Resources, Conservation and Recycling 98 (2015) 76–84
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Resources, Conservation and Recycling
jo u r n al homep age: www.elsev ier .com/ locate / resconrec
irtual water management and the water–energy nexus: A case studyf three Mid-Atlantic states
oung-Doo Wanga,∗, Jae Seung Leeb, Lawrence Agbemabiesea, Kenneth Zamea,ung-Goo Kangc
Center for Energy and Environmental Policy, University of Delaware, 278 Graham Hall, Newark Delaware 19716, USAGreen School, Korea University, 145 Anam-ro, Sungbuk-gu, Soul 136-713, South KoreaMinistry of Environment, Government Complex-Sejong, 11, Doum6-Ro, Sejong-si 339-012, South Korea
r t i c l e i n f o
rticle history:eceived 18 August 2014eceived in revised form 16 January 2015ccepted 17 January 2015
eywords:ater–energy nexusater for energy
irtual water importsater inequity
lectricity tradingustainable energy scenario
a b s t r a c t
Virtual water imports arise when electricity and input fuel imports for electricity generation are expressedin terms of the quantity of water consumption not fully accounted for through pricing of imported elec-tricity and input fuels. Such incomplete accounting means that electricity and input fuel exporters andother stakeholders suffer an unequal share of the net costs, including negative local ecological impacts.This paper utilizes the term “water inequity” to capture this phenomenon. It does not argue against elec-tricity and/or input fuel trading, but focuses on the need to reduce regional water inequity by loweringvirtual water imports through sustainable electricity policies. Under unchecked business-as-usual (BAU)trends, water inequity attributable to virtual water imports by the three case study states (Delaware,Maryland and New Jersey) could reach 420.2 million m3 by 2025, which would be 39% higher than totalin-state water consumption for electricity generation. These states are already deploying sustainableenergy-focused policy tools, including Energy Efficiency Resource Standards (EERS) and Renewable Port-folio Standards (RPS). This research demonstrates, by means of sustainable energy scenario analysis, that
EERS combined with RPS can reduce water inequity by an average of 35% in the states under review,ranging from 34% (Maryland) and 35% (Delaware) to 37% (New Jersey). This will enhance sustainabilityin terms of energy, environment, economy and equity (E4) for both importing and exporting states. Thispaper concludes by offering policy options to maximize the synergistic benefits of virtual water inequityreduction.
Societies across the globe are experiencing increased water andnergy vulnerabilities at local, regional and national scales. Somergue that the world will face two crises in the 21st century: aater crisis and an energy crisis (Brown, 1998; Flavin, 1999; Feffer,
008). A crisis of water scarcity, reflected in falling water tablesttributable to over-consumption, is being amplified by threats toater quality as contamination increases. Water security has been
dentified by some as the single most important factor regardinghe future sustainability of our planet (Biggs et al., 2013). The cur-ent conventional energy system, dominated by fossil fuels and
nuclear power, is also increasingly vulnerable, especially due tomajor climate trends such as decreasing water availability, increas-ing intensity and frequency of storm and flooding, and sea levelrise (DOE, 2013; Forster and Lilliestam, 2010). To mitigate climatechange, proper alternative energy technologies that significantlylower water consumption and lower carbon emissions need to bedeployed (Pittock, 2011). If society does not improve its manage-ment of energy and water resources in a timely manner, we willdamage the ability of future generations to meet their needs.
Given this context, there is a need for greater understandingof energy–water linkages in order to develop more effective poli-cies to address cross-vulnerabilities (Hussey and Pittock, 2012).Approaches to resolve this issue must recognize, embrace andexploit the synergies that exist between these two sectors. The
interdependence between water and energy can be collectivelyclassified as the water–energy nexus: producing and distribut-ing energy requires water, and supplying and consuming water
Virtual water is a measure of how much water is embedded inthe production and distribution of a good or service (Hoekstra and
Y.-D. Wang et al. / Resources, Cons
equires energy (Ackerman and Fisher, 2013; Siddiqi and Anadon,011; Schramm, 2013). Scott et al. (2011) conclude that “despite theperational interdependencies between water and energy, therere few examples of tandem management of both resources” (p.622).
Following the U.S. Energy Policy Act of 2005, the U.S. Depart-ent of Energy’s (DOE) national laboratories and the Electric Power
esearch Institute (EPRI) initiated a multi-year water–energy pro-ram that included R&D and outreach which was expected toost $30 million annually through 2009. Prior to this initiative,here was hardly any U.S. government support for water–energyexus issues on the national agenda. More recently, the Energynd Water Research Integration Act of 2009 (introduced as Sen-te bill 531) aimed to ensure consideration of water intensity inhe Department of Energy’s energy research, development andemonstration programs to help guarantee efficient, reliable andustainable delivery of energy and clean water resources. Althoughhis bill was not passed into law it represented an “importantational step towards energy–water policy coupling” (Scott et al.,011: p. 6623).
