The environmental effects and bioavailability of nanoparticulate iron (Fe) to plants are currently unknown. Here, plant bioavailability of synthesized hematite Fe nanoparticles was evaluated using Arabidopsis thaliana (A. thaliana) as a model. Over 56-days of growing wild-type A. thaliana, the nanoparticle-Fe and no-Fe treatments had lower plant biomass, lower chlorophyll concentrations, and lower internal Fe concentrations than the Fe-treatment. Results for the no-Fe and nanoparticle-Fe treatments were consistently similar throughout the experiment. These results suggest that nanoparticles (mean diameter 40.9 nm, range 22.3–67.0 nm) were not taken up and therefore not bioavailable to A. thaliana. Over 14-days growing wild-type and transgenic (Type I/II proton pump overexpression) A. thaliana, the Type I plant grew more than the wild-type in the nanoparticle-Fe treatment, suggesting Type I plants cope better with Fe limitation; however, the nanoparticle-Fe and no-Fe treatments had similar growth for all plant types.

The tissue level uptake and spatial distribution of gold nanoparticles (AuNPs) in rice (Oryza sativa L.) roots and shoots under hydroponic conditions was investigated using laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). Rice plants were hydroponically exposed to positively, neutrally, and negatively charged AuNPs [AuNP1(+), AuNP2(0), AuNP3(−)] with a core diameter of 2 nm. Plants were exposed to AuNPs having 1.6 mg Au/L for 5 days or 0.14 mg Au/L for 3 months to elucidate how the surface charges of the nanoparticles affects their uptake into living plant tissues. The results demonstrate that terminal functional groups greatly affected the AuNP uptake into plant tissues. Au concentration determined by LA-ICP-MS in 5 day treated rice roots followed this order: AuNP1(+) > AuNP2(0) > AuNP3(−) but this order was reversed for rice shoots, indicating preferential translocation of AuNP3(−). Bioimages revealed distributions of mesophyll and vascular AuNP dependent on organ or AuNP concentration.

Coupling with triolein-embedded cellulose acetate membrane (TECAM) technique, hydroxypropyl β-cyclodextrins (HPCD) extraction method, and the greenhouse pot experiments, the influences of biochars on polychlorinated biphenyls (PCBs) bioavailability in soil to plant (Brassica chinensis L. and Daucus carota) were investigated. Addition of 2% biochars to soils significantly reduced the uptake of PCBs in plant, especially for di-, tri- and tetra-chlorobiphenyls. PCBs concentrations in the roots of B. chinensis and D. carota were reduced for 61.5–93.7%, and 12.7–62.4%, respectively in the presence of biochars. The kinetic study showed that in the soils amended with/without biochars, PCBs concentrations accumulated in TECAM, as well as in the HPCD extraction solution, followed significant linear relationships with those in plant roots. Application of biochars to soil is a potentially promising method to reduce PCBs bioavailability whereas TECAM technique can be a useful tool to predict the bioavailability of PCBs in soil.

Crude oil is a complex mixture of petroleum hydrocarbons (PHC) with distinct chemical, physical and toxicological properties relevant for contaminated site risk assessment. Ecotoxicological effects of crude oil distillation fractions on luminescent bacteria (Vibrio fischeri), earthworms (Dendrobaena hortensis) and invertebrates (Heterocypris incongruens) were tested using two spiked soils and their elutriates. Fraction 2 (F2) had an equivalent carbon number (ECN) range of >10 to 16, and F3 from >16 to 39. F2 showed a substantially higher ecotoxicological effect than F3 for Vibrio and Dendrobaena. In contrast, severe inhibition of Heterocypris by the poorly soluble F3 is attributed to mechanical organ blockage. Immediate sequestration of PHC to the organic matter-rich soil effected reduced toxicity for all organisms. This study indicates that a more differentiated consideration (i) of PHC mixtures based on ECN range and (ii) of model soil properties employed for ecotoxicity testing should be included into PHC-contaminated site risk assessment.

Reliable approaches for predicting pollutant build-up are essential for accurate urban stormwater quality modelling. Based on the in-depth investigation of metal build-up on residential road surfaces, this paper presents empirical models for predicting metal loads on these surfaces. The study investigated metals commonly present in the urban environment. Analysis undertaken found that the build-up process for metals primarily originating from anthropogenic (copper and zinc) and geogenic (aluminium, calcium, iron and manganese) sources were different. Chromium and nickel were below detection limits. Lead was primarily associated with geogenic sources, but also exhibited a significant relationship with anthropogenic sources. The empirical prediction models developed were validated using an independent data set and found to have relative prediction errors of 12–50%, which is generally acceptable for complex systems such as urban road surfaces. Also, the predicted values were very close to the observed values and well within 95% prediction interval.

