An Economic Assessment of the Global Potential for Seawater Desalination to 2050
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data Collection
2.2. Methodology for Assessment of Economic Feasibility of SWRO
2.3. Statistical Production Cost (PC) Model
2.3.1. Capital Cost Option
t-statistic: (18.9) (156.3) (−18.9) (2.5)
t-statistic: (6.5) (29.3) (−6.5)
t-statistic: (4.8) (9.6) (−4.6)
t-statistic: (4.7) (11.9) (−4.4)
2.3.2. Capacity Option
2.3.3. O&M Cost Option
2.4. Statistical Water Price (WP) Model
t-statistic: (−1.7) (9.8) (3.7)
t-statistic: (−0.4) (2.7) (1.7)
2.5. Future Simulations with Developed PC and WP Models
- Capital cost: Capital cost is estimated using Equations (5)–(8). In these equations, plant capacity selection for each country is based on the results of the decision trees. We assume that each country tends to build the SWRO plant with the largest capacity that is also affordable. For the total installed capacity, Ghaffour, et al. [3] estimate that the current growth rate would be ~55%; here, that same past growth rate is used for the future simulations. Additionally, as in the past simulation, a discount rate of 8% and a 20-year plant life are also used for future periods [30].
- O&M cost: In both the past and the future periods, labor, membrane exchange, and chemical costs are assumed to be constant, as summarized in Table 1. Equation (10) is used to calculate the energy cost.
- Water price: The water price is estimated using Equations (12) and (13) for the two scenarios. First, these functions are used to simulate the change in the water price in each country during different years. In our long-term future simulation, the future projected water price is assumed to change uniformly every year. Second, the function, developed based on data from 56 countries, is applied to compute the deficient water price in the other 84 countries that were not included in the observed dataset. For domestic water withdrawal per capita, Hanasaki, et al. [43] estimate that the growth rate would be ~7.3 × 10−4 m3 person−1 year−1; here, that same past growth rate is used for the future simulations.
- Socioeconomic condition: Shared Socioeconomic Pathways (SSPs) are newly developed socioeconomic scenarios for use in global climate policy studies. They depict five possible future global situations (SSP1–5). In this study, we perform the future simulations primarily under the SSP2, which involves a middle-of-the road scenario with an intermediate GDP per capita and intermediate population growth. This scenario was selected because it is consistent with the development patterns that have been observed over the past century [48].
- Climate policy: As mentioned above, energy cost is an integral part of the unit production cost. This may be greatly affected by future climate policies, as different policies lead to different energy prices [27]. In the present study, to clarify the effect of climate policy on future SWRO diffusion, future simulations of PC and WP models are carried out under the following two climate policy scenarios [49]:
- No climate policy scenario (Baseline): this assumes changes in the socioeconomic conditions in different countries under SSP2 and does not account for the effect of a climate policy (i.e., it assumes there are no constraints on greenhouse gas emissions). Under such a scenario, the energy sources are dependent on traditional fossil fuels.
- Stringent climate policy scenario (RCP2.6): this assumes changes in the socioeconomic conditions in different countries under SSP2 and accounts for the effect of the stringent climate policy of RCP2.6 (i.e., it assumes a stringent constraint on greenhouse gas emissions aimed at keeping the global mean temperature increase below 2 °C by the year 2100). The RCP2.6 scenarios generally involve more renewable energy resources and a higher carbon tax than does the baseline scenario.
3. Results and Discussion
3.1. Production Cost Prediction by Future Simulation of the PC Model
3.2. Water Price Prediction According to Future Simulations of the WC Model
3.3. Economic Feasibility Assessment of SWRO on a Global Scale
3.3.1. Assessment Using the Constant Water Price in 2015
3.3.2. Assessment Incorporating Changes in Water Prices
3.3.3. Sensitivity Analysis of the Feasibility Index
3.4. Data Limitations and Uncertainties
4. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Parameter | Data | Year | Ref. |
---|---|---|---|
Capital cost | 56 countries (764 plants) | 1990–2014 | [9] |
GDP | 56 countries | 1990–2014 | [20] |
Population | 56 countries | 1990–2014 | [20] |
Electricity | 56 countries | 1990–2014 | [21] |
Water price | 56 countries | 1990–2014 | [22,23] |
Water withdrawal | 56 countries | 1990–2000 | [24] |
Water demand | 56 countries | 1990–2001 | [24] |
For future period | |||
GDP | 140 countries | 2015–2050 | [25] |
Population | 140 countries | 2015–2050 | [26] |
Electricity | 17 Regions | 2015–2050 | [27] |
Economic Parameters | |||
Labor cost | 0.1 US $/m3 | [15] | |
Chemical cost | 0.07 US $/m3 | [15] | |
Membrane exchange cost | 0.03 US $/m3 | [15] | |
Energy consumption | 4 kWh/m3 | [6] | |
Maintenance cost | 2% of capital cost | [28] |
Baseline | RCP2.6 | Baseline | ||||||
---|---|---|---|---|---|---|---|---|
(Fi = Wp-2015/Cp-2015) | (Fi = Wp-2015/Cp-2050) | (Fi = Wp-2015/Cp-2050) | (Fi = Wp-2050/Cp-2050) | |||||
2015 | 2050 | 2050 | 2050 | |||||
Class | Population | Percent | Population | Percent | Population | Percent | Population | Percent |
(Million) | (Million) | (Million) | (Million) | |||||
1 (Fi < 0.5) | 1086.8 | 14% | 1622.2 | 18% | 1695.4 | 19% | 610.4 | 7% |
2 (0.5 < Fi < 1) | 382.9 | 5% | 995.7 | 11% | 929.1 | 10% | 1018.1 | 11% |
3 (1 < Fi < 2) | 358.4 | 5% | 411.1 | 4% | 410.1 | 4% | 1238.8 | 14% |
4 (2 < Fi < 4) | 193.2 | 2% | 364.5 | 4% | 361.9 | 4% | 514.9 | 6% |
5 (4 < Fi < 7) | 0.0 | 0.0% | 3.1 | 0.0% | 0.0 | 0.0% | 14.3 | 0.2% |
Global population | 7811.3 | 9149.4 | 9149.4 | 9149.4 | ||||
Class > 2 | 551.6 | 7.1% | 778.6 | 8.5% | 771.9 | 8.4% | 1768.0 | 19.3% |
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Gao, L.; Yoshikawa, S.; Iseri, Y.; Fujimori, S.; Kanae, S. An Economic Assessment of the Global Potential for Seawater Desalination to 2050. Water 2017, 9, 763. https://doi.org/10.3390/w9100763
Gao L, Yoshikawa S, Iseri Y, Fujimori S, Kanae S. An Economic Assessment of the Global Potential for Seawater Desalination to 2050. Water. 2017; 9(10):763. https://doi.org/10.3390/w9100763
Chicago/Turabian StyleGao, Lu, Sayaka Yoshikawa, Yoshihiko Iseri, Shinichiro Fujimori, and Shinjiro Kanae. 2017. "An Economic Assessment of the Global Potential for Seawater Desalination to 2050" Water 9, no. 10: 763. https://doi.org/10.3390/w9100763