CO 2 mitigation,energy matrices,and the performance analysis of N-evacuated tube collector (ETC)-integrated modified solar distiller for water/electricity co-generation using CQD nanoparticles

Abstract

With advances in science and technology, nanofluids are the ultrafast heat transfer fluids which effectively empowers the distillation process. In this research article, N-evacuated tube collector (N-ETC)-coupled single slope solar still-equipped built-in-passive condenser and roof-top semitransparent photovoltaic (PV) module have been analyzed incorporating carbon quantum dot nanoparticles (CQD-NPs). The effect of volume concentration of nanoparticles (NPs) and packing factor (β_c) is tested to study the system performance (thermal and electrical). The use of CQD-NPs showed impressive enhancement in thermal conductivity (56.06%), Reynold's number ( $7.93 \times 10^{3}$ ), evaporative (37.9%) and convective (76.94%) heat transfer coefficient even at moderate value of β_c (0.67). Thermal energy efficiency and overall daily productivity is improved by 37.67% and 44.15%, respectively, using CQD-NPs. Moreover, thermal energy/exergy-based energy metrics and life cycle assessment has been performed for different lifespans (n = 1 to 50 years) of the proposed system. Significant improvement in life cycle conversion efficiency [31.90% (β_c= 0), 28.91% (β_c= 0.67), 24.56% (β_c= 0.75), 32.02% (β_c= 0.85), 53.38% (β_c= 0.95)] is observed; also, enviro-economic analysis showed effective rise in annual CO₂ mitigation (tons) [41.39 (β_c= 0), 104.85 (β_c= 0.67), 96.23 (β_c= 0.75), 85.14 (β_c= 0.85), 65.51 (β_c= 0.95)] and carbon credits earned using CQD-NPs. This renewable stand-alone two-in-one output system effectively meet the drinking water and electrical energy requirements of societies, and families living in arid/semiarid regions.

Keywords

CQDs solar still evacuated tube collectors photovoltaic heat exchanger nanofluid carbon mitigation

Introduction

Solar energy is an ample source of energy and its maximum utilization should be the first priority in order to preserve our non-conventional sources of energy. Nowadays, drinking water sacristy and clean electrical energy production is the global concern. We not able to balance the demand-supply equation of drinking water and clean electrical energy for human kind and this problem is getting more complex day by day. Human kind may survive without electricity or other essentials for some period but clean drinking water is the basic necessity of all living organism everyday on the planet Earth. With advances in material science, nanotechnology and thermal science, researchers and engineers continuously put efforts to find alternative technologies or methods (multiple effect desalination, microbial electrosynthesis, reverse osmosis, etc.) to produce clean drinking water from saline or filthy water. Solar distillation is one of the ancient, environment friendly technologies to produce drinking water utilizing an ample source of energy (sunlight). In last few decades, in literature, researchers have already reported experimental and theoretical work on passive and active solar distillation systems and put a lot of efforts to improve the solar still efficiency by changing design and non-conventional external integrations.^1–7 The productivity is directly proportional to the heat transfer mechanism inside the solar distiller, its area and design. The productivity or efficiency is reported low and it becomes difficult to meet the drinking water requirements for a small family in arid-regions. Active solar distillation process is more effective than the passive distillation process as reported in literature. Efficiency of these systems can further be improved incorporating and testing different types of external thermal energy providers (photovoltaic thermal flat plate collector (PVT-FPC), evacuated tube collector (ETC), and photovoltaic thermal compound parabolic concentrator (PVT-CPC), etc.), basefluids (thermal oil, EG, etc.), different nanoparticles (NPs) (CuO, SiO₂ Al₂O₃, etc.), PV technology (c-type, a-type, mono, SPV, etc.) and other minor/major modifications in the system designs.

Today, with advances in science and technology, nanofluids are available as the ultrafast embryonic fluids and behave as an excellent heat transfer carriers in solar thermal systems; and it is credited to their better thermo-physical properties (thermal conductivity, viscosity, density, and specific heat).^8–12 At the lower nanoscale (diameter below 10 nm), materials characterization is difficult and raises their cost of processing/embodied energy (EE) but it make them highly efficient due to their extremely good thermophysical properties. Better heat transfer mechanism of nanofluids is credited to the better absorption characteristics of assisting carbon quantum dot nanoparticles (CQD-NPs), which is due to the maximum overlapping of the spectrum of optical absorption spectrum and solar radiation. Moreover, in fluid suspensions, Brownian motion plays a vital process which controls the thermal behavior of NPs; and the interfacial nanolayers change the viscous forces, which in turn improves the heat transfer rates.

Lui et al.¹³ reported the study of evacuated tubes and ultrasonic foggers integrated developed passive solar distillation system using foggers and CO₃O₄ nanofluids. As the high productivity depends on the temeprature differnces between two surfaces; they operated the system via cooling down the external condensing cover and reported efficiencies of 83.87%, 18.29%, and 38.86%, potable water production, energy efficiency, and exergy efficiency, respectively. Also, the cost per liter of potable water is lowered by 11.61%. Abdelaziz et al.¹⁴ performed a detailed analysis of the tubular solar still-incorporated five major additions, viz. (1) v-corrugated aluminum basin, (2) wick material, (3) carbon black nanofluid, (4) pure paraffin-wax phase change material, and (5) v-corrugated basin combined with wick. They reported efficiencies of 82.16% and 221.8%, respectively, enhancement in thermal energy and exergy efficiencies for the best case (v); and minimized around 22.47% cost in comparison to the conventional tubular solar still. Later, Chen at al.¹⁵ performed the stability and performance analysis of solar still using of low-cost carbon quantum dots (CQDs) saline water-based nanofluids and they reported 57.9% rise in daily potable water production in compared to the conventional stills. Also, they found 34.23% and 21.52%, respectively, average energy efficiency with or without using CQD-water-based nanofluids; with 0.013–0.015 $/L cost of potable water production with CQD NPs.

Alsaiari et al.¹⁶ experimentally analyzed the performance analysis of TiO₂/Jackfruit peel nanocomposites (green synthesis) in solar distillation system. They reported 50.55% improvement in daily productivity (8.7919 L/m²) as comapred to conventional solar still. Arora et al.¹⁷ analytically analyzed partially covered N-PVT-CPC integrated solar still equipped with helically coiled heat exchanger (HCHE) incorporating MWCNTs and SWCNTs. They studied the HTCs, Nusselt number, thermal energy/exergy, economic viability and daily productivity; and found significant improvement in natural convective HTCs (46.4%) of fluid collector, heat exchanger (HE) (46.7%) and double slope solar still (76.7%) sections for SWCNT-NPs. From their analysis of the proposed system operating with and without HCHE, they suggested the necessary use of HE as a medium in the solar distiller section for the proper flow of the nanofluid; and it resolve the major issues like sedimentation, clustering of NPs, re-collection of original nanofluid, separation of NPs from the host fluid, and the reuse of nanofluids, etc. The external thermal energy from its outlet (PVT-FPC, PVT-CPC, ETC, etc.) can be in plugged directly (high efficiency) or via HE (relatively bit low efficiency) to the solar distillation unit (in case of nanofluids) as suggested above. Deshmukh et al.¹⁸ executed the experimental investigation of heat transfer characteristics, friction factor and solar thermal efficiency analysis of TiN-nanofluid filled U-pipe ETCs; and they reported the improvement in overall efficiency by 70.9%. Abdullah et al.¹⁹ experimentally investigated the performance of rotating wick solar still using two different designs, viz. (1) a path of “L” character shape (L-RWSS), and (2) a path of “LC” shape (LC-RWSS) for black jute and cotton wicks using quantum dot nanofluids. They reported 17% higher productivity of LC-RWSS always over the L-RWSS using CQD nanofluids. It has been observed that apart from the extremal integrations and fluid properties, the design modification also improves the system performance effectively, but it is equally important to restrict and lower down the unit cost or productivity cost. Ghandourah et al.²⁰ used an optimized neural network model with golden jackal optimizer for the performance analysis of aluminum and polycarbonate solar stills with air cavity. They reported improved results of the average exergy efficiency (2.30% and 3.44%), energy efficiency (42.40% and 48.80%) and daily productivity (3.40 l/m² and 3.80 l/m²) of polycarbonate for second solar still (PCSS) and aluminum for first solar still (ALSS), respectively. Later, Alsaiari et al.²¹ used artificial rabbits optimizer coupled artificial neural network to predict the daily yield of fresh water for different designs of the solar still. Sahota et al.²² analytically performed the cost analysis of modified built-in-passive condenser and roof-top semitransparent PV module integrated passive single slope solar still (SSSS). They studied the effect of β_c (packing factor) of different PV technologies. They reported 57.5%, 55.2%, 53.4%, 53.1%, and 41.4% maximum overall energy efficiency and 1.78g, 2.83, 3.66, 4.12, and 4.92 kg daily productivity for β_c= 0.85, 0.65, 0.45, 0.25 and 0, respectively, for crystalline silicon (c-Si) semitransparent PV module. Thermal and electrical outputs of this self-sustained system can be controlled varying the β_c value of roof-top semitransparent PV module according to daily domestic needs. The efficiency of this effective systems can further be improved by integrating it to the external thermal energy supplying units (PVT-FPC, PVT-CPC, ETC, etc.); and with the use of heat transfer carriers (nanofluids).

Based on the thermal energy and exergy, analysis of CO₂ mitigation and life cycle analysis (energy matrices) is an integral part of the performance analysis of the solar thermal systems. Kumar et al.²³ experimentally performed the detailed performance, thermo-enviro-economic and thermos-economic analysis of SSSS and DSSS using silver nanofluids for better design optimization. They reported 41%, 5.63%, and 7.35 kg/m² daily thermal energy, exergy and productivity output, respectively, for 0.8 cm water depth; also, they reported 7.97 tons of CO₂ mitigation. Exergo-economic and enviro-economic analysis is an important method; and it help the designers/manufacturers to find complementary procedures for the system efficiency improvement. Dhivagar et al.²⁴ depicted the performance and enviro-economic analysis of modified solar still using black iron oxide magnetic powder as an energy storage material. They reported 39.8%, 14.5%, and 31.2% improvement in evaporative heat transfer rate, convective heat transfer rate and productivity in comparison to the conventional solar still. They also analyzed thermal energy and exergy efficiencies and found significant enhancement around 18.9% and 19.04%, respectively. In addition, from the exergo-economic analysis, 45.53% improvement in CO₂ mitigation have been reported in comparison to conventional solar still. Modification in system design effectively improves the system performance; Shatar et al.²⁵ analyzed the energy/exergy, enviro-economic and exergy-economic analysis of partially thermoelectric cover cooling-based partially coated roof-top condensing cover solar still. Cooling to the roof-top condensing cover help to maintain the higher temperature difference between the two surfaces which intern raises the evaporation mechanism in the distiller chamber. They reported 128% enhancement in potable water output with 36 W thermo-electric cooling capacity; and 2.97 tons of CO₂ mitigation with 0.036$/L final productivity cost.

Nazari et al.²⁶ performed the energy, exergy and cost analysis of SSSS using the CuO nanofluid; and they reported 81%, 80.6%, 38.5% enhancement in thermal energy, thermal exergy efficiencies and productivity, respectively, with optimized 0.0218 ($/L/m²) cost and 13.8 months energy payback period. In detailed review, Iqbal et al.²⁷ put efforts to highlight the desalination process in solar stills incorporated with different nanofluids and their innovative progress in the last decade. With the advancement of nanotechnology, and photovoltaic technology, they favored the use of ultrafast heat transfer nanofluids to raise the thermal system performance (desalination process) with promising economic and environmental benefits. In recent times, many researchers reported work on solar distillation systems incorporating nanofluids and reported the performance of solar distillation systems coupled with different external thermal energy supplier systems (PVT-FPC, PVT-CPC, ETC, etc.) using water as a basefluid but very few researchers have reported with the use of different NPs (Al₂O₃, TiO₂, CuO, MWCNT, SWCNT, ZnO, SiO, SiO₂, SiC, etc.) assisted nanofluid in these hybrid systems with design modifications for the performance and thermo-exergo-enviro-economic analysis. Daily productivity of different designs of solar stills using nanofluids is presented in Table 1.

Table 1.

Previous research work on solar still's productivity improvement using water-based nanofluids.

