Water treatment works have previously shown high efficiency in removing microplastics > 25 µm from raw source water. However, what is less well known is the extent to which microplastics of this size class are generated or lost within the water distribution network, particularly whether there is a greater presence in the customer tap than in the water treatment works outlet. This study focused on the presence of 21 different types of synthetic polymer particles with sizes larger than 25 µm examined through multiple rounds of sampling at outlets of water treatment works (WTW), service reservoirs (SR), and customer taps (CT) managed by seven different water companies in Britain. Nineteen different types of polymers were detected; their signature and concentration varied based on the round of sampling, the location within the water supply network, and the water company responsible for managing the supply. Among the polymers examined, polyamide (PA), polyethene terephthalate (PET), polypropylene (PP), and polystyrene (PS) were the most commonly found. Apart from PET having its highest concentration of 0.0189 microplastic per litre (MP/L) in the SR, the concentrations of the other three most frequent polymers (PS = 0.017 MP/L, PA = 0.0752 MP/L, PP= 0.1513 MP/L) were highest in the CT. The overall prevalence of this size of microplastics in the network is low, but there was a high variability of polymer types and occurrences. These spatial and temporal variations suggested that the MP in the distribution network may exist as a series of pulses. Given the presence and polymer types, the potential for some of the microplastics to originate from materials used in the water network and domestic plumbing systems cannot be ruled out. As found before, the absolute number of microplastics in the water distribution network remained extremely low.

Summary: Some plant growth promoting bacteria (PGPB) are enigmatic in enhancing plant growth in the face of increased metal accumulation in plants. Since most PGPB colonize the plant root epidermis, we hypothesized that PGPB confer tolerance to metals through changes in speciation at the root epidermis. We employed a novel combination of fluorophore‐based confocal laser scanning microscopic imaging and synchrotron based microscopic X‐ray fluorescence mapping with X‐ray absorption spectroscopy to characterize bacterial localization, zinc (Zn) distribution and speciation in the roots of Brassica juncea grown in Zn contaminated media (400 mg kg⁻¹ Zn) with the endophytic Pseudomonas brassicacearum and rhizospheric Rhizobium leguminosarum. PGPB enhanced epidermal Zn sequestration relative to PGBP‐free controls while the extent of endophytic accumulation depended on the colonization mode of each PGBP. Increased root accumulation of Zn and increased tolerance to Zn was associated predominantly with R. leguminosarum and was likely due to the coordination of Zn with cysteine‐rich peptides in the root endodermis, suggesting enhanced synthesis of phytochelatins or glutathione. Our mechanistic model of enhanced Zn accumulation and detoxification in plants inoculated with R. leguminosarum has particular relevance to PGPB enhanced phytoremediation of soils contaminated through mining and oxidation of sulphur‐bearing Zn minerals or engineered nanomaterials such as ZnS.

A common technique to quantitatively estimate P speciation in soil samples is to apply linear combination fitting (LCF) to normalized P K-edge X-ray absorption near-edge structure (XANES) spectra. Despite the rapid growth of such applications, the uncertainties of the fitted weights are still poorly known. Further, there are few reports to what extent the LCF standards represent unique end-members. Here, the co-variance between 34 standards was determined and their significance for LCF was discussed. We present a probabilistic approach for refining the calculation of LCF weights based on Latin hypercube sampling of normalized XANES spectra, where the contributions of energy calibration and normalization to fit uncertainty were considered. Many of the LCF standards, particularly within the same standard groups, were strongly correlated. This supports an approach in which the LCF standards are grouped. Moreover, adsorbed phytates and monetite were well described by other standards, which puts into question their use as end-members in LCF. Use of the probabilistic method resulted in uncertainties ranging from 2 to 11 percentage units. Uncertainties in the calibrated energy were important for the LCF weights, particularly for organic P, which changed with up to 2.7 percentage units per 0.01 eV error in energy. These results highlight the necessity of careful energy calibration and the use of frequent calibration checks. The probabilistic approach, in which at least 100 spectral variants are analyzed, improves our ability to identify the most likely P compounds present in a soil sample, and a procedure for this is suggested in the paper.