This study conducted the development of an advanced risk assessment algorithm system and safety management strategies using pesticide residue monitoring data from soils. To understand the status of ...pesticide residues in agricultural soils, monitoring was performed on 116 types of pesticides currently in use across 300 soil sites. The analysis of the monitoring results, alongside the physicochemical properties of the pesticides, led to the selection of soil half-life as a critical component in residue analysis. The use of Toxicity Exposure Ratio (TER) and Risk Quotient (RQ) for environmental risk assessment, based on monitoring data, presents limitations due to its single-component, conservative approach, which does not align with actual field conditions. Therefore, there is a necessity for a risk assessment process applicable in real-world scenarios. In this research, an efficient and accurate risk assessment algorithm system, along with a safety management model, was developed. Using the physicochemical properties of pesticides (such as soil half-life), monitoring results, and toxicity data, cluster analysis and Principal Component Analysis (PCA) validation identified four pesticides: boscalid, difenoconazole, fluquinconazole, and tebuconazole. The k-mean cluster analysis selected three priority management sites where the contribution of these four pesticides to the RQ was between 94–99 %, showing similar results to the RQ calculated for all pesticides. Predictions made with the developed model for the time required for soil half-life based RQ to drop below 1 at these priority sites showed only a 1–9 day difference between the four pesticides of concern and all pesticides, indicating comparable outcomes. The scenario of replacing high-risk pesticides with those of lower risk demonstrated that the RQ could be consistently maintained at about 50 % level. The results of this study suggest that through monitoring, evaluation, and management, effective and accurate environmental safety management of pesticides in soil can be achieved.
Most regional municipal solid waste landfills in Serbia are operated without control of landfill leachate and gas or with no regard for implementation of national and European legislation. For the ...first time in Serbia, groundwater and soil at a landfill were subject to systematic annual monitoring according to national, European legislation and adopted methodologies. Characterisation of the groundwater and soil samples from the landfill included ten metals (Fe, Mn, As, Zn, Cd, Pb, Ni, Cr, Cu and Hg), 16 EPA PAHs, nutrients and certain physicochemical parameters, in order to assess the risks such poorly controlled landfills pose to the environment. This impact assessment was performed using specially adapted pollution indices: LWPI, the Single factor pollution index and the Nemerow index for groundwater, and geo-accumulation index, ecological risk factor and selected rations of PAHs for soil. The data analysis included multivariate statistical methods (factor analysis of principal component analysis (PCA/FA)) in order to assess the extent of the contaminants detected in the groundwater and soil samples.
The pollution indices (LWPI: 3.56–8.89; Nemerow index: 2.02–3.78) indicate the quality of the groundwater at the landfill is degrading over time, with PAH16, TOC, Cr, Cu, Pb and Zn as the substances of greatest concern. Heavy metals Hg (Igeo≤3.14), Pb (Igeo≤2.22), Cr (Igeo≤3.31) and Cu (Igeo≤2.16) represent the worst soil contamination. Hg has moderate (52.9) to very high (530.0) potential ecological risk, demonstrating the long-term potential effects of bioaccumulation and biomagnification.
The results of this work indicate that Cr and Cu should possibly be added to the EU Watch List of emerging substances. This proposition is substantiated by relevant state and alike environmental information from nations in the region. This study demonstrates the need to develop a model for prioritization of landfill closure and remediation based on environmental risk assessment.
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•Landfill groundwater and soil pollution were very high•Hg values for two soil sampling sites showed potential for ecological risk•Statistic analysis showed significance of Cu and Pb in soil and groundwater•Organic carcinogens in the soil highly correlated with groundwater Fe and Hg•Cr and Cu should be added to the European Watch List of emerging contaminants
The adverse effects of pesticides on the agricultural ecosystem have been matter of concern in recent decades. However, attention has mostly been directed to highly persistent chemicals leading to ...underestimating currently used pesticides. In this review we present an overview of the studies on monitoring currently used pesticides in agricultural soils around the world published in the last 50 years. Furthermore, all data available in the articles has been integrated into one united data set. Finally, an overall meta-analysis on the prepared data set was performed. The result of the meta-analysis has been presented in this article. It was revealed that the occurrence of currently used pesticides in the soil of agricultural regions was alarming in many countries, establishing the need for long-term monitoring programs, especially in regions with intensive agricultural activities, in order to determine real-world currently used pesticides fate and accumulation in the soil.
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•This review highlights the worldwide occurrence of CUPs in the agricultural soils.•All available numerical data in the reviewed articles were integrated into a dataset.•A meta-analysis on the dataset clarified the worldwide situation of individual active ingredients.•Regular soil monitoring programs are highly recommended.
