68055 ESTIMATING RELATIVE BENEFITS OF DIFFERING STRATEGIES FOR MANAGEMENT OF WASTEWATER IN LOWER EGYPT USING QUANTITATIVE MICROBIAL RISK ANALYSIS (QMRA) World Bank Water Partnership Program Final Report February 2012 This page intentionally left blank ESTIMATING RELATIVE BENEFITS OF DIFFERING STRATEGIES FOR MANAGEMENT OF WASTEWATER IN LOWER EGYPT USING QUANTITATIVE MICROBIAL RISK ANALYSIS (QMRA) A report on research carried out by the School of Civil Engineering, University of Leeds, the World Bank and the Holding Company for Water and Wastewater, Government of Egypt with support from the National Research Centre, Cairo, Egypt World Bank Water Partnership Program Final Report February 2012 © 2012 International Bank for Reconstruction and Development / International Development Association or The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Any queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: pubrights@worldbank.org. Acknowledgements This study was carried out with financial support from the World Bank Water Partnership Program. The principal investigator was Barbara Evans, University of Leeds, and the Task Manager was Param Iyer, World Bank. It presents a practical example of how to operationalize the 2006 WHO Guidelines on the Safe Use of Wastewater, Excreta and Greywater and the recent World Bank Policy Research Paper 5412 Improving Wastewater Use in Agriculture; An Emerging Priority. The Holding Company for Water and Wastewater in Egypt provided staff and access to facilities as well as providing valuable inputs at the review stage. In particular we would like to thank Engineer Mamdouh Raslan, Deputy Chairman, and Engineer Mounir Hosny, Director of the Project Implementation Unit of the Integrated Sanitation and Sewerage Project (ISSIP), for their valuable guidance and support. Many other staff provided invaluable assistance but in particular we would like to acknowledge the contribution of colleagues at the Kafr El Sheikh Water Company for their assistance in conducting field studies at Sidi Salem and El Moufty and providing extremely valuable additional field data. Particular mention should be made of Anwar Halawa, Eatadal El-Argway and Atef Fergany. We would also like to thank colleagues at the National Research Council, in particular Prof Dr Fatima El-Gohary and Prof.Dr. Mohamed Mohamed Kamel, for their assistance in setting up and carrying out the field work for this study. Ms Heba Yaken at the World Bank office in Cairo provided extremely useful inputs and guidance and Mr. Philippe Reymond of the Swiss Technical Institute at EAWAG/SANDEC and based in Cairo provided invaluable support and insights and proved the value of collaboration. Mr. Ahmed Atta acted as the coordinator and made a significant technical contribution. We would also like to thank our reviewers Ms. Suzanne Scheierling, Ms Caroline van den Berg , Mr Lee Travers and Ms Soma Ghosh Moulik at the World Bank and Dr Andy Sleigh at the University of Leeds for their invaluable insights and contributions. However all errors remain our own. Barbara Evans and Param Iyer February 2012 The World Bank Water Partnership Program The Water Partnership Program (WPP) is a multi-donor trust fund established in 2009 and administered by the World Bank’s Water Unit in the Sustainable Development Network. The WPP consolidates two previous programs, the Bank-Netherlands Water Program in Supply and Sanitation (BNWP) and the Bank-Netherlands Water Partnership Program in Water Resource (BNWPP) into an improved realignment and restructuring of these programs. The Program is funded by the governments of the Netherlands, the United Kingdom, and Denmark, for a total contribution of $23.7 million. i|P age This page intentionally left blank ii | P a g e Foreword The Holding Company for Water and Wastewater through its ACs is responsible for the operation and maintenance of the existing facilities to deliver safe water supplies and the management of domestic and industrial wastewater in Egypt. The management of wastewater in particular presents a growing challenge. The country is highly dependent on the water of the Nile for agricultural production. The managed re-use of agricultural runoff from the agricultural drainage network is becoming increasingly important as an input to crop production particularly in the delta region. In this context, the commitment to deliver modern networked sanitation to all householders in the region presents particular challenges. Domestic wastewater contains valuable nutrients which could be useful in crop production but also contains potentially harmful disease-causing pathogens. It is the task of HCWW to identify, develop and manage appropriate sanitation facilities, including wastewater collection networks and treatment plants, so as to ensure that domestic wastewater is treated and disposed of in ways which ensure protection of health. Recognising the potential for reuse of diluted effluents in agricultural drains HCWW are continually looking for ways to optimise the planning and design of wastewater management systems. Modern statistical tools enable the assessment of relative health risks when effluent from treatment plants is discharged into the agricultural drainage network in locations where reuse could have value in the agricultural system. Engineer Mamdouh Raslan, Deputy Chairman Holding Company for Water and Wastewater iii | P a g e This page intentionally left blank iv | P a g e Table of Contents List of Tables .................................................................................................................................... vi List of Figures ................................................................................................................................... vi List of Abbreviations .........................................................................................................................vii 1. INTRODUCTION ......................................................................................................................... 1 2. THE STUDY ................................................................................................................................. 1 Wastewater Reuse and Health....................................................................................................... 1 Aims and Objectives ...................................................................................................................... 2 3. THE CONTEXT ............................................................................................................................ 3 Wastewater Reuse in Egypt ........................................................................................................... 3 Sanitation and Wastewater Treatment .......................................................................................... 3 4. THE APPROACH.......................................................................................................................... 4 Focus on Health Risks .................................................................................................................... 4 Risk Management Strategies ......................................................................................................... 5 5. THE MODEL ............................................................................................................................... 6 Typical Drainage Basin ................................................................................................................... 6 Interventions ................................................................................................................................. 7 Field Test Sites ............................................................................................................................... 7 Calculating Health Risks from Water Quality .................................................................................. 8 6. PARAMETERS FOR USE IN THE MODEL ....................................................................................... 9 Acceptable Additional Risk to Health ............................................................................................. 9 Key Indicator Pathogens ................................................................................................................ 9 On-farm, Post-harvest and In-kitchen Measures to Reduce Health Risks ...................................... 10 Wastewater Treatment Products ................................................................................................. 10 Dilution Options .......................................................................................................................... 10 Cropping Patterns........................................................................................................................ 11 7. RESULTS................................................................................................................................... 11 Downstream Water Quality ......................................................................................................... 11 Effectiveness of Treatment .......................................................................................................... 12 Impact of Sanitation Options on Water Quality ............................................................................ 14 Cost Effectiveness ........................................................................................................................ 16 8. DISCUSSION AND CONCLUSIONS.............................................................................................. 19 Current situation ......................................................................................................................... 19 Effective sanitation options ......................................................................................................... 19 v|P ag e Water and Wastewater Quality Standards ................................................................................... 21 Conclusions and Further Work ..................................................................................................... 22 References ...................................................................................................................................... 