Dairy cattle of different ages experience different living conditions and varied frequency of antibiotic administration that likely influence the distribution of microbiome and resistome in ways that reflect different risks of microbial transmission. To assess the degree of variance in these distributions, fecal and soil samples were collected from six distinct housing areas on commercial dairy farms (n = 7) in Washington State. 16S rRNA gene sequencing indicated that the microbiota differed between different on-farm locations in feces and soil, and in both cases, the microbiota of dairy calves was often distinct from others (P < 0.05). Thirty-two specific antibiotic resistance genes (ARGs) were widely distributed on dairies, of which several clinically relevant ARGs (including cfr, cfrB, and optrA) were identified for the first time at U.S. dairies. Overall, ARGs were observed more frequently in feces and soil from dairy calves and heifers than from hospital, fresh, lactation and dry pens. Droplet-digital PCR demonstrated that the absolute abundance of floR varied greatly across housing areas and this gene was enriched the most in calves and heifers. Furthermore, in an extended analysis with 14 dairies, environmental soils in calf pens had the most antibiotic-resistant Escherichia coli followed by heifer and hospital pens. All soil E. coli isolates (n = 1,905) are resistant to at least 4 different antibiotics, and the PFGE analysis indicated that florfenicol-resistant E. coli is probably shared across geographically-separated farms. This study identified a discrete but predictable distribution of antibiotic resistance genes and organisms, which is important for designing mitigation for higher risk areas on dairy farms.

The continued increase in the global demand for oil, which reached 4,488 Mtoe in 2018, leads to large quantities of petroleum products entering the environment posing serious risks to natural ecosystems if left untreated. In this study, we evaluated the impact of co-contamination with lead on the efficacy of two bioremediation processes, natural attenuation and biostimulation of Total Petroleum Hydrocarbons (TPH) as well as the associated toxicity and the changes in the microbial community in contaminated soils. The biostimulated treatment resulted in 96% and 84% reduction in TPH concentration in a single and a co-contamination scenario, respectively, over 28 weeks of a mesocosm study. This reduction was significantly more in comparison to natural attenuation in a single and a co-contamination scenario, which was 56% and 59% respectively. In contrast, a significantly greater reduction in the associated toxicity of in soils undergoing natural attenuation was evident compared with soils undergoing biostimulation despite the lower TPH degradation when bioassays were applied. The earthworm toxicity test showed a decrease of 72% in the naturally attenuated toxicity versus only 62% in the biostimulated treatment of a single contamination scenario. In a co-contamination scenario, toxicity decreased only 30% and 8% after natural attenuation and biostimulation treatments, respectively. 16s rDNA sequence analysis was used to assess the impact of both the co-contamination and the bioremediation treatment. NGS data revealed major bacterial domination by Nocardioides spp., which reached 40% in week 20 of the natural attenuation treatment. In the biostimulated soil samples, more than 50% of the bacterial community was dominated by Alcanivorax spp. in week 12. The presence of Pb in the natural attenuation treatment resulted in an increased abundance of a few Pb-resistant genera such as Sphingopyxis spp. and Thermomonas spp in addition to Nocardioides spp. In contrast, Pb co-contamination completely shifted the bacterial pattern in the stimulated treatment with Pseudomonas spp. comprising approximately 45% of the bacterial profile in week 12. This study confirms the effectiveness of biostimulation over natural attenuation in remediating TPH and TPH-Pb contaminated soils. In addition, the presence of co-contaminants (e.g. Pb) results in serious impacts on the efficacy of bioremediation of TPH in contaminated soils, which must be considered prior to designing any bioremediation strategy.

Microbial diversity in machine oil contaminated soil was determined by high-throughput amplicon sequencing technology. The diversity of culturable microbes in the contaminated soil was further characterized using polymerase chain reaction method. Proteobacteria and Bacteroidetes were the most dominant phyla and occupied 52.73 and 16.77%, respectively, while the most abundant genera were Methylotenera (21.62%) and Flavobacterium (3.06%) in the soil. In the culturable microbes, the major phyla were Firmicutes (46.15%) and Proteobacteria (37.36%) and the most abundant genera were Bacillus (42.86%) and Aeromonas (34.07%). Four isolated microbes with high machine oil degradation efficiency were selected to evaluate their characteristics on the oil degradation. All of them reached their highest oil degradation rate after 7 days of incubation. Most of them significantly increased their oil degradation rate by additional carbon or organic nitrogen source in the incubation medium. The oil degradation rate by combination of the four microbes at the same level was also higher than the rate from each individual microbe. The protocol and findings of this study are very useful for developing micro-bioremediation method to eliminate machine oil contaminants from soil.

