Application of Portable X-ray fluorescence in the in-situ Testing of Heavy Metals in Historic Lead-Zinc Smelting Area in Yungui Plateau of China

doi:10.21203/rs.3.rs-3015324/v1

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Application of Portable X-ray fluorescence in the in-situ Testing of Heavy Metals in Historic Lead-Zinc Smelting Area in Yungui Plateau of China

https://doi.org/10.21203/rs.3.rs-3015324/v1

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Purpose Which kind of elements could be determined by the portable X-ray Fluorescence (PXRF) analyzer in field conditions? How about the accuracy of the results? It is necessary to conduct some researches in order to well understand the application of PXRF which is regarded as a new kind of in-situ measurement method.

Methods A set of 221 farmland soil samples were collected within a basin once it has been a lead-zinc smelting base. PXRF was used for field detection at all sample sites, then the soil samples were brought back to the laboratory to be analyzed again by atomic absorption spectrometry (AAS), paired T test and linear regression were conducted to analyze the difference and correlation between the result of PXRF and AAS methods.

Results There was little difference and high correlation between PXRF and AAS methods, indicating that in field conditions PXRF can effectively predict the concentrations of Pb and Zn in soil. Although there were some differences in the determinationresults of Cu, the pollution level of Cu in this study area still could be predicted. Unfortunately, PXRF method had large errors in the determination of Cd and Cr, so it was not suitable for the in-situ determination of Cd and Cr in this study area.

Conclusion The concentrations of Pb and Zn in the soil of lead-zinc smelting area can be accurately monitored by PXRF, while concentrations of Cu in soil can also be predicted by PXRF in the less accuracy level, Cd and Cr should not be monitored by PXRF.

Earth and environmental sciences/Environmental sciences

Earth and environmental sciences/Natural hazards

Physical sciences/Chemistry

XRF

in-situ

heavy metals

lead-zinc mining area

ferralsol

In the course of continuous development of industrial technology, a lot of waste produced in industrial activities has been discharged into farmland and environment, which has resulted in soil pollution. This is also a serious environmental problem in China which should be controlled (Adnan et al. 2022). In the long run, the mining and smelting of ore will go on so that heavy metals will still be released into environments, this is the main source of heavy metal pollution in the ecosystem in mining area. Pb, Cd, mercury (Hg) and other elements are toxic even if the absolute concentration is in fairly low level (Jiang et al. 2021). Measurement is the first step to well understand the soil pollution in farmland, many scholars have conducted quite a number of research on the determination methods. At present, the laboratory analysis methods for element determination mainly include induced coupled plasma optical emission spectrometry (ICP-OES) (Oyourou et al. 2019), induced coupled plasma mass spectrometry (ICP-MS) (Qu et al. 2019; Pena-Ortega et al. 2019), induced coupled plasma atomic emission spectrometry (ICP-AES) (Schneider et al. 2016; Moller et al. 2018; Wu et al. 2012), AAS (Hu et al. 2017), atomic fluorescence spectrometry (AFS) (Qu et al. 2018), and so on.

The first advantage of classic laboratory analysis for heavy metals is the high accuracy, but the high price of professional equipment and analytical reagents lead to high experimental cost (Mejia-Pina et al. 2016). Soil should be pretreated following complex processes such as sampling, drying, grinding and digestion, which takes a large amount of time (Lee et al. 2016). A variety of dangerous acids are inevitable, such as hydrochloric acid (HCl), nitric acid (HNO₃), hydrofluoric acid (HF), perchloric acid (HClO₄) and so on (Tian et al. 2018). Moreover, the acid frog and waste liquid produced in the test process are chemical pollutants in the environments (Nawar et al. 2019). So, it is necessary to find new methods which are rapid, economical and environmentally friendly. Meanwhile the kind of new methods are capable enough to provide content of heavy metal in soil samples (Pelegrino et al. 2019). X-ray Fluorescence (XRF) is competitive among these new methods, the basic principle of XRF is based on the excitement and emission rays of the atoms in soil sample (Schneider et al. 2016). Each individual atom emits characteristic spectrum when it is excited by external X-ray (Nawar et al. 2019), various elements are different in the wavelength of the emission ray which is excited by external X-ray, the identification and analysis of the excited spectrum allow to determine the composition and quantification of elements in the sample (Schneider et al. 2016). Ordinary X-ray fluorescence equipment is heavy, large and expensive, it should be installed inside the laboratory, a mass of ancillary facilities is also needed.

