+/W6+ can participate in the reduction between the electrode material and heavy metal ions, playing a role in preconcentration to some extent. Therefore, we developed a WO3/SSM electrochemical sensor for the detection of Cu(II) that utilizes the valence variation property of WO3. The crystallinity and microstructure of the WO3/SSM electrode can be regulated by controlling the deposition parameters, and we prepared three types of WO3/SSM with different morphologies to identify the influence of the electrochemical effective surface area. The proposed electrode shows high performance as a Cu(II) sensor under short preconcentration time (60 s), with an excellent sensitivity of 14.113 μA μM-1 cm-2 for 0.1-10.0 μM and 4.7356 μA μM-1 cm-2 for 10.0-20.0 μM. Overall, the combined effect of morphology and valence transfers shortens the preconcentration time and optimizes preconcentration while ensuring excellent electrode performance. This WO3/SSM electrode is expected to drive great advances in the application of tungsten oxide in the electrochemical detection of heavy metal ions.

A comparative study of different methods for the determination of cadmium in various tissues of ramie (Boehmeria nivea L.)

Remediation of cadmium (Cd) pollution is one of the priorities of global environmental governance and accurate detection of Cd content is a key link in remediation of Cd pollution. This study aimed to compare three methods (inductively coupled plasma optical emission spectrometry (ICP-OES), inductively coupled plasma mass spectrometry (ICP-MS), and graphite furnace-atomic absorption spectrometry (GF-AAS)) for the determination of Cd with different tissues of various ramie varieties, and distinguish the advantage and disadvantage of each method. In total, 162 samples of ramie (Boehmeria nivea L.), which is an ideal plant for heavy metal remediation, were detected and the results showed that the three methods were all suitable for the de-termination of Cd content in ramie. ICP-OES and ICP-MS were simpler, faster, and more sensitive than GF-AAS. ICP-MS could be recommended for the determination of samples with various concentrations of Cd. ICP-OES could be used for measurement of samples with > 100 mg/kg Cd content, while GF-AAS was suitable for the detection of samples with very high (> 550 mg/kg) or very low (< 10 mg/kg) Cd content. Overall, considering the accuracy, stability, and the cost of measurement, ICP-MS was the most suitable method for determination of Cd content. This study provides significant reference information for the research in the field of Cd pollution remediation.

Determination of Heavy Metal Ions in Infant Milk Powder Using a Nanoporous Carbon Modified Disposable Sensor

Due to the risk of heavy metal pollution in infant milk powder, it is significant to establish effective detection methods. Here, a screen-printed electrode (SPE) was modified with nanoporous carbon (NPC) to detect Pb(II) and Cd(II) in infant milk powder using an electrochemical method. Using NPC as a functional nanolayer facilitated the electrochemical detection of Pb(II) and Cd(II) due to its efficient mass transport and large adsorption capacity. Linear responses were obtained for Pb (II) and Cd(II) in the range from 1 to 60 µg L^-1 and 5 to 70 µg L^-1, respectively. The limit of detection was 0.1 µg L^-1 for Pb(II) and 1.67 µg L^-1 for Cd(II). The reproducibility, stability, and anti-interference performance of the prepared sensor were tested as well. The heavy metal ion detection performance in the extracted infant milk powder shows that the developed SPE/NPC possesses the ability to detect Pb(II) and Cd(II) in milk powder.

Ecological evaluation of heavy metal pollution in the soil of Pb-Zn mines

Soil heavy metal pollution evaluations are a necessary measure for mine ecological control projects. In this study, the heavy metals Pb, Zn and Cd were studied in mining areas, tailings areas, sewage plant areas, residential areas, reclamation areas, and farmland areas. Soil pollution assessments of lead-zinc ore mine soils in the countryside of China are performed based on the index of geoaccumulation (I_geo) and the improved analytic hierarchy process (AHP). Finally, the pollution sources were analyzed by positive matrix factorization (PMF). The I_geo for the heavy metals Pb, Zn and Cd in the mining area reached 5.20, 3.34, and 5.66, respectively. In addition, 80 and 65% of the mining area and tailings area reached extremely strong pollution, respectively. The numerical simulation predicts that the pollution hazard in the southeast of the mine is high and that the pollution is concentrated. The severity of soil pollution in mines derived by the index of improved analytic hierarchy process (P_AHP) was as follows: mining area (70.80) > sewage plant area (35.57) > tailings area (30.64) > farmland area (28.40) > residential area (21.11) > reclamation area (10.06). Among the three categories of pollution sources, one includes reclamation area, farmland area and tailings area; one includes sewage plant area and residential area; and one includes mining area. The source contribution of Pb by the phenomenon of indiscriminate discharge of wastewater after ore smelting was as high as 90.4%; The contribution of the blind mining and tailings piling phenomenon of mines to the source of heavy metals Zn and Cd was 81.4 and 90.2%, respectively. This study proposes a reliable scientific method and technical method for evaluating mine soil pollution and provides a guiding basis for mine development and protection.

Ag-decorated polymer chip for the determination of the respective concentrations of TTD and Hg2+ by surface-enhanced raman scattering

A “hotspot”-rich Ag-nanoparticle-decorated three-dimensional polymer substrate was fabricated, exhibiting an excellent surface-enhanced Raman scattering (SERS) activity.

Fabrication of a light-responsive polymer nanocomposite containing spiropyran as a sensor for reversible recognition of metal ions

Poly(spiropyran ethylacrylate-co-glycidyl methacrylate) grafted onto the surface of modified TiO2 (TiO2-g-P(SPEA-co-GMA)) as a novel stimuli-responsive polymer was fabricated and employed as sensor for reversible recognition of metal ions.

Ion-selective membrane modified microfluidic paper-based solution sampling substrates for potentiometric heavy metal detection

Ion-selective membrane modified paper substrates were used to control the unfavourable super-Nernstian response of Pb2+-ISEs when coupled with microfluidic paper-based solution sampling.