Antibiotics enter into aquatic pond sediments by wastewater and could make detrimental effects on microbial communities. In this study, we examined the effects of sulfadimidine on nitrogen removal when added to experimental pond sediments. We found that sulfadimidine increased the number of sulfadimidine resistant bacteria and significantly increased the abundance of sul2 at the end of the incubation time (ANOVA test at Tukey HSD, P < 0.05). In addition, sulfadimidine decreased the N₂O reduction rate as well as the amount of nitrate reduction. Pearson correlation analysis revealed that the N₂O reduction rate was significantly and negatively correlated with narG (r = −0.679, P < 0.05). In contrast, we found a significant positive correlation between the amount of nitrate reduction and the abundance of narG (r = 0.609, P < 0.05) and nirK (r = 0.611, P < 0.05). High-throughput sequencing demonstrated that Actinobacteria, Euryarchaeota, Gemmatimonadetes, Nitrospirae, Burkholderiaceae (a family of Proteobacteria), and Thermoanaerobaculaceae (a family of Firmicutes) decreased with sulfadimidine exposure. In sediments, Actinobacteria, Bacteroidetes, Cyanobacteria, Epsilonbacteraeota, Euryarchaeota, Firmicutes, Gemmatimonadetes, and Spirochaetesat may play key roles in nitrogen transformation. Overall, the study exhibited a net effect of antibiotic exposure regarding nitrogen removal in an aquatic microcosm environment through a combination of biochemical pathways and molecular pathways, and draws attention to controlling antibiotic pollution in aquatic ecosystems.

The persistence and toxicity of second generation anticoagulant rodenticides (SGARs) in animal tissues make these compounds dangerous by biomagnification in predatory species. Here we studied the levels of SGARs in non-target species of wildlife and the environmental factors that influence such exposure. Liver samples of terrestrial vertebrates (n = 244) found dead between 2007 and 2016 in the region of Aragón (NE Spain) were analysed. The presence of SGARs was statistically analysed with binary or ordinal logistic models to study the effect of habitat characteristics including human population density, percentage of urban surface, livestock densities and surface of different types of crops. SGARs residues were detected in 83 (34%) of the animals and levels >200 ng/g were found in common raven (67%), red fox (50%), red kite (38%), Eurasian eagle-owl (25%), stone marten (23%), Eurasian buzzard (17%), northern marsh harrier (17%), and Eurasian badger (14%). The spatial analysis revealed that the presence of SGARs residues in wildlife was more associated with the use of these products as biocides in urban areas and cattle farms rather than as plant protection products in agricultural fields. This information permits to identify potential habitats where SGARs may pose a risk for predatory birds and mammals.

Secondary inorganic aerosols, including sulfate, nitrate, and ammonium contribute to a large extent to the severe haze pollution events in China. Understanding their formation mechanisms is critical for designing effective mitigation strategies to control haze pollution, especially as the role of nitrate seemed to become more important recently, especially in some megacities. In the present study, simultaneous observations were conducted in two megacities (Chengdu and Chongqing) in Sichuan Basin of southwest China, one of the regions suffering from severe aerosol pollution. One typical long-lasting pollution event in Chengdu and Chongqing was captured during wintertime from December 25, 2016 to January 5, 2017. The campaign-average of hourly concentrations of PM2.5, sulfate, and nitrate, measured by an Aerosol Analyzer (ZSF) were 101 ± 73.8 μg/m3, 15.9 ± 11.8 μg/m3, and 24.9 ± 20.6 μg/m3, respectively, in Chengdu, and were 87.7 ± 53.8 μg/m3, 19.7 ± 13.5 μg/m3, and 15.1 ± 10.1 μg/m3, respectively, in Chongqing. Nitrate contributed substantially to PM2.5 pollution when PM2.5 was lower than 150 μg/m3, largely due to the strong secondary transformation of NOX to nitrate during the occurrence of the pollution episode. Heterogeneous hydrolysis of N2O5 dominated nitrate formation during nighttime, while photochemical reactions and high-RH enhanced gas- to aqueous-phase dissolution of NH3 and HNO3 or cloud processes likely played important roles for nitrate formation during daytime. RH-dependent heterogeneous reactions contributed greatly to the formation of sulfate. NOX is confirmed to play an important role as an oxidant in accelerating the secondary transformation of SO2 to sulfate at high RH and low O3 levels under neutralization condition during heavy PM2.5 pollution episode. Results from this study identified the formation mechanism of nitrate, especially during the daytime, and addressed the importance of heterogeneous inorganic reactions in the formation of heavy aerosol pollution events.