24 APPENDIX 1: QMRA ........................................................................................................................ 27 Introduction ................................................................................................................................ 27 Dose-response relationships .................................................................................................... 27 Disease-infection ratios ........................................................................................................... 27 APPENDIX 2: DATA TABLES ............................................................................................................. 29 List of Tables Table 1: Intervention Options used in this research ........................................................................... 7 Table 2: Health protection control measures and associated pathogen reductions .......................... 10 Table 3: Incidence of Fecal Coliforms in Drains and Canals .............................................................. 11 Table 4: Model Parameters for Water and Wastewater Quality ....................................................... 13 Table 5: Parameters for treatment options ...................................................................................... 14 Table 6: Downstream water quality in receiving drain assuming chlorination .................................. 14 Table 7: Median Infection risks from consumption of wastewater-irrigated tomatoes estimated by 10,000-trial Monte Carlo Simulation* .............................................................................................. 15 Table 8: Incidence of diarrhea and DALY burden under various scenarios ....................................... 16 Table 9: Overall reduction in icidence of diarrhoeal disease and DALYs by intervention (20 years) ... 16 Table 10: Unit costs for sanitation interventions .............................................................................. 17 Table 11: Selected Water quality parameters in Law 48/1982.......................................................... 21 Table 12: Water quality parameters considered in the development of water quality indices (WQI)22 Table 13: Water Quality Data – El Moufty El Kobra .......................................................................... 29 Table 14: Water Quality Data – Sidi Salem ....................................................................................... 31 Table 15: Hourly Water Quality Data – El Moufty El Kobra ............................................................... 33 Table 16: Hourly Water Quality Data – Sidi Salem ........................................................................... 33 Table 17: Water Quality Data – Trench/Bayaras............................................................................... 35 List of Figures Figure 1: Balancing context and additional risk .................................................................................. 2 Figure 2: Pathogen flow in the notional drainage basin ...................................................................... 5 Figure 3: Relating incidence of pathogens to health impact in downstream populations ................... 8 Figure 4: Monthly reuse of drainage water in the Nile delta during 2002/2003 (BCM) ..................... 12 Figure 5: Average observed rates of e-coli in study wastewater treatment plants* .......................... 13 Figure 6: 20-year discounted NPV for sanitation options.................................................................. 18 Figure 7: Cost effectiveness of interventions US$ per DALY avoided (log scale) ................................ 18 Figure 8: Cost effectiveness of interventions (excluding household septic tanks) US$ per DALY avoided ........................................................................................................................................... 19 Figure 9: Cost effectiveness of waste stabilization ponds systems of varying sizes (US$ per DALY avoided) .......................................................................................................................................... 21 vi | P a g e List of Abbreviations AS Activated Sludge BCM Billion cubic meter (m3) CER Cost-effectiveness Ratio DALY Disability-adjusted Life Years HCWW Holding Company for Water and Wastewater JMP WHO/UNICEF Joint Monitoring Program for Water and Sanitation MPN Most Probably Number (laboratory method for counting pathogens) NAWQAM National Water Quality and Area Management Project NPV Net Present Value OD Oxidation Ditch OFT On-farm Treatment pppy Per person per year QMRA Quantifiable Microbial Risk Assessment ST Septic Tank UNDP United Nations Development Program UNICEF United Nations Childrens Fund WHO World Health Organization WSP Waste Stabilization Pond WWTP Wastewater Treatment Plant vii | P a g e This page intentionally left blank viii | P a g e 1. INTRODUCTION This report, prepared in collaboration with the World Bank, supported by the Water Partnership Program, and the University of Leeds, lays out an approach, using modern modeling techniques and a statistical tool known as Quantifiable Microbial Risk Assessment, by which the relative effectiveness of different wastewater management strategies can be assessed in terms of optimising health benefits to downstream populations. The report uses a theoretical model of a typical drainage basin, but the approach could be applied to many of the drainage basins managed by the Holding Company for Water and Wastewater in Egypt. The conclusions of the study provide an indication of how such methods could increasingly be used to enable the selection of cost-effective and appropriate wastewater management strategies. The analysis presented here, which make a realistic assessment of relative health risks using robust statistical techniques and empirical information, has the potential to increasingly inform the debate about effluent discharge standards and the management of wastewater and agricultural runoff for reuse in agriculture. 2. THE STUDY Wastewater Reuse and Health Wastewater treatment serves two main purposes; the removal of harmful pathogens from waste with a view to protecting health and the removal of nutrients (significant amongst which are Nitrogen and Phosphorous) from waste to protect the environment. Different wastewater management systems perform these two functions with different degrees of effectiveness and at different costs. Process selection is often a matter of tradeoff between these two objectives since few processes are very effective at both. Many modern high-energy processes focus on nutrient removal and rely on chlorination for pathogen removal. A focus on nutrient removal however removes or makes significantly more costly the capture of these valuable inputs for downstream agriculture. Reuse of treated wastewater which is pathogen-free has significant potential to increase agricultural productivity and reduce reliance on chemical fertilisers. Decisions about wastewater management strategies are a process of balancing costs and effectiveness across these two objectives. The removal of pathogens is a priority where wastewater reuse is common. The transport of pathogens from human excreta back to a human host is one of the primary routes of transmission of significant disease groups, in particular diarrheal disease. The core assumption of this research is that the movement of pathogens from wastewater, via irrigation both directly to farm workers and to consumers of crops, is one of the primary transmission routes for diarrheal disease. In 2005 the UNDP Human Development Report for Egypt stated that “[p]oor water quality affects both health and land productivity with damage costs estimated …. to have reached LE 5.35 billion …. or 1.8% of GPD in 2003� (UNDP, 2005). The study makes use of the framework laid down in the WHO Guidelines for the Safe Use of Wastewater, Excreta and Greywater – Volume 2; Wastewater Use in Agriculture published in 2006, along with the 2010 update also published by WHO. The value of the 2006 WHO guidelines lies in the fact that this increased health impact can be calculated in the context of downstream conditions 1|P a ge including current disease burden and the likely pathways by which people will be exposed to contaminated wastewater (see for example Figure 1). A major advantage of the ‘relative risk’ approach taken in the 2006 WHO guidelines is that they encourage progressive measures to reduce risk of exposure to microbial hazards in contrast to earlier approaches which were more binomial in nature (either meeting or failing to meet rigid standards). This approach allows for different strategies to reduce risk exposure to be assessed. The use of normative tools such as Disability-adjusted Life-Years (DALYs) or disease incidence rates as a measure of disease burden associated with known levels of risk further allows for a direct comparison between different risk-reduction strategies. Figure 1: Balancing context and additional risk Additional Context risk Source: Authors illustration For example, in Ghana, non-treatment options such as improved irrigation practices at the farm and post-harvest handling and treatment of crops have been explored alongside more conventional approaches to improve wastewater treatment to assess the most cost-effective strategies to reduce diarrheal disease incidence in urban areas (Seidu & Drechsel, 2010). That study compared the “health gains in terms of diarrheal disease reduction [with the] cost of treatment and non-treatment interventions associated with wastewater irrigation in Ghana� (Seidu & Drechsel, 2010)p. 263. Aims and Objectives This study set out to assess the relative health impacts of different wastewater management strategies on health in the Nile delta region using an approach similar to that used in the Ghana case study mentioned above. The ultimate objective was to develop a framework for long-term investment planning based on monitoring of health and productivity impacts of proposed Bank operations which could be included in Project M&E systems. This would equip Task Teams to assess the risks and opportunities which 2|P a ge arise due to the proposed shift from on-site to networked sanitation in four governorates where the Bank has wastewater operations. A secondary objective was to assess the extent to which existing legislation supports health risk- based planning. 