Set Of Soil Samples Research Articles

Radionuclides' Dispersion from Coal-Fired Brick Kilns: Geo-Environmental Processes, Potential Risks and Management.

In order to investigate the distributions and possible dispersion mechanism(s) of naturally occurring radioactive materials (NORMs: 226Ra, 232Th, and 40K) from coal-based brick kilns, a systematic set (n = 60) of coal, ash, surface-soil, and subsurface soil samples were analyzed. High-quality analytical data of U, Th and K obtained from HPGe detector and TRIGA Mark-II research reactor-based neutron activation analysis were converted to the corresponding radioactivities. Average (n = 10) radioactivities of 226Ra, 232Th, and 40K in coal samples were 15.6, 16.7, and 145.5Bq.kg-1, respectively, where only 40K surpassed the corresponding global mean value. Average (n = 10) radioactivities of 226Ra, 232Th, and 40K in ash samples were 62.7, 88.5, and 521Bq.kg-1, respectively, where only 226Ra was within the established limit. In soil samples, average (n = 40) activities of 226Ra, 232Th, and 40K were 62.7, 95.1, and 641Bq.kg-1, respectively, which have surpassed the corresponding worldwide mean values. The observed differences in activity levels between soil samples collected near and far from the kilns, as well as between topsoil and subsoil samples, suggest the presence of distinct transport mechanisms for NORMs within the pedosphere. Dispersions of NORMs from the brick kilns to the ambient pedosphere are largely governed by aerodynamic convection and hydrodynamic leaching. These mechanisms are also influenced by geochemical mobility and relative solubility of NORMs, as well as factors such as rainfall patterns and wind-flow direction. Radiological indices invoke long-term carcinogenic-risks, whereas aerodynamic convection of finer particles (coal fly ash) from chimneys can cause significant health hazards to the nearby dwellers. Scientific processes as well as public awareness are essential to mitigate the risks.

Exchangeable acidity characteristics of farmland black soil in northeast China

Exchangeable aluminum (Exc-Al), an often overlooked yet indispensable soil parameter, predominantly contributes to soil exchangeable acidity. In this study, we utilized data from 53 sets of surface and subsurface black soil characteristics, including Exc-Al, exchangeable acid (Exc-acid), pH, soil organic matter (SOM), and available and total nutrient levels, to develop a neural network prediction model for estimating Exc-Al and Exc-acid in the black soil area of northeast China. The deterministic neural network model (NNM) was employed to predict Exc-Al and Exc-acid contents in 690 sets of surface and subsurface farmland soil samples with unknown Exc-Al and Exc-acid values. Subsequently, a black soil exchangeable acidity map for northeast China was generated through spatial interpolation. Our results revealed that the average Exc-Al and Exc-acid contents in the 53 surface soils were 0.82 and 0.93 cmol kg−1, respectively, while those in the corresponding subsurface soils were 0.58 and 0.70 cmol kg−1, respectively. Multi-layer perceptron (MLP) neural networks effectively simulated Exc-Al and Exc-acid contents in the surface and subsurface black soils, with calibrated determination coefficients (Radj2) of 0.95–0.96, relative root mean square errors (rRMSE) of 17.3%–24.8%, and statistical significance α at 0.001. The MLP estimations and spatial interpolations revealed that 2.0% and 17.6% of the surface black soil area, and 0% and 3.7% of the subsurface soil area exhibited Exc-Al content exceeding 2.0 and 1.0 cmol kg−1, respectively. Furthermore, 6.7% and 24.9% of the surface black soil area, and 0% and 6.3% of the subsurface soil area showed Exc-acid content exceeding 2.0 and 1.0 cmol kg−1, respectively. These findings break the limitation of relying solely on soil pH as the unique indicator, enrich our knowledge of black soil exchangeable acidity, and enhance our understanding of the black soil acidity status in northeast China.

Cumulative characteristics and ecological risk source analysis of soil potentially toxic elements in the northern margin of the Tibetan Plateau.

