Accepted Manuscript Cost, energy, global warming, eutrophication and local human health impacts of community water and sanitation service options Mary E. Schoen, Xiaobo Xue, Alison Wood, Troy R. Hawkins, Jay Garland, Nicholas J. Ashbolt PII:
S0043-1354(16)30895-8
DOI:
10.1016/j.watres.2016.11.044
Reference:
WR 12525
To appear in:
Water Research
Received Date: 15 June 2016 Revised Date:
31 October 2016
Accepted Date: 14 November 2016
Please cite this article as: Schoen, M.E., Xue, X., Wood, A., Hawkins, T.R., Garland, J., Ashbolt, N.J., Cost, energy, global warming, eutrophication and local human health impacts of community water and sanitation service options, Water Research (2016), doi: 10.1016/j.watres.2016.11.044. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Cost, Energy, Global Warming, Eutrophication and
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Local Human Health Impacts of Community Water
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and Sanitation Service Options
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Mary E. Schoen*a, Xiaobo Xueb, Alison Woodc, Troy R. Hawkinsd, Jay Garlande, Nicholas J.
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Ashboltf
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a.
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[email protected]
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b.
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Albany, State University of New York, 1 University Place, Rensselaer, NY 12144;
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Soller Environmental, Inc., 3022 King St., Berkeley, CA 94703;
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Department of Environmental Health Sciences, School of Public Health, University at
[email protected]
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c.
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Engineering, 301 E. Dean Keeton St. C8600, Austin, TX 78712-8600,
[email protected]
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d.
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Lexington, MA 02421;
[email protected]
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e.
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45268;
[email protected]
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The University of Texas at Austin, Dept. of Civil, Architectural and Environmental
Franklin Associates, a Division of Eastern Research Group, 110 Hartwell Avenue,
U.S. Environmental Protection Agency, 26 W. Martin Luther King Drive, Cincinnati OH
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f.
Rm. 3-57D South Academic Building, School of Public Health, University of Alberta,
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Edmonton AB T6G 2G7;
[email protected]
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ABSTRACT
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We compared water and sanitation system options for a coastal community across selected
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sustainability metrics, including environmental impact (i.e., life cycle eutrophication potential,
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energy consumption, and global warming potential), equivalent annual cost, and local human
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health impact. We computed normalized metric scores, which we used to discuss the options’
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strengths and weaknesses, and conducted sensitivity analysis of the scores to changes in variable
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and uncertain input parameters. The alternative systems, which combined centralized drinking
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water with sanitation services based on the concepts of energy and nutrient recovery as well as
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on-site water reuse, had reduced environmental and local human health impacts and costs than
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the conventional, centralized option.
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advantages of the alternative community water systems (compared to the conventional system)
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were in terms of local human health impact and eutrophication potential, despite large,
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outstanding uncertainties.
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energy recovery technologies had the least local human health impact; however, the cost of these
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options was highly variable and the energy consumption was comparable to on-site alternatives
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without water reuse or energy recovery, due to on-site water treatment. Future work should aim
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to reduce the uncertainty in the energy recovery process and explore the health risks associated
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with less costly, on-site water treatment options.
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Of the selected sustainability metrics, the greatest
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Of the alternative options, the systems with on-site water reuse and
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KEYWORDS
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Sustainability; water; wastewater; LCA; QMRA
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40 1.0 Introduction
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Planning for a sustainable community water system requires a comprehensive understanding
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and assessment of the integrated source water, drinking water, and sanitation services over their
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life cycles. In previous work, we described the need for and use of integrated sustainability
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assessment to evaluate community water systems within a stakeholder-driven framework (e.g.,
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integrated municipal water management (Thomas and Durham 2003)). In addition, we selected a
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set of technical metrics and tools which we consider critical to evaluate built water services, but
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also of reasonable effort to calculate (Xue et al. 2015). Then, we evaluated a selection of water
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service options for the coastal community of Falmouth, MA, using the proposed technical
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metrics, including environmental impacts (Xue et al. 2016), local human health impacts (Schoen
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et al. 2014), cost (Wood et al. 2015), and technical resilience (Schoen et al. 2015). In this
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companion paper, we summarize the strengths and weakness of the selected community water
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systems across the previously calculated, technical sustainability metrics using newly calculated
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normalized scores and discuss insights that can only come from looking at these metrics
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together.
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Throughout, we refer to metrics, defined as a measurable value of an attribute (e.g., equivalent
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annual cost), as well as the various input parameters (e.g., discount rate), which were used to
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calculate the metrics. An input parameter, metric, or score is referred to as variable if the
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variation in value cannot be reduced with collection of additional information; whereas
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uncertainty can be better estimated with collection of more or better data (Vose and Vose 2000). 3
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The metrics previously described include: local human health impact from pathogen and
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chemical exposures resulting from community-wide water system use; equivalent annual cost
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(EAC), which quantifies the monetary costs and benefits of each system; life cycle energy
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consumption; life cycle global warming potential (GWP) from on-site and supply chain
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greenhouse gas emissions including CO2, CH4, and N2O; life cycle eutrophication potential,
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which is based on on-site and supply chain releases of aqueous and atmospheric nitrogen and
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phosphorus; and technical resilience, which qualitatively evaluates the water system’s capacity to
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deal with potential future event and climatic challenges. Based on stakeholder input, only a
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selection of the available life cycle analysis impact categories was included in the evaluation of
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environmental impacts. Resilience was not included in the following comparative analysis
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because we were unable to differentiate the selected water system options (Schoen et al. 2015).
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This assessment is the first we are aware of to evaluate both water (i.e., potable and non-
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potable) and sanitation services (i.e., septic/sewage and greywater) across cost, environmental,
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and local human health impacts. Portions of community water systems (i.e., either water or
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sanitation) have been assessed by others using integrated or sustainability assessments for water
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supply (Lai et al. 2007, Rygaard et al. 2014), energy and water recovery options (Lee et al.
