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From national indices to regional action—An Analysis of food, energy, water security in Ecuador, Bolivia, and Peru
Environmental Science and Policy 101 (2019) 291–301
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Environmental Science and Policy journal homepage: www.elsevier.com/locate/envsci
From national indices to regional action—An Analysis of food, energy, water security in Ecuador, Bolivia, and Peru Paniz Mohammadpoura, Tasnuva Mahjabina, Jose Fernandeza, Caitlin Gradya,b, a b
T
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Civil and Environmental Engineering Department, Penn State University, 212 Sackett Building, Penn State University, University Park, PA, 16802, United States Rock Ethics Institute, Penn State University, United States
ARTICLE INFO
ABSTRACT
Keywords: Food security Water security Energy security Sustainable development goals Bolivia Peru Ecuador
The food-energy-water (FEW) nexus has emerged over the past decade to build understanding around interlinked resources as a tool for achieving sustainable development. Various frameworks developed to implement nexus thinking however, do not always consider both access and availability of resources in a security perspective. Moreover, indices that calculate FEW measures on a national scale may not adequately describe regional variation within a country. To further understanding of these coupled natural resources and tools for development, this paper presents an approach to quantify FEW security and highlights cases in Ecuador, Peru, and Bolivia where national statistics leave out important regional variation. The outcome is an integrated approach to quantify security measures that can be implemented at multiple spatial scales and institutional levels. This approach can not only provide insight into FEW security in Ecuador, Peru, and Bolivia but can also be an effective tool for assessing multiple development priorities simultaneously throughout the world.
1. Introduction
1.1. Security and the food-energy-water nexus
To sustain a reliable and secure future in food, energy, and water resources (FEW) that is environmentally sound and supports economic growth and development, interconnections and interdependencies among these three resources need to be more clearly understood. In addition to interconnections, climate change will influence the provisioning of all three resources. Increasing population also compounds natural resource availability and ecosystem functioning. Due to these complex, connecting stressors, the nexus of water, food, and energy has emerged as a field that studies the interconnection between limited resources to ensure their sustainable usage. By understanding both how to quantify water, food, and energy security and how these systems are intertwined, we can generate ideas on how to implement integrative approaches to sustainably manage our natural resources. To further understanding of these coupled natural resources, the goals of this paper are to 1) showcase how current approaches to quantifying FEW security national statistics leave out important regional variation, which could, in the future 2) help enhance sustainable development efforts worldwide. The outcome of this work provides an easily implementable framework without necessity of specialized computing equipment or complex mathematics making it well suited for implementation by a wide variety of development actors.
Although the concept of FEW research has been around for decades, the FEW nexus’s popularity in the global research topics expanded precipitously after the Bonn 2011 Conference (Hoff, 2011; Yuan et al., 2018). Hoff (2011) summarized the definitions of food, energy and water security presented in the Bonn 2011 Conference as having availability and accessibility to enough, safe, and nutritious food, having access to clean, reliable, and affordable energy services, and accessibility to safe drinking water and sanitation, respectively, all of which are closely aligned with the Sustainable Development Goals (SDGs). FEW nexus studies can be characterized based on geographical scale (such as global, national, regional, local, or watershed level), temporal scale (present conditions vs. future scenarios), methodology (quantitative, qualitative), data availability, and who is performing the study (Kurian, 2017). Prior research has developed several analytical approaches and conceptual frameworks to address FEW nexus challenges (Bazilian et al., 2011; Leck et al., 2015; Perrone and Hornberger, 2014). The footprint or indicator methods have been applied to assess the environmental impacts of commodity consumption and production (Mahjabin et al., 2018) where the footprint family is comprised of the ecological, water, carbon, land, energy, and material footprints (Galli et al., 2012). The life cycle assessment (LCA) method estimates the environmental impacts of products accounting their full life and the
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Corresponding author at: 212 Sackett Building, Penn State University, University Park, PA, 16802, United States. E-mail address: [email protected] (C. Grady).
https://doi.org/10.1016/j.envsci.2019.08.014 Received 17 March 2019; Received in revised form 26 August 2019; Accepted 26 August 2019 1462-9011/ © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
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Environmentally Extended Input-Output (EEIO) method tracks monetary flows along the supply chain to evaluate the interdependencies between sectors (Paterson et al., 2015). Chang et al. (2016) performed comprehensive nexus modeling to investigate the FEW interconnections and quantified water usage in energy and food production as well as energy consumption of water supply, management, and food processing. A systematic review of FEW nexus study methodologies found several limitations to current approaches including that the use of specific and reproducible methods is uncommon (Albrecht et al., 2018). There are clearly a wide variety of studies that have quantified aspects of the FEW nexus. Most of these studies however focus on food, energy, and water, with little regard to incorporating security perspectives. As such, we will briefly describe several perspectives on what food, energy, and water security mean and how this perspective guides our work. The Food and Agriculture Organization of the United Nations (FAO) defined food security as “when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food which meets their dietary needs and food preferences for an active and healthy life” (FAO, 1996). As such, FAO has developed a set of indicators for evaluating the state of food insecurity in the world that are classified based on four dimensions of availability, access, utilization, and stability. An alternative approach from the Economist Intelligence Unit (EIU) developed the global food security index which considers food affordability, availability, and quality (EIU, 2015). Several studies have highlighted the relevance between food policies, governance, and the agri-food chain with respect to FAO definition of food security (Mayett-Moreno and López Oglesby, 2018) as well as the use of life cycle analysis (Gava et al., 2018) to monitor and work towards achieving food security. Like food security, multiple definitions exist to describe energy security. A review of energy security definitions and indices found that the various existing definitions included components of one or more seven key themes: energy availability, infrastructure, energy prices, societal effects, environment, governance, and energy efficiency (Ang et al., 2015). International Energy Agency (IEA) developed the Energy Development Index (EDI) that includes four indicators: economy development, electricity services reliability, and access to clean cooking facilities and electricity (IEA, 2010). Similar to the described indices, lots of other studies have proposed aggregated energy security indices including several energy-related indicators (Kruyt et al., 2009; Paravantis et al., 2018; Sovacool and Mukherjee, 2011). With regard to water security, in their review article (Wheater and Gober, 2015) classified a variety of water security definitions which included examining water resources in terms of quality, quantity, access, and hazards to evaluating the integrated systems’ sustainability multi-dimensionally. (Sun et al., 2018) evaluated water security in terms of quantity, quality, and hazards in karst areas by developing an index based on the driving force–pressure–state–impact–response–management (DPSIRM) model. (Karamouz et al., 2017) developed a hybrid water sustainability index with focus on water quantity to assess the sustainability (balance) between water supply and demand. United Nations statistics offer a glimpse into the overwhelming reality that billions of people worldwide lack access to key FEW related resources. As of 2019, The UN estimates that nearly 1 billion people lack access to electricity, 3 billion people do not have access to modern cooking fuels, over 2 billion people lack access to basic sanitation services, and millions of people go without clean water or enough food every day (United Nations, 2019). These staggering numbers present a clear need to provide decision makers with a nexus framework that is capable of abstracting the overlap of FEW efforts at an appropriate level, which requires a comprehensive analysis of specific areas where greater food-energy-water security are needed. Taking into account a
perspective in security, the RAND Pardee FEW Security Index has worked to integrate some of these varying dimensions into a quantification of FEW security for each country throughout the world (Willis et al., 2016). This index, which has heavily influenced the work presented within, attempts to quantify FEW security using measures of both accessibility and availability for each security subcomponent. While the RAND Pardee FEW Security Index serves as a starting point for understanding FEW security in a way that may be helpful for decision makers, it still suffers from several limitations, which we have explored by investigating regional variation in FEW security. 1.2. The regional dimension As showcased by the indices mentioned thus far, many of the FEW indices and definitions provided in current literature are created from national and international sources measuring food, energy, and water for national-level statistics. Very few studies have sought to understand the spatial and regional dimensions of security within the nexus and thus there is a need to examine these spatial patterns of resource consumption, production, availability, how resources move from place to place, and potential upstream–downstream linkages, to understand the possibilities of addressing FEW challenges through regional or watershed approaches (Bach et al., 2012; Mcgrane et al., 2018; Rasul, 2016). McGrane et al. (Mcgrane et al., 2018) present a variety of existing nexus frameworks and modelling approaches showcasing some strengths and weaknesses of each however their overall article articulates the necessity for a more comprehensive effort to assess the interconnections between the variety of scales (i.e., spatial, temporal, and governance) for future FEW nexus studies. In an effort to tackle some of these FEW nexus study critiques, we sought to develop and apply a method for measuring FEW security at multiple scales using three neighboring countries as cases for this proof of concept. Ecuador, Peru and Bolivia, collectively representing about 15% of the population of South America, hold key ecological hot spots that will be affected by climate change (Turco et al., 2015). Glacier loss in the Andes Mountains due to climate change presents hydro-social risks to all three countries (Mark et al., 2017; Vuille et al., 2018). The entire region also plays a key role in worldwide agricultural commodity markets as net exporters yet agricultural productivity is also at risk due to shifting climates (Economic Commission for Latin America and the Caribbean, 2016). Despite these security risks, FEW security indices have rated Bolivia, Ecuador, and Peru as relatively secure using national level statistics (Willis et al., 2016). As such, this region presents a perfect opportunity to study the variation between national level and regional level FEW security measures furthering the literature on regional dimensions of FEW security and appropriate levels of implantation for decision makers. To secure food for a population, water is needed to satisfy the demands of the agricultural demands (e.g. water used for irrigation). Moreover, water is also vital to secure energy production (e.g. hydroelectricity generation). Finally, energy is also required to properly secure water for its population (e.g. water distribution systems). It is necessary to understand and address the complicated interconnections between the FEW security components and their subcomponents for SDGs. This paper advances previous FEW security indices by analyzing their applicability for studying sub-national variation between provisioning of food, energy, and water throughout three South American Countries. After presenting the results of this country level regional analysis, we discuss how this methodology could be applied to address SDGs more efficiently and effectively as the worldwide community works to achieve the 2030 targets.
