*3.1. MCDI Response Surface*

Measured response variables and calculated response variables are determined from MCDI lab tests (Table 2).

The primary response data include *[NaCl]out*, *THout* and *WR*. Comparison of *[NaCl]out* and *[NaCl]in* shows that feed water NaCl concentration is e ffectively reduced during MCDI tests. A maximal reduction of 91% in [NaCl] is found (run 20) while median removal equals only 16%. This indicates that overall removal of [NaCl] is relatively low, which is expected when aiming for partial desalination. A similar trend is found for *TH*, maximal removal amounts to 88% while median removal equals 23%. Water recovery is generally high for MCDI tests (67% min. to 85% med. to 95% max.) This is desired as MCDI *WR* is expected to largely a ffect overall water use e fficiency when MCDI is used in combination with a CT. Secondary response variables include specific energy use (kWh m<sup>−</sup>3in), estimated cost (€ m<sup>−</sup>3in) and selectivity (-). The median specific energy use of the MCDI system amounts to 0.18 kWh m<sup>−</sup>3, which is well within the expected range [9,20]. Maximal *E* (0.58 kWh m<sup>−</sup>3) is found for test run 20 in which 90% reduction in [NaCl] was obtained. Cost estimates range from 0.59 € m<sup>−</sup>3in minimum over 0.98 € m<sup>−</sup>3in median to 2.95 € m<sup>−</sup>3in maximum. Cost estimates in literature are scarce and range from low, 0.11 \$ m<sup>−</sup><sup>3</sup> for CDI (no membranes) on low salinity feed of ≤2000 ppm assuming a 15-year module depreciation [27], to high, 11.7 € ton−<sup>1</sup> for a 3 kg m<sup>−</sup><sup>3</sup> [Na+] biomass hydrolysate [28]. It needs to be mentioned that the purpose of cost estimation is to distinguish between the economics of di fferent process settings rather than to mirror the exact cost of the MCDI process. Selectivity is calculated for the di fferent runs and *S* is found to vary between 0.8 minimum and 1.45 maximum with 1.08 as median. Following data acquisition, least-squares multiple regression analysis and a subsequent model reduction procedure are applied resulting in a set of regression equations relating response variables to relevant factors and combinations thereof (Table 3).




*Energies* **2020**, *13*, 1305

The equations for the primary response variables [NaCl]out and *THout* have a good fit (*R*<sup>2</sup>*adj.*, *R*<sup>2</sup> = 0.99 and 0.95), while that for WR is less good (*R*<sup>2</sup>*adj.* = 0.83). Post-hoc testing of residuals shows that the assumption of normality is satisfied (Shapiro–Wilk's (SW) W test: *[NaCl]out*, *W* = 0.96, *p* = 0.40; *THout*, *W* = 0.98, *p* = 0.76; *WR*, *W* = 0.95, *p* = 0.17). The effect of different factors on response variables is quantified by the pareto order of their standardized effects (Table 3). It can be seen that *[NaCl]out* depends largely on the *[NaCl]in*. Besides this effect, *Qads, Iads* and *tads* have a smaller but relevant influence on desalination. Low *[NaCl]out* occurs for intermediate *tads*, high *Iads* and low *Qads*. From factor signs, it can be seen that *[NaCl]out* is lowest at low flow rates. This is in accordance with previous findings [30], ion removal rate increases with increasing flowrate, but the effect of shorter contact time due to increased flow rate is larger. *THout* depends largely on *THin* and is also lowest at intermediate *tads*, high *Iads* and low *Qads*. Trends for *THout* are highly similar to those for *[NaCl]out*. In addition, less hardness is removed from brackish water compared to sweet water, since *THout* depends also on *[NaCl]in*. Maximal *WR* is achieved at low *Iads* and short *tads*, which conflicts with the desired parameter settings required for low *THout* and *[NaCl]out*. For the secondary response variables, only the reduced equation for *Cost* has a good fit (*R*<sup>2</sup>*adj.* = 0.95). The equation (Table 3) indicates that *Cost* is depending of *Qads* and *Q*<sup>2</sup>*ads* only. Flowrate is directly related to required electrode surface, which confirms the notion that MCDI cost is largely determined by equipment cost [23]. Residuals analysis shows a systematic underprediction of cost at low flowrate and overprediction at high flowrate causing the normality assumption not to be satisfied (SW, *W* = 0.77, *p* < 0.001). A power law of *Q* and *Cost* is fit and used instead for further evaluation (*Cost* = 146, *Qads*−0.997, *R*<sup>2</sup> = 0.99). The model equation for E has a less good fit (*R*<sup>2</sup>*adj.* = 0.82) and residuals normality was not satisfied (SW, *W* = 0.91, *p* = 0.013). The model equation for *S* consists of an intercept only. This is indicative of a small but significant selectivity for Ca2+ removal (*S* = 1.11; *t* (4.9); *p* < 0.001). The equations for *S* and *E* are not further used in the analysis of the combined MCDI-CT system.

## *3.2. MCDI-CT Process Evaluation*