To understand the soil toxic and hazardous elements content, pollution level, and ecological risk status in the northern margin of the Tibetan Plateau, we collected and analyzed 8273 sets of surface soil samples. Evaluations were conducted using the single-factor pollution index, geo-accumulation, pollution load, and potential ecological risk indices, and source identification correlation and principal component analysis. The results revealed that, compared with the background levels in China, the accumulation of soil arsenic, cadmium, nickel, and chromium was greater in the surface soil of the study area. Additionally, in comparison with Qinghai Province, more mercury accumulated in the surface soil of the study area and owing to the influence of anthropogenic activities. Benchmarking against soil environmental quality standards, the study area exhibited pollution control zones primarily dominated by arsenic and cadmium (3.9%). The spatial distribution revealed distinct zones: a ridge mountain type characterized by arsenic-cadmium-chromium-nickel, a Daban mountain type with solely cadmium presence, and a Longyangxia-Jianzha South type dominated by arsenic. Compared with the Qinghai Province soil background values, evaluations using the Pollution loading index, Geological Cumulative Index, and Potential Ecological Risk Index methods revealed varying degrees of potentially toxic element content exceedance. From an ecological risk perspective, the individual element with the highest potential ecological risk coefficients were mercury, followed by cadmium and arsenic; however, the region's overall ecological risk index was classified as low. Three distinct sources were identified: natural sources leading to high background levels of chromium, nickel, copper, zinc, and mercury; mixed natural and industrial/agricultural sources contributing to elevated cadmium levels; and human activity-related mercury enrichment. Based on the evaluation results, synergistic monitoring of soil and biota in naturally occurring risk zones is recommended to ensure the safety of agricultural and pastoral products. Additionally, ecological impact assessments and pollution source mitigation studies should be conducted in regions influenced by human activities to curb the further degradation of soil ecological quality.

Data-driven intelligent modeling of unconfined compressive strength of heavy metal-contaminated soil

This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement (OPC). For dataset collection, an extensive experimental program was designed to estimate the unconfined compressive strength (Qu) of heavy metal-contaminated soils collected from a wide range of land use pattern, i.e. residential, industrial and roadside soils. Accordingly, a robust comparison of predictive performances of four data-driven models including extreme learning machines (ELMs), gene expression programming (GEP), random forests (RFs), and multiple linear regression (MLR) has been presented. For completeness, a comprehensive experimental database has been established and partitioned into 80% for training and 20% for testing the developed models. Inputs included varying levels of heavy metals like Cd, Cu, Cr, Pb and Zn, along with OPC. The results revealed that the GEP model outperformed its counterparts: explaining approximately 96% of the variability in both training (R2 = 0.964) and testing phases (R2 = 0.961), and thus achieving the lowest RMSE and MAE values. ELM performed commendably but was slightly less accurate than GEP whereas MLR had the lowest performance metrics. GEP also provided the benefit of traceable mathematical equation, enhancing its applicability not just as a predictive but also as an explanatory tool. Despite its insights, the study is limited by its focus on a specific set of heavy metals and urban soil samples of a particular region, which may affect the generalizability of the findings to different contamination profiles or environmental conditions. The study recommends GEP for predicting Qu in heavy metal-contaminated soils, and suggests further research to adapt these models to different environmental conditions.

Subgrade stabilization for road foundation in application for inundated area in Perlis, Malaysia

Abstract Inundated areas, which are prone to frequent flooding, pose significant challenges for road infrastructure due to the adverse effects of water on subgrade soils. Thus, the objectives of this research were to identify and characterize the soil type from roadside of Kampung Bakau, Kangar, Perlis, and evaluate and propose the effective subgrade stabilization methods to enhance the performance and durability of road foundations under such condition. In this research, atterberg limit, standard proctor, and california bearing ratio (CBR) tests were conducted. For CBR test, 6 sets of soil samples were considered. In addition, during the CBR tests, soaked and unsoaked method were performed to simulate the condition of flooding. In general, the soil samples taken were characterized as high plasticity silt. Besides that, the results obtained from CBR test showed that lime with 8 % addition in mixture provides the highest strength which was 4.50 kN of load resisted at 2.00 mm penetration. Meanwhile, cement with 3 % addition in mixture showed the lowest strength observed in the CBR test which was 1.75 kN. In conclusion, this research showed that for high plasticity silt type of soil, the optimized subgrade stabilization method is by lime with 8 % addition in mixture.

