Experimental investigation of designed solar parabolic concentrator based desalination system for textile industry wastewater treatment

Abstract

The escalation in demand for textile products increased the use of fresh water and treatment of wastewater; which escalates the search for suitable and energy-efficient technology for wastewater treatment. Solar assisted technology (i.e. solar desalination) for the textile industry wastewater treatment is proved to be an affordable technology. The only drawback of solar desalination is its low productivity which is the major hindrance in the global acceptance of the system. In the present study, an ingenious improvement in form of a parabolic concentrator-based solar desalination system (PCB-SDS) is designed to overcome low productivity, and the simultaneous use of source textile industry wastewater for its treatment makes this study more realistic. The performance of the designed system was examined for three different brine depths i.e. 20%, 40%, and 60% for two different processing step i.e. Dyeing and Degumming. System performance was evaluated in terms of energetic, exergetic, pollutant removal, and economic analysis. The maximum output of the system was found to be around 7440 and 8330 mL/day on clear sunny days with textile dyeing wastewater (TDyWW) and textile degumming wastewater (TDgWW) at 60% depth respectively. Daily average energy and exergy efficiency of system varies in the range 39.8–51.9 and 3.6–4.8% respectively. The degumming wastewater shows 85% COD removal, whereas, around 90% of TDS and hardness removal was also recorded. The dyeing processed wastewater showed 80% COD removal efficiency, ≅90% TDS, and hardness removal. The cost per liter of distillate output produced from designed PCB-SDS was found to be 0.014 $/L.

Keywords

Chemical oxygen demand (COD)exergy parabolic concentrator pollutant removal solar desalination textile industry wastewater

Introduction

Energy and drinking water are two of the major requirements on this earth. Energy demand will increase two to three folds till 2050 due to rising global population and expansion in developing economics.¹ Therefore, to overcome this issue Nelson² suggested exploring all possible methods of energy production and deals with climate and natural resource problems. The other very important challenge which world is facing today is freshwater demand.^3,4 By the year 2025, it is expected that around one third of the world’s population will face a severe shortage of freshwater water supply and the rest will face a vital requirement of freshwater. Industries are one of the major consumers and producers of freshwater and wastewater, respectively.

Textile industry is one of the major industries, which consumes a huge amount of water and produces a very bulky and polluted type of wastewater to the surroundings.^5,6 Due to decreasing water bodies, water level, and besides legislation overuse of water in the industry increases the demand of reuse. The demand of low energy-intensive treatment technology is required to solve the problem forindustrial wastewater. Although a number of physical, chemical, biological, solar, and hybrid treatment processes have been cited in various literature with economic and efficient ways,^7–11 a most efficient technology is still being eyed.

Therefore, to decrease the requirement of energy consumption for textile industry wastewater treatment and fulfill the requirement of freshwater; solar energy can be a possible and trusted option in the future. Different solar energy treatment options for wastewater treatment are electrolysis,¹² photo-catalysis,¹³ microbial desalination,¹⁴ advanced oxidation process⁹ and desalination.^15,16 Beside other technologies, solar desalination can prove to be most cost-effective, efficient and promising for the treatment of wastewater for freshwater generation with fewer contaminants.

Solar desalination technology is utilized in the recovery of pure water from saline water but there was very few works reported till date on the use of solar desalination in industrial sector wastewater treatment. Al-Othman¹⁷ with his co-authors tried to stimulate fulfillment of energy requirements of multistage flash driven desalination system through parabolic trough collector. The results revealed that use of two parabolic trough collectors with total area of 3160 m² can fulfill 76% of total energy demand and the rest can be completely fulfilled with solar pond. The aim of their study was to produce 1800 m³/day of distillate. Hence, it can be concluded that desalination can be a future for industrial wastewater treatment plant.

Asadi et al.¹⁸ conducted a study on the treatment of wastewater (sanitary and palm oil mill). The reduction in chemical oxygen demand (COD) and heterotrophic plate count (HPC) was reported to be 86.83% and 86.75% respectively. In the same manner, sludge based wastewater was passed through laboratory designed solar still The reduction in COD was observed from 4052 to 9 mg/L on first and 11847 to 566 mg/L on the fifth day of experiment.¹⁹

Baalbaki et al.²⁰ uses solar still as an affordable water treatment method for pharmaceutical industry. High rate of degradation of ampicillin (AMP), naproxen (NPX), and carbamazepine (CBZ) was observed beyond threshold temperature. Ibuprofen (IBU), CBZ, and NPX require both temperature and sunlight to degrade effectively. But, till date utilization of textile industry wastewater for treatment with solar desalination technology is not cited as per author’s knowledge.