3. THE CONTEXT Wastewater Reuse in Egypt Egypt is highly dependent on reuse of agricultural drainage water for irrigation. In 2002/3 it was estimated that 4.3 billion m3 (BCM) of drainage water were being used in the delta region and Fayoum through official reuse projects, and this was set to rise to around 7.6BCM on completion of further planned drainage projects (Mostafa, El-Gohary, & Shalby, Date Unknown). Unofficial reuse is generally estimated to be considerably higher. There are several water quality issues relating to agricultural reuse of drainage water.  Firstly, salinity and concentrations of naturally-occurring pollutants in irrigation water can rise to unacceptable levels due to the effects of evaporation and consequent concentration in residual flows.  Secondly, the biochemical characteristics of the drainage water can be adversely affected by the inflow of unregulated domestic and industrial wastewaters and the effluent from wastewater treatment plants. However, from a health perspective, high concentrations of harmful pathogens are of greatest concern. According to some observers “…the major problem regarding drainage water quality is not salinity, but chemical and bacteriological pollution…� (Mostafa, El-Gohary, & Shalby, Date Unknown) p.98. This report focuses on the health implications of pathogenic contamination of agricultural drainage water which is reused in agriculture. Sanitation and Wastewater Treatment The main sources of pathogenic contamination in the agricultural channels are livestock wastes from cattle sheds and fields, industrial discharges (tanneries and dairies presenting particular challenges) and informal discharges of human excreta from onsite sanitation systems. By presidential decree (Presidential Decree 135/2004), all households in Egypt are guaranteed individual connections to networked sewerage for their sanitation services. Disposal of wastewater into irrigation channels is not officially permitted and the discharge of treated domestic wastewater into such agricultural channels is strictly regulated (Government of Egypt, 1982). In theory therefore, all sewerage connections should be made to wastewater treatment facilities. A major objective of The Holding Company for Water and Wastewater (HCWW) is to increase the rate of connection to sewerage and to develop new wastewater treatment capacity. Progress towards this objective has been relatively slow. Between 1990 and 2008 rates of access to improved sanitation (essentially a hygienic toilet) in the rural areas of Egypt rose from 57% to 92% but rates of sewerage connection were around 18% in 2008 and between 2005 and 2008 progress 3|P a ge appears to have virtually stagnated (WHO/UNICEF Joint Monitoring Program for Water and Sanitation, 2010) and (WHO/UNICEF Joint Monitoring Program on Water and Sanitation, 2011). Many rural households have onsite vaults which are emptied between two to four times per month due to high water tables (World Bank, 2008). Most of this effluent is either used directly on the fields or discharged into agricultural drains and canals without treatment. In Gharbeya, Kafr El Sheikh and Beheira Governorates for example there are some 15 wastewater treatment plants serving the larger agglomerations, but most are running well below capacity and do not serve the majority of the population. A survey carried out in Gharbeya, Kafr El Sheikh and Beheira in 2007 reported that while 88% of households had latrines, 48% were connected to septic tanks. Thirty- nine percent were deemed to be ‘unsanitary’ (implying that the pits or tanks were not providing adequate storage or protection) and 12% of households had no toilet at all. Of those families with septic tanks or cess pits, 25% of households in Beheira reported that these were emptied directly into agricultural drains or canals, while 44% in Kafr El Sheikh reported that they were emptied into the canal (EcoConServ, 2007). Informal private operators provide emptying services and dispose of wastes in both irrigation channels and drainage channels. Thus the Nile delta has a high prevalence of poorly-managed onsite sanitation facilities, low rates of connectivity to wastewater treatment facilities and is cris-crossed by a network of agricultural canals and drains. None of the water companies in Lower Egypt are able to guarantee 100% collection and treatment of domestic wastewater. Significant volumes of untreated domestic wastewater and discharges from wastewater treatment facilities that are operating under-capacity are therefore discharged into the agricultural drainage system and significant volumes of the resultant mixed drain water are certainly used for irrigation in downstream areas. This undoubtedly exposes agricultural workers downstream to health risks (Abd El Lateef, Hall, Lawrence, & Negm, 2006). 4. THE APPROACH Focus on Health Risks The research examined the relative health risks associated with different wastewater management strategies in a ‘typical’ drainage basin in the delta region. The study focused on the health risks associated with the use of untreated and treated wastewater lifted from agricultural drains and canals downstream of a notional drainage basin. Inflow to the drainage basin was considered to be wastewater flows from houses, plus the flow in a notional drain. Health risks in downstream areas are a function of water quality and farming practices. In Egypt, particularly in the Nile delta region, most wastewater is discharged into agricultural drains either directly or via the sewerage/ wastewater treatment network. The resultant water quality in downstream channels therefore depends primarily on the;  Baseline water quality and flow upstream of the sanitation system under consideration  Rate and quality of water discharging via sewerage and wastewater treatment system 4|P a ge  Rate and quality of water discharging outside the sewerage/ wastewater treatment system (from domestic onsite systems and unregulated commercial discharges). Figure 2 shows how pathogens flow from households to farm workers and consumers. Figure 2: Pathogen flow in the notional drainage basin Production of wastewater at the household (connected and non-connected households) Sewer connection and Wastewater treatment Bayara and no treatment plant Discharge With dilution in agricultural drain Direct application Exposure to contaminated wastewater on the farm Additional on-farm, post-harvest and in-kitchen No additional precautions precautions Additional burden of disease associated with reuse of wastewater Source: Authors illustration On the left is what could be called the “low-risk transmission route� which involves collection of household waste in a sewer, its treatment at an appropriate treatment plant, dilution in an agricultural drain or canal prior to re-use, and the deployment of appropriate on-farm, post harvest and in-kitchen interventions, all of which minimize the risk of transmission of disease. On the right is a notional “high-risk transmission route� where untreated waste is applied directly to the field and there are no on-farm, post-harvest, or in-kitchen interventions. The actual situation is a blend of these two extremes along with a number of “medium-risk� transmission routes utilizing some but not all of the precautionary measures shown on the left hand side of Figure 2. Risk Management Strategies Reductions in risks associated with reuse of wastewater can broadly be achieved in three ways: (a) diversion of wastewater flows from low-treatment to high-treatment facilities prior to discharge; (b) improved levels of treatment in existing facilities; and 5|P a ge (c) improved on-farm and post-harvest practices. The focus of current investment strategies in the Nile Delta region is primarily on:  rehabilitating existing treatment plants;  commissioning new treatment plants; and  construction of new sewer networks. As long as connectivity rates to the sewer network remain low none of these strategies is likely to reduce health risks to downstream agricultural workers or consumers. Furthermore little work has been done to assess the performance of existing treatment processes on removal of the key pathogens responsible for adverse health impacts. In reality, there are additional wastewater management options which could be considered and which might have additional merit in terms of health benefits. These include:  providing alternative (or additional) treatment steps at the household or wastewater treatment plant level;  creating incentives for higher rates of connectivity to the existing sewer networks;  increasing formal septage collection rates from onsite sanitation systems and delivery to wastewater treatment facilities thereby reducing discharge of untreated wastes;  modification of downstream agricultural practices; or  a combination of these strategies. The study set out to explore the impacts of these strategies by modeling the overall flow of pathogens through a single drainage basin, using a combination of theoretical and field-based data. The study explored likely current and future scenarios and examined a range of interventions and their impact on downstream health outcomes. 