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2013), and firefighting flows (Aydin et al. 2014). These studies rarely include metrics that span
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health, environment, economic, and technological aspects (Malmquist 2006), especially the local
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human health impacts (Lai et al. 2007, Rygaard et al. 2014) and resilience metrics (Rygaard et al.
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2014). A further common deficiency is the lack of systematic consideration of variability and
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uncertainty across metrics when comparing system options (although, the variability in a subset
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of quantitative metrics was discussed by Fagan et al. (2010) and Rygaard et al. (2014)).
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The options considered here, described in the following section, include novel treatment and
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energy recovery elements not yet widely implemented or evaluated across the cost, local human
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health, and environmental metrics. As such, there remains considerable uncertainty associated
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with the input parameters used to calculate the metrics. The objectives of this work are to
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identify system options with clear advantages across the sustainability metrics while accounting
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for natural variability and/or uncertainty; and identify results that may change with collection of
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additional data to guide future information collection efforts for these novel technologies. While
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this paper focuses on the technical sustainability assessment results, and not the entire decision-
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making process, our discussion emphasizes how the results could be used in a stakeholder-
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preferred decision approach (e.g., Multi-Criterion Decision Analysis [MCDA](Belton and
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Stewart 2002)).
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2.0 Approach
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2.1 Case Study
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The case study town of Falmouth, MA, faces expanding urbanization (with a population of
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31,500 in 2011) and seasonal tourism, yet the predominating septic systems have resulted in
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excessive nutrient exports and coastal eutrophication (Cape Cod Commission 2015).
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evaluated five community water and wastewater service options to replace current traditional
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septic systems.
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The business-as-usual (BAU) system consisted of a conventional, centralized drinking water
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system and a centralized wastewater treatment system, referred to here as the conventional
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system (see Supporting Information Figure S1 for diagrams of the BAU treatment technology).
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The Falmouth community consumes about 4.6 million gallons per day (MGD) of water,
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approximately 60% of which is extracted from surface sources (Falmouth Department of Water 5
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2013). Considering the byproducts from wastewater treatment, the effluent and sludge, the
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former entered the groundwater through filtration basins and the latter was transported (after
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dewatering) out of the watershed to a management facility. There was no additional treatment of
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the byproducts or reuse. The following “alternative” options maintained the centralized drinking
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water system, but replaced the centralized wastewater treatment system. Two alternatives using
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septic systems were proposed by the stakeholders and two additional options were selected based
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on the concepts of energy recovery and water reuse.
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The first alternative included dry composting toilets and on-site greywater treatment by the
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existing septic system (CT-SS) that utilize absorption trenchs, where “greywater” refers to non-
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toilet wastewater from sinks, showers, washing machines, etc., within households (refer to
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Supporting Information Figure S2 for CT-SS technology diagrams). In the second alternative,
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the centralized wastewater treatment was replaced with urine-diverting toilets and on-site fecal
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solids (and greywater) treatment by the septic system (UD-SS) absorption trench system (refer to
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Supporting Information Figure S3 for UD-SS technology diagrams). For these septic-based
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options, the generated compost or urine was collected and transported out of the watershed to a
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less nutrient-sensitive area for use as soil amendments. No additional treatment of the generated
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byproducts was considered. All potable and non-potable household water uses were assumed to
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be supplied by the existing centralized drinking water system.
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In the third alternative, a low-volume flush toilet and blackwater pressure sewer were modeled
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to provide the community with energy recovery via a combined heat and power (CHP) anaerobic
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digester system in combination with community food residuals co-digestion. Blackwater was
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assumed to be supplied only via the toilets and kitchen food-waste grinders, hence containing
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more concentrated organic material and nutrients than traditional sewage, which is roughly 70% 6
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greywater. The dewatered digestate was assumed to be applied to local agricultural fields in the
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environmental assessments, but shipped out of the watershed in the EAC assessment (discussed
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in Sections 2.2.2 and 2.2.3). The on-site greywater was assumed to be collected; treated using
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biological sand filtration followed by ultraviolet disinfection; and reused for toilet flushing,
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outside irrigation, and watering homegrown salad crops, hence providing blackwater energy with
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greywater reuse (BE-GR). The final alternative was identical to BE-GR with the addition of on-
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site rainwater collection, treatment by in-line filtration and ultraviolet disinfection, and use as a
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hot-water supply for showering (BE-GRR) (refer to Supporting Information Figure S4 for BE-
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GR/R technology diagrams). The Cape Cod region has an annual precipitation average of 123
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inches (based on the last 50 years) (NOAA 2013). Falmouth has an existing separate stormwater
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system; therefore, stormwater was not addressed in this comparative analysis.
