Major sources of petroleum hydrocarbons in the south of Caspian Sea (Anzali city) have been investigated through an approach which combines Gas Chromatography–Mass Spectrometry with Principal Component Analysis (PCA) and Multivariate Curve Resolution-Alternating Least Squares chemometric methods. Terpane, catagenetic hopane and sterane hydrocarbons were analyzed in the street dust, filtered sediments of runoff, soluble runoff water and river sediment samples as well as in automobiles exhaust, tires, asphalt, engine oil, gasoline and diesel samples, as possible sources of these hydrocarbons. PCA and MCR-ALS results showed that a large part of the analyzed hydrocarbons in street dust, runoffs and in some of the river sediment samples can be explained by the proposed known sources, while the observed variation of hydrocarbon concentrations in many of the river sediment samples was not much affected by the proposed known sources, and they were most probably receiving other pollution sources not included in our study. This study also has shown that results obtained from hydrocarbon marker molecular ratios, to identify petroleum pollution sources in the environments, are in agreement with those obtained from pollution sources resolved by MCR-ALS simultaneous analysis of all samples and variables.

Satellite-retrieved aerosol optical depth (AOD) is commonly used to estimate ambient levels of fine particulate matter (PM₂.₅), though it is important to mitigate the estimation bias of PM₂.₅ due to gaps in satellite-retrieved AOD. A nonparametric approach with two random-forest submodels is proposed to estimate PM₂.₅ levels by filling gaps in satellite-retrieved AOD. This novel approach was employed to estimate the spatiotemporal distribution of daily PM₂.₅ levels during 2013–2015 in the Sichuan Basin of Southwest China, where the coverage rate of composite AOD retrieved by the Terra and Aqua satellites was only 11.7%. Based on the retrieved AOD and various covariates (including meteorological conditions and land use types), the first random-forest submodel (named AOD-submodel) was trained to fill the gaps in the AOD dataset, giving a cross-validation R² of 0.95. Subsequently, the second random-forest submodel (named PM₂.₅-submodel) was trained to estimate the PM₂.₅ levels for unmonitored areas/days based on the gap-filled AOD, ground-monitored PM₂.₅ levels, and the covariates, and achieved a cross-validation R² of 0.86. By comparing the complete and incomplete (i.e., without the days when AOD data were missing) estimates, we found that the monthly PM₂.₅ levels could be overestimated by 34.6% if the PM₂.₅ values coincident with AOD gaps were not considered. The newly developed approach is valuable for deriving the complete spatiotemporal distribution of daily PM₂.₅ from incomplete remote-sensing data, which is essential for air quality management and human exposure assessment.

A special initiative in the Global Atmospheric Passive Sampling (GAPS) Network was implemented to provide information on new and emerging persistent organic pollutants (POPs) in the Group of Latin America and Caribbean (GRULAC) region. Regional-scale atmospheric concentrations of the new and emerging POPs hexachlorobutadiene (HCBD), pentachloroanisole (PCA) and dicofol indicators (breakdown products) are reported for the first time. HCBD was detected in similar concentrations at all location types (<20–120 pg/m³). PCA had elevated concentrations at the urban site Concepción (Chile) of 49–222 pg/m³, with concentrations ranging <1–8.5 pg/m³ at the other sites in this study. Dicofol indicators were detected at the agricultural site of Sonora (Mexico) at concentrations ranging 30–117 pg/m³. Legacy POPs, including a range of organochlorine (OC) pesticides and polychlorinated biphenyls (PCBs), were also monitored to compare regional atmospheric concentrations over a decade of monitoring under the GAPS Network. γ-hexachlorocyclohexane (HCH) and the endosulfans significantly decreased (p < 0.05) from 2005 to 2015, suggesting regional levels are decreasing. However, there were no significant changes for the other legacy POPs monitored, likely a reflection of the persistency and slow decline of environmental levels of these POPs. For the more volatile OCs, atmospheric concentrations derived from polyurethane foam (PUF) (acting as an equilibrium sampler) and sorbent impregnated PUF (SIP) (acting as a linear phase sampler), were compared. The complimentary methods show a good agreement of within a factor of 2–3, and areas for future studies to improve this agreement are further discussed.