As a useful tool, PXRF analyzer can be used to quickly and easily determine concentrations of trace element in-situ. Some scholars have compared the PXRF determination method with various classic laboratory analysis methods, such as ICP-AES (Moller et al. 2018; Schneider et al. 2016; Wu et al. 2012), ICP-MS (Pena-Ortega et al. 2019; Qu et al. 2019) and AAS (Hu et al. 2017). It was found that the results measured by the PXRF correlated well with those obtained by the ICP-AES (Schneider et al. 2016) and ICP-OES (Oyourou et al. 2019). The PXRF method requires no chemical reagents so it is environment-friendly, with which a large amount of laboratory labor can be saved (Ruano et al. 2019). In recent years, PXRF has been well applied and developed by scholars in many research fields, such as biology, pharmacy, archaeology, geology, mining, environmental sciences et al (Weindorf et al. 2014). PXRF is also increasingly used on different kinds of samples, including soil, water and plant sample (Pelegrino et al. 2019).

PXRF can be divided into in-situ and ex-situ measurement. PXRF in-situ is generally slightly less accurate than PXRF laboratory measurements, but in-situ PXRF determination requires lower labor costs in soil sample pre-treatment (Qu et al. 2019; Qu et al. 2018). Some scholars have conducted rapid and real-time assessment of the environment quality involving heavy metal pollution they pointed out that the PXRF in-situ measurement method was lined with the PXRF laboratory measurement method, although the sensitivity of PXRF in-situ was a little lower, in most cases the results of PXRF in-situ measurement methods kept in a certain degree of accuracy (Higueras et al. 2012). The PXRF measurements under in-situ conditions may be affected by soil water content, soil porosity, soil particle size and so forth (Tian et al. 2018). Therefore, one of the most important considerations of sample preparation for PXRF analysis is particle size and uniformity (Frahm et al. 2016). Usually in-situ PXRF determination is affected by soil moisture and soil particle size which is hardly to thoroughly avoid in the actual field environments. But in-situ PXRF analysis could been greatly corrected with some technical skills (Qu et al. 2019). A study showed that water has a great effect on the accuracy of PXRF determination (Gu et al. 2019), compared to completely dry soil, the detected concentration of metal were reduced by approximately 1–3%, 23–30% and 30–39% when the water content was 10%, 15% and 20% respectively (Kim and Choi 2017), in other words the in-situ PXRF can provide reasonable result for dry soil.

In conclusion, PXRF had been widely used in various fields. The results of PXRF determination can be used to estimate the concentration of elements quickly and roughly on spot. In order to understand the application of PXRF in-situ measurement in plateau which have been polluted by heavy metals. Farmland soil samples were collected in lead-zinc smelting area in the plateau, detection of all samples was performed on site using a PXRF analyzer, and the AAS determination method as the representative laboratory analysis was also performed. The aim of this article is to explore the kind of heavy metal which can be determined by the PXRF, the test precision and accuracy were also be assessed. The conclusion of this article can enrich the research of the soil environmental quality monitoring, heavy metal pollution controlling, mining, land planning, utilization and regulation.

2.1 Research area

The research area consists of tillage land in a small mountain basin which is located in Northeastern Yunnan Province, the mean elevation of the mountain basin is 2099 m, the total area of the basin is 374.1 km². The research area locates in the south subtropical climate zone, the annual mean temperature is 12.6 ℃, and the annual mean monsoon precipitation is 847.1 mm. The typical kind of soil is ferralsol, the main crops in the basin are maize, potato, rice and broad bean. This basin is a main grain producing base, and the commercial crops mainly include tobacco, rape, peanut, pepper and so on. Lead-zinc ore near the basin is a part of famous Sichuan-Yunnan-Guizhou lead-zinc deposit belt. The history of metal smelting in the basin can be traced back to 2200 years ago. The modern smelt factory was established in January 1951. The production lasted more than 60 years when it was eternally terminated in June 2011. After the long period of lead-zinc production, the growth of plants around the smelter has been obviously confined.