An important driver of the water–energy nexus is the realiza-ion that water withdrawal by electric power plants has more thanuadrupled in a little over 50 years: 40 billion gallons per day in950 to 201 billion gallons per day in 2005 (Kenny et al., 2009). The
argest withdrawal of water in the United States in 2005 was for usey thermoelectric power plants (49%), followed by irrigation (31%)nd public and other water users (20%) (Kenny et al., 2009). Mosthermoelectric power plants are fueled by coal, nuclear energy andatural gas, with coal power plants accounting for about 37% of theotal electricity produced in the United States in 2012, natural gas0% and nuclear energy 19% (EIA, 2012a). According to EIA (2011),hermoelectric generation will account for 85% of total electricityeneration by 2035.
The upsurge of interest in water withdrawal is paralleled byncreasing attention to the phenomenon of “embedded” or “virtual
ater” transfers that occur in the process of electricity and energyrading between states or regions. The notion of virtual water –ater embedded in energy in our case (ACEEE, 2011) – has been
aptured extensively in several studies (Verma et al., 2009; Galan-el-Castillo and Velazquez, 2010; Velázquez et al., 2010; Novotny,013). Some scholars that focus on agriculture highlight the ben-fits of treating virtual water as a tradable commodity that cane exchanged between states and/or regions, thereby enhancingverall economic efficiency in water resource use (Qadir et al.,003; Chapagain and Hoekstra, 2004; Wichelns, 2004; Dabrowski,014). This paper examines another dimension of virtual water byighlighting the equity implications (referred to as “water equity”)esulting from inter-state or inter-regional electricity and fuel trad-ng that have not previously been addressed.
In the sections which follow we first address the water–energyexus concept, focusing on “water for energy” “virtual water” andwater inequity.” After this we introduce the three case states cov-red by this study, namely, Delaware, New Jersey and Maryland.his is followed by an evaluation of water inequity in the PJMegions and beyond in the reference year of 2010 by three casetates. Next, we perform a scenario analysis with a target year of025 and evaluate the potential for reduction in water inequityhat might be realized in the context of an alternative sustainablenergy scenario (SES); one in which Renewable Portfolio StandardRPS) and Energy Efficiency Resources Standard (EERS) are assumedo be fully implemented by 2025. This reduction is compared withhe 2025 Business-as-Usual Scenario (BAU-2025) and the refer-nce year of 2010. The same approach is applied to reduction ofn-state water consumption associated with electricity generation
n 2025. In the final section we offer policy suggestions and conclu-ions.
n and Recycling 98 (2015) 76–84 77
2. Major concepts
2.1. Water–energy nexus: focusing on water for energy
At the core of the water–energy nexus is the demand of water forenergy and demand of energy for water (Gleick, 1994; Rio Carrilloand Frei, 2009; Siddiqi and Anadon, 2011). Energy for water is animportant topic (Sudeep et al., 2014), but our focus is on waterrequired for energy. The extraction and preparation of input fuelsfor electricity generation consumes significant quantities of waterand impacts water quality. According to the U.S. DOE (2006), coalmining is estimated to consume approximately 1–6 gallons permillion Btu (MMBtu), while also impacting local water quality.The typical petroleum refinery consumes 7–18 gallons per MMBtu(DOE, 2006). The production of oil from tar sands and naturalgas from shale gas also consumes a significant amount of water.Oil extracted from shale requires 15–28 gallons per million Btu(MMBtu), and oil sands require 20–50 gallons per MMBtu (DOE,2006). The U.S. EIA noted that natural gas will account for 60% ofelectricity generation capacity additions between 2011 and 2035,and shale gas is anticipated to drive this growth (EIA, 2012b).
The use of open-loop cooling systems by power plants oftendraws aquatic wildlife into the system, and aquatic environmentsare further endangered when warmer water is returned into thesurrounding ecosystem (Gagnon-Turcotte and Pebblesa, 2009).Closed-loop cooling systems withdraw less water and endangeraquatic wildlife to a lesser degree compared to open-loop cool-ing systems, but the systems consume more water since water isnot directly returned from where it came (Macknick et al., 2011).Dry cooling systems withdraw and consume minimal water, butthey have a high capital cost and have less overall power plant effi-ciency compared to closed-loop cooling systems (Gagnon-Turcotteand Pebblesa, 2009).