Industrial nitrogen (N) emissions in the Athabasca oil sands region (AOSR), Alberta, Canada, affect nitrate (NO3) and ammonium (NH4) deposition rates in close vicinity of industrial emitters. NO3–N and NH4–N open field and throughfall deposition rates were determined at various sites between 3 km and 113 km distance to the main oil sand operations between May 2008 and May 2009. NO3 and NH4 were analyzed for δ15N–NO3, δ18O–NO3, Δ17O–NO3 and δ15N–NH4. Marked differences in the δ18O and Δ17O values between industrial emissions and background deposition allowed for the estimation of minimum industrial contributions to atmospheric NO3 deposition. δ15N–NH4 values also allowed for estimates of industrial contributions to atmospheric NH4 deposition. Results revealed that particularly sites within ∼30 km radius from the main oil sands developments are significantly affected by industrial contributions to atmospheric NO3 and NH4 deposition.

Arsenic accumulation in rice grain has been identified as a major problem in some regions of Asia. A study was conducted to investigate the effect of increased organic matter in the soil on the release of arsenic into soil pore water and accumulation of arsenic species within rice grain. It was observed that high concentrations of soil arsenic and organic matter caused a reduction in plant growth and delayed flowering time. Total grain arsenic accumulation was higher in the plants grown in high soil arsenic in combination with high organic matter, with an increase in the percentage of organic arsenic species observed. The results indicate that the application of organic matter should be done with caution in paddy soils which have high soil arsenic, as this may lead to an increase in accumulation of arsenic within rice grains. Results also confirm that flooding conditions substantially increase grain arsenic.

We determined the first nationwide inventories of alkylphenol surfactants in U.S. sewage sludges (SS) using samples from the U.S. Environmental Protection Agency's 2001 national SS survey. Additionally, analysis of archived 3-year outdoor mesocosm samples served to determine chemical fates in SS-amended soil. Nonylphenol (NP) was the most abundant analyte (534 ± 192 mg/kg) in SS composites, followed by its mono- and di-ethoxylates (62.1 ± 28 and 59.5 ± 52 mg/kg, respectively). The mean annual load of NP and its ethoxylates in SS was estimated at 2408–7149 metric tonnes, of which 1204–4289 is applied on U.S. land. NP compounds showed observable loss from SS/soil mixtures (1:2), with mean half-lives ranging from 301 to 495 days. Surfactant levels in U.S. SS ten-times in excess of European regulations, substantial releases to U.S. soils, and prolonged half-lives found under field conditions, all argue for the U.S. to follow Europe's move from 20 years ago to regulate these chemicals.

Here we evaluate the performance and limitations of two frequently used model-types to predict trace element solubility in soils: regression based “partition-relations” and thermodynamically based “multisurface models”, for a large set of elements. For this purpose partition-relations were derived for As, Ba, Cd, Co, Cr, Cu, Mo, Ni, Pb, Sb, Se, V, Zn. The multi-surface model included aqueous speciation, mineral equilibria, sorption to organic matter, Fe/Al-(hydr)oxides and clay. Both approaches were evaluated by their application to independent data for a wide variety of conditions. We conclude that Freundlich-based partition-relations are robust predictors for most cations and can be used for independent soils, but within the environmental conditions of the data used for their derivation. The multisurface model is shown to be able to successfully predict solution concentrations over a wide range of conditions. Predicted trends for oxy-anions agree well for both approaches but with larger (random) deviations than for cations.

The inducibility and specificity of different czcRS operons in Pseudomonas putida X4 were studied by lacZ gene fusions. The data of β-glycosidase activity confirmed that the czcR3 promoter responded quantitatively to zinc. A zinc-specific biosensor, P. putida X4 (pczcR3GFP), was constructed by fusing a promoterless enhanced green fluorescent protein (egfp) gene with the czcR3 promoter in the chromosome of P. putida X4. In water extracts of four different soils amended with zinc, the reporter strain detected about 90% of the zinc content of the samples. Both the bioavailability assessment and the sequential extraction analysis demonstrated that the immobilization of zinc was highly dependent on the physico-chemical properties of soils. The results also showed that the lability of zinc decreased over time. It is concluded that the biosensor constitutes an alternative system for the convenient evaluation of zinc toxicity in the environment.