<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">JEP</journal-id><journal-title-group><journal-title>Journal of Environmental Protection</journal-title></journal-title-group><issn pub-type="epub">2152-2197</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/jep.2016.711122</article-id><article-id pub-id-type="publisher-id">JEP-71155</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  An Integrated Approach to Evaluate Benefits and Costs of Wastewater and Solid Waste Management to Improve the Living Environment: The Citarum River in West Java, Indonesia
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>S.</surname><given-names>M. Kerstens</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>G.</surname><given-names>Hutton</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>I.</surname><given-names>Firmansyah</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>I.</surname><given-names>Leusbrock</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>G.</surname><given-names>Zeeman</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff4"><addr-line>AEE INTEC, Gleisdorf, Austria</addr-line></aff><aff id="aff3"><addr-line>Sub-Department of Environmental Technology, Wageningen University, Wageningen, The Netherlands</addr-line></aff><aff id="aff2"><addr-line>UNICEF, New York, USA</addr-line></aff><aff id="aff1"><addr-line>Royal HaskoningDHV, Amersfoort, The Netherlands</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>sjoerd.kerstens@rhdhv.com(SMK)</email>;<email>ghutton@unicef.org(GH)</email>;<email>indra.firmansyah@wur.nl(IF)</email>;<email>i.leusbrock@aee.at(IL)</email>;<email>grietje.zeeman@wur.nl(GZ)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>11</day><month>10</month><year>2016</year></pub-date><volume>07</volume><issue>11</issue><fpage>1439</fpage><lpage>1465</lpage><history><date date-type="received"><day>July</day>	<month>26,</month>	<year>2016</year></date><date date-type="rev-recd"><day>Accepted:</day>	<month>October</month>	<year>8,</year>	</date><date date-type="accepted"><day>October</day>	<month>11,</month>	<year>2016</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
   
   Absence of wastewater and solid waste facilities impacts the quality of life of many people in developing countries. Implementation of these facilities will benefit public health, water quality, livelihoods and property value. Additional benefits may result from the potential recovery of valuable resources from wastewater and solid waste, such as compost, energy, phosphorus, plastics and paper. Improving water quality through implementation of wastewater and solid waste interventions requires, among others, an analysis of i) sources of pollution, ii) mitigating measures and resource recovery potentials and their effect on water quality and health, and iii) benefits and costs of interventions. We present an integrated approach to evaluate costs and benefits of domestic and industrial wastewater and solid waste interventions. To support a policy maker in formulating a cost and environmentally effective approach, we quantified the impact of these interventions on 1) water quality improvement, 2) resource recovery potential, and 3) monetized benefits versus costs. The integration of technical, hydrological, agronomical and socio-economic elements to derive these three tangible outputs in a joint approach is a novelty. The approach is demonstrated using the heavily polluted Indonesian Upper Citarum River in the Bandung region. Domestic interventions, applying simple (anaerobic filter) technologies, were economically most attractive with a benefit cost ratio (BCR) of 3.2, but could not reach target water quality standards. To approach the target water quality, both advanced domestic (nutrient removal systems) and industrial wastewater treatment interventions were required, leading to a BCR of 2. We showed that benefits from selling recovered resources represent here an additional driver for improving water quality and outweigh the additional costs for resource recovery facilities. While included benefits captured some of the major items, these may have been undervalued. Based on these findings, water quality interventions justify their costs and are socially and economically beneficial. 
  
 
</p></abstract><kwd-group><kwd>Sanitation</kwd><kwd> Water Quality Modeling</kwd><kwd> Economic Cost Benefit Analysis</kwd><kwd>  Resource Recovery</kwd><kwd> Asia</kwd><kwd> Indonesia</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Nearly 40% of the population in developing countries lacks access to improved sanitation facilities [<xref ref-type="bibr" rid="scirp.71155-ref1">1</xref>] , while an estimated 90% of all wastewater in developing countries is discharged untreated directly into rivers, lakes or the oceans [<xref ref-type="bibr" rid="scirp.71155-ref2">2</xref>] . Although access to improved sanitation facilities in South East Asia has reached 72%, Indonesia is lagging behind with only 61% [<xref ref-type="bibr" rid="scirp.71155-ref1">1</xref>] . Moreover, Indonesia, like other developing countries, largely lacks solid waste management services and suffers from uncontrolled discharge of industrial wastewater [<xref ref-type="bibr" rid="scirp.71155-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref4">4</xref>] . The absence of domestic and industrial wastewater and solid waste facilities is associated with a number of impacts.</p><p>First, discharge of untreated sewage can lead to adverse health effects on individuals [<xref ref-type="bibr" rid="scirp.71155-ref5">5</xref>] . Health conditions can be improved by wastewater and hygiene interventions [<xref ref-type="bibr" rid="scirp.71155-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref7">7</xref>] . Reference [<xref ref-type="bibr" rid="scirp.71155-ref8">8</xref>] showed that E. coli concentrations in canals could be substantially reduced (~4 log) by sewage collection and treatment. On-site sanitation (e.g. pit latrines as commonly applied in Indonesia) in combination with shallow ground water sources and high population density may also impact public health [<xref ref-type="bibr" rid="scirp.71155-ref9">9</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref10">10</xref>] .</p><p>Second, discharge of untreated wastewater increases nitrogen (N), phosphorus (P) and organic pollutants (Chemical oxygen demand (COD) and Biological Oxygen Demand (BOD)) loads to water bodies. This may result in eutrophication and low oxygen levels in waters, thus impacting ecosystem functioning [<xref ref-type="bibr" rid="scirp.71155-ref11">11</xref>] - [<xref ref-type="bibr" rid="scirp.71155-ref14">14</xref>] . Domestic pollution depends on living conditions and type of residential areas [<xref ref-type="bibr" rid="scirp.71155-ref15">15</xref>] - [<xref ref-type="bibr" rid="scirp.71155-ref17">17</xref>] . There is also a positive correlation between imperviousness and urban density on pollution gradients in receiving water bodies [<xref ref-type="bibr" rid="scirp.71155-ref18">18</xref>] . A range of wastewater and solid waste systems exists and their feasibility can be linked to residential features [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] (see Online Supplementary Information (OSI), Section 1). Wastewater and solid waste systems range from conventional (e.g. solid waste landfilling) to those that reduce, reuse and recycle (3R) solid waste components or recover resources from wastewater [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref20">20</xref>] . Industrial wastewater discharge may also contribute significantly to water pollution [<xref ref-type="bibr" rid="scirp.71155-ref14">14</xref>] . Applicable treatment technologies depend on type of industry, biodegradability, toxicity, robustness, effluent standards or reuse requirements [<xref ref-type="bibr" rid="scirp.71155-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref22">22</xref>] . Water quality is further affected by agricultural activities, as a result of fertilizer use, aquaculture and livestock emissions [<xref ref-type="bibr" rid="scirp.71155-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref23">23</xref>] .</p><p>Third, the value of recoverable resources from wastewater and solid waste, such as energy, water, organics, nutrients, plastic and paper is frequently neglected, whereas the sale of recovered resources can assure long-term operational and financial sustainability [<xref ref-type="bibr" rid="scirp.71155-ref24">24</xref>] - [<xref ref-type="bibr" rid="scirp.71155-ref28">28</xref>] . The potential demand for recovered resources depends on agricultural activities and possibilities to replace conventional production processes using virgin materials by processes using recyclables (paper and plastics) [<xref ref-type="bibr" rid="scirp.71155-ref29">29</xref>] .</p><p>Finally, the absence of wastewater and solid waste facilities may accrue socio-economic impacts, such as travel and waiting time for community or public toilet facilities, loss of social capital and equity and decreased property values [<xref ref-type="bibr" rid="scirp.71155-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref30">30</xref>] - [<xref ref-type="bibr" rid="scirp.71155-ref33">33</xref>] .</p><p>Thus, implementation of wastewater and solid waste interventions benefits public health, the environment, resource conservation, the economy and people’s welfare. However, given that implementation of interventions involves costs in the form of investments, operation and maintenance of the facilities, policy makers need to understand the outcomes (benefits) of major actions in relation to their costs [<xref ref-type="bibr" rid="scirp.71155-ref34">34</xref>] . The Benefit Cost Ratio (BCR) describes benefits of intervention relative to its costs. Given that benefits may require a long time to manifest and planned infrastructure are designed for long lifetimes, benefit-cost analysis should use a time horizon of at least 20 years [<xref ref-type="bibr" rid="scirp.71155-ref35">35</xref>] . A demonstrated BCR of one or more―indicating a return on investment of at least 1.0 given the discount rate used―can feed into advocacy efforts to raise funding from governments and households, and can convince the private sector to invest [<xref ref-type="bibr" rid="scirp.71155-ref32">32</xref>] .</p><p>Individual cause-effect relationships to evaluate the costs and benefits to improve water quality have been established, such as: 1) the effect of pollution load on the quality of receiving water [<xref ref-type="bibr" rid="scirp.71155-ref13">13</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref18">18</xref>] , 2) the effect of sanitation on public health improvement and reduced discharged pollution loads [<xref ref-type="bibr" rid="scirp.71155-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref36">36</xref>] , 3) economic losses as a result of poor sanitation [<xref ref-type="bibr" rid="scirp.71155-ref32">32</xref>] , and 4) technical and financial feasibility of wastewater and solid waste technologies [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] . However, no integrated framework exists in the scientific literature that quantifies the effect of applicable wastewater and solid waste interventions on 1) water quality, 2) resource recovery potential, and 3) monetized benefits and costs. This paper therefore proposes to use a combination of methods that describe these individual cause-effect relationships, and synthesize them to produce these three tangible outputs. This multi-methods approach allows policy makers to make well-informed choices in wastewater and solid waste planning.