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2.2 Metrics
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2.2.1 Local Human Health Impact
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The local human health impact from the operation and community–wide use of each option
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was estimated using quantitative risk assessment including both operating and possible failing
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conditions (Schoen et al. 2014). The resulting key pathogen and chemical risks were translated
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into DALYs (Disability-Adjusted Life Years), i.e., the sum of years of life lost due to premature
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mortality and years lived with disability (Murray and Acharya 1997). The cumulative DALYs
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for each option were expressed as the 100-year DALY per 10,000 people. The human health
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impact was not assessed for global health burdens associated with the life cycle of the systems
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(Heimersson et al. 2014, Kobayashi et al. 2015a, Kobayashi et al. 2015b). While we recognize
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the relevance of the global human health life cycle impacts, particularly impacts from fine
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particulate matter such as released during power production, these tools are currently under
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development (Fantke et al. 2014) and were not included due to uncertainty associated with their
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calculation. The exposure pathways for the conventional option included the dominant exposure of
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ingestion of contaminated drinking water from a cross-connection of a drinking water main with
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sewage and the accidental ingestion of contaminated recreational water. All but the rainwater
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harvesting alternative (BE-GRR) included shower exposures to the surrogate disinfection by-
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product, chloroform. For the energy recovery digester options (BE-GR and BE-GRR), we
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modeled exposures to a suite of pathogens from ingestion of treated greywater from non-potable
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home and garden use and from ingestion of treated rainwater while showering for BE-GRR. The
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septic-based systems (CT-SS and UD-SS) included the exposure to contaminated recreational
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water from tank effluent and leakage. The application of byproducts (e.g., compost or sludge) as
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soil amendments was not assessed. The health impact assessment system boundary and
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assumptions are provided in the Supporting Information, Figure S5 and Section S1, as well as
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Schoen et al. (2014).
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2.2.2 Economic: Equivalent Annual Cost
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The equivalent annual cost (EAC) of each system quantified the monetary costs and benefits of
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each system with the reference year of 2014 (Wood et al. 2015). EAC provides a means of
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combining one-time and ongoing costs and benefits into an annualized cost stream to allow for
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comparison across alternatives with disparate temporal distributions of costs and benefits. All
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EACs were calculated on a per-household basis.
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The scope of the EAC assessment included the material/energy inputs during the installation
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(i.e., not manufacturing), operation and maintenance of water service starting from water
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extraction and ending with the end-of-life discharge/reuse of wastewater byproducts. The local 8
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costs of transportation of byproducts out of the watershed were included but not the costs and
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benefits of using the byproducts from novel treatment systems as fertilizers or soil conditioners
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because these products are generally not legal in the U.S., and thus there exists no market. We
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implicitly assumed replacement of systems/components in perpetuity, though costs become
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irrelevant as they are further in the future because of discounting at a positive rate. The range of
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discount rates explored comes from recommendations made by the National Center for
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Environmental Economics' to use 3% and 7% for the public and private rates of return on
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investments (we selected 5% as a midpoint) (National Center for Environmental Economics
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2010).
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All data and assumptions were based on the current scenario in Falmouth, MA, whenever
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possible. For example, we assumed that the water treatment and distribution systems currently in
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place will remain in operation, so fixed costs associated with operating and maintaining
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associated infrastructure were the same across all scenarios. Also, the sludge generated by BAU
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was transported out of the watershed to a management facility (no additional treatment or soil
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application was considered). The benefits captured include the cost savings due to water supply
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reduction, as well as the benefit from sale of energy generated by the anaerobic digester. Cost
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savings due to reduced water usage by certain technologies were accounted for by adjusting
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varying supply costs according to the water demand for each scenario, based on Falmouth’s
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existing block pricing structure for water supply. Since approximately 95% of homes in
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Falmouth use septic systems, and approximately 20% of these systems are not functioning
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properly, results reported here incorporate both functional and failing cases for the entire service
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area, assuming the systems were retrofitted in the calculation of cost.
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boundary and assumptions are in the Supporting Information, Figure S7 and Section S2, as well
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as Wood et al. (2015). 2.2.3 Environmental Impact
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Due to the local stakeholders’ interests, the life cycle assessment (LCA) was focused on the
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energy consumption, global warming and eutrophication potentials of the water and wastewater
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technology options (Xue et al. 2016). The scope of the LCA metrics included energy and
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material inputs and associated emissions during the construction and operation/maintenance
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stages of water services, assuming nominal operating conditions (not including impacts from
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treatment failures), starting from water extraction and ending with wastewater discharge/reuse
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(the system boundaries are depicted in Supporting Information Figure S8). The specific metrics
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included: life cycle energy consumption (MJ per household.day); life cycle global warming
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potential (kg CO2-equivalent per household.day); and life cycle eutrophication potential (g N-
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equivalent per household.day). The metrics were computed based on U.S.-specific inventory and
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using the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts
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(TRACI) impact assessment (EPA 2014).
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The functional unit (i.e., a measure of the equivalent function of the studied systems) was the
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water and ‘waste’ service requirement to meet a household’s water and sanitation needs. In order
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to ensure a fair comparison, system expansion was conducted in order to account for the nitrogen
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and phosphorus fertilizers and electricity provided by utilizing the household outflow of
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compost, urine, and blackwater (refer to Supporting Information Table S3). Options that did not
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supply energy or fertilizer were augmented with additional grid electricity (i.e., equivalent
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electricity production) and synthetic fertilizer, so that each scenario had an equivalent amount of
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electricity and fertilizer.
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The life cycle eutrophication potential of fertilizers (or soil amendments) was estimated based
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on the following assumptions. Similar to EAC, the dewatered sludge generated by BAU was
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transported out of the watershed to a management facility (no additional treatment or soil
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application was considered) and the urine and compost from CT-SS and UD-SS were transported
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to a less nutrient-sensitive watershed where they were used as soil amendments; this was
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possible because the energy savings of displacing synthetic fertilizer with urine was large enough
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to transport urine via a diesel truck up to 70–120 km, depending on the truck characteristics.
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Whereas, unlike the EAC assumptions, the dewatered digestate generated by BE-GR/R was used
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locally for soil amendment due to the high energy used to transport it.
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about the environmental metrics, please refer to Section S3 in the Supporting Information as well
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as Xue et al. (2016).