Given the amount of water required for thermolectric use, thispaper concurs with Sovacool and Sovacool (2009), who noted theprecarious nature of electricity generation given the likelihood offuture droughts and water shortages, especially during the summermonths. For example, the U.S. Geological Survey (USGS) predictedthat almost a quarter of the United States will encounter severedroughts by 2040, with states in the West expected to suffer themost (Smith et al., 2014).
In contrast to their conventional counterparts, renewableenergy technologies such as solar photovoltaic systems and windturbines require no cooling water and only minimal water forwashing the panels and cleaning blades, respectively. Hydroelec-tricity generation also does not require water for cooling, but highvolumes of water are consumed via evaporation losses from thesurface of reservoirs and dams. Additionally, temperatures arealtered, and ecosystems are radically altered up and downstream(Torcellini et al., 2003). Water consumption by other renewabletechnologies varies substantially. For example, concentrated solarpower (CSP) plants require more cooling water per unit of elec-tricity generated compared to fossil and nuclear plants since CSPplants operate at lower temperatures with less steam efficiency(Carter and Campbell, 2009). Geothermal power plants make useof convective hydrothermal resources inside hot rock beds. How-ever, external water supplies are usually required given that manygeothermal resources do not naturally contain enough water (Clarket al., 2010).
2.2. Virtual water trading and water inequity
Hung, 2002; Galan-del-Castillo and Velazquez, 2010; Velázquezet al., 2010). The concept is well established in agricultural
fuels. Even though there may be variability in the amount of waterused for production of a given input fuel in different places, this
8 Y.-D. Wang et al. / Resources, Cons
iterature. From a production-site perspective, the virtual waterontent of a crop is the volume of fresh water used to producehe crop measured at the place of its origin. However, from aonsumptive-site perspective, it is the volume of fresh water thatould have been required to produce the crop at the place of its
onsumption (Chapagain and Hoekstra, 2004; Dabrowski, 2014).y contrast, the concept of water footprint refers to the total vol-me of water consumed by an individual or group. At the level ofuman settlements (villages, towns, megalopolises) and nations,he water footprint equals the aggregate quantity of domestic wateresources consumed by all inhabitants, plus the balance of virtualater they import and export through trade in various goods and
ervices (Srinivas, 2014).As applied in this study, virtual water refers to the total vol-
me of water utilized at all points along the energy value chain –rom fuel extraction through processing and conversion into vari-us energy forms and associated services. Given our focus on wateror energy, this conceptual tool provides a means to capture impor-ant – but largely ignored – virtual water flows associated withnergy trading relations between our case study states. As Allan1994, 2001) has noted, virtual water flows tend to be economi-ally invisible and politically silent. In our view, ecological impactsf virtual water also need urgent attention. Virtual water think-ng is therefore a critically important conceptual tool by whicho develop a more holistic understanding of economic, politicalnd environmental issues and policy options at the water–energyexus.
The notion of virtual water is important for water-shortegions or countries for which there are obvious benefits toe gained by importing water-intensive products, thereby max-
mizing the value of their domestic water resources (Qadirt al., 2003). For example, electricity or input fuels tradingay improve overall water use efficiencies or lower water
ootprints much as it has for agricultural and manufactured prod-cts when water-intensive crops or products are imported fromater-rich to water-poor regions (Hoekstra et al., 2009). Simulta-eously, however, the invisibility of virtual water in the tradingelationship means that non-trivial socio-economic and environ-ental impacts on the exporting country, region or state are
ot accounted for (Dabrowski, 2014). Under such conditions, fundamentally inequitable relationship may develop – andeepen – between water-intensive energy exporting and importingegions.
This paper focuses on the regional inequity arising from the rel-tive invisibility of virtual water in the terms of trade betweennergy importers and exporters. We argue that the direct impor-ation of electricity, and of input fuels for electricity generation,llows importing states to incur large and growing amounts of “vir-ual water indebtedness” to exporting states or regions. “Virtualater indebtedness” in energy trading is a measure of the socio-
conomic, political and environmental costs attributable to the netolume of virtual water consumed by energy importers. It is beyondhe scope of this paper to estimate such costs. However, givenhe substantial body of evidence indicating the presence of vir-ual water in energy trading, the paper treats virtual water importss a proxy measure for inequity in water consumption betweennergy importing and exporting states or regions. In the rest ofhis paper, we refer to this (largely invisible) condition as “waternequity.”