</p><p>The developed approach can be used on any river basin or delta. In this paper, the Upper Citarum River in West Java (Indonesia) is used as a case study because of its very low water quality combined with its impact on the life of millions of people downstream (see <xref ref-type="fig" rid="fig1"><xref ref-type="fig" rid="fig">Figure </xref>1</xref> and OSI Section 2).</p></sec><sec id="s2"><title>2. Materials and Methods</title><p>To assess the impact of wastewater and solid waste interventions on water quality and estimate resource recovery and economic returns, the following six consecutive steps were formulated (<xref ref-type="fig" rid="fig2"><xref ref-type="fig" rid="fig">Figure </xref>2</xref>). In step 1 the river water quality at different locations was</p><fig id="fig1"  position="float"><label><xref ref-type="fig" rid="fig1"><xref ref-type="fig" rid="fig">Figure </xref>1</xref></label><caption><title> Location of the Upper Citarum River basin (in box) within the Citarum basin</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x2.png"/></fig><fig id="fig2"  position="float"><label><xref ref-type="fig" rid="fig2"><xref ref-type="fig" rid="fig">Figure </xref>2</xref></label><caption><title> Approach applied to determine the BCR of interventions (Dashed blocks show activities for which a sensitivity analysis was performed)</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x3.png"/></fig><p>collected. This information was used as a baseline to determine the impact of different types of interventions. In step 2 the sources of pollution COD, BOD, N and P per sector (domestic, industrial and agricultural) were determined. An additional assessment on the relative contribution per sector was performed considering variations in the pollution load reaching the surface water with different urban areas [<xref ref-type="bibr" rid="scirp.71155-ref18">18</xref>] and the status of industrial pollution control [<xref ref-type="bibr" rid="scirp.71155-ref37">37</xref>] . In step 3 wastewater and solid waste interventions were defined and their associated costs estimated, based on [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] . The impact on pollution loads discharged to the environment and the associated costs were further analyzed by varying treatment technologies and the percent of households switching from a septic tank to a sewer system connection. In step 4 the impact of different interventions on water quality was determined using a river basin simulation software (RIBASIM) [<xref ref-type="bibr" rid="scirp.71155-ref38">38</xref>] . In step 5, five different benefits were monetized: health, access time, water quality, environment and revenues from resource recovery [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref31">31</xref>] . In step 6 the benefits and costs were compared over a 20 year period to estimate the benefit-cost ratios. In this final step also a sensitivity analysis was performed to determine the impact of reduced health, welfare and revenues from recovered resources and of different capital lifespan on the BCR. A description of the individual steps and method for data collection is further illustrated using the Upper Citarum River as an example.</p><sec id="s2_1"><title>2.1. Step 1: Determination of Water Quality in Upper Citarum River</title><p>Water quality data for COD, BOD, N and P for the period 2001-2009 in the upper Citarum River at Wangisagara, Sapan, Cijeruk, Dayeukholot and Nanjung (<xref ref-type="fig" rid="fig1"><xref ref-type="fig" rid="fig">Figure </xref>1</xref>) was obtained through the West Java Regional Environmental Agency [<xref ref-type="bibr" rid="scirp.71155-ref39">39</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref40">40</xref>] .</p></sec><sec id="s2_2"><title>2.2. Step 2: Determination of Sources of Pollution</title><p>Three sources of pollutions were distinguished and assessed for 2010 and 2030, being (A) Domestic, (B) Industrial and (C) Agricultural (<xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>).</p><p>A. Domestic pollution:</p><p>Domestic pollution was determined in five steps.</p><p>1. Determination of specific per person pollution loads: Domestic specific water consumption rates followed the Indonesia guidelines [<xref ref-type="bibr" rid="scirp.71155-ref16">16</xref>] for 6 categories of urban area: 1) metropolitan (&gt;1 million people), 2) large town (500,000 - 1 million people), 3) medium town (100,000 - 500,000 people), 4) small town (20,000 - 100,000 people), 5) village (3000 - 20,000 people) and 6) rural (&lt;3000 people). An 80% return factor was used to estimate wastewater production from consumed water [<xref ref-type="bibr" rid="scirp.71155-ref41">41</xref>] . Metropolitan specific pollution loads were based on [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] .</p><p>2. Correction of pollution load with varying types of urban status: The relation between urban category and pollution loads was reflected using the study of [<xref ref-type="bibr" rid="scirp.71155-ref17">17</xref>] applying a greywater pollution load decrease between urban metropolitan and rural areas of 30% of COD and N and 50% of P, while for urban categories in between metropolitan and rural areas these were made relative to water consumption data (<xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>). Because of lack of detailed data, urban and rural black water pollution load rates were assumed the same.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref></label><caption><title> Basis for applied Domestic (A), Industrial (B) and Agricultural (C) pollution reaching the surface water</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="7"  >A. Domestic per capita pollution loads reaching surface water<sup>a</sup></th><th align="center" valign="middle"  colspan="6"  >B. Industrial concentrations in effluent per type of industry</th></tr></thead><tr><td align="center" valign="middle"  rowspan="2"  >Urban category</td><td align="center" valign="middle" >Water use</td><td align="center" valign="middle" >COD</td><td align="center" valign="middle" >BOD</td><td align="center" valign="middle" >TN</td><td align="center" valign="middle" >TP</td><td align="center" valign="middle" >Coliform</td><td align="center" valign="middle"  rowspan="2"  >Type of industry</td><td align="center" valign="middle" >COD</td><td align="center" valign="middle" >BOD</td><td align="center" valign="middle" >TN</td><td align="center" valign="middle"  colspan="2"  >TP</td></tr><tr><td align="center" valign="middle" >l/cap/d</td><td align="center" valign="middle"  colspan="4"  >g/p/d</td><td align="center" valign="middle" >1/100 ml</td><td align="center" valign="middle"  colspan="5"  >mg/l</td></tr><tr><td align="center" valign="middle" >1. Metropolitan</td><td align="center" valign="middle" >190</td><td align="center" valign="middle" >82.2</td><td align="center" valign="middle" >41.1</td><td align="center" valign="middle" >12.3</td><td align="center" valign="middle" >2.1</td><td align="center" valign="middle" >1 &#215; 10<sup>8</sup></td><td align="center" valign="middle" >Food &amp; Beverage<sup>b</sup></td><td align="center" valign="middle" >5000</td><td align="center" valign="middle" >3000</td><td align="center" valign="middle" >80</td><td align="center" valign="middle"  colspan="2"  >30</td></tr><tr><td align="center" valign="middle" >2. Large town</td><td align="center" valign="middle" >170</td><td align="center" valign="middle" >81.0</td><td align="center" valign="middle" >40.5</td><td align="center" valign="middle" >12.3</td><td align="center" valign="middle" >2.0</td><td align="center" valign="middle" >1 &#215; 10<sup>8</sup></td><td align="center" valign="middle" >Paper<sup>c</sup></td><td align="center" valign="middle" >4000</td><td align="center" valign="middle" >1500</td><td align="center" valign="middle" >20</td><td align="center" valign="middle"  colspan="2"  >10</td></tr><tr><td align="center" valign="middle" >3. Medium town</td><td align="center" valign="middle" >150</td><td align="center" valign="middle" >73.5</td><td align="center" valign="middle" >36.7</td><td align="center" valign="middle" >11.3</td><td align="center" valign="middle" >1.9</td><td align="center" valign="middle" >1 &#215; 10<sup>8</sup></td><td align="center" valign="middle" >Pharmaceutical<sup>d</sup></td><td align="center" valign="middle" >5000</td><td align="center" valign="middle" >1500</td><td align="center" valign="middle" >127</td><td align="center" valign="middle"  colspan="2"  >25</td></tr><tr><td align="center" valign="middle" >4. Small town</td><td align="center" valign="middle" >130</td><td align="center" valign="middle" >65.3</td><td align="center" valign="middle" >32.7</td><td align="center" valign="middle" >10.2</td><td align="center" valign="middle" >1.7</td><td align="center" valign="middle" >1 &#215; 10<sup>8</sup></td><td align="center" valign="middle" >Rubber<sup>d</sup></td><td align="center" valign="middle" >7340</td><td align="center" valign="middle" >4400</td><td align="center" valign="middle" >1100</td><td align="center" valign="middle"  colspan="2"  >220</td></tr><tr><td align="center" valign="middle" >5. Village</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >56.9</td><td align="center" valign="middle" >28.5</td><td align="center" valign="middle" >9.1</td><td align="center" valign="middle" >1.5</td><td align="center" valign="middle" >1 &#215; 10<sup>8</sup></td><td align="center" valign="middle" >Textile<sup>e</sup></td><td align="center" valign="middle" >1350</td><td align="center" valign="middle" >450</td><td align="center" valign="middle" >60</td><td align="center" valign="middle"  colspan="2"  >20</td></tr><tr><td align="center" valign="middle" >6. Rural</td><td align="center" valign="middle" >30</td><td align="center" valign="middle" >47.3</td><td align="center" valign="middle" >23.7</td><td align="center" valign="middle" >7.9</td><td align="center" valign="middle" >1.3</td><td align="center" valign="middle" >1 &#215; 10<sup>8</sup></td><td align="center" valign="middle" >Others<sup>d</sup></td><td align="center" valign="middle" >280</td><td align="center" valign="middle" >168</td><td align="center" valign="middle" >42</td><td align="center" valign="middle"  colspan="2"  >8</td></tr><tr><td align="center" valign="middle"  colspan="13"  >C. Agricultural pollution loads (g/Yield.ha)<sup>d</sup></td></tr><tr><td align="center" valign="middle" >Type of crops</td><td align="center" valign="middle"  colspan="2"  >COD</td><td align="center" valign="middle"  colspan="3"  >BOD</td><td align="center" valign="middle" >TN</td><td align="center" valign="middle"  colspan="2"  >TP</td><td align="center" valign="middle"  colspan="3"  >Coliforms</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Rice</td><td align="center" valign="middle"  colspan="2"  >45</td><td align="center" valign="middle"  colspan="3"  >22.5</td><td align="center" valign="middle" >21.5</td><td align="center" valign="middle"  colspan="2"  >6.5</td><td align="center" valign="middle"  colspan="3"  >0</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Non-rice food crops</td><td align="center" valign="middle"  colspan="2"  >34</td><td align="center" valign="middle"  colspan="3"  >17</td><td align="center" valign="middle" >4.6</td><td align="center" valign="middle"  colspan="2"  >0</td><td align="center" valign="middle"  colspan="3"  >0</td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>a. Based on [<xref ref-type="bibr" rid="scirp.71155-ref17">17</xref>] - [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] ; b. Data obtained by authors from Food &amp; Beverage (dairy, brewery) in Indonesia; c. Values depend on type of paper and pulping process and range from 1500 to over 20,000 mg/l COD [<xref ref-type="bibr" rid="scirp.71155-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref48">48</xref>] . Applied values are based on experience of authors for Pulp and Paper South East Asia; d. Based on [<xref ref-type="bibr" rid="scirp.71155-ref47">47</xref>] ; e. Textile industry data were determined based on actual measurements of 21 textile industries in project area [<xref ref-type="bibr" rid="scirp.71155-ref37">37</xref>] and verified with [<xref ref-type="bibr" rid="scirp.71155-ref21">21</xref>] .