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For more information
2.3 Uncertainty and Variability
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In previous publications, we used three approaches to characterize the uncertainty and
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variability in each metric: 1) the LCA-based metrics combined the variability and uncertainty of
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input parameters into a Monte Carlo approach (not the life cycle impact characterization factors)
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and conducted a separate parametric uncertainty analysis based on the 5th, 50th, and 95th
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percentiles of the input parameters’ distributions (Xue et al. 2016); 2) the human health metric
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captured variability of exposure input parameters using a Monte Carlo approach and generated
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separate health impact distributions given different assumptions for a key uncertain input
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parameter, which was identified as part of a separate parametric uncertainty analysis (Schoen et
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al. 2014); and 3) the EAC metric used a parametric sensitivity analysis based on high- and low-
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input parameter estimates to characterize variability and uncertainty (Wood et al. 2015). The
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parameter/s with the most influence on each option’s metric variation using the previously
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performed parametric sensitivity and uncertainty analyses are listed in Table S6. We selected a subset of the variable or uncertain parameters: parameters that when varied,
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resulted in overlapping 5th and 95th percentiles of metric distributions across options (or the low
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to high predicted range for cost and the human health impact of BAU) in the above mentioned
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sensitivity analyses. These “key” parameters are discussed in the results section and were used
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in a sensitivity analysis of the normalized scores, described in the following section.
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In order to identify the best (and worst) performing system for each metric and compare the
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relative difference between the best and worst performing options across metrics, we calculated
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normalized scores of each metric (Linkov and Moberg 2011). We selected a zero-max scoring
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method, where the options were scored relative to the best performing option, which was given a
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score of one, based on the guidance provided by Rowley et al. (2012) (please see Supporting
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Information Section 4 for the score calculation).
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To highlight the options with clear advantages versus options with a wide range of
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performance due to natural variability and/or uncertainty, a sensitivity analysis of score was
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performed to show how the relative performance of the systems change due to variations in the
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selected, key input parameters.
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If the input parameter/s were uncorrelated among options, we recalculated all the options’
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scores using the high and low metric values identified in the sensitivity analyses for the option
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with uncertainty or variability and the best-estimate metric results for all other options (Tables
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S7-11, Supporting Information). If the variability or uncertainty was correlated, then the set of 12
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affected options was varied while the other options were set at their best estimates. This resulted
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in several scenarios for each metric, based on variations in key uncertain or variable input
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parameters, each with a set of associated scores. The 5th and 95th values of the predicted metric
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distribution were used instead of the predicted range from the parametric sensitivity analyses for
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the LCA-based metrics to simplify the presentation after a comparison of scores using both
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approaches showed little difference (results not shown).
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3.0 Results
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The results for each metric are summarized below (Figure 1).
The dominating process
contributing to each metric is listed in Table S12, Supporting Information.
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3.1 Local Human Health Impact
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The energy recovery digester and greywater reuse option (BE-GR) had the overall best local
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human health performance (due to the elimination of the exposure pathways of wastewater
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contaminated recreational water and a cross-connection between a water main and sewage). The
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alternative option that added rainwater use (BE-GRR) followed, and then the septic-based,
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composting toilet option (CT-SS) (Figure 2a). The conventional option (BAU) risk was
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attributed almost entirely to the cross-connection event of a water main with sewage. The BAU
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had two key, uncertain variables that resulted in a range of predicted performance, the dilution of
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the cross-contamination, and the frequency of sewer-to-drinking water cross-connection events.
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For the BAU median bar in in Figure 2a, a high dilution of sewage was assumed (i.e., 0.001),
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and a frequency of cross-connection events of every other year. The error bars addressed event
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frequencies of every year and 10 events in 100 years. We speculate that cross-connection events
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happen quite frequently (EPA’s Office of Ground Water and Drinking Water 2001); therefore,
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we calculated scores for the scenarios of 10, 50, and 100 events in 100 years for BAU (Table
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S13, Supporting Information). 3.2 Economic: Equivalent Annual Cost
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The alternative options had lower equivalent annual cost (EAC) than the conventional option
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(BAU) and these results were robust against the range of variability and uncertainty examined,
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except for the energy recovery digester and rainwater use option (BE-GRR) whose range of
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expected cost overlapped with the cost range of BAU (Figure 2b). The BE-GRR option may or
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may not be lower in cost than the conventional option, depending on variable and uncertain
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parameters. The parameters with the largest impact on BE-GRR’s costs were the 1) operation
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and maintenance (O&M) costs for the greywater recycling system, which vary dramatically
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depending on the specific system installed, and 2) the benefit from sales of electricity/heat
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generated in the digestion process. We calculated scores using the high and low metric results
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for the BE-GR and BE-GRR options, holding all other options at their best estimates (Table S14,
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Supporting Information).
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Costs for both the BE-GR and BE-GRR systems being (generally) lower than BAU might
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surprise professionals who know that pressure sewer systems have historically not been cost-
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competitive with gravity sewer systems. The combined system components resulted in the lower
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costs for the BE- systems. Key among these components are that extremely low-flush toilets
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were used, greywater was treated onsite, and systems were at the neighborhood scale rather than
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the city scale: these greatly reduced the volume of water being pumped and the distance of
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pumping, which greatly reduced the energy costs associated with pressure sewers.
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The septic system capital cost was a variable parameter shared by both septic-based options
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(UD-SS and CT-SS). This cost was extremely variable, depending on the specific installation
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and whether the existing septic system was usable or needed replacement. Still, if the septic costs
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were high (low) for a composting system in a given home, then the costs were similarly high
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(low) for a urine-diversion system in the same home. We calculated scores for the high and low
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septic capital cost scenarios for these options, holding all other options at their best estimates
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(Table S14, Supporting Information).
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3.3 Environmental Impact
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3.3.1 Life cycle eutrophication potential
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The conventional option (BAU) had the highest median eutrophication potential (Figure 2c).