Influencing Factors, Risk Assessment, and Source Identification of Heavy Metals in Purple Soil in the Eastern Region of Guang’an City, Sichuan Province, China

Soil heavy metal contamination poses a significant threat to both environmental health and ecological safety. To investigate the influencing factors, ecological hazards, and sources analysis of heavy metals in purple soil, 27 sets of soil samples were collected from varying genetic horizons within Guang’an City, and the contents of As, Cd, Cu, Cr, Hg, Ni, Pb, and Zn were analyzed. The results indicated higher concentrations of heavy metals in soil A horizon, compared to that of C horizon. The relevance analysis indicated that the soil’s heavy metals were strongly correlated with the soil’s physicochemical properties. The enrichment factor, pollution load index, and potential risk index highlighted slightly to severely polluted levels of soil Cd and Hg, which significantly contribute to the ecological hazards posed by soil heavy metals. The potential source of heavy metals analyzed using the APCS-MLR model identified both anthropogenic inputs and natural sources as primary contributors to heavy metal presence in soils. The Cu, Cr, Ni, Pb, and Zn contents in the samples from different genetic horizons were chiefly influenced by natural sources, such as soil matrix erosion and weathering, while the concentrations of Cd and Hg were largely affected by anthropogenic activities, specifically coal combustion and agriculture. Conversely, the As content was found to be influenced by a combination of both factors. Anthropogenic activities greatly impacted soil heavy metals at various depths within the study area, thereby underscoring the importance of monitoring these heavy metals. The findings gained from this research can give a scientific basis for the potential utilization of purple soil.

Comprehensive exploration on transfer and human health risk of potential toxic element in soil‐rice system from the Pearl River Delta

AbstractThe transfers of potential toxic elements (PTEs) from root soil to rice grains and its driving factors are of major worldwide concern. And it is still not clear whether the parent material has influence on the transfers of PTEs in soil. Thus, the aim of this study is to investigate the transfers of PTEs in soil‐rice system from different parent materials area, identify its driving factors and evaluate human health risk. 157 sets of root soil and rice grains samples collected from the areas with quaternary sediments, acidic magmatic rocks and terrigenous clastic rocks in the Pearl River Delta, China. Pearson correlation analysis, discriminant analysis, redundancy analysis, path analysis and human health risk model were utilized for data processing and analysis. The results reveal that parent materials play a primary role affecting the transfers of PTEs in soil‐rice system, and its influence on transfers of PTEs is achieved by governing physicochemical properties of soil. And physicochemical parameters like MgO, SiO2, Al2O3, TFe2O3, and organic matter (OM) exerted significant influence on transfers of PTEs. The influences of some physicochemical parameters on the transfers of PTEs are most significantly in the area of quaternary sediments. The values of the total non‐carcinogenic and the total carcinogenic risks for children and adults caused by rice consumption are much higher than the corresponding risk limits, and the main contributing elements are Pb, As, and As, Cd, respectively. The human health risks caused by rice consumption are greatest in the area with quaternary sediments.

