Antibiotics usage in animal production is considered a primary driver of the occurrence, supply and spread of antibiotic resistance genes (ARGs) in the environment. Pig farms and fish ponds are important breeding systems in food animal production. In this study, we compared and analyzed broad ARGs profiles, mobile genetic elements (MGEs) and bacterial communities in a representative pig farm and neighboring fish ponds around Poyang Lake, the largest freshwater lake in China. The factors influencing the distribution of ARGs were also explored. The results showed widespread detection of ARGs (from 57 to 110) among 283 targeted ARGs in the collected water samples. The differences in the number and relative abundance of ARGs observed from the pig farm and neighboring fish ponds revealed that ARG contamination was more serious on the pig farm than in the fish ponds and that the water treatment plant on the pig farm was not very effective. Based on the variance partition analysis (VPA), MGEs, bacterial communities and water quality indicators (WIs) codrive the relative abundance of ARGs. Based on network analysis, we found that total phosphorus and Tp614 were the most important WIs and MGEs affecting ARG abundance, respectively. Our findings provide fundamental data on farms in lakeside districts and provide insights into establishing standards for the discharge of aquaculture wastewater.

Single-chemical thresholds cannot comprehensively evaluate the risk of chemical mixture exposure in indoor air. Moreover, a large number of researches have focused on short-term and high-concentration co-exposure scenarios related to different species, based on diverse endpoints, which hampers the application and improvement of existing risk evaluation models of chemical mixture exposures. More importantly, current risk evaluation models are not user-friendly for construction practitioners who do not have sufficient toxicological knowledge. Therefore, in this study, an inhalation experiment system and a hazard index (HI) were developed to investigate the risks associated with low-concentration and long-term inhalation exposure scenarios of formaldehyde and benzene, individually and combined, based on Drosophila melanogaster mortality. The results showed that the system exhibited good reproducibility in providing stable exposure concentrations during D. melanogaster life cycle. Furthermore, in a range of experimental concentrations, the interaction between formaldehyde and benzene was additive or synergistic, which was concentration- and ratio-dependent. This study is of great significance in harmonising and providing toxicity data under long-term and low-concentration exposure scenarios, which is beneficial for establishing a new user-friendly risk evaluation model for indoor chemical mixture exposures. It should be noted that the proposed HI value could indicate the hazard degrees of long-term inhalation exposures of formaldehyde and benzene, individually and combined, to D. melanogaster. However, the applicability of this index requires further experiments to evaluate the exposure risks of other volatile organic compounds (VOCs) to D. melanogaster.

Soil contamination by potentially toxic elements (PTEs) is one of the greatest threats to environmental degradation. Knowing where PTEs accumulated in soil can mitigate their adverse effects on plants, animals, and human health. We evaluated the potential of using long-term remote sensing images that reveal the bare soils, to detect and map PTEs in agricultural fields. In this study, 360 soil samples were collected at the superficial layer (0–20 cm) in a 2574 km² agricultural area located in São Paulo State, Brazil. We tested the Soil Synthetic Image (SYSI) using Landsat TM/ETM/ETM+, Landsat OLI, and Sentinel 2 images. The three products have different spectral, temporal, and spatial resolutions. The time series multispectral images were used to reveal areas with bare soil and their spectra were used as predictors of soil chromium, iron, nickel, and zinc contents. We observed a strong linear relationship (−0.26 > r > −0.62) between the selected PTEs and the near infrared (NIR) and shortwave infrared (SWIR) bands of Sentinel (ensemble of 4 years of data), Landsat TM (35 years data), and Landsat OLI (4 years data). The clearest discrimination of soil PTEs was obtained from SYSI using a long term Landsat 5 collection over 35 years. Satellite data could efficiently detect the contents of PTEs in soils due to their relation with soil attributes and parent materials. Therefore, distinct satellite sensors could map the PTEs on tropics and assist in understanding their spatial dynamics and environmental effects.

Evidence suggests that the invasion of Spartina alterniflora (S. alterniflora) poses potentially serious risks to the stability of coastal wetlands, an ecosystem that is extremely vulnerable to both biological and non-biological threats. However, the effects and mechanisms of sulfur (S) in mediating the growth and expansion of S. alterniflora are poorly understood, particularly when sediments are contaminated with cadmium (Cd). A 6-month greenhouse study was conducted to evaluate the mediating effect of S on Cd tolerance and growth of S. alterniflora. Treatments consisted of a factorial combination of three S rates (applied as Na₂SO₄; 0, 500, 1000 mg kg⁻¹ dry weight (DW), as S₀, S₅₀₀, and S₁₀₀₀) and four Cd rates (applied as CdCl₂; 0, 1, 2, 4 mg kg⁻¹ DW, as Cd₀, Cd₁, Cd₂, and Cd₄). Results showed that although the exogenous S supply obviously increased Cd accumulation in roots (up to 71.22 ± 6.43 mg kg⁻¹ DW) due to the decrease of Fe concentration in iron plaque (down to 4.02 ± 1.18 mg g⁻¹ DW), biomass reduction and oxidative stress in plant tissues were significantly alleviated. The addition of S significantly up-regulated the concentration of compounds related to Cd tolerance, including proline and glutathione. Therefore, the translocation of Cd was restricted, and plant growth was not impacted. The present study demonstrated that the exogenous sulfur supply could promote the growth of S. alterniflora and enhance its tolerance to Cd. Therefore, under the effects of S. alterniflora, the increased fluctuations of S pool caused by the release and deposition of S might further exacerbate S. alterniflora expansion in Cd contaminated coastal wetlands.

