Received: 14 June 2019 Accepted: 14 September 2019 Published online: 23 January 2020

DOI: 10.1002/jeq2.20031

S P E C I A L S E C T I O N

System-level Nutrient Pollution Control Strategies

Assessing cost-effective nutrient removal solutions in the urbanwater systemBrock Hodgson Tyler Dell Sybil Sharvelle Mazdak Arabi

Dep. of Civil and Environmental Engineering,

Colorado State Univ., 1372 Campus Delivery,

Fort Collins, CO 80523, USA

CorrespondenceBrock Hodgson, Dep. of Civil and Environ-

mental Engineering, Colorado State Univ.,

1372 Campus Delivery, Fort Collins, CO

80523, USA.

Email: brockhodgson@gmail.com

Funding informationUSEPA, Grant/Award Number: RD835570

Assigned to Associate Editor: Ray Anderson.

AbstractMany states are adopting more stringent nutrient load restrictions, requiring utili-

ties to invest in costly improvements. To date, substantial research has been done

to independently assess the nutrient removal efficacy of wastewater treatment tech-

nologies and stormwater control measures. The analysis presented here provides a

unique assessment by evaluating combinations of nutrient load reduction strategies

across water supply, wastewater, and stormwater sectors. A demonstration study was

conducted evaluating 7812 cross-sector removal strategies in the urban water sys-

tem using empirical models to quantify efficacy of common wastewater treatment,

water management, and stormwater control measures (SCMs). Pareto optimal solu-

tions were evaluated to identify the most cost-effective strategies. To meet stringent

nutrient requirements, wastewater treatment facilities (WWTFs) will likely require

advanced biological nutrient removal with carbon and ferric addition. Even with these

technologies, WWTFs may still be unable to obtain target nutrient requirements. In

addition, municipalities can consider water management practices and SCMs to fur-

ther reduce nutrient loading or provide a more cost-effective nutrient removal strategy.

For water management practices, source separation and effluent reuse were frequently

identified as part of the most effective nutrient strategies but face engineering, polit-

ical, and social adoption barriers. Similarly, SCMs were frequently part of effective

nutrient removal strategies compared to only adopting nutrient removal practices at

WWTFs. This research provides the framework and demonstrates the value in using

an urban water system approach to identify optimal nutrient removal strategies that

can be easily applied to other urban areas.

1 INTRODUCTION

The issue of nutrient pollution is recognized as one of the

most significant environmental issues today (USEPA, 2016).

Abbreviations: 5SBAR, five-stage Bardenpho; A2O, anaerobic, anoxic,

oxic; AS, ammonia stripping; BRB, bioretention basin; CA, carbon addition;

CaRRB, centrate and return activated sludge reaeration basin; EDB,

extended detention basin; FA, ferric addition; MLE, modified Ludzack

Ettinger; NS, nitrite shunt; PAD, post-aerobic digestion; PV, present value

cost; SCM, stormwater control measure; SP, struvite precipitation; TN, total

nitrogen; TP, total phosphorus; WWTF, wastewater treatment facility.

© 2019 The Authors. Journal of Environmental Quality © 2019 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America

Many states have recently or are in the process of adopt-

ing regulations to reduce nutrient loading into watersheds

(USEPA, 2018). Nutrient pollution originates from a variety

of activities including point sources, urban nonpoint sources,

rural nonpoint sources, and atmospheric deposition (Daigger,

Datta, Stensel, Whitlock, & Mackey, 2014). In an urban water

system, nutrient pollution is primarily from wastewater treat-

ment facilities (WWTFs) and stormwater runoff.

Traditionally, reduction of nutrient from the urban water

system is primarily achieved by implementing process

improvements at WWTFs. However, improving nutrient

removal at WWTFs may have substantial capital and

534 wileyonlinelibrary.com/journal/jeq2 J. Environ. Qual. 2020;49:534–544.

HODGSON ET AL. 535

operational cost implications (Daigger et al., 2014). There-

fore, it may be necessary or more cost effective to consider

implementing a combination of water management prac-

tices, wastewater technologies, and stormwater control

measures (SCMs) throughout an urban water system. The

most effective strategies will vary based on a variety of

factors including, but not limited to, density and size of the

urban environment, the type and degree of commercial and

industrial applications, impervious area, existing infrastruc-

ture, geography, climate, and natural background nutrient

loads originating from upstream areas in the watershed. In

some areas, the contributions from nonpoint sources are so

significant that even complete elimination from point sources

would still not meet the nutrient targets (WERF, 2010),

and adopting strategies only at WWTF may not meet target

stream concentrations (Son & Carlson, 2012). Therefore, it

is important that a nutrient load reduction strategy considers

application of practices across the urban water system.