</p><p>3. Correction of pollution reaching surface water bodies: Baseline pollution correction coefficients (included in <xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>) were based on [<xref ref-type="bibr" rid="scirp.71155-ref18">18</xref>] and were 100% (metropolitan and large towns), 92% (medium town), 83% (small town), 74% (village) and 65% (rural areas). Thus, only 83% of pollution generated in a small town is expected to reach the surface water. As specific information on these coefficients was lacking for the Upper Citarum Basin, two alternative scenarios were compared, being 1) where 100% of pollution entered the surface water, and 2) where half of the baseline value entered the surface water (i.e. 50% for metropolitan and large towns, 46% for medium town, 42% for small towns, 37% for village and 33% for rural areas).</p><p>4. Determination of pollution loads reaching the surface water for 2010 and 2030: Total specific pollutions loads per location reaching the surface water were calculated applying the specific pollution loads (combining step 2 and 3 above) on population developments obtained from the Java Spatial Model (JSM). JSM shows the population development for each urban category between 2010 and 2030 [<xref ref-type="bibr" rid="scirp.71155-ref16">16</xref>] .</p><p>5. Determination of the number of people with access to wastewater facilities in 2010: The pollution loads reaching the water bodies were corrected for interventions already in place. The 2010 wastewater access data were obtained from the statistical bureau of Indonesia (BPS) and were determined as 52%. 490,000 people were connected to the Bojong Soang WWTP (pond systems) in Bandung [<xref ref-type="bibr" rid="scirp.71155-ref42">42</xref>] .</p><p>B. Industrial pollution:</p><p>838 industries in the catchment area were categorized by location and type (<xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>) and water consumption (m<sup>3</sup>/d) in which data on ground and surface water consumption were obtained from the West Java provincial agency for Energy and Mineral Resources [<xref ref-type="bibr" rid="scirp.71155-ref43">43</xref>] and provincial agency for Water Resources Management [<xref ref-type="bibr" rid="scirp.71155-ref44">44</xref>] . Pollution loads were determined by effluent flow (using 80% return factor) and effluent concentrations (<xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>). Because reliable industrial pollution data is lacking [<xref ref-type="bibr" rid="scirp.71155-ref37">37</xref>] , an impact analysis was performed (<xref ref-type="table" rid="table2"><xref ref-type="table" rid="table">Table </xref>2</xref>). A distinction is made between 1) a best case scenario, 2) a baseline scenario and 3) a worst case scenario. These scenarios vary in terms of removal efficiency and percentage of industry having a WWTP (<xref ref-type="table" rid="table2"><xref ref-type="table" rid="table">Table </xref>2</xref>). COD removal efficiencies in the best case followed self-reported COD removal efficiencies by industries, whereas the worst case effluent COD values followed externally measured COD removal efficiencies [<xref ref-type="bibr" rid="scirp.71155-ref37">37</xref>] . N and P are not measured by industries and presented values were assumed, based on [<xref ref-type="bibr" rid="scirp.71155-ref21">21</xref>] . Reference [<xref ref-type="bibr" rid="scirp.71155-ref45">45</xref>] reports that 80% of the textile industries comply with the effluent standards, whereas the environmental office in nearby Cimahi mentions 3% [<xref ref-type="bibr" rid="scirp.71155-ref46">46</xref>] . Therefore, the baseline case assumes that 80% of the largest industries (consumption &gt;2000 m<sup>3</sup>/d) treat their wastewater, while with decreasing water consumption this percentage decreases with a minimum of 25% (<xref ref-type="table" rid="table2"><xref ref-type="table" rid="table">Table </xref>2</xref>).</p><p>C. Agricultural pollution:</p><p>The 2010 and 2030 water demand for irrigation was based on [<xref ref-type="bibr" rid="scirp.71155-ref16">16</xref>] . Pollution discharged (<xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>) for rice and non-rice crops were based on [<xref ref-type="bibr" rid="scirp.71155-ref47">47</xref>] .</p></sec><sec id="s2_3"><title>2.3. Step 3: Formulation of Interventions and Their Costs</title><p>Domestic interventions:</p><p>Selection of type of domestic WWT facilities (<xref ref-type="table" rid="table3"><xref ref-type="table" rid="table">Table </xref>3</xref>) was based on the residential features following [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] . For off-site systems three scenarios were compared to identify the effect on the surface water quality and cost:</p><p>1. Simple Technology (ST): Anaerobic filter is applied for medium centralized systems and a conventional activated sludge (CAS) for centralized systems;</p><p>2. Advanced Technology (AT): Medium central and central systems apply a CAS with additional N, P removal;</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2"><xref ref-type="table" rid="table">Table </xref>2</xref></label><caption><title> Defined scenarios to determine the impact of industrial pollution loads by varying 1) removal efficiencies and 2) availability of WWTP based on size of water intake<sup>a</sup></title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Scenario</th><th align="center" valign="middle"  colspan="4"  >1. % Removal efficiency</th><th align="center" valign="middle"  colspan="5"  >2. % industries with WWTP per size of water intake (m<sup>3</sup>/d)</th></tr></thead><tr><td align="center" valign="middle" >COD</td><td align="center" valign="middle" >BOD</td><td align="center" valign="middle" >TN</td><td align="center" valign="middle" >TP</td><td align="center" valign="middle" >0 - 100</td><td align="center" valign="middle" >100 - 500</td><td align="center" valign="middle" >500 - 1000</td><td align="center" valign="middle" >1000 - 2000</td><td align="center" valign="middle" >&gt;2000</td></tr><tr><td align="center" valign="middle" >Best case</td><td align="center" valign="middle" >90</td><td align="center" valign="middle" >95</td><td align="center" valign="middle" >90</td><td align="center" valign="middle" >50</td><td align="center" valign="middle" >35</td><td align="center" valign="middle" >35</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >90</td></tr><tr><td align="center" valign="middle" >Baseline</td><td align="center" valign="middle" >65</td><td align="center" valign="middle" >69</td><td align="center" valign="middle" >65</td><td align="center" valign="middle" >36</td><td align="center" valign="middle" >25</td><td align="center" valign="middle" >25</td><td align="center" valign="middle" >50</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >80</td></tr><tr><td align="center" valign="middle" >Worst case</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >42</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >22</td><td align="center" valign="middle" >15</td><td align="center" valign="middle" >15</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >70</td></tr></tbody></table></table-wrap><p>a. <xref ref-type="table" rid="table2"><xref ref-type="table" rid="table">Table </xref>2</xref> shows for example that in the best case scenario, 90% of the industries with a water consumption exceeding 2000 m<sup>3</sup>/d have a WWTP and removal efficiencies are 90% (COD), 95% (BOD), 90% (TN) and (50% (TP).</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3"><xref ref-type="table" rid="table">Table </xref>3</xref></label><caption><title> WWT system selection based on 1) population density and 2) urban/rural category. Removal efficiencies of Simple technologies (ST), Advanced Technologies (AT) and Resource Recovery (RR) technologies for COD, BOD, TN, TP and coliforms are based on [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] </title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="3"  >System</th><th align="center" valign="middle"  colspan="2"  >Criteria for use<sup>a</sup></th><th align="center" valign="middle"  colspan="10"  >Applied removal efficiencies per type of technology</th></tr></thead><tr><td align="center" valign="middle"  rowspan="2"  >Residential population density (pp/ha)</td><td align="center" valign="middle"  rowspan="2"  >Status 2020<sup>b</sup></td><td align="center" valign="middle"  colspan="2"  >COD (%)</td><td align="center" valign="middle"  colspan="2"  >BOD (%)</td><td align="center" valign="middle"  colspan="2"  >TN (%)</td><td align="center" valign="middle"  colspan="2"  >TP (%)</td><td align="center" valign="middle"  colspan="2"  >Coliforms (%)</td></tr><tr><td align="center" valign="middle" >ST</td><td align="center" valign="middle" >AT/RR</td><td align="center" valign="middle" >ST</td><td align="center" valign="middle" >AT/RR</td><td align="center" valign="middle" >ST</td><td align="center" valign="middle" >AT/RR</td><td align="center" valign="middle" >ST</td><td align="center" valign="middle" >AT/RR</td><td align="center" valign="middle" >ST</td><td align="center" valign="middle" >AT/RR</td></tr><tr><td align="center" valign="middle" >On-site</td><td align="center" valign="middle" >&lt;100</td><td align="center" valign="middle" >Rural/Urban</td><td align="center" valign="middle"  colspan="2"  >40<sup>a</sup></td><td align="center" valign="middle"  colspan="2"  >45</td><td align="center" valign="middle"  colspan="2"  >15</td><td align="center" valign="middle"  colspan="2"  >5</td><td align="center" valign="middle"  colspan="2"  >90</td></tr><tr><td align="center" valign="middle" >CBS</td><td align="center" valign="middle" >&gt;100</td><td align="center" valign="middle" >Rural</td><td align="center" valign="middle"  colspan="2"  >80<sup>a</sup></td><td align="center" valign="middle"  colspan="2"  >85</td><td align="center" valign="middle"  colspan="2"  >15</td><td align="center" valign="middle"  colspan="2"  >5</td><td align="center" valign="middle"  colspan="2"  >99</td></tr><tr><td align="center" valign="middle" >Medium Central</td><td align="center" valign="middle" >100 - 250</td><td align="center" valign="middle" >Urban</td><td align="center" valign="middle" >80</td><td align="center" valign="middle"  rowspan="2"  >88</td><td align="center" valign="middle" >85</td><td align="center" valign="middle"  rowspan="2"  >97</td><td align="center" valign="middle" >15</td><td align="center" valign="middle"  rowspan="2"  >90</td><td align="center" valign="middle" >5</td><td align="center" valign="middle"  rowspan="2"  >67</td><td align="center" valign="middle" >99</td><td align="center" valign="middle"  rowspan="2"  >99.9</td></tr><tr><td align="center" valign="middle" >Central</td><td align="center" valign="middle" >&gt;250</td><td align="center" valign="middle" >Urban</td><td align="center" valign="middle" >88</td><td align="center" valign="middle" >97</td><td align="center" valign="middle" >73</td><td align="center" valign="middle" >29</td><td align="center" valign="middle" >99.9</td></tr></tbody></table></table-wrap><p>a. Current users in urban areas with a residential density between 25 - 100 pp/ha apply on-site systems, whereas all new development will be served by medium centralized system [<xref ref-type="bibr" rid="scirp.71155-ref50">50</xref>] ; b. Selection criteria are formulated based on the expected population status in 2020 (mid-term).