Synthetic microfibers have been identified as the most prevalent type of microplastic in samples from aquatic, atmospheric, and terrestrial environments across the globe. Apparel washing has shown to be a major source of microfiber pollution. We used California as a case study to estimate the magnitude and fate of microfiber emissions, and to evaluate potential mitigation approaches. First, we quantified synthetic microfiber emissions and fate from apparel washing in California by developing a material flow model which connects California-specific data on synthetic fiber consumption, apparel washing, microfiber generation, and wastewater and biosolid management practices. Next, we used the model to assess the effectiveness of different interventions to reduce microfiber emissions to natural environments. We estimate that in 2019 as much as 2.2 kilotons (kt) of synthetic microfibers were generated by apparel washing in California, a 26% increase since 2008. The majority entered terrestrial environments (1.6 kt), followed by landfills (0.4 kt), waterbodies (0.1 kt), and incineration (0.1 kt). California's wastewater treatment network was estimated to divert 95% of microfibers from waterbodies, mainly to terrestrial environments and primarily via land application of biosolids. Our analysis also reveals that application of biosolids on agricultural lands facilitates a directional flow of microfibers from higher-income urban counties to lower-income rural communities. Without interventions, annual synthetic microfiber emissions to California's natural environments are expected to increase by 17% to 2.1 kt by 2026. Further increasing the microfiber retention efficiency at the wastewater treatment plant would increase emissions to terrestrial environments, which suggests that microfibers should be removed before entering the wastewater system. In our model, full adoption of in-line filters in washing machines decreased annual synthetic microfiber emissions to natural environments by 79% to 0.5 kt and offered the largest reduction of all modeled scenarios.

Per-and polyfluoroalkyl substances (PFASs) have attracted extensive attention since this century due to their wide distribution, persistence, bioaccumulation/biomagnification potential, and (eco)toxicity. In the present study, we investigated the sorption kinetics, sorption isotherms and desorption behaviors of legacy and emerging PFASs with different chain lengths and functional end groups onto marine sediments at four different salinities (0, 10, 20, and 30 practical salinity units (psu)). Results revealed that the sorption of PFASs onto sediment can be well described by the pseudo-second-order kinetic model. PFASs sorption was influenced by both compound-specific and solution-specific parameters. The distribution coefficient (Kd) for PFASs were increased with the increase of perfluorocarbon chain length and salinity, suggesting that hydrophobic and electrostatic interactions were involved in the adsorption process. 6:2 FTSA showed the lowest adsorption among PFASs with eight carbon atoms (6:2 FTSA, PFOA and PFOS). The increase of perfluorocarbon chain length of PFASs and salinity would result in the decrease of desorption rate of PFASs from sediment. In addition, PFCAs were desorbed more easily from the sediment than the PFSAs with the same perfluorocarbon chain length at all salinity groups. The present study demonstrated that salinity can apparently influence the fate of PFASs in aquatic environment and provided valuable data for modeling the fate of PFASs in real environment.

With the rapid development of nanotechnology in agriculture, there is increasing urgency to assess the impacts of nanoparticles (NPs) on the soil environment. This study merged raw high-throughput sequencing (HTS) data sets generated from 365 soil samples to reveal the potential ecological effects of NPs on soil microbial community by means of metadata analysis and machine learning methods. Metadata analysis showed that treatment with nanoparticles did not have a significant impact on the alpha diversity of the microbial community, but significantly altered the beta diversity. Unfortunately, the abundance of several beneficial bacteria, such as Dyella, Methylophilus, Streptomyces, which promote the growth of plants, and improve pathogenic resistance, was reduced under the addition of synthetic nanoparticles. Furthermore, metadata demonstrated that nanoparticles treatment weakened the biosynthesis ability of cofactors, carriers, and vitamins, and enhanced the degradation ability of aromatic compounds, amino acids, etc. This is unfavorable for the performance of soil functions. Besides the soil heterogeneity, machine learning uncovered that a) the exposure time of nanoparticles was the most important factor to reshape the soil microbial community, and b) long-term exposure decreased the diversity of microbial community and the abundance of beneficial bacteria. This study is the first to use a machine learning model and metadata analysis to investigate the relationship between the properties of nanoparticles and the hazards to the soil microbial community from a macro perspective. This guides the rational use of nanoparticles for which the impacts on soil microbiota are minimized.