5. THE MODEL Typical Drainage Basin The study made use of a simple mass-balance model of a ‘typical’ drainage basin or sanitation area. It explored how the various streams of waste, treated to difference levels, impact on water quality downstream. To give maximum flexibility the model allowed for a range of scenarios to be explored. Five categories of households were defined and each household in the notional basin was assigned to one of these categories:  Category I: Connected via sewer to Wastewater Treatment Plant (WWTP) - Oxidation Ditch or Activated Sludge process  Category II: Connected via simplified sewer to WWTP - Waste Stabilization Pond  Category III: Not connected to sewer – using improved anaerobic treatment and secondary polishing),e ach system shared between three households  Category IV: Not connected to sewer – using effective septic tank, one per household 6|P a ge  Category V: Not connected (no facilities or utilizing a bayara or trench to collect household waste) At the start the model was set up using a ‘typical scenario’ for the delta region; 88% of households using poorly-functioning household facilities (known as bayaras or trenches) and the remaining 12% connected to either a centralized oxidation ditch system or a centralized activated sludge system which was assumed to be working at 50% capacity. Interventions For simplicity, the model considered that wastewater from already-connected households (category I) would remain with the same treatment option. Only households currently NOT connected to the network and having no treatment (category VI) were considered as having potential to move. Various interventions were modeled (Table 1). In each case it was assumed that new sewer connections would be made to the existing treatment plant to bring it up to full capacity. For the remaining households one of six possible interventions was considered. The model then calculated the worst-case scenario for downstream water quality assuming typical upstream values in the receiving drainage water. Table 1: Intervention Options used in this research Intervention Category Comment shift 1. Convert Bayaras to septic V to IV This option assumes the provision of onsite tank facilities. It would be enhanced by the addition of well regulated and properly financed collection services. Proprietary all-in- one systems would provide better protection from groundwater infiltration 2. Improved Bayaras to V to IV This option assumes provision of shared provide anaerobic facilities (one per three households). It would treatment and secondary be enhanced by the addition of well regulated polishing and properly financed collection services. 3. Connect Bayara households V to III Requires construction and operation of to WSP WWTP sewerage or incentives for septage to be 4. Connect Bayara households VI to II delivered to WWTP. Sewerage may require to oxidation ditch or pumping so costs will be modeled with and activated sludge WWTP without pumping. WSPs may be decentralized or centralized. 5. On-farm and post-harvest - Non-infrastructure intervention with behavior interventions change 6. Convert Bayaras to septic VI to V tank or shared anaerobic plus Infrastructure plus behavior change process with polishing behavior intervention PLUS on-farm and post- change harvest interventions Source: Authors summary of model scenarios Field Test Sites To help link the model to conditions on the ground, two locations were selected for detailed field study. These were Sidi Salem, an oxidation ditch treatment plant with extended aeration in Kafr-El 7|P a ge Sheikh Governorate, and El-Moufty El-Kobra Waste-stabilization Pond plant in the same area. Water quality testing was carried out in these two sites over the period between December 2010 and February 2011. Data from the field-testing was used to calibrate the model. Calculating Health Risks from Water Quality Quantifiable microbial risk assessment (QMRA) is a tool which can be used to help operationalize the 2006 WHO guidelines on reuse of wastewater agriculture (World Health Organisation, 2006). It does this by determining a numerical value of the risk (or probability) of a disease or infection occurring as a result of an individual being exposed to a specified number of a particular pathogen. Provided dose-response data are available QMRA can be used to estimate disease and infection risks which accrue to downstream populations who come into contact with contaminated wastewater in a range of ways for any pathogen. Figure 3 shows the logical relationship between incidence of pathogens and health impacts. In order to calculate health impacts the dose-response equation, disease-infection ratio and the impact in terms of ill-health and death must be known or estimated. QMRA then allows the probable health impacts from exposure to certain pathogens to be calculated. Further information on QMRA techniques is summarized in Appendix 1. Mara (2010) and Mara, Hamilton and Sleigh (2010) provide full details of QMRA techniques for assessing health risks associated with wastewater reuse. Figure 3: Relating incidence of pathogens to health impact in downstream populations Incidence of key pathogens Dose-response equation Infection risk Disease-infection ratio Disease risk YLL and YDL Health impact Source: Authors illustration 8|P a ge 6. PARAMETERS FOR USE IN THE MODEL Acceptable Additional Risk to Health A key step in the process was to establish an acceptable level of additional risk to health over baseline conditions associated with the use in agriculture of wastewater, either directly used or after mixing in downstream drains and canals. Using Quantifiable Microbial Risk Analysis (QMRA), this acceptable additional risk of certain disease types, could then be converted into reference standards for incidence of key pathogens in irrigation water applied at the field level. Health risk is expressed in terms of DALYs, a measure which combines both mortality and morbidity to calculate the overall impact of a disease or disease group (see Box 1 ). In this study a maximum tolerable additional DALY loss of 10-4 per person per year was used following the publication of the WHO Update to the 2006 Guidelines (World Health Organisation, 2006). This corresponds to an additional disease risk of 10-2. For an individual this is “equivalent to an additional episode of diarrheal disease every 100 years� (ibid.) over and above generalized diarrheal disease incidence which globally is equivalent to two episodes every three years. Box 1: Disability-adjusted Life Years (DALYs) DALYs are a measure of the health of a population or burden of disease due to a specific disease or risk factor. DALYs attempt to measure the time lost because of disability or death from the disease compared with a long life free of disability in the absence of the disease. DALYs are calculated by adding the years of life lost due to premature death (YLL) to the years lived with a disability (YLD). Years of life lost are calculated from age-specific mortality rates and the standard life expectancies of a given population. YLD are calculated from the number of cases of the disease multiplied by its average duration and a severity factor ranging from 1 (death) to 0 (perfect health) based on the disease − for example, watery diarrhea has a severity factor from 0.09 to 0.12, depending on the age group. DALYs are an important tool for comparing health outcomes because they account for not only acute health effects but also for delayed and chronic effects − i.e., they include both morbidity and mortality. When risk is described in DALYs, different health outcomes (e.g., fatal cancers and non-fatal diarrheal diseases) can be compared and risk management decisions can be prioritized. Source: (World Health Organisation, 2006) Key Indicator Pathogens Diarrheal disease is caused by a wide range of pathogens. The 2006 guidelines propose the following indicator organisms when considering risks from wastewater reuse in agriculture: Rotavirus, Campylobacter, e-Coli, Cryptosporidium and Ascaris In 2010, WHO noted that norovirus is the major viral pathogen causing diarrhea in adults while rotavirus mainly affects children under 5. Since adults are more likely to face exposure due to wastewater use than children, norovirus is a better indicator pathogen than rotavirus. However, due to the lack of appropriate sampling and testing facilities near to the field test sites rotavirus, e-coli and ascaris were taken as the key indicator organisms in this study. 9|P a ge On-farm, Post-harvest and In-kitchen Measures to Reduce Health Risks Since irrigation in Egypt is usually practiced by means of flooding the fields, most of the usual on- farm precautions are not available (use of drip irrigation, watering cans etc). The only option considered in the model is the use of pathogen die-off through ensuring a time delay between irrigation and harvesting. Post-harvest (overnight storage of harvested crops and special preparation of crops for market) was considered but in-kitchen preparation options were not. A summary of the relevant post-harvest interventions are shown in Table 2. Table 2: Health protection control measures and associated pathogen reductions Control Measure Pathogen reduction Comments (log units) On-farm Options Crop restrictions (no food crops eaten 6-7 Excluded - hard to enforce, uncooked) depends on crop prices On-farm treatment - Three tank system 1-2 - Simple sedimentation 0.5-1 Excluded due to lack of - Simple filtration 1-3 space Application methods - Furrow irrigation 1-2 Excluded due to prevalence - Low-cost drip irrigation 2-4 of flood irrigation - Reduction of splashing 1-2 Pathogen die-off 0.5-2 per day Included Post-harvest options at local markets Overnight storage in baskets 0.5-1 Included Produce preparation - Rinsing salad crops with clean water 1-2 - Washing with running tap water 2-3 Excluded – hard to enforce - Removing outer leaves of lettuces etc 1-3 In-kitchen preparation methods - Disinfection 2-3 - Peeling 2 Excluded – behavior - Cooking 5-6 change hard to enforce Based on (Mara, Hamilton, Sleigh, & Karavarsamis, 2010) Wastewater Treatment Products A review of the literature found limited information relating to the health implications of application of wastewater sludge from wastewater treatment processes in Egypt. For this reason, the sludge stream was not included in the analysis and only wastewater effluent from treatment plants was included. This would tend to have the effect of underestimating health risks associated with all the wastewater treatment plant options considered. For the onsite options, the quality of the mixed slurry including liquid and solid fractions was considered. Dilution Options The conditions of the channel downstream of the treatment plant or where untreated waste is discharged are a key determinant of the likely quality of water reused in agriculture. Effluent is discharged into drains of varying size – from major drainage channels to minor ditches. The quality of water in the downstream receiving water body is also important in determining how significant 10 | P a g e any contamination caused by the effluent will be. The model therefore allowed for varying flow and varying water quality in the receiving drain. Resultant concentrations of pathogens in water for reuse were calculated using a simple mass-balance calculation. No assumptions for pathogen die-off were included. Cropping Patterns The model has the potential to examine health impacts on a range of cropping outcomes. The typical Egyptian diet contains a significant element of grains and meat, none of which represent significant transmission risks for pathogens from wastewater due to the processing involved in their preparation. The diet does however contain a significant volume of tomatoes (estimated consumption 99kg/capita/ year) and grapes (17 kg/capita/year) (Arab Republic of Egypt, 2009) . Since detailed data on tomato preparation are not available, the assumption is made that 50% of the total consumption of tomatoes and all of the grapes are consumed uncooked. Contamination from this consumption pattern is assumed to be via consumption of water from the crop surface. Ingestion of contaminated soil attached to the crop is considered to be marginal. 