Plastic pollution is ubiquitous throughout the marine environment, with microplastic (i.e. <5 mm) contamination a global issue of emerging concern. The lack of universally accepted methods for quantifying microplastic contamination, including consistent application of microscopy, photography, an spectroscopy and photography, may result in unrealistic contamination estimates. Here, we present and apply an analysis workflow tailored to quantifying microplastic contamination in marine waters, incorporating stereomicroscopic visual sorting, microscopic photography and attenuated total reflectance (ATR) Fourier transform infrared (FTIR) spectroscopy. The workflow outlines step-by-step processing and associated decision making, thereby reducing bias in plastic identification and improving confidence in contamination estimates. Specific processing steps include (i) the use of a commercial algorithm-based comparison of particle spectra against an extensive commercially curated spectral library, followed by spectral interpretation to establish the chemical composition, (ii) a comparison against a customised contaminant spectral library to eliminate procedural contaminants, and (iii) final assignment of particles as either natural- or anthropogenic-derived materials, based on chemical type, a compare analysis of each particle against other particle spectra, and physical characteristics of particles. Applying this workflow to 54 tow samples collected in marine waters of North-Western Australia visually identified 248 potential anthropogenic particles. Subsequent ATR-FTIR spectroscopy, chemical assignment and visual re-inspection of photographs established 144 (58%) particles to be of anthropogenic origin. Of the original 248 particles, 97 (39%) were ultimately confirmed to be plastics, with 85 of these (34%) classified as microplastics, demonstrating that over 60% of particles may be misidentified as plastics if visual identification is not complemented by spectroscopy. Combined, this tailored analysis workflow outlines a consistent and sequential process to quantify contamination by microplastics and other anthropogenic microparticles in marine waters. Importantly, its application will contribute to more realistic estimates of microplastic contamination in marine waters, informing both ecological risk assessments and experimental concentrations in effect studies.

Continual efforts have been made to determine a simple and universal method of estimating heavy metal phytoavailability in terrestrial systems. In the present study, a mechanism-based multi-surface model (MSM) was developed to predict the partition of Ni(II) in soil–solution phases and its bioaccumulation in wheat (Triticum aestivum L.) in 19 Chinese soils with a wide range of soil properties. MSM successfully predicted the Ni(II) dissolution in 0.01 M CaCl2 extracting solution (R2 = 0.875). The two-site model for clay fraction improved the prediction, particularly for alkaline soils, because of the additional consideration of edge sites. More crucially, the calculated dissolved Ni(II) was highly correlated with the metal accumulation in wheat (R2 = 0.820 for roots and 0.817 for shoots). The correlation coefficients for the MSM and various chemical extraction methods have the following order: soil pore water > MSM ≈ diffuse gradient technique (DGT) > soil total Ni > 0.43 M HNO3 > 0.01 M CaCl2. The results suggested that the dissolved Ni(II) calculated using MSM can serve as an effective indicator of the bioavailability of Ni(II) in various soils; hence, MSM can be used as an supplement for metal risk prediction and assessment besides chemical extraction techniques.

The concern about environmental pollution has risen in the last decades because of its effects on human's health. However, evaluation of the exposure to certain pollutants is currently hampered by the availability of past environmental data. Tree rings are an alternative to reconstruct environmental variability of pre-instrumental periods. Nevertheless, this approach has some reported limitations including migration of chemical elements in the tree rings. The aim of this study was to evaluate the distribution of Cd, Cu, Hg, Na, Ni, Pb, Zn in the tree rings of Tipuana tipu (Fabaceae) to aid the reconstruction of past environmental pollution. We sampled trees in the central region of the city of São Paulo, Brazil, and scanned their tree rings using LA-ICP-MS. We used these data to evaluate the temporal trends of chemical elements under investigation. Results show a non-random distribution of these chemical elements within the tree rings, with higher content in the cell-walls of vessels and lower content in the fibers. Sodium was the only element intimately related to the axial parenchyma cells. Due to differences in elemental composition of xylem cells, temporal trends where evaluated using distinct quartiles of data distribution in each tree ring. The first quartile represents the lower content found in fibers and parenchyma, while the third quartile corresponds to the higher content found in vessels. Data from vessels better represent the decreasing trend of Cd, Cu, Pb, and Ni in the last three decades. This reduction is less significant for Na and Zn. Our results highlight the potential to improve the records of environmental pollution using data from different cells. Pronounced reduction in Pb may be attributed to the lead phase-out in gasoline, while the decreasing trend of Cd, Cu, Ni pollution is probably related to increasing efficiency of vehicles and the deindustrialization of São Paulo.Chemical elements are non-randomly distributed in tree rings. Chemical content of vessels cell-walls is a reliable record of metal pollution, which is decreasing in São Paulo.

