Microplastics may lose buoyancy and occur in deeper waters and ultimately sink to the sediment and this may threaten plankton inhabiting in various water layers and benthic organisms. Here, we conduct the first survey on microplastics in the water column and corresponding sediment in addition to the surface water in the Bohai Sea. A total of 20 stations covering whole Bohai Sea were selected, which included 6 stations specified for water column studying. Seawater was sampled every 5 m, with maximal depth of 30 m in the water column using Niskin bottles coupled with a ship-based conductivity, temperature and depth sensor (CTD) system and surface sediment samples were collected using box corer. The results indicated that higher microplastic levels accumulated at a depth range of 5–15 m in the water column in some stations, suggesting the surface water survey was not sufficient to reflect microplastics loading in a water body. Fibers predominated microplastic types in both seawater and sediment of the Bohai Sea, which accounted for 75%–96.4% of the total microplastics. However the relatively proportion of the fibers in the deeper water layers and sediment was lower than that in the surface water. Microplastic shapes are more diverse in the sediment than in the seawater in general. The microplastic sizes changed with depth in the water column and the proportion of the size-fraction < 300 μm increased with depth, probably as a result of rapid biofouling on the small microplastics due to their higher specific surface area. Such depth distribution also implied that sampling with manta net (>330 μm) that commonly used in the oceanographic survey might underestimate microplastics abundance in the water column. Further studies are recommended to focus on the sinking behavior of microplastics and their effects on marine organisms.

We examine the spatio-temporal trends of mercury, a well-known global legacy contaminant, in eleven fish species across all of the Canadian Great Lakes. These particular fish species are selected based on their ecological, commercial, and recreational importance to the biodiversity and fishing industry of the Great Lakes. We present a two-pronged Bayesian methodological framework to rigorously assess mercury temporal trends across multiple fish species and locations. In the first part of our analysis, we develop dynamic linear models to delineate the total mercury levels and rates of change, while explicitly accounting for the covariance between fish length and mercury levels in fish tissues. We then use hierarchical modelling to evaluate the spatial variability of mercury contamination between nearshore and offshore locations, as well as to examine the hypothesis that invasive species have induced distinct shifts on fish mercury contamination trends. Our analysis suggests that the general pattern across the Great Lakes was that the elevated mercury concentrations during the 1970s had been subjected to a declining trend throughout the late 1980s/early 1990s, followed by a gradual stabilization after the late 1990s/early 2000s. The declining trend was more pronounced with top fish predators, whereas benthivorous fish species mainly underwent wax-and-wane cycles with a weaker evidence of a long-term declining trend. Historically contaminated regions, designated as Areas of Concern, and bays receiving riverine inputs are still characterized by mercury concentrations that can lead to consumption restrictions. Lake Erie displayed the lowest mercury levels across all the fish species examined. However, several species of commercial importance showed a reversing (increasing) trend in the 2000s, although their current levels do not pose any major concerns for consumption advisories. These recent trend reversals can be linked with systematic shifts in energy trophodynamics along with the food web alterations induced from the introduction of non-native species, and the potentially significant fluxes from the atmosphere.

Despite intensive research carried out on particulates, correlation between engine-out particulate emissions and adverse health effects is not well understood yet. Particulate emissions hold enormous significance for mega-cities like Delhi that have immense traffic diversity. Entire public transportation system involving taxis, three-wheelers, and buses has been switched from conventional liquid fuels to compressed natural gas (CNG) in the Mega-city of Delhi. In this study, the particulate characterization was carried out on variety of engines including three diesel engines complying with Euro-II, Euro-III and Euro-IV emission norms, one Euro-II gasoline engine and one Euro-IV CNG engine. Physical, chemical and biological characterizations of particulates were performed to assess the particulate toxicity. The mutagenic potential of particulate samples was investigated at different concentrations using two different Salmonella strains, TA98 and TA100 in presence and absence of liver S9 metabolic enzyme fraction. Particulates emitted from diesel and gasoline engines showed higher mutagenicity, while those from CNG engine showed negligible mutagenicity compared to other test fuels and engine configurations. Polycyclic aromatic hydrocarbons (PAHs) adsorbed onto CNG engine particulates were also relatively fewer compared to those from equivalent diesel and gasoline engines. Taken together, our findings indicate that CNG is comparatively safer fuel compared to diesel and gasoline and can offer a cleaner transport energy solution for mega-cities with mixed-traffic conditions, especially in developing countries.

