Copper and zinc are metals that have been traditionally thought of as past contamination legacies. However, their industrial use is still extensive and current applications (e.g. nanoparticles and antifouling paints) have become additional marine environment delivery routes. Determining a pollutant's genotoxicity is an ecotoxicological priority, but in marine benthic systems putative substances responsible for sediment genotoxicity have rarely been identified. Studies that use sediment as the delivery matrix combined with exposures over life-history relevant timescales are also missing for metals. Here we assess copper and zinc's genotoxicity by exposing the ecologically important polychaete Alitta virens to sediment spiked with environmentally relevant concentrations for 9 months. Target bioavailable sediment and subsequent porewater concentrations reflect the global contamination range for coasts, whilst tissue concentrations, although elevated, were comparable with other polychaetes. Survival generally reduced as concentrations increased, but monthly analyses show that growth was not significantly different between treatments. The differential treatment mortality may have enabled the surviving worms in the high concentration treatments to capture more food thus removing any concentration treatment effects for biomass. Using the alkaline comet assay we confirm that both metals via the sediment are genotoxic at concentrations routinely found in coastal regions and this is supported by elevated DNA damage in worms from field sites. However, combined with the growth data it also highlights the tolerance of A. virens to DNA damage. Finally, using long term (decadal) monitoring data we show stable or increasing sediment concentrations of these metals for many areas. This will potentially mean coastal sediment is a significant mutagenic hazard to the benthic community for decades to come. An urgent reappraisal of the current input sources for these ‘old pollutants’ is, therefore, required.

Spatiotemporal resolved models were developed predicting daily fine particulate matter (PM₂.₅) concentrations across Switzerland from 2003 to 2013. Relatively sparse PM₂.₅ monitoring data was supplemented by imputing PM₂.₅ concentrations at PM₁₀ sites, using PM₂.₅/PM₁₀ ratios at co-located sites. Daily PM₂.₅ concentrations were first estimated at a 1 × 1km resolution across Switzerland, using Multiangle Implementation of Atmospheric Correction (MAIAC) spectral aerosol optical depth (AOD) data in combination with spatiotemporal predictor data in a four stage approach. Mixed effect models (1) were used to predict PM₂.₅ in cells with AOD but without PM₂.₅ measurements (2). A generalized additive mixed model with spatial smoothing was applied to generate grid cell predictions for those grid cells where AOD was missing (3). Finally, local PM₂.₅ predictions were estimated at each monitoring site by regressing the residuals from the 1 × 1km estimate against local spatial and temporal variables using machine learning techniques (4) and adding them to the stage 3 global estimates. The global (1 km) and local (100 m) models explained on average 73% of the total,71% of the spatial and 75% of the temporal variation (all cross validated) globally and on average 89% (total) 95% (spatial) and 88% (temporal) of the variation locally in measured PM₂.₅ concentrations.

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.

Poly- and per-fluoroalkyl substances (PFAS) and volatile methyl siloxanes (VMS) were monitored at 21 sites in the Global Atmospheric Passive Sampling (GAPS) Network. Atmospheric concentrations previously reported from 2009 were compared to concentrations measured at these sites in 2013 and 2015, to assess trends over 7 years of monitoring. Concentrations of the fluorotelomer alcohols (FTOHs) and fluorinated sulfonamides and sulfonamidoethanols (FOSAs and FOSEs) were stable at these sites from 2009 to 2015 with no significant difference (p > 0.05) in concentrations. Elevated concentrations of all the neutral PFAS were detected at the urban sites as compared to the polar/background sites. The perfluorosulfonic acids (PFSAs), meanwhile, saw a significant increase (p < 0.001) in concentrations from 2009 to 2015. The perfluorocarboxylic acids (PFCAs) had elevated concentrations in 2015, however, the difference was not statistically significant (p > 0.05). Concentrations of the PFSAs and the PFCAs were similar at all location types, showing the global reach of these persistent compounds. Concentrations of the cyclic VMS (cVMS) were at least an order of magnitude higher than the linear VMS (lVMS) and the PFAS. Octamethylcyclotetrasiloxane (D4), decamethylcyclopentasiloxane (D5) and dodecamethylcyclohexasiloxane (D6) saw a weak significant increase in concentrations from 2009 to 2013 (p < 0.05), however, hexamethylcyclotrisiloxane (D3) had a strong significant decrease in concentrations from 2009 to 2015 (p < 0.01).