References	Modification in the passive/active solar still	Productivity (kg/m²/h)
Kabeel et al.³⁴	Passive SSSS with Al₂O₃ NPs and external condenser	4.84 with Al₂O₃ and vacuum
Arora et al.³⁵	Photovoltaic thermal compound parabolic concentrator (PVT-CPC) coupled solar still equipped with HE using SWCNTs and MWCNTs–water nanofluids	Total annual yield of 11.8 and 9.15, respectively, with SWCNT and MWCNT.
Elango et al.³⁶	Single basin SSSS with Al₂O₃, ZnO, and Fe₂O₃ NPs	0.935 with Al₂O₃ 0.805 with Fe₂O₃ 0.750 with ZnO
Sadhegi and Nazari³⁷	Thermoelectric-based solar still integrated with an ETC utilizing an antibacterial-magnetic hybrid nanofluid	5.34 with Ag-Fe₃O₄/deionized water
Omara³⁸	Corrugated wick solar still providing vacuum, CuO, and Al₂O₃ NPs	1.185 with CuO, 0.876 with Al₂O₃
Shashir et al.³⁹	Passive solar still with graphite and CuO NPs; and with different cooling flow rates over the glass cover	0.211 with CuO 0.228 with graphite
Shoeibi et al.⁴⁰	Improving the thermoelectric solar still performance by using nanofluids: experimental and thermal modeling	Productivity of solar still with the thermoelectric cooling and heating using Al₂O₃, TiO₂, CuO and MWCNT nanofluids were improved by 1.6, 1.43, 1.11, and 0.932, respectively.
Addelaziz et al.⁴¹	Performance enhancement of tubular solar still using nano-enhanced energy storage material integrated with v-corrugated aluminum basin, wick, and nanofluid.	5.92 using Carbon black nanofluid.
Mahian et al.⁴²	Active solar still operating with HE; and CuO and SiO₂ NPs.	2.93 with CuO
Singh et al.⁴³	Enhancing upgraded solar still performance in summer and winter through nanofluid-based solar collectors	2.05 with nanofluid-based volumetrically absorbing solar collector; and 4.62 with solar pond
Sahota et al.⁴⁴	System (A): N-PVT-FPC-DSSS without HE and CuO, Al₂O₃, and TiO₂ NPs.	CuO—3.96; Al₂O₃—3.82; TiO₂—3.74 for System A
Sahota et al.⁴⁴	System (B): N-PVT-FPC-DSSS with heat helically coiled exchanger and CuO, Al₂O₃, and TiO₂ NPs.	CuO—3.25; Al₂O₃—3.08; TiO₂—2.86 for System B
Present work	N-ETCs integrated modified solar distiller for water/electricity co-generation using CQD nanoparticle	CO₂ mitigation, energy matrices and performance (potable water/electrical energy) using CQD NPs.

In normal passive or active or hybrid solar distillation system, condensation process takes place on the inner surface of the roof-top glass cover but raises its temperature; and lower down the potable water production as mentioned earlier. In present system, modifications have been made by replacing the roof-top glazed cover of SSSS chamber with the semitransparent PV module; and a separate built-in-passive condenser have been fitted on the rear wall of the SSSS (non-exposed to solar light). Also, a D.C. fan is connected at the top corner of the SSSS to suck and transfer water vapor's from solar still chamber to the built-in-passive condenser section shown. In the proposed system, the efficient heat transfer unit, ETC is integrated to the solar still section via HE, which is used for proper circulation of CQD-water-based nanofluids. The effect and the use of β_c on the system performance is discussed in detail in the next section. In general, the proposed system is N-evacuated tubular collector (N-ETC) integrated single slope solar distillation system having roof-top semitransparent PV module equipped with HCHE and built-in-passive copper condenser (circulation mode) using CQDs water-based nanofluids. Mathematical modeling has been developed to analyze the detailed performance and energy/exergy-based enviro-economic analysis; and the system is tested as a function of design, packing factor of PV module, nanofluid concentration, and climatic parameters valid under any circumstances. Numerical computation is executed for the climatic parameters of New Delhi, India, to evaluate daily productivity, thermal performance, heat transfer characteristics, the thermo-physical characteristics, overall electrical energy; and overall thermal energy and exergy outputs of the system. The analysis have been carried out for (1) CQD-NPs volume concentration ( $φ =$ 1% to 5%); (2) basin fluid (saline water) mass ( $M_{f}$ = 11 kg), (3) mass flow rate, $\dot{m}$ = 0.04 kg/s, (4) $N = 4$ number of external collectors (ETC), and (5) packing factor, (β_c= 0% to 95%) for the New Delhi weather conditions. Moreover, CO₂ mitigation and energy matrices (energy payback time (EPBT), energy production factor (EPF), and life cycle conversion efficiency (LCCE)) have been studied for n = 5 to n = 50 year lifespan of the system. Effects of β_c have been tested to make the proposed system (self-sustained two-in-one output) more viable and efficient to get both optimum productivity (daily yield) and electrical energy generation. From the analysis, comparative study has been reported for the conventional double glazed SSSS considering β_c equal to zero in the same model.

System description and design modification

In the proposed system (Figure 1), series connected N-ETC-fluid collectors $(1.25 m \times 0.55 m)$ are inclined at an angle of 45⁰ with south-facing with specific coordinates (latitude 28°35′ N, longitude 77°12′ E, altitude 216 m) in order to trap maximum solar intensity on its surface shown in Figure 1. Outlet of the ETC which is acting as a water heater is connected to the solar still section via HE; and the hot fluid is circulated through insulating pipes. Details of ETC components are depicted in Figure 1(d). Mechanical fluid pump powered by a D.C. motor, is used for the fluid circulation in this process as shown in Figure 1. Roof-top semitransparent PV module with different β_c is shown in Figure 1(b). Moreover, side view of the semitransparent PV module having solar cells sandwiched between two glass covers is depicted in Figure 1 (c). HCHE is properly dipped in the saline water to utilize its complete heat transfer in the solar still section. Figure 1 (e) shows the schematic view of the HCHE and passive copper condenser.

Figure 1.

(a) N-evacuated tubular collector (N-ETC)-integrated SSSS and in-built-passive condenser (N-ETC-SSSS-PC) via HCHE. (b) View of semitransparent PV module with different packing factor (β_c). (c) Side view of the semitransparent PV module. (d) Labeling of different components of ETC.⁴⁵ (e) Schematic view of (a) HCHE (HCHE) and (b) passive copper condenser.

As we know, during the condensation process, vapors lose their latent heat of vaporization and gets condensed at the inner surface of the semitransparent PV module. It raises the inner surface temperature and ultimately reduces the final productivity (potable water) of the system which is due to the fact that productivity or yield directly depend on the temperature difference between the stored water surface (saline water) and the inner surface condensing cover, which affects the evaporation rate. Keeping in mind about this, present system is further modified and two condensing surfaces in the present system have been involved, viz. (i) roof-top semitransparent PV module of area $1.05 m \times 0.65 m$ inclined at 30° (south-facing) and (ii) copper built-in-passive condenser of area $1.5 m \times 0. 25 m$ connected on the outer side's rear wall of the solar still (area = $1.0 m \times 0.6 m$ ) to keep it unexposed from the solar radiation to maintain its low temperature. The condensation will be more dominant and higher in the copper condenser section rather than the inner glass surface connecting channel. Present system work under the circulation mode; therefore, one D.C. fan (2 V, 1 A) is also connected at the top of the condenser and roof-top semitransparent PV module inside the solar still chamber which helps to transfer the vapors to the integrated copper condenser. Portion of the generated electrical energy of this roof-top PV module is used to run a D.C. fan. Packing factor (β_c) of the roof-top semitransparent PV module play a key role to decide the output of the present system. Zero value of β_c corresponds to the double gazing of the roof-top module and produces no electricity. This condition may provide maximum potable water output by providing the minimum possible electrical energy to run the D.C. fan and mechanical water pump for the circulation of fluid (NF/BF). This can be done by adding an external PV-module to the N-ETCs but it increases the cost and area of the system. Therefore, minimum value of β_c must be required to run the D.C. fan and mechanical water pump for the proper operation of the proposed system. It clearly conveys that both electrical energy generation and potable water outputs are β_c dependent, and these can be controlled to full-fill daily needs commercially by adjusting this key parameter. Accounting β_c of the semitransparent PV module, transmission of the incident solar radiation takes place through its non-packing area and the rest is converted into electricity. Moreover, the generated electrical energy is utilized to run a D.C. fan and mechanical water pump. Leftover electrical energy can be stored or utilized in another household applications using inverter, charge controller and batteries.

Opaque (solar cell) and transparent (double glazing) parts of roof-top semitransparent PV module partially reflects the incident solar radiation; and major portion of it reaches the solar still chamber and absorbed direct by the saline water in SSSS section. Also, it is absorbed by the nanofluid flowing (circulation mode) in the HCHE section; and blackened surface (thermal storage). The circulation nanofluid releases its heat to saline water available in SSSS section and raises its temperature significantly. Apart from the direct absorption of solar radiation in SSSS section, blackened surface also transfers its stored thermal energy and contribute to raise saline water temperature. Hence, the evaporation mechanism is progressed through this mechanism in the proposed system and significantly improves its heat transfer rate in solar still chamber. With modification in the proposed system, role of heat and mass transfer sink is played by additional built-in-passive condenser and D.C. fan continuously sucks water vapor from the solar still chamber and transfer to the condenser section for the condensation process. Major portion of the condensation takes place in the condenser chamber eventually collected in the measuring jar under gravity. Operation and maintenance of HCHE and built-in-passive condenser in the proposed system is easy and it do not any complexity. HE is found to be more effective than straight tube HE in the literature, resulting in a higher heat transfer rate of tubular surface. Necessity of the HE is for the use of nanofluid or other fluids except water only; because NPs can be extracted easily form the basefluid after its use and it can be effectively used without its loss during circulation. Heat from the circulated CQD-water-based nanofluid is transferred to the saline water via HE.

Although present system without operating HE has higher efficiency (direct thermal energy transfer to SSSS chamber) but it is not feasible for the case of using NPs because of NPs sedimentation, and cluster formation results their inappropriate circulation in solar still section which in turn creates their low chances of recovery from the basefluid. These issues can be resolved with the help of some separation nano sized particles-technologies which can be predicated on the NPs/size, base fluid's type, volume fraction, and thermal/optical properties, etc. Energy storage plate and saline water of solar still section directly absorbs the major portion of the incident solar radiation. Eventually, basin thermal plate, direct solar absorption, external thermal energy transfer (ETC), ultrafast thermophysical properties of CQDs, HE transfer rate all works together to raise the temperature of the saline water in the basin. After evaporation and condensation process, major portion of potable water is collected at the bottom of a built-in-passive condenser; also, some portion of it is collected at the lower end output of the SPV module through a channel/pipe as shown in Figure 1. Moreover, Table 2 lists the specifications for the proposed system's solar still and other sections.

Table 2.

Different fixed parameters used in computation.

Parameter	Numerical value	Parameter	Numerical value
$α_{g}$	$0.05$	$h_{i}$	$5.7 (W / m^{2} - K)$
$α_{b}$	$0.8$	$h_{i}^{'}$	$5.8 (W / m^{2} - K)$
$α_{B F}$	$0.6$	$h_{0}$	$9.5 (W / m^{2} - K)$
$α_{c}$	$0.9$	$h_{p f}$	$100 (W / m^{2} - K)$
$α_{p}$	$0.80$	$U_{t c, p}$	$5.58 (W / m^{2} - K)$
$β_{c}$	$0.67$	$U_{t c, a}$	$9.20 (W / m^{2} - K)$
$\in_{g}$	0.95	$U_{t p, a}$	$4.74 (W / m^{2} - K)$
$\in_{b f}$	0.95	$U_{L, m}$	$7.58. (W / m^{2} - K)$
$σ$	$5 .67 times 1 0^{- 8} (W / m^{2} K^{4})$	$U_{L, c}$	$4.71 (W / m^{2} - K)$
$τ_{g}$	$0.95$	$U_{L 1}$	$3.47 (W / m^{2} - K)$
${\dot{m}}_{f}$	0.012 $(kg / s)$	$P F_{1}$	$0.378$
$F_{r c}$	$0.869 m^{2}$	$P F_{2}$	$0.934$
$F_{r m}$	$0.811 m^{2}$	$P F_{c}$	$0.955$
$F F$	0.8	$N$	$4$
$K_{p}$	$6.04 (W / m \circ C)$	$η_{0}$	$0.15$
$K_{g}$	$0.816 (W / m \circ C)$	$X$	$0.33 m$
$K_{B}$	$0.035 (W / m \circ C)$	$d_{p}$	$5 nm$
$K_{i}$	$0.166 (W / m \circ C)$	$F^{'}$	$0.968$
$L_{i}$	$0.100 (W / m \circ C)$	$β_{0}$	$0.0045 / K$
$L_{g}$	0.0035 (m)	$L_{p}$	$0.002 m$
$L_{b}$	$0.005 m$