Salinity effects on the bioaccumulation and biokinetic processes of eight trace elements (Cu, Cr, Pb, Ni, Zn, Cd, Se, and As) in the black mussel Septifer virgatus were explored in the present study. A 6-week laboratory waterborne exposure first showed that salinity (15, 20, 25, and 30) had relatively weak or even no significant influence on trace element accumulation in the black mussels. Biokinetics including uptake and efflux was then quantified in the mussels at different salinities. Uptake rates of Ni and Zn were negatively correlated with the salinity, while the uptake of Cd was not significantly influenced by salinity. The efflux rates of Ni and Zn also exhibited an inverse relationship with salinity, whereas the case of Cd was on the contrary. Biokinetic modeling showed that the salinity effects on uptake and elimination of Ni and Zn counteracted with each other, thus weakening the combined effects on accumulation. Overall, the response of uptake to salinity could weakened, removed, or even overturned by elimination, depending on the relative magnitude of the change of the two processes. The combined effects of uptake and elimination further led to negative, no, or positive relationship between trace element accumulation and salinity.

Air pollutant levels depend on emissions but can also be affected by the meteorological situation. We examined air pollutant trends (PM₁₀, NO₂, O₃ and SO₂) in Slovenia, where in the past the main issue were SO₂ levels. Now, the population is still exposed to PM₁₀ and ozone levels that are above the recommended levels.Our goal was to assess if the levels of air pollutants were decreasing from 2002 to 2017 due to emission ceilings or were more influenced by changes in the meteorological situation. We modelled the relationship between levels, meteorological parameters, and seasonality and then used the models with the best estimated generalisation to adjust levels for meteorology. Models showed a significant relationship between meteorological parameters and PM₁₀, NO₂, and O₃ levels, but not SO₂. We analysed trends of raw and adjusted levels and compared them. Trends of PM₁₀ and SO₂ were decreasing at all locations for raw and adjusted data. The largest decrease was observed in SO₂ levels where the largest decrease in emissions occurred. Trends of NO₂ were also significant and negative at most locations. Levels of O₃ did not exhibit a significant trend at most locations.Results show that changes in the meteorological situation affected PM₁₀ levels the most, especially where the entire period (2002–2017) could be observed. There is strong empirical evidence that changes in meteorological parameters contributed to the decrease in PM₁₀ levels while the decrease in NO₂ and SO₂ levels can be attributed to emission ceilings.

Natural gas extraction (NGE) has expanded rapidly in the United States in recent years. Despite concerns, there is little information about the effects of NGE on air quality or personal exposures of people living or working nearby. Recent research suggests NGE emits polycyclic aromatic hydrocarbons (PAHs) into air. This study used low-density polyethylene passive samplers to measure concentrations of PAHs in air near active (n = 3) and proposed (n = 2) NGE sites. At each site, two concentric rings of air samplers were placed around the active or proposed well pad location. Silicone wristbands were used to assess personal PAH exposures of participants (n = 19) living or working near the sampling sites. All samples were analyzed for 62 PAHs using GC-MS/MS, and point sources were estimated using the fluoranthene/pyrene isomer ratio. ∑PAH was significantly higher in air at active NGE sites (Wilcoxon rank sum test, p < 0.01). PAHs in air were also more petrogenic (petroleum-derived) at active NGE sites. This suggests that PAH mixtures at active NGE sites may have been affected by direct emissions from petroleum sources at these sites. ∑PAH was also significantly higher in wristbands from participants who had active NGE wells on their properties than from participants who did not (Wilcoxon rank sum test, p < 0.005). There was a significant positive correlation between ∑PAH in participants' wristbands and ∑PAH in air measured closest to participants’ homes or workplaces (simple linear regression, p < 0.0001). These findings suggest that living or working near an active NGE well may increase personal PAH exposure. This work also supports the utility of the silicone wristband to assess personal PAH exposure.

