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Global and regional evaluation of energy for water Yaling Liu, Mohamad Hejazi, Page Kyle, Son H. Kim, Evan Davies, Diego G. Miralles, Adriaan J. Teuling, Yujie He, and Dev Niyogi Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b01065 • Publication Date (Web): 02 Aug 2016 Downloaded from http://pubs.acs.org on August 6, 2016
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Environmental Science & Technology
Global and regional evaluation of energy for water
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Yaling Liu1,*, Mohamad Hejazi1, Page Kyle1, Son H. Kim1, Evan Davies2, Diego G.
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Miralles3,4, Adriaan J. Teuling5, Yujie He6, Dev Niyogi7
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University Research Court, College Park, Maryland, 20740, USA
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Canada
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Department of Earth Sciences, VU University, Amsterdam, 1081 HV, The Netherlands
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Laboratory of Hydrology and Water Management, Ghent University, Ghent, B-9000, Belgium
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Hydrology and Quantitative Water Management Group, Wageningen University, Wageningen,
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6708PB, The Netherlands
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Department of Earth System Science, University of California, Irvine, California, 92697, USA
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Department of Agronomy and Department of Earth, Atmospheric and Planetary Sciences,
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Purdue University, West Lafayette, Indiana, 47907, USA
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* Corresponding author. Phone: +1-765-775-6055; Fax: +1-301-314-6719 E-mail address:
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[email protected] Pacific Northwest National Laboratory, Joint Global Change Research Institute, 5825
Department of Civil and Environmental Engineering, University of Alberta, Alberta, T6G 1H9,
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Abstract Despite significant effort to quantify the inter-dependence of the water and energy sectors,
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global requirements of energy for water (E4W) are still poorly understood, which may result in
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biases in projections and consequently in water and energy management and policy. This study
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estimates water-related energy consumption by water source, sector, and process, for 14 global
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regions from 1973 to 2012. Globally, E4W amounted to 10.2 EJ of primary energy consumption
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in 2010, accounting for 1.7-2.7% of total global primary energy consumption, of which 58%
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pertains to surface water, 30% to groundwater, and 12% to non-fresh water, assuming median
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energy intensity levels. The sectoral E4W allocation includes municipal (45%), industrial (30%),
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and agricultural (25%), and main process-level contributions are from source/conveyance (39%),
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water purification (27%), water distribution (12%) and wastewater treatment (18%). While the
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USA was the largest E4W consumer from the 1970’s until the 2000’s, the largest consumers at
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present are the Middle East, India, and China, driven by rapid growth in desalination,
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groundwater-based irrigation, and industrial and municipal water use, respectively. The
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improved understanding of global E4W will enable enhanced consistency of both water and
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energy representations in integrated assessment models.
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Key words: energy for water, water-energy nexus, energy intensity, desalination, wastewater
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1 Introduction The rapid growth of the world population and economy as well as enhancement in living
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standards have driven increasing demands for water and energy in recent decades.1 In addition,
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degradation of water resources and depletion of non-renewable energy make meeting those
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demands increasingly challenging,2-3 while climate change threatens to further aggravate
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regional water scarcity.4-5 Compounding factors include the geospatial mismatch between water
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and energy resources and demands across the globe, and competition among different sectors for
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allocation of these limited resources.6 Because of the inter-dependence between the water and
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energy sectors, the science and policy communities typically refer to a “water-energy nexus”,
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which links the water used in energy production with the energy used to supply, treat, and deliver
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water.7-9 This integrated approach can help to identify mutually beneficial policy responses,
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synergies, or trade-offs, ultimately contributing to goals of meeting future resource demands
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more sustainably.10-11
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While water use by many energy-related processes has been estimated in a number of
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studies, particularly in high energy-consuming countries such as the USA, India, China and
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Brazil,12-15 global estimates of energy consumption for water-related processes are still
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unresolved. In fact, depending on the country, data source and water process, the energy
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consumption for water supply, distribution, and treatment, or “energy for water” (E4W), may be
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classified within any of the following sectors in energy inventories: agricultural, commercial and
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municipal, industrial, or electric power. Within these sectors, the inventories typically do not
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disaggregate the energy used for any water-related activities from other energy use.16-19 As a
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result, it is difficult to extract much information about E4W from present-day energy inventories.