The notions of virtual water trading, water indebtedness andater inequity have the potential to significantly redefine the scope
nd depth of water–energy sustainability discourse. As a mod-st contribution to this discourse, this paper demonstrates howrogress towards sustainability goals such as equity may be real-
zed through better water stewardship while nurturing actions forverting or reducing unsustainable energy use.
n and Recycling 98 (2015) 76–84
3. Case study states
The three case study states (Delaware, Maryland and NewJersey) are part of the Mid-Atlantic region of the United States.The electric transmission system serving these three states is thePJM Interconnection LLC (PJM). PJM is a regional transmissionorganization (RTO) that coordinates the movement of wholesaleelectricity in all or parts of a number of states in the Mid-Atlanticregion (see Fig. 1 for territories served by PJM). PJM is part ofthe Eastern Interconnection: a major electric grid in North Amer-ica which reaches from Central Canada eastward to the Atlanticcoast (excluding Quebec), south of Florida and back west to thefoot of the Rockies (excluding most of Texas). PJM therefore trans-mits electricity from utilities within the territory it serves andbeyond its territory. As indicated in Fig. 1, most of the stateswithin the PJM region including the case study states are netimporters of electricity, indicating that they are net virtual waterdebtors.
Primary fuels for power generation such as coal and natural gaswithin PJM region are sourced within the region and beyond. In2013, about 779 million tons of coal were delivered to power plantswithin United States, with the majority of deliveries coming fromthe Powder River Basin region (which covers part of Wyoming andMontana) and the Illinois Basin (which includes portions of Indiana,Illinois and Kentucky). Of about 58.7 million tons of coal deliveredfrom coal mines in Kentucky in 2013, a little over 30% were to powerplants in the PJM region (SNL Financial, 2014). As shown in Fig. 1,electric power plants in Delaware and New Jersey rely entirely onimported coal. Delaware’s coal imports were mainly from Penn-sylvania and Kentucky in 2013. Coal imports by New Jersey in thesame year were mainly from West Virginia, Pennsylvania, Ohio andVirginia. For Maryland, in addition to coal produced within thestate, coal imports were from West Virginia, Pennsylvania, Ohio,Kentucky and Illinois.
4. Methods
4.1. Case studies and analytical method
Virtual water importation can be reduced by: (1) loweringimports of input fuels for electricity generation and (2) reducingdirect imports of electricity. The reduction of water inequity canbe done through less water-intensive electricity generation such asrenewable applications in power generation and more efficient useof electricity. Though water inequity can also be reduced throughutilization of less water-consuming power technologies by the elec-tricity industry, this is not considered in the analytical scope of thispaper.
The analytical approach used to estimate virtual water inequityin PJM and beyond PJM in the three case study states entails sum-ming up the consumptive water use for production of input fuels(coal, oil, natural gas and uranium) and the consumptive waterused in the thermoelectric cooling process of electricity genera-tion. Though the same analytical approach is used in estimatingconsumptive water use due to electricity generated in-state, theestimated water consumption is not considered as contributing tovirtual water inequity vis-à-vis other states.
Water consumption embedded in imported primary input fuelsis estimated on the basis of water consumption factors reportedby the World Energy Council (2010). These factors include thewater required for mining, extraction, refining of primary input
paper uses a single water factor as shown in Table 1 due to dataconstraints.
Y.-D. Wang et al. / Resources, Conservation and Recycling 98 (2015) 76–84 79
Fig. 1. PJM Interconnection territory showing net electricity exporting or importing stMaryland and New Jersey) in 2013.
Source: Modified from Thomas (2014).
Table 1Water consumption factors for input fuel production (World Energy Council, 2010).
Input fuel Quantity Water factor (m3/GJ)a
Coal 1 short ton 0.164Oil (petroleum) 1 barrel 1.058Natural gas 1 Mcf 0.109
bpieio(2ae
Uranium 1 MMBtu 0.086
a Water factor for each input fuel is the average of different methods of production.
Virtual water consumption for imported electricity is estimatedoth for water required for power plant cooling and input fuelroduction. Water consumption associated with electricity import
s considered as occurring at each of the following stages in thelectricity value chain: (1) water for mining, extraction and refin-ng, (2) water for production of fuels required for transportationf coal and other fossils, (3) water for electricity generation and
4) water for electricity loss due to transmission (Perrone et al.,010). Due to data constraints, this paper only considers the firstnd third stages: water for mining and water for electricity gen-ration. Water consumption factors for electricity generation are
ates in 2012 and sources of coal importation to the three case states (Delaware,
based on Gleick (1994), along with Hightower (2010) and Macknicket al. (2011). For similar reasons, the analysis does not consider theeffects of cooling technologies (on whether it is based on once-through cooling or a cooling tower) in detail. The average values ofwater consumption factors for each input fuel source were used inthe calculation as shown in the last column of Table 2. In addition topower plant cooling, the water required for the mining, extractionand refinement of input fuels consumed in generating electricity isadded.