Most cities in China experience frequent PM₂.₅ pollution, in relation to unfavorable planetary boundary layer (PBL) conditions. Partly due to the limited appropriate PBL observations, the explicit relationships between PBL structure/process and PM₂.₅ pollution in China are not yet clearly understood. Using the fine-resolution sounding measurements from 2014 to 2017, the relationships between boundary layer height (BLH) and PM₂.₅ pollution in China were systematically examined. Four regions of interest (ROIs) featured with dense population and heavy pollution were studied and compared, including Northeast China (NEC), North China Plain (NCP), East China (EC), and Sichuan Basin (SCB). From 2014 to 2017, the heaviest PM₂.₅ pollution happened in NCP with an annual average concentration of 84 μg m⁻³, followed by NEC (60 μg m⁻³), SCB (57 μg m⁻³), and EC (54 μg m⁻³). Correlation analyses revealed a significant anti-correlation between BLH and daily PM₂.₅ concentrations across China, independent of ROIs. During an annual cycle, the pollution was heaviest in winter, followed by fall and spring, and reached its minimum in summer. Such a seasonal variation of pollution was not only modulated by the emissions, but also the seasonal shifts of BLH. The low BLH in winter was often associated with strong near-surface thermal stability. Moreover, certain synoptic conditions in winter can exacerbate the pollution, leading to concurrent drops of BLH and synchronous increases of PM₂.₅ concentration in different cities of a ROI. In NCP and SCB, the mountainous terrains could further worsen the pollution by blocking effects and lee eddies.

The increase of production and consumption of copper oxide nanostructures in several areas contributes to their release into aquatic ecosystems. Toxic effects of copper oxide nanoparticles (CuO NPs), in particular, on tropical aquatic organisms are still unknown, representing a risk for biota. In this study, the effects of rod-shaped CuO NPs on the Neotropical species Ceriodaphnia silvestrii and Hyphessobrycon eques were investigated. We also compared the toxicity of CuO NPs and CuCl₂ on these species to investigate the contribution of particles and cupper ions to the CuO NPs toxicity. Considering the low copper ions release from CuO NPs (<1%), our results revealed that the toxicity of CuO NPs to C. silvestrii and H. eques was mainly induced by the NPs. The 48 h EC₅₀ for C. silvestrii was 12.6 ± 0.7 μg Cu L⁻¹ and for H. eques the 96 h LC₅₀ was 211.4 ± 57.5 μg Cu L⁻¹ of CuO NPs. There was significant decrease in reproduction, feeding inhibition and increase in reactive oxidative species (ROS) generation in C. silvestrii exposed to CuO NPs. In fish H. eques, sublethal exposure to CuO NPs caused an increase in ROS generation in gill cells and an increase in cells number that were in early apoptotic and necrotic stages. Our results showed that CuO NPs caused toxic effects to C. silvestrii and H. eques and ROS play an important role in the toxicity pathway observed. Data also indicated that C. silvestrii was among the most sensitive species for CuO NPs. Based on predicted environmental concentration in water bodies, CuO NPs pose potential ecological risks for C. silvestrii and H. eques and other tropical freshwater organisms.

Hyperspectral imaging technology has been investigated as a possible way to detect microplastics contamination in soil directly and efficiently in this study. Hyperspectral images with wavelength range between 400 and 1000 nm were obtained from soil samples containing different materials including microplastics, fresh leaves, wilted leaves, rocks and dry branches. Supervised classification algorithms such as support vector machine (SVM), mahalanobis distance (MD) and maximum likelihood (ML) algorithms were used to identify microplastics from the other materials in hyperspectral images. To investigate the effect of particle size and color, white polyethylene (PE) and black PE particles extracted from soil with two different particle size ranges (1–5 mm and 0.5–1 mm) were studied in this work. The results showed that SVM was the most applicable method for detecting white PE in soil, with the precision of 84% and 77% for PE particles in size ranges of 1–5 mm and 0.5–1 mm respectively. The precision of black PE detection achieved by SVM were 58% and 76% for particles of 1–5 mm and 0.5–1 mm respectively. Six kinds of household polymers including drink bottle, bottle cap, rubber, packing bag, clothes hanger and plastic clip were used to validate the developed method, and the classification precision of polymers were obtained from 79% to 100% and 86%–99% for microplastics particle 1–5 mm and 0.5–1 mm respectively. The results indicate that hyperspectral imaging technology is a potential technique to determine and visualize the microplastics with particle size from 0.5 to 5 mm on soil surface directly.