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Recent years have seen progress on the evaluation of energy consumption for specific
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water-related processes (e.g., wastewater treatment, Table S2b) in selected regions (e.g., 17 out
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of 27 water supply related studies are for the USA, and 7 out of the 17 are for California, Table
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S2a). For example, starting from energy inventories, Sanders and Webber20 have estimated total
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energy consumption for water use in the USA for 2010, although their E4W system bounds are
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broader than ours, as discussed below.
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A primary motivation for this study is to construct a historical dataset that can be used for
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calibration of energy and water systems models, particularly integrated assessment models
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(IAMs) that link sub-models of energy, water, agriculture, land, and climate.21 In modeling the
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water and energy systems, failure to include and properly characterize E4W may lead to
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inconsistencies in model outcomes. For instance, by omitting E4W, the current generation of
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IAMs may underestimate the future electricity demands of many arid regions where future water
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demands are likely to be met by energy-intensive methods like seawater desalination, deep
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groundwater pumping, or long-distance transportation. Similarly, the economic viability of such
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options will depend on future regional energy prices, availabilities, policies, and technology
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characteristics, among other factors. Since IAM-derived emissions scenarios are inputs to the
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climate models used for climate change impacts assessments,21 the inclusion of E4W will also
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contribute to the advancement of climate research.
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This study is the first to estimate global E4W by region, process, sector, and water source.
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To this end, we (1) define benchmark energy intensities for each water-related process, and (2)
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assess E4W globally across different water sources, economic sectors, water processes, and
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regions from 1973 to 2012. Specifically, the following water-related processes are considered in
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this study: withdrawal from the source, conveyance, treatment, distribution, and wastewater
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collection, treatment and discharge.22-24 Note that several studies6,20 have also classified energy
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applied to water in the residential, commercial, industrial, and even electric power sector as
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“energy for water.” When included, these processes tend to account for the vast majority of
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estimated E4W. However, as explained in Kyle et al.,25 we exclude processes whose primary
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output is not water from the system boundaries of “energy for water.” Instead, these activities are
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classified as “water and energy for other purposes,” and will be addressed in subsequent research.
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2. Methods and data
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This study follows four steps to estimate global and regional primary energy consumption
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for water. The first step is the construction of a database estimating historical water withdrawals
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by country, based primarily on FAO AQUASTAT,26 which has country-level estimates of water
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withdrawals by the municipal, agricultural, and industrial sectors from 1973 to 2012 (we do not
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include data prior to 1973 here as it is mostly incomplete). AQUASTAT provides detail on the
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types of water withdrawal in each country – fresh surface water, fresh groundwater (hereafter
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called surface water and groundwater, respectively) – as well as the amount of municipal
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wastewater being treated. Processes that use non-fresh water (i.e., brackish water and seawater)
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that are considered in this study include desalination and abstraction of cooling water at coastal
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thermoelectric power plants.
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Because of different energy intensities of water use, industrial water withdrawals are
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disaggregated to electricity generation and manufacturing, as described by Kim et al.27 The same
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study is also used to estimate seawater withdrawals by power plants, which are not included in
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AQUASTAT. The portion of manufacturing sector water withdrawals that are assumed to be
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treated prior to discharge is set equal to the ratio of treated municipal wastewater to municipal
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water withdrawal in AQUASTAT for each country. While AQUASTAT provides estimates of
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the volumes of desalinated water in each region, there is a wide range of energy intensities for
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this process, influenced by the desalination technology types and the salinity of the source water.
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These characteristics are assigned in each region based on a global assessment by the Australian
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National Water Commission.28 Due to differing energy intensities, irrigation water withdrawals
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are disaggregated to surface and groundwater according to several data sources.26, 29-32 Further,
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due to differing primary energy footprints, the irrigation water withdrawals in each country are
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also partitioned into power and gravity irrigation, according to area-based estimates reported in
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FAO.26 All steps in the construction of the water-use database are detailed in Sections S1 and S2
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of the Supporting Information.
