The inconsistency of available methods and the lack of harmonization in current microplastics (MPs) analysis in soils demand approaches for extraction and quantification which can be utilized across a wide variety of soil types. To enable robust and accurate assessment of extraction workflows, PET MPs with an inorganic tracer (Indium, 0.2% wt) were spiked into individual soil subgroups and standard soils with varying compositions. Due to the selectivity of the metal tracer, MPs recovery rates could be quickly and quantitatively assessed using ICP-MS. The evaluation of different methods specifically adapted to the soil properties were assessed by isolating MPs from complex soil matrices by systematically investigating specific subgroups (sand, silt, clay, non-lignified and lignified organic matter) before applying the workflow to standard soils. Removal of recalcitrant organic matter is one of the major hurdles in isolating MPs for further size and chemical characterization, requiring novel approaches to remove lignocellulosic structures. Therefore, a new biotechnological method (3-F-Ultra) was developed which mimics natural degradation processes occurring in aerobic (Fenton) and anaerobic fungi (CAZymes). Finally, a Nile Red staining protocol was developed to evaluate the suitability of the workflow for non-metal-doped MPs, which requires a filter with minimal background residues for further chemical identification, e.g. by μFTIR spectroscopy. Image analysis was performed using a Deep Learning tool, allowing for discrimination between the number of residues in bright-field and MPs counted in fluorescence mode to calculate a Filter Clearness Index (FCI). To validate the workflow, three well-characterized standard soils were analyzed applying the final method, with recoveries of 88% for MPs fragments and 74% for MPs fibers with an average FCI of 0.75. Collectively, this workflow improves our current understanding of how to adapt extraction protocols according to the target soil composition, allowing for improved MPs analysis in environmental sampling campaigns.

Tasmanian recreational fishers have reported the presence of dark pigmentations in the usually white fillets of southern sand flathead (Platycephalus bassensis), a phenomenon known as muscle melanisation. Based on histology, it is suggested that eumelanin and pheomelanin are involved in the occurrence of the phenomenon. A gross melanisation scoring system was validated through a comparison with an image analysis technique, that quantified the percentage surface area of the fillets affected by muscle melanisation. The occurrence of muscle melanisation was most severe in fish inhabiting Deceitful Cove, Tamar Estuary. This indicated that muscle melanisation in P. bassensis may be caused by yet to be identified site specific factors. No significant relationships were evident between the percentage surface area of melanised muscle with condition index, age, sex, maturation stage, fish weight, fish length and size of melano-macrophage centres in the liver or spleen. Overall, this study has provided critical information that will frame the direction and focus of future P. bassensis muscle melanisation research.

As a strong reductant and highly active alkali, hydrazine (N2H4) has been widely used in chemical industry, pharmaceutical manufacturing and agricultural production. However, its high acute toxicity poses a threat to ecosystem and human health. In the present study, a ratiometric fluorescent probe for the detection of N2H4 was designed, utilizing dicyanoisophorone as the fluorescent group and 4-bromobutyryl moiety as the recognition site. 4-(2-(3-(dicyanomethylene)-5,5-dimethylcyclohex-1-enyl) phenyl 4-brobutanoate (DDPB) was readily synthesized and could specially sense N2H4 via an intramolecular charge transfer (ICT) pathway. The cyclization cleavage reaction of N2H4 with a 4-bromobutyryl group released phenolic hydroxyl group and reversed the ICT process between hydroxy group and fluorophore, turning on the fluorescence in the DDPB-N2H4 complexes. DDPB exhibits a low cytotoxicity, reasonable cell permeability, a large Stokes shift (186 nm) and a low detection limit (86.3 nM). The quantitative determination of environmental water systems and the visualization fluorescence of DDPB test strips provides a strong evidence for the applications of DDPB. In addition, DDPB is suitable for the fluorescence imaging of exogenous N2H4 in HeLa cells and zebrafish.