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The septic-based options (CT-SS and UD-SS) had the least eutrophication potential over the
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range of variability and uncertainty explored. This was due to the assumption that urine and
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compost were collected from households and transported to a less nutrient-sensitive watershed
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where they could be used as soil amendments; whereas, we assumed that the digestate was used
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locally for soil amendments due to the high energy use to transport it.
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The eutrophication potential from the energy recovery digester options (BE-GR and BE-GRR)
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was highly variable and uncertain, depending on the composition of feed to the digester, and on
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various operation conditions such as temperature and retention time. We calculated scores using
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the 5th and 95th percentile eutrophication potential for the BE-GR and BE-GRR options, holding
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all other options at their best estimates (Table S15, Supporting Information).
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3.3.2 Life cycle energy consumption
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The conventional option (BAU) was the most energy intensive over the range of variability
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and uncertainty considered (Figure 2d), driven by the equivalent electricity production, sewage
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treatment, and drinking water treatment and distribution. Conversely, the blackwater energy
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recovery sewer options (BE-GR and BE-GRR), because of the associated electricity output, had
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the lowest median net energy requirement. Looking only at the septic-based options, UD-SS was always more energy intensive in the
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Monte Carlo iterations than CT-SS since the former demanded more treated drinking water than
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the latter. For the energy recovery digester options, BE-GRR was more energy intensive than
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BE-GR, since the rainwater treatment was more energy intensive than treating and supplying
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shower water with a centralized drinking water system.
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There was a great deal of overlap in the predictions of the septic-based options and the energy
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recovery digester options, and the dominating sources of variability and uncertainty were
341
uncorrelated. Variation in the direct electricity consumption of greywater treatment and reuse
342
had a great impact on metric variation for the BE-GR and BE-GRR alternatives. To estimate the
343
impact of this variation on the score, we calculated scores using the 5th and 95th percentiles of the
344
energy consumption distributions for the BE-GR and BE-GRR options, holding all other options
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at their best estimates (Table S16, Supporting Information).
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Uncertainty in the septic-based options’ energy consumption was introduced from the
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equivalent electricity production estimate. The energy produced from the bioreactors, which
348
sourced from household food waste and restaurant grease traps, was uncertain because of
349
uncertain compositions of digestion feed, which influenced the modeled biogas generation rate
350
and the methane content. We calculated scores using the 5th and 95th percentiles of the energy
351
consumption distributions for the CT-SS, UD-SS, and BAU options, holding the energy recovery
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digester options at their best estimate metric values (Table S16, Supporting Information).
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3.3.3 Life cycle global warming potential (GWP)
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The options with the energy recovery digester (BE-GR and BE-GRR) had much lower life
355
cycle greenhouse gas emissions over the range of variability and uncertainty explored (Figure
356
2e), mainly because the conventional (BAU) and septic-based options (CT-SS and UD-SS)
357
shared an additional equivalent electricity production. Although the BAU, CT-SS, and UD-SS
358
options had large, overlapping ranges of variability and uncertainty, the CT-SS and UD-SS
359
options had less GWP potential than BAU over the Monte Carlo iterations, given that all share
360
the equivalent electricity production; however, BAU also included the energy intensive
361
centralized wastewater treatment and sewerage collection system.
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Variability for all options was due, in part, to natural variation in the life cycle GWP of the
363
electricity mix (i.e., the percentages for various energy sources such as coal, natural gas,
364
biomass, etc.).
365
introduced by the amount of electricity produced from co-digestion and CHP processes. We
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calculated scores using the 5th percentile value of the GWP distribution for the BAU, CT-SS, and
367
UD-SS options due to low electricity produced from co-digestion and CHP processes, holding
368
the other options at their best estimate (Table S17, Supporting Information). We did not include
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a scenario with high GWP since the higher values of the predicted GWP distributions likely
370
resulted from high GWP of the electricity mix, which is a factor shared by all options.
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For the conventional and septic-based options, additional uncertainty was
3.4 Normalized Scores
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The comparison of technical sustainability metric scores of the water and wastewater system
373
options is summarized as a performance matrix (Table 1). The conventional option (BAU) had
374
the poorest performance among options for all scenarios examined across the local human health
375
impact, economic, and environmental impact metrics and for the range of variability and
376
uncertainty explored (Table 1), with one exception: the energy recovery digester option with
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greywater reuse and rainwater use (BE-GRR) had variable relative performance compared to that
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of BAU in EAC, depending on the assumptions. Hence, no alternative option dominated in performance across all metrics. Given the input
380
assumptions, the septic-based options (CT-SS and UD-SS) scored relatively better in life cycle
381
eutrophication potential; the energy recovery digester options (BE-GR and BE-GRR) scored
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relatively better in human health impact and GWP.
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It was difficult to differentiate the alternatives in terms of EAC due to variability. The relative
384
performance of the alternatives in terms of EAC changed depending on assumptions about the
385
cost of the greywater treatment and septic components (Figure 2a). For example, the BE-GR
386
score ranged from 0.57 to 1.00, depending on the on-site greywater treatment costs. The relative
387
performance of the alternatives in terms of life cycle energy consumption were similar and had
388
less variability and/or uncertainty than the EAC scores; however, the alternative with the highest
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score changed given assumptions about the energy requirements for greywater treatment and the
390
equivalent electricity production (Figure 2b).
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If decision makers were selecting between alternative options, BE-GR always out-performed
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BE-GRR, and CT-SS performed better than UD-SS on all metrics, except EAC. Looking closer
393
at the BE-GR and CT-SS scores, there were large differences in the local human health and
394
eutrophication potential scores between these two options, with CT-SS performing better for
395
eutrophication and BE-GR performing better for human health. Of course, these scores do not
396
account for the relative importance of the metrics for stakeholders.