</p><p>3. Resource Recovery technology (RR): Comprising Aerobic Granular Sludge (AGS) system [<xref ref-type="bibr" rid="scirp.71155-ref49">49</xref>] with sludge digestion, P-recovery as struvite and composting of produced sludge. The removal efficiencies of AT and RR are the same.</p><p>Associated investment and operational costs were based on [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] (see <xref ref-type="table" rid="table">Table </xref>S1 of the OSI Section 1). The effects on discharged pollution loads reaching the surface water and associated investment costs of a 25%, 50% and 75% switch of households currently applying on-sites system to an off-site system were compared.</p><p>Industrial interventions:</p><p>Three industrial wastewater treatment types were formulated based on currently applied technologies [<xref ref-type="bibr" rid="scirp.71155-ref51">51</xref>] (see OSI, Section 3): 1) textile wastewater using reactive dyes (typically used for traditional batik), apply a CAS and activated carbon for color removal, 2) textile wastewater using non-reactive dyes apply CAS followed by Dissolved Air Flotation (DAF), and 3) other industries apply pre-treatment (DAF) and CAS. Future effluent values should meet at least current standards [<xref ref-type="bibr" rid="scirp.71155-ref46">46</xref>] defined as 80 mg/l COD, 20 mg/l BOD, 10 mg/l N and 10 mg/l P. Investment and operational costs were determined for different sizes of treatment capacities, based on available engineering cost standards (see OSI, Section 3).</p><p>Municipal Solid Waste (MSW) interventions:</p><p>Solid waste system selection interventions (<xref ref-type="table" rid="table">Table </xref>4) and their costs are based on [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] and distinguish home composting, landfilling and centralized and decentralized 3R application (see OSI Section 4).</p></sec><sec id="s2_4"><title>2.4. Step 4: Assessment of Impact of Interventions on Pollution Loads and Water Quality</title><p>A generic model package (RIBASIM) for simulating the behavior of river basins under various hydrological conditions was used to simulate the effect of different interventions on water quality development in the Upper Citarum River [<xref ref-type="bibr" rid="scirp.71155-ref38">38</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref52">52</xref>] . Based on pollution loads produced in each defined catchment area and resulting water flows</p><table-wrap id="table4" ><label><xref ref-type="table" rid="table">Table </xref>4</label><caption><title> MSW system selection for Indonesia as a function of density, urban/rural status [<xref ref-type="bibr" rid="scirp.71155-ref50">50</xref>] </title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Type of area &amp; Density Activity</th><th align="center" valign="middle"  colspan="2"  >Rural</th><th align="center" valign="middle"  colspan="2"  >Urban</th></tr></thead><tr><td align="center" valign="middle" >&lt;25 pp/ha</td><td align="center" valign="middle" >&gt;25 pp/ha</td><td align="center" valign="middle" >&lt;100 pp/ha</td><td align="center" valign="middle" >&gt;100 pp/ha</td></tr><tr><td align="center" valign="middle" >Collection</td><td align="center" valign="middle" >no</td><td align="center" valign="middle" >yes</td><td align="center" valign="middle"  colspan="2"  >yes</td></tr><tr><td align="center" valign="middle" >Disposal</td><td align="center" valign="middle" >no</td><td align="center" valign="middle" >yes</td><td align="center" valign="middle"  colspan="2"  >yes</td></tr><tr><td align="center" valign="middle" >Level of 3R</td><td align="center" valign="middle" >Home composting</td><td align="center" valign="middle" >Decentralized composting and plastic/paper recovery</td><td align="center" valign="middle"  colspan="2"  >Central digestion and composting and plastic &amp; paper recovery</td></tr></tbody></table></table-wrap><p>concentrations are calculated. The RIBASIM model and defined catchment areas are further explained in OSI Section 5. The pollution loads entering the Upper Citarum River were varied, using 6 scenarios (<xref ref-type="table" rid="table">Table </xref>5).</p><p>The output of the 2010 RISBASIM average pollutant concentrations was calibrated based on the average measured concentration (step 1).</p></sec><sec id="s2_5"><title>2.5. Step 5: Benefits Analysis of Different Interventions</title><p>Five economic benefits of wastewater and solid waste management improvements were defined following [<xref ref-type="bibr" rid="scirp.71155-ref32">32</xref>] and [<xref ref-type="bibr" rid="scirp.71155-ref53">53</xref>] :</p><p>A. Health:</p><p>Averted costs of fecal-oral disease from improved on-site sanitation and wastewater management: An average disease reduction of 36% by on-site sanitation and an additional 20% by adding improved off-site facilities was applied [<xref ref-type="bibr" rid="scirp.71155-ref54">54</xref>] - [<xref ref-type="bibr" rid="scirp.71155-ref56">56</xref>] . The average annual health cost per 5 member family as a result of unimproved sanitation was US $316 [<xref ref-type="bibr" rid="scirp.71155-ref31">31</xref>] .</p><p>Associated averted health impacts (infectious diseases and skin complaints) of less exposure during flooding events: Reported health cases during a period of several flooding events (January-March 2009) were compared to the same period in a non-flood year (January to March 2010) and was scaled to reflect all the flooded communities in the Citarum River basin, resulting in an estimated 15,000 averted cases of diarrhea in an average year [<xref ref-type="bibr" rid="scirp.71155-ref53">53</xref>] . The economic value was estimated by multiplying the average number of additional cases per year by the unit cost of inpatient (hospitalized) and outpatient services, including productivity losses [<xref ref-type="bibr" rid="scirp.71155-ref31">31</xref>] .</p><p>B. Access time:</p><p>Value of time savings from reduced travel time and/or queuing for meeting sanitation needs: An average daily gain of 115 minutes per household with an annual value of US $95 per household is used [<xref ref-type="bibr" rid="scirp.71155-ref31">31</xref>] . Only the time of adults and school-aged children were included, valued at 30% and 15% of the hourly rate implied by the GDP per capita, respectively [<xref ref-type="bibr" rid="scirp.71155-ref57">57</xref>] . This figure was applied to the access gain afforded by on-site sanitation facilities of 45% of households for the period from 2010 until 2030.</p><p>C. Water:</p><p>Reduced drinking water treatment costs to households and industries: The total cost of water treatment (including both capital and operating costs) using surface water of a better quality source will decrease from 0.13 to 0.06 US $/m<sup>3</sup> [<xref ref-type="bibr" rid="scirp.71155-ref16">16</xref>] . This saving was</p><table-wrap id="table5" ><label><xref ref-type="table" rid="table">Table </xref>5</label><caption><title> Defined intervention scenario (S1 - S6); ST = Simple Technology ; AT = Advanced Technology and percentage of population served by a municipal solid waste (MSW) system</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="2"  >Name</th><th align="center" valign="middle" >Description</th></tr></thead><tr><td align="center" valign="middle"  colspan="2"  >S1: Baseline</td><td align="center" valign="middle" >2010: Baseline situation</td></tr><tr><td align="center" valign="middle"  colspan="2"  >S2: No intervention</td><td align="center" valign="middle" >2030: Baseline case; same WWT access percentage as 2010 applied. Only correction for population growth for WWT and MSW</td></tr><tr><td align="center" valign="middle"  rowspan="6"  >S3:</td><td align="center" valign="middle" >25% ST</td><td align="center" valign="middle" >2030: 100% Domestic access, use ST and 25% switch + 100% MSW</td></tr><tr><td align="center" valign="middle" >25% AT</td><td align="center" valign="middle" >2030: 100% Domestic access, use AT and 25% switch + 100% MSW</td></tr><tr><td align="center" valign="middle" >50% ST</td><td align="center" valign="middle" >2030: 100% Domestic access, use ST and 50% switch + 100% MSW</td></tr><tr><td align="center" valign="middle" >50% AT</td><td align="center" valign="middle" >2030: 100% Domestic access, use AT and 50% switch + 100% MSW</td></tr><tr><td align="center" valign="middle" >75% ST</td><td align="center" valign="middle" >2030: 100% Domestic access, use ST and 75% switch + 100% MSW</td></tr><tr><td align="center" valign="middle" >75% AT</td><td align="center" valign="middle" >2030: 100% Domestic access, use AT and 75% switch + 100% MSW</td></tr><tr><td align="center" valign="middle"  colspan="2"  >S4: Industrial only</td><td align="center" valign="middle" >2030: Industrial WWT intervention; 100% of big (&gt;1000 m<sup>3</sup>/d), 90% of medium (500 - 1000 m<sup>3</sup>/d), 80% small (100 - 500 m<sup>3</sup>/d), and 75% of very small (&lt;100 m<sup>3</sup>/d) sized industries apply intervention. Domestic WWT, MSW interventions follow S2</td></tr><tr><td align="center" valign="middle"  colspan="2"  >S5: 25% - 75% ST/AT</td><td align="center" valign="middle" >2030: Combination of scenario 3 and 4</td></tr><tr><td align="center" valign="middle"  colspan="2"  >S6a: 25% - 75% RR</td><td align="center" valign="middle" >2030: Same as S5, using recovery technologies for domestic, industrial effluent recycling and MSW</td></tr></tbody></table></table-wrap><p>a: Except for S6, where a MSW resource recovery based system is applied, all other cases apply a conventional MSW system (no resource recovery).</p><p>multiplied by the assessed annual production of water from surface water sources (207 million m<sup>3</sup> for domestic and 70 million m<sup>3</sup> for industrial consumers) in 2030.</p><p>Improved fish yields from farming in downstream lakes due to improved water quality: Data collected through interviews with the regional Fisheries Office showed a decrease in fish catch of 5,000 ton/year in recent years [<xref ref-type="bibr" rid="scirp.71155-ref58">58</xref>] . Fish kills in Saguling (<xref ref-type="fig" rid="fig1"><xref ref-type="fig" rid="fig">Figure </xref>1</xref>) related to discharge of untreated wastewater have been described by [<xref ref-type="bibr" rid="scirp.71155-ref12">12</xref>] and [<xref ref-type="bibr" rid="scirp.71155-ref23">23</xref>] . By 2030 the fish capture is estimated to increase by 8,000 metric tons per year [<xref ref-type="bibr" rid="scirp.71155-ref58">58</xref>] . The increase of improved water quality was assumed to account for one-third of this expected annual gain of farmed fish in the Citarum basin [<xref ref-type="bibr" rid="scirp.71155-ref53">53</xref>] . A market prices of fish of 1.5 US $/kg was used [<xref ref-type="bibr" rid="scirp.71155-ref58">58</xref>] .