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In a second step, energy intensity (EI) values for each water process and source are
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collected from a literature survey, and the range of reported values for each process assessed is
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estimated, with 25th, 50th, and 75th percentiles used to represent the plausible range of energy
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intensity, over time and across regions. Recycled water is assigned the same energy intensities as
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all other water used by the corresponding sectors because of data scarcity; the net effects of this
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assumption are likely minimal, given that recycled water accounts for less than 2% of global
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water withdrawal (except for India where it reached 14% abruptly in 2010) 26. Because of large
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historical changes in the energy intensity of reverse osmosis (RO) desalination, due to
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improvement in membrane technology and energy efficiency,33 we apply a time-evolving EI in
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the case of RO desalination (Table S4), as detailed in Section S3. All other processes are
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assigned constant EI values over time, because of a lack of data and the relatively modest
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changes over time as compared to that noted for desalination. In addition, effects of groundwater
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depth on EI for groundwater pumping are considered by estimating region-specific average
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groundwater depth (see Section S3).
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The third step applies data on electricity generation and demand from the International
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Energy Agency Energy Balances17-18 to estimate region- and time-specific conversion ratios (CR)
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from primary energy to electricity. These ratios for each region and year are calculated as the
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sum of all primary energy used by the power sector divided by the total electricity consumption
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across all end users;17-18 as such, each ratio accounts for transformation-related losses as well as
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electricity transmission and distribution losses. These ratios, shown for each region over time in
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Table S5, are used to convert the electricity used by water-related activities to total primary
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energy consumption. While these electricity data are considered in the energy research
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community to be of high quality, the actual primary to electric conversion ratios of the electricity
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used for the water-related processes may be somewhat different from the regional averages. To
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address this source of uncertainty, we have generated annual fuel-specific CR for each region
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for each 5-year time period,17-18 and have examined the CR-induced uncertainty based on a non-
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parametric bootstrapping approach34 (see Section S5). Note that for estimating the E4W for
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power plant cooling water withdrawals, we use the ratios of the specific power plant types rather
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than the regional primary:electric conversion ratios.
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Finally, the 50th percentiles of energy intensity, converted to primary energy equivalents
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where appropriate (using the region-average CR), are multiplied by historical water withdrawal
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quantities aggregated by 14 geopolitical regions (Fig. S2) in order to estimate the magnitude of
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E4W for the different sectors, sources and processes. We estimate the region-specific energy
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consumption for each water process by adding up country-level products of the water flow
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amounts and the corresponding EI values within that region. Note that here we represent the
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E4W in the form of primary energy. Generally, the estimation of region-level E4W follows the
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equation below: n
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Ei ,k = ∑ (TEIi , j ,k + EEIi , j ,k × CRi ) ×Wi, j ,k × ∂i , j ,k
(1)
j =1
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where i, j and k stand for the i-th time period, the j-th country within the specific region and the
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k-th water process, TEI and EEI represent thermal and electricity energy intensity (kWh/m3),
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respectively, CR is the region-specific conversion ratio from primary energy to electricity, W
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refers to the amount of water withdrawal (109 m3, bcm), ∂ is a scalar factor that accounts for the
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the portion of water that actually involves energy consumption, and E represents the
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corresponding E4W (EJ). The proportion of the total primary energy consumption allocated to
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E4W is also calculated for each of the 14 regions as well as globally. In general, we use the
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estimates derived from the 50th percentile EI and region-average CR as our central estimate.
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Additionally, we use non-parametric bootstrapping approach34 to investigate the EI- and CR-
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induced uncertainty in the E4W estimates (see Section S5).
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3 Results
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3.1 Estimates of Energy Intensity
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Based upon an extensive literature survey, we provide benchmark values and a plausible
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range of variability of EI for each water-use process (Fig. 1a, Table S1). The range in EI for each
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process is affected by multiple factors, and thus EI may be subject to different sources of
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uncertainty, which directly influence the resulting E4W estimates. Specifically, the EI of source
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and conveyance, water distribution and wastewater pumping are affected by, among others, the
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pumping fuel type, pipe pressure, flow rate, volume of water transported, distance and
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and discharging locations. In addition,, the process of source and conveyance is also affected by
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local water source characteristics (e.g., aquifer depth). Typically, long-distance water transfer
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and high-height water lifting require high EI (e.g., in California), as opposed to shallow surface
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water withdrawal (e.g., in New York). Further, the EI of water treatment and wastewater
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treatment are influenced by quality of the source water, intended end use, technologies applied to
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treat water and wastewater, and size of the water purification/treatment facilities.35-37
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As shown in Fig. 1, both the mean and the variance of EI for surface water “source and
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conveyance” are especially high; in fact, the mean value is higher than the mean for groundwater.