As the metabolites of tetrabromobisphenol A (TBBPA), tetrabromobisphenol A mono- and di-methyl ethers (TBBPA MME and TBBPA DME) have been detected in various environmental media. However, knowledge of the contribution of plants to their environmental fates, especially to the interactions between TBBPA DME and TBBPA, is quite limited. In this study, the metabolism and behaviors of TBBPA DME was studied with pumpkin plants through 15-day hydroponic exposure. The TBBPA were also studied separately using in-lab hydroponic exposure for comparison. The results showed that more TBBPA DME accumulated in pumpkin roots and translocated up to stems and leaves compared with TBBPA. Transformation of TBBPA DME occurred later and more slowly than that of TBBPA. Interconversion between TBBPA DME and TBBPA was verified in intact plants for the first time. Namely, TBBPA DME can be biotransformed to TBBPA MME (transformation ratio in mole mass, TRMM 0.50%) and to TBBPA (TRMM 0.53%) within pumpkin; and TBBPA can be biotransformed to TBBPA MME (TRMM 0.58%) and to TBBPA DME (TRMM 0.62%). In addition, two single benzene-ring metabolites, 2,6-dibromo-4-(2-(2-hydroxyl)-propyl)-anisole (DBHPA, TRMM 3.4%) with an O-methyl group and 2,6-dibromo-4-(2-(2-hydroxyl)-propyl)-phenetole (DBHPP, TRMM 0.57%) with an O-ethyl group, were identified as the transformation products in the TBBPA exposure experiments. The transformation and interconversion from TBBPA DME back to TBBPA is reported as a new pathway and potential source for TBBPA in the environment.

The release of toxic organic pollutants and heavy metals by primitive electronic waste (e-waste) processing to waterways has raised significant concerns, but little is known about their potential ecological effects on aquatic biota especially microorganisms. We characterized the microbial community composition and diversity in sediments sampled along two rivers consistently polluted by e-waste, and explored how community functions may respond to the complex combined pollution. High-throughput 16S rRNA gene sequencing showed that Proteobacteria (particularly Deltaproteobacteria) dominated the sediment microbial assemblages followed by Bacteroidetes, Acidobacteria, Chloroflexi and Firmicutes. PICRUSt metagenome inference provided an initial insight into the metabolic potentials of these e-waste affected communities, speculating that organic pollutants degradation in the sediment might be mainly performed by some of the dominant genera (such as Sulfuricurvum, Thiobacillus and Burkholderia) detected in situ. Statistical analyses revealed that toxic organic compounds contributed more to the observed variations in sediment microbial community structure and predicted functions (24.68% and 8.89%, respectively) than heavy metals (12.18% and 4.68%), and Benzo(a)pyrene, bioavailable lead and electrical conductivity were the key contributors. These results have shed light on the microbial assemblages in e-waste contaminated river sediments, indicating a potential influence of e-waste pollution on the microbial community structure and function in aquatic ecosystems.

The environmental impact of endocrine-disrupting chemicals (EDCs)—compounds that interfere with endocrine system function at minute concentrations—is now well established. In recent years, concern has been mounting over a group of endocrine disruptors known as hormonal growth promotants (HGPs), which are natural and synthetic chemicals used to promote growth in livestock by targeting the endocrine system. One of the most potent compounds to enter the environment as a result of HGP use is 17β-trenbolone, which has repeatedly been detected in aquatic habitats. Although recent research has revealed that 17β-trenbolone can interfere with mechanisms of sexual selection, its potential to impact sequential female mate choice remains unknown, as is true for all EDCs. To address this, we exposed female guppies (Poecilia reticulata) to 17β-trenbolone at an environmentally relevant level (average measured concentration: 2 ng/L) for 21 days using a flow-through system. We then compared the response of unexposed and exposed females to sequentially presented stimulus (i.e., unexposed) males that varied in their relative body area of orange pigmentation, as female guppies have a known preference for orange colouration in males. We found that, regardless of male orange pigmentation, both unexposed and exposed females associated with males indiscriminately during their first male encounter. However, during the second male presentation, unexposed females significantly reduced the amount of time they spent associating with low-orange males if they had previously encountered a high-orange male. Conversely, 17β-trenbolone-exposed females associated with males indiscriminately (i.e., regardless of orange colouration) during both their first and second male encounter, and, overall, associated with males significantly less than did unexposed females during both presentations. This is the first study to demonstrate altered sequential female mate choice resulting from exposure to an endocrine disruptor, highlighting the need for a greater understanding of how EDCs may impact complex mechanisms of sexual selection.