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Fig. 1. Geographic Location of Study Sites.
2. Methodology
the Andes mountain range, spanning a portion of the central and western sides of each country, influences hydroclimatic conditions across the region. These three countries also share similarities for national development statistics. All three have high national FEW security (Willis et al., 2016), high to medium Human Development Index (HDI) (UNDP, 2019) and exhibit key risks to climate change (Villamizar et al., 2017; Vuille et al., 2018). All three countries also achieved significant progress towards achieving the Millennium Development Goals (MDGs). Based on the UNDP’s report, these countries achieved secured improvement in access to market, official development assistant, and access to new information and communication technologies which are three important dimensions in moving toward MDGs (CEPAL, 2010). Due to the unique nature of FEW resources across these countries and the strong national FEW indices, they are well suited to serve as a case study for investigating regional variation across FEW security. Additionally, this work is driven by the hypothesis that regional variation of FEW indices exists and is significantly different from national level statistics. Exploring such regional variation will provide new insights into where resource security in each country is highest and lowest, how the variation is distributed, and what are the factors that contribute to resource insecurity for each region. As we work to implement the SDGs, identifying sub-national areas of need in multiple resource categories has the potential to help development practitioners prioritize strategy development and project implementation. Table A1 lists the data sources for FEW security indicators for the administrative
To analyze the Food-Energy-Water (FEW) security at regional levels, we quantified the FEW security by enhancing an existing integrated FEW security index to ensure transferability, reproducibility, and accuracy. In this paper, Food-Energy-Water Security Index (FEWI) is formulated for evaluating the FEW Nexus conditions in the South American countries of Ecuador, Peru, and, Bolivia at their corresponding administrative-area levels (provinces, regions, and departments, respectively). The framework used for this evaluation is based on the work presented by (Willis et al., 2016) which is going to be referred in this paper as the RAND Pardee approach. First, we outline a detailed description of our study area, then Section 2.2 describes the existing RAND Pardee approach, and finally we describe our approach and how this approach strengthens the transferability, reproducibility, and accuracy of previous work for an integrated FEW security index. 2.1. Study sites- Ecuador, Peru and Bolivia Ecuador, Peru, and Bolivia have a collective population of about 60 million of people and population density of 59, 25 and 10 of people per km2, respectively. Fig. 1 shows the map of these countries' location and their capital cities. These three countries share similar geographical and natural features, which are aspects that have impacts on their respective FEW nexus situations. For example, the eastern edge of each country encompasses a portion of the Amazon rainforest. Additionally,
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Table 1 Components and subcomponents of FEW security index (Modified as described from Pardee RAND approach, Willis et al., 2016). Sub-indices
Security Indicators
Measure
Description
unit
Food
Food Availability
Dietary food supply
Per capita supply of food
Minimum dietary requirement
Kcal Cap . day
Energy
Food Accessibility
Food price level index
Energy Availability
Share of dietary supply from non-starchy foods Electricity consumption
Weighted average of the minimum energy requirements of the different gender-age groups in the population a measure of the monthly change in each region’s prices of a basket of food commodities Ratio of the energy supply provided by all foods except cereals, roots, and tubers to total dietary energy supply Per capita electricity consumption
Per capita electricity requirement
Per capita electricity required to meet basic human needs: 4000*
Electrification rate Percentage access to modern fuel for cooking and heating Municipal water withdrawal
Percentage of the population with access to electricity Percentage of population using modern fuels for cooking and heating.
Ratio Ratio
Country-wide total water withdrawals for municipal uses
Population Per capita water needs for human consumption Percentage access to improved drinking water Percentage access to improved sanitation
Population of the region Per capita water requirements for basic municipal purposes (cooking, eating, and sanitation): 50* The proportion of the population using an improved source of drinking water The proportion of the population using improved sanitation facilities
lit day
Energy Accessibility Water
Water Availability
Water Accessibility
areas of the three countries.
The RAND corporation developed a global index for evaluating the FEW Security which is called FEW Index. This index prepare information for development agencies and research (Willis et al., 2016). The integrated FEW Index is an unweighted, geometric mean of three subindices; food, energy, and water sub-indices. FEW index is mentioned as FEWI in this study and it is determined using, Eq. (1): 3
(FI ) × (EI ) × (WI )
Ratio Kcal Kcal / Cap . day Cap . day kWh Cap kWh Cap
Continuous value lit Cap . day
Ratio Ratio
accessibility, and it is defined as “availability of water resources to meet new needs or compensate for declines in existing sources” (Willis et al., 2016). Willis et al. (2016) considered per capita electricity required to meet basic human needs as 4000 kwh (Pasternak, 2000; Steinberger and Roberts, 2009) and per capita water requirements for basic municipal purposes as 50 lit/Cap.day (Gleick, 1996) that are presented in Table 3 with * above them. In calculating the indices and sub-indices, Willis et al. (2016) decided to normalize the value to prevent the indices from being affected by any one of their single component’s scale. Overall, higher values in this equation therefore represent higher levels of security while lower values represent greater insecurity.
2.2. The RAND Pardee approach
FEWI =
Kcal Cap . day
(1)
Where FI, EI, and WI are food security sub-index, energy security subindex, and water security sub-index, respectively. Among different dimensions that can affect security (e.g. supply reliability, supply diversity and sustainability), each resource’s sub-index in the FEWI include two or more indicators that reflect both availability and accessibility aspects. Availability is defined as the extent to which a given population has enough resources to meet their daily requirements. Accessibility describes how FEW resources are distributed throughout a given population. As adopted by the RAND Pardee approach, we define food availability as the food supplies sufficiency to meet population’s basic nutritional needs. Accessibility to a diverse diet to meet the population’s nutritional needs is defined as food accessibility. Based on the RAND Pardee report description, energy availability is defined as a situation in which “nation's electricity infrastructure meets the needs of individuals to promote human development” and the energy accessibility is defined when “individuals have access to modern forms of energy for residential uses.” Residential energy uses includes electricity, modern heating and cooking fuels. Water availability is defined as the amount of water withdrawals relative to the required water amount to meet basic domestic water needs (cooking, eating, and sanitation). Water accessibility is described as “access of each countries' population to improved drinking water and sanitation.” For water security, water adaptive capacity is considered in addition to availability and
Normalized value =
(Actual Value Logical Minimum) (Logical Maximum Value Logical Minimum) (2)
To select the logical minimum and maximum values, they considered both “the concept being measured” and the “distribution of countries along the scale”. Specifically, for a logical minimum, "0" was the suitable value in all cases while for the logical maximum, in general, it was considered the observed maximum value. However, when the observed value was greater than the maximum possible value, maximum possible value was considered as the logical maximum. The logical minimum and maximum values used to normalize indicators are presented in the Pardee RAND report (Willis et al., 2016). 2.3. From national indices to regional action In order to build upon the existing indicators and test our hypothesis on regional variation we began by developing clearly reproducible variables and equations for each sub-index. The equation for each indicator began based on the RAND Pardee definition for the corresponding indicator however we made modifications and logical leaps when adequate information was not provided by the RAND Pardee report for calculating each sub-index. The focus of FEW nexus application in the RAND Pardee approach was on national level. The
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Table 2 Developed variables and equations for FEW indices. Sector
Security Indicators
Equation
Food
Food Availability
FAv =
DFS MDR
FAc =
2
Food Accessibility
Energy
Water
FEW
Food Security Sub-Index Energy Availability
(Normalized FPI )
EAv =
SDSnon starchy DFS
log(ERcap)
Energy Security Sub-Index
EI = 2 EAv × EAc WAv =
WAc = 2 AID × AIS
Water Security Sub-Index
WI = 3 WAv × WAc
FAv: Food Availability DFS: Dietary Food Supply MDR: Minumum Dietary Requirement FAc: Food Accessibility FPI: Food Price Level Index SDSnon-starchy: Share of Dietary Supply from nonstarchy Foods DFS: Dietary Food Supply FI: Food Security Sub-Index
(3)
WAv: Water Availability MWWcap: Per Capita Municipal Water Withdrawal WNCcap: Per Capita Water Needs for Human Consumption WAc: Water Accessibility AID: Access to Improved Drinking Water (%) AIS: Access to Improved Sanittion (%) WI: Water Security Sub-Index
MWWcap WNCcap
Water Accessibility
)
Eq.