Thorium and uranium rapid quantification in soil with portable X‐ray fluorescence

AbstractThis study aims to evaluate the thorium (Th) and uranium (U) quantification in soil employing a commercial routine in a portable X‐ray fluorescence (pXRF) spectrometer. Certified reference materials (CRMs), as well as a soil sample set, were measured by pXRF and gamma‐ray spectrometry. The pXRF results showed that the thorium average detection and quantification limits (in mg kg−1) were 3.3 ± 0.5 and 11.0 ± 1.7, respectively. The uranium values were 3.0 ± 0.4 and 9.9 ± 1.3. Quantitative pXRF results for Th were in accordance with the reference reported for most CRMs analyzed, and the same accordance was obtained in the comparison with gamma‐ray spectrometry results for the soil sample set. However, U results were overestimated by pXRF when compared both with the CRM‐reported values and the gamma‐ray spectrometry results. In conclusion, the tested pXRF commercial routine may be a viable technique to identify variations in natural Th levels in soil but needs to be used with caution to identify and quantify U.

Taxonomic diversity and abundance of enchytraeids (Annelida, Clitellata, Enchytraeida) in the Northern Palaearctic. 1. Asian part.

Enchytraeids, or potworms, are tiny oligochaetes that are distributed worldwide in many terrestrial, freshwater and marine ecosystems. Despite their key role in the functioning of ecosystems, the diversity and abundance of Enchytraeidae are rarely studied due to the laborious process of species identification. The present study addresses this gap and sheds some light on the distribution and abundance of enchytraeids in the lands of the Northern Palearctic. The provided dataset constitutes the latest and comprehensive field sampling of enchytraeid assemblages across the Asiatic part of the Northern Palearctic, encompassing an original set of soil samples systematically collected throughout the region from 2019 to 2022. The dataset includes occurrences from 131 georeferenced sites, encompassing 39 species and 7,074 records. This represents the first dataset providing species-specific information about the distribution and abundance of terrestrial enchytraeids across an extensive geographic area covering the Asian sector of the Northern Palaearctic. The compiled dataset is the key for exploring and understanding local and regional enchytraeid diversity. It may also serve as a valuable resource for monitoring and conserving the entire soil biodiversity.

Comparison between Rock-Eval® and temperature-programmed pyrolysis/mass spectrometry for the analysis of environmental and geological samples

Natural organic matter (OM) has a complex structure whose complete structural and chemical description remains a challenge. Rock-Eval® device constitutes a rapid and affordable method for obtaining key quantitative and qualitative parameters on OM. Previous studies on soil samples proposed to deconvolute or to split into temperature slices Rock-Eval® S2 pyrograms in order to distinguish and quantify chemical fractions of increasing thermal lability. In order to provide support for such an assumption, this work proposes a methodological approach based on coupling a temperature-programmed pyrolyser to a standard mass spectrometer (Py-MS). In this manuscript, we compare results acquired by Rock-Eval® pyrolysis with those from Total Ion Current (TIC) traces obtained by Py-MS on a set of reference soil samples, completed by dissolved OM, source rock and coal samples, in order to test the extent to which this approach can be generalized. Our results show good quantitative and qualitative agreements between the two methods. This comparison is a prerequisite before going further and addressing the molecular significance of S2 pyrograms deconvolution through the examination of m/z fragments abundance curves.

Interacting Effects of Land Use Type, Soil Attributes, and Environmental Factors on Aggregate Stability

