Avoiding foraging under increased predation risk is a common anti-predator behaviour. Using artificial light to amplify predation risk at ecologically valuable sites has been proposed to deter introduced mice (Mus musculus) and ship rats (Rattus rattus) from degrading biodiversity in island ecosystems. However, light may adversely affect native species; in particular, little is known about invertebrate responses to altered lighting regimes. We investigated how endemic orthopterans responded to artificial light at Maungatautari Ecological Island (Waikato, New Zealand). We predicted that based on their nocturnal behaviour, ecology and evolutionary history, tree weta (Hemideina thoracica) and cave weta (Rhaphidophoridae) would reduce their activity under illumination. Experimental stations (n = 15) experienced three evenings under each treatment (order randomised): (a) light (illuminated LED fixture), (b) dark (unilluminated LED fixture) and (c) baseline (no lighting fixture). Weta visitation rates were analysed from images captured on infra-red trail cameras set up at each station. Light significantly reduced the number of observations of cave (71.7% reduction) and tree weta (87.5% reduction). In observations where sex was distinguishable (53% of all visits), male tree weta were observed significantly more often (85% of visits) than females (15% of visits) and while males avoided illuminated sites, no detectable difference was observed across treatments for females. Sex could not be distinguished for cave weta. Our findings have implications for the use of light as a novel pest management strategy, and for the conservation of invertebrate diversity and abundance within natural and urban ecosystems worldwide that may be affected by light pollution.

Maternal arsenic exposure leads to adverse birth outcomes, but the critical window of this susceptibility keeps unclear. To determine whether the associations between maternal arsenic exposure and birth outcomes were trimester-specific, we conducted a birth cohort study of 1390 women from 2014 to 2016 in Wuhan, China. We examined associations between total urinary arsenic concentrations in three trimesters and birth weight, birth length and the risk of small for gestational age (SGA), and the differences of these associations across trimesters using generalized estimating equations. Maternal urinary arsenic concentrations varied across trimesters and were weakly correlated. Arsenic concentrations in the 3rd trimester, but not in the 1st and 2nd trimesters, were associated with birth outcomes. For each doubling of arsenic levels in the 3rd trimester, birth weight was decreased 24.27 g (95% confidence interval (CI): −46.99, −1.55), birth length was decreased 0.13 cm (95% CI: −0.22, −0.04), and the risk for SGA birth was increased 25% (95% CI: 1.03, 1.49). Further, stratified analyses indicated that these associations were only observed in female infants. Our findings indicate maternal arsenic levels in the 3rd trimester seemed to have significant impacts on birth outcomes, and also emphasize the public health interventions relevance to arsenic exposure in late pregnancy.

The urban water ecosystems, such as the landscape ponds are commonly considered under the influence of anthropogenic disturbances, which can lead to the deterioration of the water quality. The prokaryotic communities are considered as one of the best indicators of the water quality. However, there are significant gaps in understanding the ecological processes that shape the composition and function of prokaryotic communities in the urban water ecosystems. Here, we investigated the biogeographic distribution of prokaryotic assemblages in water environments including landscape ponds, drinking water reservoirs, influents (IFs) and effluents (EFs) of wastewater treatment plants of a coastal city (Xiamen), China, by using 16S rDNA amplicon sequencing. Our results indicated that the ponds had higher α-diversity of prokaryotic communities than those in the reservoirs, while there were significant variations in the community compositions among ponds, reservoirs, IFs and EFs. Moreover, ponds harbored a significantly higher proportion of sewage- and fecal-indicator taxa than those in the reservoirs, suggesting the occurrence of exogenous pollution in the urban ponds. Null model analysis revealed that dispersal limitation was the main ecological processes resulting in the divergence of prokaryotic community compositions between ponds and other environments, while dispersal limitation and variable selection played an essential role in the formation of unique prokaryotic assemblages in the reservoirs. Function predication analysis demonstrated that the ponds shared more similar functional profiles with IFs or EFs (e.g., chemoheterotrophy, fermentation, chlorate reducers, nitrate reduction and respiration) than the reservoirs, whereas dominance of photoautotrophy was observed in the reservoirs. Overall, this study provides a profound insight of the ecological mechanisms underlying the responses of prokaryotic communities in the urban landscape ponds to the anthropogenic disturbances.

Despite of their ubiquitous distribution in marine sediments, the role of benthic fauna in microplastic transport at the sea floor has received little attention yet. The present study investigated the influence of bioturbation activity of the polychaete Arenicola marina on microplastic transport and burial in marine sediments. Sediment ingestion was assessed in a long term mesocosm experiment with exposure times ranging from 106 to 240 days, using three particle tracers with different particle diameters (microplastic: 500 and 1000 μm, respectively; luminophores: 130 μm). Sediment grain size distributions were assessed after experiment termination in all feeding layers at 8–12 cm depth to determine the influence of size-selective feeding of A. marina on median grain size and microplastic retention. Burial of microplastic occurred in all mesocosms up to a depth of 20 cm and was strongly dependent on individual sediment feeding rates. For low bioturbation conditions, both microplastic and luminophore concentrations exhibited an exponential decrease with increasing sediment depth, indicating particle burial via feeding funnel transport. Particle concentrations remained high in the uppermost 4 cm of the sediment. At high bioturbation rates, no microplastic particles remained in near-surface sediment layers, but a distinct accumulation of microplastic was observed in the feeding layer, suggesting the discrimination of plastic particles during feeding. In contrast, luminophores displayed a similar accumulation, but additionally showed uniform distributions above feeding layers, indicating ingestion and defecation by polychaetes. In accordance with these findings, an overall coarsening of median grain sizes was observed in all feeding layers, indicating the retention of large microplastic due to size-selective feeding. These findings demonstrate the ability of the conveyor belt-feeding polychaete A. marina to promote unidirectional transports of microplastic ≥500 μm and the potential for the long-term retention of these particles in marine sediments.

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.