Online assessment of sand filter performance for bacterial removal in a full-scale drinking water treatment plant

Microbiological risks associated with drinking water can be minimized by providing enhanced integrity monitoring of bacterial removal by water treatment processes. This study aimed to evaluate the efficacy of real-time bacteriological counters for continuously assessing the performance of a full-scale sand filter to remove bacteria. Over the course of an 8-day evaluation, online counting of bacteria was successfully performed, providing continuous bacterial counts in the sand filter influent and effluent over approximate ranges from 17 × 10 4 to 94 × 10 4 and from 0.2 × 10 4 to 1.3 × 10 4 counts/mL, respectively. Periodic variations were observed with online bacterial counts in the sand filter influent because of the changes in the performance of flocculation and sedimentation processes. Overall, online removal rates of bacteria determined during the full-scale test were 95.2?99.3% (i.e., 1.3?2.2-log), indicating that online bacterial counting can continuously demonstrate over 1.3-log removal in the sand filter. Real-time bacteriological counting technology can be a useful tool for assessing variability and detecting bacterial breakthrough. It can be integrated with other online water quality measurements to evaluate underlying trends and the performance of sand filters for bacterial removal, which can enhance the safety of drinking water

N-Nitrosodimethylamine Formation from Treatment of Seasonally and Spatially Varying Source Water

N-nitrosodimethylamine (NDMA) is a disinfection by-product (DBP) that has been classified as a probable human carcinogen in multiple risk assessments. NDMA presence in drinking water is widespread and dependent on source water, disinfectant type, precursors, and water treatment strategies. The objectives of this study were to investigate NDMA formation potential in a modeled monochloramine water treatment plant (WTP) fed by seasonally and spatially varying source water; and to optimize DBP precursor removal by combining conventional and additional treatment techniques. After NDMA analysis, it was found that NDMA formation was significantly dependent on source water type and monochloramine contact time (CT); e.g., at 24 h CT, Cork Brook produced 12.2 ng/L NDMA and Bailey Brook produced 4.2 ng/L NDMA, compared with 72 h CT, Cork Brook produced 4.1 ng/L NDMA and Bailey Brook produced 3.4 ng/L NDMA. No correlations were found between traditional DBP precursors such as total organic carbon and total nitrogen, and the formation of NDMA. The laboratory bench-top treatment system was highly effective at removing traditional DBP precursors, highlighting the need for WTPs to alter their current treatment methods to best accommodate the complex system of DBP control

Assimilable Organic Carbon (AOC) in Soil Water Extracts Using Vibrio harveyi BB721 and Its Implication for Microbial Biomass

Assimilable organic carbon (AOC) is commonly used to measure the growth potential of microorganisms in water, but has not yet been investigated for measuring microbial growth potential in soils. In this study, a simple, rapid, and non-growth based assay to determine AOC in soil was developed using a naturally occurring luminous strain Vibrio harveyi BB721 to determine the fraction of low molecular weight organic carbon in soil water extract. Calibration of the assay was achieved by measuring the luminescence intensity of starved V. harveyi BB721 cells in the late exponential phase with a concentration range from 0 to 800 µg l−1 glucose (equivalent to 0–16.0 mg glucose C kg−1 soil) with the detection limit of 10 µg l−1 equivalent to 0.20 mg glucose C kg−1 soil. Results showed that bioluminescence was proportional to the concentration of glucose added to soil. The luminescence intensity of the cells was highly pH dependent and the optimal pH was about 7.0. The average AOC concentration in 32 soils tested was 2.9±2.2 mg glucose C kg−1. Our data showed that AOC levels in soil water extracts were significantly correlated (P<0.05) with microbial biomass determined as microbial biomass carbon, indicating that the AOC concentrations determined by the method developed might be a good indicator of soil microbial biomass. Our findings provide a new approach that may be used to determine AOC in environmental samples using a non-growth bioluminescence based assay. Understanding the levels of AOC in soil water extract provides new insights into our ability to estimate the most available carbon pool to bacteria in soil that may be easily assimilated into cells for many metabolic processes and suggest possible the links between AOC, microbial regrowth potential, and microbial biomass in soils

Characterization of the Microbiome at the World’s Largest Potable Water Reuse Facility

