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.

To improve the accuracy and temporal-spatial resolution for a vehicle emission inventory in a medium-sized city with a strip road network, this study was conducted based on detailed hourly traffic-flow data for each day of 2014, and covered all road types and regions in the city of Foshan. Detailed hourly emission characteristics and sources in five regions were analysed. The results showed that the total vehicle emissions of CO, NOX, VOCs, and PM2.5 were 13.10 × 104, 0.23 × 104, 4.46 × 104, and 0.18 × 104 tons, respectively. Motorcycles (MCs) and light passenger cars (LPCs) were the dominant contributors of CO emissions, while buses and heavy passenger cars (HPCs) were the dominant contributors for NOX. As a whole, the daytime contributions to total emissions were close to 80%, and emissions during the peak periods accounted for almost 40%. Specifically, the hourly emissions of each pollutant on workdays were higher than on non-workdays (maximum up to 64.2%), and for some roads the early peak periods changed significantly from workdays to non-workdays. At expressways, artery roads, and local roads, the daily emission intensities of CO, NOx, and PM2.5 in Foshan were close to or even higher than that of Beijing. On a regional scale, the temporal variation of vehicle emissions on workdays at artery roads of different regions were similar. In addition, the higher emission intensities of CO and VOCs were identified in DaLiang-RongGui (DLRG) and that of NOX and PM2.5 were in Central Region (CR). These results are meaningful for decision-makers to help provide more detailed vehicle pollution control measures in Foshan with a strip road network and only one ring road.

As a major group of plasticizers and flame-retardants, organophosphate esters (OPEs) have attracted particular attention due to their wide occurrence and potential impacts on human health and ecosystems. In the present study, the occurrence and distribution of 14 OPEs, including seven Alkyl-OPEs, three Cl-OPEs, and four Aryl-OPEs, were investigated in 65 road dust samples collected from November to December 2014 in Beijing, China. Cl-OPEs were the predominant compounds in the road dust samples, with the median concentration of 646 μg/kg, followed by the Alkyl-OPEs (median 135 μg/kg) and Aryl-OPEs (median 129 μg/kg). Tris(2-chloro-1-methylethyl) phosphate (TCPP) was the most abundant OPE with the median concentration of 384 μg/kg. In addition, OPEs levels showed significant difference (p < 0.05) in the spatial distribution. Markedly higher levels of OPEs were observed in 2nd and 3rd ring road with heavy traffic and high population density, indicating that the traffic and population were important factors for this distribution pattern. It was further supported by the analysis of OPEs in roadside soil and indoor dust in the vicinity of road dust sample sites. Finally, the average daily dose (ADD) for OPEs via inhalation, dermal absorption, and ingestion was calculated to evaluate the carcinogenic and non-carcinogenic risks to residents exposed to OPEs in the road dust. Risk assessment revealed that the risk originating from exposure to OPEs of road dust is currently low in Beijing, China.

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.

Plastic debris has become an environmental problem during recent years. Among the plastic debris, microplastics (<5 mm; MPLs) imply an extra problem due to their capacity to enter into the fauna through ingestion. In this work, we study the capacity of three MPLs, that include high-density polyethylene (HDPE), polystyrene (PS) and polystyrene carboxylate (PS-COOH), to sorb 18 perfluoroalkyl substances (PFASs; including carboxylic acids, sulphonates and one sulphonamide) from the surrounding waters (freshwater and seawater).Conclusions drawn from the results are that perfluoro sulphonates and sulphonamides have more tendency to be sorbed onto MPLs. In addition, PS and PS-COOH have more affinity for PFASs than HDPE. Finally, the increment of conductivity and pH of the water decreases the exposure time that is necessary to reach equilibrium. However, the presence of salts decreases the tendency of PFASs to be sorbed onto plastic surfaces. These results highlight the problem associated with the presence of MPLs in inland and marine waters since toxic compounds can be sorbed onto surrounding plastics that could be ingested by aquatic fauna.