Mine waste classification preceding mining constitutes a proactive solution to classify and segregate mine waste into geo-environmental domains based upon the magnitude of their environmental risks. However, upstream classification requires multi-disciplinary and integrated approaches. This study integrates geological modeling and kinetic modeling to inform upstream mine waste classification based on the pH generated from the main acid-generating and acid-neutralizing reactions once the mine solid waste is stored in oxidizing conditions. Geological models were used to depict the ante-mining spatial distribution of the main reactive minerals: pyrite, albite and calcite. Subsequently, the corresponding block models were created. The dimension of the elementary voxels for each block model was set at 40х40х40 m for this study. The kinetic modeling approach was performed using PHREEQC and VS2DRTI to consider unsaturated conditions. The kinetic modeling simulated a 1D column for each voxel. The column simulates the excavated state of the hosting rock involving kinetic reactions and unsaturated flow under highly oxidizing conditions. Subsequently, the resulting pH for different intervals of time was assigned to its respective voxel. The outcome consists of a spatio-temporal visualization of the pH defining ante-mining geo-environmental domains, thereby providing the opportunity for formulating proactive management measures regarding the hazardous geo-environmental domains.

In recent years, the cardiovascular toxicity of urban fine particulate matter (PM₂.₅) has sparked significant alarm. Mitochondria produce 90% of ATP and make up 30% of the volume of cardiomyocytes. Thus knowledge of myocardial mitochondrial dysfunction due to PM₂.₅ exposure is essential for further cardiotoxic effects. Here, the mechanism of PM₂.₅-induced cardiac hypertrophy through calcium overload and mitochondrial dysfunction was investigated in vivo and in vitro. Male and female BALB/c mice were given 1.28, 5.5, and 11 mg PM₂.₅/kg bodyweight weekly through oropharyngeal inhalation for four weeks and were assigned to low, medium, and high dose groups, respectively. PM₂.₅-induced myocardial edema and cardiac hypertrophy were detected in the high-dose group. Mitochondria were scattered and ruptured with abnormal ultrastructural morphology. In vitro experiments on human cardiomyocyte AC16 showed that exposure to PM₂.₅ for 24 h caused opened mitochondrial permeability transition pore --leading to excessive calcium production, decreased mitochondrial membrane potential, weakened mitochondrial respiratory metabolism capacity, and decreased ATP production. Nevertheless, the administration of calcium chelator ameliorated the mitochondrial damage in the PM₂.₅-treated group. Our in vivo and in vitro results confirmed that calcium overload under PM₂.₅ exposure triggered mTOR/AKT/GSK-3β activation, leading to mitochondrial bioenergetics dysfunction and cardiac hypertrophy.

Exposure to tobacco smoke during pregnancy has been associated with a series of adverse reproductive outcomes; however, the underlying molecular mechanisms are not well-established. We conducted an untargeted metabolome-wide association study to identify the metabolic perturbations and molecular mechanisms underlying the association between cotinine, a widely used biomarker of tobacco exposure, and adverse birth outcomes. We collected early and late pregnancy urine samples for cotinine measurement and serum samples for high-resolution metabolomics (HRM) profiling from 105 pregnant women from the Atlanta African American Maternal-Child cohort (2014–2016). Maternal metabolome perturbations mediating prenatal tobacco smoke exposure and adverse birth outcomes were assessed by an untargeted HRM workflow using generalized linear models, followed by pathway enrichment analysis and chemical annotation, with a meet-in-the-middle approach. The median maternal urinary cotinine concentrations were 5.93 μg/g creatinine and 3.69 μg/g creatinine in early and late pregnancy, respectively. In total, 16,481 and 13,043 metabolic features were identified in serum samples at each visit from positive and negative electrospray ionization modes, respectively. Twelve metabolic pathways were found to be associated with both cotinine concentrations and adverse birth outcomes during early and late pregnancy, including tryptophan, histidine, urea cycle, arginine, and proline metabolism. We confirmed 47 metabolites associated with cotinine levels, preterm birth, and shorter gestational age, including glutamate, serine, choline, and taurine, which are closely involved in endogenous inflammation, vascular reactivity, and lipid peroxidation processes. The metabolic perturbations associated with cotinine levels were related to inflammation, oxidative stress, placental vascularization, and insulin action, which could contribute to shorter gestations. The findings will support the further understanding of potential internal responses in association with tobacco smoke exposures, especially among African American women who are disproportionately exposed to high tobacco smoke and experience higher rates of adverse birth outcomes.