Statistical Modeling of the Partitioning of Nonylphenol in Soil

Partition coefficients K _P of nonylphenol (NP) in soil were determined for 193 soil samples which differed widely in content of soil organic carbon (SOC), hydrogen activity, clay content, and in the content of dissolved organic carbon (DOC). By means of multiple linear regression analysis (MLR), pedotransfer functions were derived to predict partition coefficients from soil data. SOC and pH affected the sorption, though the latter was in a range significantly below the pK_a of NP. Quality of soil organic matter presumably plays an important but yet not quantified role in sorption of NP. For soil samples with SOC values less than 3 g kg^?1, model prediction became uncertain with this linear approach. We suggest that using only SOC and pH data results in good prediction of NP sorption in soils with SOC higher than 3 g kg^?1. Considering the varying validity of the linear model for different ranges of the most sensitive parameter SOC, a more flexible, nonlinear approach was tested. The application of an artificial neuronal network (ANN) to predict sorption of NP in soils showed a sigmoidal relation between K _P and SOC. The nonlinear ANN approach provided good results compared to the MLR approach and represents an alternative tool for prediction of NP partitioning coefficients.     

Depth distribution and bioavailability of pollutants in long-term differently tilled soils

Pollutants can be introduced to soil through the application of organic and inorganic fertilizers and pesticides and through atmospheric depositions. The objective of this research was to evaluate the influence of long-term (9–17 years) tillage systems on the behavior of pollutants in soils. Bioavailability and enrichment of heavy metals, arsenic, and organics, i.e. polychlorinated biphenyls (PCB’s) and a chlorinated phenol (2,4-DCP) were measured in a Eutric Cambisol and a Luvisol under conventional tillage (CT), reduced tillage (RT), and no-tillage (NT). Soil samples were collected from 0 to 3, 3 to 10, and 10 to 25 cm depths.

The upper layer of NT soils was enriched in pollutants, but concentrations decreased with increasing soil depth. Atmospheric deposition of pollutants and input via organic fertilizers was noticeable in soils under long-term NT. Total amount of zinc (59 mg kg⁻¹) was significantly enriched in the 0–3 cm depth of the Luvisol under NT and this was attributed to higher sorption capacity for heavy metal input via liquid manure. In the Eutric Cambisol, NT resulted in significant increase of cadmium extracted by aqua regia in the arable layer of 0–25 cm. As a result of higher soil organic C, long-term accumulation of PCB’s in NT soils was more pronounced than in plowed soils. In plowed soils the mixing effect resulted in homogeneous distribution of pollutants within a soil depth of 0–25 cm.

The enrichment of organic C in RT and NT soils emphasizes the role of soils as a sink for pollutants, buffering the contaminants against leaching and transfer into crops.     

Transfer of Metals in Soil-Grass Ecosystems under Long-Term N,P, K Fertilization in Hesse,Germany

Soil and plant samples (Lolio-Cynosuretum) were taken from four different locations in Hesse, Germany. Different doses of nitrogen, phosphorus, and potassium fertilizers were applied to verify metal input due to fertilization. Metal concentrations in plants increased due to mineral fertilization. Detected plant cadmium (Cd), copper (Cu), manganese (Mn), lead (Pb), and zinc (Zn) concentrations in non-fertilized plots were 0.04, 4.13, 106.5, 0.57, and 23.0 mg kg^?1 and in long-term NPK-amended plots they were 0.31, 15.3, 524.9, 3.49, and 60.0 mg kg^?1, respectively. Transfer factor (TF) was observed to decrease in the order of Cd>Cu>Zn>Mn>Pb. The results of regression analysis showed that organic carbon (C_org) content, effective-cation exchange capacity (CEC_eff), and bioavailable metal content are the most important predictors for plant metal uptake. This study confirmed that plant metal uptake was not only highly affected by the soil metal content but also influenced by soil properties.     

Partitioning of polycyclic musk compounds in soil and aquatic environment—experimental determination of K<Subscript>DOC</Subscript>

Purpose  

Polycyclic musk compounds (PMC) are used as fragrances in cosmetics and detergents and enter rivers via domestic wastewater and sewage treatment plants. Soils can be contaminated by PMC through application of sewage sludge. Accumulation of PMC occurs in sediments and biota due to their persistence and lipophilicity. Dissolved organic matter (DOM) is of special relevance for their transport and behavior in the environment as it acts as solubilizer and carrier in aquatic and terrestrial systems. With the distribution coefficient K_DOC, one can predict their affinity to DOM. Different approaches exist to determine K_DOC, resulting in a range of coefficients for a number of organic pollutants. The objective of this study was to determine K_DOC values for PMC using solid-phase microextraction (SPME).     

A miniaturized method for fast,simple, and sensitive pesticide analysis in soils

Journal of Soils and Sediments - Organochlorine pesticides (OCPs) like lindane and DDT have been used extensively after World War II until the 1990s. Still, residues of these pesticides can be...