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This reflects the geographic bias of the sample: many studies that present estimates of EI for
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source and conveyance of surface water are from California, which has very high surface water
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EI due to long-distance, intra- and inter-basin water transfers. To remove this bias, the remainder
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of this analysis uses the corresponding EPRI (2002) values as the 50th percentile for surface
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water and groundwater source and conveyance, since these values represent an overall estimate
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across the whole USA. For the 25th and 75th percentile of EI, 0.05 and 0.10 kWh/m3 were
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assigned based on literature sources other than those for California (Table S2a). As indicated in
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Fig. 1, the estimated EI values for municipal and industrial wastewater are relatively high – 0.48
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kWh/m3 and 0.65 kWh/m3, respectively – because of the energy required to remove high
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contaminant loadings before discharging wastewater to the environment. Further, industrial
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wastewater treatment is understood to be more energy-intensive than municipal because of
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comparatively low flow rates and potentially higher loadings.34 Water distribution also requires
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relatively high EI to deliver the treated water from the public municipal facilities to end-use
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points. In contrast, wastewater discharge involves the least energy consumption among the
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water-use processes considered.
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While typically classified as water treatment, desalination is an alternate means of
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providing fresh water. As shown in Table S1 and Fig. 1b, thermal desalination technologies such
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as multistage flash distillation (MSF) and multi-effect distillation (MED) are extremely energy-
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intensive, requiring 2-5 kWh/m3 electrical energy plus 20-120 kWh/m3 thermal energy,
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compared with 2-7 kWh/m3 electrical energy for membrane technologies such as reverse osmosis
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(RO) and electrodialysis (ED). Unlike membrane-based technologies, where the EI depends
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strongly on the salinity of the source water, the EI difference caused by source-water salinity for
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thermal-based technologies is not distinguishable relative to other sources of variation such as
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equipment age and plant capacity, among others.
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3.2 Changes in water withdrawal
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Water withdrawal volumes are inherently linked with the E4W estimates for each region,
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water source type, process, sector and time period (see Eq. 1). Globally, water withdrawals have
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increased gradually in recent decades from 2876 bcm (109 m3) in 1975 to 4169 bcm in 2010 (Fig.
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2), although local decreases have been reported for regions such as the Former Soviet Union
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(FSU) and Eastern Europe in the aftermath of the fall of the FSU, as well as Western Europe due
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to improvements in water use efficiency. Accounting for ~70% of global total fresh water
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withdrawals, agricultural water withdrawals have increased rapidly in India, the Middle East,
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Africa and Latin America, in contrast to the FSU, Eastern Europe, Australia and New Zealand.
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Municipal and industrial water withdrawal has also grown quickly in developing regions such as
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China, India, and Latin America, in contrast to developed regions such as the USA, Canada and
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Western Europe. With respect to water sources, groundwater withdrawals have risen, particularly
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in dry regions such as the Middle East and India, where groundwater-based irrigation has grown
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dramatically in the last few decades.29, 31, 33, 38 In fact, groundwater withdrawals increased from
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654 to 1020 bcm (109 m3) from 1973-2012 globally, and its share in total fresh water withdrawal
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increased over the same period from 24% to 27% (Fig. 2), stimulated by the development and
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availability of low-cost pumps, and by individual investment for irrigation and domestic uses.9
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3.3 Energy for Water
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We find that globally, E4W has increased steadily in the past four decades, from 5.9 EJ in
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1975 to 10.2 EJ in 2010 (using median EI estimates and region-averaged CR). In the following
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sections, we analyze the E4W variations across the three water sources, three end-use sectors, six
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water-use processes and fourteen regions, in order to present comprehensive information on
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E4W from a variety of perspectives.
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3.3.1 E4W across three water sources
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The use of surface water accounts for the majority of the E4W – 5.89 EJ or 58% of total
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E4W in 2010 (Fig. 3, Table S8) – due to its large share (76%) in total fresh and non-fresh water
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withdrawal (Fig. 2, Table S9), even though the EI for surface water tends to be lower than that of
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groundwater except for the case of long-distance transfers (Table S1, S2a). E4W related to
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groundwater amounts to 3.08 EJ in 2010; this accounts for 30% of total E4W, compared with the
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fraction of 25% in total fresh and non-fresh water withdrawal. The rapid growth of desalination,
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especially in the Middle East, USA and FSU (Fig. 4), caused the desalination share of total E4W
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to increase from 0.9% in 1980 to 9.4% in 2010. Large amounts of seawater withdrawal for
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thermoelectric power plant cooling in coastal regions such as Japan, the Middle East, the USA
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and South Korea also lead to a considerable E4W value of 0.27 EJ, out of the 0.96 EJ total for
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non-fresh water in 2010.
