A cross-reactive plasmonic sensing array for drinking water assessment.

The continuous monitoring of remote drinking water purification systems is a global challenge with direct consequences for human and environmental health. Here, we utilise a "nano-tastebud" sensor comprised of eight chemically-tailored plasmonic metasurfaces, for testing the composition of drinking water. Through undertaking a full chemometric analysis of the water samples and likely contaminants we were able to optimise the sensor specification to create an array of suitable tastebuds. By generating a unique set of optical responses for each water sample, we show that the array-based sensor can differentiate between untreated influent and treated effluent water with over 95% accuracy in flow and can detect compositional changes in distributed modified tap water. Once fully developed, this system could be integrated into water treatment facilities and distribution systems to monitor for changes in water composition.

BODIPY-Labeled Estrogens for Fluorescence Analysis of Environmental Microbial Degradation.

Biodegradation of estrogen hormone micropollutants is a well-established approach toward their remediation. Fluorescently labeled substrates are used extensively for rapid, near-real-time analysis of biological processes and are a potential tool for studying biodegradation processes faster and more efficiently than conventional approaches. However, it is important to understand how the fluorescently tagged surrogates compare with the natural substrate in terms of chemical analysis and the intended application. We derivatized three natural estrogens with BODIPY fluorophores by azide-alkyne cycloaddition click reaction and developed an analytical workflow based on simple liquid-liquid extraction and HPLC-PDA analysis. The developed methods allow for concurrent analysis of both fluorescent and natural estrogens with comparable recovery, accuracy, and precision. We then evaluated the use of BODIPY-labeled estrogens as surrogate substrates for studying biodegradation using a model bacterium for estrogen metabolism. The developed analytical methods were successfully employed to compare the biological transformation of 17ß-estradiol (E2), with and without the BODIPY fluorescent tag. Through measuring the complete degradation of E2 and the transformation of BODIPY-estradiol to BODIPY-estrone in the presence of a co-substrate, we found that BODIPY-labeled estrogens are biologically viable surrogates for investigating biodegradation in environmental bacteria.

Highly sensitive detection of estradiol by a SERS sensor based on TiO2 covered with gold nanoparticles.

We propose the use of gold nanoparticles grown on the surface of nanoporous TiO2 films as surface-enhanced Raman scattering (SERS) sensors for the detection of 17ß-estradiol. Gold deposition on top of a TiO2 surface leads to the formation of nanoparticles the plasmonic properties of which fulfil the requirements of a SERS sensor. The morphological and optical properties of the surface were investigated. Specifically, we demonstrate that the TiO2 background pressure during pulsed laser deposition and the annealing conditions offer control over the formation of Au nanoparticles with different sizes, shapes and distributions, yielding a versatile sensor. We have exploited the surface for the detection of 17ß-estradiol, an emerging contaminant in environmental waters. We have found a limit of detection of 1 nM with a sensitivity allowing for a dynamic range of five orders of magnitude (up to 100 µM).

Average daily flow of microplastics through a tertiary wastewater treatment plant over a ten-month period.

Microplastics (MPs, <5 mm in size) are classified as emerging contaminants but treatment processes are not designed to remove these small particles. Wastewater treatment systems have been proposed as pathways for MPs pollution to receiving waters but quantitative and qualitative data on MP occurrence and transport remains limited, hindering risk assessment and regulation. Here, for the first time, the stepwise abundance and loading of MPs (60-2800 µm) in a tertiary wastewater treatment plant in the UK was assessed by sampling from May 2017 to February 2018. Microplastics were found in all sampling campaigns, with an average inflow of 8.1 × 108 (95% CI, 3.8 × 108 to 1.2 × 109) items day-1. Their prevalence decreased from influent to final effluent. Overall abundances decreased on average by 6%, 68%, 92%, and 96% after the pre-treatment, primary, secondary, and tertiary treatment stages respectively, although considerable variability occurred throughout the year. Sufficient particles remained in the treated effluent to generate an average discharge of 2.2 × 107 (95% CI, 1.2 × 107 to 3.2 × 107]) particles day-1 to the recipient river. Secondary MPs were predominant, while primary MP abundances were minimal. Fibres comprised 67% of all items, followed by films (18%) and fragments (15%). Chemical characterisation confirmed the presence of different types of polymers, with polypropylene fibres and fragments most abundant (23%). This research informs understanding of how wastewater effluent may channel MPs to the natural environment and their composition, and helps understand control points for optimising advanced treatment processes.

