Effects of photochemical and microbial degradation on variations in composition and molecular-size of dissolved organic matter (DOM) from different sources (algal and soil) and the subsequent influence on Cu(II) binding were investigated using UV–Vis, fluorescence excitation-emission matrices coupled with parallel factor analysis, flow field-flow fractionation (FlFFF), and metal titration. The degradation processes resulted in an initial rapid decline in the bulk dissolved organic carbon and chromophoric and fluorescent DOM components, followed by a small or little decrease. Specifically, photochemical reaction decreased the aromaticity, humification and apparent molecular weights of all DOM samples, whereas a reverse trend was observed during microbial degradation. The FlFFF fractograms revealed that coagulation of both protein- and humic-like DOM induced an increase in molecular weights for algal-DOM, while the molecular weight enhancement for allochthonous soil samples was mainly attributed to the self-assembly of humic-like components. The Cu(II) binding capacity of algal-derived humic-like and fulvic-like DOM consistently increased during photo- and bio-degradation, while the soil-derived DOM exhibited a slight decline in Cu(II) binding capacity during photo-degradation but a substantial increase during microbial degradation, indicating source- and degradation-dependent metal binding heterogeneities. Pearson correlation analysis demonstrated that the Cu(II) binding potential was mostly related with aromaticity and molecular size for allochthonous soil-derived DOM, but was regulated by both DOM properties and specific degradation processes for autochthonous algal-derived DOM. This study highlighted the coupling role of inherent DOM properties and external environmental processes in regulating metal binding, and provided new insights into metal-DOM interactions and the behavior and fate of DOM-bound metals in aquatic environments.

Environmental contamination of the Arctic has widely been used as a worldwide pollution marker. Various classes of organic pollutants such as pesticides, personal care products, PAHs, flame retardants, biomass burning markers, and many others emerging contaminants have been regularly detected in Arctic samples. Although numerous papers have been published reporting data from the Canadian, Danish, and Norwegian Arctic regions, the environmental situation in Russian Arctic remains mostly underreported. Snow analysis is known to be used for monitoring air pollution in the regions with cold climate in both short-term and long-term studies. This paper presents the results of a nontargeted study on the semivolatile organic compounds detected and identified in snow samples collected at the Russian Artic Archipelago Novaya Zemlya in June 2016. Gas chromatography coupled to a high-resolution time-of-flight mass spectrometer enabled the simultaneous detection and quantification of a variety of pollutants including those from the US Environmental Protection Agency (EPA) priority pollutants list, emerging contaminants (plasticizers, flame retardants-only detection), as well as the identification of novel Arctic organic pollutants, (e.g., fatty acid amides and polyoxyalkanes). The possible sources of these novel pollutants are also discussed.GC-HRMS enabled the detection and identification of emerging contaminants and novel organic pollutants in the Arctic, e.g., fatty amides and polyoxyalkanes.

Rapid development of industrial production has stimulated the growth of consumption of raw and auxiliary materials including organic paints, among which volatile organic compounds (VOCs) are proved harmful to the population who inhale the polluted air based on epidemiologic studies. Therefore, new types of environment-friendly paints were developed to replace solvent-based paints (SBPs). Nevertheless, new types of paints containing VOCs failed to replace SBPs entirely due to certain disadvantages. Hence, five kinds of paints were employed in simulation experiments to assess the health risk of primary receptor including three kinds of water-based paints (WBPs) and two kinds of SBPs. Conclusions showed that mean TVOC concentration in breathing zone of primary receptor ranged from 9.5 to 13.6 mg/m³ and 3.4 × 10³ to 1.4 × 10⁴ mg/m³ for WBPs and SBPs, respectively. Assessments of non-cancer risk concluded that nearly one third quantified compounds exceeded corresponding thresholds for WBPs, and the maximum risk value was 101.33; for SBPs, the maximum risk value reached 50760.20, and twenty-two compounds exceeded the reference limits. The calculation of cancer risk values showed that seventeen compounds were higher than acceptable limit amongst which 1,2-dibromoethane had maximum values of 1.27 × 10⁻² to 3.24 × 10⁻² for WBPs; for SBPs, all quantified compounds exceeded the acceptable limit, and 82.61% VOCs were distributed in a scope larger than 1 × 10⁻³. Additionally, a removal efficiency of 60% was considered for primary receptor with personal protective equipment, and subsequent results confirmed its inability of lowering the risk resulted from hazardous VOCs. The calculated potential health risk could be applied to estimate the total health risk for both primary and secondary receptor based on consumed materials. The finding suggested that WBPs could improve VOCs exposure condition and reduce the direct and potential health risk significantly for primary receptor, although they might dissatisfy acceptable limit.

A novel mobile laser radar system was used for mapping gaseous atomic mercury (Hg0) atmospheric pollution in the Wanshan district, south of Tongren City, Guizhou Province, China. This area is heavily impacted by legacy mercury from now abandoned mining activities. Differential absorption lidar measurements were supplemented by localized point monitoring using a Lumex RA-915M Zeeman modulation mercury analyzer. Range-resolved concentration measurements in different directions were performed. Concentrations in the lower atmospheric layers often exceeded levels of 100 ng/m3 for March conditions with temperature ranging from 5 °C to 20 °C. A flux measurement of Hg0 over a vertical cross section of 0.12 km2 resulted in about 29 g/h. Vertical lidar sounding at night revealed quickly falling Hg0 concentrations with height. This is the first lidar mapping demonstration in a heavily mercury-polluted area in China, illustrating the lidar potential in complementing point monitors.

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.