</p><p>D. Environment:</p><p>Reduced frequency of river and reservoir dredging due to improved sludge and waste management: An estimated 35 l/person/year of septic waste [<xref ref-type="bibr" rid="scirp.71155-ref9">9</xref>] and 11% and 17% of domestic urban and rural solid waste [<xref ref-type="bibr" rid="scirp.71155-ref59">59</xref>] accumulating to nearly 500 ktonne/year are currently discharged to the surface water and will be prevented from being disposed in the surface water in 2030 with the described interventions (<xref ref-type="table" rid="table">Table </xref>5). With a cost of dredging estimated at US $3.76 [<xref ref-type="bibr" rid="scirp.71155-ref16">16</xref>] per ton of sediment (assuming no degradation), the total annual cost averted was estimated.</p><p>Rise in land prices due to improved aesthetics of riverside and lakeside real estate: Currently the Citarum riverside area is not developed due to water pollution. However, the area is expected to become a place where riverside property could be developed for inhabitants, small businesses, and tourist facilities in a situation where water quality is improved. The current agricultural land price (10.7 US $/m<sup>2</sup>) in the vicinity of Bandung was used as a benchmark for current riverside land prices. The current market suggests that land prices can climb to 71.3 US $/m<sup>2</sup> in highly desirable locations [<xref ref-type="bibr" rid="scirp.71155-ref16">16</xref>] . In this study 50% of this increase is attributed to improved water quality. This value was multiplied by an estimated 50 ha of land that could be developed each year after the water quality improvements have occurred [<xref ref-type="bibr" rid="scirp.71155-ref53">53</xref>] .</p><p>Averted maintenance costs of hydro-electric facilities: Improved solid waste management would avert the current costs of US $0.1 million [<xref ref-type="bibr" rid="scirp.71155-ref16">16</xref>] to evacuate the solid and unmanaged sludge waste to avoid equipment damage in the hydroelectric facility [<xref ref-type="bibr" rid="scirp.71155-ref53">53</xref>] .</p><p>E. Recovery of resources:</p><p>In scenario 6, resource recovery was considered (see also <xref ref-type="table" rid="table">Table </xref>S4 in the OSI, Section 4):</p><p> Off-site wastewater systems: Production of energy (sludge digestion), struvite (from centrate) and compost (digested sludge composting).</p><p> MSW: Energy and compost production from organic waste and recovery of plastics and paper.</p><p> Industrial wastewater: industries with a water consumption exceeding 2000 m<sup>3</sup>/d reused 80% of the effluent, whereas for industries using 1000 - 2000 m<sup>3</sup>/d this was 50%.</p><p>To compare the production (recovery) of resources with the potential demand in the Upper Citarum River catchment area in 2030, the compost, struvite, plastic and paper demand in the whole of West Java obtained from [<xref ref-type="bibr" rid="scirp.71155-ref29">29</xref>] was corrected for people living in the Upper Citarum River basin area. The amount of recycled water from industries was compared to the total domestic and industrial water demand in 2030 in the catchment area [<xref ref-type="bibr" rid="scirp.71155-ref16">16</xref>] . Energy production from digestion is compared to the energy demand for domestic wastewater treatment in the area applying aerobic granular sludge technology [<xref ref-type="bibr" rid="scirp.71155-ref19">19</xref>] .</p></sec><sec id="s2_6"><title>2.6. Step 6: Assessment of Benefits versus Costs</title><p>To relate benefits and costs to either wastewater or solid waste interventions, BCR’s were presented separately. To analyze the individual impact of domestic, industrial and resource recovery interventions the BCR of scenarios S3: (50% ST and S3: 50% AT), S4: (Industrial interventions only), S5: (50% ST; S5: 50% AT) and S6 (50% RR) were determined (see also <xref ref-type="table" rid="table">Table </xref>5). A sensitivity analysis was performed in which input values that have the highest anticipated impact were varied: (1) health and access time benefits reduced from 100% to 50%, (2) lifespan of all wastewater and solid waste facilities varied from 20 years to 15 and 40 years, and (3) resource selling price reduced to half baseline values [<xref ref-type="bibr" rid="scirp.71155-ref32">32</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref53">53</xref>] . Health and access time benefits were all attributed to domestic intervention. Water quality and environmental benefits were attributed to the fraction of COD load discharged by domestic and industrial sources respectively.</p></sec></sec><sec id="s3"><title>3. Results</title><sec id="s3_1"><title>3.1. Water Quality in Upper Citarum River</title><p><xref ref-type="fig" rid="fig3"><xref ref-type="fig" rid="fig">Figure </xref>3</xref> shows the average 2000-2009 water quality from upstream to downstream locations. Maximum allowable concentrations are defined in class II standard [<xref ref-type="bibr" rid="scirp.71155-ref60">60</xref>] and are COD 25 mg/l, BOD 3 mg/l and P 0.2 mg/l. From Sapan on (<xref ref-type="fig" rid="fig1"><xref ref-type="fig" rid="fig">Figure </xref>1</xref>) all measured values exceed these standards. Concentrations in several Citarum branches passing high density urban areas, show COD values approaching 500 mg/l and pathogen levels as high as 10<sup>7</sup> Units/100 ml [<xref ref-type="bibr" rid="scirp.71155-ref40">40</xref>] .</p></sec><sec id="s3_2"><title>3.2. Sources of Pollution</title><p>Current cumulative pollution loads in the Upper Citarum River basin of COD (585 tonne/d), BOD (264 tonne/d), TN (91 tonne/d) and TP (20 tonne/d) were determined as the baseline values (<xref ref-type="table" rid="table">Table </xref>6). The sensitivity analysis with variations in domestic pollution coefficient [<xref ref-type="bibr" rid="scirp.71155-ref18">18</xref>] and performance of industries shows considerable differences with the baseline scenario (<xref ref-type="table" rid="table">Table </xref>6) with COD loads varying between 325 and 688 tonne/d (see also OSI, Section 7).</p></sec><sec id="s3_3"><title>3.3. Effect of Selected Interventions on Costs and Pollution Loads</title><p>The domestic pollution loads entering the Upper Citarum River depend on (1) the type of technology applied (simple versus advanced) and (2) the rate of current households applying on-site systems in urban areas that will switch to an off-site system (<xref ref-type="fig" rid="fig4"><xref ref-type="fig" rid="fig">Figure </xref>4</xref>). The use of advanced compared to simple technologies has a minor impact on COD removal in the range of 3% - 4%, but a major impact on N-removal in which a rate of</p><table-wrap id="table6" ><label><xref ref-type="table" rid="table">Table </xref>6</label><caption><title> COD, BOD, TN and TP pollution loads reaching the surface water by source for the baseline scenario and varying pollution correction factors and industrial practices</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Source</th><th align="center" valign="middle" >Scenario</th><th align="center" valign="middle" >COD (tonne/d)</th><th align="center" valign="middle" >BOD (tonne/d)</th><th align="center" valign="middle" >TN (tonne/d)</th><th align="center" valign="middle" >TP (tonne/d)</th></tr></thead><tr><td align="center" valign="middle"  rowspan="3"  >Domestic</td><td align="center" valign="middle" >Baseline loads</td><td align="center" valign="middle" >388</td><td align="center" valign="middle" >188</td><td align="center" valign="middle" >68</td><td align="center" valign="middle" >12</td></tr><tr><td align="center" valign="middle" >100% reaches surface water</td><td align="center" valign="middle" >440</td><td align="center" valign="middle" >213</td><td align="center" valign="middle" >78</td><td align="center" valign="middle" >14</td></tr><tr><td align="center" valign="middle" >Half of baseline loads reach surface water</td><td align="center" valign="middle" >194</td><td align="center" valign="middle" >94</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >6</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >Industrial</td><td align="center" valign="middle" >Baseline</td><td align="center" valign="middle" >163</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >2.6</td></tr><tr><td align="center" valign="middle" >Best case</td><td align="center" valign="middle" >98</td><td align="center" valign="middle" >33</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >2.2</td></tr><tr><td align="center" valign="middle" >Worst case</td><td align="center" valign="middle" >215</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >3.0</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Agriculture</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >17</td><td align="center" valign="middle" >16</td><td align="center" valign="middle" >5</td></tr><tr><td align="center" valign="middle"  rowspan="3"  >Total</td><td align="center" valign="middle" >Baseline<sup>a</sup> (S1)</td><td align="center" valign="middle" >585</td><td align="center" valign="middle" >264</td><td align="center" valign="middle" >91</td><td align="center" valign="middle" >20</td></tr><tr><td align="center" valign="middle" >Minimum<sup>b</sup></td><td align="center" valign="middle" >325</td><td align="center" valign="middle" >144</td><td align="center" valign="middle" >54</td><td align="center" valign="middle" >13</td></tr><tr><td align="center" valign="middle" >Maximum<sup>c</sup></td><td align="center" valign="middle" >688</td><td align="center" valign="middle" >310</td><td align="center" valign="middle" >103</td><td align="center" valign="middle" >22</td></tr></tbody></table></table-wrap><p>a. Total baseline values comprise domestic and industrial baseline loads + agricultural loads; b. Total minimum values add domestic low pollution correction coefficient and Industrial best case + agricultural loads; c. Total maximum values add domestic high pollution correction coefficient and Industrial worst case + agricultural loads.</p><fig id="fig3"  position="float"><label><xref ref-type="fig" rid="fig3"><xref ref-type="fig" rid="fig">Figure </xref>3</xref></label><caption><title> Average and standard variations of COD, BOD (primary y-axis) and N, P (secondary y-axis) concentrations at indicated locations in the upper Citarum (2000-2009) [<xref ref-type="bibr" rid="scirp.71155-ref39">39</xref>] and COD, BOD and N limits</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x4.png"/></fig><fig id="fig4"  position="float"><label><xref ref-type="fig" rid="fig4"><xref ref-type="fig" rid="fig">Figure </xref>4</xref></label><caption><title> Calculated domestic COD, BOD (left) and N, P (right) pollution loads per type of intervention and their investment costs (secondary y-axis). S1 (baseline), S2 (no intervention) and S3 (domestic interventions) applying simple (ST) or advanced technologies (AT) with increasing (25%, 50% and 75%) values for urban on-site users that switch to off-site systems</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x5.png"/></fig><p>25% households switching to off-site systems leads to a 29% difference and a rate of 75% households switching to off-site systems leads to a 37% difference (<xref ref-type="fig" rid="fig4"><xref ref-type="fig" rid="fig">Figure </xref>4</xref>).