2.2 Soil sampling, preparation and analysis

A plan of sampling was designed as the first step of this study, the precise positions of sample points were fixed with a 500 m × 500 m grid, and the exact location information of sample points were imported into the GPS set. 221 soil samples were collected from the basin in April 2022, the real position of all samples is shown in Fig. 1. In field, after tested by PXRF analyzer, 30 cm deep top layer of tillage soil was digged out then 1 kg soil was brought back into the laboratory for air drying. For each sample, appropriate amount of air-dried soil was fetched to be milled in a mortar, the soil should totally pass through two kinds of sifters, the sieve diameter of the sifters were 15 and 100 holes per inch, the treated soil was put into a self-sealed bag, sealed for testing.

2.2.1 Analysis with PXRF

The instrument used in this study was Sky-ray Explorer 9000 portable X-ray fluorescence analyzer. In order to check the performance of the instrument, before application in field three certified standard reference soils (GSD-11, GSD-12 and GSD-14) were measured with this analyzer. C_Pb, C_Zn, C_Cu, C_Cd and C_Cr (In this article, we refer to the heavy metal content in soil as C_{heavy metal} for short. For example, content of Pb in soil is called C_Pb for short.) were directly determined for 10 times, the duration was 60 seconds every time. It was found that the results of X-ray fluorescence are close to AAS, it means the analyzer worked very well.

In-situ determination with PXRF: following the guide of the GPS set, the location of the sample point in field was accurately found. The surface layer of the soil was pressed with a rubber hammer, a little plot of bran-new plastic film was used only one time to cover onto the surface of the front part of the instrument to keep the clean condition for probe. The probe of instrument was aligned at the plastic plot, the soil was screened for 60 seconds, C_Pb, C_Zn, C_Cu, C_Cd and C_Cr in the soil samples were determined simultaneously.

2.2.2 Analysis with AAS

Soil and sediment determination of copper, zinc, lead, nickel and chromium, Flame atomic absorption spectrophotometry (HJ 491-2019) (Ministry of Ecological Environment 2019)is a widely accepted industrial standard in China. According to this standard, C_Pb, C_Zn, C_Cuand C_Cr were analyzed following prescriptive steps. Analysis of Cd followed the steps of a national standard, the Soil quality — Determination of lead, cadmium — Graphite furnaceatomic absorption spectrophotometry (GB/T 17141-1997) (Ministry of Ecological Environment 1997).

The samples were pretreated so that all of the soil can pass through 100 mesh sieve, 0.2000 g of soil was weighed into a polytetrafluoroethylene crucible, the volume was 50 ml, purified water was dripped into the crucible to moisten the soil. l0 ml of HCl was added, the crucible was heated at 90 ℃ ~ 100 ℃ on an electric heating plate inside the fume hood to decompose the sample preliminarily. 9 ml HNO₃ was added when the digestion solution remained at 3 ml left, the crucible was covered and heated until there were no particles. 5 ~ 8 ml of HF was added, the crucible was uncapped and heated at 120 ℃ for 30 minutes. The crucible was moved away from the heating plate, 1 ml HClO₄ was added 5 minutes later when the solution was cool, then the crucible was still put back onto the heating plate at 150 ℃ ~ 170 ℃ until white smoke emitted. The most important operation is the crucible should be shaken frequently in the whole course of heating. If there was black carbide on the wall of the crucible, 1 ml HClO₄ was added, the crucible was caped and heated again until the black carbide disappeared. At last, the solution looked like several brown dewdrops in the bottom of the crucible. 3 ml HNO₃ was added, the soluble residue was transferred into a 25 ml volumetric bottle, the solution was diluted with 1% nitric acid to 25 ml volumetric.

2.2.3 Measurement of water content and pH

Measurement of the soil moisture content: soil samples were measured using gravimetric method. The aluminum boxes with soil sample were heated at 105 ℃ for more than 4 hours, the water lost could be assessed by the loss of total gravity.

Measurement of pH: 10 g soil in the size of 2 mm was added into a little glass cup, then 25 ml purified water without carbon dioxide was also added into the cup, the soil and the water were stirred with a glass robe, after 30 minutes pH of turbid liquid was measured with a pH meter (pH BJ-260, Shanghai, China).