Sources of nutrient pollution and strategies for reducing

loading have been evaluated in a variety of watersheds, most

notably in coastal estuaries, across the United States, includ-

ing the Long Island Sound, Chesapeake Bay, Gulf of Mexico,

and San Francisco Bay, to name a few (Falk et al., 2015;

Howarth, Sharpley, & Walker, 2002). Various approaches

have been applied to evaluate the individual effectiveness of

wastewater technologies and SCMs. For WWTFs, there is a

variety of treatment approaches and process configurations

that can be considered. These configurations are typically

evaluated with mechanistic models that use a series of

state variables, kinetic parameters, and water quality and

process-specific inputs to evaluate biological, chemical, pH,

gas–liquid, and mass transfer reactions (WERF, 2003). To

reduce the level of treatment necessary at WWTFs, water

management practices like source separation of urine or gray-

water reuse can be adopted to reduce influent nutrient load

to a WWTF. Similarly, WWTF effluent reuse can reduce the

effluent flow and associated nutrient load directly discharged

to the receiving water body. McKenna, Silverstein, Sharvelle,

and Hodgson (2018) and Hodgson, Sharvelle, Silverstein,

and McKenna (2018) used a mass balance analysis combined

with mechanistic modeling to quantify the impacts of com-

mon water management strategies on WWTF performance

and downstream water quality, identifying a benefit to

downstream water quality when adopting source separation,

graywater irrigation reuse, or effluent reuse. For stormwater,

pollutant load and SCM effectiveness are typically quantified

using the Simple Method or computer-based models like

USEPA’s Stormwater Management Model (SWMM) or the

Hydrologic Simulation Programming-FORTRAN (HSPF,

where FORTRAN stands for “formula translation”) model

(Ohrel, 2000; Schueler, 1987). Both model approaches

have been implemented effectively where the Simple

Method provides an estimate with fewer inputs, whereas the

Core Ideas• Identifying Pareto optimal solutions facilitates

urban water system evaluations.

• Nutrient strategies integrating water, stormwater,

and wastewater are most effective.

• A holistic urban water approach is needed to meet

stringent nutrient requirements.

• Source separation of urine, although challenging,

was common among effective strategies.

computer-based models provide a higher level of accuracy

but require more data for inputs and model calibration.

The existing tools and modeling approaches for evaluating

the effectiveness of a nutrient removal practice are data inten-

sive and time consuming (WERF, 2010). Additionally, the

modeling efforts focus on evaluating nutrient removal from

a single sector (i.e., either stormwater or wastewater). Lim-

ited research has assessed efficacy of nutrient removal across

sectors within the urban water system. An urban water system

evaluation framework is needed to enable cross-sector analy-

sis to identify optimal nutrient removal strategies considering

water management practices, wastewater treatment technolo-

gies, and SCMs.

The objectives of this research were to investigate the most

effective nutrient removal strategies considering adoption of

water management practices, WWTF process configurations,

and SCMs, and to explore tradeoffs between cost and effi-

ciency for removing nitrogen and phosphorus. To accomplish

this, a framework was developed to identify the most effective

nutrient removal strategies for meeting target loading condi-

tions by implementing empirical models and estimating cost

to quantify and compare the cost effectiveness of each sce-

nario. Optimal, or nondominated, solutions were identified

from all possible combinations of nutrient control strategies.

The approach developed here provides a framework to assess

and compare many nutrient removal strategies across sectors

to identify optimal strategies at the urban system scale.

2 MATERIALS AND METHODS

2.1 Framework for urban water systemanalysis

The urban water system analysis framework applied here

includes use of empirical models to estimate performance of

wastewater technologies, water management strategies, and

SCMs to estimate urban system nutrient load reduction based

on readily available inputs. Optimization algorithms are then

applied to identify nondominated solutions that minimize

536 HODGSON ET AL.

F I G U R E 1 Overview of urban water system cross-sector

analysis framework for evaluating and identifying effective nutrient

removal strategies. WWTF, wastewater treatment facility; SCMs,

stormwater control measures

cost, while maximizing nutrient load reduction. Details of the

empirical models, cost estimations, and optimization algo-

rithms are included in the sections below.