Volunteer cleanup operations collect large datasets on anthropogenic litter that are seldom analyzed. Here we assess the influence of land use in both near-stream and watershed scale source domains on anthropogenic litter concentration (standing stock, kg km−1) in riparian zones of Iowa, USA. We utilized riparian litter concentration data on four classes of anthropogenic litter (metal, recyclable, garbage, and tires) from volunteer cleanup operations. Anthropogenic litter data were tested for correlation with near-stream and watershed scale land uses (developed, road density, agricultural, and open lands). Road density (road length/area) and developed land use (% area) were significantly correlated to anthropogenic litter, but agricultural (% area) and open lands (% area) were not. Metal objects correlated to near-stream road density (r = 0.79, p = 0.02), while garbage and recyclable materials correlated to watershed scale road density (r = 0.69, p = 0.06 and r = 0.71, p = 0.05 respectively). These differences in the important spatial scales of land use may be related to differences in transport characteristics of anthropogenic litter. Larger, denser metal objects may be transported more slowly through the watershed/channelized system and thus, dependent on more proximal sources, whereas smaller, less dense garbage and recyclable material are likely transported more rapidly, resulting in concentrations that depend more on watershed scale supply. We developed a linear regression model that used near-stream road density and the total amount of observed litter to predict an average anthropogenic litter density of 188 kg km−1 and a standing stock of 946 t in all Iowa streams (>4th Strahler order). The techniques employed in this study can be applied to other professional and volunteer litter datasets to develop prevention and cleanup efforts, inform investigations of process, and assess management actions.

Over 80,000 endocrine-disrupting chemicals (EDCs) are considered emerging contaminants (ECs), which are of great concern due to their effects on human health. Quantitative structure-activity relationship (QSAR) models are a promising alternative to in vitro methods to predict the toxicological effects of chemicals on human health. In this study, we assessed a deep-learning based QSAR (DL-QSAR) model to predict the qualitative and the quantitative effects of EDCs on the human endocrine system, and especially sex-hormone binding globulin (SHBG) and estrogen receptor (ER). Statistical analyses of the qualitative responses indicated that the accuracies of all three DL-QSAR methods were above 90%, and greater than the other statistical and machine learning models, indicating excellent classification performance. The quantitative analyses, as assessed using deep-neural-network-based QSAR (DNN-QSAR), resulted in a coefficient of determination (R²) of 0.80 and predictive square correlation coefficient (Q²) of 0.86, which implied satisfactory goodness of fit and predictive ability. Thus, DNN was able to transform sparse molecular descriptors into higher dimensional spaces, and was superior for assessment qualitative responses. Moreover, DNN-QSAR demonstrated excellent performance in the discipline of computational chemistry by handling multicollinearity and overfitting problems.

Emission from manufacturing facilities to the surrounding environment is one of the important input source of pollutants. However, no information on the levels of organophosphate esters (OPEs) contamination in the environmental media around the manufacturing facility is available to date. In this study, samples from various environmental media, including sediments, water, surface soils, and tree bark, were obtained near an OPE manufacturing plant in Hengshui, Hebei Province, North China. The three main congeners, detected were tris(2-chloroethyl) phosphate (TCEP), tris(2-chloroisopropyl) phosphate (TCIPP), and triphenyl phosphate (TPHP), with the summed OPE concentrations (∑OPEs) ranging from 340 to 270,000 μg kg⁻¹ dry weight (d.w.), 7100 to 33,000 ng L⁻¹, not detected (N.D.) to 14,000 ng kg⁻¹ d.w., and 5300 to 19,000 ng g⁻¹ lipid weight in the sediments, water, soils, and tree bark, respectively. These findings suggest that point sources of OPEs could have widespread effects on its surrounding environments. Sediment and water concentrations of TCEP and TCIPP measured in this study were among the highest concentrations yet reported in the world. Meanwhile, the concentration ranges of TCEP and TCIPP in surface soils were significantly lower than those in the sediment and water, and among the lowest concentrations yet reported in soil data worldwide. This suggests that the manufacturing facility influenced the OPE distribution in different environmental media in different ways. Furthermore, TCEP and TCIPP might have been transported within the water stream from roots into the aboveground plants and then accumulated in tree barks.

Despite high production and usage of parabens and bisphenols, little is known about their spatiotemporal distribution in the marine environment. In this study, we determined the concentrations of several parabens and their metabolites as well as bisphenol analogues in sediment collected from coastal areas of northern China. All sediment samples, including surface sediment and sediment cores, contained at least one of the parabens analyzed, and the total concentrations of parabens (ΣPBs; sum of six parabens) ranged from 1.37 to 24.2 ng/g dw (geometric mean: 3.30–6.09 g/g dw), which was comparable to or slightly higher than those found for the total concentrations of five detectable bisphenols (ΣBPAs; geometric mean: 2.18–4.61 ng/g dw). 4-hydroxybenzoic acid, a common metabolite of parabens, was found in all samples at concentrations in the range of 6.85–437 ng/g dw, which was one order of magnitude lower than those found for benzoic acid. Methyl-, ethyl-, and propyl-parabens were the predominant paraben analogues, collectively accounting for >88% of ΣPBs. Bisphenol A and bisphenol F were the two major bisphenols, collectively accounting for >86% of ΣBPAs. We also examined vertical profiles in concentrations of target analytes in sediment cores. The sediment core from the Shandong Peninsula showed a gradual increase in the concentrations of several parent and metabolic parabens as well as bisphenols during the past decade. Relatively higher concentrations of parabens and bisphenols were found in sediment cores collected from industrialized areas. Significant positive correlations were found among the concentrations of parabens in sediment, which suggested the existence of similar sources for these compounds. Overall, our findings suggest that the Bohai Sea coast is moderately contaminated with parabens and bisphenols in comparison to other coastal areas in China or elsewhere.

