Screening for Autochthonous Phytoextractors in a Heavy Metal Contaminated Coal Mining Area

In order to protect public health and crops from soil heavy metal (HM) contamination at a coal mining area in Henan, central China, HM pollution investigation and screening of autochthonous HM phytoextractors were conducted. The concentrations of cadmium (Cd), lead (Pb), copper (Cu) and zinc (Zn) in surface soils exceeded the corresponding local background values and the China National Standard (CNS). The maximum potential ecological risk (RI) was 627.30, indicating very high ecological risk. The monomial risk of Cd contributed the most to the RI, varying from 85.48% to 96.48%. The plant community structure in the study area was simple, and was composed of 24 families, 37 genera and 40 species. B. pilosa, A. roxburghiana, A. argyi, A. hispidus were found to be the most dominant species at considerable risk sites. Based on the comprehensive analysis of Cd concentration, bioconcentration factor, translocation factor and adaptability factor, B. pilosa and A. argyi had potential for phytoextraction at considerable risk sites. A. roxburghiana had potential for Cd phytoextraction at moderately risk sites and A. hispidus seemed suitable for phytostabilization. The results could contribute to the phytoremediation of the similar sites

The Sources and Potential Hosts Identification of Antibiotic Resistance Genes in the Yellow River, Revealed by Metagenomic Analysis

The fate of antibiotic resistance genes (ARGs) has been revealed in various environmental media in recent years. Namely, the emergence of genes that resist colistin and carbapenems has attracted wide attention. However, the pollution condition of ARGs and sources in the Yellow River is still little understood, despite the river being the second longest in China. The present study determined the levels of ARG pollution in the Henan section of the Yellow River and evaluated the role of the aquaculture industry in the spread of ARGs. As revealed by the results, a total of 9 types of ARGs were detected in the sediments of the Yellow River, and the total ARG content in the Yellow River ranges from 7.27 to 245.45 RPKM. Sul1 and sul2 are the dominant ARGs, and the huge usage of sulfonamides, horizontal gene transfer, and wide bacteria host contribute to the prevalence of these two genes. The results of Spearman correlation analysis indicate that the breeding industry has little influence on ARGs in the Yellow River. Network analysis reveals that the opportunistic pathogen Pseudomonas is the potential host of sul1, tetG, and ANT(3′′)-IIa, which can pose a risk to human health

Tracking the extracellular and intracellular antibiotic resistance genes across whole year in wastewater of intensive dairy farm

Monitoring the annual variation of antibiotic resistance genes (ARGs) in livestock wastewater is important for determining the high-risk period of transfer and spread of animal-derived antibiotic resistance into the environment. However, the knowledge regarding the variation patterns of ARGs, especially intracellular ARGs (iARGs) and extracellular ARGs (eARGs), over time in livestock wastewater is still unclear. Herein, we conducted a year-round study to trace the profiles of ARGs at a Chinese-intensive dairy farm, focusing on the shifts observed in different months. The results showed significant differences in the composition and variation between iARGs and eARGs. Tetracycline, sulfonamide, and macrolide resistance genes were the major types of iARGs, while cfr was the major type of eARG. The environmental adaptations of the host bacteria determine whether ARGs appear as intracellular or extracellular forms. The total abundance of ARGs was higher from April to September, which can be attributed to the favorable climatic conditions for bacterial colonization and increased antibiotic administration during this period. Integron was found to be highly correlated with most iARGs, potentially playing a role in the presence of these genes within cells and their similar transmission patterns in wastewater. The intracellular and extracellular bacterial communities were significantly different, primarily because of variations in bacterial adaptability to the high salt and anaerobic environment. The intracellular co-occurrence network indicated that some dominant genera in wastewater, such as Turicibacter, Clostridium IV, Cloacibacillus, Subdivision5_genera_incertae_sedis, Saccharibacteria_genera_incertae_sedis and Halomonas, were potential hosts for many ARGs. To the best of our knowledge, this study demonstrates, for the first time, the annual variation of ARGs at critical points in the reuse of dairy farm wastewater. It also offers valuable insights into the prevention and control of ARGs derived from animals

Stochastic analysis of oscillatory hydraulic tomography

This paper investigates the effectiveness of different oscillatory hydraulic tomography (OHT) frequencies for estimating heterogeneous fields. The analysis first formulates the effects of uncharacterized aquifer responses, T, and S fields as the ensemble mean residual flux and residual storage terms in the stochastic unconditional and conditional mean equations. These terms persist unless the T, S, or head fields are specified everywhere. We then conducted OHT to estimate the T and S fields using Monte Carlo experiments. The experiments show that using the heads in response to periodic pumping with different frequencies or multifrequency, the estimates' performance metrics vary from one realization to others. The mean performance metrics over many realizations are, however, indistinguishable, despite the frequency. We attribute the variation in the performance metrics to the lack of parameter or state variable ergodicity. Lastly, we emphasize the importance of dense monitoring networks and a cost-effective data collection strategy to improve the resolution of characterizing aquifer heterogeneity. © 2021 Elsevier B.V.CRDF Global24 month embargo; first published online 27 February 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Assessing impacts of mining:Recent contributions from GIS and remote sensing

Mining produces several environmental, social, and economic impacts which can be analysed spatially using remote sensing (RS) and geographical information systems (GIS). This paper provides an overview of recent studies using these techniques to assess mining impacts on water, land, and society. It also highlights the geographic complexities of these impacts via mining case studies, and discusses spatial research methods, data sources, and limitations. Despite noted simplifications, risks, and uncertainties of mapping the impacts of mining, the cases included in our overview illustrate that there are clearly beneficial applications. At a local level, these include environmental and socioeconomic risk assessments, disaster mitigation, and adjudication on mine-related conflicts. At a regional level, spatial analyses can support cumulative and strategic impact assessments. At a global level, spatial analyses can reveal industry-wide land use trends, and provide key land use data for comparative analyses of mining impacts between commodities, locations, and mine configurations. The degree to which such benefits are realised will likely depend on the resources afforded to what is a growing field of study