Spot urine samples were collected in summer and winter season to examine the association between temperature variation and phthalate concentration in an occupationally exposed group. We analysed samples by high-performance liquid chromatography with mass spectrometry (HPLC-MS/MS) to determine the concentrations of four phthalate metabolites: mono (2-ethylhexyl) phthalate (MEHP), monobutyl phthalate (MnBP), monoethyl phthalate (MEP), and monoisononyl phthalate (MiNP). We observed significantly higher urinary concentrations of all monitored phthalate metabolites collected during the summer in occupationally exposed group (MEP p < 0.0015, MiNP p < 0.0001, MnBP p < 0.00019, and MEHP p < 0.05); however, in general, population was noticed this difference only for MEHP (p < 0.05) in winter season. We conclude that increasing indoor and outdoor temperature is related to phthalate exposure in specific types of work environment.

To better understand the past and present impact of contaminants of emerging concern (CECs) in coastal and marine ecosystems, archived samples were analyzed for a broad suite of analytes, including pharmaceuticals and personal care products (PPCPs), flame retardants (including PBDEs), perfluorinated compounds (PFCs), and current-use pesticides. Surface sediment, mussels (Mytilus spp.) and sediment core samples collected from the California (USA) coast were obtained from environmental specimen banks. Selected CECs were detected in recent surface sediments, with nonylphenol (4-NP), its mono- and di-ethoxylates (NP1EO and NP2EO), triclocarban, and pyrethroid insecticides in the greatest abundance. Alkylphenols, triclocarban, and triclosan were present in sediment core segments from the 1970s, as well as in Mytilus tissue collected during the 1990s. Increasing concentrations of some CECs (e.g., miconazole, triclosan) were observed in the surface layers (ca. 2007) of a sediment core, in contrast to peak concentrations of 4-NP and triclocarban corresponding to input during the 1970s, and an apparent peak input for PBDEs during the 1990s. These results suggest that chemicals sometimes referred to as “emerging” (e.g., alkylphenols, triclocarban) have been present in the aquatic environment for several decades and are decreasing in concentration, whereas others (e.g., miconazole, triclosan) are increasing.

Since the 1970s, environmental specimen banks (ESB) have emerged in many countries. Their highly standardised sampling and archiving strategies make them a valuable tool in tracing time trends and spatial distributions of chemicals in ecosystem compartments. The present article intends to highlight the potential of ESBs for regulatory agencies in the European Union (EU). The arguments are supported by examples of retrospective monitoring studies conducted under the programme of the German ESB. These studies have evaluated the success of regulatory and industry provisions for substances of concern (i.e. PCB, polybrominated diphenyl ethers, perfluorinated compounds, alkylphenol compounds, organotin compounds, triclosan/methyl-triclosan, musk fragrances). Time trend studies revealed for example that levels of organotin compounds in marine biota from German coastal waters decreased significantly after the EU had decided on a total ban of organotin-based antifoulings in 2003. Similarly, concentrations of commercially relevant congeners of polybrominated diphenyl ethers decreased in herring gull eggs from the North Sea only after an EU-wide ban in 2004. The data presented demonstrate the usefulness of ESB samples for (retrospective) time trend monitoring and underline the benefit of a more intensive cooperation between chemicals management and specimen banking.

Hibernia is Canada’s largest offshore oil platform. Produced water is the major waste byproduct discharged into the ocean. In order to evaluate different potential disposal methods, a comprehensive study was performed to determine the impact from the discharge. Microorganisms are typically the first organisms to respond to changes in their environment. The objectives were to characterize the microbial communities and the chemical composition in the produced water and to characterize changes in the seawater bacterial community around the platform. The results from chemical, physicochemical, and microbial analyses revealed that the discharge did not have a detectable effect on the surrounding seawater. The seawater bacterial community was relatively stable, spatially. Unique microorganisms like Thermoanaerobacter were found in the produced water. Thermoanaerobacter-specific q-PCR and nested-PCR primers were designed, and both methods demonstrated that Thermoanaerobacter was present in seawater up to 1000 m from the platform. These methods could be used to track the dispersion of produced water into the surrounding ocean.

This paper uses panel cointegration techniques and Granger causality tests to examine the dynamic causal link between per capita real gross domestic product (GDP), combustible renewables and waste (CRW) consumption, and CO₂ emissions for a panel of five North African countries during the period 1971–2008. Granger causality test results suggest short- and long-run unidirectional causalities running from CO₂ emissions and CRW consumption to real GDP and a short-run unidirectional causality running from CRW to CO₂ emissions. The results from panel long-run fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimates show that CO₂ emissions and CRW consumption have a positive and statistically significant impact on GDP. Our policy recommendations are that these countries should use more CRW because this increases their output, reduces their energy dependency on fossil energy, and may decrease their CO₂ emissions.

