X-ray fluorescence spectrometry for environmental analysis: Basic principles, instrumentation, applications and recent trends

Metal halide perovskite polymer composites for indirect X-ray detection

Metal halide perovskites (MHPs) have emerged as a promising class of materials for radiation detection due to their high atomic numbers and thus high radiation absorption, tunable and efficient luminescent properties and simple solution processability. Traditional MHP scintillators, however, suffer from environmental degradation, spurring interest in perovskite-polymer composites. This paper reviews recent developments in these composites tailored for scintillator applications. It discusses various synthesis methods, including solution-based and mechanochemical techniques, that enable the formation of composites with enhanced performance metrics such as light yield, detection limit, and environmental stability. The review also covers the remaining challenges and opportunities in fabrication techniques and performance metric evaluations of this class of materials. By offering a comprehensive overview of current research and future perspectives, this paper underscores the potential of perovskite-polymer composites to revolutionize the field of radiation detection.

Assessment of portable X-ray fluorescence (pXRF) for plant-available nutrient prediction in biochar-amended soils

Portable X-ray Fluorescence probe (pXRF) is a tool used to measure many elements quickly and efficiently in soil with minimal sample preparation. Although this sensing technique has been widely used to determine total elemental concentrations, it has not been calibrated for plant-available nutrient predictions. We evaluated the potential of using pXRF for fast plant-available nutrient quantification. Two experiments were conducted in soils treated with two types of biochars to obtain a practical range of soil pH (5.5 - 8.0) and organic carbon (2.0 - 5.5%). Biochars applied were derived from switchgrass (SGB) and poultry litter (PLB). The first experiment received biochars at application rates up to 8% (w/w) and had no plants. The second experiment had up to 4% of SGB or PLB planted with ryegrass (Lolium perenne). Linear regression (LR), polynomial regression (PolR), power regression (PowR), and stepwise multiple linear regression (SMLR) were the models tested. Regardless of the extraction method, phosphorus (P) showed a strong relationship between pXRF and several laboratory extraction methods; however, K prediction via pXRF was sensitive to the plant factor. The optimum soil available-P corresponding to the maximum P uptake in plant tissues can be assessed with pXRF. The LR was inconsistent for calcium (Ca), sulfur (S), and copper (Cu) and non-significant for magnesium (Mg), iron (Fe), and zinc (Zn). Our results showed that pXRF is applicable to estimate P availability in soils receiving organic amendments. More evaluations are needed with diverse soil types to confirm the findings before using pXRF for fertilizer recommendation.

Optimizing the development of contaminated land in China: Exploring machine-learning to identify risk markers

Often available for use, previously developed land, which includes residential and commercial/industrial areas, presents a significant challenge due to the risk to human health. China's 2018 release of health risk assessment standards for land reuse aimed to bridge this gap in soil quality standards. Despite this, the absence of representative indicators strains risk managers economically and operationally. We improved China's land redevelopment approach by leveraging a dataset of 297,275 soil samples from 352 contaminated sites, employing machine learning. Our method incorporating soil quality standards from seven countries to discern patterns for establishing a cost-effective evaluative framework. Our research findings demonstrated that detection costs could be curtailed by 60% while maintaining consistency with international soil standards (prediction accuracy = 90-98%). Our findings deepen insights into soil pollution, proposing a more efficient risk assessment system for land redevelopment, addressing the current dearth of expertise in evaluating land development in China.

Towards direct and eco-friendly analysis of plants using portable X-ray fluorescence spectrometry: A methodological approach

The assessment of the nutritional status of plants is traditionally performed by wet-digestion methods using oven-dried and ground samples. This process requires sampling, takes time, and it is non-environmentally friendly. Agricultural and environmental science have been greatly benefited by in-field, ecofriendly methods, and real-time element measurements. This work employed the portable X-ray fluorescence spectrometry (pXRF) to analyze intact and fresh leaves of crops aiming to assess the effect of water content and leaf surface (adaxial and abaxial) on pXRF results. Also, pXRF data were used to predict the real concentration of macro- and micronutrients. Eight crops (bean, castor plant, coffee, eucalyptus, guava tree, maize, mango, and soybean) with contrasting water contents were used. Intact leaf fragments (∼2 × 2 cm), fresh or oven-dried (60 °C) were obtained to be analyzed via pXRF on both adaxial and abaxial surface. Conventional wet-digestion method was also performed on powdered material to obtain the concentration of macro- and micronutrients via ICP-OES. The data were subjected to descriptive statistics, principal component analysis (PCA) and random forest (RF) algorithm regression. RF was used to predict the real concentration of macro- and micronutrients based on pXRF measurements obtained directly on intact leaves. Water content had a significant effect on pXRF results. However, a positive correlation between the concentration of macro- and micronutrients obtained via pXRF directly on intact leaves and conventional analysis performed on powdered samples was obtained. PCA analysis allowed a clear differentiation of crops based on elemental composition. The concentrations of macro- and micronutrients were very accurately predicted via RF. Even elements not detected by pXRF (N and B) were satisfactory predicted. From this pilot study, it is possible to concluded that pXRF is feasible for in-field assessment of nutritional status of plants. Further studies are needed to obtain specific and robust calibrations for each crop.