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3.3.2 E4W across three sectors The municipal water sector consumed 4.61 EJ of total primary energy in 2010, which
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accounted for 45% of the total E4W for all processes examined, in contrast to its proportion of
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80%) of E4W for desalination as they are more
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energy-intensive (Fig.1, Fig. S3). In addition, >60% of the production capacity in the Middle
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East – accounting for nearly half of worldwide capacity40 – still comes from thermal systems,
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especially MSF.28, 41 Rapid development of desalination in recent years, especially in the Middle
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East, the USA and the FSU, has driven the fast growth of E4W for desalination; as noted above,
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its share of total global E4W increased from 0.9% in 1980 to 9.4% in 2010. Further, there is
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broad agreement that desalination will be expanded in the future to meet the mounting needs for
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freshwater, as freshwater becomes more scarce and desalination costs continue to decrease.33, 42-
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43
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3.3.4 E4W across fourteen regions
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Thus, desalination-related E4W is likely to increase in the future.
There are distinct regional differences in the E4W estimates. While the USA was the
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biggest E4W consumer before 2002 (1.25 EJ in 2000), the Middle East, India, and China
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surpassed the USA from 2003 onwards and became the three largest E4W consumers, with E4W
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values of 1.71, 1.51 and 1.29 EJ in 2005, respectively (Fig. 4 and 5). The decline of E4W in the
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USA resulted mainly from the reduction of the total water withdrawal, as reported by the US
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Geological Survey.44-51 In contrast, groundwater irrigation has expanded in India in the last few
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decades, 29, 31, 52 with the powered irrigation share increasing from 53% to 83% between 1993
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and 2001.26 Further, municipal water use in India has doubled from the early 1990s to 2010.26
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These developments together have led to the rapid growth of E4W in India since the 1990s, and
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to an especially significant increase of E4W relative to total primary energy consumption. In the
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case of the Middle East, the increase in desalination in recent decades – especially the energy-
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intensive MSF – has resulted in dramatic growth of E4W: desalination energy consumption
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increased from 0.02 EJ in 1980 to 0.60 EJ in 2010. The rapid increase of E4W in China has
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occurred mainly as a result of the significant growth of industrial and municipal water
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withdrawals, which have tripled and doubled since late 1980’s, respectively. Nonetheless, on a
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per capita basis, China and India have a relatively low E4W rate when compared to the USA or
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the Middle East (Fig. S4a).
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Rapid growth in E4W has also occurred in developing regions such as Southeast Asia,
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Latin America and Africa. While the biggest E4W increases have occurred in the municipal
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sector in all three regions (Fig. 4), Africa also saw a rapid rise in E4W for agricultural purposes,
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which is not so noticeable in Southeast Asia and Latin America. In contrast to most other regions,
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the FSU and Eastern Europe present a negative trend from the early 1990s to the present, mainly
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due to the decreases of water withdrawal volumes in the aftermath of the dissolution of the
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Soviet Union, which led to abandonment of irrigation pumping facilities and irrigated
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cropland.53-55
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3.4 E4W as a fraction of total primary energy consumption
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Globally, E4W accounts for 1.7-2.7% of total primary energy consumption, considering
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the uncertainties in energy intensities and primary:electric conversion ratios (Fig. 6), with
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notable regional variation in these shares. At the upper end, the Middle East and India had E4W
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shares of 3.0-10.0% in 2010 (Fig. 6 and S3b), mainly because of energy-intensive thermal
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desalination and groundwater pumping for irrigation, respectively. Shares of E4W in Egypt and
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Sudan also amounted to 3.0-5.0% (Fig. S3b), as a result of their wide use of energy-intensive
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power irrigation,26, 56 and despite their low overall energy use, which is characteristic of
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developing economies. In contrast, E4W only accounts for 1.0-1.4% of total primary energy
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consumption in Canada, in part because of its reliance on surface water resources (accounting
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for >95% of the total water withdrawal) and the low energy requirement associated with surface
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water use (see Table S1). Most regions show a declining trend in the proportion of total primary
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energy allocated to E4W in the last few decades, as energy consumption for other uses has
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increased more rapidly than for E4W. However, India and Africa present an increasing trend for
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E4W proportion, mainly because of the rapid growth in groundwater irrigation.
