The wide usage of hexachlorocyclohexanes (HCHs) as pesticides has caused soil pollution and adverse health effects through direct contact or bioaccumulation in the food chain. This study quantified major HCH isomers in farmland topsoils across China, and evaluated their correlations with microbial community structure, function, and abiotic variables (e.g., moisture, pH, and temperature). Recalcitrant β-HCH was more abundant than α-, γ-, and δ-HCHs, and α-HCH enantiomeric fractions (EF) were larger than 0.5, indicating preferential degradation of (−)-α-HCH. Sphingomonas was not only a predominant population (especially in samples collected in the south), but also a promising biomarker indicating total- and β-HCH residuals, and EF values of α-HCH. Soil moisture and temperature were among the most influential factors that structured the diversity and function of soil microbial communities. The results suggested that increasing soil moisture (in the range of 5–45%) would benefit the growth of HCH-degrading populations and the enrichment of HCH-degradation related pathways. Revealing the site-specific relationships between topsoil physical, chemical, and microbial properties will benefit the in situ bioremediation of farmlands with relatively low HCH residuals across the world.

Environmental pollution, local climatic conditions and their association with the prevalence and exacerbation of asthma are topics of intense current medical investigation.Air pollution in the area of Vladivostock was estimated both by the index of emission volumes of "air gaseous components" (nitrogen oxide and nitrogen dioxide, formaldehyde, hydrogen sulfide, carbon monoxide) in urban atmosphere and by mass spectrometric analysis of precipitates in snow samples. A total of 172 local asthma patients (101 controlled-asthma patients–CAP and 71 non-controlled asthma patients – nCAP) were evaluated with the use of spirometry and body plethysmography. Airway obstruction reversibility was evaluated with the use of an inhaled bronchodilator. Using discriminant analysis the association of environmental parameters with clinical indices of asthma patients is explored and thresholds of impact are established.CAP presented high sensitivity to large-size suspended air particles and to several of the studied climatic parameters. Discriminant analysis showed high values of Wilks’ lambda index (α = 0.69–0.81), which implies limited influence of environmental factors on the respiratory parameters of CAP. nCAP were more sensitive and susceptible to the majority of the environmental factors studied, including air suspended toxic metals particles (Cr, Zn and Ni). Air suspended particles showed higher tendency for pathogenicity in nCAP population than in the CAP, with a wider range of particle sizes being involved. Dust fractions ranging from 0 to 1 μm and from 50 to 100 μm were additionally implicated compared to CAP group. Considerably lowest thresholds levels of impact are calculated for nCAP.

The combined pollution of radionuclides and heavy metals has been given rise to widespread concern during uranium mining. The influence of As(V) on U(VI) immobilization by Mucor circinelloides (M. circinelloides) was investigated using batch experiments. The activity of antioxidative enzymes and concentrations of thiol compounds and organic acid in M. circinelloides increased to respond to different U(VI) and As(V) stress. The morphological structure of M. circinelloides changed obviously under U(VI) and As(V) stress by SEM and TEM analysis. The results of XANES and EXAFS analysis showed that U(VI) was mainly reduced to nano-uraninite (nano-UO2, 30.1%) in U400, while only 9.7% of nano-UO2 was observed in the presence of As(V) in U400-As400 due to the formation of uranyl arsenate precipitate (Trögerite, 48.6%). These observations will provide the fundamental data for fungal remediation of uranium and heavy metals in uranium-contaminated soils.

