In China, the cadmium (Cd) levels in paddy fields have increased, which has led to the excessive uptake of Cd into rice grains. In this study, we determined the physicochemical properties of soil samples, including the pH, soil organic matter (SOM) content, cation exchange capacity (CEC), and total Cd content (Cdsoil) in order to establish a quadratic discriminant analysis (QDA) model for assessing the risk of Cd in rice and to calculate its prior probability. Decision tree and logistic regression models were also established for comparison. The results showed that the accuracy rate was 74% with QDA, which was significantly higher than that obtained using the decision tree (67%) and logistic regression (68%) models. The correlation coefficients between the soil pH and the other three factors (CEC, SOM, and Cdsoil) were higher in the inaccurate set than the accurate set, whereas the correlation coefficients were smaller in the inaccurate set than the accurate set.

Effects of photochemical and microbial degradation on variations in composition and molecular-size of dissolved organic matter (DOM) from different sources (algal and soil) and the subsequent influence on Cu(II) binding were investigated using UV–Vis, fluorescence excitation-emission matrices coupled with parallel factor analysis, flow field-flow fractionation (FlFFF), and metal titration. The degradation processes resulted in an initial rapid decline in the bulk dissolved organic carbon and chromophoric and fluorescent DOM components, followed by a small or little decrease. Specifically, photochemical reaction decreased the aromaticity, humification and apparent molecular weights of all DOM samples, whereas a reverse trend was observed during microbial degradation. The FlFFF fractograms revealed that coagulation of both protein- and humic-like DOM induced an increase in molecular weights for algal-DOM, while the molecular weight enhancement for allochthonous soil samples was mainly attributed to the self-assembly of humic-like components. The Cu(II) binding capacity of algal-derived humic-like and fulvic-like DOM consistently increased during photo- and bio-degradation, while the soil-derived DOM exhibited a slight decline in Cu(II) binding capacity during photo-degradation but a substantial increase during microbial degradation, indicating source- and degradation-dependent metal binding heterogeneities. Pearson correlation analysis demonstrated that the Cu(II) binding potential was mostly related with aromaticity and molecular size for allochthonous soil-derived DOM, but was regulated by both DOM properties and specific degradation processes for autochthonous algal-derived DOM. This study highlighted the coupling role of inherent DOM properties and external environmental processes in regulating metal binding, and provided new insights into metal-DOM interactions and the behavior and fate of DOM-bound metals in aquatic environments.

With the rapid development of urbanization and industrialization, the peri-urban areas are often the sites for waste dumps, which may exacerbate the occurrence and spread of antibiotic resistance from waste to soil bacteria. However, the profiles of antibiotic resistomes and the associated factors influencing their dissemination in peri-urban areas have not been fully explored. Here, we characterized the antibiotic resistance genes (ARGs) in peri-urban arable and pristine soils in four seasons at the watershed scale, by using high-throughput qPCR. ARGs in peri-urban soils were diverse and abundant, with a total of 222 genes were detected in the peri-urban soil samples. The arable soil harbored more diverse ARGs compared to the pristine soils, and nearly all the ARGs detected in the pristine soils were also detected in the farmlands. A random forest prediction showed that the overall patterns of ARGs clustered closely with the landuse type. Mantel test and partial redundancy analysis indicated that bacterial community variation is a major contributor to antibiotic resistome alteration. Significant positive correlation was found between the abundance of ARGs and mobile genetic elements (MGEs), suggesting potential mobility of ARGs in peri-urban areas. Our results extend knowledge of the resistomes compositions in peri-urban areas, and suggest that anthropogenic activities driving its spatial and temporal distribution.

To explore the effect of elevated CO₂ concentrations ([CO₂]) on phosphine formation in paddy fields, the matrix-bound phosphine (MBP) content, different phosphorus fractions and various carbon forms in soil samples from rice cultivation under varying CO₂ concentrations of 400 ppm, 550 ppm and 700 ppm by indoor simulation experiment were determined. This study showed that MBP concentration did not increase significantly with elevated [CO₂] over four-week cultivation periods of rice seedlings, regardless of soil layers. MBP had a significant positive correlation with total phosphorus (TP) and inorganic phosphorus (IP), and multiple stepwise linear regression analysis further indicated that MBP preservation in neutral paddy soils with depths of 0–20 cm may have been due to conversion from FeP and CaP. Based on redundancy analysis and forward selection analysis, speculated that the formation of MBP in the neutral paddy soils as the response to atmospheric elevated [CO₂] was due to two processes: (i) FeP transformation affected by the changes of soil respiration (SCO₂) and TOC was the main precursor for the production of MBP; and (ii) CaP transformation resulting from variation in HCO₃⁻ was the secondary MBP source. The complex combination of these two processes is simultaneously controlled by SCO₂. In a word, the soil environment in the condition of elevated [CO₂] was in favor of MBP storage in neutral paddy soils. The results of our study imply that atmospheric CO₂ participates in and has a certain impact on the global biogeochemical cycle of phosphorus.