4.2. Scenario analysis
Using 2010 as a base year and 2025 as a target year, the fol-lowing scenarios are used in a water inequity analysis for the casestudies: (1) 2025 Business-as-Usual Scenario (BAU-2025); and (2)
An alternative sustainable energy scenario (SES-2025) in whichboth Energy Efficiency Resource Standards (EERS) and RenewablePortfolio Standards (RPS) are applied.
The major assumptions for the BAU-2025 Scenario include:
80 Y.-D. Wang et al. / Resources, Conservation and Recycling 98 (2015) 76–84
Table 2Water consumption factors for electricity generation (Gleick, 1994; Hightower, 2010; Macknick et al., 2011).
Power plant Gleick (1994) Hightower (2010)a Macknick et al. (2011) a Values used
a Unit conversion from gallon per MWh to m3 per MWh is made for Hightower an average of various cooling technologies.
electricity consumption increases at a rate of 1% every year from2010. This is based on PJM’s predicted “Load Growth Rate” of 1.6%between 2010 and 2025 for the Mid-Atlantic region (PJM 2011)which is reduced by an assumed 0.6% of autonomous energy effi-ciency improvement (AEEI) applied to the expected load growthrate;the share of renewables in the production of electricity increasesat an annual rate of 0.4%;for electricity imports from PJM, allocation of fuel sources in2025 is based on the generation mix in PJM in 2010 adjusted byautonomous renewable energy applications;input-fuel imports in 2025 are the similar proportion as those in2010 except for natural gas from shale through hydraulic fractur-ing; andnatural gas required for electricity generation from shale gas isexpected to be 20%.
Major assumptions for the SES-2025 Scenario include:
targets of EERS (20%) and RPS (20–25%) are successfully achievedby 2025;electricity generation mix is adjusted by replacing portions ofconventional electricity with renewable electricity based onPJM’s forecasted generation mix;renewable energy applications for each case state are based onrenewable sources eligible under its RPS, along with the specificmark-up (i.e., 3.5% solar carve-out in DE);for the RPS Scenario, water intensive electricity generationoptions are reduced while the use of natural gas increases, mainlydue to the increased production of shale gas projected by EIA.According to EIA (2012a), shale gas is expected to move from a23% share of U.S. natural gas production in 2010 to a 49% shareby 2035;natural gas required for electricity generation from shale gas isexpected to be 30%; andfor the SES, the effect of EERS is first identified and then RPS isapplied, not the sum of the individual effects of both EERS andRPS to avoid overestimation of their impacts.
. Results and discussion
.1. Virtual water imports in the reference year of 2010
Overall virtual water imports are the sum of the embeddedater from importing electricity directly and input fuels imports
or electricity generation. To compare the magnitude of virtual
acknick et al. For Hightower and Macknick et al., water consumption for cooling is
water imports among the case studies, their in-state water use forelectricity generation is also estimated.
5.1.1. Water inequity from input fuel imports: 2010Most of the electricity generated in Delaware comes from fossil
fuels such as natural gas (50.9%) and coal (45.6%). In the case ofMaryland, coal is also the dominant input fuel (54.3%), followedby nuclear power (32.1%). In New Jersey, a significant amount ofelectricity is generated by nuclear power plants (49.9%) and naturalgas (37.9%).
These states imported most of their coal for electricity gener-ation from other states within the PJM region (92.3%), while theyimported other input fuels such as natural gas, petroleum and ura-nium from beyond the PJM region. In the case of Delaware andMaryland, the virtual water imports from the PJM for input fuelsare higher than those from states beyond PJM. By contrast, virtualwater imports by New Jersey and the associated water inequity suf-fered beyond PJM are much higher than those in PJM due to its highreliance on nuclear energy and natural gas.
5.1.2. Water inequity from electricity imports: 2010Net interstate electricity trade for the PJM states in 2010 shows
that the three PJM case states were all net importers of electricity.Delaware imported 6.9 TWh, which is less than a third of the quanti-ties imported by Maryland (21.4 TWh) and New Jersey (27.4 TWh).Though other PJM states such as Illinois, Indiana, Michigan, Penn-sylvania and West Virginia were net exporters, the overall PJMregion was a net importer of electricity (28.0 TWh) which is 2.1%of total retail sales (EIA, 2012b). The EIA estimates net interstateelectricity trade as total electricity supply less total electric indus-try retail sales, direct electricity use, total international electricitytrade (if it applies) as well as less estimated losses. This is illustratedby the equation: Net Interstate Trade = Total Supply − (Total Elec-tric Industry Retail Sales + Direct Use + Total International Exports(if applies) + Estimated Losses).