EAv: Energy Availability ECcap: Per Capita Electricity Consumption ERcap: Per Capita Electricity Requirement EAc: Energy Accessibility Erate: Electrification Rate (%) AMFC,h: Access to Modern Fuel for Cooking and Heating (%) EI: Energy Security Sub-Index
log(ECcap)
EAc = 2 Erate × AMFc, h
Food-Energy-Water Security Index
×(
FI = 2 FAv × FAc
Energy Accessibility
Water Availability
1
Variable definitions
FEWI: Food-Energy-Water Security Index
FEWI = 3 FI × EI × WI
difference between this study and the RAND Pardee in the study area scale should be considered in implementing the equations. For example, in this study, the resource uses, demands, and population values were based on each countries’ sub-national administrative areas instead of the national value. We also removed the RAND Pardee calculation for water adaptive capacity because as defined by RAND Pardee, the measure was not calculating a value that held relevance to the meaning of ‘adaptive capacity’ in accordance with the SDGs. Therefore, our water security sub-index indicators consist of a calculated value for water accessibility and water availability. Another important change in our method compared to RAND Pardee approach is in the definiton of Food Price Level Index (FPI). We calculated the FPI based on the FAO description which is defined as “a measure of the monthly change in international prices of a basket of food commodities” However, RAND Pardee report defined the FPI as the ratio of food price in a country to
(4)
(5) (6)
(7)
(8) (9)
(10) (11)
the price of the generic consumption basket. The information that RAND Pardee report cited for their definition for FPI was not available, thefore we used the FAO definition in order to allow for countries to easily reproduce similar analyses. Tables 1 and 2 outline each variable description and definition used throughout the analysis. Finally, the FEW security index can be determined by using the Eq. (11) which is equal to Eq. (1). After calculating the FEW security indices for each administrative area in our study site, we compared national and regional scale results to further understand if and how national statistics can reliably represent FEW security for a particular country. In determining the spatial variation of security for each FEW we visualize and analyze the geographic patterns of their security situation and describe the potential factors that contribute to each resource’s security and insecurity within each region. Outlining each calculated index strengthens and furthers previous literature on FEW security
Fig. 2. Results of FEWs Security Indices for each region.
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Fig. 3. Variation and national calculated values for each country for FI (panel A), EI (panel B), WI (panel C), and FEWI (panel D).
quantification. These equations are computationally accessible to development practitioners from multiple backgrounds.
secured region within the country. As per Fig. 3, another point is that for all 4 indices, the widest regional variation and the least amounts (except for food index) are related to Peru, even though, nationally all of its indices are higher than Bolivia. For Bolivia, the national value for WI and FEW indices are close to the lower limit of the variation range which means that the national value may be underestimating the regional WI and FEW security while the opposite trend is true for Bolivia’s EI security.
3. Results & discussion 3.1. FEW security indices for Bolivia, Peru and Ecuador As shown in Fig. 2, we found wide variation among the calculated indices for each region within our countries of interest. Ecuador showcased the overall highest values with all of their indices above 0.5. All three countries followed similar trends where water security results were highest and food security results were lowest. In each country, larger variation among different regions’ water security and energy security indices exist in contrast to food security, which exhibits lower variation among different regions of each country. While Fig. 2 showcases the array of results for each province, one key goal of this study was to investigate how this type of approach (regional) may differ from national level approaches on measuring FEW Security. Fig. 3 showcases the regional variation for each index with respect to the calculated national statistic. For Ecuador, national values of FI, EI and FEW indices approach the upper limit of the variation range indicating that a reported national statistic may overestimate the FEW security in comparison to regional level values. The widest spatial variation range of the indices is related to water security for Peru (0.310.94) indicating that even though the national water security index for Peru represents close to the average regional amount, water security differs significantly between the least secured region and the most
3.2. Spatial distribution of FEW security indices After calculating these indices at regional level throughout our study area, we evaluated the spatial distribution of the results as shown in Fig. 4. Interpreting the spatial variation of the results, energy and water security in Bolivia share similar distribution patterns with central regions of the country, on both the eastern and western edges, have higher security indices than the northern and southern provinces. The difference between food and water security levels for regions numbered 1, 4, 5, 8, and 9 of Bolivia is also visible. In particular, two provinces in Bolivia, La Paz and Oruro, have high water security despite being located in the Andes Mountains with lower annual rainfall than the northeastern part of the country, which is dominated by rainfall patterns from the Amazon. El Beni presents as the region in Bolivia with the lowest value for FEW security which is dominated by low food and water security according to this index. Peru shares similar distribution patterns as Bolivia where the areas with high energy and water sub-indices are similar for both measures.
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Fig. 4. Spatial distribution of FEWs Security Results. Corresponding province names to numbered location found in Annex Table A2.
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change. Additionally, we have chosen to denote our scale with respect to political boundaries at their corresponding administrative-area levels (provinces, regions, and departments) in these countries which limits the ability for us to build understanding around ecological aspects of FEW security that transcend political boundaries (Cash et al., 2006). The strength of any quantification tool for FEW nexus studies is also heavily tied to the strength of the data. As such, data quality can certainly be investigated as a limitation of this work. For example, within the water security index, we utilize water resource accounting which historically has failed to accurately account for availability and use of groundwater resources. In future use of this framework, it will be critical to continue to improve data availability within the indices. Another interesting pursuit that fell outside the scope of this work is how access to resources might change in the future. For example, currently there is a high reliance on gas in Peru and Bolivia, and gas and crude in Ecuador for energy resources. It would be interesting to track and build greater understanding on how FEW resources are connected to one another and how changes in access to resources such as movement from gas to hydropower could affect FEW resources security.
In Peru, Huancavelica is shown to have the lowest measure of FEW security which is dominated by the low food and water security indices. In general, Bolivia and Ecuador show somewhat uniform spatial distribution in FEW security compared to Peru whose least secured regions are located centrally within the country. This index calculates Ecuador as the most FEW secure. 3.3. Discussion, limitations, and application of FEW security While measuring FEW security can be an important part of achieving global progress, our study showcases that national statistics often misrepresent regional variation for various indicators of food, energy, and water security. Complementing other literature that has highlighted this challenge (Cash et al., 2006; Mcgrane et al., 2018), we have showcased a potential methodology for development agencies to analyze subnational data. An investigation of multiple scales within the nexus can showcase the disparity between human actions and the environment within which these actions take place (Cash et al., 2006). This methodology has the potential to be used across various scales and units of governance. Albrecht et al suggested in their systematic review of nexus studies that strategies to better address policy needs including scenario analysis, site-specific research designs, and engaging stakeholders in participatory activities has the potential to advance nexus approaches (Albrecht et al., 2018). This article attempts to move away from national level FEW assessment tools and towards region specific and in the future site-specific analysis. As showcased in Fig. 3 however, it is important to note that moving between scales has the potential to present starkly different results highlighting a limitation of this approach. Additionally, regarding replicability and applicability in future contexts, employing this method does not require specialized software or complex mathematics making it well suited for development practitioners with multiple backgrounds. Although we did not perform scenario analysis or engage directly with stakeholders, both of these approaches could be logical next steps for this work. Several limitations for nexus frameworks have argued that these approaches often demonstrate a lack of originality, lack of clarity, lack of practical applicability, and or have excluded key information due to bias, ensuring that the frameworks may contribute to a discussion on these topics but ultimately yield no action (Albrecht et al., 2018; Cairns and Krzywoszynska, 2016; Wichelns, 2017). As we build upon previous nexus quantification tools, it is important to reflect on these limitations. We have presented a framework that could be applied at multiple scales with data already being collected by many governments worldwide to provide a tool that may aid decision makers at multiple governance levels. A large limitation of this presented framework is that we have calculated these indices for one respective point in time thus not adequately taking into account time series variability in FEW security interactions including resource availability changes due to climate
4. Conclusions The method proposed in this paper to quantify food, energy, and water security provides a new and practical approach for the enhancement of global development; in particular, it proposes a more holistic view to implement the SDGs in partnership with more than one development goal at a time. With this perspective, the analysis of resource security can be improved to include aspects of both access and availability for national and regional FEW security. The first part of the analysis further highlighted previous calls to understand regional variation behind national statistics to ensure development agents do not leave populations behind when national statistics represent a better picture than many people living throughout the country. Then, the approach suggests that geographical representation of these statistics can allow for targeting multiple security priority at a time. We propose to use selected proxies/indicators based mainly on previous literature and available data allowing reproducible science to continue to influence development practice. Bringing together food, energy, and water security also has the potential to allow development actors to prioritize regions for improvement on multiple goals at the same time. Funding This research was supported by Penn State University and did not receive any specific external grant from funding agencies in the public, commercial, or not-for-profit sectors.