Systems biology approach to elucidation of contaminant biodegradation in complex samples - integration of high-resolution analytical and molecular tools.

We present here a data-driven systems biology framework for the rational design of biotechnological solutions for contaminated environments with the aim of understanding the interactions and mechanisms underpinning the role of microbial communities in the biodegradation of contaminated soils. We have considered a multi-omics approach that employs novel in silico tools to combine high-throughput sequencing data (16S rRNA amplicons) with chemical data including high-resolution analytical data generated by comprehensive two-dimensional gas chromatography (GC × GC). To assess this approach, we have considered a matching dataset with both microbiological and chemical signatures available for samples from two former manufactured gas plant sites. On this dataset, we applied the numerical procedures informed by ecological principles (predominantly diversity measures) as well as recently published statistical approaches that give discriminatory features and their correlations by maximizing the covariances between multiple datasets on the same sample space. In particular, we have utilized sparse projection to latent discriminant analysis and its derivative to multiple datasets, an N-integration algorithm called DIABLO. Our results indicate microbial community structure dependent on the contaminated environment and unravel promising interactions of some of the microbial species with biodegradation potential. To the best of our knowledge, this is the first study that incorporates with the microbiome an unprecedented high-level distribution of hydrocarbons obtained through GC × GC.

Microscopy and elemental analysis characterisation of microplastics in sediment of a freshwater urban river in Scotland, UK.

Understanding of the sources, fate, and impact of microplastics (MPs, < 5 mm) remains limited, particularly in freshwater environments, while limited comparability across available surveys hinders adequate monitoring and risk assessment of these contaminants. Here, the distribution of microscopic debris in an urban river close to the marine environment in the West of Scotland was investigated to assess concentration and distribution of primary and secondary MPs. Also, the efficiency of light and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS) was evaluated for characterisation and quantification of MPs sized 2.8 mm-11 µm. Bank sediment samples were collected twice from the River Kelvin in Glasgow and were size-fractionated and processed for extraction of MPs by density separation. Sample MPs spiking and use of procedural blanks allowed the influence of processing on field data quality to be considered. Total abundances were 161-432 MPs kg-1 dry sediment, with fibres as the dominant type, comprising > 88% of total counts. Nevertheless, fibres in blanks suggest potential contributions from atmospheric contamination. Moreover, fibres concentrated mainly in fractions < 0.09 mm suggesting that their fate may be influenced by drivers of fine sediment dynamics in rivers. While no primary MPs were observed, metallic and glass pellets were present in high abundances in settled material and could be easily misidentified by visual inspection, demonstrating that compositional analysis is needed to avoid analytical errors from MP misidentification and overestimation. SEM-EDS allowed for a quick screening of plastic vs non-plastic pellets and improved identification of smaller fragments, whereas more advanced techniques are needed for proper identification of fibres. This study is the first to report on MPs in freshwater rivers in Scotland and suggests that diffuse sources of pollution may be delivering secondary MPs to the river. Their sources, fate, and risk in these systems will thus warrant further attention.

Bioaugmentation Mitigates the Impact of Estrogen on Coliform-Grazing Protozoa in Slow Sand Filters.