Simultaneous aggregation and retention of nanoparticles can occur during their transport in porous media. In this work, the concurrent aggregation and transport of GO in saturated porous media were investigated under the conditions of different combinations of temperature, cation type (valence), and electrolyte concentration. Increasing temperature (6–24 °C) at a relatively high electrolyte concentration (i.e., 50 mM for Na⁺, 1 mM for Ca²⁺, 1.75 mM for Mg²⁺, and 0.03 and 0.05 mM for Al³⁺) resulted in enhanced GO retention in the porous media. For instance, when the temperature increased from 6 to 24 °C, GO recovery rate decreased from 31.08% to 6.53% for 0.03 mM Al³⁺ and from 27.11% to 0 for 0.05 mM Al³⁺. At the same temperature, increasing cation valence and electrolyte concentration also promoted GO retention. Although GO aggregation occurred in the electrolytes during the transport, the deposition mechanisms of GO retention in the media depended on cation type (valence). For 50 mM Na⁺, surface deposition via secondary minima was the dominant GO retention mechanism. For multivalent cation electrolytes, GO aggregation was rapid and thus other mechanisms such as physical straining and sedimentation also played important roles in controlling GO retention in the media. After passing through the columns, the GO particles in the effluents showed better stability with lower initial aggregation rates. This was probably because less stable GO particles with lower surface charge densities in the porewater were filtered by the porous media, resulting in more stable GO particle with higher surface charge densities in the effluents. An advection–dispersion-reaction model was applied to simulate GO breakthrough curves and the simulations matched all the experimental data well.

Studies differentiating the cardiorespiratory morbidity effects of PM₂.₅, PM₁₀, and PM₂.₅∼₁₀ (i.e. coarse PM or PMc) are still limited and inconsistent.To estimate the acute, cumulative, and harvesting effects of exposure to the three size-specific PM on cardiorespiratory morbidity, and their concentration-response relations.A total of 6,727,439 emergency department (ED) visits were collected from 16 public teaching hospitals in Guangzhou, from January 1st 2012 to December 31st 2015, among which over 2.1 million were asthma, COPD, pneumonia, respiratory tract infection (RTI), hypertension, stroke, and coronary heart disease (CHD). Distributed lag non-linear models (DLNM) was used to estimate the associations between the three size-specific PM and ED visits for the cardiovascular diseases. Long-term trends, seasonality, influenza epidemics, meteorological factors, and other gas pollutants, including SO2, NO₂, and O₃, were adjusted. We stratified the analyses by gender and age.Elevated PM₂.₅ and PM₁₀ were significantly associated with increased ED visits for pneumonia, RTI, and CHD at both lag₀ and lag₀₋₃. A 10 μg/m³ increment of PMc (at lag₀₋₁₄) was estimated to increase ED visits for pneumonia by 6.32% (95% CI, 4.19, 8.49) and for RTI by 4.72% (95% CI, 3.81, 5.63), respectively. PMc showed stronger cumulative effects on asthma in children than elderly. We observed significant harvesting effects (i.e. morbidity displacements) of the three size-specific PM on respiratory but very little on cardiovascular ED visits. The concentration-response curves suggested non-linear relations between exposures to the three different sizes of PM and respiratory morbidity.Overall, the three size-specific PM demonstrated distinct acute and cumulative effects on the cardiorespiratory diseases. PM₂.₅ and PMc would have significant effects on pneumonia and RTI. Strategies should be considered to further reduce levels of ambient PM₂.₅ and PMc.

Magnetic biochar (MBC) has been used to remove hexavalent chromium (Cr(VI)) from water, but the roles of Fe₃O₄ and persistent free radicals (PFRs) in MBC in Cr(VI) removal are still less investigated. In this work, the MBC synthesized by microwave co-pyrolysis of solid-state FeSO₄ and rice husk was employed to remove Cr(VI) from water. In comparison to the rice husk biochar (BC), the MBC exhibits the 3.2- and 11.7-fold higher adsorption and reduction efficiency of Cr(VI), resulting in the higher Cr(VI) removal efficiency (84.3%) and equilibrium adsorption capacity of MBC (8.35 mg g⁻¹) than that (26.5% and 2.63 mg g⁻¹) of BC. Multiple characterization results revealed that the high Cr(VI) removal performance of MBC was mainly attributed to the presence of active Fe₃O₄ and carbon-centered PFRs in the porous and graphitic MBC. The Fe₃O₄ not only provided active chemisorption/reduction sites for Cr(VI) via its Fe(II)ₒcₜ and Fe(III)ₒcₜ coordination, but also facilitated the generation of more active electron donating carbon-centered PFRs than carbon-centered PFRs with an oxygen atom in the graphitic structure to reduce Cr(VI). The presence of Fe₃O₄ also elevated 36.7 m² g⁻¹ of BET-surface area and 0.043 cm² g⁻¹ of pore volume of MBC, promoting the Cr(VI) removal. The Fe₃O₄ and carbon-centered PFRs contributed to ∼81.8% and ∼18.2% of total Cr(III) generation, respectively. In addition, the initial solution pH was responsible for determining the relative significance of Cr(VI) adsorption and reduction. This study provides new insights into the mechanisms of Cr(VI) removal from water by the MBC.