In urbanized regions with expansive impervious surfaces and often low vegetation cover, air pollution due to motor vehicles and other combustion sources, is a problem. The poor air quality days in Montreal, Quebec are mainly due to fine particulate matter and ozone. Businesses using wood ovens are a source of particulates. Careful vegetation selection and increased green roof usage can improve air quality. This paper reviews different green roofs and the capability of plants in particulate matter (PM), ozone (O3) as well as nitrogen dioxide (NO2) level reductions. Both the recommended green roof category and plants to reduce these pollutants in Montreal's zone 5 hardiness region are provided. Green roofs with larger vegetation including shrubs and trees, or intensive green roofs, remove air pollutants to a greater extent and are advisable to implement on existing, retrofitted or new buildings. PM is most effectively captured by pines. The small Pinus strobus ‘Nana’, Pinus mugho var. pumilio, Pinus mugho ‘Slowmound’ and Pinus pumila ‘Dwarf Blue’ are good candidates for intensive green roofs. Drought tolerant, deciduous broadleaved trees with low biogenic volatile organic compound emissions including Japanese Maple or Acer palmatum ‘Shaina’ and ‘Mikawa-Yatsubusa’ are options to reduce O3 levels. Magnolias are tolerant to NO2 and it is important in their metabolic pathways. The small cold-tolerant Magnolia ‘Genie’ is a good option to remove NO2 in urban settings and to indirectly reduce O3 formation. Given the emissions by Montreal businesses' wood ovens, calculations performed based on their respective complex roof areas obtained via Google Earth Pro indicates 88% Pinus mugho var. pumilio roof coverage can annually remove 92.37 kg of PM10 of which 35.10 kg is PM2.5. The removal rates are 4.00 g/m2 and 1.52 g/m2 for PM10 and PM2.5, respectively. This paper provides insight to addressing air pollution through urban rooftop greening.

Heavy metals are concerned for its adverse effect on human health and long term burden on biogeochemical cycling in the ecosystem. In this study, a provincial-level emission inventory of 13 kinds of heavy metals including V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Sn, Sb, Ba and Pb from 10 anthropogenic sources was developed for China, based on the 2015 national emission inventory of primary particulate matters and source category-specific speciation profiles collected from 50 previous studies measured in China. Uncertainties associated with the speciation profiles were also evaluated. Our results suggested that total emissions of the 13 types of heavy metals in China are estimated at about 58000 ton for the year 2015. The iron production is the dominant source of heavy metal, contributing 42% of total emissions of heavy metals. The emissions of heavy metals vary significantly at regional scale, with largest amount of emissions concentrated in northern and eastern China. Particular, high emissions of Cr, Co, Ni, As and Sb (contributing 8%–18% of the national emissions) are found in Shandong where has large capacity of industrial production. Uncertainty analysis suggested that the implementation of province-specific source profiles in this study significantly reduced the emission uncertainties from (−89%, 289%) to (−99%, 91%), particularly for coal combustion. However, source profiles for industry sectors such as non-metallic mineral manufacturing are quite limited, resulting in a relative high uncertainty. The high-resolution emission inventories of heavy metals are essential not only for their distribution, deposition and transport studies, but for the design of policies to redress critical atmospheric environmental hazards at local and regional scales. Detailed investigation on source-specific profile in China are still needed to achieve more accurate estimations of heavy metals in the future.