7. RESULTS Downstream Water Quality Data from the field observations and a review of previous studies confirmed that the quality of water in receiving drains is extremely poor in the Delta region (see Appendix 2). Incidence of Ascaris and Rotavirus is highly variable (probably reflecting infection rates in the command areas of the plants under study) and the performance of the plants in removing pathogens was also mixed. There have been numerous studies that have analyzed and modeled water quality in various drains and canals in the delta region. Few of these provide detailed information on pathogenic contamination. Work carried out in preparation for the World Bank’-supported Integrated Sanitation and Sewerage Infrastructure Project (ISSIP) however noted very “high pollution loads as a result mainly of sewage and industrial wastewater discharges� (EcoConServ, 2007). This finding confirmed earlier extensive monitoring of the Nile system (DAI and IRG, June 2003) which noted that “total coliform bacteria reach 106 MPN/11ml …in many drains in the delta which is considerably higher than the Egyptian standard of 5000 MPN/100ml.� A selection of data from Gharbeya and Kafr El Sheikh are shown below. Table 3: Incidence of Fecal Coliforms in Drains and Canals Location Observed Value Mit Yazid Canal >10,000 MPN/100ml Mit Yazid Command >60,000 MPN/100ml Area Drains Mahmoudia Canal >100,000 MPN/100ml System Drains Source: (EcoConServ, 2007) Most observers comment that the highest concentrations of most water quality parameters occur during the winter time (El Sayad & Abdel Gawad, September 2001). This finding was confirmed by a study of the incidence of parasite eggs in drain water where incidence appeared to be higher in the 11 | P a g e autumn and winter months (August-January) than in spring and summer (Stott, Jenkins, Shabana, & May, 1997). This higher concentration of pathogens in the winter coincides with the period of minimum flow. Seasonal variation in reuse for example is high with peak reuse flows in the period from June to September coinciding with the peak summer season (Figure 4) and the lowest rates in January and February. Figure 4: Monthly reuse of drainage water in the Nile delta during 2002/2003 (BCM) 0.8 0.7 0.6 0.5 Western delta 0.4 Middle delta 0.3 Eastern delta 0.2 0.1 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Source: (Mostafa, El-Gohary, & Shalby, Date Unknown) Overall the literature confirmed that there are high levels of pathogenic contamination in the canal and drain network. Likely sources include both domestic waste discharged directly from household septic tanks and cess pits, discharge of partially treated wastes from treatment plants and industrial effluent discharges. Information on the quality of wastewater and the incidence of our key indicator pathogens is drawn from the field testing carried out as part of this project and cross checked with data from earlier field studies ( (Stott, Jenkins, Shabana, & May, 1997), (El Gohary, El-Hawarry, Badr, & Rashed, 1996) (Sherief, El-S Easa, El-Samra, & Mancy, 1996). A summary of the data used for the model is shown in Table 4. Effectiveness of Treatment The waste stabilization pond at El Moufty El Kobra appeared to be functioning well below its design capability during the period of this study. This was confirmed by field observations to be caused by contamination of the sewer network from a dairy operation within the community. Visual observations confirmed heavy algal growth in all the ponds and possibly overloading which may have been exacerbated due to high levels of animal excreta in the influent. At Sidi Salem, as would be expected, the removal of pathogens upstream of the chlorination system was relatively poor, and even below the chlorinator some pathogens remained suggesting some inefficiencies in the process. 12 | P a g e Table 4: Model Parameters for Water and Wastewater Quality Model Parameter Raw Wastewater (Bayara) e-Coli 2.00E+07 (/100ml) Rotavirus 1.00E+05 (/100ml) Ascaris 3 nr/liter Raw Sewage e-Coli 1.00E+07(/100ml) Rotavirus 1.00E+04(/100ml) Ascaris 3 nr/liter Receiving Drain Water e-Coli 4.00E+02(/100ml) Rotavirus 1.00E+01(/100ml) Ascaris 0 nr/liter Source: Authors summary estimates Figure 5: Average observed rates of e-coli in study wastewater treatment plants* e-coli 1.00E+08 1.00E+07 1.00E+06 1.00E+05 1.00E+04 1.00E+03 1.00E+02 1.00E+01 1.00E+00 5ENC 3FP1 3FP2 1WW 1WW 2AB1 2AB2 4MP1 4MP2 9CDD 6EC 9CDD 8CM 8CM 9CD 7CU 7CU Ave Ave El-Mofti El-Kobra Sidi Salem Source: Field study data *See Appendix 2 for a detailed breakdown. WW= wastewater influent, AB=Anaerobic Basin, FP=Facultative Pond, MP= Maturation Pond, CU=Drain upstream of WWTP discharge point, CM = drain at mixing point, CDD = drain downstream of mixing point, ENC= effluent upstream of chlorination, EC = effluent downstream of chlorination The baseline scenario is thus very poor. A high percentage of wastewater is reaching drains untreated, drains are in poor condition generally to begin with, and pathogen removal at the existing treatment plants is not particularly effective. Using both the field observations and literature, typical treatment efficiencies for the options under consideration were used in the model assuming that treatment processes were working to their full potential for Egyptian conditions (see Table 5). 13 | P a g e Table 5: Parameters for treatment options Effectiveness of Treatment Log reduction rates Activated Waste Anaerobic Septic tank Sludge/ stabilization treatment oxidation pond and polishing ditch Upstream of chlorination e-Coli 0.44 3 3 2 Rotavirus 0 2 2 2 Ascaris 0 2 2 2 At Chlorination e-Coli 3 n/a n/a n/a Rotavirus 3 n/a n/a n/a Ascaris 2 n/a n/a n/a Source: Authors summary estimates Impact of Sanitation Options on Water Quality The project model reconfirmed the observed results for the Baseline scenario in the context of the model drainage basin. Downstream water quality was then calculated under the study scenarios and the results are shown in Table 6 which indicates the worst quality water that would result under each intervention. Table 6: Downstream water quality in receiving drain assuming chlorination Intervention Baseline 1 2 3 4 5 6 Mixed drain water total fecal unit/100ml 1.E+08 1.E+06 1.E+05 3.E+04 3.E+04 4.E+04 1.E+06 coliforms e-coli unit/100ml 2.E+07 1.E+05 1.E+04 3.E+03 3.E+03 4.E+03 2.E+05 Rotavirus unit/100ml 1.E+05 1.E+02 1.E+02 8.E+01 9.E+01 1.E+02 1.E+03 Ascaris unit/100ml 3.E+00 8.E-01 8.E-01 8.E-01 9.E-01 1.E+00 3.E-02 Sludge total kg/day 9.E+02 9.E+02 1.E+03 5.E+03 6.E+03 1.E+04 9.E+02 volume total fecal MPN/day 9.E+11 9.E+11 1.E+12 9.E+11 2.E+12 1.E+13 9.E+09 coliforms Source: Study results Incidence of Ascaris is low (and this is reinforced by findings in the literature) (Stott, Jenkins, Shabana, & May, 1997) but it has been included in the analysis because of its relative importance with respect to onsite sanitation systems. The main health impacts however are associated with Rotavirus infection which remains a significant health risk in Egypt (Khoury, Ogilvie, El Khoury, Duan, & Goetghebeur, 2001). 14 | P a g e Table 7 shows the results for QMRA simulations of health risks associated with exposure to rotavirus as a function of exposure to all fecal coliforms (for a longer discussion on this method see (Mara, Sleigh, Blumenthal, & Carr, 2007)). Table 7: Median Infection risks from consumption of wastewater-irrigated tomatoes estimated by 10,000-trial Monte Carlo Simulation* Wastewater Quality (e- Median Infection risks coli per 100ml) associated with rotavirus pppy 107 - 108 1 106 - 107 1 105- 106 0.96 104 - 105 0.28 103 - 104 3.2E-02 102 - 103 3.1E-03 10 – 102 3.2E-04 1 – 10 3.34E-05 Source: Results of simulations using (Mara & Sleigh, QMRA: A Beginners Guide - Monte carlo simulation programmes, 2008) *375g of raw tomato eaten per person per 2 days; 3.5–4ml wastewater remaining on 375g tomato after irrigation; 0.1–1 rotavirus per 105 e. coli; 1022–1023 rotavirus die-off between harvest and consumption; ID50 ¼ 6.7 ^ 25% and a ¼ 0.253 ^ 25% for rotavirus. The acceptable marginal health risk is 10-2 (See above and also (Mara, Sleigh, Blumenthal, & Carr, 2007) gives a target wastewater quality at the farm gate (for irrigation workers) or at market (for consumers of crops) of the order of 103 total FC per 100ml. Based on the median wastewater quality experienced in the downstream drains under baseline conditions a total reduction in pathogens of the order of 106 is required to achieve this acceptable level of risk. Using the QMRA to assess the impact on downstream health of exposure to irrigated crops Table 8 indicates the annual incidence of disease in the affected population. It is worth noting here the very conservative assumption which is that only the population in the command sanitation basin under consideration consumes crops irrigated there. In reality crops are likely to be exported to urban areas and the affected population is likely to be greater than that shown here. Table 8 shows that some of the proposed interventions could have a significant positive impact on health. Improved on-farm and post-harvest management of food crops could reduce diarrheal incidence by more than 90%, preventing more than 2.5 million diarrhea cases in the area over 20 years (for a population of around 225,000 people) when combined with improvements to the design and operation of onsite sanitation systems. Networked sewerage with treatment also has a significant impact on health but in the case of activated sludge and oxidation ditches this is highly dependent on effective and continuous chlorination. The overall health impact, expressed in diarrheal disease incidence in the total population is summarized in Table 9. 