397
potential was the most important metric in the decision process, as for the Falmouth
398
stakeholders, and the other metrics were roughly half as important or less, then CT-SS would
399
have a combined best-estimate score (i.e., the sum of the product of the best estimate normalized
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If the eutrophication
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score and a metric-specific importance weight for each metric) greater than BE-GR, even though
401
BE-GR scored better in local human health, EAC and GWP. However, the relative comparison
402
would likely change if our assumptions about the use of byproducts as soil amendments was
403
altered (see Section 4.2).
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4.0 Discussion
405
4.1 How could the results be used?
406
The normalized scores were computed to illustrate the strengths and weaknesses of the system
407
options across metrics. However, the scores can also be used in a decision process to further
408
explore tradeoffs. Previous work on integrated sustainability assessment of urban water systems
409
have identified the following general steps in a multiple criteria decision process: 1) structuring
410
the decision problem; 2) articulating and modeling the preferences; 3) aggregating the alternative
411
evaluations; and 4) developing recommendations (Guitouni and Martel 1998, Lai et al. 2008).
412
Decision makers interested in the options reported herein may choose to consider the
413
sustainability metric findings and normalized scores, along with other considerations (e.g., global
414
health impact (Fantke et al. 2014), water withdrawal, social, cultural, political and governance
415
aspects (Bertera 2013)), in steps 1, 3, and 4 using their preferred decision approach to select an
416
option.
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When aggregating the alternative evaluations and developing recommendations, we
418
recommend an approach that captures the variability and uncertainty in technical metric
419
performance. Many of the options had a wide range of metric performance due to outstanding
420
uncertainty and/or natural variability, particularly the local human health impact, EAC, and life
421
cycle energy use. This uncertainty (or variation) as well as the possible correlation among
422
system options can be included in the aggregating step using, at a minimum, the multiple zero-
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423
max score sets for EAC and life cycle energy use, based on variations in key uncertain or
424
variable parameters (see Supporting Information Tables S18-S23 for linear scores).
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advanced stochastic methods for aggregation require Monte Carlo samples from metric
426
distributions or score distributions, which would could be generated from the high, low scenarios
427
for EAC (Tervonen and Figueira 2008).
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Given the selected community water system options and assumptions, the outstanding
429
variability and uncertainty associated with EAC and energy consumption would be important to
430
resolve if these metrics were important to stakeholders in a decision process. Additional data on
431
the electricity production from digestion/co-digestion may affect the rankings of the alternative
432
options in life cycle energy consumption. This uncertainty also affected the GWP predictions,
433
but did not greatly affect the normalized scores of the options. Additional data on GWP and
434
EAC would not influence the decision process if, for example, eutrophication potential was
435
highly important compared to the other metrics. In addition, improvements to the metrics (i.e.,
436
the models) could better characterize the life-cycle eutrophication potential, EAC, and technical
437
resilience of system options (discussed in the Supporting Information, Section S5).
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4.2 Assumptions not explored through sensitivity analysis
439
For the septic-based options (CT-SS and UD-SS), we assumed that collected urine or compost
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was shipped out of the watershed and applied to a less nutrient-sensitive location.
441
assumption resulted in a relatively low eutrophication potential for the septic-based options. If
442
the byproducts were applied to soils within the watershed, perhaps due to geography or limited
443
access to transportation, the eutrophication potential of the septic-based options would increase
444
by an unknown magnitude, with likely small decreases in GWP and energy consumption.
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This
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We assumed that a distribution-wide cross-connection between potable and non-potable water
446
was unlikely for CT-SS, UD-SS, and BE-GR/R because these systems eliminated the traditional,
447
centralized sewerage distribution system. For the local human health impact of BE-GR/R, we
448
accounted for non-potable exposures to poorly treated or untreated greywater and rainwater;
449
however, we did not include isolated potable exposures to the untreated, on-site collected waters.
450
Using the results from the Supporting Information, Section S1, the 100-year human health
451
burden would increase by approximately 2 DALY per 10,000 people or less if one percent of the
452
population ingested of a mouthful (i.e., approximately 100 ml day-1) of contaminated water for a
453
duration of approximately a month each year. An increase in total BE-GR/R DALY of this
454
magnitude would not change the rankings of the options in terms of local human health impact.
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4.3 Scope Across Metrics
456
A key challenge was selecting the scope for each analysis.
For example, the scale of impacts
was different across metrics (e.g., local, non-local, and global), especially considering the
458
impacts from the application of byproducts., We accounted for the eutrophication potential from
459
both the local application of digestate generated from the co-digestion process and non-local
460
application of compost generated from the dry composting toilets.
461
assessment, we assumed that all of the options shared the same local health impacts from
462
agricultural applications given the fixed area of agricultural land, regardless if traditional
463
fertilizers or digestate was applied. We did not estimate non-local or global health impacts.
464
Whereas, for EAC, we did not quantify the costs and benefits of using fertilizer or soil
465
conditioner products generated from human waste because these products are generally not legal
466
in the U.S., and thus there exists no market and limited data to estimate the costs or benefits. We
467
recommend a comprehensive assessment to identify the tradeoffs between environmental,
For the human health
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468
economic, and human health aspects of utilizing urine/digestate/compost in agriculture for future
469
work. For the LCA-based metrics, environmental impacts including life cycle energy consumption,
471
global warming and eutrophication potentials, were calculated assuming equal provision of water
472
and wastewater service in Falmouth across options. For the local human health impact, we did
473
not assume equal provision of water and wastewater service across options; rather, we captured
474
expected local health impacts to the exposed users. Therefore, our analysis did not include
475
health impacts resulting from the utilization of LCA-derived “equivalent” products like
476
fertilizers.
477
differences between LCA impact assessment and microbial risk assessment quantifying local
478
human health impact (Harder et al. 2015, Harder et al. 2014).
