Volatile organic compounds (VOCs) from two sampling sites (HB and XB) in a power station centralized area, in Shuozhou city, China, were sampled by stainless steel canisters and measured by gas chromatography-mass selective detection/flame ionization detection (GC-MSD/FID) in the spring and autumn of 2014. The concentration of VOCs was higher in the autumn (HB, 96.87 μg/m3; XB, 58.94 μg/m3) than in the spring (HB, 41.49 μg/m3; XB, 43.46 μg/m3), as lower wind speed in the autumn could lead to pollutant accumulation, especially at HB, which is a new urban area surrounded by residential areas and a transportation hub. Alkanes were the dominant group at both HB and XB in both sampling periods, but the contribution of aromatic pollutants at HB in the autumn was much higher than that of the other alkanes (11.16–19.55%). Compared to other cities, BTEX pollution in Shuozhou was among the lowest levels in the world. Because of the high levels of aromatic pollutants, the ozone formation potential increased significantly at HB in the autumn. Using the ratio analyses to identify the age of the air masses and analyze the sources, the results showed that the atmospheric VOCs at XB were strongly influenced by the remote sources of coal combustion, while at HB in the spring and autumn were affected by the remote sources of coal combustion and local sources of vehicle emission, respectively. Source analysis conducted using the Positive Matrix Factorization (PMF) model at Shuozhou showed that coal combustion and vehicle emissions made the two largest contributions (29.98% and 21.25%, respectively) to atmospheric VOCs. With further economic restructuring, the influence of vehicle emissions on the air quality should become more significant, indicating that controlling vehicle emissions is key to reducing the air pollution.

Mercury (Hg) exposure poses a threat to both fish and human health. Sharks are known to bioaccumulate Hg, however, little is known regarding how Hg is distributed between different tissue groups (e.g. muscle regions, organs). Here we evaluated total mercury (THg) concentrations from eight muscle regions, four fins (first dorsal, left and right pectorals, caudal-from both the inner core and trailing margin of each fin), and five internal organs (liver, kidney, spleen, heart, epigonal organ) from two different shark species, bonnethead (Sphyrna tiburo) and silky shark (Carcharhinus falciformis) to determine the relationships of THg concentrations between and within tissue groups. Total Hg concentrations were highest in the eight muscle regions with no significant differences in THg concentrations between the different muscle regions and muscle types (red and white). Results from tissue collected from any muscle region would be representative of all muscle sample locations. Total Hg concentrations were lowest in samples taken from the fin inner core of the first dorsal, pectoral, and caudal (lower lobe) fins. Mercury concentrations for samples taken from the trailing margin of the dorsal, pectoral, and caudal fins (upper and lower lobe) were also not significantly different from each other for both species. Significant relationships were found between THg concentrations in dorsal axial muscle tissue and the fin inner core, liver, kidney, spleen and heart for both species as well as the THg concentrations between the dorsal fin trailing margin and the heart for the silky shark and all other sampled tissue types for the bonnethead shark. Our results suggest that biopsy sampling of dorsal muscle can provide data that can effectively estimate THg concentrations in specific organs without using more invasive, or lethal methods.

In the last few years, ship emissions have attracted growing attention in the scientific community. The main reason is the constant increase of marine emissions over the last twenty years due to the intensification of port traffic. Thus, this study aimed to evaluate ship emissions (PM10, PM2.5, NOx, SO2, CO, CO2, N2O CH4, NMVOC, and HC) through the activity-based methodology in four of the main ports of Portugal (Leixões, Setúbal, Sines and Viana do Castelo) during 2013 and 2014. The analysis was performed according to ship types (bulk carrier, container, general cargo, passenger, Ro-Ro cargo, tanker and others) and operational modes (manoeuvring, hotelling and during cruising). Results indicated that tankers were the largest emitters in two of the four analysed ports. Regarding cruising emissions, container ships were the largest emitters. . CO2, NOx and SO2 estimated emissions represented more than 95% of the cruising and in-port emissions. Results were also compared with the total national emissions reported by the Portuguese Environment Agency, and if the in-port emissions estimated in the present study would have been taken into account to these totals, emissions of NOx and SO2 would increase 15% and 24% in 2013 and 16% and 28% in 2014. Summing up ships seem to be an important source of air pollution, mainly regarding NOx and SO2.

Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model long-term dependencies, and most neglect spatial correlations. In this paper, a novel long short-term memory neural network extended (LSTME) model that inherently considers spatiotemporal correlations is proposed for air pollutant concentration prediction. Long short-term memory (LSTM) layers were used to automatically extract inherent useful features from historical air pollutant data, and auxiliary data, including meteorological data and time stamp data, were merged into the proposed model to enhance the performance. Hourly PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm) concentration data collected at 12 air quality monitoring stations in Beijing City from Jan/01/2014 to May/28/2016 were used to validate the effectiveness of the proposed LSTME model. Experiments were performed using the spatiotemporal deep learning (STDL) model, the time delay neural network (TDNN) model, the autoregressive moving average (ARMA) model, the support vector regression (SVR) model, and the traditional LSTM NN model, and a comparison of the results demonstrated that the LSTME model is superior to the other statistics-based models. Additionally, the use of auxiliary data improved model performance. For the one-hour prediction tasks, the proposed model performed well and exhibited a mean absolute percentage error (MAPE) of 11.93%. In addition, we conducted multiscale predictions over different time spans and achieved satisfactory performance, even for 13–24 h prediction tasks (MAPE = 31.47%).

With the increasing production and applications of TiO2 nanoparticles (NPs), their presence in aquatic environments, especially in sediments, will inevitably increase over time. Most studies investigating the influence of TiO2 NPs on the bioaccumulation of co-existing contaminants have focused on the aqueous phase; however, few have examined the sediment phase, which contains more TiO2 NPs and contaminants. We investigated the effects of TiO2 NPs on Pb accumulation by Corbicula fluminea in sediments, and explored extracellular and intracellular Pb concentrations in the various soft tissues of the bivalve. Pb was spiked with 50 mg/kg in sediment and TiO2 NPs/sediments ratios were within the range 0.2–3.0%. The results showed that TiO2 NPs presented larger adsorption capacity and affinity to Pb ions than the sediments. In addition, the large adsorption capacity of TiO2 NPs and the strong adsorption affinity to Pb ions caused part of the Pb ions released from sediments to aqueous phase were re-adsorbed by TiO2 NPs in sediments. The concentration of TiO2 NPs in C. fluminea tissues significantly increased with increasing TiO2 NP content in sediments, following the order: gill > mantle > foot > visceral mass, which differed from the results found in the aqueous phase. In addition, the proportions of extracellular and intracellular Pb concentrations changed significantly in all the tissues as a result of TiO2 NP contamination of sediments. TiO2 NPs promote increased extracellular Pb in foot, mantle, and gill tissues, and increased intracellular Pb in the visceral mass. These results may be beneficial to more scientifically evaluate and predict the environmental risks of TiO2 NPs to benthic organisms in sediments contaminated by heavy metals.

Numerous studies have evaluated the effects of long-term exposure to ambient air pollution on hypertension. However, little information exists regarding its effects on prehypertension, a very common, but understudied cardiovascular indicator. We evaluated data from 24,845 adults (ages 18–74 years) living in three Northeastern Chinese cities in 2009. Blood pressure (BP) was measured by trained observers using a standardized mercuric-column sphygmomanometer. Three-year (from 2006 to 2008) average concentrations of particles with an aerodynamic diameter ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxides (NO2), and ozone (O3) were calculated using data from monitoring stations. Effects were analyzed using generalized additive models and two-level regression analyses, controlling for covariates. We found positive associations of all pollutants with prehypertension (e.g. odds ratio (OR) was 1.17 (95% confidence interval (CI), 1.09–1.25) per interquartile range (IQR) of PM10) in a fully adjusted model, as compared to normotensive participants. These associations were stronger than associations with hypertension (e.g. OR was 1.03 (95% CI, 1.00, 1.07) per IQR of PM10). We have also found positive associations of all studied pollutants with systolic and diastolic BP: e.g., associations with PM10 per IQR were 1.24 mmHg (95% CI, 1.03–1.45) for systolic BP and 0.47 mmHg (95% CI, 0.33–0.61) for diastolic BP. Further, we observed that associations with BP were stronger in women and in older participants (systolic BP only). In conclusion, long-term exposure to ambient air pollution was more strongly associated with prehypertension than with hypertension, especially among females and the elderly. Thus, interventions to reduce air pollution are of great significance for preventing future cardiovascular events, particularly among individuals with prehypertension.