15 | P a g e Table 8: Incidence of diarrhea and DALY burden under various scenarios Scenario Baseline 1 2&3 4 5 6 Disease Risk pppy Rotavirus 1.00E+00 9.90E-01 2.40E-01 2.75E-01 9.90E-01 9.00E-02 Cryptosporidium 1.80E-01 1.70E-02 1.45E-03 1.65E-03 1.70E-02 2.00E-04 Ascaris 3.00E-04 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00 Disease incidence (cases per year) Rotavirus 225,000 222,750 54,000 61,875 222,750 20,250 cryptosporidium 40,500 3,825 326 371 3,825 45 Ascaris 68 0 0 0 0 0 Total 265,568 226,575 54,326 62,246 226,575 20,295 REDUCTION 0% 15% 80% 77% 15% 92% DALYs (cases per year) rotavirus* 5,850 5,792 1,404 1,609 5,792 527 cryptosporidium 61 6 0 1 6 0 Ascaris 1 0 0 0 0 0 Total 5,911 5,797 1,404 1,609 5,797 527 REDUCTION 0% 2% 76% 73% 2% 91% */1 DALY loss per case of disease Rotavirus: 2.6E-2; Cryptosporidium 1.5E-3; (Mara & Bos, Risk Analysis and Epidemiology; The WHO 2006 Guidelines for Safe Use of Wastewtater in Agriculture, 2010) Ascaris 8.25E-3 ( (Mara D. D., Hamilton, Sleigh, Karavarsamis, & Seidu, 2010) */2assume children under 2 not consuming irrigated crops Source: Model results Table 9: Overall reduction in icidence of diarrhoeal disease and DALYs by intervention (20 years) Scenario ddi DALY Annual Total Annual Total reduction reduction reduction reduction 1 38,993 779,850 114 2,281 2&3 211,241 4,224,825 4,507 90,136 4 203,321 4,066,425 4,302 86,040 5 38,993 779,850 114 2,281 6 245,273 4,905,450 5,385 107,695 Source: Model results Cost Effectiveness Cost data for the various options was assembled from project reports and cross checked with data included in the Egyptian Guidelines on Rural Sanitation (Chemonics Egypt, Ahmed Gaber and Associates, 2006). Unit costs were assessed for typical systems of a reference size since the unit costs of sewerage networks and wastewater treatment systems do vary with the size and distribution of the population served. Typical values were selected for this analysis, but more 16 | P a g e detailed comparisons could be made for particular cases on the ground. The cost data are summarized in Table 10. These unit costs were converted to 20-year lifecycle costs assuming discount rate of 8%. Net present values were then calculated for each option (Figure 6). Using these data, costs of the notional interventions could be compared to the 20-year health impacts computed from the data in Table 8. Cost-effectiveness ratios for each option are shown in Figure 7 against a logarithmic scale. Figure 7 shows that replacing septic tanks with no additional treatment improvements is significantly less cost-effective than other ‘engineered’ solutions. Figure 8 therefore shows only the engineered solutions against a linear scale. Table 10: Unit costs for sanitation interventions Unit Capital costs Annual Operational costs (per unit) Connections Design EGP US$ EGP US$ population Household/ cluster options Network 0 0 0 0 0 Septic tank 1 5 600 101 150 25 Anaerobic Treatment plus 3 15 750 126 200 34 Polish Decentralized options Network 1,000 5,000 4,000,000 670,017 60,000 10,050 Waste stabilization 1,000 5,000 500,000 83,752 25,000 4,188 pond (WSP) Centralized options Network 10,000 50,000 40,000,000 6,700,168 600,000 100,503 Network with 10,000 50,000 40,000,000 6,700,168 4,000,000 670,017 pumping Waste stabilization 10,000 50,000 2,500,000 418,760 250,000 41,876 pond (WSP) Activated sludge/ 10,000 50,000 12,500,000 2,093,802 2,500,000 418,760 oxidation ditch On farm practices (36 months) 3,000,000 502,513 120,000 20,101 Source: Authors estimates based on ISSIP project documents and cross checked with (Chemonics Egypt, Ahmed Gaber and Associates, 2006) 17 | P a g e Figure 6: 20-year discounted NPV for sanitation options OFT plus ST OFT AS/OD with pumping AS/OD Centralised WSP with pumping Centralised WSP Decentralised WSP Anaerobic treatment plus polishing Improved septic tanks $- $50 $100 $150 $200 $250 $300 Source: Model results OFT – On-farm treatment; AS/OD = Activated Sludge or Oxidation Ditch; WSP = Waste Stabilization Pond Figure 7: Cost effectiveness of interventions US$ per DALY avoided (log scale) Improved septic tanks +OFT OFT AS/OD with pumping AS/OD Centralised WSP with pumping Centralised WSP Decentralised WSP Anaerobic treatment plus polishing Improved septic tanks $1 $10 $100 $1,000 $10,000 Source: Model results OFT – On-farm treatment; AS/OD = Activated Sludge or Oxidation Ditch; WSP = Waste Stabilization Pond 18 | P a g e Figure 8: Cost effectiveness of interventions (excluding household septic tanks) US$ per DALY avoided Improved septic tanks +OFT OFT AS/OD with pumping AS/OD Centralised WSP with pumping Centralised WSP Decentralised WSP Anaerobic treatment plus polishing $0 $100 $200 $300 $400 $500 $600 $700 OFT – On-farm treatment; AS/OD = Activated Sludge or Oxidation Ditch; WSP = Waste Stabilization Pond 8. DISCUSSION AND CONCLUSIONS Current situation The data and model all confirm that the most significant health risk is posed by the un-regulated dumping of waste from poorly-performing household cess pits and septic tanks. It is worth noting here that discharges from industrial units have not been included in this analysis, but this could be incorporated relatively easily. In the drainage basins observed during this study however visual observation suggests that dumping of the contents of domestic systems is a significant contributory factor in polluting the drains. Furthermore, some domestic waste may be being dumped into secondary and tertiary drainage/ irrigation channels and recycled for irrigation without dilution. Effective sanitation options Currently the focus of much HCWW investment is on the construction of additional treatment capacity. However the mass –balance modeling carried out here along with an analysis of potential water treatment options suggests that other, lower cost, alternatives may have equal importance and more potential in the short term to reduce health risks to downstream irrigators. The most effective treatment intervention was the replacement of faulty household septic tanks/ cess pits, with effective primary and secondary treatment. This could be provided through neighborhood anaerobic systems with polishing or proprietary household septic tanks which are properly constructed and managed. 19 | P a g e Even where centralized systems are preferred in the long run improvements to onsite sanitation represent an important and cost-effective short-term intervention that could have significant health implications. Furthermore household facilities could take advantage of more flexible approaches to finance, with households bearing a greater share of the upfront costs; willingness to pay to reduce the inconvenience of the current system of bayaras which need to be emptied frequently. Improved management of onsite systems could be a very useful focus of wastewater management strategies in the delta. Waste stabilization ponds also provide good health protection and are not reliant on the operation of chlorinators for pathogen removal. Surprisingly, the available field data and data from the literature along with the modeling did not suggest that the Extended Aeration Oxidation ditches and Activated Sludge plants have a significant impact in terms of achieving required health targets unless effective chlorination could be guaranteed; field observations suggest this is not the case at present. Furthermore the analysis presented here excludes the health implications of managing sludge products from these plants – the cost and risks associated with sludge handling make these options even less attractive than is suggested by our analysis. More significantly, almost all infrastructure interventions were bettered by changes in on-farm and post-harvest behaviors in terms of cost-effective health protection. This is an intervention which should not be ignored. The costs of aerated systems are extremely high when compared to ponds because of the high operational costs of the former when energy prices are properly calculated. Ponds are considered to be expensive due to their higher land take, but at flow rates up to around 20,000m3 per day, the Rural Sanitation Guidelines suggest that they are better value for money over their operational lifetime (Chemonics Egypt, Ahmed Gaber and Associates, 2006). The relative cost-effectiveness of all the treatment processes is highly dependent on their scale. Like most networks with treatment processes, centralization has a positive effect on unit costs up to a point. Decentralized waste stabilization ponds for example are more costly than centralized systems using the same treatment (Figure 9) if we assume that per capita operational costs for the sewer network remain equal. If however community management of at least some part of the operation of the system is viable and advantageous for other reasons, then decentralized options become more financially attractive. Furthermore the use of smaller systems could obviate the need for pumping which is the single most effective way of bringing down unit costs and reducing the long term financial burden on the water companies. 20 | P a g e Figure 9: Cost effectiveness of waste stabilization ponds systems of varying sizes (US$ per DALY avoided) DC 10000 DC8000 DC6000 DC4000 DC2000 DC1000 DC500 DC100 $130 $135 $140 $145 $150 $155 $160 $165 $170 $175 Source: Model results Note: Y axis values indicate the number of connections per system under consideration. Water and Wastewater Quality Standards Until recently, legislation relating to reuse of agricultural drainage water was extremely restrictive. It is based on Egyptian Water Protection Law 48/1982 Articles 65 and 68 respectively. Table 11: Selected Water quality parameters in Law 48/1982 Parameter Standard TDS 2000 mg/l DO >4mg/l Temperature <35°C Ph 6-9 TDS 2000mg/l TSS 50mg/l BOD 60mg/l NO2 1mg/l NO3 45mg/l Phosphate 1mg/l The National Water Quality and Availability Management Program (NAWQAM) developed two composite indicators for water quality based on the standards. Table 12 shows the parameters considered in the development of these indices. 