Appendix A
298
299
Electrification Rate
Percentage Access to Modern Fuel for Cooking and Heating Electricity Consumption
Energy Accessibility
Energy Availability
1. Fascículos Provinciales Ecuador (INEC, 2010)
Minimum Dietary Requirement
Dietary Food Supply
1. Perfil de Seguridad Alimentaria y Nutricional Ecuador (FAO, 2014a) 2. Encuesta Nacional de Salud y Nutrición (ENSANUT-ECU, 2012) Encuesta Nacional de Salud y (NutriciónENSANUT-ECU, 2012)
Share of Dietary Supply from Nonstarchy Foods
Food Availability
Variaciones Porcentuales e Índices, Según Divisiones de Bienes y Servicios: Nacional, Regional y Ciudades (INEC, 2018)
Food Price Level Index
2. Human Energy Requirements (FAO et al., 2001)
Ecuador
Food Accessibility
Data Source
Measure
Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Acceso a la Energía en el Perú: Algunas Opciones de Política (OSINERGMIN, 2011) Anuario Estadístico de Electricidad 2009 (Ministerio de Energía y Minas, 2009)
Compendio Estadístico Perú: Electricidad y Agua (INEI, 2013)
Peru
Perú: Formas de acceso al agua y saneamiento básico (INEI, 2015a) Perú: Formas de acceso al agua y saneamiento básico (INEI, 2015b) Perú: Anuario de Estadísticas Ambientales (INEI, 2014) Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Peru
1. Población Estimada al 30 de junio, Por Años Calendario y Sexo (INEI, 2017) 2. Perú: Población total al 30 de junio, por grupos quinquenales de edad, según departamento, provincia y distrito 2015 (INEI, 2015b) 3. Human Energy Requirements (FAO et al., 2001)
1. Perfil de Seguridad Alimentaria y Nutricional Perú (FAO, 2014a) 2. Sala Situacional Alimentaria Nutricional 2: Consumo Alimentario (INEI, ENAHO, 2007)
1. Índice de Precios al Consumidor por Departamentos (INEI, 2009) 2. Índice de Precio al Consumidor Nivel Nacional (Banco Central de Reserva del Perú, 2018) Perfil de Seguridad Alimentaria y Nutricional Perú (FAO, 2014b)
Peru
Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Consumo Anual Per Cápita Ecuador (INEC, 2016)
Name on Document Cobertura Anual del Servicio Eléctrico (ARCONEL, 2016) Fascículos Provinciales Ecuador (INEC, 2010)
Ecuador
Data Source
Sub-Index
Food Security Indicators
Per Capita Electricity Requirement
Measure
Agua potable y alcantarillado para erradicar la pobreza en el Ecuador (SENPLADES, 2014) Agua potable y alcantarillado para erradicar la pobreza en el Ecuador (SENPLADES, 2014) Breve descripción de la administración de los recursos hídricos en el Ecuador (SENAGUA, 2008) Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Ecuador
Data Source
Sub-Index
Energy Security Indicators
Per Capita Water Needs for Consumption
Percentage Access to Improved Drinking Water Percentage Access to Improved Sanitation Municipal Water Withdrawal
Water Accessibility
Water Availability
Measure
Sub-Index
Water Security Indicators
Table A1 Complete data sources and references of FEW security indicators for study sites.
1. Perfil de Seguridad Alimentaria y Nutricional Bolivia (FAO, 2013) 2. Seguridad Alimentaria en Bolivia: La brecha existente entre disponibilidad y demanda calórica (Ximena Alejandra Paz Portal, 2014) 1. Bolivia: Proyecciones de población por departamentos, según sexo y grupos de edad periodo 2000-2030 (INE, 2000) 2. Human Energy Requirements (FAO et al., 2001)
Perfil de Seguridad Alimentaria y Nutricional Bolivia (FAO, 2013)
Índices de Precios al Consumidor, Según División, Enero 2008-Enero 2018 (INE, 2018)
Bolivia
Principal combustible o energía que utilizan para cocinar (INE, 2012) 1. Informe de Rendición Publica de Cuentas (Ministerio de Hidrocarburos y Energía, 2015) 2. Bolivia: Consumo y Numero de Abonados de Energía Eléctrica, Según Departamento (INE, 2016b) Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Mapa del Sistema Eléctrico Nacional Año 2011 (Ministerio de Hidrocarburos y Energía, 2011)
Bolivia
Agua y saneamiento básico: derecho para todos los bolivianos (UDAPE and PNUD Bolivia, 2012) Agua y saneamiento básico: derecho para todos los bolivianos (UDAPE and PNUD Bolivia, 2012) 1. Recursos hídricos de Bolivia (Victor Choque Colque, 1987) 2. INE: Nota de prensa (INE, 2016a) Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Bolivia
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Table A2 Corresponding notation of Provinces in Fig. 4. ID number
Bolivia
Peru
Ecuador
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Chuquisaca Cochabamba El Beni La Paz Oruro Pando Potosí Santa Cruz Tarija
Amazonas Ancash Apurímac Arequipa Ayacucho Cajamarca Callao Cusco Huánuco Huancavelica Ica Junín La Libertad Lambayeque Lima Province Lima Loreto Madre de Dios Moquegua Pasco Piura Puno San Martín Tacna Tumbes Ucayali
Azuay Bolivar Cañar Carchi Chimborazo Cotopaxi El Oro Esmeraldas Galápagos Guayas Imbabura Loja Los Rios Manabi Morona Santiago Napo Orellana Pastaza Pichincha Santa Elena Santo Domingo Sucumbios Tungurahua Zamora Chinchipe
References Associated with Table Annex A ARCONEL. (2016). Cobertura Anual del Servicio Electrico. Quito: ARCONEL. Banco Central de Reserva del Peru. (2018). Indice de Precio al Consumidor Nivel Nacional. Lima: Banco Central de Reserva del Peru. Colque, V. C. (1987). Recursos hidricos de Bolivia. La Paz. ENSANUT-ECU. (2012). Encuesta Nacional de Salud y Nutricion. Quito: ENSANUT-ECU. FAO. (2013). Perfil de Seguridad Alimentaria y Nutricional Bolivia. FAO. FAO. (2014). Perfil de Seguridad Alimentaria y Nutricional Ecuador. FAO. FAO. (2014). Perfil de Seguridad Alimentaria y Nutricional Peru. FAO. FAO, WHO, UNU. (2001). Human Energy Requirements. Rome: FAO. INE. (2000). Bolivia: Proyecciones de poblacion por departamentos, segun sexo y grupos de edad periodo 2000-2030. La Paz: INE. INE. (2012). Principal combustible of energia que utilizan para cocinar. La Paz: INE. INE. (2016). Bolivia: Consumo y Numero de Abonados de Energia Electrica, Segun Departamento. La Paz: INE. INE. (2016). INE: Nota de prensa. La Paz: INE. INE. (2018). Bolivia: Indices de Precios al Consumidor, Segun Division, Enero 2008-Enero 2018. La Paz: INE. INEC. (2010). Fasciculos Provinciales Ecuador. Quito: INEC. INEC. (2016). Consumo Anual Per Capita Ecuador. Quito: INEC. INEC. (2018). Variaciones Porcentuales e Indices, Segun Divisiones de Bienes y Servicios: Nacional, Regional, y Ciudades. Quito: INEC. INEI. (2009). Indice de Precios al Consumidor por Departamentos. Lima: INEI. INEI. (2013). Compendio Estadistico Peru: Electricidad y Agua. Lima: INEI. INEI. (2014). Peru: Poblacion total al 30 de junio, por grupos quinquenales de edad, segun departamento, provincia y distrito. Lima: INEI. INEI. (2015). Peru: Anuario de Estadisiticas Ambientales 2015. Lima: INEI. INEI. (2015). Peru: Formas de acceso al agua y saneamiento basico. Lima: INEI. INEI. (2017). Poblacion Estimada al 30 de junio, por anos, calendario y sexo. Lima: INEI. INEI, ENAHO. (2007). Sala Situacional Alimentaria Nutricional 2: Consumo Alimentario. Lima: INEI. Ministerio de Energia y Minas. (2009). Anuario Estadistico de Electricidad 2009. Lima: Ministerio de Energia y Minas. Ministerio de Hidrocarburos y Energia. (2011). Mapa del Sistema Electrico Nacional Ano 2011. La Paz: Ministerio de Hidrocarburos y Energia. Ministerio de Hidrocarburos y Energia. (2015). Informe de Rendicion Publica de Cuentas. La Paz: Ministerio de Hidrocarburos y Energia. OSINERGMIN. (2011). Acceso a la Energia en el Peru: Algunas Opciones de Politica. Lima: OSINERGMIN. Portal, X. A. (2014). Seguridad Alimentaria en Bolivia: La brecha existente entre disponibilidad y demanda calorica. La Paz. SENAGUA. (2008). Breve descripcion de la administracion de los recursos hidricos en el Ecuador. Quito: SENAGUA. SENPLADES. (2014). Agua potable y alcantarillado para erradicar la pobreza en el Ecuador. Quito. La Secretaría Nacional de Planificación y Desarrollo (SENPLADES). UDAPE and PNUD. (2012). Agua y saneamiento basico: derecho para todos los bolivianos. La Paz. Unidad de Analisis de Politicas Sociales y Economicas (UNDAPE), Programa de las Naciones Unidas para el Desarrollo en Bolivia (PNUD Bolivia).