</p><p>When increasing the switch factor from 25% to 75%, the additional removed COD and N increased with 5% and 1% for simple technologies and 6% and 9% for advanced technologies. BOD removal follows the COD trend, whereas P removal follows the N trend. Thus, the application of advanced technologies or a higher rate of people switching from on-site system to off-site systems mainly affects the additional nutrient removal, while organic removal is less affected. The numeric values of this analysis and further elaboration on costs of interventions and their impact on water quality are described in the OSI, Section 7.</p><p>The industrial pollution load amounts to 28% of the total load (<xref ref-type="table" rid="table">Table </xref>6), but industrial interventions can result in a relatively large COD reduction (35%) compared to the combined domestic and industrial COD reduction (see also OSI, Section 7).</p></sec><sec id="s3_4"><title>3.4. Effect of Interventions on Water Quality</title><p>Figures 5(a)-(f) shows the effect of interventions on the year round average water quality at different locations. The location names are approximate locations, as RIBASIM calculates concentrations in defined segments of a river (see OSI, <xref ref-type="fig" rid="fig">Figure </xref>S8). Without</p><fig-group id="fig5"><label><xref ref-type="fig" rid="fig">Figure </xref>5</label><caption><title> Modelled COD, BOD (primary y-axis) and N, P (secondary y-axis) concentrations at indicated locations in 2030 with varying switch factors % and simple (ST) or advanced technologies AT). (a) S2, no intervention; (b) S3: 50% AT); (c) S4: Industrial only; (d) S5: 50% AT; (e) S6: 25% ST; (f) S6: 75% AT. Limits for COD, BOD, and P are 100 mg/l, 3 mg/l and 0.2 mg/l.</title></caption><fig id ="fig5_1"><label> (b)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x6.png"/></fig><fig id ="fig5_2"><label>(c)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x7.png"/></fig><fig id ="fig5_3"><label> (d)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x8.png"/></fig><fig id ="fig5_4"><label>(e)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x9.png"/></fig><fig id ="fig5_5"><label> (f)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x10.png"/></fig><fig id ="fig5_6"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x11.png"/></fig></fig-group><p>additional interventions all concentrations will increase compared to the 2010 values (<xref ref-type="fig" rid="fig3"><xref ref-type="fig" rid="fig">Figure </xref>3</xref>) with values as high as 100 mg/l of COD (<xref ref-type="fig" rid="fig">Figure </xref>5(a)). The modeled pollutant concentrations in water entering Saguling reservoir (approximate location Nanjung) are 80 mg/l COD, and 7 mg/l TN and 1 mg/l TP. When applying S3 with 50% AT (<xref ref-type="fig" rid="fig">Figure </xref>5(b)) a considerable drop in all pollution concentrations is achieved, whereas the introduction of industrial interventions result in approximately 20% COD &amp; BOD removal and about 4% N &amp; P removal (<xref ref-type="fig" rid="fig">Figure </xref>5(c)). The combination of these interventions (S5: 50% AT; <xref ref-type="fig" rid="fig">Figure </xref>5(d)) results in concentrations of 30 mg/l for COD, 10 mg/l for BOD, 3.4 mg/l for TN and 0.7 mg/l for TP. The maximum removal scenario (<xref ref-type="fig" rid="fig">Figure </xref>5(f)) results in values approximating the class II standard (COD &lt; 25, BOD &lt; 3, P&lt;0.2 mg/l). Comparing <xref ref-type="fig" rid="fig">Figure </xref>5(e) (ST) with <xref ref-type="fig" rid="fig">Figure </xref>5(f) (AT) shows limited impact on COD or BOD removal, while considerable extra N, P removal is shown when using advanced instead of simple domestic technologies.</p><p>To reach the desired water quality levels (class II) both industrial and domestic municipal interventions are needed. In addition, the applied off-site technologies should also include N and P removal, requiring more advanced and more costly technologies (see <xref ref-type="fig" rid="fig4"><xref ref-type="fig" rid="fig">Figure </xref>4</xref>) compared to the application of only anaerobic filters.</p></sec><sec id="s3_5"><title>3.5. Benefits of Interventions</title><p>The maximum quantified economic benefits are US $430 million per year in which health benefits account for 39% (<xref ref-type="fig" rid="fig">Figure </xref>6). Health benefits largely result from reductions in fecal-oral diseases, since 1) the people without access to wastewater (on-site and Bojong Soang WWTP) facilities (48%) all have access by 2030 (55.2% of health benefits), and 2) people that have access to a well-managed off-site or fecal sludge management system increased from 7% to 73% (44.6% of health benefits). Associated averted health impact due to irregular flooding events is only US $0.3 million.</p><p>Convenience and time savings are among the top five reasons for having a latrine in the home area [<xref ref-type="bibr" rid="scirp.71155-ref31">31</xref>] . Based on [<xref ref-type="bibr" rid="scirp.71155-ref31">31</xref>] a mean annual gain of US $77 million was determined for an additional 45% of the population in 2030 having access to their own</p><fig id="fig6"  position="float"><label><xref ref-type="fig" rid="fig">Figure </xref>6</label><caption><title> Contribution of calculated overall economic benefits expressed in million US $ (total US $430 million) of each monetized impact (Scenario 6). Sedimentation (US $2M; 0% contribution) and Dam maintenance (US $0.1; 0% contribution) are not shown</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x12.png"/></fig><p>latrine facilities. This estimate is conservative as 1) it excludes travel needs for urination purposes, and 2) time is valued conservatively at 30% of the GDP per capita at hourly values.</p><p>US $13.9 million of the total US $23 million reduction in water treatment cost will accrue to the public water utilities and their consumers, while industries are expected to benefit US $4.7 million annually. The value of farmed fish yields is expected to be US $4 million annually.</p><p>The combined environmental benefits (increased land value, reduced dredging, averted maintenance costs of hydro-electric facilities) amount to US $17 million, of which nearly 90% is attributed to increases in land value based on annual land sales. The benefits of reduced dredging (even assuming no decomposition or organic waste) have minor benefits.</p><p><xref ref-type="table" rid="table">Table </xref>7 shows the estimated reuse benefits based on the per capita production features and resource values (<xref ref-type="table" rid="table">Table </xref>S4 in OSI). 87% of the US $147 million yearly potential revenues are from municipal solid waste, 11% from domestic wastewater treatment and recovery and reuse of its resources and recycling, and 2% from industrial wastewater treatment and recycling. The potential demand for recoverable resources is higher than the potential supply through recovery (<xref ref-type="table" rid="table">Table </xref>7), ranging from a factor 13 for water to a factor 1.6 for plastic.</p></sec><sec id="s3_6"><title>3.6. Assessment of Benefits versus Costs</title><p>Following the anticipated benefits (<xref ref-type="fig" rid="fig">Figure </xref>6) and corresponding investment and operational costs (<xref ref-type="table" rid="table">Table </xref>S6 in OSI, Section 8) the BCR was calculated (<xref ref-type="fig" rid="fig">Figure </xref>7). The BCR varied between the interventions. The highest BCR of 3.2 is achieved by implementing simple technologies (S3: 50% ST), in other words an economic return of US $3.2 is anticipated for each US $1 invested. Because of higher costs for AT compared to ST, the BCR is expected to be lower for the AT scenario (BCR in S3: 50% AT = 2.06). The lowest BCR (0.52) is found in scenario 4 (industrial interventions alone). A joint approach</p><table-wrap id="table7" ><label><xref ref-type="table" rid="table">Table </xref>7</label><caption><title> Resource recovery potential, sector of recovery (Domestic, Industrial or MSW), potential demand, recovery percentage and annual economic values associated with reuse options based on baseline prices (<xref ref-type="table" rid="table">Table </xref>S4 in OSI)</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Parameter</th><th align="center" valign="middle"  colspan="7"  >Recoverable resources per sector and potential demand</th><th align="center" valign="middle"  rowspan="2"  >Total revenues (million US $/year)</th></tr></thead><tr><td align="center" valign="middle" >Domestic WWT</td><td align="center" valign="middle" >Industrial WWT</td><td align="center" valign="middle" >MSW</td><td align="center" valign="middle" >Total recovery</td><td align="center" valign="middle" >Potential demand</td><td align="center" valign="middle" >Unit</td><td align="center" valign="middle" >Recovery percentage</td></tr><tr><td align="center" valign="middle" >Compost</td><td align="center" valign="middle" >91</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >351</td><td align="center" valign="middle" >442</td><td align="center" valign="middle" >1240</td><td align="center" valign="middle" >ktonne/y</td><td align="center" valign="middle" >36%</td><td align="center" valign="middle" >44.2</td></tr><tr><td align="center" valign="middle" >Plastic</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >228</td><td align="center" valign="middle" >228</td><td align="center" valign="middle" >366</td><td align="center" valign="middle" >ktonne/y</td><td align="center" valign="middle" >62%</td><td align="center" valign="middle" >45.5</td></tr><tr><td align="center" valign="middle" >Paper</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >193</td><td align="center" valign="middle" >193</td><td align="center" valign="middle" >1185</td><td align="center" valign="middle" >ktonne/y</td><td align="center" valign="middle" >16%</td><td align="center" valign="middle" >38.6</td></tr><tr><td align="center" valign="middle" >Electricity</td><td align="center" valign="middle" >27</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >89</td><td align="center" valign="middle" >116</td><td align="center" valign="middle" >78.8</td><td align="center" valign="middle" >GWh/y</td><td align="center" valign="middle" >147%</td><td align="center" valign="middle" >11.6</td></tr><tr><td align="center" valign="middle" >Water</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >43</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >43</td><td align="center" valign="middle" >563</td><td align="center" valign="middle" >Mm<sup>3</sup>/y</td><td align="center" valign="middle" >8%</td><td align="center" valign="middle" >2.6</td></tr><tr><td align="center" valign="middle" >Struvite</td><td align="center" valign="middle" >4.2</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >-</td><td align="center" valign="middle" >4.2</td><td align="center" valign="middle" >35</td><td align="center" valign="middle" >ktonne/y</td><td align="center" valign="middle" >12%</td><td align="center" valign="middle" >4.1</td></tr><tr><td align="center" valign="middle"  colspan="8"  >Total economic value</td><td align="center" valign="middle" >146.6</td></tr></tbody></table></table-wrap><fig id="fig7"  position="float"><label><xref ref-type="fig" rid="fig">Figure </xref>7</label><caption><title> Calculated BCR per analyzed scenarios, differentiating the BCR in which only wastewater treatment (WWT) interventions are considered and the BCR that considers both WWT and municipal solid waste (MSW) interventions. Scenarios that approach the target water quality are S5: 50%-AT and S6: 50%-RR</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-6703084x13.png"/></fig><p>tackling both domestic and industrial pollution results in a BCR ranging from 1.83 (S5: 50% AT) to 2.64 (S5: 50% ST). However, simple technologies were not found sufficient to improve the water quality to levels approaching class II, especially in terms of nutrient (N, P) removal (<xref ref-type="fig" rid="fig">Figure </xref>5).