The use of reclaimed wastewater for irrigation is foreseen as a possible strategy to mitigate the pressure on water resources in dry regions. However, there is the risk of potential accumulation of contaminants of emerging concern (CECs) in the edaphic environment, their percolation and consequently contamination of aquifers. In the present study, we measured the levels of a wide range of commonly used pharmaceutically active compounds (PhACs) in sewage from a local wastewater treatment plant (WWTP) and in soils irrigated with treated wastewater. Analysis of target compounds showed total concentrations between 73 and 372 μg L⁻¹ in WWTP influents, and from 3 to 41 μg L⁻¹ in effluents. The total concentrations of PhACs detected in surface soil samples were in the range of 2 and 15 ng g⁻¹, with predominance of analgesics and anti-inflammatories (maximum concentration = 10.05 ng g⁻¹), followed by antibiotics and psychiatric drugs (maximum concentration = 5.45 ng g⁻¹ and 3.78 ng g⁻¹, respectively). Both effluent samples and irrigated soils shared similar compositional patterns, with compounds such as hydrochlorothiazide and diclofenac being predominant. Additionally, PhACs were also detected in soil samples at a depth of 150 cm, indicating that these chemical undergo leaching associated with heavy-rain episodes. Their occurrence in soils was affected by temperature too, as maximum concentrations were measured in colder months (up to 14 ng g⁻¹), indicating higher persistence at lower temperatures. Finally, the ecotoxicological risk of PhACs in soil was evaluated by calculating their risk quotients (RQs). The risk was very low as RQ values ranged between <0.01 and 0.07. However, this initial assessment could be improved by future works on toxicity using specific terrestrial organisms.

Hyperspectral imaging technology has been investigated as a possible way to detect microplastics contamination in soil directly and efficiently in this study. Hyperspectral images with wavelength range between 400 and 1000 nm were obtained from soil samples containing different materials including microplastics, fresh leaves, wilted leaves, rocks and dry branches. Supervised classification algorithms such as support vector machine (SVM), mahalanobis distance (MD) and maximum likelihood (ML) algorithms were used to identify microplastics from the other materials in hyperspectral images. To investigate the effect of particle size and color, white polyethylene (PE) and black PE particles extracted from soil with two different particle size ranges (1–5 mm and 0.5–1 mm) were studied in this work. The results showed that SVM was the most applicable method for detecting white PE in soil, with the precision of 84% and 77% for PE particles in size ranges of 1–5 mm and 0.5–1 mm respectively. The precision of black PE detection achieved by SVM were 58% and 76% for particles of 1–5 mm and 0.5–1 mm respectively. Six kinds of household polymers including drink bottle, bottle cap, rubber, packing bag, clothes hanger and plastic clip were used to validate the developed method, and the classification precision of polymers were obtained from 79% to 100% and 86%–99% for microplastics particle 1–5 mm and 0.5–1 mm respectively. The results indicate that hyperspectral imaging technology is a potential technique to determine and visualize the microplastics with particle size from 0.5 to 5 mm on soil surface directly.

Soil contamination due to atmospheric deposition of metals originating from smelters is a global environmental problem. A common problem associated with this contamination is the discrimination between anthropic and natural contributions to soil metal concentrations: In this context, we investigated the characteristics of soil contamination in the surrounding area of a world class smelter. We attempted to combine several approaches in order to identify sources of metals in soils and to examine contamination characteristics, such as pollution level, range, and spatial distribution. Soil samples were collected at 100 sites during a field survey and total concentrations of As, Cd, Cr, Cu, Fe, Hg, Ni, Pb, and Zn were analyzed. We conducted a multivariate statistical analysis, and also examined the spatial distribution by 1) identifying the horizontal variation of metals according to particular wind directions and distance from the smelter and 2) drawing a distribution map by means of a GIS tool. As, Cd, Cu, Hg, Pb, and Zn in the soil were found to originate from smelter emissions, and As also originated from other sources such as abandoned mines and waste landfill. Among anthropogenic metals, the horizontal distribution of Cd, Hg, Pb, and Zn according to the downwind direction and distance from the smelter showed a typical feature of atmospheric deposition (regression model: y = y0 + αe−βx). Lithogenic Fe was used as an indicator, and it revealed the continuous input and accumulation of these four elements in the surrounding soils. Our approach was effective in clearly identifying the sources of metals and analyzing their contamination characteristics. We believe this study will provide useful information to future studies on soil pollution by metals around smelters.

