Environmental and economic analysis for desalinating seawater of high salinity using reverse osmosis: a life cycle assessment approach

Abstract

Although seawater reverse osmosis (SWRO) desalination is mainstream worldwide, the performance of SWRO in some arid states faces some challenges. Two SWRO desalination plants (DPs) in Kuwait have reduced their operations and consume additional energy and chemicals compared to the average SWRO DPs. The objective of this study is to evaluate two local SWRO DPs environmentally using life cycle assessments and economically using the levelized cost of water method. In addition, this paper conducts hypothesis tests and regression analyses to investigate the relationships among different seawater parameters, salinity and turbidity, and the environmental and economic impacts of SWRO desalination. The results indicate that the environmental impact for SWRO DPs in Kuwait is approximately 40% higher than that in another international study of comparable parameters. The economic analysis showed that the SWRO desalination unit cost is $1.36/m³ on average, compared to the world average unit cost of $0.5–0.66/m³. Finally, the regression analysis reveals the significant contribution of turbidity to the consumption of ferric chloride and sulfuric acid. However, both turbidity and conductivity had significant effects on anti-scalant consumption. The environmental and economic feasibility of a SWRO DP is highly dependent on the plant’s location.

Appendices

Appendix 1: Cost and TWC calculations

See Table 10

Table 10 Cost data for SWRO DPs in Kuwait (MEW, 2020)

• 1. Compute ${\text{NPV}}_{p}$ for each DP with n = 30 and i = 6.67% according to Eq. (1):

  $$\begin{aligned} {\text{NPV}}_{1} = & - 290,400,000 - 2,756,160\left( {P/A, g,i,30} \right) - 4,478,327.7 \left( {P/A,g,i,25} \right)\left( {P/F,i,5} \right) \\ & - 2,063,522.67 \left( {P/A,i,25} \right)\left( {P/F,i,5} \right) - 7,675,800\left( {P/A,i,25} \right)\left( {P/F,i,5} \right) \\ = & - \$ 466,504,210 \\ \end{aligned}$$
  $$\begin{aligned} {\text{NPV}}_{2} = & - 311,181,420 - 1,972,872\left( {P/A, g,i,30} \right) - 3,863,469.39\left( {P/A,g,i,25} \right)\left( {P/F,i,5} \right) \\ & - 1,769,522.57\left( {P/A,i,25} \right)\left( {P/F,i,5} \right) - 317,024.334\left( {P/A,i,25} \right)\left( {P/F,i,5} \right) \\ = & - \$ 401,058,992 \\ \end{aligned}$$

• 2. Find $AE_{p}$ for each DP according to Eq. (6):

  $${\text{AE}}_{1} = - 466,504,210\left( {A/P, i,30} \right) = - 36,355,463.4 \$ /{\text{year}}$$
  $${\text{AE}}_{2} = - 401,058,992 \left( {A/P, i,30} \right) = - 31,255,206.8 \$ /{\text{year}}$$

• 3. Determine ${\text{TWC}}_{p}$ of each DP according to Eq. (7):

  $${\text{TWC}}_{1} = \frac{36,355,463.4}{{24,847,791.42}} = \$ 1.46/{\text{m}}^{3}$$
  $${\text{TWC}}_{2} = \frac{31,255,206.8}{{24,847,791.42}} = \$ 1.26/{\text{m}}^{3}$$

Appendix 2: Residual plots

See Figs. 16, 17, 18, 19.

Fig. 16

Residual plots for the energy consumption in (kWh) using a multiple regression model including turbidity, conductivity and production

Fig. 17

Residual plots for Ferric Chloride consumption in (Ltr) using a multiple regression model including turbidity, conductivity and production

Fig. 18

Residual plots for Antiscalant consumption in (Ltr) using a multiple regression model including turbidity, conductivity and production

Fig. 19

Residual plots for Sulphuric acid consumption in (Ltr) using a multiple regression model including turbidity, conductivity and production