21 | P a g e Table 12: Water quality parameters considered in the development of water quality indices (WQI) Parameter WQI-65 WQI-68 TDS Yes Yes DO Yes Yes Fecal Coliform Yes Yes Temperature Yes Yes pH Yes Yes Turbidity Yes Yes BOD Yes No NO3 Yes No Phosphate Yes No Source: (NAQWAM, 2001) NAWQAM went on to carry out extremely valuable monitoring and analysis of water quality in selected drains and to assess the impact of WWTPs on water quality. However, Table 12 shows the very high number of parameters that must be considered when assessing drain water quality irrespective of the downstream context in which drainage water will be reused. The conclusion of the study on the Hados drain was that ‘most WWTPs operating within the study area violate the Egyptian law 48/1982’. The study further went on to conclude that ‘the most appropriate treatment technique in the Delta of Egypt is the activated sludge process. Trickling filters and oxidation ponds may also be used’ (NAQWAM, 2001). This final conclusion suggests that the use of composite parameters may place a much stronger emphasis on nutrient removal than on the removal of pathogens that are harmful to human health since the activated sludge process tends to be more effective at the former than the latter (Jimenez, Mara, Carr, & Brissaud, 2010). Some observers have noted that the new National Code for wastewater reuse issued in 2000 is “less restricted� than previous legislation (notably Decree 44). The National Code allows for a consideration of standards and levels of treatment alongside monitoring and analysis of cropping patterns, irrigation methods and health protection measures. This approach is more in line with the latest guidelines for WHO on safe use of wastewater, excreta and greywater (World Health Organisation, 2006) which take a risk-minimization approach rather than the earlier approach of setting absolute targets for a range of water quality parameters. Use of this more flexible approach opens up the opportunity for a more nuanced analysis of investment strategies – with more emphasis on achieving optimum outcomes in terms of both health protection and nutrient re-use when considering agricultural applications of treated, partially treated and untreated wastewater. Such an approach might result in rather different conclusions than those reached by the NAQWAM team. Conclusions and Further Work The study explored the likely health impacts of wastewater management and sanitation investments in the Delta region of Egypt. Overall the study found that conventional approaches to sanitation management, and in particular the preference for centralized wastewater treatment processes with extended aeration many not always offer the most cost-effective solution in terms of health protection. While these options will remain an important part of the solution, health considerations as well as the need to keep operational costs as low as possible suggest that other more modern approaches may offer a better solution. These might include a blend of onsite sanitation 22 | P a g e improvements, including the use of proprietary prefabricated septic tanks, better management and financial arrangements for emptying of septic tanks and pits and some decentralized and centralized wastewater treatment. The study developed a modeling approach which combines simple assessments of impacts on downstream water quality with QMRA to assess broad health impacts. The approach, while relatively simple and easy to carry out, would be improved with more detailed location-specific data and in particular more information on downstream irrigation and harvesting practices for key crops. Further work would enhance the value and accuracy of the model used as real cost data from operational systems could progressively be included to provide a more accurate assessment particularly of operational costs. Field testing of key indicator pathogens could usefully be scaled up as there is limited data currently available with which the efficacy of existing treatment processes in terms of health protection can be assessed. 23 | P a g e References Abd El Lateef, E., Hall, J. E., Lawrence, P. C., & Negm, M. S. (2006). Cairo-East bank Effluent Reuse Study – Effect of Field Crop Irrigation with Secondary Treated Wastewater on Biological and Chemical properties of Soil and Groundwater. Biologica, Bratislava , 16/ Suppl. Arab Republic of Egypt. (2009). Sustainable Agricultural Development Strategy Towards 2030. Cairo: Ministry of Agriculture and Land Reclamation. Chemonics Egypt, Ahmed Gaber and Associates. (2006). Guidelines on Rural Sanitation. Cairo, Ehypt: Danida Environmental Sector Program. DAI and IRG. (June 2003). Nile River Water Quality Management Study, Report Number 67. Cairo: Ministry of Water Resources and Irrigation, USAID. EcoConServ. (2007). Environmental and Social Impact Assessment Framework; Integrated Sanitation and Sewerage Infrastructure Project (ISSIP). Cairo: Holding Company for Water and Wastewater. El Gohary, F., El-Hawarry, S., Badr, S., & Rashed, Y. (1996). Wastewater treatment and reuse for aquaculture. Wat. Sci. Tech. Vol 32 Nr 11 , 127-136. El Sayad, A., & Abdel Gawad, S. T. (September 2001). Wastewater Reclamation and Reuse Potential in Rural Areas of Egypt. International Wrokshop on Wastewater Reuse Management. Seoul: ICID. El-Deeb Ghazy, M. M., El-Senousy, W. M., Abdel-Aatty, A. M., & Kamel, M. (2008). Performacne Evaluation of a Waste Stabilisation Pond in a Rural Area of Egypt. American Journal of Environmental Sciences , 4(4): 316-325. Government of Egypt. (1982). Law 48: Nile River and Watercourses Protection Law. Cairo. Hendy, S. M. (2006). Wastewater Management and Reuse in Egypt. Regional Workshop on Health Aspects of Wastewater Reuse in Agriculture. Amman, Jordan. Holding Company for Water and Wastewater. (2008). National Sanitation Strategy. Cairo. Jimenez, B., Mara, D. D., Carr, R., & Brissaud, F. (2010). Wastewater treatment for pathogen removal and nutrient conservation: suitable systems for use in developing countries. In P. Dechsel, C. A. Scott, L. Rashid-Ali, M. Redwood, & A. Bahri, Wastewater Irrigation and Health; Assessing and Mitigating Risk in Low-income Countries. USA: IDRC and IWMI. Khoury, H., Ogilvie, I., El Khoury, A. C., Duan, Y., & Goetghebeur, M. M. (2001). Burden of Rotavirus Gastroenteritis in the Middle Eastern and North African Pediatric Population. BMC Infectious Disesases , 11:9. Mara, D. D. (2010). Quantiative Microbial Risk Analysis: the 2006 WHO Guidelines and Beyond - An Introduction. Washington DC: World Bank. Mara, D. D., & Bos, R. (2010). Risk Analysis and Epidemiology; The WHO 2006 Guidelines for Safe Use of Wastewtater in Agriculture. In P. Drechsel, C. Scott, L. Raschid-Sally, M. Redwood, & A. Bahri, Wastewater Reuse and Health: Assessing and Mitigating Risk in Low Income Countries. London: Earthscan. 24 | P a g e Mara, D. D., & Sleigh, P. A. (2008). QMRA: A Beginners Guide - Monte carlo simulation programmes. Retrieved May 12, 2011, from School of Civil Engineering, University of Leeds: http://www.personal.leeds.ac.uk/~cen6ddm/QMRAbeginners.html Mara, D. D., Hamilton, A., Sleigh, A., Karavarsamis, N., & Seidu, R. (2010). Tools for Risk Analysis: Updating teh 2006 WHO Guidelines. In P. Drechsel, C. Scott, L. Raschid-Sally, M. Redwood, & A. Bahri, Wastewater Irrigation and Health: Assessing and Mitigating Risk in Low Income Countries. London: Earthscan. Mara, D. D., Sleigh, P. A., Blumenthal, U. J., & Carr, R. A. (2007). Health risks in wastewater irrigation: Comparing estimates from Quantiative Microbial Risk Analysis and Epidemiological Studies. Journal of Water and Health , 5:1. Mara, D., Hamilton, A., Sleigh, P. A., & Karavarsamis, N. (2010). Discussion Paper: Options for updating the 2006 Guidelines. Geneva: World Health Organisation. Ministry of Housing. (2000). Decree 44, Article 15: Egyptian Standards for Effluent Quality and the Conditions for Reuse. Cairo: Government of Egypt. Mostafa, H., El-Gohary, F., & Shalby, A. (Date Unknown). Reuse of Low Quality Water in Egypt. NAQWAM. (2001). National Water Quality Monitoring Project Bulletin Nr.1. Scheierrling, S. M., Bartone, C., Mara, D. D., & Drechsel, P. (2010). Improving Wastewater Use in Agriculture; An Emerging Priority - World Bank Policy Research Working Paper 5412. Washington DC: World Bank . Seidu, R., & Drechsel, P. (2010). Cost-effectiveness analysis of interventions for diarrhoeal disease reduction among consumers of wastewater-irrigation lettuce in Ghana. In P. Drechsel, C. A. Scott, L. Rashid-Ali, M. Redwood, & A. Bahri, Wastewater Irrigation and Health; Assessing and Mitigating Risk in Low-income Countries. USA: IDRC and IWMI. Sherief, M. M., El-S Easa, M., El-Samra, M. I., & Mancy, K. H. (1996). A Demonsrtation of Wasgteater Treatment for Resuse Applications in Fish Production and Irrigation in Suez, Egypt. Wat. Sci. Tech. Vol 32, Nr 11 , 137-144. Shuval, H. I., Avner, A., Badri Fal Eliyahu, R., & Perez, Y. (1986). Integrated Resource Recovery; Wastewater Irrigation in Developing Countries - Health Effects and Technical Solutions. Washington DC: World Bank. Stenstrom, T. R., Seidu, R., Ekane, N., Zurbrugg, C., & Tilly, E. (2010). Microbial Exposure and Health ASsessments in Sanitation Systems. Stockholm: Stockholm Environment Institute. Stott, R., Jenkins, T., Shabana, M., & May, E. (1997). A Survey of the Microbial Quality of Wasteaters in Ismailia, Egypt and the Implications for Wastewater Reuse. Wat.Sci.Tech Vol.35, No.11-12 , 211- 217. UNDP. (2005). Water and Sanitation; the Silent Emergency - Policy Brief Nr. 7 Egypt Human Development Report. 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Bull World Health Organ , Vol 18 No 3. 