Dimensions of the SSSS/passive condenser		Constants	Numerical value
$A_{b}$	$1.0 m \times 0.6 m$	$C_{w}$	$4188 (J / kg \circ C)$
$A_{c o n d}$	$1.5 m \times 0. 25 m$	$L_{c o n d}$	$0.05 m$
$n$	$36$	$M_{w}$	$11 kg$
$N$	$1100 rpm$	${\dot{m}}_{v}$	$0.001 kg / s$
$I_{s c}$	$6.31 A$	$K_{c o n d}$	$210 (W / m \circ C)$
$V_{o c}$	$21.40 V$	$P_{f a n}$	$12 W$
$P_{m a x}$	$100 W_{p}$	$θ$	$30^{0}$

$Collectors (tube in tube type)$
Parameter	Numerical value	Parameter	Numerical value
Tube material	$C o p p e r t u b e s$	Collector efficiency factor	$0.968$
Inner tube diameter	$0.0250 m$	Angle of collectors	$45 \circ$
Tube thickness	$0.0005 m$	Riser-Outer Diameter	$0.0127 m$
Outer radius of the coaxial evacuated glass tube		Motor used for the water pump	$D C s h u n t m o t o r$ $(12 V, 24 W and 2800 rpm)$
Inner radius of the coaxial evacuated glass tube	$0.0165 m$	Effective area of ETC	$2 \times 1.5 m^{2}$
Thickness of the coaxial evacuated glass tube	$0.002 m$	Spacing between two risers	$0.112 m$
Inclination angle of ETC	45°	Riser thickness	$0.56 \times 10^{- 3} m$
Weight of the collector	48 kg
$Semitransparent PV module (under standard test conditions)$
Size of PV module	$1.05 m \times 0.66 m$	Fill factor	$0.85$
Packing factor	$0.67$	Efficiency of the module	$12 %$
Max power rating P_max	$40 W$
Helical heat exchanger
Length of the HE	$1.937 m$	Diameter of the coil	$0.045 m$
Diameter of the coil tube	$0.0125 m$	Number of turns	24

Mathematical modeling

Following assumptions have been made to study the performance of the proposed:

Quasi-steady state is maintained on every hour of the day.

All heat exchange points follow the Fourier's law of heat flux.

The quoted values of thermos-physical characteristics through aid of numerical computation have been calculated averaging over every hour.

No radiation exchange occurs in the second condenser.

Proposed system is leakage free.

Energy balance equations of different components of the proposed system:

Roof-top semitransparent PV module of the SSSS section (first condensing cover)

α_{c} τ_{g} β_{c} I (t) A_{m} = U_{t c, a} (T_{c} - T_{a}) A_{m} + U_{b c, w} (T_{c} - T_{w}) A_{m} + η_{c} τ_{g} β_{c} I (t) A_{m}

(1)

Solving the above equation, $T_{c}$ can be obtained as

T_{c} = \frac{α_{c} τ_{g} β_{c} I (t) A_{m} - η_{c} τ_{g} β_{c} I (t) A_{m} + A_{m} (U_{t c, a} T_{a} + U_{b c, w} T_{w})}{A_{m} (U_{t c, a} + U_{b c, w})}

(2)

where,

U_{t c, a} = {[\frac{1}{h_{o}} + \frac{L_{g}}{K_{g}} + \frac{L_{s c}}{K_{s c}} + \frac{L_{g}}{K_{g}}]}^{- 1}

, an overall HTC from the inner condensing cover to ambient air through solar cell material and top glass cover of semitransparent PV module. Also, for small inclination of SPV module,

A_{m} \approx A_{b}

Blackened surface of the SSSS section

(1 - α_{w}) α_{b} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} = h_{b w} (T_{b} - T_{w}) A_{b} + U_{b a} (T_{b} - T_{a}) A_{e f f}

(3)

with

A_{e f f} = \frac{(A_{b} + A_{s})}{A_{b}} > 1

depending upon the water depth in the basin of SSSS.

Solving above equation, the basin temperature $(T_{b})$ is

T_{b} = \frac{(1 - α_{w}) α_{b} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} + h_{b w} T_{w} A_{b} + U_{b a} T_{a} A_{b}}{A_{b} (h_{b w} + U_{b a})} .

(4)

Basin water of the SSSS section

h_{b w} (T_{b} - T_{w}) A_{b} + α_{w} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} + {\dot{Q}}_{u N} = h_{1} (T_{w} - T_{c}) A_{m} + (M_{w} C_{w}) \frac{d T_{w}}{d t} + (U A)_{S L} (T_{w} - T_{a}) A_{s} + {\dot{m}}_{f} c_{f} (T_{w} - T_{c o n d})

(5)

Here, the value of ${\dot{Q}}_{u N}$ , rate of heat transfer from the outlet of $N^{t h}$ ETC point is expressed as,

{\dot{Q}}_{u N} = {\dot{m}}_{f} C_{f} (T_{F o N} - T_{f i})

(6)

where $T_{f o N}$ from the $N^{t h}$ ETC expressed as³²

T_{f o N} = [\frac{{(A F_{R} α τ)}_{1}}{{\dot{m}}_{f} C_{f}}] [\frac{1 - K_{K}^{N}}{1 - K_{K}}] I (t) + [\frac{{(A F_{R} U_{L})}_{1}}{{\dot{m}}_{f} C_{f}}] [\frac{1 - K_{K}^{N}}{1 - K_{K}}] T_{a} + K_{K}^{N} T_{f i}

(7)

Unknown terms are given in the Appendix.

Helical HE immersed in basin water of the SSSS section

{\dot{m}}_{f} C_{f} \frac{d T_{f}}{d x} d x = - (2 π r_{11} U) (T_{H E} - T_{f}) d

(8)

Boundary conditions (BCs): $T_{f} (x = 0) = T_{F o N} and T_{f} (x = L) = T_{f i}$ .

Solving Eq. (4) using above BCs,

T_{f i} = T_{f} [1 - \exp (- \frac{2 π r_{11} U L}{{\dot{m}}_{f} C_{f}})] + T_{F o N} \exp (- \frac{2 π r_{11} U L}{{\dot{m}}_{f} C_{f}})

(9)

where,

U = {[\frac{1}{h_{b f}} + (\frac{r_{11}}{K_{1}}) \log (\frac{r_{22}}{K_{1}}) + (\frac{r_{11}}{r_{22}}) (\frac{1}{h_{b f}})]}^{- 1}

Substituting $T_{f o N}$ from Eq. (5) and $T_{f i}$ from Eq. (7) in Eq. (4) to solve ${\dot{Q}}_{u N}$ .

\begin{aligned} {\dot{Q}}_{u N} = & {\dot{m}}_{f} C_{f} [([\frac{{(A F_{R} α τ)}_{1}}{{\dot{m}}_{f} C_{f}}] [\frac{1 - K_{K}^{N}}{1 - K_{K}}] I (t) + [\frac{{(A F_{R} U_{L})}_{1}}{{\dot{m}}_{f} C_{f}}] [\frac{1 - K_{K}^{N}}{1 - K_{K}}] T_{a} + K_{K}^{N} T_{f i}) \\ - (T_{f} [1 - e x p (- \frac{2 π r_{11} U L}{{\dot{m}}_{f} C_{f}})] + T_{F o N} e x p (- \frac{2 π r_{11} U L}{{\dot{m}}_{f} C_{f}}))] \end{aligned}

(10)

Built-in-passive condenser (second condensing cover)

{\dot{m}}_{f} c_{f} (T_{w} - T_{c o n d}) = U_{t c o n d, a} (T_{c o n d} - T_{a}) A_{c o n d} + {\dot{m}}_{c o n d} L_{v}

(11)

where

C_{d} = 0.9 < 1

is the coefficient of diffusion depending upon the pressure difference between the two condensing chambers. In the present case, we have considered

C_{d} = 1

to make analysis analytical.

From the above equation, the condenser temperature $(T_{c o n d})$ can be expressed as

T_{c o n d} = \frac{({\dot{m}}_{f} c_{f}) T_{w} - ({\dot{m}}_{c o n d}) L_{v} + A_{c o n d} (U_{t c o n d, a}) T_{a}}{(A_{c o n d} U_{t c o n d, a} + {\dot{m}}_{f} c_{f})}

(12)

On solving Eq. (3) using Eqs. (2), (4), and (12), we get,

\begin{aligned} h_{b w} (\frac{(1 - α_{w}) α_{b} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} + h_{b w} T_{w} A_{b} + U_{b a} T_{a} A_{b}}{A_{b} (h_{b w} + U_{b a})} - T_{w}) A_{b} + α_{w} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} + {\dot{Q}}_{u N} \\ = h_{1} (T_{w} - \frac{α_{c} τ_{g} β_{c} I (t) A_{m} - η_{c} τ_{g} β_{c} I (t) A_{m} + A_{m} (U_{t c, a} T_{a} + U_{b c, w} T_{w})}{A_{m} (U_{t c, a} + U_{b c, w})}) A_{m} + (M_{w} C_{w}) \frac{d T_{w}}{d t} \\ + (U A)_{S L} (T_{w} - T_{a}) A_{s} + {\dot{m}}_{f} c_{f} (T_{w} - \frac{({\dot{m}}_{f} c_{f}) T_{w} - ({\dot{m}}_{c o n d}) L_{v} + A_{c o n d} (U_{t c o n d, a}) T_{a}}{(A_{c o n d} U_{t c o n d, a} + {\dot{m}}_{f} c_{f})}) \end{aligned}

(13)

On solving further by substituting the value of

{\dot{Q}}_{u N}

from Eq. (10), we get

\begin{aligned} \frac{d T_{w}}{d t} & + T_{w} [\frac{h_{1} A_{m}}{M_{w} C_{w}} - \frac{h_{1} A_{m} U_{b c, w}}{M_{w} C_{w} (U_{t c, a} + U_{b c, w})} + \frac{{(U A)}_{S L}}{M_{w} C_{w}} + \frac{m_{f} {\dot{c}}_{f}}{M_{w} C_{w}} - \frac{{(m_{f} {\dot{c}}_{f})}^{2}}{M_{w} C_{w} (A_{c o n d} U_{t c o n d, a} + m_{f} {\dot{c}}_{f})} \\ - \frac{A_{b} {(h_{b w})}^{2}}{M_{w} C_{w} (h_{b w} + U_{b a})} + \frac{h_{b w}}{M_{w} C_{w} (h_{b w} + U_{b a})} + \frac{{(U A)}_{e f f}}{M_{w} C_{w}}] \\ = h_{b w} [\frac{(1 - α_{w}) α_{b} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} + U_{b a} T_{a} A_{b}}{h_{b w} + U_{b a}}] + α_{w} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} + (α τ)_{e f f} I_{c} (t) \\ + (U A)_{e f f} T_{a} + h_{1} [\frac{(α_{c} - η_{c}) τ_{g} β_{c} I (t) A_{m} + A_{m} U_{t c, a} T_{a}}{U_{t c, a} + U_{b c, w}}] \\ + (U A)_{S L} T_{a} A_{S} + m_{f} {\dot{c}}_{f} (\frac{- {\dot{m}}_{c o n d} L_{v} + A_{c o n d} U_{t c o n d, a} T_{a}}{A_{c o n d} U_{t c o n d, a} + m_{f} {\dot{c}}_{f}}) \end{aligned}

(14)

In simplified form, the above equation can be expressed as

\frac{d T_{w}}{d t} + a T_{w} = f (t)

(15a)

where,

a = (\frac{1}{M_{w} C_{w}}) [h_{1} A_{m} - \frac{h_{1} A_{m} U_{b c, w}}{{(A H)}_{1}} + {(U A)}_{S L} + m_{f} {\dot{c}}_{f} - \frac{{(m_{f} {\dot{c}}_{f})}^{2}}{{(A H)}_{2}} - \frac{A_{b} {(h_{b w})}^{2}}{{(A H)}_{3}} + \frac{h_{b w}}{{(A H)}_{3}} + {(U A)}_{e f f}]

and

\begin{aligned} f (t) = & h_{b w} [\frac{(1 - α_{w}) α_{b} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} + U_{b a} T_{a} A_{b}}{{(A H)}_{3}}] \\ + α_{w} τ_{g}^{2} (1 - β_{c}) I (t) A_{m} + (α τ)_{e f f} I_{c} (t) + (U A)_{e f f} T_{a} + h_{1} [\frac{(α_{c} - η_{c}) τ_{g} β_{c} I (t) A_{m} + A_{m} U_{t c, a} T_{a}}{{(A H)}_{1}}] \\ + (U A)_{S L} T_{a} A_{S} + m_{f} {\dot{c}}_{f} (\frac{- {\dot{m}}_{c o n d} L_{v} + A_{c o n d} U_{t c o n d, a} T_{a}}{{(A H)}_{2}}) \end{aligned}

The solution of Eq. (15a) with initial condition of

T_{w} = T_{w 0}

at t = 0 for 0–t time interval becomes,

T_{w} = \frac{\bar{f (t)}}{a} (1 - e^{- a t}) + T_{w 0} e^{- a t}

(15b)

Here, assumptions of average solar radiation,

\bar{I (t)}

, and ambient air temperature,

{\bar{T}}_{a}

have been taken for t-time interval (i.e., every one hour).