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From national indices to regional action—An Analysis of food, energy, water security in Ecuador, Bolivia, and Peru Paniz Mohammadpoura, Tasnuva Mahjabina, Jose Fernandeza, Caitlin Gradya,b, a b
T
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Civil and Environmental Engineering Department, Penn State University, 212 Sackett Building, Penn State University, University Park, PA, 16802, United States Rock Ethics Institute, Penn State University, United States
ARTICLE INFO
ABSTRACT
Keywords: Food security Water security Energy security Sustainable development goals Bolivia Peru Ecuador
The food-energy-water (FEW) nexus has emerged over the past decade to build understanding around interlinked resources as a tool for achieving sustainable development. Various frameworks developed to implement nexus thinking however, do not always consider both access and availability of resources in a security perspective. Moreover, indices that calculate FEW measures on a national scale may not adequately describe regional variation within a country. To further understanding of these coupled natural resources and tools for development, this paper presents an approach to quantify FEW security and highlights cases in Ecuador, Peru, and Bolivia where national statistics leave out important regional variation. The outcome is an integrated approach to quantify security measures that can be implemented at multiple spatial scales and institutional levels. This approach can not only provide insight into FEW security in Ecuador, Peru, and Bolivia but can also be an effective tool for assessing multiple development priorities simultaneously throughout the world.
1. Introduction
1.1. Security and the food-energy-water nexus
To sustain a reliable and secure future in food, energy, and water resources (FEW) that is environmentally sound and supports economic growth and development, interconnections and interdependencies among these three resources need to be more clearly understood. In addition to interconnections, climate change will influence the provisioning of all three resources. Increasing population also compounds natural resource availability and ecosystem functioning. Due to these complex, connecting stressors, the nexus of water, food, and energy has emerged as a field that studies the interconnection between limited resources to ensure their sustainable usage. By understanding both how to quantify water, food, and energy security and how these systems are intertwined, we can generate ideas on how to implement integrative approaches to sustainably manage our natural resources. To further understanding of these coupled natural resources, the goals of this paper are to 1) showcase how current approaches to quantifying FEW security national statistics leave out important regional variation, which could, in the future 2) help enhance sustainable development efforts worldwide. The outcome of this work provides an easily implementable framework without necessity of specialized computing equipment or complex mathematics making it well suited for implementation by a wide variety of development actors.
Although the concept of FEW research has been around for decades, the FEW nexus’s popularity in the global research topics expanded precipitously after the Bonn 2011 Conference (Hoff, 2011; Yuan et al., 2018). Hoff (2011) summarized the definitions of food, energy and water security presented in the Bonn 2011 Conference as having availability and accessibility to enough, safe, and nutritious food, having access to clean, reliable, and affordable energy services, and accessibility to safe drinking water and sanitation, respectively, all of which are closely aligned with the Sustainable Development Goals (SDGs). FEW nexus studies can be characterized based on geographical scale (such as global, national, regional, local, or watershed level), temporal scale (present conditions vs. future scenarios), methodology (quantitative, qualitative), data availability, and who is performing the study (Kurian, 2017). Prior research has developed several analytical approaches and conceptual frameworks to address FEW nexus challenges (Bazilian et al., 2011; Leck et al., 2015; Perrone and Hornberger, 2014). The footprint or indicator methods have been applied to assess the environmental impacts of commodity consumption and production (Mahjabin et al., 2018) where the footprint family is comprised of the ecological, water, carbon, land, energy, and material footprints (Galli et al., 2012). The life cycle assessment (LCA) method estimates the environmental impacts of products accounting their full life and the
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Corresponding author at: 212 Sackett Building, Penn State University, University Park, PA, 16802, United States. E-mail address: [email protected] (C. Grady).
https://doi.org/10.1016/j.envsci.2019.08.014 Received 17 March 2019; Received in revised form 26 August 2019; Accepted 26 August 2019 1462-9011/ © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
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Environmentally Extended Input-Output (EEIO) method tracks monetary flows along the supply chain to evaluate the interdependencies between sectors (Paterson et al., 2015). Chang et al. (2016) performed comprehensive nexus modeling to investigate the FEW interconnections and quantified water usage in energy and food production as well as energy consumption of water supply, management, and food processing. A systematic review of FEW nexus study methodologies found several limitations to current approaches including that the use of specific and reproducible methods is uncommon (Albrecht et al., 2018). There are clearly a wide variety of studies that have quantified aspects of the FEW nexus. Most of these studies however focus on food, energy, and water, with little regard to incorporating security perspectives. As such, we will briefly describe several perspectives on what food, energy, and water security mean and how this perspective guides our work. The Food and Agriculture Organization of the United Nations (FAO) defined food security as “when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food which meets their dietary needs and food preferences for an active and healthy life” (FAO, 1996). As such, FAO has developed a set of indicators for evaluating the state of food insecurity in the world that are classified based on four dimensions of availability, access, utilization, and stability. An alternative approach from the Economist Intelligence Unit (EIU) developed the global food security index which considers food affordability, availability, and quality (EIU, 2015). Several studies have highlighted the relevance between food policies, governance, and the agri-food chain with respect to FAO definition of food security (Mayett-Moreno and López Oglesby, 2018) as well as the use of life cycle analysis (Gava et al., 2018) to monitor and work towards achieving food security. Like food security, multiple definitions exist to describe energy security. A review of energy security definitions and indices found that the various existing definitions included components of one or more seven key themes: energy availability, infrastructure, energy prices, societal effects, environment, governance, and energy efficiency (Ang et al., 2015). International Energy Agency (IEA) developed the Energy Development Index (EDI) that includes four indicators: economy development, electricity services reliability, and access to clean cooking facilities and electricity (IEA, 2010). Similar to the described indices, lots of other studies have proposed aggregated energy security indices including several energy-related indicators (Kruyt et al., 2009; Paravantis et al., 2018; Sovacool and Mukherjee, 2011). With regard to water security, in their review article (Wheater and Gober, 2015) classified a variety of water security definitions which included examining water resources in terms of quality, quantity, access, and hazards to evaluating the integrated systems’ sustainability multi-dimensionally. (Sun et al., 2018) evaluated water security in terms of quantity, quality, and hazards in karst areas by developing an index based on the driving force–pressure–state–impact–response–management (DPSIRM) model. (Karamouz et al., 2017) developed a hybrid water sustainability index with focus on water quantity to assess the sustainability (balance) between water supply and demand. United Nations statistics offer a glimpse into the overwhelming reality that billions of people worldwide lack access to key FEW related resources. As of 2019, The UN estimates that nearly 1 billion people lack access to electricity, 3 billion people do not have access to modern cooking fuels, over 2 billion people lack access to basic sanitation services, and millions of people go without clean water or enough food every day (United Nations, 2019). These staggering numbers present a clear need to provide decision makers with a nexus framework that is capable of abstracting the overlap of FEW efforts at an appropriate level, which requires a comprehensive analysis of specific areas where greater food-energy-water security are needed. Taking into account a
perspective in security, the RAND Pardee FEW Security Index has worked to integrate some of these varying dimensions into a quantification of FEW security for each country throughout the world (Willis et al., 2016). This index, which has heavily influenced the work presented within, attempts to quantify FEW security using measures of both accessibility and availability for each security subcomponent. While the RAND Pardee FEW Security Index serves as a starting point for understanding FEW security in a way that may be helpful for decision makers, it still suffers from several limitations, which we have explored by investigating regional variation in FEW security. 1.2. The regional dimension As showcased by the indices mentioned thus far, many of the FEW indices and definitions provided in current literature are created from national and international sources measuring food, energy, and water for national-level statistics. Very few studies have sought to understand the spatial and regional dimensions of security within the nexus and thus there is a need to examine these spatial patterns of resource consumption, production, availability, how resources move from place to place, and potential upstream–downstream linkages, to understand the possibilities of addressing FEW challenges through regional or watershed approaches (Bach et al., 2012; Mcgrane et al., 2018; Rasul, 2016). McGrane et al. (Mcgrane et al., 2018) present a variety of existing nexus frameworks and modelling approaches showcasing some strengths and weaknesses of each however their overall article articulates the necessity for a more comprehensive effort to assess the interconnections between the variety of scales (i.e., spatial, temporal, and governance) for future FEW nexus studies. In an effort to tackle some of these FEW nexus study critiques, we sought to develop and apply a method for measuring FEW security at multiple scales using three neighboring countries as cases for this proof of concept. Ecuador, Peru and Bolivia, collectively representing about 15% of the population of South America, hold key ecological hot spots that will be affected by climate change (Turco et al., 2015). Glacier loss in the Andes Mountains due to climate change presents hydro-social risks to all three countries (Mark et al., 2017; Vuille et al., 2018). The entire region also plays a key role in worldwide agricultural commodity markets as net exporters yet agricultural productivity is also at risk due to shifting climates (Economic Commission for Latin America and the Caribbean, 2016). Despite these security risks, FEW security indices have rated Bolivia, Ecuador, and Peru as relatively secure using national level statistics (Willis et al., 2016). As such, this region presents a perfect opportunity to study the variation between national level and regional level FEW security measures furthering the literature on regional dimensions of FEW security and appropriate levels of implantation for decision makers. To secure food for a population, water is needed to satisfy the demands of the agricultural demands (e.g. water used for irrigation). Moreover, water is also vital to secure energy production (e.g. hydroelectricity generation). Finally, energy is also required to properly secure water for its population (e.g. water distribution systems). It is necessary to understand and address the complicated interconnections between the FEW security components and their subcomponents for SDGs. This paper advances previous FEW security indices by analyzing their applicability for studying sub-national variation between provisioning of food, energy, and water throughout three South American Countries. After presenting the results of this country level regional analysis, we discuss how this methodology could be applied to address SDGs more efficiently and effectively as the worldwide community works to achieve the 2030 targets.