PJM power generation consists of diverse fuels with fossil fuelsbeing the largest of total fuels (62%). The dominant fuel for the gen-eration of electricity in PJM is coal (49%), followed by nuclear energy(34%) and natural gas (13%). Imported electricity from within PJMfor each case state is assumed to be produced in PJM according toits fuel generation mix.
Water consumption is estimated for power plant cooling fromthe profiles of electricity importation from PJM. In addition topower plant cooling, the water required for the mining, extrac-
tion and refining of input fuels consumed in generating electricityin PJM is added. Water inequity in PJM arising from import-ing electricity is much bigger than that from beyond PJM. SinceMaryland imports more electricity from PJM, its contribution to
Y.-D. Wang et al. / Resources, Conservation and Recycling 98 (2015) 76–84 81
Table 3Estimated total water inequity in PJM and beyond PJM by three case states, 2025: BAU (unit: million m3).
Indicator: water inequity Delaware Maryland New Jersey
PJM Beyond PJM Beyond PJM Beyond
rs
52
ifrabsb
5
vvtiamttv
5s
aeOfaolJbP
tPciPPit
5s
eim
Input fuel imports for electricity generation 4.5 3.4Electricity imported from PJM 23.9 6.8Total water inequity 28.4 10.2
egional water inequity in PJM is the largest among the casetates.
.1.3. Total virtual water Imports from PJM and Beyond PJM:010
Water inequity from importing electricity directly and fuelmports is estimated for PJM and beyond PJM. Virtual water importsrom PJM in Delaware and Maryland is 24.2 and 122.8 million m3,espectively, almost 3 times greater than that of beyond PJM (9.2nd 47.2 million m3), whereas New Jersey’s water inequity fromeyond PJM is 16% higher compared to that of PJM because thetate imports a significant amount of uranium and natural gas fromeyond PJM.
.1.4. Total in-state water consumption: 2010In-state water consumption for electricity generation cooling vs.
irtual water imported varied among states in 2010. In Delaware,irtual water imports from both PJM and beyond PJM was morehan 3 times greater than the water consumed for in-state electric-ty generation (33.3 vs. 10.6 million m3). While Maryland registeredlmost 2 times, New Jersey was the opposite as it used 1.1 timesore water in-state for electricity generation cooling, mainly due
o its reliance on nuclear energy. For all the case states combined,otal in-state water consumption is about 30% less than their totalirtual water imports (259.4 vs. 363.8 million m3).
.2. Virtual water imports in the target year of 2025: BAUcenario
Under the BAU 2025 Scenario, total electricity consumptionmong the case states, could reach 198.2 TWh in 2025, with net gen-ration at 133.4 TWh and import from PJM amounting to 64.7 TWh.ur estimates of virtual water imports linked to input fuel imports
or electricity generation in 2025 are based on the generation mixnd the proportion of fuel imports, along with the predicted volumef electricity generation in 2025. As in 2010, Delaware and Mary-and have higher virtual water imports from PJM, whereas Newersey has significantly higher imports (more than 5 times) fromeyond PJM. Combing all three states, virtual water imports fromJM is more than 3 times greater than that to states beyond PJM.
The estimated total water inequity to PJM and beyond PJM ishe sum of virtual water imports from both input fuel imports byJM and electricity generation within PJM which is exported to thease states. As shown in Table 3, for Delaware and Maryland, waternequity to PJM is more than 2 times greater than that of beyondJM, while in the case of New Jersey, water inequity created beyondJM is greater than that within PJM (88.6 vs. 97.5 million m3) due tomporting significant amounts of uranium and natural gas beyondhe PJM.
.3. Virtual water management: alternative sustainable energycenarios
In contrast to the BAU Scenario, an alternative sustainablenergy scenario (SES) is built as a means of estimating virtual waternequity reduction. SES consists of demand-side options that pro-
ote energy efficiency and conservation and supply-side options
45.7 28.3 14.7 76.594.7 26.8 73.9 20.9
140.4 55.1 88.6 97.5
that promote renewable energy applications in the electricitysector.
Improvements in efficiency and conservation in the end usesector significantly reduce electricity consumption, resulting inreduced virtual water import in electricity importing states. Thoughenergy use in the U.S increased by 28% (from 75.6 quads to about97 quads from 1973 to 2013), energy intensity dropped by morethan half and could be further reduced in the near future by 30%(Bossong, 2013) as substantial technical, economic and achievableenergy efficiency potential remains (Tietenberg, 2009). Accordingto Laitner et al. (2012), in 2010 the U.S. economy consumed a totalof 98 quads, but it would require a total of only 70 quads (42%) in2050.