The rate of vapor condensation on the inner surface of semitransparent PV module cover (minor contribution) and in-built-passive condenser chamber (major contribution) can be estimated from the following expressions:

{\dot{q}}_{c, e w} = h_{e w_{1}} (T_{w} - T_{c})

(16)

and,

{\dot{q}}_{c o n d, e w} = h_{e w_{2}} (T_{w} - T_{c o n d})

(17)

Expressions of other important time-dependent parameters of the system can be expressed as follows:

The hourly energy and exergy are

E_{t h, e n} = [h_{e f, c} (T_{f} - T_{c i}) + h_{e f, c o n d} (T_{f} - T_{c o n d})] A_{b}

(18)

\begin{aligned} E_{t h, e x} = & {h_{e f, c} [(T_{f} - T_{c i}) - (T_{a} + 273) \ln (\frac{T_{f} + 273}{T_{c i} + 273})] \\ + h_{e f, c o n d} [(T_{f} - T_{c o n d}) - (T_{a} + 273) \ln (\frac{T_{f} + 273}{T_{c o n d} + 273})]} A_{b} \end{aligned}

(19)

The electrical efficiency of the roof-top semitransparent PV module is

η_{m} = τ_{g} β_{c} η_{c}

(20)

The electrical energy of the roof-top semitransparent PV module is

\dot{E} = η_{m} A_{m} I (t)

(21)

The net electrical energy is

{\dot{E}}_{n e t} = \dot{E} - P_{f a n}

(22)

The thermal gain of the system is

{\dot{Q}}_{t h} = {\dot{m}}_{f} c_{f} [(T_{w} - T_{c o n d}) + (T_{w} - T_{c i})]

(23)

The overall thermal energy gain is

{\dot{Q}}_{o v r} = {\dot{Q}}_{t h} + \frac{\dot{E}}{0.38}

(24)

The thermal energy efficiency is

η_{t h} = \frac{{\dot{m}}_{f} c_{f} (T_{w} - T_{c o n d})}{A_{m} I (t)}

(25)

The overall thermal energy efficiency is

η_{o v r} = η_{t h} + \frac{η_{c}}{0.38}

(26)

where 0.38 is known as the conversion factor in a power plant.³²

Furthermore, the rate of condensed water in kg/h is expressed as

{\dot{M}}_{c, e w} = \frac{h_{e w_{1}} (T_{w} - T_{c}) A_{b}}{L_{v}} \times 3, 600

(27)

and

{\dot{M}}_{c o n d, e w} = \frac{h_{e w_{2}} (T_{w} - T_{c o n d}) A_{c o n d}}{L_{v}} \times 3, 600

(28)

Hence, total yield from the proposed solar distillation system is given by

{\dot{M}}_{e w} = {\dot{M}}_{c, e w} + {\dot{M}}_{c o n d, e w}

(29)

where

h_{e w 2} = \frac{0.016 \times h_{c} [P_{w} - P_{c o n d}]}{(T_{w} - T_{c o n d})}

(30)

where the latent heat of vaporization

(L_{v})

is,^32,33

L_{v} = 3.1625 \times 10^{6} + [1 - (7.616 \times 10^{- 4} \times (T_{v}))] for T_{v} > 70 \circ C

L_{v} = 2.4935 \times 10^{6} [1 - (9.4779 \times 10^{- 4} \times (T_{v}) + 1.3132 \times 10^{- 7} \times (T_{v}^{2}) - 4.7974 \times 10^{- 3} \times (T_{v}^{3}))] for T_{v} < 70^{o} C

Hourly variation of all the above-mentioned time-dependent parameters of the system can be obtained using the correlations of thermo-physical properties of vapors (Table 3(a)), basefluid (Table 3(b)), and nanofluid (Table 3(c)–(d)); and the heat transfer relations (Table 4).

Table 3(a).

Thermophysical properties of vapor.^26,27

Quantity	Symbol	Expression
Specific heat	$C_{v}$	$999.2 + 0.1434 \times (T_{v}) + 1.101 \times (T_{v}^{2}) - 6.7581 \times 10^{- 8} \times (T_{v}^{3})$
Density	$ρ_{v}$	$353.44 / (T_{v} + 273.15)$
Thermal conductivity	$k_{v}$	$0.0244 + 0.7673 \times 10^{- 4} \times (T_{v})$
Viscosity	$μ_{v}$	$1.718 \times 10^{- 5} + 4.620 \times 10^{- 8} \times (T_{v})$
Latent heat of vaporization of fluid	$L$	$3.1625 \times 10^{6} + [1 - (7.616 \times 10^{- 4} \times (T_{v}))]; for T_{v} > 70^{\circ} C$
		$2.4935 \times 10^{6} [1 - (9.4779 \times 10^{- 4} \times (T_{v}) + 1.3132 \times 10^{- 7}$ $\times (T_{v}^{2}) - 4.7974 \times 10^{- 3} \times (T_{v}^{3}))]; f o r T_{v} < 70^{\circ} C$
Partial vapor pressure at condensing cover and fluid temperature	P_gi	$P (g i) = e x p [25.317 - (\frac{5144}{T (g i) + 273})]$ $P (f l u i d) = e x p [25.317 - (\frac{5144}{T (f l u i d) + 273})]$
Thermal expansion coefficient	$β_{v}$	$1 / (T_{v} + 273.15)$

Note: where $T_{v} = \frac{(T_{f} + T_{g})}{2}$

Table 3(b).

Thermo-physical properties of the base fluid.^26,27

Quantity	Symbol	Expression
Density	$ρ_{b f}$	$999.79 + 0.0683 \times T_{b f} - 0.0107 \times T_{b f}^{2} + 0.00082 \times T_{b f}^{2.5} - 2.303 \times 10^{- 5} \times T_{b f}^{3}$
Specific heat	$C_{b f}$	$4.217 - 0.00561 \times T_{b f} + 0.00129 \times T_{b f}^{1.5} - 0.000115 \times T_{b f}^{2} + 4.149 \times 10^{- 6} \times T_{b f}^{2.5}$
Viscosity	$μ_{b f}$	$\frac{1}{\begin{matrix} (557.82 - 19.408 \times T_{b f} + 0.136 \times T_{b f}^{2} - 3.116 \times 10^{- 4} \times T_{b f}^{3}) \end{matrix}}$
Thermal conductivity	$k_{b f}$	$0.565 + 0.00263 \times T_{b f} - 0.000125 \times T_{b f}^{1.5} - 1.515 \times 10^{- 6} \times T_{b f}^{2} - 0.000941 \times T_{b f}^{0.5}$

Table 3(c).

Thermo-physical properties of the CQD-water-based nanofluid.

Quantity	Expression
Specific heat²⁸	$C_{n f} = φ_{p} * C_{b f} * \frac{ρ_{p}}{ρ_{n f}} + (1 - φ_{p}) * C_{b f}$
Density²⁸	$ρ_{n f} = (1.199 - 0.005633 * e^{- 0.0947 + φ_{p}^{2}} - 0.1928 * e^{- 0.0947 * φ}) * ρ_{b f}$
Thermal conductivity²⁹	$k_{n f} = 0.9768 - 0.00004797 * T^{2} + 0.03823 * (φ_{p}) + 0.004406 * T * φ_{p}) * k_{b f}$
Viscosity³⁰	$μ_{n f} = μ_{b f} * (1.871 - 0.05077 * T + 0.06839 * φ_{p}^{3} + 0.004406 * T^{2}$ $- 0.00000003126 * T^{4})$

Table 3(d).

Thermo-physical properties of CQDs-NPs and the base fluid (water).

Physical properties	Base fluid (Water)	CQD NPs
Density $(kg / m^{3})$	997( $ρ_{b f}$ )	12300 ( $ρ_{b}$ )
Specific heat $(J / kg - K)$	4179	225 ( $C_{p}$ )
Thermal conductivity $(W / m - K)$	0.613( $K_{b f}$ )	6.0459 ( $K_{p}$ )

Table 4.

Heat transfer coefficients in ETC, HE, and solar still sections.^17,32

HTCs	Relations
Natural convective HTC from the still basin to fluid	Nusselt number: $(N u)_{f} = \frac{h_{b, f} X}{k} = C (R e P r)^{n}$ [Where, C = 0.54 and n = ¼ horizontal plate facing upward]Reynold’s number: $(R e)_{f} = {(\frac{ρ v X}{μ})}_{f}$ ; Prandtl number: $(P r)_{f} = {(\frac{μ C_{p}}{k})}_{f}$ Rayleigh number: $(R a)_{f} = (R e P r)_{f} = {[\frac{ρ v X C_{p}}{k}]}_{f}$
Internal HTC from the fluid surface to inner surface of the glass cover	From the Cooper and Dunkle model,Evaporative HTC; $h_{e v, f} = (0.016273) h_{c, f} [\frac{P_{f} - P_{g i}}{T_{f} - T_{g i}}]$ Convective HTC: $h_{c, f} = (0.844) (Δ T)^{1 / 3}$ where $P_{x} = e x p [25.317 - (\frac{5144}{T_{x} + 273})]$ ; $Δ T = (T_{f} - T_{g i}) + [\frac{(P_{f} - P_{g i}) (T_{f} + 273)}{2.689 \times 10^{5} - P_{f}}]$ Radiative HTC $h_{r, f} = \in_{e f f} σ [{(T_{f} + 273)}^{2} + {(T_{g i} + 273)}^{2}] [T_{f} + T_{g i} + 546]$ where; $\frac{1}{\in_{e f f}} = \frac{1}{\in_{w}} + \frac{1}{\in_{g}} - 1$
Within ETC	In case of the base fluid (water) $N u = 1.75 {(\frac{μ_{b f}}{μ_{b f}^{b}})}^{0.14} [G z_{m} + 0.0083 {(G r_{m} P r_{m})}^{0.75}]^{1 / 3}$ Arithmetic mean of the Graetz number: $G z_{m} = \frac{{\dot{m}}_{r} C_{b f}}{K_{b f} L}$ ;Arithmetic mean of the Grashof number: $G r_{m} = \frac{g D^{2} Δ T}{μ_{b f}^{b}}$ where $T = bulk temperature difference$ ; $D =$ tube diameter; L = length of the heated section of the tube.In case of the nanofluid $h_{E T C} = (N u)_{n f} \frac{k_{n f}}{D_{i}}$ ; $(N u)_{n f} = \frac{(\frac{f}{8}) ({(R e)}_{n f} - 10^{3}) {(P r)}_{n f}}{1 + 12.7 \sqrt{(\frac{f}{8})} ({(P r)}^{2 / 3} - 1)}$ for $3 \times 10^{3} \leq (R e)_{n f} \leq 5 \times 10^{5}$ and $0.55 \leq (P r)_{n f} \leq 2 \times 10^{3}$ $(R e)_{n f} = \frac{4 {\dot{m}}_{r}}{π D_{i} μ_{n f}}$ ; $(P r)_{n f} = \frac{μ_{n f} C_{n f}}{k_{n f}}$ ${\dot{m}}_{r} =$ mass flow rate in any riser and $f =$ Darcy friction factor.Petukhov correlation for smooth tubes $f = [0.79 \ln {(R e)}_{n f} - 1.64]^{- 2}$ Colebrook correlation for roughness of the $\frac{1}{\sqrt{f}} = - 2 l o g (\frac{\frac{\in}{D_{i}}}{3.7}) + \frac{2.51}{{(R e)}_{n f} \sqrt{f}}$ for $4 \times 10^{3} \leq (R e)_{n f} \leq 10^{5}$ and $0 < \frac{\in}{D_{i}} < 0.05$ (relative roughness)
Within the HE	In case of the base fluid (water) $(N u)_{n f} = (2.153 + 0.318 {(D e)}^{0.643}) P r^{0.177}$ For $20 < D e < 2 \times 10^{3}$ and $0.7 < P r < 200$ Dean’s number: $(D e)_{n f} = (R e)_{n f} \sqrt{\frac{d_{i}}{d_{c}}}$ ; Reynold’s number; $(R e)_{n f} = \frac{4 {\dot{m}}_{r}}{π d_{i} μ_{n f}}$ $d_{c} = coil diameter$ ; $d_{i} = r_{11} = Inner tube diameter$ In case of the nanofluid $(N u)_{n f} = 3.67 (D e)^{0.67} δ^{0.009} φ^{1.004}$ $h_{n f} = \frac{{(N u)}_{n f} k_{e f f}}{d_{i}}$ ;

Energy matrices and CO₂ mitigation (environmental cost)

For any renewable energy-based system design, energy matrices, viz., EPBT, EPF, and LCCE; and CO₂ mitigation analysis are important. Apart from the annual energy/exergy generated by the system, these parameters depend on the EE or energy densities of all the internal and external components used for the system design. It is the processing energy required to make the final component during manufacturing; and represent the equivalency of carbon emissions in kilograms per volume of material (kg-CO₂/m³). The EE of all the components used for the design of the proposed system is listed in Table 5. It majorly controls the values of the energy matrices and CO₂ mitigation. In general, EPBT is used as a basic criterion to check the viability of the system. Conclusively, low production cost of potable water and electrical energy generation; the use of low-cost materials with their longer durability; low EE values of used components; and low annual maintenance can effectively lower down the EPBT value.