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Fig. 1. Geographic Location of Study Sites.
2. Methodology
the Andes mountain range, spanning a portion of the central and western sides of each country, influences hydroclimatic conditions across the region. These three countries also share similarities for national development statistics. All three have high national FEW security (Willis et al., 2016), high to medium Human Development Index (HDI) (UNDP, 2019) and exhibit key risks to climate change (Villamizar et al., 2017; Vuille et al., 2018). All three countries also achieved significant progress towards achieving the Millennium Development Goals (MDGs). Based on the UNDP’s report, these countries achieved secured improvement in access to market, official development assistant, and access to new information and communication technologies which are three important dimensions in moving toward MDGs (CEPAL, 2010). Due to the unique nature of FEW resources across these countries and the strong national FEW indices, they are well suited to serve as a case study for investigating regional variation across FEW security. Additionally, this work is driven by the hypothesis that regional variation of FEW indices exists and is significantly different from national level statistics. Exploring such regional variation will provide new insights into where resource security in each country is highest and lowest, how the variation is distributed, and what are the factors that contribute to resource insecurity for each region. As we work to implement the SDGs, identifying sub-national areas of need in multiple resource categories has the potential to help development practitioners prioritize strategy development and project implementation. Table A1 lists the data sources for FEW security indicators for the administrative
To analyze the Food-Energy-Water (FEW) security at regional levels, we quantified the FEW security by enhancing an existing integrated FEW security index to ensure transferability, reproducibility, and accuracy. In this paper, Food-Energy-Water Security Index (FEWI) is formulated for evaluating the FEW Nexus conditions in the South American countries of Ecuador, Peru, and, Bolivia at their corresponding administrative-area levels (provinces, regions, and departments, respectively). The framework used for this evaluation is based on the work presented by (Willis et al., 2016) which is going to be referred in this paper as the RAND Pardee approach. First, we outline a detailed description of our study area, then Section 2.2 describes the existing RAND Pardee approach, and finally we describe our approach and how this approach strengthens the transferability, reproducibility, and accuracy of previous work for an integrated FEW security index. 2.1. Study sites- Ecuador, Peru and Bolivia Ecuador, Peru, and Bolivia have a collective population of about 60 million of people and population density of 59, 25 and 10 of people per km2, respectively. Fig. 1 shows the map of these countries' location and their capital cities. These three countries share similar geographical and natural features, which are aspects that have impacts on their respective FEW nexus situations. For example, the eastern edge of each country encompasses a portion of the Amazon rainforest. Additionally,
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Table 1 Components and subcomponents of FEW security index (Modified as described from Pardee RAND approach, Willis et al., 2016). Sub-indices
Security Indicators
Measure
Description
unit
Food
Food Availability
Dietary food supply
Per capita supply of food
Minimum dietary requirement
Kcal Cap . day
Energy
Food Accessibility
Food price level index
Energy Availability
Share of dietary supply from non-starchy foods Electricity consumption
Weighted average of the minimum energy requirements of the different gender-age groups in the population a measure of the monthly change in each region’s prices of a basket of food commodities Ratio of the energy supply provided by all foods except cereals, roots, and tubers to total dietary energy supply Per capita electricity consumption
Per capita electricity requirement
Per capita electricity required to meet basic human needs: 4000*
Electrification rate Percentage access to modern fuel for cooking and heating Municipal water withdrawal
Percentage of the population with access to electricity Percentage of population using modern fuels for cooking and heating.
Ratio Ratio
Country-wide total water withdrawals for municipal uses
Population Per capita water needs for human consumption Percentage access to improved drinking water Percentage access to improved sanitation
Population of the region Per capita water requirements for basic municipal purposes (cooking, eating, and sanitation): 50* The proportion of the population using an improved source of drinking water The proportion of the population using improved sanitation facilities
lit day
Energy Accessibility Water
Water Availability
Water Accessibility
areas of the three countries.
The RAND corporation developed a global index for evaluating the FEW Security which is called FEW Index. This index prepare information for development agencies and research (Willis et al., 2016). The integrated FEW Index is an unweighted, geometric mean of three subindices; food, energy, and water sub-indices. FEW index is mentioned as FEWI in this study and it is determined using, Eq. (1): 3
(FI ) × (EI ) × (WI )
Ratio Kcal Kcal / Cap . day Cap . day kWh Cap kWh Cap
Continuous value lit Cap . day
Ratio Ratio
accessibility, and it is defined as “availability of water resources to meet new needs or compensate for declines in existing sources” (Willis et al., 2016). Willis et al. (2016) considered per capita electricity required to meet basic human needs as 4000 kwh (Pasternak, 2000; Steinberger and Roberts, 2009) and per capita water requirements for basic municipal purposes as 50 lit/Cap.day (Gleick, 1996) that are presented in Table 3 with * above them. In calculating the indices and sub-indices, Willis et al. (2016) decided to normalize the value to prevent the indices from being affected by any one of their single component’s scale. Overall, higher values in this equation therefore represent higher levels of security while lower values represent greater insecurity.
2.2. The RAND Pardee approach
FEWI =
Kcal Cap . day
(1)
Where FI, EI, and WI are food security sub-index, energy security subindex, and water security sub-index, respectively. Among different dimensions that can affect security (e.g. supply reliability, supply diversity and sustainability), each resource’s sub-index in the FEWI include two or more indicators that reflect both availability and accessibility aspects. Availability is defined as the extent to which a given population has enough resources to meet their daily requirements. Accessibility describes how FEW resources are distributed throughout a given population. As adopted by the RAND Pardee approach, we define food availability as the food supplies sufficiency to meet population’s basic nutritional needs. Accessibility to a diverse diet to meet the population’s nutritional needs is defined as food accessibility. Based on the RAND Pardee report description, energy availability is defined as a situation in which “nation's electricity infrastructure meets the needs of individuals to promote human development” and the energy accessibility is defined when “individuals have access to modern forms of energy for residential uses.” Residential energy uses includes electricity, modern heating and cooking fuels. Water availability is defined as the amount of water withdrawals relative to the required water amount to meet basic domestic water needs (cooking, eating, and sanitation). Water accessibility is described as “access of each countries' population to improved drinking water and sanitation.” For water security, water adaptive capacity is considered in addition to availability and
Normalized value =
(Actual Value Logical Minimum) (Logical Maximum Value Logical Minimum) (2)
To select the logical minimum and maximum values, they considered both “the concept being measured” and the “distribution of countries along the scale”. Specifically, for a logical minimum, "0" was the suitable value in all cases while for the logical maximum, in general, it was considered the observed maximum value. However, when the observed value was greater than the maximum possible value, maximum possible value was considered as the logical maximum. The logical minimum and maximum values used to normalize indicators are presented in the Pardee RAND report (Willis et al., 2016). 2.3. From national indices to regional action In order to build upon the existing indicators and test our hypothesis on regional variation we began by developing clearly reproducible variables and equations for each sub-index. The equation for each indicator began based on the RAND Pardee definition for the corresponding indicator however we made modifications and logical leaps when adequate information was not provided by the RAND Pardee report for calculating each sub-index. The focus of FEW nexus application in the RAND Pardee approach was on national level. The
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Table 2 Developed variables and equations for FEW indices. Sector
Security Indicators
Equation
Food
Food Availability
FAv =
DFS MDR
FAc =
2
Food Accessibility
Energy
Water
FEW
Food Security Sub-Index Energy Availability
(Normalized FPI )
EAv =
SDSnon starchy DFS
log(ERcap)
Energy Security Sub-Index
EI = 2 EAv × EAc WAv =
WAc = 2 AID × AIS
Water Security Sub-Index
WI = 3 WAv × WAc
FAv: Food Availability DFS: Dietary Food Supply MDR: Minumum Dietary Requirement FAc: Food Accessibility FPI: Food Price Level Index SDSnon-starchy: Share of Dietary Supply from nonstarchy Foods DFS: Dietary Food Supply FI: Food Security Sub-Index
(3)
WAv: Water Availability MWWcap: Per Capita Municipal Water Withdrawal WNCcap: Per Capita Water Needs for Human Consumption WAc: Water Accessibility AID: Access to Improved Drinking Water (%) AIS: Access to Improved Sanittion (%) WI: Water Security Sub-Index
MWWcap WNCcap
Water Accessibility
)
Eq.