Soil erosion and surface pollution near reservoirs can adversely affect water quality and safety. Soil aggregate stability is an important predictor of soil water loss and erosion resistance that is strongly influenced by land use. This study therefore aimed to identify factors affecting soil aggregate stability near reservoirs to provide empirical and theoretical insights that could guide the development of management measures to increase land quality, optimize land use, and maximize sustainability. This study focuses on the land around the Shitoukoumen Reservoir in China and examines the effects of six land use types, eleven soil physicochemical properties, and five environmental factors. Ninety-four sets of soil samples were collected in 2021 for analysis of soil aggregates and properties. Particle size classification of soil aggregates was carried out using the wet sieve method and four indicators were calculated to evaluate the effects of land use, soil physicochemical properties, and environmental factors on soil aggregate stability: water stable aggregates (WSA), mean weight diameter (MWD), geometric mean diameter (GMD), and fractal dimension (D). Descriptive statistics and geostatistics were used to explore the spatial distributions of soil aggregate stability around the reservoir and the influence of soil properties was studied using correlation analysis and path analysis. The conclusion indicates that land use type significantly affects aggregate stability. The most stable aggregates were found in paddy fields (WSA = 0.77, MWD = 0.76, GMD = 0.57) and forests (WSA = 0.75, MWD = 0.76, GMD = 0.55), followed by an orchard, irrigated land, and grassland. Aggregate stability was worst in upland sites (WSA = 0.61, D = 2.28), where soil aggregates were highly fragmented. There were clear spatial correlations between all four stability indicators. The environmental factors and soil physicochemical characteristics with the strongest influence on aggregate stability were soil organic matter, pH, soil clay content, total nitrogen, and temperature changes. Path analysis revealed that some soil properties affect aggregate stability indirectly, with particularly complex relationships between clay, soil organic matter, and pH. In conclusion, land use type, soil organic matter, pH, soil clay content, total nitrogen, these soil physicochemical properties, and environmental factors, especially temperature, significantly affect soil aggregate stability around reservoirs. In the future, it is necessary to appropriately change upland into paddy land, increase forest land, and appropriately add organic fertilizer to improve soil quality.

Quality Assurance of Potential Radioanalytical Methods for 14C in Environmental Samples

Today, the measurement of 14C in environmental samples is of particular interest, as it enables the assessment of the impact caused by nuclear activities and the fossil fuel industry on the environment. In order to assure the quality of 14C measurement results, the strategy to enlarge the validation of three radioanalytical methods in environmental samples using liquid scintillation spectrometry—the direct counting of water, bubbling of water and combustion of solids—is presented. Due certain difficulties, such as the lack of quality control materials and the scarcity of proficiency test and intercomparison exercises, especially in solid samples, a set of water and soil samples were prepared for the purpose by tracing them with known quantities of a 14C standard solution at two activity levels. Aliquots were subjected to the corresponding method and their activity concentration was calculated. Finally, uncertainty, detection limit, accuracy, precision, repeatability and linearity were analysed. The acceptance criteria for the quality parameters were previously established according to ISO 13528:2015 standard and Eurachem Laboratory Guide to Method Validation. In all the methods, the studied parameters fall within the acceptance range, so they are validated. The quality of the results in real samples is controlled through field validation.

Health Risk Assessment and Environmental Benchmark of Heavy Metals in Cultivated Land in Wanjiang Economic Zone

Focusing on the cultivated land in Wanjiang Economic Zone, 338 sets of soil samples of rice, wheat, and their roots were collected; the concentrations of five heavy metals (As, Cd, Cr, Hg, and Pb) were determined; the soil-crop pollution characteristics were evaluated using the method of geo-accumulation index and comprehensive evaluation; the human health risk of ingesting heavy metals from crops was assessed; and the soil environmental reference value of the regional cultivated land was inverted based on the species sensitive distribution model (SSD). The results showed that in the study area, the soil of rice and wheat was polluted by heavy metals (As, Cd, Cr, Hg, and Pb) in varying degrees, among which Cd was the primary pollution factor of rice, with the over-standard rate of 13.33%, and Cr was the main over-standard factor of wheat, with the over-standard rate of 11.32%. The cumulative index showed that the percentage of Cd pollution in rice was 80.7%, and that in wheat was 35.85%. Contrary to the high pollution level of soil heavy metals, only 17.19% and 7.55% of Cd in rice and wheat exceeded the national food safety limit, and the accumulation capacity of the heavy metal Cd was rice>wheat. The health risk assessment indicated that heavy metals had high non-carcinogenic risk and unacceptable carcinogenic risk to adults and children in this study. The carcinogenic risk of rice intake was higher than that of wheat, and the health risk of children was higher than that of adults. SSD inversion showed that the reference values of As, Cd, Cr, Hg, and Pb in paddy soil in the study area were an HC5 of 6.24, 0.13, 258.27, 0.12, and 53.61 mg·kg-1 and an HC95 of 68.81, 5.71, 1068.92, 0.80, and 174.22 mg·kg-1, respectively. The reference values of As, Cd, Cr, Hg, and Pb in wheat soil HC5 were 32.99, 0.04, 271.14, 0.09, and 47.53 mg·kg-1, and the values of HC95 were 225.28, 0.71, 998.58, 1.43, and 241.99 mg·kg-1, respectively. The reverse analysis showed that the HC5 of heavy metals in rice and wheat were lower than the soil risk screening values in the current standard to varying degrees. The current soil standard had loosened for the evaluation results of this region.