Table 5.

Embodied energy of different components of the proposed system.

Name of component	Embodied energy, EE $(kWh)$
FRP body of SSSS	$511.44$
GI angle iron	$350.80$
Double-glazed glass cover	$350.80$
Copper HE	$18.31$
EE of CQD-NPs (Average)	$91.82$
EE of the double-glazed passive system ( ${\dot{Q}}_{u N} = 0, β_{c} = 0$ )
(i) With CQD-NPs	$1, 451.38$
(ii) Without CQD-NPs	$1, 359.56$
EE of the hybrid system ( ${\dot{Q}}_{u N} 0) f o r d i f f e r e n t β_{c}$
EPC $(N = 4)$	$1, 593.31$
D.C. mechanical water pump	$252.23$
Insulating pipes	$113.31$
Charge controller	$61.55$
Storage battery	$313.78$
Fluid flow meters $(n = 2)$	$221.97$
Nanofluid steel tank	$89.33$
Water storage plastic tank (250 L capacity)	$103.41$
For different values of the packing factor	$β_{c} = 0.67$	$β_{c} = 0.75$	$β_{c} = 0.85$	$β_{c} = 0.95$
Semitransparent PV (glass –glass)	$801.41$	$980.87$	$1, 043.85$	$1, 145.85$
EE energy of the hybrid system with CQD-NPs	$5, 001.68$	$5, 181.14$	$5, 250.12$	$5, 352.44$
EE energy of the hybrid system without CQD-NPs	$4, 909.86$	$5, 089.32$	$5, 160.3$	$5, 260.62$

Mathematically,

Energy payback time (EPBT)_{en / ex} = \frac{Embodied energy / exergy (E_{in})}{Annual energy / exergy out (E_{out, ann})} years

(31)

Next important parameter of energy matrices is the EPF. It is opposite to the EPBT and determines overall system/design performance based on the first law of thermodynamics.

Mathematically,

Energy production factor (E P F)_{en / ex} = {[\frac{Embodied energy / exergy in (E_{in})}{Annual energy / exergy out (E_{out, ann})}]}^{- 1}

(32)

Another important parameter of energy matrices is the LCCE. It is the net energy produced by the system w.r.t the inputs received (solar energy) during its entire life-span (n-years) in working mode. LCCE never be higher than unity; if it happens, then, the system design is said to be the best.

Mathematically,

Life cycle conversion efficiency (LCCE)_{en / ex} = \frac{(E_{en / ex, ann} \times n) - E_{in}}{E_{sol, ann} \times n}

(33)

where,

E_{en / ex, ann}

is the annual solar energy/exergy output,

E_{sol, ann}

is the annual solar energy retrieved by the system.

Moreover, control of CO₂ emission and conservation of our conventional sources of energy is the global concern for environmental sustainability. Many international bodies are working on the water–energy nexus for their cleaner production. Enviro-economic analysis is to compute the amount of CO₂ mitigation of renewable energy-based systems to maximize their use and commercialization. Considering transmission $(20 %)$ and distribution losses $(40 %)$ , the amount of ${CO}_{2}$ emitted per $kWh$ comes out to be $2.0 kg$ .³³ Mathematically, the environmental cost (carbon credits—CCs) and the amount of ${CO}_{2}$ mitigated per annum can be estimated from the following expressions:^26,27

Carbon credits earned (Z_{{CO}_{2}}) = φ_{{CO}_{2}} \times z_{{CO}_{2}} $

(34)

Energy based on the amount of

{CO}_{2}

mitigated per annum is given by

(φ_{{CO}_{2}}) = \frac{(\frac{ψ_{{CO}_{2}}}{0.38}) \times E_{e n, a n n}}{10^{3}}

(35a)

Exergy based on the amount of

C O_{2}

mitigated per annum is given by

(φ_{{CO}_{2}}) = \frac{ψ_{{CO}_{2}} \times E_{e x, a n n}}{10^{3}}

(35b)

where

ψ_{{CO}_{2}}

is the average

{CO}_{2}

equivalent intensity for electricity generation from coal (

2.04 kg C O_{2} / kWh

); and the price of one tone of

C O_{2} (z_{C O_{2}})

is equal to $

14.5

.³² Roof-top semitransparent PV module generates electrical energy and therefore, the factor 0.38 is used to covert it into the equivalent thermal energy as mentioned above. Exergo-economic analysis help to figure out other alternative options to find best methods/technologies to further improve the system design and performance.

Methodology

N-ETC integrated SSSS with two major modifications, viz. (i) built-in-passive condenser on the rear side of the still and (ii) roof-top-semitransparent PV module is analyzed using CQD-water-based nanofluid ( $φ_{p} = 3 %$ ). Research work have been carried out to check out the performance and enviro-economic analysis of the proposed system for the New Delhi weather conditions for the month of May for $N = 4$ number of collectors, $M_{f} = 11 kg$ solar still's saline water mass, ${\dot{m}}_{f} = 0.04 kg / s$ mass flow rate. Following steps have been taken into consideration to execute the developed thermal model of the proposed system with the help of MATLAB2022b.

Step (i)

Using raw data of global and diffused solar radiations available on India Metallurgical Department, Pune website, solar intensity falling at a particular angle for chosen geographical location (New Delhi) for a specific month (May) and day (c-type weather condition) is obtained from a separate MATLAB022b code.

Step (ii)

Initially, thermo-physical properties (thermal conductivity, specific heat, density, and viscosity) of the base fluid (Table (3a) and (3b)) and nanofluid (Table (3c) and (3d)); and all internal-external HTCs (Table 4), have been estimated every hour with iteration using known values of time dependent parameters.

Step (iii)

Initial values of fluid (BF/NF) temperature of all different sections, viz. HE, SSSS section, N-ETC, built-in-passive condenser, semitransparent roof-top, and blackened surface have been taken nearly equal to the ambient temperature

(T_{a})

to execute the 24 h. iterations in MATLAB code. At the end, the final BF/NF is calculated from Eq.

T_{f}

[Eq. (15b)].

Step (iv)

The instantaneous values of temperature of the fluid (Eq. (15b)), roof-top semitransparent PV module (Eq. (2)), ETC's N^th outlet (Eq. (7)) and built-in-passive condenser (Eq. (12)) have been evaluated. All these time dependent parameters are used to estimate other useful performance parameters, i.e., thermal energy (Eq. (18)), exergy (Eq. (19)), roof-top semitransparent PV module efficiency (Eq. (20)), overall thermal energy efficiency (Eq. (25)), and overall thermal exergy efficiency (Eq. (26)), and daily yield (Eq. (29)).

Step (v)

Using above analysis (steps (i)–(iv)) Energy and exergy-based enviro-economic analysis have been carried to estimate the annual CO₂ mitigation (Eq. (35a) and (35b)), and carbon-credits (CCs) (Eq. (34)) earned from the proposed system. Moreover, Energy matrices, viz. EPF (Eq. (31)), EPBT (Eq. (32)), and LCCE (Eq. (33)) are estimated for every 5 years of lifespan of the proposed system up to 50 years.

Flow chart and logic diagram for the MATLAB code execution is described below:

Results

Based on the analytical analysis, CO₂ mitigation, thermal characteristics, and performance of N-ETC integrated single slope solar distillations system is analyzed for the New Delhi weather conditions of the month May. As discussed in the system description section, single layer 3 mm roof-top toughen glass is replaced by semitransparent photovoltaic module (SPV) and passive copper condenser is fitted on the side rear wall of the system. One DC fan (6–12 V) is also fitted at the junction of SPV module and copper condenser. Internally the system is operated in circulation mode to get high evaporation rate in the condensing chamber. Figure 2 presents the hourly variation of solar radiation, and ambient temperature of the month May. Particularly, c-type weather condition includes twelve number of clear sunshine days, and this data is used to execute the analysis. Before analyzing the system efficiency and performance, thermo-physical characteristics (thermal conductivity, viscosity, density, and specific heat) of the system with and without using CQD-water-based nanofluid is tested. Figure 3 presents the hourly variation of all four mentioned thermo-physical characteristics and expected trends have been observed but with significant improvements using CQDs at their fixed volume concentration (φ= 2.5%). Thermal conductivity and specific heat are enhanced by 56.06% and 1.02%, respectively, during sunshine hours. On the other hand, significant plunge around 1.22% and 85.03% in density and viscosity, respectively, have been observed using CQDs. Both the density and viscosity trends show maintained difference with and without using CQD-water-based nanofluid after off-sunshine hours and sunset, which intern helps the saline water to continuously sustain the internal convective (basin liner to fluid) evaporation rate for longer period. Moreover, thermal conductivity plays the key role among all thermo-physical properties; and it shows huge jump using ultrafast CQDs in water-based nanofluid. Eventually, external integration of N-ETCs, basin liner, and better heat transfer thermal properties of CQDs (via HE) significantly raises the saline water temperature. Moreover, significant enhancement in thermo-physical characteristics is credited to the better absorption mechanism of assisting CQD-NPs due to maximum overlapping of its optical spectrum with the solar radiation spectrum. Figure 4 shows the variation of maximum values of thermo-physical characteristics of the nanofluid with CQD-NPs volume concentration up to 5%. It has been noted that density, thermal conductivity, and viscosity increases; and specific heat decreases sharply with increase in concentration of CQD-NPs; and fixed water mass and mass flow rate in the circulation pipes connected with external integration and HE restricts the improvement in thermophysical characteristics beyond fixed volume concentration of CQD NP-water-based nanofluids.

Figure 2.

Hourly variation of the total radiation and ambient temperature of the New Delhi weather conditions of the month of May (Official data, IMD, Pune, India).

Figure 3.

Hourly variation of TPPs of the basefluid and CQDs-water-based nanofluid (φ =2.5%).

Figure 4.

Effect of volume-fraction of CQD NPs on TPPs of the respective nanofluid.