In order to clarify whether the mitochondrial dysfunction is closely related to the cell homeostasis maintenance after particulate matter (PM₂.₅) exposure, oxidative, inflammatory, apoptotic and mitochondrial endpoints were carefully studied in human bronchial epithelial BEAS-2B, normal human bronchial epithelial (NHBE) and chronic obstructive pulmonary disease (COPD)-diseased human bronchial epithelial (DHBE) cells acutely or repeatedly exposed to air pollution-derived PM₂.₅. Some modifications of the mitochondrial morphology were observed within all these cell models repeatedly exposed to the highest dose of PM₂.₅. Dose- and exposure-dependent oxidative damages were reported in BEAS-2B, NHBE and particularly COPD-DHBE cells acutely or repeatedly exposed to PM₂.₅. Nuclear factor erythroid 2-p45 related factor 2 (NRF2) gene expression and binding activity, together with the mRNA levels of some NRF2 target genes, were directly related to the number of exposures for the lowest PM₂.₅ dose (i.e., 2 μg/cm²), but, surprisingly, inversely related to the number of exposures for the highest dose (i.e., 10 μg/cm²). There were dose- and exposure-dependent increases of both nuclear factor kappa-B (NF-κB) binding activity and NF-κB target cytokine secretion in BEAS-2B, NHBE and particularly COPD-DHBE cells exposed to PM₂.₅. Mitochondrial ROS production, membrane potential depolarization, oxidative phosphorylation, and ATP production were significantly altered in all the cell models repeatedly exposed to the highest dose of PM₂.₅. Collectively, our results indicate a cytosolic ROS overproduction, inducing oxidative damage and activating oxygen sensitive NRF2 and NF-ₖB signaling pathways for all the cell models acutely or repeatedly exposed to PM₂.₅. However, one of the important highlight of our findings is that the prolonged and repeated exposure in BEAS-2B, NHBE and in particular sensible COPD-DHBE cells further caused an oxidative boost able to partially inactivate the NRF2 signaling pathway and to critically impair mitochondrial redox homeostasis, thereby producing a persistent mitochondrial dysfunction and a lowering cell energy supply.

In this paper, results from receptor modelling performed on a well-characterised PM₁ dataset were combined to chemical light extinction data (bₑₓₜ) with the aim of assessing the impact of different PM₁ components and sources on light extinction and visibility at a European polluted urban area. It is noteworthy that, at the state of the art, there are still very few papers estimating the impact of different emission sources on light extinction as we present here, although being among the major environmental challenges at many polluted areas. Following the concept of the well-known IMPROVE algorithm, here a tailored site-specific approach (recently developed by our group) was applied to assess chemical light extinction due to PM₁ components and major sources.PM₁ samples collected separately during daytime and nighttime at the urban area of Milan (Italy) were chemically characterised for elements, major ions, elemental and organic carbon, and levoglucosan. Chemical light extinction was estimated and results showed that at the investigated urban site it is heavily impacted by ammonium nitrate and organic matter. Receptor modelling (i.e. Positive Matrix Factorization, EPA-PMF 5.0) was effective to obtain source apportionment; the most reliable solution was found with 7 factors which were tentatively assigned to nitrates, sulphates, wood burning, traffic, industry, fine dust, and a Pb-rich source. The apportionment of aerosol light extinction (bₑₓₜ,ₐₑᵣ) according to resolved sources showed that considering all samples together nitrate contributed at most (on average 41.6%), followed by sulphate, traffic, and wood burning accounting for 18.3%, 17.8% and 12.4%, respectively.