It is critical to estimate the exposure to indoor air pollution of residents spending most of their time in such microenvironments. However, the understanding regarding PM2.5 exposure in residential indoor environments is very limited. In this study, we collected participants' basic information and time–activity patterns, as well as details of other factors related to indoor air pollution exposure, through questionnaires presented to a large population in 37 counties of China. Continuous monitoring of ambient PM2.5 concentrations was performed using an environmental fixed-site monitoring network. Residential indoor PM2.5 concentrations were predicted using a mass balance model based on the data obtained. Evaluation of continuous daily average residential indoor PM2.5 exposure doses for large populations during winter revealed concentrations ranged from 67 to 195 μg/m3. Finally, differences in residential indoor PM2.5 exposure between northern and southern China were investigated. The results suggested that residential indoor PM2.5 concentrations in northern China, associated with heating, were higher than in the south. The established model could be important for improved understanding of human exposure to indoor PM2.5 air pollution.

Low-cost air quality sensors offer high-resolution spatiotemporal measurements that can be used for air resources management and exposure estimation. Yet, such sensors require frequent calibration to provide reliable data, since even after a laboratory calibration they might not report correct values when they are deployed in the field, due to interference with other pollutants, as a result of sensitivity to environmental conditions and due to sensor aging and drift. Field calibration has been suggested as a means for overcoming these limitations, with the common strategy involving periodical collocations of the sensors at an air quality monitoring station. However, the cost and complexity involved in relocating numerous sensor nodes back and forth, and the loss of data during the repeated calibration periods make this strategy inefficient. This work examines an alternative approach, a node-to-node (N2N) calibration, where only one sensor in each chain is directly calibrated against the reference measurements and the rest of the sensors are calibrated sequentially one against the other while they are deployed and collocated in pairs. The calibration can be performed multiple times as a routine procedure. This procedure minimizes the total number of sensor relocations, and enables calibration while simultaneously collecting data at the deployment sites. We studied N2N chain calibration and the propagation of the calibration error analytically, computationally and experimentally. The in-situ N2N calibration is shown to be generic and applicable for different pollutants, sensing technologies, sensor platforms, chain lengths, and sensor order within the chain. In particular, we show that chain calibration of three nodes, each calibrated for a week, propagate calibration errors that are similar to those found in direct field calibration. Hence, N2N calibration is shown to be suitable for calibration of distributed sensor networks.

PM₁ might be more hazardous than PM₂.₅ (particulate matter with an aerodynamic diameter ≤ 1 μm and ≤2.5 μm, respectively). However, studies on PM₁ concentrations and its health effects are limited due to a lack of PM₁ monitoring data.To estimate spatial and temporal variations of PM₁ concentrations in China during 2005–2014 using satellite remote sensing, meteorology, and land use information.Two types of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) data, Dark Target (DT) and Deep Blue (DB), were combined. Generalised additive model (GAM) was developed to link ground-monitored PM₁ data with AOD data and other spatial and temporal predictors (e.g., urban cover, forest cover and calendar month). A 10-fold cross-validation was performed to assess the predictive ability.The results of 10-fold cross-validation showed R² and Root Mean Squared Error (RMSE) for monthly prediction were 71% and 13.0 μg/m³, respectively. For seasonal prediction, the R² and RMSE were 77% and 11.4 μg/m³, respectively. The predicted annual mean concentration of PM₁ across China was 26.9 μg/m³. The PM₁ level was highest in winter while lowest in summer. Generally, the PM₁ levels in entire China did not substantially change during the past decade. Regarding local heavy polluted regions, PM₁ levels increased substantially in the South-Western Hebei and Beijing-Tianjin region.GAM with satellite-retrieved AOD, meteorology, and land use information has high predictive ability to estimate ground-level PM₁. Ambient PM₁ reached high levels in China during the past decade. The estimated results can be applied to evaluate the health effects of PM₁.