As discussed above, ultrafast heat transfer properties of CQD-water-based nanofluid directly accelerate the convective and evaporative heat transfer rates; and it is clearly depicted in Figure 5. Hourly variation of internal convective heat transfer coefficient (HTC) taken place between the horizontal blackened plate and saline water; and evaporative HTC is shown in Figure 5(a) and (b), respectively. Sharp improvement around 39.2% and 112.04% in convective and evaporative HTCs, respectively, have been observed, thanks to thermo-physical properties of CQDs-water-based nanofluids. Surface plasmon resonance (SPR) is the manifestation of resonance effect which is due to the oscillation of free electrons in the conduction band and interaction with photons (light). The interaction relies on the size/shape of the metal NPs as well as on the nature/composition of the dispersion medium. The SPR effectively alters the thermo-physical characteristics of the water-based nanofluid properties. As the size of CQD-NPs is extremely lower, they do not settle down (non-sedimentation) due to its Brownian motion in the fluid. The energy of vibrations of these CQD-NPs gets dissipated in the form of heat to its surroundings and effectively modify the heat transfer rates. Moreover, change in packing factor (β_c) of the roof-top semitransparent PV module effectively alters the heat convection and evaporation rates as shown in Figures 6 and 7 with and without using CQD-NPs, respectively. Lower β_c allows high solar radiation to enter in the solar still cavity and raises the convective and evaporative heat transfer rates but it lowers the electrical energy generation output. Therefore, it is necessary to select an optimum value of the β_c in order to maintain the required minimum value of electrical energy to run the mechanical water pump and D.C.-fan. Range of maximum values of convective HTC around 86.3–71.3 W/m²-K and 62.58–61.2 W/m²-K is observed with and without using CQD-NPs, respectively, for β_c variation (0.67, 0.69, 0.75, 0.85, and 0.95). On the other hand, for evaporative HTC, it is around 58.1–9.12 W/m²-K and 32.91–6.11 W/m²-K with and without using CQD-NPs, respectively, for the variation of β_c of 0.67–0.95. The use of CQD-NPs showed impressive enhancement in evaporative (37.9%) and convective (76.94%) HTCs even at moderate value of β_c (0.67) and sharply decreases with increase in β_c which is due to maximum blockage of incident solar radiation by the semitransparent solar cell. ETCs are the best to use for solar water heaters, found in literature. Entropy generation mechanism is lower down inside the external integration (ETC) at high volume concentration of NPs as well as high mass flow rate; and help to raise the convective HTCs (Reynold's number). Collectively, it improves the fluid temperature and other thermal parameters, i.e., thermal energy/exergy and efficiency of the system.³¹ Apart from the entropy generation, due to better thermal conductivity and other optical properties, change-in-flow, and change-in-thermal field behavior of CQD-NPs in the water-based fluid also significantly improves the heat transfer rates in the ETC and HE sections which directly improves the evaporation and convective heat transfer rates of saline water in the solar still section. Figure 8 depicts the variation of fluid temperature of saline water stored in SSSS section. It is raised with accumulative effect of heat transfer by blackened surface (convective HTC), circulation of external hot fluid (BF/NF) transfer from the outlet of ETC via HE, direct absorption of incident solar radiation and mainly CQDs. It is found to be around 97.18°C using CQDs-water-based nanofluid as compared to water as a basefluid (21.5% rise) at 69% value of β_c. Also, it increases with increase in concentration of NPs as shown in Figure 9. As discussed above, β_c effectively controls the heat transfer rate and hence fluid temperature (T_f) of the SSSS section; its effect is shown in Figure 10 which shows the variation of T_f for different values of β_c. It is found to be higher for lower values of β_c and found to be higher during sunshine hours. The β_c value of 0.67 is found to be optimum, which gives a very high value of T_f such that it just about to touch the boiling point of the fluid. At commercial level, user can utilize the flexible range of β_c of 0.67–0.95, which give sharp change in the value of T_f around 97.18°C–60.01°C in this range. This can be elected on the basis of requirement of electrical generation and drinking water output. Moreover, the variation of maximum value of T_f which occurs around sunshine hours; and the concentration of CQD-NPs is presented in Figure 11. It increases with increase in concentration of NPs. From the analysis, it has been observed that there is just 0.51°C variation in T_f for the wide range of CQD-NPs concentration (1%–5%), which is credited to their ultrafast heat transfer characteristics even at low concentration of CQD-NPs and showed saturation beyond 1% volume concentration because of fixed quantity of basefluid (water) flowing in the insulating pipes and HE in circulation. It is very significant outcome which clearly suggest to use CQD-NPs in place of other NPs such as TiO₂, CuO, Al₂O₃, SiO₂, etc. These mentioned NPs in literature shows significant results but at the use of higher concentration which ultimately increase the effective cost of the system. Moreover, apart from the sunshine hours value of solar intensties and ambient temperatures, the maximum values to all thermal variations including all HTCs are restricted by the viscous forces; and these thermal values increases continuously with increase in volume fraction of CQD-NPs due to thermal conductance forces which define the optimal point by balance of these forces. Motion of the flowing fluid inside the hellicaly coiled HE is also responsible for the significant enhancement of HTCs. The rate of heat transfer per unit length of the HE’s tube is effectively dominated by the the swirl flow of the fluid (centrifugal forces formation) and it causes secondary convective transport inside the HE, which in turn developes diffusion and convection vertices of flow; and it restrics the rise of HTCs or temperature beyond fixed concentration of CQD-NPs. Figure 12 shows the hourly variation of in-built-passive condenser temperature (a) with and (b) wthout using CQD-NPs. It has been observed that condeser temprature range is almost same as saline water temperature in solar still section after sunshine hours but it is partially lower before noons hours. It is due to the fact that water vapors releases its latent heat ofvaporization and raises the condenser temperature after sometime. Ambient temperature also plays effective role in condensation proces in this case; beacause passive condenser is attached on th rear wall of the solar still section and it is not exposed to the solar radiation directly. Therefore, natural outer colling of the condenser continously maintain the condensation rate and hence the final productivity of the modified system. Around 10°C−12°C differences in temperature of passive condenser have been repoted with and without using CQD-NPs for β_c value of 0.67.

Figure 5.

Hourly variation of (a) convective and (b) evaporative HTC with basefluid and CQD-water-based nanofluid.

Figure 6.

Hourly variation of convective HTC with (a) basefluid and (b) CQD-water-based nanofluid for different packing factors of the roof-top semitransparent PV module.

Figure 7.

Hourly variation of evaporative HTC with (a) basefluid and (b) CQD-water-based nanofluid for different packing factors (β_c) of the roof-top semitransparent PV module.

Figure 8.

Hourly variation saline water temperature (solar still section) with and without using CQD-NPs.

Figure 9.

Variation of saline water temperature (solar still section) with volume concentration CQD-NPs for fix packing factors (β_c= 0.67).

Figure 10.

Hourly variation of saline water temperature (solar still section) for different packing factors (β_c).

Figure 11.

Variation of maximum value of saline water temperature (solar still section) with volume concentration of CQD-NPs for fixed packing factors (β_c).

Figure 12.

Hourly variation of in-built-passive condenser temperature with and wthout using CQD-NPs for fixed packing factors (β_c= 0.67).

In circulation mode or hybrid solar distillation process, Reynold's number analysis is really important as shown in Figure 13. From its hourly variation, it is found to be higher during sunshine hours; and higher $(7.93 \times 10^{3})$ for CQD-water-based nanofluid. Significant enhanecemt around 10.44% have been observed in Reynold's number; which directly improves the Nusselt number and hence the natural convective and evaporative HTCs. Obsevations depicts that around 6%–11% constant difference in variation of Reynold's number have been mainatined for the complete day. Moreover, the maximum value of Reynold's number increses with increases in the concentration of CQD-NPs (Figure 14); and improved results are credited to the phenomenon of entropy generation in inner surface of ETC, helical HE, change in flow patern and thermal field behavior as discussed above incorporating CQD-NPs.

Figure 13.

Hourly variation of Reynold's number with and wthout using CQD-NPs for fixed packing factors (β_c= 0.67).

Figure 14.

Variation of Reynold's number (maximum values) with volume concentration of CQD-NPs for fixed packing factors (β_c= 0.67).

Figure 15 (a) and (b) depicts the variation of thermal energy and exergy, respectively, for fixed packing factors (β_c= 0.69) of roof-top semitransparent PV module using basefluid and nanofluid in the system. Both time-dependent parameters are found to be significantly higher using CQD-NPs. Figure 15(a) shows huge rise in thermal exergy (247.4%) during sunshine hours and maintains effect till evening hours. On the other hand, thermal exergy (Figure 15(b)) enhancement around 27.31% have been observed using CQD-NPs during sunshine hours. The significant rise in thermal energy and exergy parameters is attributed to the mutual effect of external integration, CQD-NPs, direct solar energy absorption, and basin liner-thermal plate. Figure 16 (a) and (b) presents the hourly variation of thermal energy efficiency and electrical energy efficiency, respectively, attained by the system. Thermal energy efficiency is found to be around 37.67% and 26.81%, respectively, for CQD-water-based nanofluid and basefluid (water). On the other hand, expected difference in electrical efficiency with and without using CQD-NPs have been observed. It is due to the fact that major condensation takes place in the in-built-passive condenser section and vapors releases latent heat there only; which means that inner surface temeprature of the roof-top-SPV module remains high due to trap of more heat (humid effect) in solar ditillation unit using CQD-NPs in the system. A maximum electrical efficiency around 3.48% has been obseved for the β_c value of 0.67 and it will further increase with an increase in the value of β_c. It is important to select roof-top semitransparent PV module having sufficient number of solar cells on it to run mechanical water pump as well as a DC fan. Otherwise, a separate module would be required to integrate with ETC but it will cover more area and increase the unit cost; and this case would be considered for the requirement of more drinking water for bigger communities in society. Moreover, it has been observed that solar cell temperature $(T_{c e l l})$ and its efficiency $(η_{c})$ characteristics are vice-verse to each other as shown in Figure 17. Hourly variation shows that $T_{c e l l}$ increases with increase in β_c and its efficiency is lower down. Higher value of β_c conveys more trap of incident solar radiation which intern raises its temperature but it decreases the solar cell efficiency. It is really important to cool down the outer surface of the roof-top semitransparent PV module in order to attain high electrical efficiency for higher values of β_c. From our findings, it is important to operate roof-top semitransparent PV module having moderate value of β_c; because its higher values bring up two main concerns, viz. (a) production of lower potable water output due to high blockage area of SPV module (b) low efficiency at higher temperatures, which may create problem to deliver electrical energy to run a mechanical water pump and a DC fan. With recent advances in science and technology, research work is in progress to process materials which can maintain their surface temperature on exposing to high value of incident solar radiation. Also, in present system, it can be resolved using constant flow rate of water over the roof-top of SPV module, which will continuously maintain its temperature and improves its efficiency. Figure 18 shows the hourly variation of potable water productivity and drastic improvement around 187.7% has been reported during noon-hours using the CQD-water-based nanofluid. On dividing 24 h variation in three segments (6 am–12 pm, 12 pm–6 pm and 6 pm–6 am); Major portion of potable water is collected from the in-built-passive condenser end and minor (below 2–3%) is collected at the lower end of the roof-top-SPV module channel. In the first segment, CQD-NPs shows their absorptive and optical behavior such that its effect is minimal; and it suddenly rises after 11 am onward. In second segment, which is the peak noon hours in which productivity increase sharply and around 187.87% maximum enhancement have been observed. CQD-NPs showed excellent thermal behavior and their effect is found to be very consistent even in the third segment as shown in Figure 18(a). Overall, 44.15% daily productivity enhancement has been observed using CQD-NPs for fixed value of packing factor and volume concentration of NPs as shown in bar diagram, Figure 18(b). Maximum/minimum values (sunshine hours span) of all the time-dependent parameters, i.e., TPPs, all HTCs, thermal energy/exergy, and temperatures are listed in Tables 6–8 for a fixed value of β_c. From the performance analysis, this proposed system is double functional stand-alone system as it produces both electrical energy generation as well as potable water production. These two-in-one outs can be easily controlled or varied with change in packing factor and CQD NPs volume concentration. Extra-generated electrical energy can be stored in batteries using inverter and charge controllers and further can be used in home appliances. Proposed system completely solved the water–energy nexus, and their outputs can be improved further with advances in material science and technology.

Figure 15.

Hourly variation of (a) thermal energy and thermal exergy with and without CQD-water-based nanofluid for fixed packing factors (β_c= 0.69) of the roof-top semitransparent PV module.

Figure 16.

Hourly variation of (a) thermal energy efficiency (maxima should come around noon hours) and electrical efficiency with and without CQD-water-based nanofluid for fixed packing factors (β_c= 0.67) of the roof-top semitransparent PV module.

Figure 17.

Hourly variation of solar cell temperature and efficiency (SPV-roof top) using CQD-NPs for different packing factors.

Figure 18.

(a) Hourly variation of potable water production and (b) overall daily potable water production with and without using CQD-water-based nanofluid for fixed packing factors (β_c= 0.67) of the roof-top semitransparent PV module.

Table 6.

Annual yield, thermal energy, and thermal exergy obtained with and without using CQD-NPs.

	Estimated values
Measuring parameters	$β_{c} = 0$		$β_{c} = 0.67$		$β_{c} = 0.75$		$β_{c} = 0.85$		$β_{c} = 0.95$
Measuring parameters	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF
Annual yield $(kg)$	989.43	1298.4	2188.63	3283.6	1784.3	2873.3	1532.7	2585.6	1743.4	2187.5
Total thermalenergy $(kWh)$	1101.6	1453.5	2790.5	3553.9	2560.8	3183.5	2265.7	2987.1	221.5	2678.9
Total thermalexergy $(kWh)$	93.3	107.5	404.4	462.7	355.6	423.6	298.4	376.3	1298.7	341.2

Table 7.

Energy/exergy-based CO₂ mitigation and CCs earned (enviro-economic parameters) obtained with and without using CQD-NPs.

	Estimated values
Measuring parameters	$β_{c} = 0$		$β_{c} = 0.67$		$β_{c} = 0.75$		$β_{c} = 0.85$		$β_{c} = 0.95$
	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF
CO₂ mitigation $(t)$ (Energy)	41.39	54.2	104.8	135.6	96.2	119.4	85.1	112.7	65.5	100.4
CO₂ mitigation $(t)$ (Exergy)	3.5	4.04	15.4	17.8	19.7	15.4	13.3	14.3	11.7	12.8
CCs ($)(Energy)	600.2	792.6	1520.3	1958.3	1395.4	1734.7	1234.7	1627.8	949.9	1459.7
CCs ($)(Exergy)	50.4	58.7	220.9	252.3	193.2	230.8	162.5	206.7	120.8	186.3

Note: Average unit electricity cost is taken Rs. 7–8/ kWh (8–10 US cents per kWh). 1 US $=83.29 Rs. on November 18, 2023.