The main objective of this study was to examine the possibility of using designed solar parabolic concentrator based desalination technologyfor the processing of textile industry wastewater in place of saline water make this study more novel and applicable. However, the treatment of industrial wastewater that has both organic and inorganic pollutants is a major challenge. In fact, the presence of minerals and salinity disrupts biological treatment processes. The proposed method is perhaps one of the most appropriate methods for managing such wastewater.The experimental analysis was carried out during summer with three distinct brine depths which was set according to the size of basin/absorber i.e. 20%, 40% and 60%. The tests were conducted during month of May 2019 in Katra (J&K), India. A comparison between treatment efficiency, distillate output productivity with energy and exergy efficiency for the designed system is judiciously presented with economic analysis.

Hence, here in this article integration of solar desalination for textile industry wastewater treatment is proposed; which is solution for both energy and freshwater demand. This technology is totally dependent on renewable energy i.e. solar and will prove to be effective technology in future.

Experimental setup and procedure

This section is divided in four subsections: detailed designing, construction and instrumentation, experimental procedure and uncertainty propagation. In the next section, detailed design, construction and instrumentation have been discussed. The discussion on detailed experimental procedure of experimental investigation is presented through the Experimental procedure section. In the last subsection, uncertainty in measuring instrument and performance parameters has been discussed in the last section i.e. the Uncertainty propagation section.

Solar desalination system design, construction and instrumentation

The experimental investigation of the system has been carried out at Katra (Shri Mata Vaishno Devi University,), (J&K) India (Latitude 32.9915°N,Longitude 74.9318°E). The schematic diagram/layout design of parabolic collector based solar desalination system (PCB-SDS) is shown through Figure 1. The parabolic collector was manually adjusted to two axis mode one from east to west and other from north to south. The collector was rotated every hour at 4° from east to west since 0600 hrs in the morning to 1900 hrs till late evening. The absorber is used to grab all reflected solar radiation from the reflector. Absorber was fixed at focal point of the parabolic collector, painted with black colour to absorb maximum amount of solar radiation incident on the surface. To remove the heat losses all sides of absorber except from bottom was insulated with rock wool of 50.8 mm (2 inches) thickness. The collected steam is transferred to heat exchanger through proper channel where the water vapour get condensed and collected for further use. Table 1 illustrate the designed parameters of the PCB-SDS.

Figure 1.

Schematic view of experimental setup.

Figure 2.

Experimental rig arrangement.

Table 1.

Design specification and dimensions of PCB-SDS system.

Item	Specifications/Value
Aperture Area of concentrator	1.645 m²
Concentration ratio	212.5
Material of concentrator	Aluminium ionized sheet
Reflectivity (γ) of concentrator	0.92
Height of stand from ground	1645 mm
Tracking	Manual two axis tracking
Coating on stand	Powder coated to withstand rusting etc,
Material of absorber/basin	Copper
Thermal conductivity of absorber material	386 W/mK at 20 °C
Coating on absorber	Black chrome coating
Thickness of absorber material	50.8 mm (2 inches)
Width of absorber	480 mm
Height of absorber	250mm
Distance of absorber from ground	2015 mm
Diameter of inlet pipe	50 mm
Diameter of outlet pipe	350 mm
Material of pipes	Cooper
Insulation thickness on absorber	50.8 mm (2 inches)
Type of heat exchanger	Cross flow
Area of heat exchanger	0.5 m²
Material of heat exchanger	Copper
Material of outer cover of heat exchanger	Al sheet
Inlet and outlet tank material	Polyethylene
Capacity of inlet tank for heat exchanger	100 Liter
Capacity of inlet tank for absorber	30 Liter
Insulation thickness around tanks	50.8 mm (2 inches)
RTD temperature sensors	−50 to 600 °C

The schematic view of the designed investigational system is shown through Figure 1. The arrangement of different components used in experimental are shown through Figure 2.

Figure 3.

Energy balance inside the absorber used for the system.

The temperature values at different state points of the system were recorded. The position of temperature sensors at various points of system can be well understood through Figure 1. T₁ measures ambient temperature, Temperature sensor T₂ measures wet bulb temperature, Temperature sensor T₃ and T₄ measures the water temperature of the basin (absorber), Temperature sensor T₅ measures the lower surface temperature of the absorber, Temperature sensor T₆ and T₇ measures the temperature difference or losses from outer surface of the absorber and after insulation to the surrounding respectively, whereas, Temperature sensor T₈ and T₉ measures the temperature difference of reflective surface from front and back. All temperature measurements were logged in Masibus 85xx + 24 channel data logger after every minute. The solar radiation, wind velocity and other environmental parameters were taken from SRRA station (QC V1.2 2014–3) installed at University campus.