Artificial lighting at night has becoming a new type of pollution posing an important anthropogenic environmental pressure on organisms. The objective of this research was to examine the potential association between nighttime artificial light pollution and nest densities of the three main sea turtle species along Florida beaches, including green turtles, loggerheads, and leatherbacks. Sea turtle survey data was obtained from the “Florida Statewide Nesting Beach Survey program”. We used the new generation of satellite sensor “Visible Infrared Imaging Radiometer Suite (VIIRS)” (version 1 D/N Band) nighttime annual average radiance composite image data. We defined light pollution as artificial light brightness greater than 10% of the natural sky brightness above 45° of elevation (>1.14 × 10⁻¹¹ Wm⁻²sr⁻¹). We fitted a generalized linear model (GLM), a GLM with eigenvectors spatial filtering (GLM-ESF), and a generalized estimating equations (GEE) approach for each species to examine the potential correlation of nest density with light pollution. Our models are robust and reliable in terms of the ability to deal with data distribution and spatial autocorrelation (SA) issues violating model assumptions. All three models found that nest density is significantly negatively correlated with light pollution for each sea turtle species: the higher light pollution, the lower nest density. The two spatially extended models (GLM-ESF and GEE) show that light pollution influences nest density in a descending order from green turtles, to loggerheads, and then to leatherbacks. The research findings have an implication for sea turtle conservation policy and ordinance making. Near-coastal lights-out ordinances and other approaches to shield lights can protect sea turtles and their nests. The VIIRS DNB light data, having significant improvements over comparable data by its predecessor, the DMSP-OLS, shows promise for continued and improved research about ecological effects of artificial light pollution.

Process-based models have been widely used for predicting environmental fate of contaminants. Nevertheless, accurate modeling of pentachlorophenol (PCP) dissipation in soils at the millimeter-scale remains a challenge due to the scarcity of observation data and uncertainty associated with model assumptions and estimation of the model parameters. To provide quantitative analysis of PCP-dissipation at the anaerobic/aerobic interface of a rhizobox experiment, this study implemented Bayesian parameter estimation for a process-based reactive chemical transport model. The model considered the main transport and transformation processes of chemicals including diffusion, sorption and degradation. The contributions of the processes to PCP dissipation were apportioned both in space and time. Using the maximum-a-posteriori (MAP) estimation of parameters, our model fitted the experimental data better compared with the previous work. Our results indicated that the most reactive zone for PCP dissipation occurred in the layer of 0–2.4 mm where degradation in solid phase dominated the PCP dissipation, while upward diffusion was the main mechanism for the reduction of PCP concentration in deeper layer (2.4–4.8 mm). By considering the coupled reactive transport of PCP and Cl⁻, the average degrees of PCP dechlorination in each layer were estimated from corresponding total concentrations of PCP and Cl⁻. The degrees of PCP dechlorination in the ponding water and the top layer of soil profile were highest, while 2,3,4,5- TeCP and 3,4,5- TCP were identified as the main dechlorination products in the soil. This study demonstrated that combining Bayesian estimation with process-based reactive chemical transport model can provide more insights of PCP dissipation at the millimeter-scale. This approach can help to understand complex dissipation mechanisms for other contaminants.

Microplastics and fibres occur in high concentrations along urban coastlines, but the occurrence of microplastic ingestion by fishes in these areas requires further investigation. Herein, the ingestion of debris (i.e., synthetic and natural fibres and synthetic fragments of various polymer types) by three benthic-foraging fish species Acanthopagrus australis (yellowfin bream), Mugil cephalus (sea mullet) and Gerres subfasciatus (silverbiddy) in Sydney Harbour, Australia has been quantified and chemically speciated by vibrational spectroscopy to identify the polymer type. Ingested debris were quantified using gut content analysis, and identified using attenuated total reflectance Fourier transform infrared (ATR-FTIR) and Raman microspectroscopies in combination with principal component analysis (PCA). The occurrence of debris ingestion at the time of sampling ranged from 21 to 64% for the three species, and the debris number ranged from 0.2 to 4.6 items per fish for the different species, with ∼53% of debris being microplastic. There was a significant difference in the amount of debris ingested among species; however, there was no difference among species when debris counts were standardised to fish weight or gut content weight, indicating that these species ingest a similar concentration of debris relative to their ingestion rate of other material. ATR-FTIR microspectroscopy successfully identified 72% of debris. Raman spectroscopy contributed an additional 1% of successful identification. In addition, PCA was used to non-subjectively classify the ATR-FTIR spectra resulting in the identification of an additional 9% of the debris. The most common microplastics found were polyester (PET), acrylic-polyester blend, and rayon (semi-synthetic) fibres. The potential of using Raman microspectroscopy for debris identification was investigated and provided additional information about the nature of the debris as well as the presence of specific dyes (and hence potential toxicity).