Biochar addition to soil may change the hydrophobicity of amended soil and influence soil hydraulic properties. Soil hydrophobicity, i.e. soil water repellency (SWR) can interrupt water infiltration and form preferential flow leading to a potential risk of soil erosion or groundwater pollution. Up to date, the effect of different biochars on soil hydrophobicity remains unclear and the association of SWR with soil hydraulic properties is still unknown. To link the biochar hydrophobicity to SWR and soil water holding capacity (WHC), the surface structure and chemical composition of 27 biochars with different feedstocks and pyrolysis temperatures were characterized, and the SWR and soil WHC of biochar-added soil were investigated. Carboxylic groups on the biochar surface, surface area and pore volume were mostly influenced by pyrolysis temperature, which suggested the dominant factor determining the severity of biochar hydrophobicity was pyrolysis temperature. Hydrophilic soil became hydrophobic after biochar amendment. A higher addition rate led to a stronger SWR of hydrophilic soil. Biochar addition increased soil WHC of hydrophilic soil with low total organic carbon (TOC) content. Biochar did not have significant influence on SWR and soil WHC of hydrophobic soil with high TOC content. It implied that the influence of biochar on SWR and soil hydraulic properties mainly depended on soil original hydrophobicity and TOC content. Therefore, the properties of biochar and influence on soil hydrophobicity and hydraulic properties should be considered before processing biochar application.

Global urbanisation has resulted in population densification, which is associated with increased air pollution, mainly from anthropogenic sources. One of the systems proposed to mitigate urban air pollution is urban forestry. This study quantified the spatial associations between concentrations of CO, NO₂, SO₂, and PM₁₀ and urban forestry, whilst correcting for anthropogenic sources and sinks, thus explicitly testing the hypothesis that urban forestry is spatially associated with reduced air pollution on a city scale. A Land Use Regression (LUR) model was constructed by combining air pollutant concentrations with environmental variables, such as land cover type and use, to develop predictive models for air pollutant concentrations. Traffic density and industrial air pollutant emissions were added to the model as covariables to permit testing of the main effects after correcting for these air pollutant sources. It was found that the concentrations of all air pollutants were negatively correlated with tree canopy cover and positively correlated with dwelling density, population density and traffic count. The LUR models enabled the establishment of a statistically significant spatial relationship between urban forestry and air pollution mitigation. These findings further demonstrate the spatial relationships between urban forestry and reduced air pollution on a city-wide scale, and could be of value in developing planning policies focused on urban greening.

Mesoporous nanocomposite of MgFe₂O₄ nanoparticles (NPs) and graphene oxide (GO) was synthesized using facile sonication method. Its potential was tested for the removal of Ni (II) and Pb (II) ions from water. The 2:1 w/w ratio of MgFe₂O₄:GO was optimum for the maximum removal of metal ions. Nanocomposite was characterized employing XRD, FT-IR, VSM, SEM-EDX, XPS, TEM and BET analyses. It possessed higher surface area (63.0 m² g⁻¹) than pristine NPs. Batch experiments were performed to study the effect of process parameters viz. pH, dose, contact time, initial metal ion concentration, co-existing ions and temperature. Statistical parameters were also determined. Langmuir, Temkin and Freundlich models were followed in perfect way. Langmuir model showed the monolayer adsorption of metal ions onto the homogeneous surface of nanocomposite with maximum adsorption capacity of 100.0 mg g⁻¹ and 143.0 mg g⁻¹ for Ni (II) and Pb (II) ions respectively, which was higher than the same for MgFe₂O₄ NPs and GO. Kinetic studies demonstrated that the pseudo-second order model well described the adsorption process. The ΔS° and ΔG° values revealed spontaneous nature of adsorption process. Positive ΔH° values using MgFe₂O₄ NPs and nanocomposite indicated endothermic removal; whereas using GO the removal was exothermic. The observed trend for coexisting ions correlated with hydrated ion radii. Efficiency of the adsorbents was also tested for realistic nickel electroplating industrial effluent. Apart from the higher adsorption potential of nanofabricated composite, its magnetic properties are advantageous in utilizing metal loaded nanocomposite for adsorption-desorption cycles for reuse.