The determination of values of abundance of antibiotic resistance genes (ARGs) per mass of soil is extremely useful to assess the potential impacts of relevant sources of antibiotic resistance, such as irrigation with treated wastewater or manure application. Culture-independent methods and, in particular, quantitative PCR (qPCR), have been regarded as suitable approaches for such a purpose. However, it is arguable if these methods are sensitive enough to measure ARGs abundance at levels that may represent a risk for environmental and human health. This study aimed at demonstrating the range of values of ARGs quantification that can be expected based on currently used procedures of DNA extraction and qPCR analyses. The demonstration was based on the use of soil samples spiked with known amounts of wastewater antibiotic resistant bacteria (ARB) (Enterococcus faecalis, Escherichia coli, Acinetobacter johnsonii, or Pseudomonas aeruginosa), harbouring known ARGs, and also on the calculation of expected values determined based on qPCR.The limits of quantification (LOQ) of the ARGs (vanA, qnrS, blaTEM, blaOXA, blaIMP, blaVIM) were observed to be approximately 4 log-units per gram of soil dry weight, irrespective of the type of soil tested. These values were close to the theoretical LOQ values calculated based on currently used DNA extraction methods and qPCR procedures. The observed LOQ values can be considered extremely high to perform an accurate assessment of the impacts of ARGs discharges in soils. A key message is that ARGs accumulation will be noticeable only at very high doses. The assessment of the impacts of ARGs discharges in soils, of associated risks of propagation and potential transmission to humans, must take into consideration this type of evidence, and avoid the simplistic assumption that no detection corresponds to risk absence.

The concentrations of Cd, Cr and Pb in soil samples and As, Cd, Cr and Pb in plant specimens were analyzed in an arid area in central Iran. Plants were categorized into desert-adapted (Haloxylon ammodendron, Atraphaxis spinosa and Artemisia persica) and non-desert species. It was found that the trace element (TE) accumulating potential of the desert species (Haloxylon ammodendron and Artemisia persica) with a mean value of 0.1 mg kg⁻¹ for Cd was significantly higher than that of the majority of the non-desert species with an average of 0.05 mg kg⁻¹. Artemisia also had a high As accumulating capability with a mean level of 0.8 mg kg⁻¹ in comparison with an average of 0.2 mg kg⁻¹ for most of the other plant species. The mean values of Cr and Pb in Haloxylon ammodendron and Artemisia persica were 5 and 3 mg kg⁻¹, respectively. Among the desert-adapted plants, Atraphaxis proved to be a species with high Cr and Pb accumulating potential, as well. The geoaccumulation index and the overall pollution scores indicated that the highest environmental risk was related to Cd. Different statistical analyses were used to study the spatial patterns of soil Cd and their connections with pollution sources. The variogram was estimated using a classical approach (weighted least squares) and was compared with that of the posterior summaries that resulted from the Bayesian technique, which lay within the 95% Bayesian credible quantile intervals (BIC) of posterior parameter distributions. The prediction of cadmium values at un-sampled locations was implemented by multi-Gaussian kriging and sequential Gaussian simulation methods. The prediction maps showed that the region most contaminated by Cd was the north-eastern part of the study area, which was linked to mining activities, while agricultural influence contributed less in this respect.

Microplastics are emerging pollutants which have been extensively detected in water environments. However, little is known about microplastic pollution in soil environments. In this study, we investigated microplastics and mesoplastics in farmland soils from twenty vegetable fields around the suburbs of Shanghai. In each site, three duplicate soil samples were collected from shallow (0–3 cm) and deep soils (3–6 cm), respectively. Microplastics (sizes of 20 μm - 5 mm) and mesoplastics (5 mm - 2 cm) were detected using methods of density extraction, 30% H₂O₂ digestion and micro-fourier transform infrared spectroscopy. The abundance of microplastics was 78.00 ± 12.91 and 62.50 ± 12.97 items kg⁻¹ in shallow and deep soils, respectively. While, mesoplastics were found with abundance of 6.75 ± 1.51 and 3.25 ± 1.04 items kg⁻¹ in shallow and deep soils. Among these micro(meso)plastics, 48.79% and 59.81% were in size of <1 mm in shallow and deep soils. The main morphotypes of microplastics included fiber, fragment and film, mostly in color of black or transparent. Moreover, we found that topsoil contained higher concentrations and larger sizes of micro(meso)plastics than deep soil. In addition, the vast majority of micro(meso)plastics were polypropylene (50.51%) and polyethylene (43.43%). This study reveals occurrence and characteristics of microplastic pollution in typical farmland soils. It provides important data for subsequent research on microplatics in the terrestrial ecosystem.