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4 Discussion
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We estimate that in 2010, about 10.2 EJ of primary energy were used globally for water
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abstraction, treatment, distribution, and post-use wastewater treatment and handling. Considering
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several prominent sources of uncertainty, this corresponds to between 1.7% and 2.7% of total
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global primary energy consumption (Fig. 6), comparable with the estimate of less than or equal
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to 3% by Williams and Simmons (2013). As our system boundaries for E4W include only
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processes where water is the output (see Section 1), and exclude processes where energy is
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applied to water for other purposes,25 our estimate of 1.0-1.9% for USA is much lower than the
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47% estimated by Sanders and Webber.20
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While 1.7-2.7% may not appear significant, it nevertheless represents a large quantity of
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energy, and therefore also a significant source of greenhouse gas emissions. Moreover, it is a
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source of energy demand and emissions that stands to grow substantially in the future as (a) an
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increasing share of the global population becomes supplied by municipal water systems, (b) local
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environmental laws are adopted requiring treatment of wastewater prior to discharge, (c)
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irrigated lands expand to support growing populations and economies,57-58 and (d) increasing
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water scarcity leads to the use of lower-quality or saline water,27 deeper groundwater pumping59
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and long-distance transfers.
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However, these and other trends that are important for future E4W and related emissions
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do not occur in isolation, and the existing projections of both the energy and water systems could
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be greatly improved by explicit consideration of relevant cross-sectoral linkages between the two.
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This study contributes to these developments by providing necessary estimates of the quantities
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of energy for water in the base year, water withdrawal volumes by sectors, sources, and
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processes, and benchmark energy intensities that relate specific water-related processes to energy
340
consumption requirements. This step will help to build internal consistency into the water and
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energy system representations in integrated models of the water and energy systems, furthering
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the capacity of these models to address research questions related to the water-energy nexus.
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Limitations to this study arise primarily from data availability and quality (see Section 2).
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The most significant data need is energy supplier-based estimates of the significant E4W flows
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in several large nations or groups thereof, which would allow evaluation of the accuracy of the
346
energy intensity levels assumed globally and over time in this study. Where we used a wide
347
range of energy intensity assumptions to address the unknown average values in each region, this
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uncertainty could be narrowed substantially if the municipal and irrigation water sectors’ energy
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consumption were included in national energy statistics questionnaires. As well, the estimates
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may be biased by not explicitly considering recycled water as an alternate means to supply water
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to end users. The direction and magnitude of this bias likely vary by region, and depend on the
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amount of water re-use, as well as the relative difference in energy intensity between recycled
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water treatment and distribution, compared with freshwater abstraction, treatment, and
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distribution. Limitations also lie in the data-filling approach used with the AQUASTAT raw
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dataset, and the accuracy of the values in the AQUASTAT database (see Section S1).
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This study presents the first overall analysis of global E4W, including its regional and
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temporal variability, and its partitioning among different sectors, water sources and water-use
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processes. Despite the limitations and caveats, our work enhances the understanding of the role
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of E4W in regional energy systems, and more broadly in the water-energy nexus. This work sets
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the foundation for integrated and long-term analysis of the implications of various policy and
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technology strategies in the context of future demands and resource availabilities of both energy
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and water.
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Acknowledgements
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This research was supported by the Office of Science of the U.S. Department of Energy
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through the Integrated Assessment Research Program. PNNL is operated for DOE by Battelle
366
Memorial Institute under contract DE-AC05-76RL01830.