</p><p>The economic returns on combined wastewater and solid waste interventions are lower than the returns on wastewater interventions only (<xref ref-type="fig" rid="fig">Figure </xref>7). Economic costs related to absence of solid waste services are associated with unhygienic living conditions [<xref ref-type="bibr" rid="scirp.71155-ref31">31</xref>] , loss of tourism developments or value of land [<xref ref-type="bibr" rid="scirp.71155-ref61">61</xref>] . Loss of land value, however, contributes to only a fraction (4%) of total related economic impact (<xref ref-type="fig" rid="fig">Figure </xref>6) and on their own do not outweigh the estimated costs (see <xref ref-type="table" rid="table">Table </xref>S6 in OSI) to establish the MSW management systems. The willingness of households to pay for solid waste collection and treatment services has been better established compared to wastewater services in Indonesia [<xref ref-type="bibr" rid="scirp.71155-ref62">62</xref>] . This may be attributed to direct visibility of improving solid waste management [<xref ref-type="bibr" rid="scirp.71155-ref63">63</xref>] . Consequently, there is a larger potential for recovering some of the costs through MSW tariffs paid by households compared with tariffs for wastewater services. Potential revenues from fees were excluded from the BCR analysis, but are relevant for development of a cost-effective wastewater and solid waste management system.</p><p>Additional benefits of resource recovery from MSW can be a driver for improving water quality. The BCR (including MSW) of scenario 5 (applying AT) is 1.19 and will increase to 1.65 by applying resource recovery (<xref ref-type="table" rid="table">Table </xref>8). The BCR of scenario 6 with MSW recovery is even higher than the BCR of Scenario 5 applying ST (1.49) showing that required additional costs to improve the water quality can be financed through the sale of resources recovered from solid waste. However, application of resource recovery from wastewater only results in a minor increase in BCR (from 1.83 to 1.85) compared to applying only advanced technology. Thus, from a financial perspective using existing market prices, the additional investments to recover resources from wastewater out</p><table-wrap id="table8" ><label><xref ref-type="table" rid="table">Table </xref>8</label><caption><title> Calculated Benefits Costs Ratio (BCR) and five alternative BCR’s distinguishing (A) only WWT based BCR or (B) WWT and MSW based BCR</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Category</th><th align="center" valign="middle"  rowspan="2"  >Sub category</th><th align="center" valign="middle"  colspan="6"  >A. WWT costs and benefits</th><th align="center" valign="middle"  colspan="6"  >B. WWT and MSW costs and benefits</th></tr></thead><tr><td align="center" valign="middle" >S3: 50%_ST</td><td align="center" valign="middle" >S3: 50%_AT</td><td align="center" valign="middle" >S4: industrial only</td><td align="center" valign="middle" >S5: 50%_ST</td><td align="center" valign="middle" >S5: 50%_AT</td><td align="center" valign="middle" >S6: 50%_RR</td><td align="center" valign="middle" >S3: 50%_ST</td><td align="center" valign="middle" >S3: 50%_AT</td><td align="center" valign="middle" >S4: Industrial only</td><td align="center" valign="middle" >S5: 50%_ST</td><td align="center" valign="middle" >S5: 50%_AT</td><td align="center" valign="middle" >S6: 50%_RR</td></tr><tr><td align="center" valign="middle"  rowspan="6"  >BCR</td><td align="center" valign="middle" >Baseline BCR</td><td align="center" valign="middle" >3.20</td><td align="center" valign="middle" >2.06</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >2.64</td><td align="center" valign="middle" >1.83</td><td align="center" valign="middle" >1.85</td><td align="center" valign="middle" >1.62</td><td align="center" valign="middle" >1.26</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >1.49</td><td align="center" valign="middle" >1.19</td><td align="center" valign="middle" >1.65</td></tr><tr><td align="center" valign="middle" >Resource prices 50% of baseline</td><td align="center" valign="middle" >3.20</td><td align="center" valign="middle" >2.06</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >2.64</td><td align="center" valign="middle" >1.83</td><td align="center" valign="middle" >1.79</td><td align="center" valign="middle" >1.62</td><td align="center" valign="middle" >1.26</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >1.49</td><td align="center" valign="middle" >1.19</td><td align="center" valign="middle" >1.37</td></tr><tr><td align="center" valign="middle" >Health impact 50% of baseline</td><td align="center" valign="middle" >2.22</td><td align="center" valign="middle" >1.42</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >1.86</td><td align="center" valign="middle" >1.29</td><td align="center" valign="middle" >1.34</td><td align="center" valign="middle" >1.12</td><td align="center" valign="middle" >0.87</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >1.05</td><td align="center" valign="middle" >0.84</td><td align="center" valign="middle" >1.33</td></tr><tr><td align="center" valign="middle" >40 year capital lifespan</td><td align="center" valign="middle" >4.94</td><td align="center" valign="middle" >3.01</td><td align="center" valign="middle" >0.60</td><td align="center" valign="middle" >3.80</td><td align="center" valign="middle" >2.58</td><td align="center" valign="middle" >2.61</td><td align="center" valign="middle" >2.11</td><td align="center" valign="middle" >1.65</td><td align="center" valign="middle" >0.60</td><td align="center" valign="middle" >1.91</td><td align="center" valign="middle" >1.54</td><td align="center" valign="middle" >2.18</td></tr><tr><td align="center" valign="middle" >15 year capital lifespan</td><td align="center" valign="middle" >2.60</td><td align="center" valign="middle" >1.70</td><td align="center" valign="middle" >0.48</td><td align="center" valign="middle" >2.19</td><td align="center" valign="middle" >1.53</td><td align="center" valign="middle" >1.55</td><td align="center" valign="middle" >1.40</td><td align="center" valign="middle" >1.09</td><td align="center" valign="middle" >0.48</td><td align="center" valign="middle" >1.29</td><td align="center" valign="middle" >1.03</td><td align="center" valign="middle" >1.42</td></tr><tr><td align="center" valign="middle" >Access time gained 50% of baseline</td><td align="center" valign="middle" >2.75</td><td align="center" valign="middle" >1.76</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >2.28</td><td align="center" valign="middle" >1.58</td><td align="center" valign="middle" >1.61</td><td align="center" valign="middle" >1.39</td><td align="center" valign="middle" >1.08</td><td align="center" valign="middle" >0.52</td><td align="center" valign="middle" >1.28</td><td align="center" valign="middle" >1.03</td><td align="center" valign="middle" >1.50</td></tr></tbody></table></table-wrap><p>weigh the benefits by a small margin.</p><p>In case recovered resources are sold at only half the current market price (<xref ref-type="table" rid="table">Table </xref>8) the BCR of resource recovery (S6) is lower than for AT, but still higher than 1. The BCR may change depending on the lifespan of capital stock (<xref ref-type="table" rid="table">Table </xref>8). A lifespan of 40 years results in a BCR approaching 5 (S3: 50%_ST). A major part of the cost (<xref ref-type="table" rid="table">Table </xref>S1 in OSI) is related to sewer system developments that have typically much longer potential lifespans (even up to 100 years) [<xref ref-type="bibr" rid="scirp.71155-ref64">64</xref>] and therefore it is likely the BCR will be higher than the baseline BCR of 3.2 for that same scenario (S3: 50%_ST).</p></sec></sec><sec id="s4"><title>4. Discussion</title><sec id="s4_1"><title>4.1. Added Value of Integrated Approaches</title><p>Evaluating the economic performance of wastewater and solid waste interventions is a complex process, involving many variables and alternative combinations and coverage levels of interventions. Therefore a methodology was developed that combines several assessment methods and data sources in order to support decision making. The added value of the integrated approach allows for a nuanced view on interrelations compared to single cause-effect relations [<xref ref-type="bibr" rid="scirp.71155-ref65">65</xref>] . Thus the effects of different interventions on water quality, resource recovery potential, and related economic returns could be evaluated in parallel (Figures 5-7). This parallel evaluation provides significant benefits in a dynamic context [<xref ref-type="bibr" rid="scirp.71155-ref66">66</xref>] . It also addresses the need for a method that can quantitatively evaluate a set of sanitation alternatives to resolve trade-offs across sustainability dimensions (social, environmental, and economic) [<xref ref-type="bibr" rid="scirp.71155-ref67">67</xref>] .</p></sec><sec id="s4_2"><title>4.2. Added Value of the Approach in Practical Applications</title><p>The practical application of the integrated approach is first demonstrated in the analysis of contribution of pollution per sector (industry, domestic or agriculture) related to the pollution prevention costs. The large contribution of domestic pollution was unambiguous and confirmed in a sensitivity analysis (see also OSI, Section 7). Presented results are in line with findings of [<xref ref-type="bibr" rid="scirp.71155-ref13">13</xref>] who determined that households contributed 55%, industries 40% and agriculture 6% of BOD pollution entering the Saguling reservoir. Reference [<xref ref-type="bibr" rid="scirp.71155-ref11">11</xref>] demonstrated the importance of fertilizer use management to avoid future coastal eutrophication in Indonesian Rivers, which corresponds with the large nutrient load as a result of agricultural activities (25% for P) determined in the current study. Despite a relative low (28%) contribution of industrial COD pollution, 35% of COD can be reduced by industrial interventions, whereas the investment costs for industrial interventions are less than 10% of the domestic interventions (<xref ref-type="table" rid="table">Table </xref>S6 in OSI). Further, the number of industries is only a fraction (~1%) of the number of households in the Citarum area and monitoring interventions would be much more practical than monitoring individual household connections. Thus, although COD pollution from industry is relatively small, it is more cost effective (&gt;factor 5) than domestic, which may help a policy maker in prioritizing interventions.