Mariculture sediment has been recognized as a major contributor of environmental antibiotic resistance genes (ARGs), which are challenging the treatment of infections worldwide. Both antibiotics and fishmeal are used in aquaculture, and each has the potential to facilitate ARG dissemination, however their combined impact on the sediment resistome and their relative contribution remain unclear. In this study, microcosms were exposed to varying concentrations of tetracycline with or without fishmeal (0.1% wt/wt) for 14 days. Sediment genomic DNA was analyzed using high throughput quantitative PCR and 16S rRNA gene amplicon sequencing to compare the contribution of fishmeal and tetracycline to antibiotic resistomes and bacterial communities in mariculture sediment. Sixty-seven ARGs were detected potentially correlating to resistance for several major antibiotics. Fishmeal, but not the dose of tetracycline, contributed to the significant increase of both ARG abundance and diversity in the sediment. Based on principle coordinate analysis and hierarchical clustering, ARGs were clustered into two groups depending on whether fishmeal was added. Aminoglycoside, macrolide–lincosamide–streptogramin b (MLSb) and tetracycline resistance genes were the most abundant when fishmeal was used, while a significant increase in mobile genetic element (MGE) abundance was also detected (P < 0.05). Meanwhile, bacterial community structures were detected with distinct patterns between the two groups (Adonis, P < 0.05). Using the Mantel test and partial least squares path modeling, we identified that sediment resistomes were significantly correlated with microbial community structures (P < 0.05) which were mainly driven by nutrients in fishmeal. Together our findings suggested that fishmeal plays a more important role than tetracycline in proliferation of ARGs in mariculture sediment. This study may provide new insights into the mitigation of ARG propagation in mariculture operations.

The application of the fungicide thiabendazole (TBZ) in fruit packaging plants (FPP) results in the production of effluents which are often disposed in adjacent field sites. These require remediation to prevent further environmental dispersal of TBZ. We assessed the bioaugmentation potential of a newly isolated TBZ-degrading bacterial consortium in a naturally contaminated soil (NCS) exhibiting a natural gradient of TBZ levels (12000, 400, 250 and 12 mg kg⁻¹). The effect of aging on bioaugmentation efficacy was comparatively tested in a soil with similar physicochemical properties and soil microbiota, which was artificially, contaminated with the same TBZ levels (ACS). The impact of bioaugmentation and TBZ on the bacterial diversity in the NCS was explored via amplicon sequencing. Bioaugmentation effectively removed TBZ from both soils at levels up to 400 mg kg⁻¹ but failed at the highest contamination level (12000 mg kg⁻¹). Dissipation of TBZ in bioaugmented samples showed a concentration-dependent pattern, while aging of TBZ had a slight effect on bioaugmentation efficiency. Bioaugmentation had no impact on the soil bacterial diversity, in contrast to TBZ contamination. Soils from the hotspots of TBZ contamination (12000 mg kg⁻¹) showed a drastically lower α-diversity driven by the dominance of β- and γ-proteobacteria at the expense of all other bacterial phyla, especially Actinobacteria. Overall, bioaugmentation with specialized microbial inocula could be an effective solution for the recovery of disposal sites contaminated with persistent chemicals like TBZ.

From December 1993 to January 1995 and from October 2009 to October 2010, a total of 320 and 365 daily samples of the PM2.5 were collected at a rural background site (National Atmospheric Observatory Košetice) in Central Europe. The PM2.5 samples were analyzed for 29 and 26 elements respectively by Particle-Induced X-ray Emission (PIXE) and water-soluble inorganic ions by Ion Chromatography (IC) in 2009/2010. The Positive Matrix Factorization (PMF) was applied to the chemical composition of PM2.5 to determine its sources. The decreasing trends of almost all elements concentrations, especially the metals regulated by the EU Directive (2004/107/EC) are evident. The annual median ratios indicate a decrease in concentrations of the PM2.5 elements. The slight increase of K concentrations and Spearman's rank correlation coefficient rs 0.09 K/Se points to a rise in residential wood combustion. The S concentrations are nearly comparable (higher mean in 2009/2010, while the annual median ratio is under 1). The five major source types in the mid-1990s were ascribed to brown coal combustion, oil combustion, sea salt and dust – long-range transport, re-suspended dust and black coal combustion. The industrial combustion of brown and/or black coal (rs 0.75 Se/As, rs 0.57 Ga/Ge and rs 0.20 As/Zn) and oil (rs 0.72 V/Ni) of the regional origin dominated. In the 1990s, the potential source regions were the border area of Czech Republic, German and Poland (brown coal), the Moravia-Silesia region at the Czech-Polish border (black coal), and Slovakia, Austria, Hungary, and the Balkans (oil). In 2009/2010, the apportioned sources were sulfate, residential heating, nitrate, industry, re-suspended dust, and sea salt and dust – long-range transport. The secondary sulfate from coal combustion and residential biomass burning (rs 0.96, K/K+) of local origin dominated.The declining trend of the elemental concentrations and change in the source pattern of the regional background PM2.5 in Central Europe between the mid-1990s and 2009/10 reflects the economic transformation and impact of stricter legislation in Central Europe.