Maternal 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) serum levels during pregnancy have been negatively linked to child neurodevelopment in contrast to intake of omega-3 and -6 (ω-3 and ω-6) fatty acids.To assess whether maternal dietary intake of ω-3 and ω-6 during pregnancy modifies the association between exposure to DDE and child neurodevelopment from age 42–60 months.Prospective cohort study with 142 mother–child pairs performed in Mexico. DDE serum levels were determined by electron capture gas chromatography. Dietary ω-3 and ω-6 intake was estimated by questionnaire. Child neurodevelopment was assessed by McCarthy Scales.Docosahexaenoic (DHA) fatty acid intake significantly modified the association between DDE and motor component: increased maternal DDE was associated with lower motor development in children whose mothers had lower DHA intake (βlog2DDE = −1.25; 95% CI: −2.62, 0.12), in contrast to the non-significant increase among children whose mothers had higher DHA intake (βlog2DDE-motor = 0.50; 95% CI: 0.55, 1.56). Likewise, arachidonic fatty acid (ARA) intake modified the association between DDE and memory component: increased maternal DDE was associated with a significantly larger reduction in the memory component in children whose mothers had lower ARA intake (βlog2DDE = −1.31; 95% CI: −2.29, −0.32) than children whose mothers had higher ARA intake (βlog2DDE-memory = 0.17; 95% CI: −0.78, 1.11).Dietary intake of DHA and ARA during pregnancy may protect against child neurodevelopment damage associated with prenatal maternal DDE levels.

The aryl hydrocarbon receptor (AhR) plays an important role in mediating dioxins toxicity. Currently, genes of P450 families are major research interests in studies on AhR-mediated gene alterations caused by dioxins. Genes related to other metabolic pathways or processes may be also responsive to dioxin exposures. Amino acid transporter B0AT1 (encoded by SLC6A19) plays a decisive role in neutral amino acid transport which is present in kidney, intestine and liver. However, effects of dioxins on its expression are still unknown. In the present study, we focused on the effects of dioxin and dioxin-like compounds on SLC6A19 expression in HepG2 cells. We identified SLC6A19 as a novel putative target gene of AhR activation in HepG2 cells. 2, 3, 7, 8-tetrachlorodibenzo-p-dioxin (TCDD) increased the expression of SLC6A19 in time- and concentration-dependent manners. Using AhR antagonist CH223191 and/or siRNA assays, we demonstrated that certain AhR agonists upregulated SLC6A19 expression via AhR, including TCDD, 1,2,3,7,8-pentachlorodibenzo-p-dioxin (1,2,3,7,8-PeCDD), 2,3,4,7,8- pentachlorodibenzofuran (2,3,4,7,8-PeCDF) and PCB126. In addition, the expression of B0AT1 was also significantly induced by TCDD in HepG2 cells. Our study suggested that dioxins might affect the transcription and translation of SLC6A19 in HepG2 cells, which might be a novel putative gene to assess dioxins' toxicity in amino acid transport and metabolism in liver.

Particulate matter with diameter less than 1 μm (PM1) has been found to be closely associated with air quality, climate changes, and even adverse human health. However, a large gap in our knowledge concerning the large-scale distribution and variability of PM1 remains, which is expected to be bridged with advanced remote-sensing techniques. In this study, a hybrid model called principal component analysis-general regression neural network (PCA-GRNN) is developed to estimate hourly PM1 concentrations from Himawari-8 aerosol optical depth in combination with coincident ground-based PM1 measurements in China. Results indicate that the hourly estimated PM1 concentrations from satellite agree well with the measured values at national scale, with R2 of 0.65, root-mean-square error (RMSE) of 22.0 μg/m3 and mean absolute error (MAE) of 13.8 μg/m3. On daily and monthly time scales, R2 increases to 0.70 and 0.81, respectively. Spatially, highly polluted regions of PM1 are largely located in the North China Plain and Northeast China, in accordance with the distribution of industrialisation and urbanisation. In terms of diurnal variability, PM1 concentration tends to peak in rush hours during the daytime. PM1 exhibits distinct seasonality with winter having the largest concentration (31.5±3.5 μg/m3), largely due to peak combustion emissions. We further attempt to estimate PM2.5 and PM10 with the proposed method and find that the accuracies of the proposed model for PM1 and PM2.5 estimation are significantly higher than that of PM10. Our findings suggest that geostationary data is one of the promising data to estimate fine particle concentration on large spatial scale.

In this study, the measurement of volatile organic compounds (VOCs) was conducted at Beijing Capital International Airport (ZBAA) and a background reference site in four seasons of 2015. Total concentrations of VOCs were 72.6 ± 9.7, 65.5 ± 8.7, 95.8 ± 11.0, and 79.2 ± 10.8 μg/m3 in winter, spring, summer, and autumn, respectively. The most abundant specie was toluene (10.1%–17.4%), followed by benzene, ethane, isopentane, ethane, acetylene, and n-butane. Seasonal variations of VOCs were analyzed, and it was found that the highest concentration occurring in summer, while the lowest in spring. For the diurnal variation, the concentration of VOCs in the daytime (9:00–15:00) was less than that at night (15:00–21:00) obviously. Ozone Formation Potential (OFP) was calculated by using Maximum Incremental Reactivity (MIR) method. The greatest contribution to OFP from alkenes and aromatics, which accounted for 27.3%–51.2% and 36.6%–58.6% of the total OFP. The WRF-CMAQ model was used to simulate the impact of airport emissions on the surrounding area. The results indicated that the maximum impact of VOCs emissions and all sources emissions at the airport on O3 was 0.035 and −23.8 μg/m3, respectively. Meanwhile, within 1 km from the airport, the concentration of O3 around the airport was greatly affected by airport emitted.