2.2 Urban water system nutrient load analysis

Urban water system nutrient load analysis was accomplished

by using previously developed empirical models for water,

wastewater, and stormwater technologies (described below) to

estimate nutrient removal effectiveness. Unit costs were esti-

mated as a function of percentage adoption to determine the

total cost and cost per pound of nutrient load reduced. Empir-

ical model inputs could be readily obtained for a study area

and scenarios developed to evaluate combinations of nutrient

removal strategies across the urban water system (Figure 1).

The following practices were included in the analysis:

• Water management practices: urine source separation,

graywater irrigation reuse, WWTF effluent reuse.

• WWTF process configurations: existing process, modified

Ludzack Ettinger (MLE), MLE + nitrite shunt (NS), MLE

+ carbon addition (CA), MLE + ferric addition (FA), MLE

+ CA + FA, MLE + struvite precipitation (SP), MLE

+ ammonia stripping (AS), MLE + centrate and return

activated sludge reaeration basin (CaRRB), MLE + post-

aerobic digestion (PAD), anaerobic, anoxic, oxic (A2O),

and five-stage Bardenpho (5SBAR).

• SCMs: extended detention basin (EDB), bioretention basin

(BRB).

Scenarios were developed combining the above practices,

which included 1 of 12 WWTF process arrangements, none

or one of three water management practices, and none or one

of two SCMs. In the study area, water management practices

were evaluated at 5% adoption intervals from 0–50% of the

population, and SCMs were evaluated at 10% adoption inter-

vals from 0–100% capture of the impervious area; therefore, a

total of 7812 scenarios were evaluated for achieving nutrient

reduction targets.

Evaluating combinations of these practices was accom-

plished by synthesizing previously developed modeling

approaches from each sector. The modeling approach for

each sector was developed using means and methods con-

sistent with standard practice and calibrated and validated to

measured data where possible (Hodgson & Sharvelle, 2019;

Hodgson et al., 2018; Schueler, 1987).

2.3 Water management practices

Previous studies completed by McKenna et al. (2018) and

Hodgson et al. (2018) quantified the impact of indoor

conservation, source separation, graywater toilet reuse,

graywater irrigation reuse, and WWTF effluent reuse on

wastewater treatment efficiency, effluent water quality, and

downstream nutrient loading using a calibrated wastewater

model (BioWin; EnviroSim Associates, 2017). BioWin

is widely used to evaluate WWTF performance based on

various process simulations (Foley, de Haas, Hartley, & Lant,

2010; WERF, 2003). The impact of indoor conservation and

graywater toilet reuse had negligible impacts on WWTF per-

formance and effluent water quality (Hodgson et al., 2018),

and high levels of indoor water conservation can even neg-

atively affect influent and effluent water quality, especially

total nitrogen (TN) (McKenna et al., 2018). Therefore, for this

paper, indoor conservation and graywater toilet reuse were

not evaluated. To account for the uncertainty across WWTFs

with adoption of source separation and graywater irrigation

reuse, additional work was performed to evaluate the analysis

performed by Hodgson et al. (2018) using three additional

WWTFs (Supplemental Figures S1 and S2). General char-

acteristics of these WWTFs are provided in Supplemental

Table S1. A linear regression analysis was performed based

on BioWin models calibrated to observed data for four

WWTFs and validated using a model based on independent

data from a fifth WWTF to account for the uncertainty across

variations in wastewater process characteristics and treatment

configurations (Equation 1; Supplemental Table S2):

Δ𝐿EFF = β0 + β1 × (%population)

+ β2 × (%population)2 + ε (1)

Lastly, a mass balance model was applied for quantifying

the fractional change in load removed (ΔLEFF) with adop-

tion of effluent reuse as a function of percentage flow reused

(Equation 2; Supplemental Table S2):

Δ𝐿EFF = β0 + β1 × (%eff luent reuse) + ε (2)

HODGSON ET AL. 537

2.4 Wastewater treatment facility processes

To enable evaluation and comparison of nutrient removal

effectiveness for different WWTF processes, Hodgson and

Sharvelle (2019) developed generalized regression relation-

ships using four calibrated wastewater models (BioWin). The

models were obtained from different utilities and have been

developed and calibrated to reasonably represent the WWTF

performance based on measured data (effluent concentration).

The model results were used to develop simplified empiri-

cal models to facilitate systems level evaluations of wastew-

ater treatment performance while accounting for uncertainty

across WWTF based on variations in process characteristics,

influent wastewater characteristics, and operational controls.