EAv: Energy Availability ECcap: Per Capita Electricity Consumption ERcap: Per Capita Electricity Requirement EAc: Energy Accessibility Erate: Electrification Rate (%) AMFC,h: Access to Modern Fuel for Cooking and Heating (%) EI: Energy Security Sub-Index
log(ECcap)
EAc = 2 Erate × AMFc, h
Food-Energy-Water Security Index
×(
FI = 2 FAv × FAc
Energy Accessibility
Water Availability
1
Variable definitions
FEWI: Food-Energy-Water Security Index
FEWI = 3 FI × EI × WI
difference between this study and the RAND Pardee in the study area scale should be considered in implementing the equations. For example, in this study, the resource uses, demands, and population values were based on each countries’ sub-national administrative areas instead of the national value. We also removed the RAND Pardee calculation for water adaptive capacity because as defined by RAND Pardee, the measure was not calculating a value that held relevance to the meaning of ‘adaptive capacity’ in accordance with the SDGs. Therefore, our water security sub-index indicators consist of a calculated value for water accessibility and water availability. Another important change in our method compared to RAND Pardee approach is in the definiton of Food Price Level Index (FPI). We calculated the FPI based on the FAO description which is defined as “a measure of the monthly change in international prices of a basket of food commodities” However, RAND Pardee report defined the FPI as the ratio of food price in a country to
(4)
(5) (6)
(7)
(8) (9)
(10) (11)
the price of the generic consumption basket. The information that RAND Pardee report cited for their definition for FPI was not available, thefore we used the FAO definition in order to allow for countries to easily reproduce similar analyses. Tables 1 and 2 outline each variable description and definition used throughout the analysis. Finally, the FEW security index can be determined by using the Eq. (11) which is equal to Eq. (1). After calculating the FEW security indices for each administrative area in our study site, we compared national and regional scale results to further understand if and how national statistics can reliably represent FEW security for a particular country. In determining the spatial variation of security for each FEW we visualize and analyze the geographic patterns of their security situation and describe the potential factors that contribute to each resource’s security and insecurity within each region. Outlining each calculated index strengthens and furthers previous literature on FEW security
Fig. 2. Results of FEWs Security Indices for each region.
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Fig. 3. Variation and national calculated values for each country for FI (panel A), EI (panel B), WI (panel C), and FEWI (panel D).
quantification. These equations are computationally accessible to development practitioners from multiple backgrounds.
secured region within the country. As per Fig. 3, another point is that for all 4 indices, the widest regional variation and the least amounts (except for food index) are related to Peru, even though, nationally all of its indices are higher than Bolivia. For Bolivia, the national value for WI and FEW indices are close to the lower limit of the variation range which means that the national value may be underestimating the regional WI and FEW security while the opposite trend is true for Bolivia’s EI security.
3. Results & discussion 3.1. FEW security indices for Bolivia, Peru and Ecuador As shown in Fig. 2, we found wide variation among the calculated indices for each region within our countries of interest. Ecuador showcased the overall highest values with all of their indices above 0.5. All three countries followed similar trends where water security results were highest and food security results were lowest. In each country, larger variation among different regions’ water security and energy security indices exist in contrast to food security, which exhibits lower variation among different regions of each country. While Fig. 2 showcases the array of results for each province, one key goal of this study was to investigate how this type of approach (regional) may differ from national level approaches on measuring FEW Security. Fig. 3 showcases the regional variation for each index with respect to the calculated national statistic. For Ecuador, national values of FI, EI and FEW indices approach the upper limit of the variation range indicating that a reported national statistic may overestimate the FEW security in comparison to regional level values. The widest spatial variation range of the indices is related to water security for Peru (0.310.94) indicating that even though the national water security index for Peru represents close to the average regional amount, water security differs significantly between the least secured region and the most
3.2. Spatial distribution of FEW security indices After calculating these indices at regional level throughout our study area, we evaluated the spatial distribution of the results as shown in Fig. 4. Interpreting the spatial variation of the results, energy and water security in Bolivia share similar distribution patterns with central regions of the country, on both the eastern and western edges, have higher security indices than the northern and southern provinces. The difference between food and water security levels for regions numbered 1, 4, 5, 8, and 9 of Bolivia is also visible. In particular, two provinces in Bolivia, La Paz and Oruro, have high water security despite being located in the Andes Mountains with lower annual rainfall than the northeastern part of the country, which is dominated by rainfall patterns from the Amazon. El Beni presents as the region in Bolivia with the lowest value for FEW security which is dominated by low food and water security according to this index. Peru shares similar distribution patterns as Bolivia where the areas with high energy and water sub-indices are similar for both measures.
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Fig. 4. Spatial distribution of FEWs Security Results. Corresponding province names to numbered location found in Annex Table A2.
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change. Additionally, we have chosen to denote our scale with respect to political boundaries at their corresponding administrative-area levels (provinces, regions, and departments) in these countries which limits the ability for us to build understanding around ecological aspects of FEW security that transcend political boundaries (Cash et al., 2006). The strength of any quantification tool for FEW nexus studies is also heavily tied to the strength of the data. As such, data quality can certainly be investigated as a limitation of this work. For example, within the water security index, we utilize water resource accounting which historically has failed to accurately account for availability and use of groundwater resources. In future use of this framework, it will be critical to continue to improve data availability within the indices. Another interesting pursuit that fell outside the scope of this work is how access to resources might change in the future. For example, currently there is a high reliance on gas in Peru and Bolivia, and gas and crude in Ecuador for energy resources. It would be interesting to track and build greater understanding on how FEW resources are connected to one another and how changes in access to resources such as movement from gas to hydropower could affect FEW resources security.
In Peru, Huancavelica is shown to have the lowest measure of FEW security which is dominated by the low food and water security indices. In general, Bolivia and Ecuador show somewhat uniform spatial distribution in FEW security compared to Peru whose least secured regions are located centrally within the country. This index calculates Ecuador as the most FEW secure. 3.3. Discussion, limitations, and application of FEW security While measuring FEW security can be an important part of achieving global progress, our study showcases that national statistics often misrepresent regional variation for various indicators of food, energy, and water security. Complementing other literature that has highlighted this challenge (Cash et al., 2006; Mcgrane et al., 2018), we have showcased a potential methodology for development agencies to analyze subnational data. An investigation of multiple scales within the nexus can showcase the disparity between human actions and the environment within which these actions take place (Cash et al., 2006). This methodology has the potential to be used across various scales and units of governance. Albrecht et al suggested in their systematic review of nexus studies that strategies to better address policy needs including scenario analysis, site-specific research designs, and engaging stakeholders in participatory activities has the potential to advance nexus approaches (Albrecht et al., 2018). This article attempts to move away from national level FEW assessment tools and towards region specific and in the future site-specific analysis. As showcased in Fig. 3 however, it is important to note that moving between scales has the potential to present starkly different results highlighting a limitation of this approach. Additionally, regarding replicability and applicability in future contexts, employing this method does not require specialized software or complex mathematics making it well suited for development practitioners with multiple backgrounds. Although we did not perform scenario analysis or engage directly with stakeholders, both of these approaches could be logical next steps for this work. Several limitations for nexus frameworks have argued that these approaches often demonstrate a lack of originality, lack of clarity, lack of practical applicability, and or have excluded key information due to bias, ensuring that the frameworks may contribute to a discussion on these topics but ultimately yield no action (Albrecht et al., 2018; Cairns and Krzywoszynska, 2016; Wichelns, 2017). As we build upon previous nexus quantification tools, it is important to reflect on these limitations. We have presented a framework that could be applied at multiple scales with data already being collected by many governments worldwide to provide a tool that may aid decision makers at multiple governance levels. A large limitation of this presented framework is that we have calculated these indices for one respective point in time thus not adequately taking into account time series variability in FEW security interactions including resource availability changes due to climate
4. Conclusions The method proposed in this paper to quantify food, energy, and water security provides a new and practical approach for the enhancement of global development; in particular, it proposes a more holistic view to implement the SDGs in partnership with more than one development goal at a time. With this perspective, the analysis of resource security can be improved to include aspects of both access and availability for national and regional FEW security. The first part of the analysis further highlighted previous calls to understand regional variation behind national statistics to ensure development agents do not leave populations behind when national statistics represent a better picture than many people living throughout the country. Then, the approach suggests that geographical representation of these statistics can allow for targeting multiple security priority at a time. We propose to use selected proxies/indicators based mainly on previous literature and available data allowing reproducible science to continue to influence development practice. Bringing together food, energy, and water security also has the potential to allow development actors to prioritize regions for improvement on multiple goals at the same time. Funding This research was supported by Penn State University and did not receive any specific external grant from funding agencies in the public, commercial, or not-for-profit sectors.