2.3 Data analysis

According to the Soil environmental quality Risk control standard for soil contamination of agricultural land (GB15618-2018) (Ministry of Ecological Environment 2018), screening values and intervention values are important index in the management of soil environmental quality, so the content of heavy metals were divided into different groups. Statistical analysis was performed with the software of SPSS 19.0. To assess the accuracy of the data obtained by PXRF analyzer, Paired T-test method was applied for each element to compare the index obtained by the PXRF analyzer with those by AAS. The linear regression model was applied to explore the relationship between the concentrations obtained by PXRF method in-situ and the concentrations measured by the AAS. R² was used as quality assessment for the following formula: y = ax + b . y is the PXRF concentration, x is the AAS concentration, b is the intercept of the regression line, and a is the slope.

3.1 Water content and pH

Water content in the soil had great influence on the results of PXRF determination. In this study PXRF in-situ measurement had been conducted in spring, it is the dry season in study area. The maximum of water content was 10.60%, the minimum was 3.37%, the mean content was 5.05% in 221 soil samples. Compared to completely dry soil, the test value of metal content was reduced by approximately 1-3% when the water content in soil was 10% (Kim and Choi 2017). In this study, the maximum value of pH was 8.14% while the minimum value was 4.34%. More than 75% of pH values were less than 6.5, the mean was 5.92, so the soil in this study area was weakly acidic generally.

3.2 Contents of heavy metals measured with PXRF and AAS

The mean, minimum, maximum and standard deviation value of PXRF and AAS methods are shown in Table 1.

Table1 The comparison of the AAS measurements and PXRF in-situ measurement

Using the method of PXRF in-situ, the measured maximum C_Pb is 4585.80 mg kg^-1, minimum value is 18.38 mg kg^-1, and the mean value is 408.67 mg kg^-1. Using the method of AAS in lab, the maximum C_Pb is 5140.18 mg kg^-1, minimum value is 19.73 mg kg^-1, and the mean value is 432.24 mg kg-¹. The standard deviation (SD) of two methods are 598.64 and 657.91, there are significant different when the two maximum values are compared, but the minimum values, the mean value and the SD are not significant different between two methods.

By the PXRF in-situ method, the maximum of C_Zn is 6179.84 mg kg^-1, the minimum is 60.01 mg kg^-1, and the mean value is 786.35 mg kg^-1. When the C_Zn is measured using AAS method, the maximum value is 9783.04 mg kg^-1, the minimum value is 124.58 mg kg^-1, and the mean value is 869.24 mg kg^-1. The SD of two methods are 959.33 and 1099.43. There are some differences between the entire range and mean value of Zn between two methods. The result of PXRF in-situ method is lower.

When the C_Cu is measured using PXRF in-situ method, in 221 soil samples the maximum value is 255.31 mg kg^-1, minimum value is 2.16 mg kg^-1, and the mean value is 176.73 mg kg^-1. With the AAS measurement method, the maximum value of C_Cu is 292.14 mg kg^-1, minimum value is 118.00 mg kg^-1, and the mean value is 209.80 mg kg^-1. The SD of two methods are 44.48 and 36.02. There is difference in the minimum values. In summary, the values of PXRF in-situ method are lower than those of the method of AAS. The SD of AAS method is lower.

When C_Cd is measured using PXRF in-situ method, the maximum value in 221 soil samples is 0.55 mg kg^-1, the minimum value is 0.03 mg kg^-1, and the mean value is 0.11 mg kg^-1. By the AAS method, the maximum of C_Cd is 40.00 mg kg^-1, minimum value is 2.32 mg kg^-1, and the mean value is 8.64 mg kg^-1. The SD of two methods are 0.06 and 5.87. Thus, the result using PXRF in-situ method is a great error unfortunately.

C_Cr is measured using PXRF in-situ method, in 221 soil samples the maximum value is 316.91 mg kg^-1, minimum value is 37.21 mg kg^-1, and the mean value is 208.52 mg kg^-1. In the AAS method measurement, maximum value of C_Cr is 247.22 mg kg^-1, minimum value is 84.51 mg kg^-1, and the mean value is 134.70 mg kg^-1. The SD of two methods are 41.18 and 24.79. Cr is different from the other elements, as the maximum content value, mean value and SD of PXRF in-situ measurement method are higher than AAS method.