Exposure to endocrine-disrupting chemicals (EDCs), such as estrogens, is a growing issue for human and animal health as they have been shown to cause reproductive and developmental abnormalities in wildlife and plants and have been linked to male infertility disorders in humans. Intensive farming and weather events, such as storms, flash flooding, and landslides, contribute estrogen to waterways used to supply drinking water. This paper explores the impact of estrogen exposure on the performance of slow sand filters (SSFs) used for water treatment. The feasibility and efficacy of SSF bioaugmentation with estrogen-degrading bacteria was also investigated, to determine whether removal of natural estrogens (estrone, estradiol, and estriol) and overall SSF performance for drinking water treatment could be improved. Strains for SSF augmentation were isolated from full-scale, municipal SSFs so as to optimize survival in the laboratory-scale SSFs used. Concentrations of the natural estrogens, determined by gas chromatography coupled with mass spectrometry (GC-MS), revealed augmented SSFs reduced the overall estrogenic potency of the supplied water by 25% on average and removed significantly more estrone and estradiol than nonaugmented filters. A negative correlation was found between coliform removal and estrogen concentration in nonaugmented filters. This was due to the toxic inhibition of protozoa, indicating that high estrogen concentrations can have functional implications for SSFs (such as impairing coliform removal). Consequently, we suggest that high estrogen concentrations could impact significantly on water quality production and, in particular, on pathogen removal in biological water filters.

Fingerprinting polychlorinated biphenyls in environmental samples using comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry.

A GC × GC-TOFMS installed with a Rtx-PCB (60 m × 0.18 mm × 0.18 µm) in the first dimension and Rxi- 17 (1.5 m × 0.1 mm × 0.1 µm) column in the second dimension was used to separate 188 out of 209 congeners. A further 12 congeners were identified through additional data processing resulting in the identification of a total of 200 congeners. However, caution is advised if these 12 congeners were to be used in quantitative assessments. The remaining 9 co-eluting congeners were three doublets (CB65 + CB62, CB160 + CB163 and CB201 + CB204) and one triplet (CB20 + CB21 + CB33). This method was tested on five Aroclors and resulted in the separation of all congeners present in the heavier Aroclor mixtures A1254 and A1260. The suitability of this method for applications in biological matrices was demonstrated on extracted whiting and guillemot liver samples which resulted in the identification of 137 individual PCBs in the whiting liver sample and 120 in the guillemot sample. Fingerprinting was able to show clear differences in the PCB signature of the two animals. This highlights the potential of this method for PCB fingerprinting in environmental forensics studies and other assessments that require congener specific analysis.

Multivariate statistical methods for the environmental forensic classification of coal tars from former manufactured gas plants.

Compositional disparity within a set of 23 coal tar samples (obtained from 15 different former manufactured gas plants) was compared and related to differences between historical on-site manufacturing processes. Samples were prepared using accelerated solvent extraction prior to analysis by two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. A suite of statistical techniques, including univariate analysis, hierarchical cluster analysis, two-dimensional cluster analysis, and principal component analysis (PCA), were investigated to determine the optimal method for source identification of coal tars. The results revealed that multivariate statistical analysis (namely, PCA of normalized, preprocessed data) has the greatest potential for environmental forensic source identification of coal tars, including the ability to predict the processes used to create unknown samples.

Ultra resolution chemical fingerprinting of dense non-aqueous phase liquids from manufactured gas plants by reversed phase comprehensive two-dimensional gas chromatography.

Ultra resolution chemical fingerprinting of dense non-aqueous phase liquids (DNAPLs) from former manufactured gas plants (FMGPs) was investigated using comprehensive two-dimensional gas chromatography coupled with time of flight mass spectrometry (GC×GC TOFMS). Reversed phase GC×GC (i.e. a polar primary column coupled to a non-polar secondary column) was found to significantly improve the separation of polycyclic aromatic hydrocarbons (PAHs) and their alkylated homologues. Sample extraction and cleanup was performed simultaneously using accelerated solvent extraction (ASE), with recovery rates between 76% and 97%, allowing fast, efficient extraction with minimal solvent consumption. Principal component analysis (PCA) of the GC×GC data was performed in an attempt to differentiate between twelve DNAPLs based on their chemical composition. Correlations were discovered between DNAPL composition and historic manufacturing processes used at different FMGP sites. Traditional chemical fingerprinting methods generally follow a tiered approach with sample analysis on several different instruments. We propose ultra resolution chemical fingerprinting as a fast, accurate and precise method of obtaining more chemical information than traditional tiered approaches while using only a single analytical technique.