Experimental procedure

In this study, wastewater after two processing steps was taken from textile industry namely dyeing (TDyWW) and degumming (TDgWW) with three depths (20%, 40% and 60%) in the constructed PCB-SDS. Six cases of solar still are tested: (test-1) TDyWW was taken with 20% depth, (test-2) TIDyWW was considered with 40% depth while (test-3) comprises of TDyWW with 60% depth. And, test-4: absorber/basin was filled with TDgWW with 20% depth, test-5: TDgWW with 40% depth and test-6: TDgWW with 60% depth was considered. Table 2 summarizes the detailed experimental setup for each test.

Table 2.

Experimentation details.

Depth (%)	Test	Date of experimental study	Wastewater type	No. of runs
20	Test 1	16/05/2019	Dyeing (TDyWW)	01
20	Test 4	21/05/2019	Degumming (TDgWW)	01
40	Test 2	22/05/2019	Dyeing (TDyWW)	01
40	Test 5	24/05/2019	Degumming (TDgWW)	01
60	Test 3	23/05/2019	Dyeing (TDyWW)	01
60	Test 6	25/05/2019	Degumming (TDgWW)	01

Below detailed experimental procedure was carried out:-

At the start of every experimental measurements, the experiment setup was cleaned, all measuring instruments checked, wastewater was filled inside an inlet tank, heat exchanger was cleaned properly, absorber and pipes was cleaned with water from back pressure so that no impurities remain present inside the system which will impact the environmental pollutant parameters, insulation was checked.

Parabolic trough collector was manually tracked every hour and adjusted accordingly in two axis path.

During every measurement, it was ensured that data was collected at the same time and data logger is logging the measured values SRRA records solar data, ambient temperature, and wind velocity.

The distillate output is collected and measured carefully through measuring cylinder and recorded; and analysis of distillate output was done for pollutant removal.

Each time when reading was logged step 2, 3 and 4 is repeated.

Different environmental pollutant parameters are analysed in the experimental laboratory at the end of every day.

Uncertainty propagation

In this section uncertainties arising during the experimental procedure are studied. Some of these values are obtained from instrument supplier and instrument data sheet. In most of the cases, an essential quantity that cannot be directly evaluated is rather determined as a function of variables that are measured directly i.e. $X = f (Y_{1}, Y_{2}, Y_{3}, \dots)$ . The evaluated parameters $(Y_{1}, Y_{2}, Y_{3}, \dots)$ have a random variability which is termed as uncertainty. The reason of this analysis is to evaluate how the uncertainties in each of the calculated variables propagate into the value of measured quantity. Taylor (1997)²¹ explained the uncertainty and errors of the experimental results as:

U_{X} = \sqrt{\sum_{i} {(\frac{\partial X}{{\partial Y}_{i}})}^{2}} U_{Y i}^{2}

(1)

where, U stands for uncertainty of the variables.

It is assumed that the calculated parameters were mainly dependent on the recorded (measured) value. The instrument utilized for recording of temperature wereMasibus 85xx + data logger with temperature sensors (RTD) type (range −50 – 600 °C) with maximum uncertainty of ±1.2 °C and accuracy of ± 0.10 °C. SRRA station was utilized for recording and collection of solar radiation data with maximum uncertainty of ≤10 W/m². Measuring flask was calibrated based on a standard during the experiments and output results stated in this work consider the calibration result data. Based on the above equation the uncertainty of the energy and exergy efficiency varies in the range of ±1.5–2.1% and 0.3–08% respectively.

Selection, collection and characterization of industrial wastewater

Selection and collection of industrial wastewater with its pollutant level is covered in this section to be utilized as water input in the system for treatment and distillate/freshwater output. This section is subdivided in two parts. In the first part (next section), importance and region is discussed based on which industrial wastewater was selected for treatment in designed PCB-SDS. The collection methodology and characterization of industrial wastewater was explained in the Collection and characterization of wastewater collected from textile industry section with instruments used for the heavy metal analysis.

Selection criteria of industrial wastewater

The selection of industrial wastewater in the present study was done on different aspects i.e. high wastewater generation, the production of wastewater from the particular industry should be very large with high pollutants level and should be novel/unique enough to be used in solar desalination system, from previous literature. Keeping these properties in mind, textile industry has been selected to be used in the present study which is novel in its type, as no work was reported till date on the use of textile industry based upon author’s knowledge and literature survey.