3.3 Comparison between the results of PXRF and ASS

In this study, the top layer soil was measured by the PXRF analyzer in field condition, then the same soil sample was carried into the lab to be analyzed again by AAS instrument. Is there some difference between two methods? It is necessary to conduct the paired T-tests. In Table 2, P values of Pb (0.65) and Zn (0.12) are both greater than the significant level of 0.01. It indicates that there is no significant difference between methods of PXRF and AAS. P value of Cu, Cd and Cr are less than 0.01, so the results of Cu, Cd, Cr are extremely significant different between two methods.

Table2 Paired T-tests for the AAS and the PXRF in-situ determination methods

In order to easily understand the difference between two methods, the following violin map is drawn with OriginPro 2021. It can be clearly found from Fig. 2 that the overall trend of the data is consistent when Pb and Zn are analyzed using two different methods. However, C_Pb and C_Zn are higher in AAS method, there is a certain difference between two methods. The difference is that the C_Cu obtained by PXRF is lower, there is a big difference between two methods. It can be seen in the figure that there is no any trend between the results of two methods for element of Cd. The results of Cr in two methods are also very different.

3.4 Relationship between the results of PXRF and ASS

For C_Pb, C_Zn and C_Cu the linear regression analysis between results of AAS and PXRF are shown in Fig. 3. The determination coefficient (R²) of Pb is 0.92, and the slope of regression equation is close to 1 (a = 0.87). There is a strong association between results of PXRF in-situ measurement and AAS measurement. The R²of Zn by PXRF in-situ measurement and AAS measurement is 0.80, and the slope of regression equation is also close to 1 (a = 0.78). It shows there is a great correlation in two measurement methods for Zn. The R²of Cu is 0.45 in the linear regression analysis, the results indicate that the linear relationship between two methods is poor. The R² of Cd and Cr are 0.11 and 0.007, so there is relatively poor linear equation for Cd and Cr. In other words, the linear regression formulas of Cd and Cr are meaningless.

In order to test the linear relationship between the dependent variable y (PXRF method) and the independent variable x (AAS method), regression coefficient F test was conducted. The significance of C_Pb, C_Zn, C_Cu is nearly zero, and all the significant value are less than 0.01. Therefore, the linear regression relationship of Pb, Zn, Cu between the determination method y by PXRF and the determination method x of AAS was very significant.

4.1 Soil contamination risk level

In order to assess the soil contamination risk level, there are two demarcation critical values in GB 15618 − 2018 (Ministry of Ecological Environment 2018) which is shown in Table 3, the critical values are also determined by the value of pH. The first value is screening value, it means if the content of a kind of heavy metal is above this value the plot should be monitored. The other value is intervention value, it means if the content is above this value, the management of the plot should be intervened by local government. In this study, the results of PXRF are divided into three risk levels based on the screening value and intervention value.

Table 3 Soil contamination risk level based on results of AAS and PXRF

C_Pb of more than 50% samples are between screening value and intervention value in the research area whatever using AAS or PXRF methods, the risk level of more than a half samples belonged to grade Ⅱ. C_Zn and C_Cu are mostly higher than screening values, so the total risk level belonged to grade Ⅱ. When using AAS methods, C_Zn of more than 98% soil samples are higher than screening value, and C_Cu of 100% soil is higher than screening value. When using PXRF methods, above 88% C_Zn of soil is above screening value, and 99.5% C_Cu is higher than screening value. Because of there is no Zn and Cu intervention values are given in national standard (GB15618 2018), so it can only be classified in the second grade that no matter how high the content in the soil sample is. In fact, mean value of Zn and Cu are both more than 4 times of the screening value when use AAS methods, so the classification about Zn and Cu base on the result of PXRF cannot accurately describe the pollution levels. Researches show that Pb, Zn and Cu are well predicted by the PXRF method. This finding in this article is similar to the study of Hu et al (2017).

C_Cd of all soil samples are higher than intervention value when using AAS, but when using PXRF method 98% C_Cd is below screening value. In this study area, 80% C_Cr by AAS method is lower than the screening value, and more than 90% C_Cr by PXRF method is between the screening value and the intervention value. The results of Cd and Cr obtained by the two methods are quite different from each other.