Ants accumulate heavy metals and respond to pollution with modification in species composition, community structure, altered behaviour and immunity. However, the levels of heavy metals in ants’ nests and explicit individual-level responses towards heavy metals have not been revealed. We found that red wood ants Formica lugubris accumulate high and correlated values of such heavy metals as Al, Cd, Co, Cu, Fe, Ni, Pb and Zn both in ants and nest material near cobalt smelter in Finland. Relative differences in metal concentrations were higher in nests than in ants. The highest values were obtained for elements such as Co (36.6), Zn (14.9), Cd (9.7), Pb (8.5), Cu (7.4), Ni (6.4), As (4.7), Cr (2.9) and Fe (2.4) in nest material, and Co (32.7), Cd (6.3), Pb (6), Fe (2.8), Ni (2.9) and Zn (2.1) in ants. In industrial and reference areas, ants have no differences in size, but differed in dry and residual body mass. In polluted areas, F. lugubris had less melanised heads, but not thoraxes. The sensitivity of cuticular colouration in red wood ants subjected to heavy metal pollution might be related to metal-binding properties of melanins. The overall results are useful for the improvement of biomonitoring techniques using ants as indicators of industrial contamination and for further discovery of novel ecotoxicological biomarkers.

Nanosized particles (NPs), such as TiO₂, Silver, graphene NPs, nanoscale zero-valent iron, carbon nanotubes, etc., are increasingly used in industrial processes, and releases at production plants and from landfills are likely scenarios for the next years. As a consequence, appropriate procedures and tools to quantify the risks for human health associated to these releases are needed.The tiered approach of the standard ASTM procedure (ASTM-E2081-00) is today the most applied for human health risk assessment at sites contaminated by chemical substances, but it cannot be directly applied to nanoparticles: NP transport along migration pathways follows mechanisms significantly different from those of chemicals; moreover, also toxicity indicators (namely, reference dose and slope factor) are NP-specific. In this work a risk assessment approach modified for NPs is proposed, with a specific application at Tier 2 to migration in groundwater. The standard ASTM equations are modified to include NP-specific transport mechanisms. NPs in natural environments are typically characterized by a heterogeneous set of NPs having different size, shape, coating, etc. (all properties having a significant impact on both mobility and toxicity). To take into account this heterogeneity, the proposed approach divides the NP population into classes, each having specific transport and toxicity properties, and simulates them as independent species. The approach is finally applied to a test case simulating the release of heterogeneous Silver NPs from a landfill. The results show that taking into account the size-dependent mobility of the particles provides a more accurate result compared to the direct application of the standard ASTM procedure. In particular, the latter tends to underestimate the overall toxic risk associated to the nP release.

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.

Aerosol samples (as PM₁₀, n = 250) were collected from three rural/remote receptor locations in the mid Brahmaputra plain region and were chemically characterized for metals (Al, Fe, Co, Cu, Cr, Cd, Mn, Ni, Pb), ions (Ca²⁺, Mg²⁺, Na⁺, K⁺, NH₄⁺, F⁻, Cl⁻, NO₃⁻, SO₄²⁻), and carbon. Vital ratios like NO₃⁻/SO₄²⁻, EC/OC, K⁺/EC, K⁺/OC, enrichment factors and inter-species correlations were exploited to appreciate possible sources of aerosol. These empirical analyses pointed towards anthropogenic contributions of aerosol, particularly from biomass burning, vehicular emission, and road dust. The chemically characterized concentration data were subsequently fed into two receptor models viz. Principal Component Analysis-Multiple Linear Regression (PCA-MLR) and Chemical Mass Balance (CMB) for apportionment of sources of aerosol. The PCA-MLR estimates identified that the combustion sources together accounted for ∼42% of aerosol and the contribution of secondary formation to be 24%. Road and crustal dusts have been well apportioned by PCA-MLR, which together accounts for ∼26% of the aerosol. The CMB model estimates explained that the combustion sources taken together contributed ∼47% to the aerosol, which includes biomass burning (27%), vehicular emission (13%), coal (1%), kerosene (4%), and petroleum refining (2%). Other major sources that were apportioned were road dust (15%), crustal dust (26%), and construction dust (6%). There are inherent limitations in the source strength estimations because of uncertainty present in the source emission profiles that have been applied to the remote location of India. However, both the models (PCA-MLR and CMB) estimated the contribution of combustion sources to 42 and 47% respectively, which is comparable.