Silver nanoparticles (AgNPs) in aquatic ecosystems are toxic to aquatic organisms. In this study, we aimed to investigate the toxicities and molecular mechanisms of AgNPs with different surface coatings (sodium citrate and polyvinylpyrrolidone) and particle sizes (20 nm and 100 nm) in the gills, intestines, and muscles of zebrafish after 96 h of exposure. Our results indicated that the contribution of particle size to AgNP toxicity was greater than that of the surface coating. Citrate-coated AgNPs were more toxic than polyvinylpyrrolidone-coated AgNPs, and 20-nm AgNPs were more toxic than 100-nm AgNPs. The toxic effects of AgNPs to the tissues were in the order intestines > gills > muscles. Differential expression of genes with the different AgNPs confirmed that they had toxic effects in the zebrafish tissues at the molecular level. Our comprehensive comparison of the toxicities of different AgNPs to aquatic ecosystems will be helpful for further risk assessments of AgNPs.

This work aimed to determine the concentrations of parabens and triclosan (TCS) in shellfish from coastal waters of Shenzhen, South China. A method of isotope dilution with high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was used to determine TCS and five paraben analogues, including methyl paraben (MeP), ethyl paraben (EtP), propyl paraben (PrP), butyl paraben (BuP), and benzyl paraben (BeP), in 186 shellfish samples covering eight species. Concentrations of parabens and TCS were 0.13–25.5 ng/g wet weight (ww) and <LOQ–6.51 ng/g ww, respectively, indicating their ubiquitous contamination in Shenzhen coastal waters. MeP was the most predominant paraben, followed by EtP and PrP. These three analogues accounted for more than 95% of the total concentrations of parabens. The “high” estimated daily intakes of parabens and TCS with the 95th percentage concentrations were estimated to be 2.15–26.1 and 0.41–10.3 ng/kg bw/day, respectively, much lower than the acceptable dietary intakes of parabens (1 × 10⁷ ng/kg bw/day) and TCS (200 ng/kg bw/day), indicating no significant human health risks from shellfish consumption in the studied region. To our knowledge, this is the first report on the occurrences of parabens and TCS in shellfish products from Shenzhen coastal waters.

Phytochelatins (PCs) play a vital role in the tolerance and enrichment of cadmium (Cd) in higher plants by chelating with Cd2+. The aim of this study was to perform a full-scale metabolomics analysis of metabolic responses highly correlated with PCs generation. These metabolites and metabolic pathways were expected to promote PCs generation and further optimize Cd absorption in plants. In the current study, Amaranthus hypochondriacus, a potential species for phytoremediation, was first adopted to investigate physiological responses to Cd stress via LCMS/MS-based metabolomics and the HPLC based determination of thiol compounds. The results showed that the leaves of A. hypochondriacus under high Cd stress accumulated 40 times the amount of Cd compared to the leaves of the plants not under Cd stress and had an increased content of three types of PCs. Metabolomics qualitatively identified 12084 substances in total, among which 41 were significantly different metabolites (SDMs) between the two groups and involved in 7 metabolic pathways. Among the SDMs, 12 metabolites were highly linearly correlated with PCs involved in three pathways (Val, Leu and Ile biosynthesis; Ala, Asp and Glu metabolism; and Arg and Pro metabolism). These results provide an innovative method to promote PCs synthesis for the restoration of Cd-contaminated-soil.

The silica-composited biochars (SBC) were synthesized by adding silica particulates into bamboo biomass during pyrolysis at 700 °C to examine the effect of silica addition on biochar stabilities and adsorption properties for tetracycline (TC). Silica addition increased the total pore volume and average pore diameter of biochar due to the abundant mesopores in SBC, but decreased specific surface area due to the blockage of biochar pore with silica particles. Biochar stability was obviously enhanced with silica addition due to the decreased atomic ratio of H/C and O/C, the reduced C loss amount after chemical oxidation treatment, and the increased thermal stability. The adsorption capacities of SBC for TC were greatly enhanced with silica addition and increased with the increasing silica addition amount, which can be attributed to the facilitating effect of π–π electron donor acceptor (EDA) interaction and pore-filling effect. In addition, silica addition can also effectively enhance the oxidation resistance of biochar for TC adsorption, since the decreased degree (δ) of TC adsorption amounts on the biochars after chemical oxidation decreased with the increasing silica addition level. The observed positive correlations between δ values and the corresponding C loss amount of biochars after chemical oxidation suggested that the high carbon stability was favorable for the maintenance of biochar adsorption capacity. These results can provide a new way to improve biochar stabilities, aging resistance, and adsorption properties for organic pollutants.