By mid-2013, renewables accounted for 14% of U.S. totalelectricity generation, with almost half coming from non-hydrorenewables. Recent growth rates and price drops suggest thatthe use of renewables could greatly accelerate in the near term.Between 2003 and 2012, for example, energy produced from windincreased by a factor of twelve, biofuels output grew more thanfive times, and solar generation quadrupled (Bossong, 2013). Dueto the links between energy and water, and the fact that electricityconsumption constitutes a significant portion of consumers’ waterfootprint, solutions to energy problems inadvertently create bene-fits in terms of water availability and quality.
Twenty-five states, which together account for 61% of electric-ity sales in the United States, have established Energy EfficiencyResource Standards (EERS) (ACEEE, 2013). In addition, RenewablePortfolio Standards (RPS) has been adopted by 30 states and the Dis-trict of Columbia (Warren, 2013). The three PJM case states are atthe forefront of clean energy initiatives with commitments towardsenergy efficiency and renewable energy programs:
• New Jersey set its energy savings goal at 20% by 2020 in its EnergyMaster Plan of 2008. The state’s Board of Public Utilities, however,has yet to achieve a binding EERS. Even though the renewableenergy goal of 30% was targeted in its Energy Master Plan, NewJersey’s RPS target is 22.5%;
• The State of Delaware’s RPS target is for 25% renewable energy by2025. Delaware’s EERS of 15% by 2015 was created in 2009. Withthe contribution of its Sustainable Energy Utility (SEU) program, itis expected that energy efficiency could easily reach 20% by 2025.The State’s SEU model is a third party administered not-for-profitfor delivering energy efficiency and customer-sited renewableenergy to end users. With a green financing framework in place,the State’s SEU is poised to expanding its energy efficiency market(Byrne and Trenton, 2010); and
• Maryland has set up an RPS target at 20% by 2022, and anenergy efficiency target of 15% by 2015. However, through strongefforts by the Maryland Energy Administration (MEA), this paperprojects that energy efficiency improvement is expected to reach20% in 2025.
5.3.1. Reduction in virtual water inequity: BAU-2025 vs.
SES-2025
Since most of the input fuels used for electricity generation,except for coal and shale gas, are imported from beyond PJM, virtualwater imports from PJM are much smaller than that of beyond PJM
82 Y.-D. Wang et al. / Resources, Conservation and Recycling 98 (2015) 76–84
Fig. 2. Water inequity in case study states compared under various scenarios (a) and percentage reduction in volume of water inequity from other scenarios over BAUscenario (b).
Fs
(tf3e
sginbi
5S
P1tPtvitwr
ig. 3. Water inequity in PJM and beyond PJM: comparing 2025 sustainable energycenario (SES) against base year 2010 scenario (unit: million m3).
61.6 compared to 111.6 million m3 in the case of BAU-2025). Underhe SES-2025 Scenario, virtual water imports from PJM resultingrom input fuel imports are estimated to fall by 44% (from 61.6 to4.5 million m3) while virtual water imports from beyond PJM arestimated to fall by 37% (from 108.3 to 68.0 million m3).
All of the case states import electricity from PJM which con-umes water for both input fuels production and for electricityeneration cooling. With the exception of coal, PJM imports most ofts input fuels from outside of its territory. Under the SES-2025 Sce-ario, water inequity in PJM from directly imported electricity wille reduced by 32% (192.6 vs. 130.3 million m3) while virtual water
mports from beyond PJM will fall by 34% (54.5 vs. 35.8 million m3).
.3.2. Reduction in total virtual water inequity: BAU-2025 vs.ES-2025
Under the SES-2025 Scenario, total virtual water imports fromJM and beyond PJM are expected to be reduced by 35% (257.5 vs.67.9 million m3) and 36% (162.8 vs. 103.8 million m3), respec-ively, when combining the case states. Virtual water imports fromJM are greatly influenced by direct electricity imports due to elec-ricity generation cooling for thermal power plants in PJM, whileirtual water imports from beyond PJM are significantly affected bynput fuel imports due to water consumption for mining, extrac-
ion and refining from outside of PJM. The total reduction of virtualater imports among the case states under the SES-2025 Scenario
anges from 34% in Maryland to 37% in New Jersey. The overall
Fig. 4. Reduced in-state water consumption for electricity generation for 2025 sce-narios relative to the base year of 2010 and the 2025 BAU (unit: million m3).
reduction of virtual water imports by for all of the case states com-bined is 35% (from 420.2 to 271.7 million m3) as shown in Fig. 2.