The empirical models were tested against a fifth wastewa-

ter model and verified against measured effluent data (Hodg-

son & Sharvelle, 2019). The study used a 95% prediction

interval to verify that the empirical models reasonably esti-

mate nutrient removal under various process configurations

while accounting for the uncertainty due to excluded vari-

ables, variations across WWTFs, and model fit. The general-

ized models estimate the percentage TN and total phosphorus

(TP) removal characterized as a linear regression relationship

based on influent ratio of chemical oxygen demand (COD) to

TN or TP (Equation 3 and Equation 4, respectively):

TN (%) = β0 + β1 × (COD∕TN) + β2 × (COD∕TN)2

+ β3 × (COD∕TN)3 + ε (3)

TP (%) = β0 + β1 × (COD∕TP) + ε (4)

The parameters for Equation 3 and 4 are presented in Sup-

plemental Table S3. For TN and TP removal with CA, bio-

logical phosphorus removal (A2O and 5SBAR), and FA, the

percentage removal was assumed based on literature reported

achievable removal efficiencies to establish the maximum

percentage removable achievable and account for challenges

associated with biological process modeling (Hodgson &

Sharvelle, 2019). The achievable TN removal was assumed to

be 95% for CA, and the achievable TP removal was assumed

to be 90% for FA (USEPA, 2010). For biological phosphorus

removal, 80–90% TP removal is achievable (USEPA, 2010);

therefore, TP removal was assumed to be 85% for A2O and

90% for 5SBAR.

2.5 Stormwater control measures

The impacts of SCMs on nutrient loading were estimated

based on the Simple Method (Schueler, 1987), which is a

widely accepted method for estimating pollutant load based

on land use to calculate the urban stormwater loads with

and without implementation of various SCMs where nutrient

loading is calculated based on Equation 5:

𝐿 = 0.1 × 𝑃 × Pr × Rv × 𝐴 × 𝐶 (5)

where L is the pollutant load in kilograms, P is the precipita-

tion in centimeters, Pr is the fraction of precipitation events

that produces runoff, Rv is the runoff volume coefficient

(based on impervious area), A is the drainage area in hectares,

C is the event mean pollutant concentration as milligrams per

liter, and 0.1 represents the unit conversion.

A Pr value of 0.9 was assumed based on local conditions

(Schueler, 1987), and Rv was calculated as a function of the

percentage impervious to account for the amount of precipita-

tion that results in runoff as indicated in Equation 6 (Schueler,

1987):

Rv = 0.05 + 0.009 × 𝐼 (6)

where I is the percentage imperviousness.

To conduct the analysis, current land use areas must

be obtained from the local municipality(s). The percent-

age imperviousness for each land use polygon is calculated

using the 2011 USGS National Land Cover Database (USGS,

2014), and the land use types are generalized to open space,

residential, commercial, industrial, institutional, or highway.

Lastly, median runoff concentrations for TN and TP are

assumed from literature reported measured runoff concentra-

tions based on land use classification (Wright Water Engi-

neers et al., 2013; Supplemental Table S4).

To account for the change in pollutant load with the

implementation of SCMs, Equation 5 was adapted to apply a

percentage removal of nutrient loads to percentage of imper-

vious area treated. Stormwater control measures were not

considered to reduce the load for pervious areas. Equation 7

shows the adaption that accounts for the load from the imper-

vious area treated by the SCM and the load from the area

not treated by the SCM where the treated area is calculated

based on Equation 8, the not treated area is calculated based

on Equation 9, and the percentage impervious area for the

not treated area is adjusted based on Equation 10:

𝐿 = 0.1 × 𝑃 × Pr × 𝐶 ×[𝐴NT

(0.05 + 0.009 × 𝐼NT

)]

+𝐴T × [(0.05 + 0.009 × 100%)𝑅%] (7)

𝐴T = 𝑇% × 𝐴 × 𝐼 (8)

𝐴NT = 𝐴 − 𝐴T (9)

𝐼NT =𝐴 × 𝐼 − 𝐴T × 100%

𝐴NT(10)

538 HODGSON ET AL.

where AT represents the area impervious area that is treated

by the SCM, T% represents the percentage of impervious area

treated by the SCM, ANT represents the remaining area not

treated by the SCM, INT represents the percentage impervious

of the nontreated area, and the R% is the assumed percentage

removal from a SCM based on values from literature (CWP,

2007).