Although large amounts of pesticides are used annually and a majority enters the soil to form short- or long-term residues, extensive soil surveys for currently used pesticides (CUPs) are scarce. To ...determine the status of CUPs' occurrence in arable land in Central Europe, 51 CUPs and 9 transformation products (TPs) were analysed in 75 arable soils in the Czech Republic (CR) several months after the last pesticide application. Moreover, two banned triazines (simazine and atrazine) and their TPs were analysed because of their frequent detection in CR waters. Multi-residue pesticide analysis on LC-MS/MS after soil QuEChERS extraction was used. The soils contained multiple pesticide residues frequently (e.g. 51% soils with ≥5 pesticides). The levels were also noticeable (e.g. 36% soils with ≥3 pesticides exceeding the threshold of 0.01mg/kg). After triazine herbicides (89% soils), conazole fungicides showed the second most frequent occurrence (73% soils) and also high levels (53% soils with total conazoles above 0.01mg/kg). Frequent occurrence was found also for chloroacetanilide TPs (25% of soils), fenpropidin (20%) and diflufenican (17%). With the exception of triazines' negative correlation to soil pH, no clear relationships were found between pesticide occurrence and soil properties. Association of simazine TPs with terbuthylazine and its target crops proved the frequent residues of this banned compound originate from terbuthylazine impurities. In contrast, frequent atrazine-2-hydroxy residue is probably a legacy of high atrazine usage in the past. The occurrence and levels of compounds were closely associated with their solubility, hydrophobicity and half-life. The results showed links to CR water-monitoring findings. This study represents the first extensive survey of multiple pesticide residues in Central European arable soils, including an insight into their relationships to site and pesticide properties.
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•53 pesticides and 15 transformation products analysed in 75 arable soils•Multiple pesticide residues with noticeable levels were found in a high number of soils.•Triazines and conazoles are most frequent and present at high concentrations.•Significant simazine entry to soils as terbuthylazine impurity indicated•Links found to the results of CR water monitoring
Various soil organic carbon (SOC) models and additional methods to calculate carbon (C) input to soil are used to simulate SOC stocks, e.g. for national greenhouse gas inventories. Most of the SOC ...models used on a regional to national scale share the principle of process-based multi-compartment models, but differ in their initialization or decomposition modifying factors. We performed a model comparison to identify the model or multi-model ensemble that best fits trends in SOC stocks of German croplands. We combined six SOC models (C-TOOL, CCB, CENTURY, ROTH-C, ICBM and YASSO07) with five C input estimation methods (bolinder, bze, ccb, ctool, ipcc-nir), producing a model set of 30 model combinations. We used data from agricultural permanent soil monitoring sites in Germany to compare modeled and measured trends of SOC stock time series. The absolute mean error (AME) of the trends for the model combinations varied between 0.01 Mg ha−1 a−1 and 0.86 Mg ha−1 a−1, with C-TOOL, CENTURY and YASSO07 generally showing smaller AME than ICBM and CCB. The scatter of the modeled trends of the 30 model combinations indicated that the choice of SOC model was more important than the choice of C input estimation method. A multi-objective criterion was used to summarize results from AME, root mean squared error (RMSE) and the probability that the measured trend lies within the confidence interval of the modeled trend. We set up a multi-model ensemble consisting of all 30 model combinations, and reduced the number of participating models until the multi-objective criterion of the ensemble was smallest. A multi-model ensemble with nine model combinations was found to be the best ensemble. The multi-model ensemble performed better than the single model combinations, with AME of 0.004 Mg ha−1 a−1 and RMSE of 0.56 Mg ha−1 a−1. Based on our results, we recommend the use of a multi-model ensemble for predicting trends in SOC stocks as it reduces structural uncertainties and solves the problem of choosing the right SOC model or C input estimation method.
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•First time using a multi-model ensemble for estimating trends in soil carbon stocks•A multi-model ensemble was built for robust modeling of temperate cropland soils.•Multi-model ensemble performed better than the average of individual models.
The importance of building/maintaining soil carbon, for soil health and CO
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mitigation, is of increasing interest to a wide audience, including policymakers, NGOs and land managers. Integral to any ...approaches to promote carbon sequestering practices in managed soils are reliable, accurate and cost-effective means to quantify soil C stock changes and forecast soil C responses to different management, climate and edaphic conditions. While technology to accurately measure soil C concentrations and stocks has been in use for decades, many challenges to routine, cost-effective soil C quantification remain, including large spatial variability, low signal-to-noise and often high cost and standardization issues for direct measurement with destructive sampling. Models, empirical and process-based, may provide a cost-effective and practical means for soil C quantification to support C sequestration policies. Examples are described of how soil science and soil C quantification methods are being used to support domestic climate change policies to promote soil C sequestration on agricultural lands (cropland and grazing land) at national and provincial levels in Australia and Canada. Finally, a quantification system is outlined - consisting of well-integrated data-model frameworks, supported by expanded measurement and monitoring networks, remote sensing and crowd-sourcing of management activity data - that could comprise the core of a new global soil information system.
