Modeling Uptake of Selected Pharmaceuticals and Personal Care Products into Food Crops from Biosolids-Amended Soil

Biosolids contain a variety of pharmaceuticals and personal care products (PPCPs). Studies have observed the uptake of PPCPs into plants grown in biosolids-amended soils. This study examined the ability of Dynamic Plant Uptake (DPU) model and Biosolids-amended Soil Level IV (BASL4) model to predict the concentration of eight PPCPs in the tissue of plants grown in biosolids-amended soil under a number of exposure scenarios. Concentrations in edible tissue predicted by the models were compared to concentrations reported in the literature by calculating estimated human daily intake values for both sets of data and comparing them to an acceptable daily intake value. The equilibrium partitioning (EqP) portion of BASL4 overpredicted the concentrations of triclosan, triclocarban, and miconazole in root and shoot tissue by two to three orders of magnitude, while the dynamic carrot root (DCR) portion overpredicted by a single order of magnitude. DPU predicted concentrations of triclosan, triclocarban, miconazole, carbamazepine, and diphenhydramine in plant tissues that were within an order of magnitude of concentrations reported in the literature. The study also found that more empirical data are needed on the uptake of cimetidine, fluoxetine, and gemfibrozil, and other ionizable PPCPs, to confirm the utility of both models. All hazard quotient values calculated from literature data were below 1, with 95.7% of hazard quotient values being below 0.1, indicating that consumption of the chosen PPCPs in plant tissue poses de minimus risk to human health

Dynamic Passive Dosing for Studying the Biotransformation of Hydrophobic Organic Chemicals: Microbial Degradation as an Example

Biotransformation plays a key role in hydrophobic organic compound (HOC) fate, and understanding kinetics as a function of (bio)­availability is critical for elucidating persistence, accumulation, and toxicity. Biotransformation mainly occurs in an aqueous environment, posing technical challenges for producing kinetic data because of low HOC solubilities and sorptive losses. To overcome these, a new experimental approach based on passive dosing is presented. This avoids using cosolvent for introducing the HOC substrate, buffers substrate depletion so biotransformation is measured within a narrow and defined dissolved concentration range, and enables high compound turnover even at low concentrations to simplify end point measurement. As a case study, the biodegradation kinetics of two model HOCs by the bacterium Sphingomonas paucimobilis EPA505 were measured at defined dissolved concentrations ranging over 4 orders of magnitude, from 0.017 to 658 μg L^–1 for phenanthrene and from 0.006 to 90.0 μg L^–1 for fluoranthene. Both compounds had similar mineralization fluxes, and these increased by 2 orders of magnitude with increasing dissolved concentrations. First-order mineralization rate constants were also similar for both PAHs, but decreased by around 2 orders of magnitude with increasing dissolved concentrations. Dynamic passive dosing is a useful tool for measuring biotransformation kinetics at realistically low and defined dissolved HOC concentrations

Experimental Results and Integrated Modeling of Bacterial Growth on an Insoluble Hydrophobic Substrate (Phenanthrene)

Metabolism of a low-solubility substrate is limited by dissolution and availability and can hardly be determined. We developed a numerical model for simultaneously calculating dissolution kinetics of such substrates and their metabolism and microbial growth (Monod kinetics with decay) and tested it with three aerobic phenanthrene (PHE) degraders: <i>Novosphingobium pentaromativorans</i> US6-1, <i>Sphingomonas</i> sp. EPA505, and <i>Sphingobium yanoikuyae</i> B1. PHE was present as microcrystals, providing non-limiting conditions for growth. Total PHE and protein concentration were tracked over 6–12 days. The model was fitted to the test results for the rates of dissolution, metabolism, and growth. The strains showed similar efficiency, with <i>v</i>_max values of 12–18 g dw g^–1 d^–1, yields of 0.21 g g^–1, maximum growth rates of 2.5–3.8 d^–1, and decay rates of 0.04–0.05 d^–1. Sensitivity analysis with the model shows that (i) retention in crystals or NAPLs or by sequestration competes with biodegradation, (ii) bacterial growth conditions (dissolution flux and resulting chemical activity of substrate) are more relevant for the final state of the system than the initial biomass, and (iii) the desorption flux regulates the turnover in the presence of solid-state, sequestered (aged), or NAPL substrate sources

Estimated soil-water partition coefficient <i>K_d</i> (Sauvé regression) vs. measured <i>K_d</i> (determined from CaCl₂ extractions).

<p>The dotted line indicates a ratio of one.</p

Measured soil parameters (depth, dry density <i>ρ_S,dry</i>, field capacity, <i>FC,</i> and permanent wilting point, <i>PWP</i>) of the soil layers.

<p>Measured soil parameters (depth, dry density <i>ρ_S,dry</i>, field capacity, <i>FC,</i> and permanent wilting point, <i>PWP</i>) of the soil layers.</p

Leaching of water from soil layer 2.

<p>Model compared to measurement for CTR, MSW and GSW treatments. Model is average of all predictions, min and max is minimum and maximum lysimeter measurements, MSW(I) and CTR(II), respectively.</p

Amendment application (second half of September in each given year) and input of Cd and Pb with amendment for the different treatments.

<p>GWS: Co-compost of green waste and sewage sludge, BIOW: Biowaste compost, FYM: Farmyard manure and MSW: Municipal solid waste compost.</p

Overview of the field and simulation study.

<p>For wheat and barley the starting point of growth takes place after seeding.</p

Simulated water balance and content of soil.

<p>(a) Simulated annual water balance, control scenario, August 1998 to October 1999; (b) simulated water content of the five soil layers, same simulation event.</p

Comparison of predicted and measured concentrations in plants (mg kg dw⁻¹) for the five treatments.

<p>October 1999 to July 2007. Model predictions are connected by lines for clearer comparison to measured values. Vertical lines denote the range of measured values and symbols the medians of the four replicates (values below QL were set equal to ½ QL (note that QLs from 1999–2005 were applied for all years). Top arrows recall the time of amendment application.</p