For this analysis, the baseline condition assumes that no

SCMs are present. Although there are many SCMs that can

be implemented, this evaluation focused on BRBs and EDBs,

which are two of the most common. The achievable percent-

age TN and TP removal for BRBs was assumed to be 46

and 5%, respectively, and for EDB, the TN and TP percent-

age removal was assumed to be 24 and 20%, respectively

(CWP, 2007). The percentage of impervious area implement-

ing SCMs (T%) was evaluated from 0–100% adoption at 10%

adoption intervals.

2.6 Cost analysis

For each urban water management solution, annualized unit

costs were developed to assess cost effectiveness of a scenario

(Supplemental Table S5). Cost effectiveness was defined as

the solution that yielded the lowest nutrient removal unit cost

(most nutrient removal relative to cost). The annual unit cost

analysis approach was adapted based on the USEPA Guide-

lines for Preparing Economic Analysis (USEPA, 2014). A

present value cost (PV) was calculated accounting for fixed

cost (FC), annual operating and maintenance cost (MC),

opportunity cost (OC), irregular cost (RC), and reduced cost

(S) over the life of the project discounted to account for the

time value of money (Equation 11):

PV = FC +𝑛∑

𝑡=1

1(1+𝑟)𝑡

[MC𝑡 + OC𝑡 + RC𝑡 − 𝑆𝑡

](11)

where PV is present value cost, FC is fixed cost incurred with

initial practice adoption, t is the annual period, n is the final

period (assumed 20 yr), r is the interest rate (assumed 4.3%),

MC is the yearly maintenance costs, OC is the opportunity

costs, RC is the irregular costs, and S is the reduced costs. The

PV represents the total cost to install and maintain the vari-

ous practices for the practice life, which was conservatively

assumed to be 20 yr for all practices.

The PVs were primarily developed referencing literature

cost data (CDM, 2007; Huang & Shang, 2006; Hydroman-

tis, 2014; Ishii & Boyer, 2015; Reynolds & Richards, 1995;

RSMeans, 2018; USEPA, 2008, 2010, 2015; WSTB, 2016).

When cost information from literature was limited, engineer-

ing cost estimates were developed for practice adoption. The

development of the unit costs is documented in the supple-

mental material. The PV costs were developed as a unit cost

(per gallons per day [gpd], per capita, or per acre), so the PV

estimate could be applied at different levels of adoption and

treatment scales. All costs were adjusted to 2018 dollars based

on the Consumer Price Index (CPI) by multiplying by the CPI

ratio as indicated in Equation 12:

CPI ratio =CPI2018CPI𝑡

(12)

When necessary, future costs were adjusted to account for

inflation at an assumed rate of 2.5%.

2.7 Demonstration area

The developed systems approach was demonstrated using Fort

Collins, CO, as the study area. Fort Collins is an urban area

with a population of 143,986 (2010 US Census) and a mix of

residential, commercial, and open space areas, and it is served

by two WWTFs (Table 1). Per capita water use was estimated

based on Hodgson et al. (2018). The effluent nutrient concen-

tration and flow from the WWTFs and the upstream nutrient

load were obtained from 2014 effluent water quality reported

for regulatory compliance and obtained from the USEPA

Water Quality Portal. Additional influent WWTF water qual-

ity data were obtained from the wastewater utility. The

T A B L E 1 Model inputs and assumptions

Parameter Value UnitsWater management practices

Population 143,986 people

Graywater generation 94.6 L capita−1 d−1

WWTF

Average flow (total) 0.54 m3 s−1

Permitted flow (total) 1.26 m3 s−1

Influent TN (avg.) 32.0 mg L−1

Influent TP (avg.) 4.0 mg L−1

Influent COD/TN 14.0 ratio

Influent COD/TP 112.0 ratio

Effluent TN (avg.) 11.9 mg L−1

Effluent TP (avg.) 2.0 mg L−1

Current LCC treatment cost 0.79 US$ L−1 d−1

SCMs

Avg. annual rainfall 40.8 cm yr−1

Open space 2891 ha

Residential 8825 ha

Commercial 2374 ha

Industrial 620 ha

Institutional 308 ha

Highway 122 ha

Note. WWTF, wastewater treatment facility; TN, total N; TP, total P; COD, chem-

ical oxygen demand; LCC, life cycle cost; SCM, stormwater control measure.