Pesticides move to surface water via various pathways including surface runoff, spray drift and subsurface flow. Little is known about the relative contributions of surface runoff and spray drift in agricultural watersheds. This study develops a modeling framework to address the contribution of spray drift to the total loadings of pesticides in receiving water bodies. The modeling framework consists of a GIS module for identifying drift potential, the AgDRIFT model for simulating spray drift, and the Soil and Water Assessment Tool (SWAT) for simulating various hydrological and landscape processes including surface runoff and transport of pesticides. The modeling framework was applied on the Orestimba Creek Watershed, California. Monitoring data collected from daily samples were used for model evaluation. Pesticide mass deposition on the Orestimba Creek ranged from 0.08 to 6.09% of applied mass. Monitoring data suggests that surface runoff was the major pathway for pesticide entering water bodies, accounting for 76% of the annual loading; the rest 24% from spray drift. The results from the modeling framework showed 81 and 19%, respectively, for runoff and spray drift. Spray drift contributed over half of the mass loading during summer months. The slightly lower spray drift contribution as predicted by the modeling framework was mainly due to SWAT's under-prediction of pesticide mass loading during summer and over-prediction of the loading during winter. Although model simulations were associated with various sources of uncertainties, the overall performance of the modeling framework was satisfactory as evaluated by multiple statistics: for simulation of daily flow, the Nash-Sutcliffe Efficiency Coefficient (NSE) ranged from 0.61 to 0.74 and the percent bias (PBIAS) < 28%; for daily pesticide loading, NSE = 0.18 and PBIAS = −1.6%. This modeling framework will be useful for assessing the relative exposure from pesticides related to spray drift and runoff in receiving waters and the design of management practices for mitigating pesticide exposure within a watershed.

To evaluate the seasonal distribution of antibiotic resistance genes (ARGs) and explore the reason for their patterns in different seasons and different systems, two wastewater treatment systems were selected and analyzed using high-throughput qPCR. Linear discriminant analysis (LDA) effect size (LEfSe) was used to discover the differential ARGs (biomarkers) and estimate the biomarkers’ effect size. We found that the total absolute abundances of ARGs in inflows and excess sludge samples had no obvious seasonal fluctuations, while those in winter outflow samples decreased in comparison with the inflow samples. Eleven differentially abundant ARGs (biomarker genes, BmGs) (aadA5-02, aac-6-II, cmlA1-01, cmlA1-02, blaOXA10-02, aadA-02, tetX, aadA1, ereA, qacEΔ1-01, and blaTEM) in summer samples and 10 BmGs (tet-32, tetA-02, aacC2, vanC-03, aac-6-I1, tetE, ermB, mefA, tnpA - 07, and sul2) in winter samples were validated. According to 16S rRNA gene sequencing, the relative abundance of bacteria at the phylum level exhibited significant seasonal changes in outflow water (OW), and biomarker bacteria (BmB) were discovered at the family (or genus) level. Synechococcus and vadinCA02 are BmB in summer, and Trichococcus, Lactococcus, Pelosinus, Janthinobacterium, Nitrosomonadaceae and Sterolibacterium are BmB in winter. In addition, BmB have good correlations with BmGs in the same season, which indicates that bacterial community changes drive different distributions of ARGs during seasonal changes and that LEfSe is an acute and effective method for finding significantly different ARGs and bacteria between two or more classes.In conclusion, this study demonstrated the seasonal changes of BmGs and BmB at two wastewater treatment systems.