4.2 Influence of the absolute values on the measurement accuracy of PXRF method

With the continuous development of detection technology, PXRF was gradually used in various research fields. In order to verify the accuracy and detection range of PXRF when it was used on heavy metal polluted soil in lead-zinc smelting area in this study, classic AAS laboratory analysis was also conducted as a reference. According to the results of paired T-test, it can be found that there was just a little difference between AAS and PXRF determination results of Pb and Zn elements, and there was strong correlation between the two methods for these two elements. On the contrary the results of Cu, Cd and Cr were different between two methods.

A research showed that there was excellent regression when content of Pb was less than 2000 mg kg^− 1 as the results of PXRF was compared to ICP-AES (Rouillon and Taylor 2016). When content of Zn was less than 5000 mg kg^− 1, the regression line was close to y = x (Schneider et al. 2016). Compared to the laboratory analyzation, PXRF underestimated content of Cr, especially for the soil samples with higher concentrations (Schneider et al. 2016). This conclusion differs from that of this study, the usage of PXRF method would overestimate content of Cr may be due to the low content of Cr in this study area. PXRF could be used as an accurate field screening tool for the determination of Pb and Zn elements. With the development of proximity sensors, PXRF will be able to detect even more heavy metals, which indicates that the method had great potential.

4.3 Should AAS be replaced by PXRF?

There had been studies which investigated the effectiveness of in-situ PXRF in generating reliable measurements on soil Pb concentrations (Rouillon and Taylor 2016). Compared to traditional laboratory analysis, stronger linear correlations were obtained from in-situ PXRF determination for Zn and Cu (Tian et al. 2018; Wan et al. 2019), then Zn and Cu could be detected in a wider range (Tian et al. 2018). These conclusions were consistent with this paper. But in the determination of heavy metal content in greenhouse soil, no strong correlation was found between the PXRF and ICP-MS data of Pb, perhaps the reason is the narrow range of trace Pb in greenhouse soils (Tian et al. 2018). When the content of Cd in soil was low, the accuracy of repeated determination was also low (Rouillon and Taylor 2016).

The data of this study show that although caution should be exercised when comparing results obtained from different measurement techniques, PXRF was still capable of generating comparable data compared with those returned by accredited commercial laboratories (Rouillon and Taylor 2016). Therefore, PXRF can be used to determine the moderately and highly contaminated soil with Pb, Zn and Cu to strengthen soil management in areas contaminated by heavy metals.

4.4 How to avoid the influence of water in soil?

Water content was recognized as components which were likely influence result of concentration of elements in the samples of soil (Burlakovs et al. 2015). When the soil moisture content increased, the deviation of results also increased while the precision decreased (Schneider et al. 2016; Yang et al. 2016). When soil water content was high, sometime a noticeable layer of water covering the window of the instrument was often observed after the scanning was completed which led to a lower precision, poorer detection limit and lower accuracy (Sahraoui and Hachicha 2017). When the water content were 10%, 15% and 20% of soil, the measure results were 1%-3%, 23%-30%, and 30%-39% lower than dry soil respectively (Kim and Choi 2017). Researchers found that Cu and Zn were most likely affected by water content, Cr was not influenced by water content (Santana et al. 2019). Therefore, we chose dry season to measure and collect soil.

Soil environmental quality is assessed based on the content of heavy metals in China, in this study PXRF was considered as a kind of on spot analyze method to rapid monitor heavy metals, the performance of the instrument was studied on farmland soil samples in lead-zinc mining area, the results of PXRF were compared with AAS method. Then, we can securely draw two clearly conclusions:

(1) In this study, in-situ determination by PXRF analyzer can accurately detect the content of Pb and Zn, and the detection results just have little difference from results of AAS. When Cu is concerned, although there are some differences between the determination results and the laboratory results, the content of Cu in this study area can still be predicted by PXRF analyzer. However, the in-situ determination content of Cd and Cr by PXRF analyzer are different from result of laboratory, so Cd and Cr are not suitable determined by PXRF analyzer.

(2) PXRF instrument is more suit to detect the soil with excessive content of heavy metal, and the detection accuracy is low in relatively clean areas.

Acknowledgments

This paper is supported by National Natural Science Foundation of China (NSFC) under grant No. 41967024

Competing Interests: The authors have no relevant financial or non-financial interests to disclose.