</p><p>Secondly, the integrated approach supports determination of cost-effective interventions. The added value of applying more advanced technologies or switching more people to a sewer system showed that required additional investments can be justified from the point of nutrient removal, but less so from COD removal (<xref ref-type="fig" rid="fig4"><xref ref-type="fig" rid="fig">Figure </xref>4</xref>). In addition, the use of software tools like RIBASIM to model and estimate the impact of discharged pollution loads on the anticipated water quality allows the policy maker to relate interventions and their cost to applicable water quality standards.</p><p>Thirdly, linking the resource recovery potential and its revenues to its potential demand may benefit formulation of policies or increase government involvement to foster financial sustainability of sanitation facilities [<xref ref-type="bibr" rid="scirp.71155-ref24">24</xref>] . The value of recoverable resources from solid waste has resulted in a very active, but informal waste recovery sector in Indonesia [<xref ref-type="bibr" rid="scirp.71155-ref68">68</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref69">69</xref>] . In addition, the demonstrated potential recovery of resources exceeding the agricultural demand allows for selective marketing, focusing on safe reuse (e.g. on non-edible crops) [<xref ref-type="bibr" rid="scirp.71155-ref70">70</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref71">71</xref>] . Electricity production from the joint wastewater and solid waste facilities is potentially higher than the demand for domestic wastewater and supports the potential for a joint development of wastewater and solid waste facilities [<xref ref-type="bibr" rid="scirp.71155-ref72">72</xref>] .</p><p>Fourthly, monetizing both direct use and indirect non-use values of sanitation implementation in relation to achievable surface water quality enables the formulation of a cost and environmental effective approach. The performed analysis demonstrated that the most cost effective scenario (S3: 50%_ST) with the highest BCR differs from the scenario reaching the required water quality (e.g. S5: 50%_AT). Therefore, a policy maker needs to prioritize between these two options. As a cost effective strategy, application of advanced technologies may be restricted to the most highly densely populated urban areas (where most pollution is produced). Alternatively, a phased approach in which first simple (low cost) technologies are implemented that are later replaced, converted or extended by systems that allow for nutrient removal [<xref ref-type="bibr" rid="scirp.71155-ref73">73</xref>] . Monetizing benefits may further help to raise funds from other sources or actors that benefit from improved water quality, such as residential project developers or tourism sites [<xref ref-type="bibr" rid="scirp.71155-ref32">32</xref>] .</p><p>The outcomes of the study were formulated in a planning document for the Indonesian government [<xref ref-type="bibr" rid="scirp.71155-ref53">53</xref>] and confirmed our hypothesis that quantification of tangible outputs using the presented approach can support policy-makers in the field.</p></sec><sec id="s4_3"><title>4.3. Options for Extending the Approach</title><p>The presented framework can be further extended given the following considerations:</p><p> To assess the sustainability of interventions and ensure that pollution is being removed and not displaced, environmental emissions other than water pollution (COD, N, P), such as odor or greenhouse gasses may be included. The effect of greenhouse gasses emitted by low cost technologies (e.g. anaerobic filters or septic tanks) is excluded from the current evaluation.</p><p> In the determination of the water quality, several assumptions were made that may affect obtained results and could be incorporated in a next phase (see also OSI Section 9). First, a connection between surface and ground water was assumed in which infiltrated septic tank effluent load directly influences the surface water quality. Second, RIBASIM model disregards biological conversion of pollutants in the surface water, whereas these are observed in the field [<xref ref-type="bibr" rid="scirp.71155-ref12">12</xref>] . Third, all interventions are assumed to be designed, constructed, operated and maintained correctly, which may be optimistic in view of current practice [<xref ref-type="bibr" rid="scirp.71155-ref37">37</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref74">74</xref>] . Fourth, the effect of dumped solid waste on water quality is excluded. Finally, surface water pollution from animal manure was excluded.</p><p> The low BCR of industrial interventions (0.52, <xref ref-type="table" rid="table">Table </xref>8) and the weak mandatory industrial regulation in Indonesia [<xref ref-type="bibr" rid="scirp.71155-ref75">75</xref>] may suggest limited possibilities to implement industrial pollution prevention. However, alternative means to spur Indonesian industries to comply with environmental standards such as public disclosure (the regular collection and dissemination of information about firms’ environmental performance) have been shown to be effective [<xref ref-type="bibr" rid="scirp.71155-ref76">76</xref>] .</p><p> Aerobic technologies were used as industrial references, whereas the use of anaerobic technologies may result in lower investment and/or operational costs [<xref ref-type="bibr" rid="scirp.71155-ref77">77</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref78">78</xref>] .</p><p> Not all economic impacts were quantified in this study (see also OSI, Section 10), such as consumption of fish imbibing toxic wastes or otherwise infected [<xref ref-type="bibr" rid="scirp.71155-ref79">79</xref>] , reduced land subsidence and improved recreational values [<xref ref-type="bibr" rid="scirp.71155-ref30">30</xref>] [<xref ref-type="bibr" rid="scirp.71155-ref80">80</xref>] . In addition, long-term impacts on the river and population of industrially discharged toxins and heavy metals were excluded and would specifically increase the BCR of scenario S4 (industrial intervention). Although the current study focuses on a part of a river basin only and uses locally collected data, a further detailing on a city or community level may be required to prevent overgeneralization and misunderstanding of individuals’ preference tradeoffs [<xref ref-type="bibr" rid="scirp.71155-ref81">81</xref>] .</p><p> Applying advanced technologies (AT) will improve water quality (<xref ref-type="fig" rid="fig">Figure </xref>5), but will not increase quantified health or welfare impact. At the same, anticipated long- term effects of reduced eutrophication and less impacted ecosystem functioning [<xref ref-type="bibr" rid="scirp.71155-ref11">11</xref>] were not quantified, whereas these would further increase the BCR.</p><p> The BCR considers the overall societal perspective, whereas different costs and benefits are incurred and enjoyed by different stakeholders. Thus, the costs of domestic interventions are to a large extent paid for by the national and local governments (in Indonesia ~ 70%) and to lesser extent by individual households [<xref ref-type="bibr" rid="scirp.71155-ref50">50</xref>] , whereas industries typically pay the costs of the interventions themselves [<xref ref-type="bibr" rid="scirp.71155-ref37">37</xref>] . Benefits of improved water quality as a result of interventions can be either increased revenues (e.g. sale of recovered resources) or averted costs (e.g. lower water treatment costs) which benefit a single party, or are generalized to the population (e.g. averted health or time costs) which benefit society as a whole [<xref ref-type="bibr" rid="scirp.71155-ref30">30</xref>] . In the elaboration of a planning document, the incidence of costs and benefits should be further detailed. In addition, serious institutional challenges have been identified in providing access to sanitation in a development world’s context [<xref ref-type="bibr" rid="scirp.71155-ref82">82</xref>] . To implement the planned sanitation development, the responsible institutions need to be identified and budgets should be allocated. A methodology to do this, involving private households, local and national governments, was described by [<xref ref-type="bibr" rid="scirp.71155-ref50">50</xref>] .</p></sec></sec><sec id="s5"><title>5. Conclusions</title><p>In this study, an integrated method was presented that quantified the economic costs and benefits of wastewater and solid waste interventions in relation to water quality improvements and resource recovery potential. The approach provides added value in the decision making process in a complex and dynamic context since it helps resolve trade-offs across different dimensions of sustainability (e.g. social, environmental and economic).</p><p>Identification of pollution sources and the impact of interventions on discharged pollution loads allows for prioritizing of actions. By simultaneously modeling the water quality and cost impact of variations in 1) type of technology and 2) the household numbers switching from poor-performing septic tanks to off-site systems, insight into the cost-effectiveness of environmental policies is provided. This allows a policy maker to optimize economic and water quality benefits.</p><p>In the presented case of the Upper Citarum River, domestic interventions applying simple technologies were most attractive, with an estimated BCR of 3.2. However, to achieve the target water quality both industrial and advanced domestic WWT technologies would be required, leading to an estimated BCR of 2.0. Resource recovery from MSW was found to be a driver for improving water quality, as benefits through the sale of recovered resource outweighed the additional costs to improve the water quality.</p></sec><sec id="s6"><title>Acknowledgements</title><p>The authors acknowledge the contribution of Aart van Nes, Fery Hardianto and Wil van der Krogt in the data collection and RIBASIM modeling as part of the 6 Ci’s project funded by the ADB (TA7189-INO: Institutional Strengthening for Integrated Water Resources Management (IWRM) in the 6 Ci’s River Basin Territory-Package B). The economic works of this study was funded by WSP’s Multi-Donor Trust Fund for WSP East Asia and the Pacific, supported by the Government of Australia. Guy Hutton conducted the work while employed at the World Bank. We thank Isabel Blackett, Almud Weitz, Enrico Rahadi Djonoputro, and Deviariandy Setiawan for their valuable input. In loving memory of pak Nugroho-Director of Urban, Housings and Settlements, National Development Planning Agency (Bappenas); may you rest in peace.</p></sec><sec id="s7"><title>Cite this paper</title><p>Kerstens, S.M., Hutton, G., Firmansyah, I., Leusbrock, I. and Zeeman, G. (2016) An Integrated Approach to Evaluate Benefits and Costs of Wastewater and Solid Waste Management to Improve the Living Environment: The Citarum River in West Java, Indonesia. Journal of Environmental Protection, 7, 1439-1465. http://dx.doi.org/10.4236/jep.2016.711122</p></sec></body><back><ref-list><title>References</title><ref id="scirp.71155-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">WHO and UNICEF (2015) Progress on Sanitation and Drinking Water—2015 Update and MDG Assessment. 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