Water Resources in the UAE The UAE is characterized by mean annual rainfall of less than 100 mm per year, an annual evaporation rate of 2-3 meters, a groundwater recharge rate of less than 4% of the total annual water used, and no reliable perennial surface water (Brook, Al Houqani, Darawsha, & Achary, 2006). The water requirement in the UAE is 24 times higher than its annually renewable natural water resource of 150 million m3 (Frenken, 2009). The Emirate of Abu Dhabi has 32 decentralized wastewater treatment plants located in different regions (Figure 1), which presents an opportunity to locally utilize treated effluent for irrigation purposes. Currently, desalination plants provide a significant portion of the freshwater supply, up to 70% in Abu Dhabi city (Environment Agency Abu Dhabi, 2009; Statistics Centre - Abu Dhabi (SCAD), 2012). Additionally, only up to 60% of the treated wastewater is currently utilized for landscape irrigation, while the remaining amount is disposed to the sea (Dawoud, Sallam, & Abdelfattah, 2012). Figure 1. Locations of the wastewater treatment plants in the Emirate of Abu Dhabi (Dawoud et al., 2012). Hence, the use of treated wastewater for the irrigation of edible crops in the UAE presents an opportunity to enhance food security while overcoming water scarcity issues due to the arid climate and a growing water demand in the region. Developing reliable Quantitative Microbial Risk Assessment (QMRA) procedures is crucial for setting recommendations on reuse applications of treated wastewater. In this study, pathogens present at different stages of the treatment plant were studied, and a QMRA using stochastic modeling was conducted. Objectives of study
Pathogen screening The aim of this research was to demonstrate three different approaches to study microbial community and the presence and distribution of pathogens in a secondary wastewater treatment plant (WWTP) at three different stages of treatment (Figure 2). Figure 2. Sampling locations at three stages of the central activated sludge wastewater treatment plant. The three molecular biology approaches used for pathogen screening in this study are summarized in Figure 3. In the first approach, overall bacterial diversity was analyzed using PCR-DGGE with universal primers, with subsequent band sequencing. In the second approach, next generation sequencing (NGS) on the Illumina® MiSeq platform was used for 16S rRNA gene molecular analysis of all bacteria. As a third approach, a microdiversity analysis was conducted using PCR-DGGE, targeting Escherichia coli, with group specific primers. Figure 3. Work-flow the methodology and data analysis used for microbial macro-diversity study of all bacteria and micro-diversity study of Escherichia coli. The approach used for non-targeted pathogen analysis is indicated in orange boxes, whereas the targeted pathogenic organism analysis is indicated with blue boxes. Bioinformatics analyses were performed using the Quantitative Insights Into Microbial Ecology (QIIME) protocol by closed-reference clustering of sequences against the 16S Human Pathogenic Bacteria Database (Cai & Zhang, 2013). The results of this portion of the study were recently published in journal, Environmental Science and Technology (Kumaraswamy et al., 2014). QMRA QMRA is a process employed to estimate adverse health effects resulting from exposure to microorganisms (Petterson, Signor, Ashbolt, & Roser, 2006). It involves four steps: (i) hazard identification, (ii) exposure assessment, (iii) dose-response assessment, and (iv) risk characterization (Figure 4). Figure 4. Steps involved in QMRA (Petterson, Signor, Ashbolt, & Roser, 2006). A QMRA was conducted to determine the risk of salmonella infections from wastewater reuse for edible crop irrigation. Quantitative-PCR (qPCR) was used to enumerate Salmonella spp. in post-disinfected samples collected in triplicates form eight sampling time-point. The results were used to construct a distribution fit-graph, using parametric bootstrap of 1000 resamples. A QMRA model was constructed to estimate the disease burden from raw consumption of vegetables (lettuce, cabbage and cucumber) irrigated with treated wastewater. Exposure models were developed and simulated using Monte Carlo analysis using 10,000 iterations per simulation, to account for variability and uncertainty of the model input parameters. Two scenarios were considered for each vegetable: a population that washes vegetables before consumption and a population that does not. Additionally, the impact of prolonging the withhold period, the time between the last irrigation event and harvest, on the output parameters was investigated. Sensitivity analysis was conducted using Spearman Rank-order correlation coefficient analysis, to investigate the influence of uncertainty and variation of input parameters on the risk calculation. The QMRA portion of the work is currently in review at the journal, Water Science and Technology (Amha, 2014). References Amha, Y. (2014). A probabilistic QMRA of Salmonella in direct agricultural reuse of treated wastewater. Wat. Sci. Tech., In review. Brook, M., Al Houqani, H., Darawsha, T., & Achary, M. A. A. (2006). Groundwater Resources: Development & Management in the Emirate of Abu Dhabi, United Arab Emirates. Cai, L., & Zhang, T. (2013). Detecting human bacterial pathogens in wastewater treatment plants by a high-throughput shotgun sequencing technique. Environmental science & technology, 47(10), 5433-5441. Dawoud, M. A., Sallam, O. M., & Abdelfattah, M. A. (2012, April 22-24). Treated wastewater managment and reuse in arid regions: Abu Dhabi case study. Paper presented at the The 10th Gulf water conference: Water in the GCC States The Water-Energy-Food Nexus Doha, Qatar. Environment Agency Abu Dhabi, E. (2009). Abu Dhabi Water Resources Master Plan Frenken, K. (2009). Irrigation in the Middle East region in figures AQUASTAT Survey-2008. Water Reports(34). Kumaraswamy, R., Amha, Y. M., Anwar, M. Z., Henschel, A., Rodríguez, J., & Ahmad, F. (2014). Molecular analysis for screening human bacterial pathogens in municipal wastewater treatment and reuse. Environmental Science & Technology, 48(19), 11610-11619. Petterson, S., Signor, R., Ashbolt, N., & Roser, D. (2006). QMRA methodology. Microrisk Research Project. Statistics Centre - Abu Dhabi (SCAD). (2012). Statistical Yearbook of Abu Dhabi 2011 (pp. 333-337). Abu Dhabi, UAE: SCAD. |
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