Appendix A
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299
Electrification Rate
Percentage Access to Modern Fuel for Cooking and Heating Electricity Consumption
Energy Accessibility
Energy Availability
1. Fascículos Provinciales Ecuador (INEC, 2010)
Minimum Dietary Requirement
Dietary Food Supply
1. Perfil de Seguridad Alimentaria y Nutricional Ecuador (FAO, 2014a) 2. Encuesta Nacional de Salud y Nutrición (ENSANUT-ECU, 2012) Encuesta Nacional de Salud y (NutriciónENSANUT-ECU, 2012)
Share of Dietary Supply from Nonstarchy Foods
Food Availability
Variaciones Porcentuales e Índices, Según Divisiones de Bienes y Servicios: Nacional, Regional y Ciudades (INEC, 2018)
Food Price Level Index
2. Human Energy Requirements (FAO et al., 2001)
Ecuador
Food Accessibility
Data Source
Measure
Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Acceso a la Energía en el Perú: Algunas Opciones de Política (OSINERGMIN, 2011) Anuario Estadístico de Electricidad 2009 (Ministerio de Energía y Minas, 2009)
Compendio Estadístico Perú: Electricidad y Agua (INEI, 2013)
Peru
Perú: Formas de acceso al agua y saneamiento básico (INEI, 2015a) Perú: Formas de acceso al agua y saneamiento básico (INEI, 2015b) Perú: Anuario de Estadísticas Ambientales (INEI, 2014) Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Peru
1. Población Estimada al 30 de junio, Por Años Calendario y Sexo (INEI, 2017) 2. Perú: Población total al 30 de junio, por grupos quinquenales de edad, según departamento, provincia y distrito 2015 (INEI, 2015b) 3. Human Energy Requirements (FAO et al., 2001)
1. Perfil de Seguridad Alimentaria y Nutricional Perú (FAO, 2014a) 2. Sala Situacional Alimentaria Nutricional 2: Consumo Alimentario (INEI, ENAHO, 2007)
1. Índice de Precios al Consumidor por Departamentos (INEI, 2009) 2. Índice de Precio al Consumidor Nivel Nacional (Banco Central de Reserva del Perú, 2018) Perfil de Seguridad Alimentaria y Nutricional Perú (FAO, 2014b)
Peru
Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Consumo Anual Per Cápita Ecuador (INEC, 2016)
Name on Document Cobertura Anual del Servicio Eléctrico (ARCONEL, 2016) Fascículos Provinciales Ecuador (INEC, 2010)
Ecuador
Data Source
Sub-Index
Food Security Indicators
Per Capita Electricity Requirement
Measure
Agua potable y alcantarillado para erradicar la pobreza en el Ecuador (SENPLADES, 2014) Agua potable y alcantarillado para erradicar la pobreza en el Ecuador (SENPLADES, 2014) Breve descripción de la administración de los recursos hídricos en el Ecuador (SENAGUA, 2008) Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Ecuador
Data Source
Sub-Index
Energy Security Indicators
Per Capita Water Needs for Consumption
Percentage Access to Improved Drinking Water Percentage Access to Improved Sanitation Municipal Water Withdrawal
Water Accessibility
Water Availability
Measure
Sub-Index
Water Security Indicators
Table A1 Complete data sources and references of FEW security indicators for study sites.
1. Perfil de Seguridad Alimentaria y Nutricional Bolivia (FAO, 2013) 2. Seguridad Alimentaria en Bolivia: La brecha existente entre disponibilidad y demanda calórica (Ximena Alejandra Paz Portal, 2014) 1. Bolivia: Proyecciones de población por departamentos, según sexo y grupos de edad periodo 2000-2030 (INE, 2000) 2. Human Energy Requirements (FAO et al., 2001)
Perfil de Seguridad Alimentaria y Nutricional Bolivia (FAO, 2013)
Índices de Precios al Consumidor, Según División, Enero 2008-Enero 2018 (INE, 2018)
Bolivia
Principal combustible o energía que utilizan para cocinar (INE, 2012) 1. Informe de Rendición Publica de Cuentas (Ministerio de Hidrocarburos y Energía, 2015) 2. Bolivia: Consumo y Numero de Abonados de Energía Eléctrica, Según Departamento (INE, 2016b) Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Mapa del Sistema Eléctrico Nacional Año 2011 (Ministerio de Hidrocarburos y Energía, 2011)
Bolivia
Agua y saneamiento básico: derecho para todos los bolivianos (UDAPE and PNUD Bolivia, 2012) Agua y saneamiento básico: derecho para todos los bolivianos (UDAPE and PNUD Bolivia, 2012) 1. Recursos hídricos de Bolivia (Victor Choque Colque, 1987) 2. INE: Nota de prensa (INE, 2016a) Developing the Pardee RAND Food-Energy-Water Security Index (Willis et al., 2016)
Bolivia
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Table A2 Corresponding notation of Provinces in Fig. 4. ID number
Bolivia
Peru
Ecuador
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Chuquisaca Cochabamba El Beni La Paz Oruro Pando Potosí Santa Cruz Tarija
Amazonas Ancash Apurímac Arequipa Ayacucho Cajamarca Callao Cusco Huánuco Huancavelica Ica Junín La Libertad Lambayeque Lima Province Lima Loreto Madre de Dios Moquegua Pasco Piura Puno San Martín Tacna Tumbes Ucayali
Azuay Bolivar Cañar Carchi Chimborazo Cotopaxi El Oro Esmeraldas Galápagos Guayas Imbabura Loja Los Rios Manabi Morona Santiago Napo Orellana Pastaza Pichincha Santa Elena Santo Domingo Sucumbios Tungurahua Zamora Chinchipe
References Associated with Table Annex A ARCONEL. (2016). Cobertura Anual del Servicio Electrico. Quito: ARCONEL. Banco Central de Reserva del Peru. (2018). Indice de Precio al Consumidor Nivel Nacional. Lima: Banco Central de Reserva del Peru. Colque, V. C. (1987). Recursos hidricos de Bolivia. La Paz. ENSANUT-ECU. (2012). Encuesta Nacional de Salud y Nutricion. Quito: ENSANUT-ECU. FAO. (2013). Perfil de Seguridad Alimentaria y Nutricional Bolivia. FAO. FAO. (2014). Perfil de Seguridad Alimentaria y Nutricional Ecuador. FAO. FAO. (2014). Perfil de Seguridad Alimentaria y Nutricional Peru. FAO. FAO, WHO, UNU. (2001). Human Energy Requirements. Rome: FAO. INE. (2000). Bolivia: Proyecciones de poblacion por departamentos, segun sexo y grupos de edad periodo 2000-2030. La Paz: INE. INE. (2012). Principal combustible of energia que utilizan para cocinar. La Paz: INE. INE. (2016). Bolivia: Consumo y Numero de Abonados de Energia Electrica, Segun Departamento. La Paz: INE. INE. (2016). INE: Nota de prensa. La Paz: INE. INE. (2018). Bolivia: Indices de Precios al Consumidor, Segun Division, Enero 2008-Enero 2018. La Paz: INE. INEC. (2010). Fasciculos Provinciales Ecuador. Quito: INEC. INEC. (2016). Consumo Anual Per Capita Ecuador. Quito: INEC. INEC. (2018). Variaciones Porcentuales e Indices, Segun Divisiones de Bienes y Servicios: Nacional, Regional, y Ciudades. Quito: INEC. INEI. (2009). Indice de Precios al Consumidor por Departamentos. Lima: INEI. INEI. (2013). Compendio Estadistico Peru: Electricidad y Agua. Lima: INEI. INEI. (2014). Peru: Poblacion total al 30 de junio, por grupos quinquenales de edad, segun departamento, provincia y distrito. Lima: INEI. INEI. (2015). Peru: Anuario de Estadisiticas Ambientales 2015. Lima: INEI. INEI. (2015). Peru: Formas de acceso al agua y saneamiento basico. Lima: INEI. INEI. (2017). Poblacion Estimada al 30 de junio, por anos, calendario y sexo. Lima: INEI. INEI, ENAHO. (2007). Sala Situacional Alimentaria Nutricional 2: Consumo Alimentario. Lima: INEI. Ministerio de Energia y Minas. (2009). Anuario Estadistico de Electricidad 2009. Lima: Ministerio de Energia y Minas. Ministerio de Hidrocarburos y Energia. (2011). Mapa del Sistema Electrico Nacional Ano 2011. La Paz: Ministerio de Hidrocarburos y Energia. Ministerio de Hidrocarburos y Energia. (2015). Informe de Rendicion Publica de Cuentas. La Paz: Ministerio de Hidrocarburos y Energia. OSINERGMIN. (2011). Acceso a la Energia en el Peru: Algunas Opciones de Politica. Lima: OSINERGMIN. Portal, X. A. (2014). Seguridad Alimentaria en Bolivia: La brecha existente entre disponibilidad y demanda calorica. La Paz. SENAGUA. (2008). Breve descripcion de la administracion de los recursos hidricos en el Ecuador. Quito: SENAGUA. SENPLADES. (2014). Agua potable y alcantarillado para erradicar la pobreza en el Ecuador. Quito. La Secretaría Nacional de Planificación y Desarrollo (SENPLADES). UDAPE and PNUD. (2012). Agua y saneamiento basico: derecho para todos los bolivianos. La Paz. Unidad de Analisis de Politicas Sociales y Economicas (UNDAPE), Programa de las Naciones Unidas para el Desarrollo en Bolivia (PNUD Bolivia).
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