Interaction of climate, topography and soil properties with cropland and cropping pattern using remote sensing data and machine learning methods

Precision agriculture which facilitates and enables crop management through site-specific recommendations, is essential to optimize agricultural inputs in space and time. In this study, we used Landsat and MODIS-NDVI product data with climatic, topographic data and laboratory-analyzed soil samples to map the spatial distribution of seven soil properties; soil texture (T), electrical conductivity (EC), potential hydrogen (pH), nitrogen (N), phosphorus (P), potassium (K), and organic matter (OM) in the Punjab, Pakistan from 2000 to 2020. We examined and compared three statistical prediction models: the support vector machine (SVM), the random forest regression (RFR), and the multiple linear regression (MLR). The predictions were validated against a separate set of soil samples while considering the modeling region and an extrapolation area. Model performance statistics showed that the RFR often provided the highest accuracy, with the machine learning algorithms performing slightly better than the MLR. It was discovered that one obstacle to accurately forecasting soil parameters at unsampled areas with MLR was its inability to handle non-linear connections between independent and dependent variables. The results indicate that the cultivated area decreased from 43.16 % in 2000 to 38.24% in 2020. The soil has a high level of EC due to salinity. In general, the soils contained < 1% OM with lower N. However, the K and P contents were considered medium and adequate. Free remote sensing data has made it possible to improve soil knowledge at local and regional scales in data like Punjab with little outlays of time and money.

Elemental stoichiometry and Rock-Eval® thermal stability of organic matter in French topsoils

Abstract. The quality and quantity of soil organic matter (SOM) are key elements that impact soil health and climate regulation by soils. The Rock-Eval® thermal analysis technique is becoming more commonly used, as it represents a powerful method for SOM characterization by providing insights into bulk SOM chemistry and thermal stability. In this study, we applied this technique on a large soil sample set from the first campaign (2000–2009) of the French Soil Quality Monitoring Network (RMQS – Réseau de mesures de la qualité des sols). Based on our analyses of ca. 2000 composite surface (0–30 cm) samples collected across mainland France, we observed a significant impact of land cover on both the SOM thermal stability and elemental stoichiometry. Cropland soils had a lower mean hydrogen index value (a proxy for the SOM H/C ratio) and a higher thermal stability than grasslands and forests. Regarding the oxygen index (a proxy for the SOM O/C ratio), we observed significant differences among the values for croplands, grasslands, and forests. Positive correlations of the temperature parameters with the clay content and pH highlight the protective effect of clay on organic matter as well as the impact of pH on microorganisms' mineralization activity. Surprisingly, we found weak effects of climatic parameters on the thermal stability and stoichiometry of SOM. Our data suggest that topsoil SOM is on average more oxidized and biogeochemically stable in croplands. More generally, the high number and even distribution of data across the whole French territory allow one to build a national interpretative reference for these indicators in surface soils.