This study illustrates the successful application of near-infrared reflectance spectroscopy extended with chemometric modeling to profile Cd, Cu, Pb, Ni, Cr, Zn, Mn, and Fe in cultivated and ...fertilized Haplic Luvisol soils. The partial least-squares regression (PLSR) models were built to predict the elements present in the soil samples at very low contents. A total of 234 soil samples were investigated, and their reflectance spectra were recorded in the spectral range of 1100–2500 nm. The optimal spectral preprocessing was selected among 56 different scenarios considering the root mean squared error of prediction (RMSEP). The partial robust M-regression method (PRM) was used to handle the outlying samples. The most promising models were obtained for estimating the amount of Cu (using PRM) and Pb (using the classic PLS), leading to RMSEP expressed as a percentage of the response range, equal to 9.63% and 11.5%, respectively. The respective coefficients of determination for validation samples were equal to 0.86 and 0.58, respectively. Assuming similar variability of model residuals for the model and test set samples, coefficients of determination for validation samples were 0.94 and 0.89, respectively. Moreover, the favorable PLS models were also built for Zn, Mn, and Fe with coefficients of determinations equal to 0.87, 0.87, and 0.79.
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•Monitoring the concentrations of eight elements in cultivated Haplic Luvisol soils.•NIR and determination of elements in soils at low concentrations.•Robust PLS modeling in the presence of outlying samples.
The application of synthetic pesticides to agricultural fields for the protection of crops leads to the formation of residues in soils. While the short-term behavior of pesticide residues in soils ...after an application is generally known from laboratory and field studies required for authorization (prospective risk assessments), there is still a lack of in-situ observations that address their long-term fate. Long-term soil monitoring programs, with comprehensive site-specific records of pesticide application data, constitute an invaluable, complementary, retrospective exposure assessment tool to address this gap. Considering the pesticide applications over the past 10–15 years, this study assessed the occurrence of pesticides in agricultural soils of Switzerland and put their presence or absence, as well as their concentrations, in the context of their previous application. The results showed that pesticides could also be detected at sites without a connection to previous applications and that small residual mass fractions of pesticides, even of some non-persistent compounds, were found in soils, years or decades after their last application. This finding points to an environmental issue that may not be adequately captured in prospective risk assessment and calls attention to the need for comprehensive long-term recording and monitoring as a complementary retrospective exposure assessment.
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•Soils from 31 agricultural sites were analyzed for 34 pesticides and 7 metabolites.•The presence or absence of pesticides was related to their previous application.•Pesticides were also detected at sites not associated with previous applications.•Some pesticides persisted much longer than predicted from their half-lives.•Residual mass fractions of a few % were found years after the last application.
•Mapping, digital mapping and monitoring soil over large areas contribute to soil security.•Soil capability and condition contribution is large but some key functions are still missing.•Soil capital ...changes should be better covered by soil monitoring.•Soil connectivity requires better adapting our communication to the target audiences.•Soil codification is raising, but still need more connectivity to citizens and policy-makers.
Soil Security includes dimensions, soil capability, soil condition, soil capital, soil connectivity and soil codification (the “five C's”). This article provides a short review on how soil mapping, digital soil mapping and soil monitoring systems (SM, DSM and SMS) over large areas contribute to these five C's at scales ranging from country to globe. Changes and the evolution in aims of SM, DSM and SMS were driven both by main issues related to policy priorities and associated advances in science and technology. This review shows that SM, DSM and SMS can provide the basis for assessing soil capability and condition over large areas, especially if we assume that capability mainly depends on rather stable soil attributes. Repeated DSM or SMS are appropriated tool to monitor changes in soil condition at these scales. They may even allow mapping changes in soil capability. However, broad-scale SM, DSM and SMS have not yet fully achieved the provision of information concerning the delivery of some soil functions and soil-based ecosystem services. Although significant progress in estimating the capital dimension of soil security has been achieved, there is need to progress monitoring changes in soil capital. Broad-scale SM, DSM and SMS has great potential to increase soil connectivity. The main challenge is adapting our language and our communication to the target audience. There are encouraging initiatives to enhance soil codification. Codification issues are largely driven by the political agenda, there is still an urgent need to increase soil connectivity, especially towards citizens, NGOs and policy-makers.
A multiparametric sequential injection system for the determination of phosphate, nitrite, nitrate, potassium, and iron(III) in a single manifold was developed. The main goal of the proposed method ...was to develop an efficient tool to assess a number of essential chemical compounds in soils, providing the corresponding information on soil fertility and, additionally, information on possible groundwater contamination. The method was applied for the quantification of the aforementioned parameters in simulated leachates produced in laboratory-scale core columns. The relative standard deviations of ten replicate analyses of a standard were: 6% for phosphate; 2% for nitrite; 2% for nitrate; 5% for potassium; and 6% for iron(III). The limits of detection and quantification were: 2.15 and 7.18 μmol/L for phosphate determination; 0.22 and 0.73 μmol/L for nitrite determination; 3.42 and 8.00 μmol/L for nitrate determination; 39 μmol/L (limit of detection) for potassium determination; and 0.46 and 1.85 μmol/L for iron(III) determination. The sequential injection system was successfully applied for the quantification of multiple soil chemical components (PO43−, NO2−, NO3−, K+, and Fe3+) in soil leachates. The analysis of a sample, involving all the analytes, has a duration of 28 min.
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•Design of a multiparametric flow-based system for soil analysis.•Real-time assessment of soil fertility.•Miniaturized and automatic tool for soil nutrients monitoring in a single manifold.•Easy to adapt to a specific analyte/s or to all the analyte’s quantification.•Successful application to agricultural soil leachates.
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