Adnan M, Xiao B, Xiao P et al. (2022) Research Progress on Heavy Metals Pollution in the Soil of Smelting Sites in China. Toxics 10(5): 231. https://doi.org/10.3390/TOXICS10050231
Burlakovs J, Kaczala F, Orupold K et al. (2015) Field-portable X-ray fluorescence spectrometry as rapid measurement tool for landfill mining operations: comparison of field data vs. laboratory analysis. Int J Environ An Ch 95(7): 609–617. https://doi.org/10.1080/03067319.2015.1036865
Frahm E, Monnier G F, Jelinski N A et al. (2016) Chemical soil surveys at the Bremer Site (Dakota county, Minnesota, USA): Measuring phosphorous content of sediment by portable XRF and ICP-OES. J Archaeol Sci 75: 115–138. https://doi.org/10.1016/j.jas.2016.10.004
Gu R Y, Lei M, Chen T B et al. (2019) Impact of Soil Water on the Spectral Characteristics and Accuracy of Energy-Dispersive X-ray Fluorescence Measurement. Anal Chem 91(9): 5858–5865. https://doi.org/10.1021/acs.analchem.9b00201
Hu B F, Chen S C, Hu J et al. (2017) Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution. Plos One 12(2): e.0172438 https://doi.org/10.1371/journal.pone.0172438
Higueras P, Oyarzun R, Iraizoz J M et al. (2012) Low-cost geochemical surveys for environmental studies in developing countries: Testing a field portable XRF instrument under quasi-realistic conditions. J Geochem Explor 113: 3–12. https://doi.org/10.1016/j.gexplo.2011.02.005
Jiang L, Sun H, Peng T et al. (2021) Comprehensive evaluation of environmental availability, pollution level and leaching heavy metals behavior in non-ferrous metal tailings. J Environ Manage 290: 112639. https://doi.org/10.1016/j.jenvman.2021.112639
Kim S M, Choi Y (2017) Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data. Int J Env Res Pub He 14(6): 16, 654–654. https://doi.org/10.3390/ijerph14060654
Lee H, Choi Y, Suh J et al. (2016) Mapping Copper and Lead Concentrations at Abandoned Mine Areas Using Element Analysis Data from ICP-AES and Portable XRF Instruments: A Comparative Study. Int J Env Res Pub He 13(4): 384. https://doi.org/10.3390/ijerph13040384
Moller K M, Hartwell J G, Simon-Friedt B R, Wilson et al. (2018) Soil contaminant concentrations at urban agricultural sites in New Orleans, Louisiana: A comparison of two analytical methods. J Agric Food Syst Co 8(2): 139–149. https://doi.org/10.5304/jafscd.2018.082.010
Mejia-Pina K G, Huerta-Diaz M A, Gonzalez-Yajimovich O (2016) Calibration of handheld X-ray fluorescence (XRF) equipment for optimum determination of elemental concentrations in sediment samples. Talanta 161: 359–367. https://doi.org/10.1016/j.talanta.2016.08.066
Ministry of Ecological Environment (2019) Soil and sediment-Determination of copper, zinc, lead, nickel and chromium—Flame atomic absorption spectrophotometry (HJ491-2019). (in Chinese)
Ministry of Ecological Environment (1997) Soil quality-Determination of lead, cadmium-Graphite furnace atomic absorption spectrophotometry (GB/T17141-1997). (in Chinese)
Ministry of Ecological Environment (2018) Soil environmental quality Risk control standard for soil contamination of agricultural land (GB 15618–2018). (in Chinese)
Nawar S, Delbecque N, Declercq Y et al. (2019) Can spectral analyses improve measurement of key soil fertility parameters with X-ray fluorescence spectrometry? Geoderma 350: 29–39. https://doi.org/10.1016/j.geoderma.2019.05.002
Oyourou J N, McCrindle R, Combrinck S et al. (2019) Investigation of zinc and lead contamination of soil at the abandoned Edendale mine, Mamelodi (Pretoria, South Africa) using a field-portable spectrometer. J S Afr I Min Metall 119(1): 55–62. https://doi.org/10.17159/2411-9717/2019/v119n1a7
Pena-Ortega M, Del Rio-Salas R, Valencia-Sauceda J et al. (2019) Environmental assessment and historic erosion calculation of abandoned mine tailings from a semi-arid zone of northwestern Mexico: insights from geochemistry and unmanned aerial vehicles. Environ Sci Pollut R 26(25): 26203–26215. https://doi.org/10.1007/s11356-019-05849-w
