Analysis of transduction in wastewater bacterial populations by targeting the phage-derived 16S rRNA gene sequences

Bacterial 16S rRNA genes transduced by bacteriophages were identified and analyzed in order to estimate the extent of the bacteriophage-mediated horizontal gene transfer in the wastewater environment. For this purpose, phage and bacterial DNA was isolated from the oxidation tank of a municipal wastewater treatment plant. Phylogenetic analysis of the 16S rRNA gene sequences cloned from a phage metagenome revealed that bacteriophages transduce genetic material in several major groups of bacteria. The groups identified were as follows: Betaproteobacteria, Gammaproteobacteria, Alphaproteobacteria, Actinomycetales and Firmicutes. Analysis of the 16S rRNA gene sequences in the total bacterial DNA from the same sample revealed that several bacterial groups found in the oxidation tank were not present in the phage metagenome (e.g. Deltaproteobacteria, Nitrospira, Planctomycetes and many Actinobacteria genera). These results suggest that transduction in a wastewater environment occurs in several bacterial groups; however, not all species are equally involved into this process. The data also showed that a number of distinctive bacterial strains participate in transduction-mediated gene transfer within identified bacterial groupings. Denaturing gradient gel electrophoresis analysis confirmed that profiles of the transduced 16S rRNA gene sequences and those present in the whole microbial community show significant differences.

Quantifying contributions of domestic wastewater treatment systems to nutrient fluxes in stream headwaters

Effective implementation of the Water Framework Directive requires a reappraisal of conventional approaches to water quality monitoring. Quantifying the impact of domestic wastewater treatment systems (DWWTS) in Irish catchments is further complicated by high levels of natural heterogeneity. This paper presents a numerical model that couples attenuation to flow along different hydrological pathways contributing to river discharge; this permits estimation of the impact of DWWTS to overall nutrient fluxes under a range of geological conditions. Preliminary results suggest high levels of attenuation experienced
before DWWTS effluent reaches bedrock play a significant role in reducing its ecological impact on aquatic receptors. Conversely, low levels of attenuation in systems discharging directly to surface water may affect water quality more significantly, particularly during prolonged dry periods in areas underlain by low productivity aquifers (>60% of Ireland), where dilution capacity is limited.

A field study assessing the impact of on-site wastewater treatment systems on surface water quality in a Co. Monaghan catchment

Poorly functioning on-site wastewater treatment systems (OSWTS) can be among the many sources of pollution to groundwater and surface water, which are of critical concern owing to potential human and ecological health risks. An investigation into the effects of on-site wastewater treatment systems (OSWTS) on surface water quality has been undertaken at several sites within a catchment in Co. Monaghan. The study sites were located in areas of 'low’ permeability, suggesting that run-off usually dominates over infiltration. Poor treatment performance of OSWTS within the catchment were found to be the result of several factors, including location in areas with unsuitable soil and site characteristics, incorrect installation, poor maintenance and inappropriate operation by the home owner.

Geophysical and hydrogeological characterisation of the impacts of on-site wastewater treatment discharge to groundwater in a poorly productive bedrock acquifer

Contaminants discharging from on-site wastewater treatment systems (OSWTSs) can impact groundwater quality, threatening human health and surface water ecosystems. Risk of negative impacts becomes elevated in areas of extreme vulnerability with high water tables, where thin unsaturated intervals limit vadose zone attenuation. A combined geophysical/hydrogeological investigation into the effects of an OSWTS, located over a poorly productive aquifer (PPA) with thin subsoil cover, aimed to characterise effluent impacts on groundwater. Groundwater, sampled from piezometers down-gradient of the OSWTS percolation area displayed spatially erratic, yet temporally consistent, contaminant distributions. Electrical resistivity tomography identified an area of gross groundwater contamination close to the percolation area and, when combined with seismic refraction and water quality data, indicated that infiltrating effluent reaching the water table discharged to a deeper more permeable zone of weathered shale resting on more competent bedrock. Subsurface structure, defined by geophysics, indicated that elevated chemical and microbiological contaminant levels encountered in groundwater samples collected from piezometers, down-gradient of sampling points with lower contaminant levels, corresponded to those locations where piezometers were screened close to the weathered shale/competent rock interface; those immediately up-gradient were too shallow to intercept this interval, and thus the more impacted zone of the contaminant plume. Intermittent occurrence of faecal indicator bacteria more than 100 m down gradient of the percolation area suggested relatively short travel times. Study findings highlight the utility of geophysics as part of multidisciplinary investigations for OSWTS contaminant plume characterisation, while also demonstrating the capacity of effluent discharging to PPAs to impact groundwater quality at distance. Comparable geophysical responses observed in similar settings across Ireland suggest the phenomena observed in this study are more widespread than previously suspected.

COD and NH4-N Estimation in the Inflow of Wastewater Treatment Plants using Machine Learning Techniques

The in-line measurement of COD and NH4-N in the WWTP inflow is crucial for the timely monitoring of biological wastewater treatment processes and for the development of advanced control strategies for optimized WWTP operation. As a direct measurement of COD and NH4-N requires expensive and high maintenance in-line probes or analyzers, an approach estimating COD and NH4-N based on standard and spectroscopic in-line inflow measurement systems using Machine Learning Techniques is presented in this paper. The results show that COD estimation using Radom Forest Regression with a normalized MSE of 0.3, which is sufficiently accurate for practical applications, can be achieved using only standard in-line measurements. In the case of NH4-N, a good estimation using Partial Least Squares Regression with a normalized MSE of 0.16 is only possible based on a combination of standard and spectroscopic in-line measurements. Furthermore, the comparison of regression and classification methods shows that both methods perform equally well in most cases.