Compared to the reference year of 2010, the SES-2025 resultsalso show that water inequity is expected to decrease by an aver-age of 25% in the combined three case states, ranging from 24% inMaryland, 25% in Delaware to 27% in New Jersey. Since these statesare expected to generate much more electricity in 2025 than in2010 (16% more), a 25% reduction (from 364 to 272 million m3)in water inequity through SES is significant achievement. This isshown in Fig. 3.
5.3.3. Reduction in total water consumption for electricitygeneration: 2025
Water inequity reduction through sustainable electricity poli-cies also decreases in-state water consumption for electricitygeneration. All three states combined show a 34% average reduc-tion in water consumption, ranging from 31% in Maryland, 35% inDelaware to 36% in New Jersey. Even compared with 2010, the SES-2025 Scenario shows that all three states are expected to decreasewater consumption needed for electricity generation by 23% in2025 (259.4 vs. 200.0 million m3). This is displayed in Fig. 4.
6. Conclusions
As this paper has assumed that EERS and RPS will be successfullyimplemented by our target year of 2025, we do not offer specificpromotional policies to achieve these targets. However, based on
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he results of our water inequity analyses, this paper offers theollowing policy suggestions:
analysis of energy policy should include water impacts;energy and water utilities need to have well-rounded coordi-nation (including pricing strategies) to promote both water andelectricity savings;policy-makers need to take into consideration the environmen-tal and socio-economic impacts of energy policies from whereenergy is imported;policies need to be adopted at the federal level to fund R&D ofwater and energy systems that maximize the synergistic benefitsof the water–energy nexus;the promotion and development of integrative approaches forrenewable energy and energy efficient technologies should beencouraged, as it has great potential for reducing virtual waterimports, consequently improving regional water equity; andthere should be continuous investment in research and devel-opment of less water-consuming power technologies and powerefficiency improvements.
With population and economic growth likely to continue, thehallenges of ‘energy for water’ and ‘water for energy’ in theecades to come will become increasingly critical for states, regionsnd countries. Currently, the dominant energy infrastructure haserious implications for water withdrawal and consumption. Elec-ric utilities routinely ignore water concerns with proposals forossil fuel and nuclear plants in water-stressed areas and managend assess them only by state administrative boundaries, ratherhan on a regional basis, when addressing their impacts (Sovacoolnd Sovacool, 2009).
As indicated, the premise of this paper is not to argue againstlectricity and/or input fuel trading. Rather, given the occur-ence of trading, the research herein focused on reducing regionalater inequity by lowering virtual water imports through sustain-
ble electricity policies. Water inequity occurs when one localitymports electricity and input fuels to generate electricity fromnother. Water inequity in PJM and beyond PJM caused by electric-ty consumption in three case states (Delaware, Maryland and Newersey) is estimated to be 420.2 million m3 in 2025, which is 39%igher than that of total in-state water consumption for generatinglectricity by these states (303.4 million m3).
As a means of reducing this significant volume of virtual watermports and the associated water inequities, this paper exam-ned the impacts of both demand-side and supply-side policy toolsf EERS and RPS, respectively, on water inequity reduction. Theesearch showed that under the SES-2025 Scenario, EERS combinedith RPS can reduce water inequity by an average of 35% in all three
ase states, ranging from 34% in Maryland and 35% in Delaware to7% in New Jersey. Besides greater conservation of water, the ben-fits of this strategy include a minimization of water pollution intates that export fuels for electricity generation, as well as directlyxport electricity.
In addition to improving regional sustainability and equity,educed virtual water imports via EERS and RPS can also reducen-state water consumption needed for electricity generation. Com-ared to the 303.4 million m3 expected to be used by three casetates in 2025, our alternative SES-2025 Scenario shows a 32% dropn consumption to 206.3 million m3. This further buttresses our
ontention that water inequity reduction can deliver benefits inhe economy, environment, energy and equity (E4) dimensions notnly in states that import fuels and electricity, but in the exportingtates as well (Wang et al., 2012; Wang, 2009).
n and Recycling 98 (2015) 76–84 83
Acknowledgements
This work was supported by the National Research Foundationof Korea Grant funded by the Korean Government (Ministry of Sci-ence, ICT & Future Planning) under the 2013 University-InstituteCooperation Program. We would like to express our special thanksto Profs. Ky Yual Bang and Kyung Nam Kim of the Green School atKorea University. Our thanks also go to Joohee Lee for her assistancein leading the student research team and participating in the dataanalysis. We also appreciate assistance of Chu Chu and Curt Davis onthe data collection and analysis of this research work and Drs. RayScattone, Jerry Kauffman, and William Ritter for their review of ourdraft. Constructive comments from the two anonymous reviewersare very much appreciated.
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