HODGSON ET AL. 539

T A B L E 2 Target nutrient loading for total N and total P

kg yr−1

Tier Streamflow condition Total N load Total P load1 30% improvement from existing nutrient load 209,991 30,470

2 2009 average flow, 2.50 m3 s−1 184,158 15,576

3 Average of 10-yr annual median flows, 1.88 m3 s−1 119,230 10,084

4 2009 median flow, 0.31 m3 s−1 45,292 3831

average annual precipitation data were obtained from NOAA

as an annual average precipitation and assumed evenly dis-

tributed throughout the study area. This assumption is accept-

able at smaller scales, but the spatial distribution of precip-

itation will be more significant as the evaluation scale is

increased. Land use boundaries were obtained from the city of

Fort Collins and generalized to open space, residential, com-

mercial, industrial, institutional, and highway.

2.8 Target conditions

Historic water quality data and receiving water body flows

were reviewed for the demonstration area to identify existing

conditions and acceptable stream loading conditions and are

included as part of the supplemental material. The state of

Colorado regulates annual TN and TP loading based on the

annual median of the daily average flows with an allowable

1-in-5-yr median exceedance. Based on the last 10 yr of data

(USGS Gauge no. 06752280, Supplemental Figure S3), this

would be the 2009 annual median flow of 0.31 m3 s−1, which

represents the second driest year in the period. Stream con-

centrations were obtained upstream of the demonstration area,

between the two WWTFs, and downstream of the demonstra-

tion area from data reported to the state of Colorado in 2014,

which is a recent requirement with the adoption of statewide

nutrient regulatory requirements.

2.9 Identifying tradeoffs and pareto optimalstrategies

Multiple and often conflicting objectives were incorporated

in the evaluation of nutrient management strategies, includ-

ing PV, TN load, and TP load. The nondominated sorting

genetic algorithm II (NSGA-II) nondominated sorting algo-

rithm (Deb, Pratap, Agarwal, & Meyarivan, 2002) was used to

identify nondominated solutions from all possible combina-

tions of nutrient control strategies. In this study, a total of 7812

scenarios were simulated. Nondominated solutions comprise

the Pareto optimal front. Solutions that belong to the Pareto

frontier cannot be improved for an objective without degrad-

ing one or more of the other objectives. The analysis was used

to explore tradeoffs among the assessment objectives and to

identify the least cost-effective strategies.

3 RESULTS

Based on the 2009 median streamflow, the downstream load-

ing capacity for TN and TP is 45,292 and 3831 kg yr−1,

respectively (Table 2). The 1-in-5-yr median exceedance

represents a much lower loading capacity than the average

streamflow because of highly variable receiving stream flows.

Due to this large variability, four different target removal

levels were considered, representing four tiers of nutrient

removal required (Table 2, Supplemental Figure S4).

A total of 7812 nutrient strategies were evaluated to

characterize the effluent TN loading, TP loading, and PV

(Figure 2). The nondominated sorting algorithm was per-

formed to identify optimal scenarios considering tradeoffs

in minimizing PV, TN discharge, and TP discharge. Of the

7812 evaluated strategies, a total of 176 optimal nondomi-

nated solutions were identified in the Pareto front (indicated

in color on Figure 2). Of the nondominated solutions, viable

strategies were identified that meet the defined nutrient tar-

gets developed based on the historical flow analysis and base-

line loading conditions (Table 2). Since the evaluation defines

both TN and TP loading conditions, there are limited opti-

mal nutrient removal strategies capable of meeting both of the

defined nutrient targets.

A 30% improvement in the existing loading conditions

requires the least amount of nutrient removal improvement

and therefore results in the largest number of viable strategies

that meet the target load (Figure 2). Based on the 2009 aver-

age flow, there is still a variety of strategies capable of meet-

ing the target TN and TP requirements. However, as the tar-

get load is decreased, there are no viable strategies that meet

the target based on the average 10-yr median flow target or

the 2009 median flow target (Colorado regulatory target). To

meet these targets, background nutrient loading would need to

be addressed in addition to the removal strategies evaluated in

the urban water system.