In recent decades, most big cities in China have experienced severe air pollution accompanied by rapid economic and social development. Analysis of measurements of air pollutants form a fundamental basis for understanding the characteristics of air pollution and are important references for policy-making. In this study, five-year measurements of air pollutants at 6 sites in Lhasa, a typical high altitude big city in southwestern China, were analyzed from January 2013 to December 2017. Air pollutants at all the 6 sites in Lhasa generally displayed similar patterns of both diurnal and monthly variations, indicating the mixed atmospheric environment and the overall effect of the meteorological conditions in the city. Spatially, the air pollutant concentrations at the 6 sites were generally characterized by high concentrations of SO₂, NO₂, CO, PM₁₀ and PM₂.₅ at urban sites and high O₃ concentrations at suburban sites. In comparison with other provincial capital cities in China, Lhasa has low concentrations of air pollutants, except for O₃, and thus, better air quality. Although Lhasa has experienced rapid urbanization and economic development, air pollution conditions have remained rather stable and even decreased slightly in term of particular air pollutants. We suggested that the relatively isolated location, low air pollutant emissions associated with its industrial structure and renewable energy consumption, and effective air pollution control measures, collectively contributed to the synchronous improvement of the economy and air quality in Lhasa. Such “Lhasa pattern” may serve as a positive example for other regional hub cities in China and beyond that experience socioeconomic development and simultaneously seek to improve air quality.

Epidemiologists use prediction models to downscale (i.e., interpolate) air pollution exposure where monitoring data is insufficient. This study compares machine learning prediction models for ground-level ozone during wildfires, evaluating the predictive accuracy of ten algorithms on the daily 8-hour maximum average ozone during a 2008 wildfire event in northern California. Models were evaluated using a leave-one-location-out cross-validation (LOLO CV) procedure to account for the spatial and temporal dependence of the data and produce more realistic estimates of prediction error. LOLO CV avoids both the well-known overly optimistic bias of k-fold cross-validation on dependent data and the conservative bias of evaluating prediction error over a coarser spatial resolution via leave-k-locations-out CV. Gradient boosting was the most accurate of the ten machine learning algorithms with the lowest LOLO CV estimated root mean square error (0.228) and the highest LOLO CV Rˆ2 (0.677). Random forest was the second best performing algorithm with an LOLO CV Rˆ2 of 0.661. The LOLO CV estimates of predictive accuracy were less optimistic than 10-fold CV estimates for all ten models. The difference in estimated accuracy between the 10-fold CV and LOLO CV was greater for more flexible models like gradient boosting and random forest. The order of estimated model accuracy depended on the choice of evaluation metric, indicating that 10-fold CV and LOLO CV may select different models or sets of covariates as optimal, which calls into question the reliability of 10-fold CV for model (or variable) selection. These prediction models are designed for interpolating ozone exposure, and are not suited to inferring the effect of wildfires on ozone or extrapolating to predict ozone in other spatial or temporal domains. This is demonstrated by the inability of the best performing models to accurately predict ozone during 2007 southern California wildfires.

China has performed crop residue burning (CRB) for a long time and has suffered from resultant environmental pollution. High temporal resolution has not been fully discussed in attempts to address the temporal and spatial impact of CRB in China on air quality. Our study used the MOD14A1 product of the MODerate resolution Imaging Spectrometer (MODIS) to extract the daily CRB for China during the period from 2014 to 2016, and the daily aerosol optical depth (AOD) provided by MODIS Collection 6 was obtained to simultaneously reflect the air pollution. First, the study area was classified into five subregions. A temporal analysis was conducted on the daily variation in the number of CRB events and the regional mean value of AOD, the spatial contribution ratio of CRB on aerosol pollution was then calculated, and finally, a temporal and spatial Pearson correlation was calculated to find the spatially varying relationship between CRB and aerosol. The results suggest the following: (1) CRB possesses seasonal characteristics that are associated with the harvest time or sowing time of major crops in the region. (2) The impact of CRB on aerosol was delayed by 1–6 days. (3) High contribution ratios (70%–90%) occurred in northeast China on a large scale; even when the impact of the CRB on aerosol pollution in the Huang-Huai-Hai river basin occurred on a large scale, the value was merely approximately 30%. Relatively low contributions of CRB have been found in other places, whereas the contribution of CRB was severe in some places with high-density populations. (4) Temporal-spatial correlation provided an accurate index to reflect the correlation of CRB and aerosol in a specific location, which suggests that, in places with large scale and dense CRB, CRB tends to have a high positive correlation with aerosol pollution for each day.