Pelegrino M H P, Weindorf D C, Silva S H G et al. (2019) Synthesis of proximal sensing, terrain analysis, and parent material information for available micronutrient prediction in tropical soils. Precis Agric 20(4): 746–766. https://doi.org/10.1007/s11119-018-9608-z
Qu M K, Chen J, Li W D et al. (2019) Correction of in-situ portable X-ray fluorescence (PXRF) data of soil heavy metal for enhancing spatial prediction. Environ Pollut 254: 112993. https://doi.org/10.1016/j.envpol.2019.112993
Qu M K, Wang Y, Huang B et al. (2018) Spatial uncertainty assessment of the environmental risk of soil copper using auxiliary portable X-ray fluorescence spectrometry data and soil pH. Environ Pollut 240: 184–190. https://doi.org/10.1016/j.envpol.2018.04.118
Ruano S M, Martin-Peinado F J, Molina C M E et al. (2019) A quick methodology for the evaluation of preliminary toxicity levels in soil samples associated to a potentially heavy-metal pollution in an abandoned ore mining site. Chemosphere 222: 345–354. https://doi.org/10.1016/j.chemosphere.2019.01.123
Rouillon M, Taylor M P (2016) Can field portable X-ray fluorescence (pXRF) produce high quality data for application in environmental contamination research? Environ Pollut 214: 255–264. https://doi.org/10.1016/j.envpol.2016.03.055
Schneider A R, Cances B, Breton C et al. (2016) Comparison of field portable XRF and aqua regia/ICPAES soil analysis and evaluation of soil moisture influence on FPXRF results. J Soil Sediment 16(2): 438–448. https://doi.org/10.1007/s11368-015-1252-x
Sahraoui H, Hachicha M (2017) EFFECT OF SOIL MOISTURE ON TRACE ELEMENTS CONCENTRATIONS USING PORTABLE X-RAY FLUORESCENCE SPECTROMETER. J Fundam Appl Sci 9(1): 468–484. https://doi.org/10.4314/jfas.v9i1.26
Santana M L T, Carvalho G S, Guilherme L R G et al. (2019) Elemental concentration via portable x-ray fluorescence spectrometry: Assessing the impact of water content. Cienc Agrotec 43. https://doi.org/10.1590/1413-7054201943029218
Tian K, Huang B, Xing Z et al. (2018) In situ investigation of heavy metals at trace concentrations in greenhouse soils via portable X-ray fluorescence spectroscopy. Environ Sci Pollut R 25(11): 11011–11022. https://doi.org/10.1007/s11356-018-1405-8
Wu C M, Tsai H T, Yang K H et al. (2012) How Reliable is X-Ray Fluorescence (XRF) Measurement for Different Metals in Soil Contamination? Environ Forensics 13(2): 110–121. https://doi.org/10.1080/15275922.2012.676603
Weindorf D C, Bakr N, Zhu Y D (2014) Advances in Portable X-ray Fluorescence (PXRF) for Environmental, Pedological, and Agronomic Applications. Adv Agron 128: 1–45. https://doi.org/10.1016/B978-0-12-802139-2.00001-9
Wan M X, Hu W Y, Qu M K et al. (2019) Application of arc emission spectrometry and portable X-ray fluorescence spectrometry to rapid risk assessment of heavy metals in agricultural soils. Ecol Indic 101: 583–594. https://doi.org/10.1016/j.ecolind.2019.01.069
Yang G L, Shang Z C, Li L J et al. (2016) Application of portable-XRF spectrometry for rapid determination of common heavy metals in soil. Applied Chemical Industry, 45(8): 1586–1591. (in Chinese) https://doi.org/10.16581/j.cnki.issn1671-3206.20160527.025

Tables 1 to 3 are available in the Supplementary Files section

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Application of Portable X-ray fluorescence in the in-situ Testing of Heavy Metals in Historic Lead-Zinc Smelting Area in Yungui Plateau of China

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Abstract

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1 Introduction

2 Materials and methods

3 Results and analysis

4 Discussion

4.1 Soil contamination risk level

4.2 Influence of the absolute values on the measurement accuracy of PXRF method

4.3 Should AAS be replaced by PXRF?

4.4 How to avoid the influence of water in soil?

5 Conclusions

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References

Tables

Additional Declarations

Supplementary Files

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