Table 8.

Maximum values obtained of different time dependent parameters for the basefluid (water) and CQD- water-based nanofluid for different values of $β_{c}$ .

	$β_{c} = 0$		$β_{c} = 0.67$		$β_{c} = 0.75$		$β_{c} = 0.85$		$β_{c} = 0.95$
Time-dependent parameters	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF	WithoutNF	WithNF
Base fluid (solar still) (°C)	48.3	99.31	81.39	99.74	74.0	86.86	67.49	78.21	57.18	61.41
Roof-top PV module temperature/cell temperature (°C)	28.9021	33.0789	32.909	35.689	35.185	39.6551	40.742	44.5248	44.5171	50.5591
Copper condenser (°C)	74.9872	80.6929	78.4547	87.3381	82.8720	93.4296	84.6076	95.9241	88.2476
Thermal energy (kWh)	0.2247	2.3214	1.8476	7.2406	4.4292	9.8421	7.7409	13.4818	11.7370	18.383
Thermal exergy (kWh)	0.2135	1.06	1.6734	2.1362	3.1628	3.6231	5.1195	7.4995	9.2678	10.2314
Thermal energy efficiency (%)	0.1744	12.2639	26.2933	35.1763	32.271	41.6375	35.1783	44.8081	39.3163	48.1819
Electrical energy efficiency (%)	0	0	24.125	7.716	18.685	4.0625	16.291	3.6291	12.953	1.7282
Convective HTC (W/m²-K)	67.7781	93.3009	62.744	87.6763	62.2336	83.8441	61.6907	76.9385	61.3731	72.5298
Evaporative HTC (W/m²-K)	37.5403	78.247	32.0303	67.8163	8.6572	10.3609	6.9868	9.5091	3.8812	10.4516
Total yield (kg)	0.1565	0.7314	1.4169	3.51499	3.3512	6.4509	5.2377	7.5687	8.7155	9.7229
Heat capacity (J/kg-K)	3177.7	3789.4	4019.8	4252.7	4109.5	4336.5	4196.3	4414.7	4287.3	4700.1
Thermal conductivity(W/m-K)	0.7181	1.5057	0.6811	1.0621	0.6779	0.9988	0.6707	0.9024	0.6623	0.9272
Viscosity(kg/m-s)	1.2845×10⁻⁴	1.8173×10⁻⁴	2.1378×10⁻⁴	2.391×10⁻⁴	2.3073×10⁻⁴	2.7365×10⁻⁴	2.836×10⁻⁴	3.2476×10⁻⁴	3.3695×10⁻⁴	3.4851×10⁻⁴
Density	941.41	953.94	960.6075	981.5985	981.6864	985.667	982.9660	987.8967	985.2538	990.1567

Moreover, to improve the system performance, it is vital to filter the inefficiencies generated within the system. As discussed above, entropy generation mechanism is useful in order to characterize the estimation of thermal processes. In conjunction with heat transfer based on the second law of thermodynamics, it allows the evaluation of irreversibilities related to heat transport in the system. Due to irreversibilities, the entropy of the system increases continuously and attains maximum value at the state of equilibrium; and all the irreversibilities mechanism ceases out at this stage. From the off state of equilibrium, system begins entropy exchange (matter/heat) with the exterior and irreversible process begins to operate. The entropy of the system decreases the process due to heat loss. Moreover, in association with this heat transfer, exergy transfer depends on the temperature level at which it occurs in relation to the ambient temperature; and exergy of the system has important property, i.e., it is conserved only when all processes of the system and the ambient are reversible which implies exergy destruction occurs on triggering of irreversible process. It means that system carries more thermal exergy gain as it deviates more from the ambient. In general, reducing the inefficiencies in the existing systems, exergy gain, or exergy efficiencies help us to develop a more efficient energy system. Therefore, energy/exergy-based matrices, viz. EPBT, EPF, LCCE, have been evaluated for different lifespans of the system (n = 1:5:50 years) for different values of β_c (0, 0.67, 0.75, 0.85, and 0.95) of semitransparent PV module. For the evaluation of these energy matrices and enviro-economic analysis (CO₂ mitigation), EE value of each component of the system plays a crucial role. EE and carbon footprint are indicators for selecting materials with lower environmental burden at the product life cycle; and it provides fast and reliable information to design new products. Figure 19 shows the energy-based variation of EPF and EPBT for different lifespans of the system with basefluid (Figure 19 (a)) and CQD-water-based nanofluid (Figure 19 (b)) for different values of β_c. EPF increases with increase in lifespan of the system (n = 50 years maximum) and it decreases on increasing the packing factor of the semitransparent PV module [40.51 (β_c= 0), 27.92 (β_c= 0.67), 25.11 (β_c= 0.75), 21.92 (β_c= 0.85), 16.60 (β_c= 0.95)]. It is the highest for the case of β_c= 0 (double-glazed roof-top). It is due to that fact that addition of EE of the solar cells of semitransparent PV module. Moreover, generation of more annual energy with passage of time raise the EPF. On the other hand, EPBT show the reverse effect of the EPF [0.0247 (β_c= 0), 0.0358 (β_c= 0.67), 0.0398 (β_c= 0.75), 0.0456 (β_c= 0.85), 0.0603 (β_c= 0.95)]. Figure 20 shows the exergy-based variation of EPF and EPBT for different lifespans of the system with basefluid (Figure 20 (a)) and CQD-water-based nanofluid (Figure 20 (b)) for different values of β_c; and same trend have been observed as shown in Figure 19. The energy-based variation of LCCE for different lifespans of the system with basefluid (Figure 21 (a)) and CQD-water-based nanofluid (Figure 21 (b)) for different values of β_c is depicted in Figure 21. It decreases on increasing the packing factor of the semitransparent PV module, whereas it increases with passage of lifespan of the system [0.326 (β_c= 0), 0.377 (β_c= 0.67), 0.346 (β_c= 0.75), 0.306 (β_c= 0.85), 0.236 (β_c= 0.95)]. Moreover, LCCE improves significantly for the system using CQD-water-based nanofluids. Similar trends have been observed on carrying the analysis on an exergy basis [0.0196(β_c= 0), 0.0414 (β_c= 0.67), 0.0343 (β_c= 0.75), 0.0264 (β_c= 0.85), 0.0158 (β_c= 0.95)] as shown in Figure 22. Higher values have been observed using CQD-NPs in the proposed system which is credited to the fact of high generation of annual thermal energy and rise of net EE. As the CQD-NPs shows impressive TPPs due to their lower size (3–5 nm); and processing of this much of size raises the EE values of CQD NPs which significantly alters the values of energy matrices (EPF, EPBT, and LCCE). Picking the highest limit of the lifespan of the system (n = 50 years), significant enhancement in EPF [23.35% (β_c= 0), 28.65% (β_c= 0.67), 22.34% (β_c= 0.75), 29.74% (β_c= 0.85), 50.75% (β_c= 0.95)]; EPBT [23.51% (β_c= 0), 28.77% (β_c= 0.67), 22.4% (β_c= 0.75), 29.91% (β_c= 0.85), 50.81% (β_c= 0.95)]; and LCCE [31.90% (β_c= 0), 28.91% (β_c= 0.67), 24.56% (β_c= 0.75), 32.02% (β_c= 0.85), 53.38% (β_c= 0.95)] has been observed using CQD-NPs on the bases of energy.

Figure 19.

Energy based, the variation of EPF (year⁻¹) and EPBT (year) with different life-spans (years) of the system using (a) basefluid and (b) CQD-water-based nanofluid for different values of β_c.

Figure 20.

Exergy based, variation of EPF (year⁻¹) and EPBT (year) using (a) basefluid and (b) CQD-water-based nanofluid with lifespan (years) of the system for different values of β_c.

Figure 21.

Energy based, LCCE variation with lifespan of the system using (a) with basefluid and (b) CQD-water-based nanofluid for different values of β_c.

Figure 22.

Exergy based, LCCE (%) variation with lifespan (years) of the system using (a) basefluid and (b) CQD-water-based nanofluid for different values of β_c.

On performing the enviro-economic analysis, CO₂ mitigation and CCs earned have been estimated with and without using nanofluids on energy and exergy basis for different values of semitransparent PV module (β_c). Table 5 presents the annual values of thermal energy, thermal exergy, and productivity of the system for different values of β_c; and these are used to estimate the annual CO₂ mitigating and CCs earned. CO₂ mitigation (tons) decreases on increasing β_c [41.39 (β_c= 0), 104.85 (β_c= 0.67), 96.23 (β_c= 0.75), 85.14 (β_c= 0.85), 65.51 (β_c= 0.95)] as shown in Figure 23 (a); because solar cell restricts the solar radiation to reach the solar distiller unit and hence reduces the potable water production/annual energy output. It increases significantly using CQD-water-based nanofluid [31.94% (β_c= 0), 28.8% (β_c= 0.67), 24.31% (β_c= 0.75), 31.82% (β_c= 0.85), 53.32% (β_c= 0.95)], which is due to the better performance of the system due to ultrafast TPPs of CQD-NPs as discussed above. Similar trends have been observed on carrying the analysis on exergy basis with and without using CQD-NPs (Figure 23 (b)). Moreover, Figure 24 depicts the CCs earned per annum for different values of β_c on the basis of energy (Figure 24 (a)) and exergy (Figure 24 (b)). CCs earned decreases on increasing the β_c [600.27$ (β_c= 0), 1520.35$ (β_c= 0.67), 1395.4$ (β_c= 0.75), 1234.51$ (β_c= 0.85), 949.98$ (β_c= 0.95)]; and it increases significantly using CQD-NPs. Similar trends have been observed on carrying the analysis on the exergy basis with and without using CQD-NPs (Table 7). Practically, this system provide both drinking water and electrical energy output. One can withdraw these outputs according to their daily needs as it critically depends on the packing factor of the roof-top semitransparent PV module. With advances in science and technology, small size efficient model of this system can be developed to replace it with modern RO units. This stand-alone two-in-one output system require low-maintenance, easy operation; and it effectively meet the daily needs of drinking water and electrical energy of societies, and families living in scarcity areas (arid/semiarid regions).

Figure 23.

Annual CO₂ mitigation (tons) obtained with basefluid and CQD-water-based nanofluid for different values of β_c on the basis of (a) energy and (b) exergy.

Figure 24.

Annual CCs earned with basefluid and CQD-water-based nanofluid for different values of β_c on the basis of (a) energy and (b) exergy.

Conclusion

Analytical analysis of the proposed system N-ETC equipped with HCHE, built-in-passive condenser, and roof-top semitransparent PV module with/without using CQD-water-based nanofluid provide the promising solution of potable water production and electrical energy generation. Among all the thermo-physical properties, thermal conductivity shows the dominating effect to improve the thermal characteristics (temperature, energy/exergy, all internal/external HTCs, Reynold's number, etc.) of the proposed system. A rise of 56.06% is observed in thermal conductivity during sunshine hours using CQD-NPs for packing factor 0.67 (β_c). Maximum values of evaporative HTCs are observed in the range 9.12–58.1 W/m²-K; and 6.11–32.91 W/m²-K, respectively, with and without using CQD-NPs for the variation of β_c of 0.95–0.67. These thermal characteristics deliver around 187.7% enhancement in productivity during noon-hours; and 44.15% improvement in the overall daily productivity for a fixed value of β_c (0.67) and volume concentration of CQD-NPs. In the proposed system, CQD-NPs act as a vital system performance parameter and form the thermal efficiency point of view, but β_c is the system's output controlling parameter. It decides the quantity of electrical energy generation and potable production output to meet the demands of arid/semiarid regions according to their needs. Low value of β_c produces high potable production but low electrical energy output and vice versa. Therefore, it is necessary to keep in mind to consider an optimum value of the β_c to run the internally connected D.C. fan and external mechanical water pump for the circulation of nanofluid, viz. integration (ETC). Moreover, for balanced output of potable water and electrical energy, a separate PV module can be coupled with the ETCs; and, in this case, β_c can be taken zero (double-glazed roof-top case). Cost analysis shows, generation of more annual energy with passage of time raise the EPF. It increases with increase in lifespan of the system (n = 50 years maximum) and it decreases on increasing the packing factor of the semitransparent PV module [40.51 (β_c= 0), 27.92 (β_c= 0.67), 25.11 (β_c= 0.75), 21.92 (β_c= 0.85), 16.60 (β_c= 0.95)] credits to the addition of EE values of the solar cells. On the other hand, EPBT shows the reverse effect of the EPF. LCCE shows similar trends. From enviro-economic analysis, implies annual CO₂ mitigation (tons) decreases on increasing β_c [41.39 (β_c= 0), 104.85 (β_c= 0.67), 96.23 (β_c= 0.75), 85.14 (β_c= 0.85), 65.51 (β_c= 0.95)] and increases significantly using CQD-water-based nanofluid. CCs earned decreases on increasing the β_c [600.27$ (β_c= 0), 1520.35$ (β_c= 0.67), 1395.4$ (β_c= 0.75), 1234.51$ (β_c= 0.85), 949.98$ (β_c= 0.95)]; and it increases significantly using CQD-NPs. In general, reducing the inefficiencies in the existing system, i.e., exergy gain, or exergy efficiencies improves the energy metrics (EPBT, EPF, and LCCE), which help designers to develop more efficient energy systems.