Odontarrhena muralis is one of the most promissing plant species for Ni phytomining, and soil amendments can further increase its Ni phytoextraction ability. Here we investigated whether Ni phytomining/phytoremediation using this Ni hyperaccumulator can benefit from applying citric acid to a serpentine soil that is naturally enriched in Ni (>1000 mg kg⁻¹). Synchrotron micro X-ray fluorescence (μ-SXRF) was used to image Ni and other metal distributions in whole fresh leaves of O. muralis. Leaf Ni accumulation in plants grown on citric acid-amended soil increased up to 55% while Co, Cr, Fe, Mn, and Zn concentrations were 4-, 14-, 6-, 7- and 1.3-fold higher than the control treatment. O. muralis presented high bioconcentration factors (leaf to soil concentration ratio) to Ni and Zn whereas Cr was seemingly excluded from uptake. The μ-SXRF images showed a uniform distribution of Ni, preferential localization of Co in the leaf tip, and clear concentration of Mn in the base of trichomes. The citric acid treatments strongly increased the Co fluoerescence intensity in the leaf tip and altered the spatial distribution of Mn across the leaf, but there was no difference in Ni fluorescence counts between the trichome-base region and the bulk leaf. Our data from a serpentine soil suggests that citrate treatment enhances Ni uptake, but Co is excreted from leaves even in low leaf concentrations, which can make Co phytoming using O. muralis unfeasible in natural serpentine soils.

Microplastic pollution within the marine environment is of pressing concern globally. Accordingly, spatial monitoring of microplastic concentrations, composition and size distribution may help to identify sources and entry pathways, and hence allow initiating focused mitigation. Spatial distribution patterns of microplastics were investigated in two compartments of the southern North Sea by collecting sublittoral sediment and surface water samples from 24 stations. Large microplastics (500−5000 μm) were detected visually and identified using attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy. The remaining sample was digested enzymatically, concentrated onto filters and analyzed for small microplastics (11−500 μm) using Focal Plane Array (FPA) FTIR imaging. Microplastics were detected in all samples with concentrations ranging between 2.8 and 1188.8 particles kg−1 for sediments and 0.1–245.4 particles m−3 for surface waters. On average 98% of microplastics were <100 μm in sediments and 86% in surface waters. The most prevalent polymer types in both compartments were polypropylene, acrylates/polyurethane/varnish, and polyamide. However, polymer composition differed significantly between sediment and surface water samples as well as between the Frisian Islands and the English Channel sites. These results show that microplastics are not evenly distributed, in neither location nor size, which is illuminating regarding the development of monitoring protocols.

In the present study, we evaluate our previously developed non-destructive soil algal toxicity method using species from a different class of algae; Class Trebouxiophyceae (Chlorella vulgaris and Chlorella sorokiniana), and directly measure the photosynthetic activity of these species adsorbed onto the soil as a new toxicity endpoint. This study shows that non-destructive soil algal toxicity method is applicable to non-specific test species, including those of Class Trebouxiophyceae as well as Class Chlorophyceae (Chlorococcum infusionum and Chlamydomonas reinhardtii). Furthermore, by performing photosynthesis image analysis, we verify that it is possible to measure the photosynthetic activity of soil algae Chlorella vulgaris adsorbed onto soils without the need to extract algal cells from the soil. We propose that the non-destructive soil algal toxicity method represents a novel technique for 1) evaluating pollutants in soil using non-specific algae and 2) conveniently and rapidly assessing the photosynthetic activity of soil algae Chlorella vulgaris adsorbed onto soil as a new toxicity endpoint.

