Residues of pyrethroid insecticides tend to accumulate in bed sediments due to their strong hydrophobicity. Rather than the total or bulk sediment concentration, it is the freely dissolved concentration (Cfᵣₑₑ) that drives toxicity to benthic invertebrates. In this study we developed thin film-based samplers for in situ ambient monitoring of pyrethroids at trace levels in sediment. Out of five common polymer materials, polyethylene (PE) and silicone rubber (SR), were identified to offer superior enrichment for pyrethroids from sediment. To circumvent the slow equilibrium process, ¹³C-permethrin and bifenthrin-d₅ were preloaded onto the films as performance reference compounds (PRCs). The PRC-preloaded film samplers were deployed at five sites in Southern California under field conditions for 7 d and retrieved for analysis. The sediment porewater Cfᵣₑₑ of eight pyrethroids derived from PRC-PE films ranged from 173 to 903 ng/L, accounting for 18.2–36.1% of the corresponding total porewater concentrations. The PRC-SR film samplers yielded Cfᵣₑₑ values closely mimicking those from the PRC-PE samplers, cross-validating the two sampling devices. Additionally, a significant positive association was found between the observed mortality from toxicity tests using Hyalella azteca and the Cfᵣₑₑ of bifenthrin (r = 0.628, p = 0.02). A significant linear correlation (R² = 0.99) between Cfᵣₑₑ derived from in situ monitoring and that of ex situ measurement under equilibrium conditions was also observed. Results from this study demonstrated that the film-based samplers may be used for in situ ambient monitoring to detect biologically relevant contamination of pyrethroids in bed sediments, which may contribute to improved risk assessment for this class of widely used insecticides.

The state of practice for noise assessment utilizes established standards for emission and propagation modelling of linear and point sources. Recently, land use regression (LUR) modelling has emerged as an alternative method due to relatively low data and computing resource demands. However, a limitation of LUR modelling is that is does not account for noise attenuation and reflections by features of the built environment. This study demonstrates and validates a method that combines the two modelling frameworks to exploit their respective strengths: Emission and propagation based prediction of traffic noise, the predominant source of noise at the level of streetscapes, and a LUR-based correction for noise sources that vary on spatial scales beyond the streetscape.Multi-criteria analysis, location-allocation modelling and stakeholder consultation identified 220 monitoring sites with optimal coverage for a 1-week sampling period. A subset of sites was used to validate a road traffic noise emission and propagation model and to specify a LUR model that predicted the contribution of other sources. The equivalent 24-h sound pressure level (LAeq) for all sites was 62.9 dBA (SD 6.4). This varied by time of day, weekday, types of roads and land uses. The traffic noise emission model demonstrated a high level of covariance with observed noise levels, with R² values of 0.58, 0.60 and 0.59 for daytime, nighttime and 24-h periods, respectively. Combined with LUR models to correct for other noise sources, the hybrid models R² values were 0.64, 0.71 and 0.67 for the respective time periods.The study showed that road traffic noise emissions account for most of the variability of total environmental noise in Toronto. The combined approach to predict fine resolution noise exposures with emission and receptor-based models presents an effective alternative to noise modelling approaches based on emission and propagation or LUR modelling.

Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system.By 2046–2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH3), and sulfur dioxide (SO2) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively large increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NOx, VOC, and NH3, while emissions from both the on-road and non-road modes have strong contributions to PM and SO2 emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations.

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.