Sequential oxidation-composting-phytoremediation treatment for the management of an oily sludge from petroleum refinery.

Oily sludges are generated in large quantities in petroleum refinery wastewater treatment plants. Given their complex composition, they are classified as hazardous waste. Selecting a single treatment technique for their remediation is challenging. This work aims to assess the extent of composting followed by phytoremediation on an oily sludge from an API separator unit, pre-treated by chemical oxidation with alkaline activated persulfate (PS). 18% of total petroleum hydrocarbons (TPH) were determined by IR spectroscopy. The aliphatic hydrocarbon content was 4714 ± 250 ppm by GC-FID, and aromatics were not detectable, suggesting a high amount of non-chromatographable complex hydrocarbons. The density of generalist and hydrocarbon-degrading populations of the oily sludge estimated by quantitative polymerase chain reaction (qPCR) evidenced an autochthonous microbiota with hydrocarbon-degrading capacity. The oxidative treatment with PS removed 31% of the TPH determined by IR after 20 days. The significant reduction of the native bacterial community was counterbalanced by coupling a composting treatment. Co-composting the sludge with goat manure and oat straw produced, after a year, a 96% reduction in TPH content, regardless of the oxidative pretreatment. Organic matter transformation was evidenced by the decrease of dissolved organic carbon (DOC) and the variation in E4/E6 ratio. The matrices obtained of composting were used as substrates for phytoremediation for 4 months. Ryegrass seeds were planted in both PS-treated and untreated sludge substrates. The presence of the plant grown in the pre-oxidised and composted substrate resulted in a higher aerial biomass of ryegrass (67%), an increase in enzymatic activities, and higher concentration of DOC, although without evidence of additional dissipation of TPH. The dynamics of the bacterial communities of the different substrates generated during the biological treatment were analyzed by Illumina NovaSeq DNA sequencing of 16S rRNA amplicons. The findings mirrored a succession compatible with that described in contaminated matrices, but also in other non-contaminated ones. According to these findings, an organic matter transformation process occurred, which included the complex hydrocarbons of the oily sludge, resulting in an active substrate that promoted the retention of nutrients and water and provided the necessary support for plant development.

Datathons: fostering equitability in data reuse in ecology.

Approaches to rapidly collecting global biodiversity data are increasingly important, but biodiversity blind spots persist. We organized a three-day Datathon event to improve the openness of local biodiversity data and facilitate data reuse by local researchers. The first Datathon, organized among microbial ecologists in Uruguay and Argentina assembled the largest microbiome dataset in the region to date and formed collaborative consortia for microbiome data synthesis.

Assessment of Biological Contribution to Natural Recovery of Anthropized Freshwater Sediments From Argentina: Autochthonous Microbiome Structure and Functional Prediction.

Monitored natural recovery (MNR) is an in situ technique of conventional remediation for the treatment of contaminated sediments that relies on natural processes to reduce the bioavailability or toxicity of contaminants. Metabarcoding and bioinformatics approaches to infer functional prediction were applied in bottom sediments of a tributary drainage channel of Río de La Plata estuary, in order to assess the biological contribution to MNR. Hydrocarbon concentration in water samples and surface sediments was below the detection limit. Surface sediments were represented with high available phosphorous, alkaline pH, and the bacterial classes Anaerolineae, Planctomycetia, and Deltaproteobacteria. The functional prediction in surface sediments showed an increase of metabolic activity, carbon fixation, methanogenesis, and synergistic relationships between Archaeas, Syntrophobacterales, and Desulfobacterales. The prediction in non-surface sediments suggested the capacity to respond to different kinds of environmental stresses (oxidative, osmotic, heat, acid pH, and heavy metals), predicted mostly in Lactobacillales order, and the capacity of Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Actinomyces classes to degrade xenobiotic compounds. Canonical correspondence analysis (CCA) suggests that depth, phosphate content, redox potential, and pH were the variables that structured the bacterial community and not the hydrocarbons. The characterization of sediments by metabarcoding and functional prediction approaches, allowed to assess how the microbial activity would contribute to the recovery of the site.