Two stages of selection from a pool of 56 fatty acids analyzed in Helix pomatia yielded a set of 12 biomarker acids undergoing significant changes in contact with three microdoses of toxic substances, i.e. three molluscicides containing metaldehyde, methiocarb, and potassium chloride (PC). The proposed palette of acids, including saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA), determined separately in the foot tissues and hepatopancreas of Gastropoda, can be used in ecotoxicological research as a reliable test of the effect of trace doses of stressors. The final set of the biomarker FA comprised C16:0; C18:0; C23:0; C18:1 n-9; C20:1 n-9; C18:2 n-6; C18:3 n-3; C20:2; C20:4 n-6; C20:5 n-3; C22:4 n-6; and C22:5 n-3. A clear physiological response manifested as changes in the content of fatty acids (FA) was observed in the snails even in the case of the lowest doses of the pollutants. All experimental factors analyzed, i.e., the dose (5, 10, or 15 μl 0.01% w/v concentration) and the type of preparation (metaldehyde, methiocarb or PC), had a significant (p ≤ 0.01) impact on the FA composition of the foot and hepatopancreas. Limitation of the analysis to a narrow pool of reactive FA meets the requirements of parameters of biomarkers of exposure and facilitates and accelerates visualization of the bioindicator organism's response to the presence of the stressor in the environment.

Bauxite extraction by-products (red mud) were used to evaluate their potential ability to stabilize trace elements from dredged and aerated/humidified marine sediment. The investigated by-products were: bauxaline®(BX) that is a press-filtered red mud; bauxsol™(BS) that is a press-filtered red mud previously washed with excess of seawater, and gypsum neutralized bauxaline® (GBX). These materials were separately mixed to dredged composted sediment sample considering 5% and 20% sediment: stabilizer ratios. For pilot experiments, rainfall events were regularly simulated for 3 months. Concentrations of As, Mo, Cd, Cr, Zn, Cu, and Ni were analyzed in collected leachates as well as toxicity. Results showed that Cd, Mo, Zn, and Cu were efficiently stabilized in the solid matrix when 20% of BX, BS, and GBX was applied. Consequently, toxicity of leachates was lower than for the untreated sediment, meaning that contaminants mobility was reduced. A 5% GBX was also efficient for Mo, Zn and Cu stabilization. In all scenarios, As stabilization was not improved. Compared to all other monitored elements, Mo mobility seemed to depend upon temperature-humidity conditions during pilot experiments suggesting the need of further investigations.

Human and ecosystem health concerns for arsenic (As) in the lower Athabasca River downstream of Athabasca Bituminous Sands (ABS) mining (Alberta, Canada) prompted an investigation to determine its forms in surface and groundwater upstream and downstream of industry. Dissolved As species, together with total and particulate As, were used to evaluate the potential bioavailability of As in water as well as to decipher inputs from natural geological processes and ABS mining and upgrading activities. Water samples were collected from the river in October at 13 locations in 2014 and 19 locations in 2015, spanning up to 125 km. Additional samples were collected from groundwater, tributaries and springs. “Dissolved” (<0.45 μm) As was consistently low in the Athabasca River (average 0.37 ± 0.01 and 0.34 ± 0.01 μg L⁻¹ in 2014 and 2015, respectively) as well as tributaries and springs (<1 μg L⁻¹), with As(V) as the predominant form. The average total As concentration was higher in 2014 (12.7 ± 2.8 μg L⁻¹) than 2015 (3.3 ± 0.65 μg L⁻¹) with nearly all As associated with suspended solids (>0.45 μm). In 2014, when total As concentrations were greater, a significant correlation (p < 0.05) was observed with thorium in particles > 0.45 μm, suggesting that mineral material is an important source of As. Naturally saline groundwater contained low dissolved As (<2 μg L⁻¹) and did not appear to be a significant source to the river. Arsenic in shallow groundwater near a tailings pond exceeded 50 μg L⁻¹ predominantly as As(III) warranting further investigation.

Understanding the colloidal stability of graphene is essential for predicting its transport and ecological risks in aquatic environments. We investigated the agglomeration of ¹⁴C-labeled few-layer graphene (FLG) at concentrations spanning nearly four orders of magnitude (2 μg/L to 10 mg/L) using dynamic light scattering and sedimentation measurements. FLG agglomerates formed rapidly in deionized water at concentrations >3 mg/L. From 1 mg/L to 3 mg/L, salt-induced agglomeration was decreased with dilution of FLG suspensions; the critical coagulation concentration of the more concentrated suspension (3 mg/L) was significantly lower than the dilute suspension (1 mg/L) in the presence of NaCl (1.6 mmol/L and 10 mmol/L, respectively). In contrast, FLG underwent slow agglomeration and settling at concentrations ≤0.1 mg/L in NaCl solutions and ambient waters with low ionic strength (<10 mmol/L). FLG nanoparticles with smaller lateral sizes (25 nm–75 nm) were shown to agglomerate more slowly than larger FLG, and these small FLG particles exhibited greater bioaccumulation in zebrafish embryo and stronger chorion penetration ability than larger FLG particles. These findings suggest that FLG at more environmentally relevant concentration is relatively stable and may have implications for exposure of small FLG to ecological receptors.