Rapid method of arsenic estimation in geological samples by WD-XRF using a novel concept of As-Pb concentration equivalence

The presence of arsenic in ground waters of many countries has been a subject of global concern due to its toxicity. Primary sources of arsenic are geogenic, i.e. weathering and erosion of rocks and soils containing arsenic. This paper presents a rapid method for determination of arsenic in solid geological samples by wavelength dispersive X-ray fluorescence spectrometer. To achieve the best LLD (lower limit of detection), the most intense X-ray fluorescence line Kα1,2 is preferably used for determination of elemental concentrations because it pertains to the most probable transition. But the greatest challenge in arsenic estimation is the serious line overlap of AsKα1,2 lines with the equi-energy PbLα1,2 lines. By using the conventional line overlap correction methods, uncertainty and detection limits in arsenic determination are degraded to an unacceptable degree in samples which contains high lead and low arsenic concentrations. The proposed method bypasses the line overlap issue in employing a novel concept of arsenic-lead concentration equivalence factor for the cumulative peak of AsKα1,2 and PbLα1,2 fluorescence lines. The constancy of this factor for all geological matrices facilitates arsenic determination in samples universally irrespective of matrix elements. For the method validation, 22 international certified reference materials have been analysed and the results proved to be propitious wherein only one value out of 22 determinations showed relative error more than 20% of the certified values. This attests to the high accuracy of the proposed method which can effectively determine arsenic below 5 mg/kg in the presence of high lead concentration up to 1000 mg/kg.

Pb speciation and elemental distribution in leeks by micro X-ray fluorescence and X-ray absorption near-edge structure

Vegetables are crucial to a human diet as they supply the body with essential vitamins, minerals, etc. Heavy metals that accumulate in plants consequently enter the food chain and endanger people's health. Studying the spatial distribution and chemical forms of elements in plant/vegetable tissues is vital to comprehending the potential interactions between elements and detoxification mechanisms. In this study, leek plants and soil from vegetable gardens near lead-zinc mines were collected and cultivated with 500 mg L-1 PbNO3 solutions for three weeks. Micro X-ray fluorescence was used to map the distribution of Pb and other chemical elements in leek roots, and X-ray absorption near-edge spectroscopy was used to assess the Pb speciation in leek roots and leaves. These findings demonstrated that Pb, Cu, Mn, Cr, Ti and Fe were detected in the outer rings of the root's cross section, and high-intensity points were observed in the epidermis. Zn, K and Ca, on the other hand, were distributed throughout the root's cross section. Leek root and leaf contained significant quantities of lead phosphate and basic lead carbonate at more than 80%, followed by lead sulfide (19%) and lead stearate (11.1%). The capacity of leek roots to convert ambient lead into precipitated lead and fix it on the root epidermis and other inner surfaces is a key mechanism for reducing the toxic effects of Pb.

Quantitative determination of heavy metal contaminants in edible soft tissue of clams, mussels, and oysters

Aquatic environments are important sources of healthy and nutritious foods; however, clams, mussels, and oysters (the bivalves most consumed by humans) can pose considerable health risks to consumers if contaminated by heavy metals in polluted areas. These organisms can accumulate dangerously high concentrations of heavy metals (e.g., Cd, Hg, Pb) in their soft tissues that can then be transferred to humans following ingestion. Monitoring contaminants in clams, mussels and oysters and their environments is critically important for global human health and food security, which requires reliable measurement of heavy-metal concentrations in the soft tissues. The aim of our present paper is to provide a review of how heavy metals are quantified in clams, mussels, and oysters. We do this by evaluating sample-preparation methods (i.e., tissue digestion / extraction and analyte preconcentration) and instrumental techniques (i.e., atomic, fluorescence and mass spectrometric methods, chromatography, neutron activation analysis and electrochemical sensors) that have been applied for this purpose to date. Application of these methods, their advantages, limitations, challenges and expected future directions are discussed.