Differences in the distribution, partitioning, and bioaccumulation characteristics of arsenicals between freshwater and saltwater systems remain poorly understood. To determine the characteristics of distribution and behavior of arsenicals, multimedia environmental samples including water, suspended particles, zooplankton, sediments, and porewater were collected from inner (five sites, freshwater) and outer (five sites, saltwater) regions of the estuary dike of the Youngsan River Estuary in South Korea (Nov., 2012). Six organic and inorganic forms of As were separated and measured using HPLC–ICP/MS equipped with an anion exchange column. Concentrations of arsenicals in water samples of the inner region (mean = 1.5 μg As L−1) were significantly lower than in those of the outer region (mean = 5.2 μg As L−1). Conversely, concentrations of As in suspended particles in the inner region (mean = 14 μg As g−1) were much greater than in the outer region (mean = 5.7 μg As g−1). The field-based distribution coefficient (Kd) for As depended strongly on salinity; relatively greater Kd values were found in freshwater compared with saltwater. The AsV was found to be the major form of As in all water and particle samples in both inner and outer regions. The zooplankton species were significantly distinguishable between the inner and outer regions; cladocerans were the most dominant species in freshwater and cyclopoida were predominantly found in saltwater. The As concentrations in zooplankton were shown to be particle-concentration dependent, suggesting that dietary exposure plays a substantial role in the bioaccumulation of As. Inorganic arsenicals, such as AsV and AsIII were the most dominant forms found in zooplankton. Partitioning behavior of As between porewater and sediments was similar to that in water–particle distributions. The results of the present study enhance the understanding of As biogeochemistry in river and estuarine environments.

Coastal salt marshes provide the valuable ecosystem service of removing anthropogenic nitrogen (N) via microbially-mediated denitrification. During the 2010 Deepwater Horizon (DWH) spill, oil exposure killed marsh plants in some regions and contributed to rapid compositional shifts in sediment microbial communities, which can impact ecosystem denitrification capacity. Within 3–5 years of the spill, plant biomass and microbial communities in some impacted marshes can recover to a new stable state. The objective of this study was to determine whether marsh recovery 6 years after the DWH oil spill results in subsequent recovery of denitrification capacity. We measured denitrification capacity (isotope pairing technique), microbial 16S rRNA gene composition, and denitrifier abundance (quantitative PCR) at sites subjected to light, moderate, and heavy oiling during the spill that were not targeted by any clean-up efforts. There were no differences in plant belowground biomass, sediment extractable NH₄⁺, inorganic nitrogen flux, 16S rRNA composition, 16S rRNA diversity, or denitrifier functional gene (nirS, norB, and nosZ) abundances associated with oiling status, indicating that certain drivers of ecosystem denitrification capacity have recovered or achieved a new stable state six years after the spill. However, on average, denitrification capacities at the moderately and heavily oiled sites were less than 49% of that of the lightly oiled site (27.7 ± 14.7 and 37.2 ± 24.5 vs 71.8 ± 33.8 μmol N m⁻² h⁻¹, respectively). The presence of heavily weathered oiled residue (matched and non-matched for MC252) had no effect on process rates or microbial composition. The loss of function at the moderately and heavily oiled sites compared to the lightly oiled site despite the comparable microbial and environmental factors suggests that oiling intensity plays a role in the long-term recovery of marsh ecosystem services.

Inefficient biomass combustion in traditional cookstoves generates high levels of household air pollution (HAP) that is associated with numerous adverse environmental and human health conditions. Many cookstoves have been evaluated using laboratory tests, but past studies revealed discrepancies between laboratory and field measurements. Fuel re-loading, a common operation in actual use but not required in the laboratory test, might be a contributing factor to this laboratory-field gap. In this study, we evaluated the pollutant emissions performance of a semi-gasifier cooking stove using both laboratory and field measurements. Emission factors and real-time properties of CO and PM₂.₅ were separately measured during the following 4 phases of a typical cooking event: lighting, stable combustion, fuel re-loading and post fuel re-loading. We quantified the CO and PM₂.₅ contributions to total cooking event emissions in each phase. We found over 70% lower PM₂.₅ emissions and 60% lower CO emissions during 3 no re-loading laboratory tests compared with all 16 field tests. Lighting generated 83.8% ± 15.6% of the total PM₂.₅ and 39.1% ± 7.8% of the total CO in laboratory tests without fuel re-loading, and 57.8% ± 33.5% and 37.9% ± 21.2% of the total PM₂.₅ and CO in field tests, respectively. On average, fuel re-loading led to 29.1% ± 30.8% of PM₂.₅ emissions and 24.9% ± 22.6% of CO emissions in 16 field tests, which also contributed to significant discrepancies between laboratory and field-based emissions. According to the ISO IWA tiered stove ratings for emissions, fuel re-loading led to at least one tier lower ranking in both laboratory and field cookstove tests. Fuel re-loading could be an important factor causing laboratory-field discrepancy of emissions, thus it could be considered in future cookstove selection and intervention projects.