Air pollution epidemiologic and health impact studies often rely on home addresses to estimate individual subject's pollution exposure. In this study, we used detailed cell phone location data, the call detail record (CDR), to account for the impact of spatiotemporal subject mobility on estimates of ambient air pollutant exposure. This approach was applied on a sample with 9886 unique simcard IDs in Shenzhen, China, on one mid-week day in October 2013. Hourly ambient concentrations of six chosen pollutants were simulated by the Community Multi-scale Air Quality model fused with observational data, and matched with detailed location data for these IDs. The results were compared with exposure estimates using home addresses to assess potential exposure misclassification errors. We found the misclassifications errors are likely to be substantial when home location alone is applied. The CDR based approach indicates that the home based approach tends to over-estimate exposures for subjects with higher exposure levels and under-estimate exposures for those with lower exposure levels. Our results show that the cell phone location based approach can be used to assess exposure misclassification error and has the potential for improving exposure estimates in air pollution epidemiology studies.

Raptor feathers have been increasingly used to assess pollutants in ecotoxicological monitoring studies. However, the suitability of down feathers to detect pollutants has not yet been investigated. In this study, concentrations of persistent organic pollutants (POPs) and organophosphate ester flame retardants (OPEs) were assessed in down and juvenile contour feathers of Spanish cinereous vulture (Aegypius monachus) nestlings (circa 73 days old) and contaminant concentrations were compared between both types of feathers from the same individuals. Concentrations of polychlorinated biphenyls (PCBs: 1.30–6.16 ng g−1 dw feather), polybrominated diphenyl ethers (PBDEs: 0.23–1.35 ng g−1 dw feather), p,p'-dichlorodiphenyldichloroethylene (pp-DDE: 0.09–6.10 ng g−1 dw feather) and tris (1-chloro-2-propyl) phosphate (TCiPP: 0.86–48.96 ng g−1 dw feather) were significantly higher in down than in contour feathers. In contrast, contour feathers showed higher levels of the more volatile POP, lindane (0.25–3.12 ng g−1 dw feather). Concentrations of hexachlorobenzene (HCB) and OPEs (except TCiPP) were similar between the two types of feathers. By showing high accumulation of the most persistent POPs investigated, down feathers presented a contamination profile similar to that previously described in raptor eggs. As these feathers grow during the first days of a vulture chicks life, they probably reflect the contaminant burden of the chick due to maternal transfer to the egg. Overall, the present study provides the first indication that down feathers may be useful for biomonitoring studies. Further research is needed to confirm whether nestling down feathers reflect the concentrations in the egg.

Marine pollution, overrepresented by plastic, is a growing concern worldwide. However, there is little knowledge on occurrence and detrimental impacts of marine debris in cetaceans. To partially fill in this gap of knowledge, we aimed to investigate the occurrence and pathologies associated with foreign bodies (FBs) in a large cohort of cetaceans (n = 465) stranded in the Canary Islands. The Canary Islands shelter the greatest cetacean biodiversity in Europe, with up to 30 different species, of which nine are regularly present year around. We found at least one ingested FB in 36 out of 465 (7.74%) studied cetaceans, involving 15 different species, including eight out of the nine (80%) cetacean species present year-round in the Canary Islands. Risso's dolphin was the species most affected, followed by sperm whale, beaked whale and mysticetes. Plastic FB were the most common item found (80.56%). FB was directly associated with death in 13/36 (36.11%) animals. Poor body condition and deep diving behavior were found to be risk factors for FB ingestion, whereas the adult age was a protective factor. To the authors knowledge this is the first study that use statistical analysis to investigate risk and protective factors for FB ingestion. This study also provides insights of the potential impact caused by ingested FBs on the animal's health and mortality. This knowledge is critical to better understand and assess the impact of FB in cetaceans setting the scientific basis for prospective impact monitoring and future conservation policies.

Aquatic animals live in an acoustic world in which they often rely on sound detection and recognition for various aspects of life that may affect survival and reproduction. Human exploitation of marine resources leads to increasing amounts of anthropogenic sound underwater, which may affect marine life negatively. Marine mammals and fishes are known to use sounds and to be affected by anthropogenic noise, but relatively little is known about invertebrates such as decapod crustaceans. We conducted experimental trials in the natural conditions of a quiet cove. We attracted shore crabs (Carcinus maenas) and common shrimps (Crangon crangon) with an experimentally fixed food item and compared trials in which we started playback of a broadband artificial sound to trials without exposure. During trials with sound exposure, the cumulative count of crabs that aggregated at the food item was lower, while variation in cumulative shrimp count could be explained by a negative correlation with crabs. These results suggest that crabs may be negatively affected by artificially elevated noise levels, but that shrimps may indirectly benefit by competitive release. Eating activity for the animals present was not affected by the sound treatment in either species. Our results show that moderate changes in acoustic conditions due to human activities can affect foraging interactions at the base of the marine food chain.