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Recent publications include a comprehensive discussion on system boundary
4.4 Use of results for other locations
480
The human health impact findings can be transferred to other coastal localities for the selected
481
options. Only the recreational water risks were specific to Falmouth. Although the recreational
482
risks may change for other locations based on treatment plant outfall locations, septic density,
483
and other assumptions, the overall ranking of the options would likely remain unchanged, given
484
the extremely high health burden associated with the BAU cross-connection event and the low
485
health burden associated with the BE-GR/R options.
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In terms of cost, the centralized systems will vary the most from location to location,
487
depending on factors such as housing density, soil types, and plant design. For decentralized
488
systems, regional effects are likely to be smaller than the variation and uncertainty already
489
incorporated in the cost estimates, especially for the most sensitive parameters. It is likely that in
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490
other coastal locations where septic systems are the current norm, the septic options would also
491
have lower costs than the centralized option and the digester would remain highly uncertain. Considering the life cycle energy consumption and GWPs, the ability to apply the results
493
specific to Falmouth to other coastal localities is limited by the use of specific values
494
representing local topography, water resources and quality, plant design, and climate. For
495
example, the energy consumption of wastewater and blackwater collection is highly dependent
496
on local factors such as topography, population density, and transport distance. However, the
497
energy consumption and GWP of the on-site greywater reuse system with a designated treatment
498
technology should vary less across different locations than the BAU would. The absolute values
499
of eutrophication potentials will vary based the digester characteristics, when applicable; the
500
nutrient transport and fate in the local environment; and the characteristics of the receiving water
501
body.
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4.5 Insights: Alternative community water systems for coastal communities
503
The community water systems that incorporated elements of water reuse and energy recovery
504
did not perform best across the selected sustainability metrics compared to options without these
505
elements. The local human health impact of options with community energy recovery and on-site
506
water reuse was lower than options without these elements (i.e., options incorporating septic-
507
based sanitation services and the conventional system); however, the cost of these energy
508
recovery and water reuse options was highly uncertain and variable, due in part to the variability
509
in cost of the on-site water treatment systems. In addition, the life-cycle energy consumption was
510
comparable for alternatives options with and without energy recovery, for the majority of the
511
sensitivity analysis runs. The sensitivity analysis of the cost and energy consumption scores
512
indicated that decreasing the on-site greywater treatment cost and energy use increases the
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relative performance of systems that incorporated elements of water reuse and energy recovery.
514
Given this knowledge and the predicted low health risks associated with the reuse of treated
515
greywater and harvested rainwater for non-potable purposes (please refer to the review of health
516
risk from non-potable reuse (Schoen and Garland 2015)), future work should explore the health
517
risks of on-site treatment options that are less costly and less energy intensive than biological
518
sand filtration followed by conventional ultraviolet disinfection.
520
5.0 Conclusions •
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Alternative community water systems, based on the concepts of energy and nutrient recovery as well as on-site water reuse, had reduced environmental and local human
522
health impacts and costs than a conventional, centralized system for the selected coastal
523
community.
524
•
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The sensitivity analysis of the normalize sustainability metric scores to changes in key, uncertain and variable parameters identified options with clear advantages for some
526
metrics and options with a wide range of performance due to natural variability and/or
527
uncertainty. •
Of the selected sustainability metrics, the greatest advantages of the alternative
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community water systems (compared to the conventional system) were in terms of
530
local human health impact and eutrophication potential, despite large, outstanding
531 532 533
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uncertainties. Whereas, the outstanding variability and uncertainty made it difficult to differentiate the relative performance of the options in terms of cost and energy consumption.
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534
•
Additional research on the expected energy generation from community digesters could
535
be important to collect to differentiate the overall sustainably of the options, but only if
536
energy consumption is relatively important to stakeholders. •
The LCA practice of “system expansion” remains problematic when estimating the
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local human health impact given that the local risk assessment focused on expected
539
exposures to users. •
Ultimately, modifications to the technology and additional iterations of integrated
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sustainability assessment are required to find a water and sanitation service solution
542
that performs best across all technical sustainability metrics.
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Abbreviations
544
EAC, equivalent annual cost which quantifies the monetary costs and benefits of each system;
545
GWP, life cycle global warming potential which is resulted from on-site and supply chain
546
greenhouse gas emissions including CO2, CH4, and N2O; BAU, the business-as-usual system,
547
consisted of a conventional, centralized drinking water system and a centralized wastewater
548
treatment system; CT-SS, composting toilets and on-site greywater treatment by the existing
549
septic tank absorption trench system; UD-SS, urine-diverting toilets and on-site fecal solids
550
treatment by the septic tank absorption trench system; BE-GR, non-potable greywater reuse
551
paired with a low-volume flush toilet and blackwater pressure sewer with energy recovery via a
552
combined heat and power anaerobic digester system in combination with community food
553
residuals co-digestion; BE-GRR, identical to BE-GR, with the addition of on-site rainwater use
554
as a hot-water supply for showering; MCDA, Multi-Criterion Decision Analysis; MGD, million
555
gallons per day; CHP, combined heat and power; DALYs, Disability-Adjusted Life Years;
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TRACI, Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts;
557
LCA, Life Cycle Assessment; and O&M, operation and maintenance.
558
Funding Sources
559
This project was supported by the U.S. Environmental Protection Agency Office of Research and
560
Development.
561
Acknowledgment
562
This project was supported by the U.S. Environmental Protection Agency Office of Research and
563
Development. The views expressed in this article are those of the authors and do not necessarily
564
reflect the views or policies of the U.S. Environmental Protection Agency. Any mention of
565
specific products or processes does not represent endorsement by the U.S. EPA. We thank our
566
peer reviewers, Dr. Jennifer Cashdollar, Dr. Cissy Ma, Dr. Michael Blackhurst, and Dr.
