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We investigated the response of the dominant bacterial taxa in gravelly sand to the addition of biochar and/or mixtures of volatile petroleum hydrocarbons (VPHs) using denaturing gradient gel electrophoresis (DGGE) and sequencing of cut bands. Biochar addition alone had only weak effects on the soil bacterial community composition in batch study samples, while VPH addition had strong effects. Indirect effects of biochar on soil bacterial communities were apparent in column study samples, where biochar-enhanced sorption affected VPH spreading. Following VPH addition, cell abundance increased by no more than a factor of 2 and several Pseudomonas spp. became dominant in soil with and without biochar. We present a VPH fate model that considers soil bacterial biomass dynamics and a nutrient limited soil biomass carrying capacity. The model simulates an apparent lag phase before the onset of a brief period of intensive VPH biodegradation and biomass growth, which is followed by substantially slower VPH biodegradation, when nitrogen needs to be recycled between decaying and newly formed biomass. If biomass growth is limited by a factor other than the organic pollutant bioavailability, biochar amendment may enhance VPH attenuation in between a VPH source below ground and the atmosphere by reducing the risk of overloading the soil's biodegradation capacity. [ABSTRACT FROM AUTHOR]

Volatile Petroleum Hydrocarbon (VPH) class effects on soil microbial composition were investigated using two next-generation sequencing (NGS) techniques – 454 pyrosequencing and ion torrent sequencing. Microbial activity was stimulated by adding different VPH compound classes to the sandy soil in comparison with live controls without VPH addition. Microbial community structure was significantly affected by the various VPH classes. At the genus level, Rhodococcus, Desulfosporosinus , Polaromonas, Mesorhizobium and Methylibium had the highest relative abundances in the straight-chain alkane (str-alk) treated soil as compared to the control (p < 0.05, 2 sample t-tests) while Pseudomonas was more dominant in the cyclic alkane (cyc-alk) contaminated soil. Pseudonocardia was significantly higher in relative abundance in the aromatic hydrocarbon (aro-H) treated batches as compared to the control (p < 0.05, 2 sample t-tests). A non-metric multidimensional scaling (NMDS) of the Bray Curtis similarity between microbial communities in the batches revealed at least 60% similarity for each treatment and also showed that VPH class was a statistically significant factor in shaping the bacterial communities in the soil treatments (Global R = 0.861, p < 0.01). The NGS platforms (454 GS Junior and Ion torrent) compared in this study did not appear to affect the outcomes of the microbial community structure and composition analysis. Image 1 • Volatile petroleum hydrocarbon (VPH) class mixtures stimulated microbial activity. • Microbial diversity decreased following addition of different VPH class mixtures. • VPH classes contributed to shaping the microbial communities in batch treatments. • Bacterial species demonstrated varying responses to different VPH class mixtures. • NGS platforms did not alter the outcomes of microbial community structures. 16S amplicon sequencing revealed how soil microbial communities respond to addition of different volatile petroleum hydrocarbons. [ABSTRACT FROM AUTHOR]

Quantitative Structure Biodegradation Relationships (QSBRs) are a tool to predict the biodegradability of chemicals. The objective of this work was to generate reliable biodegradation data for mono-aromatic chemicals in order to evaluate and verify previously developed QSBRs models. A robust biodegradation test method was developed to estimate specific substrate utilization rates, which were used as a proxy for biodegradation rates of chemicals in pure culture. Five representative mono-aromatic chemicals were selected that spanned a wide range of biodegradability. Aerobic biodegradation experiments were performed for each chemical in batch reactors seeded with known degraders. Chemical removal, degrader growth and CO 2 production were monitored over time. Experimental data were interpreted using a full carbon mass balance model, and Monod kinetic parameters (Y, K s , q max and μ max) for each chemical were determined. In addition, stoichiometric equations for aerobic mineralization of the test chemicals were developed. The theoretically estimated biomass and CO 2 yields were similar to those experimentally observed; 35% (s.d ± 8%) of the recovered substrate carbon was converted to biomass, and 65% (s.d ± 8%) was mineralised to CO 2. Significant correlations were observed between the experimentally determined specific substrate utilization rates, as represented by q max and q max /K s , at high and low substrate concentrations, respectively, and the first order biodegradation rate constants predicted by a previous QSBR study. Similarly, the correlation between q max and selected molecular descriptors characterizing the chemicals structure in a previous QSBR study was also significant. These results suggest that QSBR models can be reliable and robust in prioritising chemical half-lives for regulatory screening purposes. Image 1 • The biodegradation rates for five mono-aromatic chemicals were estimated. • Carbon mass balance models were used to assess the reliability of the estimated rates. • Biodegradation rates (i.e. q max) from this study showed same rank prioritisation to those rates from a previous QSBR study. • These rates enabled validation and calibration of the principle behind in silico QSBRs. [ABSTRACT FROM AUTHOR]

The objective of this work was to develop a QSBR model for the prioritization of organic pollutants based on biodegradation rates from a database containing globally harmonized biodegradation tests using relevant molecular descriptors. To do this, we first categorized the chemicals into three groups (Group 1: simple aromatic chemicals with a single ring, Group 2: aromatic chemicals with multiple rings and Group3: Group 1 plus Group 2) based on molecular descriptors, estimated the first order biodegradation rate of the chemicals using rating values derived from the BIOWIN3 model, and finally developed, validated and defined the applicability domain of models for each group using a multiple linear regression approach. All the developed QSBR models complied with OECD principles for QSAR validation. The biodegradation rate in the models for the two groups (Group 2 and 3 chemicals) are associated with abstract molecular descriptors that provide little relevant practical information towards understanding the relationship between chemical structure and biodegradation rates. However, molecular descriptors associated with the QSBR model for Group 1 chemicals (R2 = 0.89, Q2 loo = 0.87) provided information on properties that can readily be scrutinised and interpreted in relation to biodegradation processes. In combination, these results lead to the conclusion that QSBRs can be an alternative tool to estimate the persistence of chemicals, some of which can provide further insights into those factors affecting biodegradation. Image 1 • QSBR models that can predict half-life of wide range of aromatic chemicals have been developed. • Developed QSBR models provide insight into those factors affecting biodegradation. • Developed QSBR models can be a tool of prioritising and classifying chemicals in PBT assessment. [ABSTRACT FROM AUTHOR]