Conventional water resources are not sufficient in many regions to meet the needs of growing populations. Due to cyclical weather cycles, drought, and climate change, water stress has increased worldwide including in Southern California, which serves as a model for regions that integrate reuse of wastewater for both potable and non-potable use. The Orange County Water District (OCWD) Advanced Water Purification Facility (AWPF) is a highly engineered system designed to treat and produce up to 100 million gallons per day (MGD) of purified water from a municipal wastewater source for potable reuse. Routine facility microbial water quality analysis is limited to standard indicators at this and similar facilities. Given recent advances in high throughput DNA sequencing techniques, complete microbial profiling of communities in water samples is now possible. By using 16S/18S rRNA gene sequencing, metagenomic and metatranscriptomic sequencing coupled to a highly accurate identification method along with 16S rRNA gene qPCR, we describe a detailed view of the total microbial community throughout the facility. The total bacterial load of the water at stages of the treatment train ranged from 3.02 × 106 copies in source, unchlorinated wastewater feed to 5.49 × 101 copies of 16S rRNA gene/mL after treatment (consisting of microfiltration, reverse osmosis, and ultraviolet/advanced oxidation). Microbial diversity and load decreased by several orders of magnitude after microfiltration and reverse osmosis treatment, falling to almost non-detectable levels that more closely resembled controls of molecular grade laboratory water than the biomass detected in the source water. The presence of antibiotic resistance genes and viruses was also greatly reduced. Overall, system design performance was achieved, and comprehensive microbial community analysis was found to enable a more complete characterization of the water/wastewater microbial signature

Potential human pathogenic bacteria in a mixed urban watershed as revealed by pyrosequencing.

Current microbial source tracking (MST) methods for water depend on testing for fecal indicator bacterial counts or specific marker gene sequences to identify fecal contamination where potential human pathogenic bacteria could be present. In this study, we applied 454 high-throughput pyrosequencing to identify bacterial pathogen DNA sequences, including those not traditionally monitored by MST and correlated their abundances to specific sources of contamination such as urban runoff and agricultural runoff from concentrated animal feeding operations (CAFOs), recreation park area, waste-water treatment plants, and natural sites with little or no human activities. Samples for pyrosequencing were surface water, and sediment collected from 19 sites. A total of 12,959 16S rRNA gene sequences with average length of ≤400 bp were obtained, and were assigned to corresponding taxonomic ranks using ribosomal database project (RDP), Classifier and Greengenes databases. The percent of total potential pathogens were highest in urban runoff water (7.94%), agricultural runoff sediment (6.52%), and Prado Park sediment (6.00%), respectively. Although the numbers of DNA sequence tags from pyrosequencing were very high for the natural site, corresponding percent potential pathogens were very low (3.78-4.08%). Most of the potential pathogenic bacterial sequences identified were from three major phyla, namely, Proteobacteria, Bacteroidetes, and Firmicutes. The use of deep sequencing may provide improved and faster methods for the identification of pathogen sources in most watersheds so that better risk assessment methods may be developed to enhance public health

Sampling locations for middle Santa Ana River pathogen source evaluation study^*.

*<p>Modified from Ibekwe et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079490#pone.0079490-Ibekwe2" target="_blank">[21]</a>.</p><p>Sampling from site S10 was discontinued after one sampling due to construction activities on the site.</p><p>GPS; geographic positioning system.</p><p>OCWD; Orange County Water District.</p><p>WWTP; waste water treatment plant.</p

Rarefaction curves of seven sources at cutoff of 3%.

<p>Two sources (urban runoff water and sediment) are not included because of low sequence tags obtained.</p

16S rRNA sequence similarity to known pathogens within each genus.

<p>The five most abundant genus are shown with their distributions within each source.</p

List of potential human pathogenic bacterial sequences identified from different sources within the Santa Ana watershed using 454 pyrosequencing obtained from RDP Classifier data.

<p>N = Natural site; W = Water, S = sediment, CC = Cypress Channel, CN = Chino Creek; P = Prado wetland area: e.g. NS = Natural site sediment.</p

Number of sequence tags assigned to potential pathogenic genus from Santa Ana River watershed as determined by 454 pyrosequencing using RDP Classifier databases.

*<p>WWTP; waste water treatment plant.</p