Spatio-Temporal Variability of Soil Properties and Nutrient Uptake for Sustainable Intensification of Rainfed Pigeon Pea (Cajanus cajana) in Semi-Arid Tropics of India

A study was conducted at Kalamandari Tanda-1 micro-watershed, Karnataka, India, to assess the spatio-temporal variability of surface soil properties sampled from 23 varied soil-phase units, delineated using IRS P6 LISS-IV merged Cartosat-I imagery (2.5 m spatial resolution). Three sets of surface soil samples (231 in each set) were collected, analyzed, and interpolated to evaluate the soil spatio-temporal variability. Further soil-phase-wise composite representative samples (23 in each set) were collected before the sowing and after the harvest of pigeon peasin January 2019 and 2020. Results showed that the soil OC with N, Mg with Ca, exchangeable sodium percentage (ESP), and cation exchange capacity (CEC) with Mn and K2O have a significantly positive association (p &lt; 0.01) during both years. Similarly, a significantly positive association (p &lt; 0.05) was observed among soil OC and N with Cu, Mn with CEC, and Zn with Fe, while a negative association was seen between available P2O5 and Na. Skewness from descriptive statistics revealed that pH, EC, Cu, Mg, B, and ESP distribution varied temporally, whereas other parameters remained almost unchanged. Geo-statistically, the spatial distribution of measured soil properties was best fitted to exponential, stable, and K-Bessel models. The available N in 2018 and the ESP in 2019 have shown weak spatial dependency, whereas the rest of the soil parameters showed moderate and strong spatial dependency. These interpolated maps were exported as vector layers to quantify soil-phase-wise spatio-temporal variability of soil properties.

Digital Soil Mapping of Cadmium: Identifying Arable Land for Producing Winter Wheat with Low Concentrations of Cadmium

Intake of cadmium (Cd) via vegetable food poses a possible health risk. Cereals are one of the major sources of Cd, and the Cd concentration in the soil has a great effect on the levels in the grain. The aim of the study was to produce decision support for identification of areas suitable for low-Cd winter wheat production in the form of a detailed digital soil map covering an important agricultural region in southern Sweden. A two-step approach was used: (1) we increased the number of soil Cd observations by combining two sets of soil samples, one with laboratory Cd analyses (304 samples) and one with predicted Cd from a portable x-ray fluorescent (PXRF) sensor (2097 samples); and (2) a digital soil mapping (DSM) model (gradient boosting regression) was calibrated on all 2401 soil samples to create a soil Cd concentration map using a number of covariates, of which airborne gamma ray data was identified as the most important. In the first step, cross-validation of the PXRF model obtained a model efficiency (E) of 0.82 and mean absolute error (MAE) of 0.08 mg kg−1. The DSM model had an E of 0.69 and MAE of 0.11 mg kg−1. The map of predicted soil Cd concentrations were compared against 307 winter wheat (Triticum aestivum L.) grain samples with laboratory-analyzed Cd concentrations. Areas in the map with low soil Cd concentrations had a high frequency of lower grain Cd concentrations. The map thus seemed to have potential for finding areas suitable for production of low-Cd winter wheat; e.g., for baby food.

Laboratory Design Criteria for Monitoring Biostimulated Bioremediation of a Crude Oil Contaminated Soil in Niger Delta Using Total Petroleum Hydrocarbon

The remediation of crude oil-impacted soil has always been a challenge in different soil environments and climatic conditions. Bioremediation technology has offered a breakthrough in restoring crude oil-impacted soil/sediment in muddy, dry soil and wetlands. Though, there have been varied environmental conditions that have hampered the success of the bioremediation process. This study has evaluated the effectiveness of a biostimulated bioremediation of crude oil-impacted soil using some design criteria—nutrient amendment (NPK fertilizer) and moisture content. Soil sample sets—A, B, C, D, E, F, and G were impacted with crude oil at a ratio of 10 g/kg and amended with varying amounts of nutrient 30, 60, and 80 g of N.P.K fertilizer. The medium for the inoculation of the nutrient was water and the volume of water applied varied from 30% to 80% saturation. The soil sample sets were harvested at an interval of 3 months for 180 days to determine the concentration of total petroleum hydrocarbon left in the soil. The analysis of the total petroleum hydrocarbon was achieved using a GC-FID with a capillary column and autosampler. Soil samples were extracted with mixed solvent dichloromethane and acetone at a 1:1 ratio. The total petroleum hydrocarbon results show that biostimulated bioremediation achieved better results in soil sample sets with low moisture content (30% water saturation) and moderate nutrient amendment. The biodegradation of the sample sets with high water saturation and a high nutrient amendment was slow with a higher amount of total hydrocarbon content at the end of the 180 days. The variability in the hydrocarbon degradation pattern of contaminated soil shows that biostimulated bioremediation achieved better results in soils with low moisture content than in soil environments with high water content (saturation). More so, nutrient overdosing of the substrate hampered the effectiveness of the remediation process.