367
Supporting Information
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The supporting information describes the detailed methodology and adjustment to energy
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intensity and water withdrawal, and also provides details of the uncertainty analysis. Supporting
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figures and tables are included: (a) coverage of available data for the key variables in
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AQUASTAT from 1973 to 2012 (Fig. S1); (b) global map of the 14 geopolitical regions used in
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this study (Fig. S2); (c) variations of E4W for desalination by technologies and regions from
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1973–2012 (Fig. S3); (d) country-scale analysis of E4W in 2010 (Fig. S4); (e) energy intensity
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for different processes across different sectors and sources (Table S1); (f) summary of energy
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intensity values by water sources and end-use sectors for water supply system (Table S2a) and 17 ACS Paragon Plus Environment
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wastewater system (Table S2b) and ; (g) summary of energy intensity values for desalination by
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technologies and water sources (Table S3); (h) time-involving energy intensity for RO
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desalination (Table S4); (i) time-involving and region-specific conversion ratio from primary
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energy to electricity (Table S5); (j) time-involving and region-specific percent of industrial water
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withdrawal for power plant cooling (Table S6); (k) time-involving and region-specific seawater
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withdrawal for power plant cooling (Table S7); (l) region-specific E4W at water sources, water-
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use processes and end-use sectors levels in 2010 (Table S8); and (m) region-specific water
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withdrawal at water sources, water-use processes and end-use sectors levels in 2010 (Table S9).
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Aditionally, the appendix S1 includes downloadable data in an Excel file for country-level key
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variables and estimated E4W for 2010. This information is available free of charge via the
386
Internet at http://pubs.acs.org/.
387
Author contributions
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Y.L. and M.A.H. initiated and designed this work. Y.L. conducted the analysis and wrote the
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manuscript. All authors contributed to discussions and interpretations of the results and editing of
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the manuscript.
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References
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54. Łabędzki, L., Irrigation in Poland—current status after reforms in agriculture and future development. Journal of Water and Land Development 2007, 11, 3-16. 55. Baldock, D.; Caraveli, H.; Dwyer, J.; Einschütz, S.; Petersen, J. E.; Sumpsi-Vinas, J.; VarelaOrtega, C. The environmental impacts of irrigation in the european union; Institute for European Environment Policy: London, UK, 2000. 56. Siebert, S., Döll, P., Feick, S., Frenken, K., Hoogeveen, J., Global map of irrigation areas version 4.0.1. In University of Frankfurt and FAO: Frankfurt, Germany, and Rome, Italy, 2007. 57. Bruinsma, J. The resource outlook to 2050. FAO Expert meeting on how to feed the world in 2050, 2009, 1-33 58. Liu, Y., et al. Agriculture intensifies soil moisture decline in Northern China. Scientific Reports 2015, 5, 11261. 59. Taylor, R. G.; Scanlon, B.; Döll, P.; Rodell, M.; Van Beek, R.; Wada, Y.; Longuevergne, L.; Leblanc, M.; Famiglietti, J. S.; Edmunds, M., Ground water and climate change. Nature Climate Change 2013, 3, (4), 322-329. 60. Burn, S., Hoang, M., Zarzo, D., Olewniak, F., Campos, E., Bolto, B., Barron, O., Desalination techniques—A review of the opportunities for desalination in agriculture. Desalination. 2015, 364, 2-16.
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Figure captions
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Figure 1 Range of energy intensity (EI, kWh/m3): (a) by water use processes (ww = wastewater) and water sources (sf = surface water, gw = groundwater) and end-use sectors; and (b) by desalination technologies MSF = multi-stage flash, MED = multi-effect distillation, RO = reverse osmosis, ED = electrodialysis) and water sources. On each box, the edges of the box are the 25th and 75th percentiles and the black line within the box stands for 50th percentile, which was derived from literature listed in Table S2a, S2b and S3. The whiskers extend to the most extreme data points not considered outliers (individual red crosses).
531 532 533 534
Figure 2 Region-specific water withdrawals (109 m3/yr) during 1973–2012 by end-use sectors and by water sources (ag = agricultural, ind = industrial, mun = municipal, sf =surface water, gw = groundwater, nonfresh = non-fresh water, each figure legend item is a specific combination of end-use sector and water source).
535 536 537 538 539 540
Figure 3. Flow of energy for water (E4W, EJ) from water sources to water processes and to water end-use sectors in 2010. Note that this diagram is not intended to show the flows of water from one water process to the next; rather, it is structured so as to highlight the energy flows. Note that 2%, 34% and 64% of E4W embedded in desalination is allocated to agricultural, industrial and municipal sectors based on the installed capacity by end users as reported in ref. 60.