CuO engineered nanoparticles (NPs) are of increasing concern due to their extensive use in daily life and adverse effect on aquatic organisms. The investigations on the toxicity of CuO NPs to aquatic plants through uptake from roots versus fronds are limited. This paper discusses the interactions of CuO NPs with Lemna minor, a floating plant. After CuO NPs (150 μg L⁻¹) exposure for 7 days, the frond number, frond surface area and dry weights of whole plants significantly decreased by 32%, 47% and 33%; the responses were dose-dependent. Microscopy imaging showed that the epidermis was severely damaged in fronds, edges were severely sloughed off and cell integrity was damaged in roots. Shrinkage of both chloroplast and starch grains were observed in the frond cells. Internalization of CuO NPs in root and frond cells during CuO NPs (1 mg L⁻¹) exposure was confirmed with the root Cu levels of Lemna minor being three times higher than the fronds by using transmission electron microscopy and flame atomic absorption spectrophotometry. Reactive oxygen species, mainly H₂O₂ (increased by 56%) and ·OH (increased by 57%), accumulated in Lemna minor tissues in response to CuO NPs exposure. Moreover, chloroplasts were confirmed as a site of ROS production. These findings are helpful for better understanding the biological responses of aquatic plants upon NPs exposure.

Artificial lighting at night has becoming a new type of pollution posing an important anthropogenic environmental pressure on organisms. The objective of this research was to examine the potential association between nighttime artificial light pollution and nest densities of the three main sea turtle species along Florida beaches, including green turtles, loggerheads, and leatherbacks. Sea turtle survey data was obtained from the “Florida Statewide Nesting Beach Survey program”. We used the new generation of satellite sensor “Visible Infrared Imaging Radiometer Suite (VIIRS)” (version 1 D/N Band) nighttime annual average radiance composite image data. We defined light pollution as artificial light brightness greater than 10% of the natural sky brightness above 45° of elevation (>1.14 × 10⁻¹¹ Wm⁻²sr⁻¹). We fitted a generalized linear model (GLM), a GLM with eigenvectors spatial filtering (GLM-ESF), and a generalized estimating equations (GEE) approach for each species to examine the potential correlation of nest density with light pollution. Our models are robust and reliable in terms of the ability to deal with data distribution and spatial autocorrelation (SA) issues violating model assumptions. All three models found that nest density is significantly negatively correlated with light pollution for each sea turtle species: the higher light pollution, the lower nest density. The two spatially extended models (GLM-ESF and GEE) show that light pollution influences nest density in a descending order from green turtles, to loggerheads, and then to leatherbacks. The research findings have an implication for sea turtle conservation policy and ordinance making. Near-coastal lights-out ordinances and other approaches to shield lights can protect sea turtles and their nests. The VIIRS DNB light data, having significant improvements over comparable data by its predecessor, the DMSP-OLS, shows promise for continued and improved research about ecological effects of artificial light pollution.

Unmanned aerial vehicles (UAVs) offer new opportunities to monitor pollution and provide valuable information to support remediation. Their low-cost, ease of use, and rapid deployment capability make them ideal for environmental emergency response. Here we present a UAV-based study of the third largest coal ash spill in the United States. Coal ash from coal combustion is a toxic industrial waste material present worldwide. Typically stored in settling ponds in close proximity to waterways, coal ash poses significant risk to the environment and drinking water supplies from both chronic contamination of surface and ground water and catastrophic pond failure. We sought to provide an independent estimate of the volume of coal ash and contaminated water lost during the rupture of the primary coal ash pond at the Dan River Steam Station in Eden, NC, USA and to demonstrate the feasibility of using UAVs to rapidly respond to and measure the volume of spills from ponds or containers that are open to the air. Using structure-from-motion (SfM) imagery analysis techniques, we reconstructed the 3D structure of the pond bottom after the spill, used historical imagery to estimate the pre-spill waterline, and calculated the volume of material lost. We estimated a loss of 66,245 ± 5678 m3 of ash and contaminated water. The technique used here allows rapid response to environmental emergencies and quantification of their impacts at low cost, and these capabilities will make UAVs a central tool in environmental planning, monitoring, and disaster response.

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM2.5 levels and wind speed.