Scope of future work

Characteristic curve analysis of this system can be carried out to study the thermal energy/exergy gain and loss efficiencies with different integrations. Also, other solo/hybrid NPs with different basefluids can be tested to improve the potable water output and environmental impact (CO₂ mitigation and CCs earned). Kitchen wall (outer side-Sun facing) mounted thermosyphon incorporated prototype model of this system can be tested to make it commercial (RO replacement).

Footnotes

Highlights

Acknowledgments

I, corresponding author, Dr Lovedeep Sahota would like to thank Late Prof. Manoj Kumar Arora for his work dedication and knowledge delivered in research and academics. Throughout his wonderful teaching/research career, Prof. Arora guided many students/colleagues to achieve their goals.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Harendra Pal Singh

Lovedeep Sahota

Swati Arora, Professor, Department of Physics, Cluster Innovation Center, Rugby Sevens Building, University Stadium, University of Delhi, Delhi, India.

Harendra Pal Singh, Assistant Professor, Department of Mathematics, Cluster Innovation Center, Rugby Sevens Building, University Stadium, University of Delhi, Delhi, India.

Lovedeep Sahota, Assistant Professor, Department of Physics, Swami Shraddhanand College, University of Delhi, Delhi, India.

Manoj Kumar Arora, Professor, Department of Physics, Ramjas College, University of Delhi, Delhi, India.

Ishika Rai, B. Tech. student, Cluster Innovation Center, Rugby Sevens Building, University Stadium, University of Delhi, Delhi, India.

Shurti Chauhan, B. Tech. student, Cluster Innovation Center, Rugby Sevens Building, University Stadium, University of Delhi, Delhi, India.

Riya Kumari, B. Tech. student, Cluster Innovation Center, Rugby Sevens Building, University Stadium, University of Delhi, Delhi, India.

Nomenclature

Appendix

$(P F_{1} α τ^{2} A_{R} F_{R}) = (A F_{R} α τ)_{1}$ and $K_{K} = 1 - \frac{A_{R} F_{R} U_{L}}{{\dot{m}}_{f} C_{f}}$ ; $A_{R} F_{R} U_{L} = {\dot{m}}_{f} C_{f} [1 - \exp (- \frac{2 π r L U_{L}}{{\dot{m}}_{f} C_{f}})] .$

References

Kumar

Prakash

, et al. Solar stills system design: a review. Renew Sustain Energy Rev 2015; 51: 153–181.

Tiwari

Sahota

. Review on the energy and economic efficiencies of passive and active solar distillation systems. Desalination 2017; 401: 151–179.

Kumar

Raj

Dsliva

, et al. A review of efficient high productivity solar stills. Renew Sustain Energy Rev 2019; 101: 197–220.

Abdullah

Alawee

Shanmugan

, et al. Techniques used to maintain minimum water depth of solar stills for water desalination–A comparative review. Results Eng 2023; 19: 101301.

Shanmugan

Hammodi

Eswarlal

, et al. A technical appraisal of solar photovoltaic-integrated single slope single basin solar still for simultaneous energy and water generation. Case Stud Therm Eng 2024; 54: 104032.

Abdullah

Essa

Panchal

, et al. Enhancing the performance of tubular solar stills for water purification: a comprehensive review and comparative analysis of methodologies and materials. Results Eng 2024; 21: 101722.

Elsheikh

Hammodi

Ibrahim

AMM

, et al. Augmentation and evaluation of solar still performance: a comprehensive review. Desalination 2024; 574: 117239.

Gupta

Singh

Kumar

, et al. A review on thermophysical properties of nanofluids and heat transfer applications. Renew Sustain Energy Rev 2017; 74: 638–670.

Awais

Bhuiyan

Salehin

, et al. Synthesis, heat transport mechanisms and thermophysical properties of nanofluids: a critical overview. Int J Thermofluids 2021; 10: 100086.

10.

Hamzat

Omisanya

Sahin

, et al. Application of nanofluid in solar energy harvesting devices: a comprehensive review. Energy Convers Manage 2022; 266: 115790.

11.

Kalsi

Kumar

, et al. Thermophysical properties of nanofluids and their potential applications in heat transfer enhancement: a review. Arab J Chem 2023: 105272. doi:https://doi.org/10.1016/j.arabjc.2023.105272

12.

Madas

Narayanan

Gudimetla

. Single and multi-objective optimization of PVT performance using response surface methodology with CuO nanofluid application. Sol Energy 2023; 263: 111952.

13.

Liu

, et al. Performance enhancement of solar desalination using evacuated tubes, ultrasonic atomizers, and cobalt oxide nanofluid integrated with cover cooling. Process Saf Environ Prot 2023; 171: 98–108.

14.

Abdelaziz

Algazzar

El-Said

EMS

, et al. Performance enhancement of tubular solar still using nano-enhanced energy storage material integrated with v-corrugated aluminum basin, wick, and nanofluid. J Energy Storage 2021; 41: 102933.

15.

Chen

Zhou

Zhang

, et al. Stability study of low-cost carbon quantum dots nanofluids with saline water and their application investigation for the performance improvement of solar still. Diamond Relat Mater. 2023, 138: 110194. doi:https://doi.org/10.1016/j.diamond.2023.110194

16.

Alsaiari

Shanmugan

Abulkhair

, et al. Applications of TiO₂/Jackfruit peel nanocomposites in solar still: experimental analysis and performance evaluation. Case Stud Therm Eng 2022; 38: 102292.

17.

Arora

Singh

Sahota

, et al. Performance and cost analysis of photovoltaic thermal (PVT)-compound parabolic concentrator (CPC) collector integrated solar still using CNT-water based nanofluids. Desalination 2020; 495: 114595.

18.

Deshmukh

Karmare

Patil

. Experimental investigation of convective heat transfer performance of TiN nanofluid charged U-pipe evacuated tube solar thermal collector. Appl Therm Eng 2023; 225: 120199.

19.

Abdullah

Alqsair

Aljaghtham

, et al. Productivity augmentation of rotating wick solar still using different designs of porous breathable belt and quantum dots nanofluid. Ain Shams Eng J 2023; 14: 102248.

20.

Ghandourah

Prasanna

Elsheikh

, et al. Performance prediction of aluminium and polycarbonate solar stills with air cavity using an optimized neural network model by golden jackal optimizer. Case Stud Therm Eng 2023; 47: 103055.

21.

Alsaiari

Moustafa

Alhumade

, et al. A coupled artificial neural network with artificial rabbits optimizer for predicting water productivity of different designs of solar stills. Adv Eng Softw 2023; 175: 103315.

22.

Sahota

Saini

Jain

, et al. Performance and cost analysis of a modified built-in-passive condenser and semi-transparent photovoltaic module integrated passive solar distillation system. J Energy Storage 2019; 24: 100809.

23.

Kumar

Chanda

Elsheikh

, et al. Performance improvement of single and double effect solar stills with silver balls/nanofluids for bioactivation: an experimental analysis. Sol Energy 2023; 259: 452–463.

24.

Dhivaga

Shoeibi

Kargarsharifabad

, et al. Performance enhancement of a solar still using magnetic powder as an energy storage medium-exergy and environmental analysis. Energy Sci Eng 2022; 10: 3154–3166.

25.

Shatar

Sabri

MFM

Salleh

MFM

, et al. Energy, exergy, economic, environmental analysis for solar still using partially coated condensing cover with thermoelectric cover cooling. J Cleaner Prod 2023; 387: 13583.

26.

Nazari

Safarzadeh

Bahiraei

. Experimental and analytical investigations of productivity, energy and exergy efficiency of a single slope solar still enhanced with thermo-electric channel and nanofluid. Renew Energy 2019; 135: 729–744.

27.

Iqbal

Mahmoud

Sayed

, et al. Evaluation of the nano-fluid assisted desalination through solar stills in the last decade. J Environ Manag 2021; 277: 111415.

28.

Pak

Cho

. Hydrodynamic and heat transfer study of dispersed fluids with submicron metallic oxide particles. Exp Heat Trans: J Therm Energy Generat, Trans, Storage, Convers 1998; 11: 151–170.

29.

Xue

. Model for thermal conductivity of carbon nanotube-based composites. Phys B Condens Matter 2005; 368: 302–307.

30.

Brinkman

. The viscosity of concentrated suspensions and solutions. J Chem Phys 1952; 20: 71.

31.

Mahian

Kianifar

Sahin

, et al. Entropy generation during Al₂O₃/ water nanofluid flow in a solar collector: effects of tube roughness, nanoparticle size and different thermo-physical models. International Journal of Heat Mass Transfer 2014; 78: 64–75.

32.

Tiwari

Sahota

. Advanced solar distillation systems: Basic principles, Thermal modelling and its applications. UK: Springer, 2017.

33.

Tiwari

. Solar energy: Fundamentals, Designs, modelling and applications.

Narosa Publications

. 2002, ISBN: 084932409.

34.

Kabeel

Omara

Essa

. Enhancement of modified solar still integrated with external condenser using nanofluids: an experimental approach. Energy Convers Manage 2014; 78: 493–498.

35.

Arora

Singh

Sahota

, et al. Energy matrices, enviro-economic and characteristic equation-based performance analyses of photovoltaic thermal compound parabolic concentrator (PVT-CPC) coupled solar still equipped with heat exchanger using SWCNTs and MWCNTs–water nanofluids. Int J Ambient Energy 2024; 45: 2308039.

36.

Elango

Kannan

Murugavel

. Performance study on single basin single slope solar still with different water nanofluids. Desalination 2015; 360: 45–51.

37.

Sadeghi

Nazari

. Retrofitting a thermoelectric-based solar still integrated with an evacuated tube collector utilizing an antibacterial-magnetic hybrid nanofluid. Desalination 2021; 500: 114871.

38.

Omara

Kabeel

Essa

. Effect of using nanofluids and providing vacuum on the yield of corrugated wick solar still. Energy Convers Manage 2015; 103: 965–972.

39.

Sharshir

Peng

, et al. Enhancing the solar still performance using nanofluids and glass cover cooling: experimental study. Appl Therm Eng 2017; 113: 684–693.

40.

Shoeibi

Rahbar

Esfahlani

, et al. Improving the thermoelectric solar still performance by using nanofluids– experimental study, thermodynamic modeling and energy matrices analysis. Sustain Energy Technol Asses 2021; 53: 101339.

41.

Abdelaziz

Algazzar

Al-Said

EMS

42.

Mahian

Kianifar

Heris

, et al. Nanofluids effects on the evaporation rate in a solar still equipped with a heat exchanger. Nano Energy 2017; 36: 134–155.

43.

Singh

Mittal

Khullar

. Enhancing upgraded solar still performance in summer and winter through nanofluid-based solar collectors. Desalin Water Treat 2024; 317: 100241.

44.

Sahota

Shyam Tiwari

. Analytical characteristic equation of nanofluid loaded active double slope solar still coupled with helically coiled heat exchanger. Energy Convers Manage 2017; 135: 308–326.

45.

Wole-Osho

Okonkwo

Abbasoglu

, et al. Nanofluids in solar thermal collectors: review and limitations. Int J Thermo-Phys 2020; 41: 57.

CO 2 mitigation,energy matrices,and the performance analysis of N-evacuated tube collector (ETC)-integrated modified solar distiller for water/electricity co-generation using CQD nanoparticles

Abstract

Keywords

Introduction

System description and design modification

Mathematical modeling

Energy matrices and CO2 mitigation (environmental cost)

Methodology

Results

Conclusion

Scope of future work

Footnotes

Highlights

Acknowledgments

Declaration of conflicting interests

Funding

ORCID iDs

Nomenclature

Appendix

References

Energy matrices and CO₂ mitigation (environmental cost)