Groundwater is an essential public and drinking water supply and its protection is a goal for global policies. Here, we investigated the presence and prevalence of antibiotic residues, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and microbial contamination in groundwater environments at various distances from urban areas. Antibiotic concentrations ranged from below detection limit to 917 ng/L, being trimethoprim, macrolide, and sulfonamide the most abundant antibiotic classes. A total of eleven ARGs (aminoglycoside, β-lactam, chloramphenicol, Macrolide-Lincosamide-Streptogramin B - MLSB, sulfonamide, and tetracycline), one antiseptic resistance gene, and two MGEs were detected by qPCR with relative abundances ranging from 6.61 × 10−7 to 2.30 × 10−1 copies/16S rRNA gene copies. ARGs and MGEs were widespread in the investigated groundwater environments, with increased abundances not only in urban, but also in remote areas. Distinct bacterial community profiles were observed, with a higher prevalence of Betaproteobacteria and Bacteroidetes in the less-impacted areas, and that of Firmicutes in the contaminated groundwater. The combined characteristics of increased species diversity, distinct phylogenetic composition, and the possible presence of fecal and/or pathogenic bacteria could indicate different types of contamination. Significant correlations between ARGs, MGEs and specific taxa within the groundwater bacterial community were identified, revealing the potential hosts of resistance types. Although no universal marker gene could be determined, a co-selection of int1, qacEΔ1 and sulI genes, a proxy group for anthropogenic pollution, with the tetC, tetO, tetW resistance genes was identified. As the tet group was observed to follow the pattern of environmental contamination for the groundwater samples investigated in this study, our results strongly support the proposal of this group of genes as an environmental tracer of human impact. Overall, the present study investigated several emerging contaminants in groundwater habitats that may be included in monitoring programs to enable further regulatory and protection measures.

This study evaluated associations between the bioreactivity of PM2.5in vitro and emission sources in the vicinity of a petrochemical complex in Taiwan. The average PM2.5 was 30.2 μg/m3 from 9 February to 23 March 2016, and the PM2.5 was clustered in long-range transport (with major local source) (12.8 μg/m3), and major (17.3 μg/m3) and minor industrial emissions (4.7 μg/m3) using a k-means clustering model. A reduction in cell viability and increases in the cytotoxicity-related lactate dehydrogenase (LDH), oxidative stress-related 8-isoprostane, and inflammation-related interleukin (IL)-6 occurred due to PM2.5 in a dose-dependent manner. The PM2.5 from major industrial emissions was significantly correlated with increased 8-isoprostane and IL-6, but this was not observed for long-range transport or minor industrial emissions. The bulk metal concentration was 9.52 ng/m3 in PM2.5. We further observed that As, Ba, Cd, and Se were correlated with LDH in the long-range transport group. Pb in PM2.5 from the major industrial emissions was correlated with LDH, whereas Pb and Se were correlated with 8-isoprostane. Sr was correlated with cell viability in the minor industrial emissions group. We demonstrated a new approach to investigate particle bioreactivity, which suggested that petrochemical-emitted PM2.5 should be a concern for surrounding residents' health.

Information on exposure levels to organochlorine compounds (OCs) in child population is limited, despite their greater vulnerability to the adverse health effects of these chemicals.To determine serum concentrations of 10 OCs (including organochlorine pesticides and polychlorinated biphenyls –PCBs–) in children living in agricultural communities from Almería (South-Eastern Spain), and to identify the main predictors of exposure related to socio-economic characteristics, diet and lifestyle.A cross-sectional study was conducted on 133 children aged 6–11 years selected from public schools of the study area. OCs compounds were determined in serum samples by GC/ECD. Anthropometric measures were obtained during sample collection. Information on sociodemographic characteristics, parental occupation, residential history, lifestyle and frequency of food consumption, among other relevant factors, was obtained by questionnaires administered to the mothers.Geometric means of serum concentrations (ng/ml) were 0.11 for β-hexachloro-cyclohexane (β-HCH), 0.09 for endosulfan, 0.20 for endosulfan-ether, 0.51 for hexachorobenzene (HCB), 0.08 for mirex, 0.06 for oxychlordane, 0.36 for p,p'-DDE, 0.20 for PCB 138, 0.36 for PCB 153, and 0.45 for PCB 180. Percentage of samples above the limit of detection (0.05 ppb) ranged from 32 (β-HCH) to 100 (HCB). A high variability in OC levels depending on the compound was observed between our results and others found in similar studies carried out in children. Variables related to fish consumption were found to be the major dietary determinant of PCB 138, p,p´-DDE, endosulfan-α, β-HCH, mirex and oxychlordane levels.Children participating in this study showed detectable levels of many OC, despite these compounds are no longer used. Their presence in children serum can be explained by their high lipophilicity and environmental persistence, leading to contamination of fatty food. In this line, fish consumption seemed to be the most relevant determinant of OC levels found in our study.