The Composition of Dissolved Organic Matter in Arable Lands: Does Soil Management Practice Matter?

Dissolved organic matter (DOM) is a key soil quality property, indicative of the organic matter stored in the soil, which may also be a function of temporal variation. This study examines whether DOM is a robust property of the soil, controlling fertility, or if it may change with time. Altogether eight sets of soil samples were collected in 2018 and 2019 from the cultivated topsoil (0–10 cm) of cropland and from a nearby grassland near Martonvásár, Hungary. The study sites were characterized by Chernozem soil and were part of a long-term experimental project comparing the effects of manure application and fertilization to the control under maize and wheat monocultures. DOM was extracted from the samples with distilled water. The dissolved organic carbon (DOC), total dissolved nitrogen (DN), biological index (BIX), fluorescence index (FI), humification index (HIX), carbon nitrogen (C/N) ratio and specific ultraviolet absorbance at 254 nm (SUVA254) index were studied in the arable soils, and the results showed that all the DOM samples were humified, suggesting relevant microbiological contributions to the decomposition of OM and its conversion into more complex molecules (FI = 1.2–1.5, BIX = ~0.5, and HIX = ~0.9). Temporal variations were detected only for the permanent grassland where higher DOM concentration was found in spring. This increased DOM content mainly originated from humified, solid phase associated, recalcitrant OM. In contrast, there were no differences among fertilization treatments and sampling dates under cropfield conditions. Moreover, climatic conditions were not proven as a general ruler of DOM properties. Therefore, momentary DOM alone is not necessarily the direct property of soil organic matter under cropfield conditions. The application of this measure needs further details of sampling conditions to achieve adequate comparability.

Zoning and Safe Utilization Method of Heavy Metal Contaminated Cultivated Land at Block Scale

The safe use of arable land is one of the important measures to ensure food security and to realize the construction of ecological civilization. In order to solve the problem of blindly selecting technical measures in the process of safe use and restoration of pollution-risk cultivated land, 244 surface soil samples and 100 sets of rice-root soil samples were collected in Echi Town, Qianjiang District, Chongqing. Based on the contents of five heavy metals of Cd, Hg, Pb, As, and Cr, as well as soil oxides, organic matter, and pH and other indicators, a prediction model was established using multiple regression and geostatistical analyses, and the plots were assigned values, combined with the soil and soil in the plots. The total amount of heavy metals in the rice, the available content of heavy metals in the soil, and the pH of the soil guided suggestions for the safe use of cultivated land at the corresponding plot scale. The results showed that the soil in the study area was mainly and strongly acidic. The percentages of Cd exceeding the soil pollution risk screening value and control value were 33.61% and 2.05%, respectively. The effective content of Cd accounted for 60%, and the Cd exceeding rate of rice was 28%. There was an obvious ecological risk of Cd in the study area. The available Cd content of the soil was mainly affected by the total amount of soil Cd and pH. The enrichment of Cd in rice was mainly affected by the content of soil organic matter, Mn, and CaO. The zoning results showed that the priority protection category of the soil in the study area accounted for 59.30%; the safe use category accounted for 40.44%, of which safe use (IAa), safe use (IAb), safe use (IBa), safe use (IIAa), safe use (IIAb), and safe use (IIBa) accounted for 19.49%, 8.01%, 1.43%, 7.04%, 1.41%, and 3.06%, respectively; and strict control accounted for 0.26%. This method combined the safety risks of soil and agricultural products and aided formation of specific recommendations for safe use, which provided a method of reference for the safe use of contaminated farmland in accordance with local conditions.