541 542 543 544 545 546 547
Figure 4 Region-specific variations of energy for water (E4W, EJ) by water-use processes and water sources and end-use sectors from 1973–2012, where the 50th percentile of EI for each process and region-averaged CR are applied. The left axis stands for the amount of E4W, and the right axis represents the share of E4W in total primary energy consumption (TPEC) and corresponds to the red line on the plot. The labels for the legend are composed in the format of sector-process-source (ag = agriculture, ind = industry, mun = municipal, supply = water supply processes, ww = wastewater processes, sf = surface water, gw = groundwater, sw = seawater).
548 549 550
Figure 5 Country-specific energy for water (E4W, EJ) in 2010. The map is generated via ESRI ESRI ArcMap10.2, and the results presented are from analysis in this study and the underlying country boundaries are from ESRI World Countries dataset.
551 552 553 554 555 556
Figure 6 Region-specific uncertainties of energy for water (E4W, EJ) derived from uncertainties in energy intensity (EI) and conversion ratio (CR). The dark and light gray area represent the spread of E4W and the spread for share of E4W in total primary energy consumption (TPEC), respectively; these are based on a 95% bootstrap confidence interval induced from the uncertainties in EI and CR. The solid line represents E4W and correspond to the left axis, and the dashed line represents the share of E4W in TPEC, and correspond to the right axis.
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558 559
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Figure 2 800
withdrawal(109 m3/yr)
800
USA
800
China
800
India
600
600
600
600
400
400
400
400
200
200
200
200
0
0
0
0
600
Western Europe
600
Former Soviet Union
600
Latin America
600
400
400
400
400
200
200
200
200
withdrawal(10 9 m3/yr)
withdrawal(10 9 m3/yr)
withdrawal(10 9 m3/yr)
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0
0
0
0
80
80
80
80
Canada
Australia&New Zealand
Eastern Europe
60
60
60
60
40
40
40
40
20
20
20
20
0
0
0
0
300
300
Japan
6000
Africa
200
200
4000
100
100
2000
0
1980
1990
2000
2010
0
1980
1990
2000
2010
0
Global
1980
1990
2000
561
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Middle East
Southeast Asia
Korea
1980
1990
2000
ag_sf ag_gw ind_sf ind_gw ind_nonfresh mun_sf mun_gw mun_nonfresh
2010
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energy for water(EJ/yr) energy for water(EJ/yr) energy for water(EJ/yr)
1.8
USA
3
China
1.5
1.6
1
1.4
6.5
2.5
1
2
6
1.5
1.5
5.5
1
7
Middle East
India
1.5
6.5
1
6
5 0.5
1.2 1
0 1.2
Western Europe
1
1.8 1.6
0.8
1.5
0 1.2
1 Former Soviet Union
1.4
0.4
1.2
0.2
1
1.8
0.6
1.6
0.4 1.4
0.2
0
1 1.8
Canada
2.2 2
0.8
0.6
0.4
0.5
0 0.4
2.5
0.5
4.5
0 1.2
4
1.6
3.8
Latin America
1
0 1.2
5 Southeast Asia
2.3
0.8
0.6
3.4 0.6
2.2
0.4
0.4
2.1
0.2
2
3.2
0.2 0
3
0
0.4
3
0.4
0.3
2.5 0.3
0.2
2
0.1
1.5 0.1
1.9 2.5
Korea
2 0.2
1.4
0.2
0.1
1.2
0.1
2 0.2
1.5
0
1
0
1
3
Japan 0.5
1.8 0.5
0.4 2
0.2
0.3
1.4
0.2 1.5
0.1 0
1980
1990
2000
1 2.2
Global
10
2.15
8
2.1
6
2.05
4
2
2
1.95
1.2 0.1
1 2010
0 12
1.6 0.4
0.3
1.5
Africa
2.5
0
1980
1990
2000
1 2010
2.5 2.4
1
3.6
Eastern Europe
0.3
5.5
0.8
Australia&New Zealand
0.3
0.5
0
1980
1990
2000
1.9 2010
share of energy for water (E4W) in total primary energy comsumption (TPEC)
566 567
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1980
1990
2000
sw_supply_sf desalination mun_ww_gw mun_ww_sf ind_ww_gw ind_ww_sf mun_supply_gw mun_supply_sf ind_supply_gw ind_supply_sf ag_supply_gw ag_supply_sf
1 2010
share of E4W in TPEC (%) share of E4W in TPEC (%) share of E4W in TPEC (%)
Figure 4 energy for water(EJ/yr)
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Figure 6
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