Indo-Pacific humpback dolphin (Sousa chinensis) are chronically exposed to organic pollutants since they inhabit shallow coastal waters that are often impacted by anthropogenic activities. The aim of this review was to evaluate existing knowledge on the occurrence of organic pollutants in Indo-Pacific humpback dolphins, identify knowledge gaps, and offer recommendations for future research directions. We discussed the trends in the bioaccumulation of organic pollutants in Indo-Pacific humpback dolphins focusing on sources, physicochemical properties, and usage patterns. Furthermore, we examined factors that influence bioaccumulation such as gender, age, dietary intake and tissue-specific distribution. Studies on bioaccumulation in Indo-Pacific humpback dolphin remain scarce, despite high concentrations above 13,000 ng/g lw we previously detected for PFOS, ∑PBDE and chlorinated paraffins. The maximum concentration of organochlorines detected was 157,000 ng/g wt. Furthermore, variations in bioaccumulation were shown to be caused by factors such as usage patterns and physicochemical properties of the pollutant. However, restrictions in sampling inhibit investigations on exposure pathway and toxicity of organic pollutants in Indo-Pacific humpback dolphin. We proposed the use of biopsy sampling, predictive bioaccumulation and toxicity modeling, and monitoring other emerging contaminants such as microplastics and pharmaceuticals for future health risk assessment on this critically endangered marine mammal species.

Several monitoring studies have shown that benzoylecgonine (BE) is the main illicit drug residue commonly measured in the aquatic system worldwide. Few studies have investigated the potential toxicity of this molecule towards invertebrate and vertebrate aquatic non-target organisms focusing on effects at low levels of the biological organization, but no one has assessed the consequences at higher ones. Thus, the present study was aimed at investigating the toxicity of a 48-h exposure to two concentrations of BE, similar to those found in aquatic ecosystems (0.5 μg/L and 1.0 μg/L), on the cladoceran Daphnia magna at different levels of the ecological hierarchy. We relied on a multi-level approach focusing on the effects at biochemical/biomolecular (biomarkers), individual (swimming activity) and population (reproduction) levels. We measured the amount of reactive oxygen species and of the activity of antioxidant (SOD, CAT, and GPx) and detoxifying (GST) enzymes to assess if BE exposure can alter the oxidative status of D. magna specimens, while the lipid peroxidation (TBARS) was measured as a marker of oxidative damage. Moreover, we also measured the acetylcholinesterase (AChE) activity because it is strictly related to behavioral changes in aquatic organisms. Changes in swimming behavior were investigated by a video tracking analysis, while the consequences on reproduction were assessed by a chronic toxicity test. Our results showed that BE concentrations similar to those found in aquatic ecosystems induced oxidative stress and inhibited AChE activity, affecting swimming behavior and the reproduction of Daphnia magna individuals.

It is widely understood that microplastics (MPs) are ubiquitous in the marine environment yet less is known about MP abundance in freshwater rivers, particularly those of the western United States. This study documents MP pollution along the Snake River (∼1735 km) and from its confluence with the Columbia River to the Pacific Ocean. Grab and plankton net samples (mesh size 100 μm) were collected from the top 25 cm of surface water every 80.5 river km. MPs were identified if they met visual criteria and were verified with the hot needle test. A small representative subset of MPs from the net samples (16.7%) were selected based on appearance for micro-Raman spectroscopy in effort to provide examples of polymer types found in this study. Seventy-five percent of grab samples and 92.8% of net samples contained MPs, with concentrations ranging from 0 to 5.405 MP L−1 and 0 to 0.014 MP L−1 (0 to 13.7 MP m−3), respectively. The majority of fragments, films and beads were between 100 μm and 333 μm. This study identifies potential hotspots of MP pollution along the Snake and Lower Columbia rivers and prioritizes areas where more intensive sampling is needed. Sites with low flow or those further down river had higher numbers and the top two hotspots were located in areas with low population density but high agricultural use. Monitoring MP abundance in freshwater systems is important for establishing baseline levels of MP pollution and can direct laboratory toxicology studies in using more environmentally relevant concentrations for a better indication of how MP pollution affects ecosystems.