From the nondominated solutions determined by the Pareto

front, the optimal solutions were highlighted according to PV,

TN unit cost, and TP unit cost for unconstrained, Tier 1, and

540 HODGSON ET AL.

F I G U R E 2 (a) Present value cost (PV) versus the annual total nitrogen (TN) load with target TN load indicated based on 2009 average flow,

average 10-yr median flow, and 2009 median flow, and (b) PV versus the annual total phosphorus (TP) load with target TP load indicated based on

2009 average flow, average 10-yr median flow, and 2009 median flow. The colored points identify nondominated strategies that meet both TN and

TP load requirements corresponding to the color of the stream target line and the Pareto front considering cost, TN, and TP. T1–T4, Tier 1 to Tier 4

Tier 2 targets (Figure 3). This demonstrates tradeoffs between

cost, TN reduction, and TP reduction. For example, strategies

that minimize TN and TP discharge come at a high cost. The

optimal solution from the Pareto front was identified as MLE

with CA + FA and adoption of 15% source separation. This

strategy was also the optimal PV for meeting the Tier 2 target,

whereas MLE + NS with 35% effluent reuse was the optimal

PV for meeting the Tier 1 target.

The optimal nutrient strategies in the urban water system

will be dependent on the defined nutrient target, as well as

characteristics like population, water use, local climate con-

siderations, and land use. Although the optimal Tier 1 and

Tier 2 strategies that minimize PV were highlighted, there are

other options that are viable and effective in balancing trade-

offs among PV, TN, and TP, as identified in the Pareto front

(Figure 2). To highlight effective practices, frequency plots

HODGSON ET AL. 541

F I G U R E 3 Optimal solutions based on Pareto front analysis identifying optimal nondominated solution, Tier 1 (T1) minimized present value

cost (PV) solution, Tier 2 (T2) minimized PV solution, minimized total nitrogen (TN) discharge solution, and minimized total phosphorus (TP)

discharge solution. MLE, modified Ludzack Ettinger; CA, carbon addition; FA, ferric addition; SS, source separation; NS, nitrite shunt; WR,

wastewater effluent reuse; BRB, bioretention basin; EDB, extended detention basin

were developed to quantify the frequency a given nutrient

removal practice was part of an optimal nutrient removal strat-

egy. This was first done for all nondominated solutions, and

then by constraining the optimal solutions to strategies that

meet defined nutrient targets (Figure 4), and grouped based

on PV as low, medium, or high. There are 176 nondominated

strategies that include a variety of combinations of WWTF

improvements, water management practices, and SCMs

(Figure 4a). If the nondominated solutions are constrained to

those that meet the Tier 1 nutrient load target, the number of

viable strategies is reduced to 140 (Figure 4b), and 61 strate-

gies that meet Tier 2 nutrient loading target (Figure 4c). When

constrained, there are no strategies that maintain the existing

wastewater treatment process and the WWTFs would need to

adopt A2O, MLE + NS, MLE + SP, MLE + FA, or MLE +CA + FA. It is worth noting that water management practices

and/or SCMs were frequently necessary in effectively meet-

ing the nutrient targets. As strategies are constrained, there is

also a shift away from low-cost strategies.

4 DISCUSSION

The nondominated strategies included a variety of combina-

tions of WWTF technologies, water management practices,

and SCMs that can be part of effective nutrient removal

scenarios. Although individual strategies with adoption of

a single practice in one sector were considered, all of the

nondominated solutions included a combination of practices

across sectors. Interestingly, implementing technologies like

5SBAR, MLE + AS, MLE + CaRRB, and MLE + PAD was

not part of any nondominated solutions. This indicates that the

cost for implementing these technologies does not result in a

reciprocal benefit to both TN and TP. Of the water manage-

ment practices assessed, wastewater effluent reuse and source

separation were identified in many of the nondominated sce-

narios (Figure 4). Although there may be social and political

barriers for these practices, these practices result in an equal

tradeoff in TN and TP load reduction while minimizing PV.

Similarly, both SCMs were frequently part of nondominated

scenarios, but adopting SCMs alone could not meet the identi-

fied nutrient targets. Of the nondominated strategies, the opti-

mal solutions were identified as the strategy that provided the

overall most efficient minimization of TN load, TP load, and

PV (Figure 3).

