Characterization of Chlorinated Aliphatic Hydrocarbons and Environmental Variables in a Shallow Groundwater in Shanghai Using Kriging Interpolation and Multifactorial Analysis

Depth and contaminant-shaped bacterial community structure and assembly at an aged chlorinated aliphatic hydrocarbon-contaminated site

Chlorinated aliphatic hydrocarbons (CAHs) are potentially toxic substances that have been detected in various contaminated environments. Biological elimination is the main technique of detoxifying CAHs in the contaminated sites, but the soil bacterial community at CAH-contaminated sites have been little investigated. Here, high-throughput sequencing analysis of soil samples from different depths (to 6 m depth) at an aged CAH-contaminated site has been conducted to investigate the community composition, function, and assembly of soil bacteria. The alpha diversity of the bacterial community significantly increased with increasing depth and bacterial community also became more convergent with increasing depth. Organohalide-respiring bacteria (OHRB) is considered keystone taxa to reduce the environmental stress of CAHs by reductive dechlorinate CAHs into nontoxic products, increases the alpha diversity of bacterial community and improves the stability of bacterial co-occurrence network. The high concentration of CAHs in deep soil and the stable anaerobic environment make deterministic processes dominate bacterial community assembly, while the topsoil is dominated by dispersal limitation. In general, CAHs at contaminated sites have a great impact on bacterial community, but the CAHs metabolic community acclimated in deep soil can reduce the environmental stress of CAHs, which provides foundation for the monitored natural attenuation technology in CAHs-contaminated sites.

Prediction of Dichloroethene Concentration in the Groundwater of a Contaminated Site Using XGBoost and LSTM

Chlorinated aliphatic hydrocarbons (CAHs) are widely used in agriculture and industries and have become one of the most common groundwater contaminations. With the excellent performance of the deep learning method in predicting, LSTM and XGBoost were used to forecast dichloroethene (DCE) concentrations in a pesticide-contaminated site undergoing natural attenuation. The input variables included BTEX, vinyl chloride (VC), and five water quality indicators. In this study, the predictive performances of long short-term memory (LSTM) and extreme gradient boosting (XGBoost) were compared, and the influences of variables on models’ performances were evaluated. The results indicated XGBoost was more likely to capture DCE variation and was robust in high values, while the LSTM model presented better accuracy for all wells. The well with higher DCE concentrations would lower the model’s accuracy, and its influence was more evident in XGBoost than LSTM. The explanation of the SHapley Additive exPlanations (SHAP) value of each variable indicated high consistency with the rules of biodegradation in the real environment. LSTM and XGBoost could predict DCE concentrations through only using water quality variables, and LSTM performed better than XGBoost.

Petroleum hydrocarbon rich oil refinery sludge of North-East India harbours anaerobic, fermentative, sulfate-reducing, syntrophic and methanogenic microbial populations

Background

Sustainable management of voluminous and hazardous oily sludge produced by petroleum refineries remains a challenging problem worldwide. Characterization of microbial communities of petroleum contaminated sites has been considered as the essential prerequisite for implementation of suitable bioremediation strategies. Three petroleum refinery sludge samples from North Eastern India were analyzed using next-generation sequencing technology to explore the diversity and functional potential of inhabitant microorganisms and scope for their on-site bioremediation.

Results

All sludge samples were hydrocarbon rich, anaerobic and reduced with sulfate as major anion and several heavy metals. High throughput sequencing of V3-16S rRNA genes from sludge metagenomes revealed dominance of strictly anaerobic, fermentative, thermophilic, sulfate-reducing bacteria affiliated to Coprothermobacter, Fervidobacterium, Treponema, Syntrophus, Thermodesulfovibrio, Anaerolinea, Syntrophobacter, Anaerostipes, Anaerobaculum, etc., which have been well known for hydrocarbon degradation. Relatively higher proportions of archaea were detected by qPCR. Archaeal 16S rRNA gene sequences showed presence of methanogenic Methanobacterium, Methanosaeta, Thermoplasmatales, etc. Detection of known hydrocarbon utilizing aerobic/facultative anaerobic (Mycobacterium, Pseudomonas, Longilinea, Geobacter, etc.), nitrate reducing (Gordonia, Novosphigobium, etc.) and nitrogen fixing (Azovibrio, Rhodobacter, etc.) bacteria suggested niche specific guilds with aerobic, facultative anaerobic and strict anaerobic populations. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) predicted putative genetic repertoire of sludge microbiomes and their potential for hydrocarbon degradation; lipid-, nitrogen-, sulfur- and methane- metabolism. Methyl coenzyme M reductase A (mcrA) and dissimilatory sulfite reductase beta-subunit (dsrB) genes phylogeny confirmed methanogenic and sulfate-reducing activities within sludge environment endowed by hydrogenotrophic methanogens and sulfate-reducing Deltaproteobacteria and Firmicutes members.

Conclusion

Refinery sludge microbiomes were comprised of hydrocarbon degrading, fermentative, sulfate-reducing, syntrophic, nitrogen fixing and methanogenic microorganisms, which were in accordance with the prevailing physicochemical nature of the samples. Analysis of functional biomarker genes ascertained the activities of methanogenic and sulfate-reducing organisms within sludge environment. Overall data provided better insights on microbial diversity and activity in oil contaminated environment, which could be exploited suitably for in situ bioremediation of refinery sludge.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1275-8) contains supplementary material, which is available to authorized users.

Natural attenuation of chlorinated ethenes in hyporheic zones: A review of key biogeochemical processes and in-situ transformation potential

Chlorinated ethenes (CEs) are legacy contaminants whose chemical footprint is expected to persist in aquifers around the world for many decades to come. These organohalides have been reported in river systems with concerning prevalence and are thought to be significant chemical stressors in urban water ecosystems. The aquifer-river interface (known as the hyporheic zone) is a critical pathway for CE discharge to surface water bodies in groundwater baseflow. This pore water system may represent a natural bioreactor where anoxic and oxic biotransformation process act in synergy to reduce or even eliminate contaminant fluxes to surface water. Here, we critically review current process understanding of anaerobic CE respiration in the competitive framework of hyporheic zone biogeochemical cycling fuelled by in-situ fermentation of natural organic matter. We conceptualise anoxic-oxic interface development for metabolic and co-metabolic mineralisation by a range of aerobic bacteria with a focus on vinyl chloride degradation pathways. The superimposition of microbial metabolic processes occurring in sediment biofilms and bulk solute transport delivering reactants produces a scale dependence in contaminant transformation rates. Process interpretation is often confounded by the natural geological heterogeneity typical of most riverbed environments. We discuss insights from recent field experience of CE plumes discharging to surface water and present a range of practical monitoring technologies which address this inherent complexity at different spatial scales. Future research must address key dynamics which link supply of limiting reactants, residence times and microbial ecophysiology to better understand the natural attenuation capacity of hyporheic systems.