26 | P a g e APPENDIX 1: QMRA Introduction Quantifiable microbial risk assessment (QMRA) is a tool which can be used to help operationalize the 2006 WHO guidelines on reuse of wastewater agriculture (World Health Organisation, 2006). It does this by determining a numerical value of the risk (or probability) of a disease or infection occurring as a result of an individual being exposed to a specified number of a particular pathogen. Provided dose-response data are available QMRA can be used to estimate disease and infection risks which accrue to downstream populations who come into contact with contaminated wastewater in a range of ways for any pathogen. Figure 3: Relating incidence of pathogens to health impact in downstream populations in the main text shows the logical relationship between incidence of pathogens and health impacts. In order to calculate health impacts the dose-response equation, disease-infection ratio and the impact in terms of ill-health and death must be known or estimated. Dose-response relationships Infection risk from a single exposure to a particular pathogen is computed using a dose-response equation. Mara gives the following approach to estimating disease and infection risk using one of the following two QMRA dose-response equations (Mara, 2010): Exponential dose-response equation (commonly used for protozoan pathogens): PI(d) = 1 − e−rd (1) (b) Beta-Poisson dose-response equation (commonly used for viral and bacterial pathogens): (2) where PI(d) is the risk of infection in an individual from a single exposure to (here, the ingestion of) a single pathogen dose d; N50 is the median infective dose (i.e., the value of d that causes infection in 50% of the exposed population); and α and r are pathogen ‘infectivity constants’. The annual risk of infection is given by: PI(A)(d) = 1 – [1 – PI(d)]n (3) where PI(A) (d) is the annual risk of infection in an individual from n exposures per year to the single pathogen dose d. Disease-infection ratios Not all infections however result in disease. The risk of disease, as opposed to the risk of infection, is given by: PD(d) = aPI(d) (4) 27 | P a g e where PD(d) is the risk of disease in an individual from a single exposure to the single pathogen dose d; and a is the disease/infection ratio (i.e., the proportion of the infected population that becomes clinically ill (thus the value of a is in the range 0−1). Mara goes on to discuss how these values of risk (probability) expressed per person per exposure event can be translated into an annual infection risk – i.e. the percentage chance an individual has of becoming infected as a result of n exposures per year. Since the values of N50 and α are subject to some uncertainty Monte Carlo (MC) risk simulation is used to provide a more robust solution to QMRA calculations (for further information on MC simulation see for example Mara, 2010). QMRA can thus be used to compute risk of disease. 28 | P a g e APPENDIX 2: DATA TABLES Table 13: Water Quality Data – El Moufty El Kobra Total Coliforms e-Coli Site Date Location (NRC) (NRC) Rotavirus Helminths El-Moufty El-Kobra 26/12/2010 1WW 2.00E+08 7.00E+07 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 1WW 4.80E+08 2.60E+07 0 2.00E+00 El-Moufty El-Kobra 27/01/2011 1WW 4.80E+08 1.80E+07 1.00E+05 1.00E+00 El-Moufty El-Kobra 21/02/2011 1WW 1.10E+08 1.10E+07 1.00E+04 3.00E+00 El-Moufty El-Kobra Ave 1WW 3.18E+08 3.13E+07 0 0 El-Moufty El-Kobra 26/12/2010 2AB1 2.40E+07 3.10E+06 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 2AB1 1.50E+07 1.60E+06 0 0.00E+00 El-Moufty El-Kobra 27/01/2011 2AB1 1.10E+07 2.10E+05 1.00E+04 1.00E+00 El-Moufty El-Kobra 21/02/2011 2AB1 1.60E+07 1.30E+05 1.00E+04 1.00E+00 El-Moufty El-Kobra Ave 2AB1 1.65E+07 1.26E+06 0 0 El-Moufty El-Kobra 26/12/2010 2AB2 2.80E+07 2.30E+06 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 2AB2 1.10E+07 1.10E+06 0 0.00E+00 El-Moufty El-Kobra 27/01/2011 2AB2 3.10E+06 4.60E+06 1.00E+05 0.00E+00 El-Moufty El-Kobra 21/02/2011 2AB2 2.80E+06 2.60E+05 1.00E+04 0.00E+00 El-Moufty El-Kobra Ave 2AB2 1.12E+07 2.07E+06 0 0 El-Moufty El-Kobra 26/12/2010 3FP1 2.10E+06 1.50E+05 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 3FP1 6.80E+05 1.40E+05 0 0.00E+00 El-Moufty El-Kobra 27/01/2011 3FP1 4.10E+05 1.00E+05 1.00E+04 0.00E+00 El-Moufty El-Kobra 21/02/2011 3FP1 3.10E+05 4.80E+04 1.00E+03 0.00E+00 El-Moufty El-Kobra Ave 3FP1 8.75E+05 1.10E+05 0 0 El-Moufty El-Kobra 26/12/2010 3FP2 9.30E+06 7.00E+05 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 3FP2 4.10E+06 2.80E+05 0 0.00E+00 El-Moufty El-Kobra 27/01/2011 3FP2 4.80E+05 4.60E+04 1.00E+04 0.00E+00 29 | P a g e Total Coliforms e-Coli Site Date Location (NRC) (NRC) Rotavirus Helminths El-Moufty El-Kobra 21/02/2011 3FP2 1.60E+05 6.80E+04 1.00E+03 0.00E+00 El-Moufty El-Kobra Ave 3FP2 3.51E+06 2.74E+05 0 0 El-Moufty El-Kobra 26/12/2010 4MP1 7.00E+05 1.20E+04 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 4MP1 1.50E+05 1.30E+04 0 0.00E+00 El-Moufty El-Kobra 27/01/2011 4MP1 7.40E+04 1.30E+04 1.00E+04 0.00E+00 El-Moufty El-Kobra 21/02/2011 4MP1 4.20E+04 4.10E+03 1.00E+02 0.00E+00 El-Moufty El-Kobra Ave 4MP1 2.42E+05 1.05E+04 0 0 El-Moufty El-Kobra 26/12/2010 4MP2 2.80E+05 1.60E+04 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 4MP2 2.60E+05 1.80E+04 0 0.00E+00 El-Moufty El-Kobra 27/01/2011 4MP2 4.60E+04 6.90E+03 1.00E+03 0.00E+00 El-Moufty El-Kobra 21/02/2011 4MP2 3.80E+04 6.10E+03 1.00E+03 0.00E+00 El-Moufty El-Kobra Ave 4MP2 1.56E+05 1.18E+04 0 0 El-Moufty El-Kobra 26/12/2010 7CU 1.20E+02 1.30E+01 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 7CU 1.10E+02 4.20E+01 0 1.00E+00 El-Moufty El-Kobra 27/01/2011 7CU 1.00E+02 5.10E+01 1.00E+01 0.00E+00 El-Moufty El-Kobra 21/02/2011 7CU 1.30E+02 3.40E+01 0.00E+00 0.00E+00 El-Moufty El-Kobra Ave 7CU 1.15E+02 3.50E+01 0 0 El-Moufty El-Kobra 26/12/2010 8CM 7.00E+04 4.60E+03 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 8CM 1.30E+04 1.10E+03 0 0.00E+00 El-Moufty El-Kobra 27/01/2011 8CM 6.80E+03 1.80E+03 1.00E+03 0.00E+00 El-Moufty El-Kobra 21/02/2011 8CM 4.60E+03 4.60E+02 1.00E+02 0.00E+00 El-Moufty El-Kobra Ave 8CM 2.36E+04 1.99E+03 0 0 El-Moufty El-Kobra 26/12/2010 9CDD 2.30E+02 1.80E+02 0 0.00E+00 El-Moufty El-Kobra 09/01/2011 9CDD 2.10E+02 1.00E+02 0 0.00E+00 30 | P a g e Total Coliforms e-Coli Site Date Location (NRC) (NRC) Rotavirus Helminths El-Moufty El-Kobra 27/01/2011 9CDD 2.40E+02 1.20E+02 1.00E+02 0.00E+00 El-Moufty El-Kobra 21/02/2011 9CDD 1.80E+02 1.00E+02 0.00E+00 0.00E+00 El-Moufty El-Kobra Ave 9CDD 2.15E+02 1.25E+02 0 0 Table 14: Water Quality Data – Sidi Salem Total Coliforms e-Coli Site Date Location (NRC) (NRC) Rotavirus Helminths Sidi Salem 26/12/2010 1WW 1.20E+08 7.00E+07 0 1.00E+00 Sidi Salem 09/01/2011 1WW 3.10E+08 4.60E+07 0 0.00E+00 Sidi Salem 27/01/2011 1WW 1.50E+08 2.70E+07 0.00E+00 0.00E+00 Sidi Salem 21/02/2011 1WW 1.10E+07 1.80E+06 0.00E+00 4.00E+00 Sidi Salem Ave 1WW 1.48E+08 3.62E+07 0 0 Sidi Salem 26/12/2010 5ENC 2.30E+06 6.40E+05 0 1.00E+00 Sidi Salem 09/01/2011 5ENC 4.10E+05 6.40E+04 0 0.00E+00 Sidi Salem 27/01/2011 5ENC 6.10E+05 4.60E+04 0.00E+00 1.00E+00 Sidi Salem 21/02/2011 5ENC 3.80E+05 2.80E+04 0.00E+00 2.00E+00 Sidi Salem Ave 5ENC 9.25E+05 1.95E+05 0 0 Sidi Salem 26/12/2010 6EC 7.00E+04 7.20E+03 0 1.00E+00 Sidi Salem 09/01/2011 6EC 6.20E+03 7.10E+02 0 0.00E+00 Sidi Salem 27/01/2011 6EC 4.30E+03 3.80E+02 0.00E+00 0.00E+00 Sidi Salem 21/02/2011 6EC 2.30E+03 1.30E+02 0.00E+00 0.00E+00 Sidi Salem Ave 6EC 2.07E+04 2.11E+03 0 0 Sidi Salem 26/12/2010 7CU 3.00E+02 1.20E+02 0 0.00E+00 Sidi Salem 09/01/2011 7CU 1.60E+03 1.60E+02 0 0.00E+00 31 | P a g e Total Coliforms e-Coli Site Date Location (NRC) (NRC) Rotavirus Helminths Sidi Salem 27/01/2011 7CU 4.80E+02 1.40E+02 0.00E+00 0.00E+00 Sidi Salem 21/02/2011 7CU 2.60E+02 9.00E+01 0.00E+00 0.00E+00 Sidi Salem Ave 7CU 6.60E+02 1.28E+02 0 0 Sidi Salem 26/12/2010 8CM 4.60E+03 1.10E+03 0 0.00E+00 Sidi Salem 09/01/2011 8CM 1.10E+03 3.10E+02 0 0.00E+00 Sidi Salem 27/01/2011 8CM 1.10E+03 2.10E+02 0.00E+00 0.00E+00 Sidi Salem 21/02/2011 8CM 4.80E+02 2.00E+02 0.00E+00 0.00E+00 Sidi Salem Ave 8CM 1.82E+03 4.55E+02 0 0 Sidi Salem 26/12/2010 9CD 1.80E+03 4.10E+02 0 0.00E+00 Sidi Salem 09/01/2011 9CD 4.10E+02 1.60E+02 0 0.00E+00 Sidi Salem 27/01/2011 9CD 3.20E+03 1.10E+02 0.00E+00 0.00E+00 Sidi Salem 21/02/2011 9CD 2.10E+02 1.10E+02 0.00E+00 0.00E+00 Sidi Salem Ave 9CD 1.41E+03 1.98E+02 0 0 Sidi Salem 26/12/2010 9CDD 3.70E+02 1.60E+02 0 0.00E+00 Sidi Salem 09/01/2011 9CDD 2.10E+02 1.20E+02 0 0.00E+00 Sidi Salem 27/01/2011 9CDD 1.00E+02 3.10E+02 0.00E+00 0.00E+00 Sidi Salem 21/02/2011 9CDD 1.10E+02 1.00E+02 0.00E+00 0.00E+00 Sidi Salem Ave 9CDD 1.98E+02 1.73E+02 0 0 32 | P a g e Table 15: Hourly Water Quality Data – El Moufty El Kobra Total Coliforms e-Coli Site Location Time (NRC) (NRC) El-Moufty El-Kobra 1WW 1415 3.10E+08 4.10E+07 El-Moufty El-Kobra 1AP2 1415 4.60E+05 6.30E+04 El-Moufty El-Kobra 1WW 1515 2.60E+08 1.60E+07 El-Moufty El-Kobra 1AP2 1515 2.30E+05 4.10E+04 El-Moufty El-Kobra 1WW 1615 2.10E+08 1.80E+07 El-Moufty El-Kobra 1AP2 1615 4.10E+04 1.20E+04 El-Moufty El-Kobra 1WW 1715 6.70E+07 7.20E+06 El-Moufty El-Kobra 1AP2 1715 1.10E+04 3.20E+03 El-Moufty El-Kobra 1WW 1815 3.50E+07 2.40E+06 El-Moufty El-Kobra 1AP2 1815 2.10E+04 2.60E+03 Table 16: Hourly Water Quality Data – Sidi Salem Total Coliforms e-Coli Site Location Time (NRC) (NRC) Sidi Salem 1WW 700 2.60E+08 2.10E+07 Sidi Salem 5ENC 700 1.20E+06 3.10E+04 Sidi Salem 6EC 700 1.10E+03 4.10E+02 Sidi Salem 1WW 800 4.10E+08 6.80E+07 Sidi Salem 5ENC 800 3.10E+05 1.10E+04 Sidi Salem 6EC 800 1.20E+03 1.00E+02 Sidi Salem 1WW 900 3.40E+08 4.10E+07 Sidi Salem 5ENC 900 9.80E+05 6.70E+04 Sidi Salem 6EC 900 4.40E+03 4.70E+02 Sidi Salem 1WW 1000 2.80E+07 1.10E+07 33 | P a g e Total Coliforms e-Coli Site Location Time (NRC) (NRC) Sidi Salem 5ENC 1000 1.10E+05 2.10E+04 Sidi Salem 6EC 1000 1.00E+03 1.10E+02 Sidi Salem 1WW 1100 4.10E+08 1.30E+06 Sidi Salem 5ENC 1100 2.10E+06 2.60E+04 Sidi Salem 6EC 1100 3.10E+03 4.10E+02 Sidi Salem 1WW 1200 2.10E+07 4.30E+06 Sidi Salem 5ENC 1200 1.20E+04 6.40E+03 Sidi Salem 6EC 1200 2.60E+02 1.00E+02 Sidi Salem 1WW 1300 1.10E+08 4.10E+07 Sidi Salem 5ENC 1300 7.50E+06 2.10E+05 Sidi Salem 6EC 1300 6.90E+03 3.20E+02 Sidi Salem 1WW 1400 2.60E+07 1.70E+06 Sidi Salem 5ENC 1400 1.80E+05 1.14E+02 Sidi Salem 6EC 1400 6.40E+03 1.70E+02 Sidi Salem 1WW 1500 1.80E+08 2.80E+06 Sidi Salem 5ENC 1500 2.60E+04 2.30E+03 Sidi Salem 6EC 1500 1.00E+02 9.00E+01 Sidi Salem 1WW 1600 2.30E+07 4.60E+06 Sidi Salem 5ENC 1600 4.50E+04 1.20E+04 Sidi Salem 6EC 1600 2.30E+02 1.00E+02 Sidi Salem 1WW 1700 1.60E+08 2.30E+06 Sidi Salem 5ENC 1700 3.40E+04 1.80E+03 Sidi Salem 6EC 1700 1.40E+02 9.00E+01 Sidi Salem 1WW 1800 4.20E+07 2.60E+05 Sidi Salem 5ENC 1800 3.70E+04 1.70E+03 34 | P a g e Total Coliforms e-Coli Site Location Time (NRC) (NRC) Sidi Salem 6EC 1800 1.30E+02 8.00E+01 Table 17: Water Quality Data – Trench/Bayaras Total Coliforms e-Coli Command Area (NRC) (NRC) Sidi Salem 4.10E+09 1.20E+08 Sidi Salem 2.60E+08 3.10E+06 Sidi Salem 3.20E+08 4.10E+07 Sidi Salem 1.70E+08 2.10E+07 Sidi Salem 6.10E+08 1.60E+07 Sidi Salem 4.20E+07 2.10E+06 Sidi Salem 3.90E+07 2.30E+06 El-Moufty El-Kobra 4.30E+08 1.20E+00 El-Moufty El-Kobra 6.10E+08 3.10E+07 El-Moufty El-Kobra 2.80E+07 1.10E+06 El-Moufty El-Kobra 2.10E+08 4.30E+06 El-Moufty El-Kobra 6.30E+07 2.80E+06 35 | P a g e 36 | P a g e