For meeting the defined Tier 1 nutrient target, a combi-

nation of WWTF improvements, water management prac-

tices, and/or SCMs was necessary and more cost effective

than implementing only WWTF improvements (Figures 3

and 4b). Considering wastewater treatment technologies, the

542 HODGSON ET AL.

F I G U R E 4 Frequency practice was part of an effective strategy as identified by the Pareto front (a) without loading constraints, (b) that meet

the Tier 1 (T1) loading constraints, and (c) that meet the Tier 2 (T2) loading constraints. Note that practices are organized by wastewater, water, and

stormwater practices from left to right. MLE, modified Ludzack Ettinger; A2O, anaerobic, anoxic, oxic; 5SBAR, five-stage Bardenpho; NS, nitrite

shunt; SP, struvite precipitation; AS, ammonia stripping; CaRRB, centrate and return activated sludge reaeration basin; PAD, post-aerobic digestion;

CA, carbon addition; FA, ferric addition; No WM, no water management practice adoption; SS, source separation; GIR, graywater irrigation reuse;

WR, effluent reuse; No SCMs, no stormwater control measure adoption; EDB, extended detention basin; BRB, bioretention basin

most cost-effective solutions adopted MLE + SP or MLE +NS (Figure 4b). These technologies were combined with some

level of water management practices (source separation or

effluent reuse) and/or implementing SCMs (EDBs or BRBs,

Figure 4b). The results suggest that investing in water man-

agement and stormwater practices can potentially provide a

more cost-effective approach in meeting nutrient targets ver-

sus investing only in WWTF improvements. To facilitate this,

water management practices and SCMs could be considered

for nutrient trading, depending on the local regulatory struc-

ture. As the nutrient load is reduced with the Tier 2 target,

water management practices and/or implementing SCMs are

still part of optimal solutions, but WWTFs would need to also

adopt MLE with CA and/or FA (Figures 3 and 4c).

As mentioned previously, there were no strategies iden-

tified for meeting the Tier 3 or Tier 4 target. In certain

HODGSON ET AL. 543

instances, stringent nutrient requirements may result in tar-

get total maximum daily loads that are not technologically

achievable with wastewater treatment and stormwater treat-

ment (WERF, 2010). To meet these targets, strategies would

need to be implemented for reducing the background nutri-

ent loading in additional to the evaluated urban water system

strategies. The ability to meet low target nutrient loads will

depend on a variety of factors unique to the urban area and the

receiving water body. Looking at the study area, the stream-

flow is highly variable and can experience very low flow con-

ditions, which are heavily influenced by climate conditions,

precipitation, and snow pack (see Supplemental Figure S3).

5 CONCLUSION

The developed urban water system analysis conducted here

provides an innovative framework that identifies Pareto opti-

mal strategies to explore tradeoffs for cross-sector nutrient

load reduction strategies. Although empirical models used

to estimate nutrient load reduction associated with strategies

may require minor modification to account for local consid-

erations, the framework applied here is broadly applicable

across urban water systems.

Among WWTF nutrient removal technologies, inclusion of

advanced biological nutrient removal systems with CA and

supplemental FA will likely be necessary to meet stringent

nutrient requirements. Even with adoption of this technology,

a holistic urban water system approach that includes water

management and stormwater control to reduce nutrient load

will likely be needed.

Of the water management practices, source separation was

most frequently identified as part of effective nutrient strate-

gies. Although source separation was consistently part of the

most effective nutrient removal strategies, there are signif-

icant barriers to adoption in terms of engineering, installa-

tion, maintenance, and public perception (Fewless, Sharvelle,

& Roesner, 2011). Conversely, many utilities already adopt

some level of effluent reuse and should also consider this as

part of a viable nutrient removal scenario.

Similarly, SCMs proved to be an important part of effec-

tive nutrient scenarios. However, given that the cost for SCMs

is primarily a function of area treated, the cost effectiveness

of SCMs will be highly variable depending on the percentage

contribution of stormwater runoff to nutrient pollution, which

will vary regionally based on precipitation. Additionally, cost

effectiveness will also be dependent on existing infrastructure

considerations like curb and gutter, in-place detention infras-

tructure, and combined versus separate stormwater systems,

to name a few.

CONFLICT OF INTERESTNo conflict of interests exists for this research.

ACKNOWLEDGMENTSThis publication was made possible by USEPA Grant

RD835570. Its contents are solely the responsibility of the

grantee and do not necessarily represent the official views of

the USEPA. Further, USEPA does not endorse the purchase

of any commercial products or services mentioned in the pub-

lication.

ORCIDBrock Hodgson https://orcid.org/0000-0003-1719-2697

Mazdak Arabi https://orcid.org/0000-0003-1817-3260

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How to cite this article: Hodgson B, Dell T,

Sharvelle S, Arabi M. Assessing cost-effective

nutrient removal solutions in the urban water system.

J. Environ. Qual. 2020;49:534–544.

https://doi.org/10.1002/jeq2.20031