567
Desmond Lawler for adding insight into this assessment. We thank the Cape Cod community,
568
US EPA Region 1, and the Cape Cod Commission, as well as specific contributors (Marilyn ten
569
Brink, Hilde Maingay, Earle Barnhart, Gerald Potamis, Ken Moraff, Valerie Nelson and
570
Abraham Noe-Hays).
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Table 1. Best estimate zero-max scores and ranges (in parentheses)1 computed from variations in selected uncertain parameters (superscript) Centralized water and digester with greywater nonpotable reuse (BEGR)
Centralized water and digester with greywater reuse and rainwater for non-potable use (BE-GRR)
1.5×10-2
Centralized water and urinediversion toilet with septic (UDSS) 7.2×10-3
Human Health Impact
1.7×10-3 (8.9×10-4-7.1×10-3)2
1.00
5.6×10-2
Life Cycle Eutrophication Potential
4.5×10-2
1.00
0.34
6.1×10-2 (4.6×10-2-9.6×10-2)3
6.1×10-2 (4.6×10-2-9.6×10-2)3
Equivalent Annual Cost
0.38 (0.26-0.38)4-5
0.81 (0.55-0.85) 4-5
1.00 (0.68-1.00) 4-5
1.00 (0.57-1.00) 4-5
0.52 (0.38-0.52) 4-5
Life Cycle Global Warming Potential
0.20 (0.31)6
0.22 (0.37) 6
0.22 (0.35) 6
1.00
0.92
Life Cycle Energy Use
0.55 (0.41-0.61)7-8
0.83 (0.63-0.93) 7-8
1.00 (0.88-1.00) 7-8
0.93 (0.84-0.93) 7-8
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Centralized water and composing toilet with septic (CT-SS)
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0.90 (0.67-1.00) 7-8
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1. The range (in parentheses) was omitted if the variation in input parameter(s) resulted in no change in score
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2. Frequency of cross-connection between a water main and sewage for BAU 3. Discharge from the digester digestate for BE-GR/R 4. Greywater treatment system operation and maintenance costs for BE-GR/R
5. Septic system costs of UD/CT-SS 6. Only one variation considered, low GWP for BAU, CT/UD-SS, due to low electricity
produced from the co-digestion and CHP process for BE-GR/R 7. Equivalent electricity required for BAU and CT/UD-SS 8. Energy consumption of greywater treatment and reuse for BE-GR/R
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b. Equivalent annual cost
1.E+03
5,000
1.E+02
4,000
1.E+01 1.E+00 1.E-01 1.E-02 UD-SS
BE-GR
BE-GRR
BAU
MJ per household.day
10 5 0
UD-SS
BE-GR
BE-GRR
1,400 1,200
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15
CT-SS
d. Life cycle energy consumption
20
1,000 800 600 400 200 0
BAU
CT-SS
UD-SS
BE-GR
BE-GRR
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e. Life cycle global warming potential 200 150
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100 50 0
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kg Co2-eq per household.day
3
1,000
SC
CT-SS
c. Life cycle eutrophication potential
2
2,000
0 BAU
1
3,000
RI PT
$ per household
DALYs per 10,000 people over 100 years
a. Local human health impact
BAU
CT-SS
UD-SS
BE-GR
BE-GRR
BAU
CT-SS
UD-SS
BE-GR
BE-GRR
ACCEPTED MANUSCRIPT
Figure 1. Sustainability metric results for (a) local human health impact (DALYs per 10,000 people over 100 years), (b) equivalent annual cost (2014 $ per household), (c) eutrophication potential (g N-equivalent per household.day), (d) energy consumption (MJ per household.day),
RI PT
and (e) global warming potential (kg CO2–equivalent per household.day). Bars represent median results and error bars present 5th and 95th percentiles (except for cost and human health impact for BAU, where the bar represents the best estimate and error bars present low and high
SC
scenarios). BAU: business-as-usual conventional, centralized sewer; CT-SS: composting toilet with greywater septic system; UD-SS: urine-diversion toilet with household sewer to septic
M AN U
system; BE-GR: blackwater sewer for energy recovery and household greywater treatment and reuse; BE-GRR: the same as BE-GR but also including rainwater harvesting, treatment, and use
AC C
EP
TE D
for hot-water.
ACCEPTED MANUSCRIPT
High septic system costs for CT/UD-SS
RI PT
Low septic system costs for CT/UD-SS BE-GRR
High greywater treatment costs for BE-GR/R
BE-GR UD-SS
Low greywater treatment costs for BEGR/R
CT-SS
Base Case Cost 0
0.2
0.4
0.6
SC
BAU
0.8
1
M AN U
a. Equivalent Annual Cost Score
Low energy requirements for greywater treatment for BE-GR/R High energy requirements for greywater treatment for BE-GR/R
TE D
Low equivalent electricity for BAU, CT/UD-SS
BE-GRR BE-GR UD-SS
High equivalent electricity for BAU, CT/UD-SS
CT-SS BAU
Base Case Energy Use
EP
0
0.2
0.4
0.6
0.8
1
b. Life Cycle Energy Consumption Score
AC C
Figure 2. Sensitivity Analysis of Zero-max scores for (a) equivalent annual cost and (b) life cycle energy consumption. The scores (x-axis) of the community water system options are presented for different input parameter assumptions (y-axis).
ACCEPTED MANUSCRIPT
•
Novel community water systems had reduced environmental and health impacts and costs than a conventional system. The greatest advantages of novel water systems were in local human health impact and
RI PT
•
eutrophication potential. •
There was large uncertainty associated with on-site water treatment and community
The novel water system options had different strengths and weaknesses across metrics.
AC C
EP
TE D
M AN U
•
SC
digesters.