Ozone exposure- and dose-response relationships based on photosynthetic leaf traits (CO2 assimilation, chlorophyll content, Rubisco and PEPc activities) were established for wheat, maize and poplar plants grown in identical controlled conditions, providing a comparison between crop and tree species, as well as between C3 and C4 plants. Intra-specific variability was addressed by comparing two wheat cultivars with contrasting ozone tolerance. Depending on plant models and ozone levels, first-order, second-order and segmented linear regression models were used to derive ozone response functions. Overall, flux-based functions appeared superior to exposure-based functions in describing the data, but the improvement remained modest. The best fit was obtained using the POD0.5 for maize and POD3 for poplar. The POD6 appeared relevant for wheat, although intervarietal differences were found. Our results suggest that taking into account the dynamics of leaf antioxidant capacity could improve current methods for ozone risk assessment for plants.

Accurate measurements of PM₂.₅ concentration over time and space are especially critical for reducing adverse health outcomes. However, sparsely stationary monitoring sites considerably hinder the ability to effectively characterize observed concentrations. Utilizing data on meteorological and land-related factors, this study introduces a radial basis function (RBF) neural network method for estimating PM₂.₅ concentrations based on sparse observed inputs. The state of Texas in the USA was selected as the study area. Performance of the RBF models was evaluated by statistic indices including mean square error, mean absolute error, mean relative deviation, and the correlation coefficient. Results show that the annual PM₂.₅ concentrations estimated by the RBF models with meteorological factors and/or land-related factors were markedly closer to the observed concentrations. RBF models with combined meteorological and land-related factors achieved best performance relative to ones with either type of these factors only. It can be concluded that meteorological factors and land-related factors are useful for articulating the variation of PM₂.₅ concentration in a given study area. With these covariate factors, the RBF neural network can effectively estimate PM₂.₅ concentrations with acceptable accuracy under the condition of sparse monitoring stations. The improved accuracy of air concentration estimation would greatly benefit epidemiological and environmental studies in characterizing local air pollution and in helping reduce population exposures for areas with limited availability of air quality data.

A dispersion-advection model was used to simulate the Elk river chemical spill 2014. The numerical and analytical solutions were used to predict the concentrations of 4-methylcyclohexane methanol (MCHM) at the water treatment plants located along the Elk and Kanawha rivers. The results are of similar magnitude as measured concentrations although a time-lag was found between modeled and measured plume arrival likely due to accumulation of systematic errors. Considering MCHM guidelines for drinking water, the spill represented a serious health threat through the water up taken by the treatment plant located on the Elk river and it also constituted a risk of contamination for the drinking water produced by treatment plants located on the Kanawha river.

The deterioration of water quality in Taihu Lake, China, has caused widespread concern in recent years. The primary pollution sources of Taihu Lake are its inflow rivers. Effective environmental water management strategies need to be implemented in these rivers to improve the water quality of Taihu Lake and to promote sustainable development in the region. In this study, the QUAL2K model is used in conjunction with the trial and error approach to assess permissible load capacities for the Wujin River (a major tributary of Taihu Lake) in terms of COD, NH₃-N, TN, and TP. Results show that permissible annual loads for these pollutants are 5216.31, 491.71, 948.53, and 104.38 t, respectively. This suggests that COD, NH₃-N, TN, and TP loads in the Wujin River catchment need to be reduced by 13.35, 27.26, 47.75, and 37.08 %, respectively, to satisfy national water quality objectives. Total amount control measures are proposed to control and reduce pollution loads of the Wujin River catchment. The method applied in this study should provide a sound basis for water environmental management decision-making.

The present work proposes a new experimental design using iron enrichment to select a single species from an entire meiobenthic nematode community. The high diversity of nematodes makes it impossible to study their responses to stressors in terms of chemical biomarkers, as this kind of research demands a single species as a form of biological material. Two assemblages, one from a control site (Canal) and one from an iron-contaminated site (Fouledh) in Bizerte Lagoon (Tunisia), were used to validate the protocol and to study whether pre-exposure to iron could affect the ease of the selection process. Analyses of variance suggested that the abundance and species number of nematodes from the Canal and Fouledh sites decreased discernibly with exposure to iron. Multivariate analyses performed on nematode abundances revealed that Oncholaimus campylocercoides, Sabatieria granifer, Sabatieria punctata and Theristus flevensis were the most tolerant species, probably due to their deposit-feeding behaviour. Species with a restricted feeding spectrum showed a low tolerance potential. At the end of the experiment, O. campylocercoides became the unique component of the nematode community from both sites. The complete alteration of the community was achieved with more difficulty for nematodes from Fouledh than for those from Canal. The identity of the selected species was confirmed at both the morphological levels and by sequencing the nuclear small subunit ribosomal DNA (18S rDNA).