Collection and characterization of wastewater collected from textile industry

The wastewater was collected from two processing steps in the textile industry situated in Panipat District at Haryana, India. The composite method was applied for collection of wastewater from two different points. Table 3 illustrates the analytical characteristic of collected wastewater from two different steps: Degumming (TDgWW) and Dyeing (TDyWW). The samples of wastewater was filtered through sieve of 1 mm size to remove large particles and stored in sterile bottles at 4 °C for further contamination and degradation. Temperature, pH, total dissolved solid (TDS) and hardness was selected as study parameters by following standard protocol of American Physical Health Association, 2012.²² Hardness was analysed by titrimetric method and chemical oxygen demand (COD) by reflux method. Concentration of heavy metals are also analysed by Inductive Coupled Plasma-Optical Emission Spectrometry method (ICP-OES) (Model: Perkin-Elmer-Optima 5300 V; Serial No. 077N508240) (APHA 2012).²² All experimental parameters are done using Lab grade chemicals from Hi-Media, Mumbai. The studied parameters are analysed in triplicates.

Table 3.

Physio-chemical parameters of TDyWW and TDgWW samples.

S. No.	Parameters	TDyWW	TDgWW	Standard for emission of discharge of pollutant (Textile and Dye industry) CPCB^23,24
1.	pH*	8.62 ± 0.16	12.22 ± 0.15	6.5-8.5
2.	TDS	3884.7 ± 16.76	4755.1 ± 23.62	2100
3.	COD	11363.4 ± 61.66	22367.3 ± 73.53	250
4.	Hardness	1118.4 ± 55.61	1305.3 ± 24.28	–
5.	Copper (Cu)	0.05	2.02	3
6.	Iron (Fe)	3.02	2.02	3
7.	Manganese (Mn)	0.18	0.12	2
8.	Nickel (Ni)	0.17	0.03	3
9.	Zinc (Zn)	4.16	7.58	5

*Except pH all parameters are given in mg/L; All values are in round off figures upto two decimal places to avoid complexity.

Energy, exergy, pollutant removal and economic analysis

In this section, energy, exergy and economic analysis of PCB-SDS are presented. While analysing the thermal analysis of the system following assumptions were made (Figure 3):

There is no steam leakage from the system.

Basin material heat capacities are negligible.

Conductive losses are negligible.

Energy analysis

Energy efficiency of any system is interpreted in terms of first law of thermodynamics.The area of designed parabolic dish collector is very small which results in very less radiative losses and convective heat losses. In this regard, the daily productivity (P_d) in kg/day of the system and total energy efficiency (η_en,total) is calculated using equation is also very small³

P_{d} = \sum P_{h}

(2)

η_{e n, total} = \frac{P_{d} h_{f g . s w}}{({C A}_{a} \sum I_{b}) Δ t} \times 100 %

(3)

Where, P_h is represented as hourly productivity in kg/h_;h_fgsw represents latent heat of vaporization of water for daily average data; Concentration ratio, (C) is given by ( $\frac{A_{a p}}{A_{a}}$ ) and Δt represents the time interval taken during measurement of solar radiation.

Where, $h_{f g . s w}$ is the latent heat of vaporization (kJ/kg) of water in the absorber is calculated as²⁵

h_{f g . s w} = 3.1615 (10^{6} - 761.6 \times T_{w w}), T_{w w} > 70

(4)

h_{f g . s w} = 2.4935 (10^{6} - 947.79 \times T_{w w} + 0.13132 \times T_{w w}^{2} - 0.0047974 \times T_{w w}^{3}) . T_{w w} < 70

(5)

Exergy analysis

The second law of thermodynamics is utilized to estimates the capability of energy to do work which is known as Exergy.

Petela, generalized the equation for exergy balance for closed system as²⁶

\sum E_{e x, input} - \sum E_{e x, output} = \sum E_{e x, destruction}

(6)

For all test cases, the exergy output of the distillate output (freshwater) for solar desalination system is computed as²⁷

E_{e x, output} = E_{e x, evaporation} = \frac{m_{e w} h_{f g . s w}}{3600} [1 - (\frac{T_{amb} + 273}{T_{w w} + 273})]

(7)

Whereas, $E_{e x, output}$ stands for output exergy from the designed solar desalination or output evaporative exergy ( $E_{e x, evaporation}$ ).

Exergy input to the designed solar desalination is computed as²⁶

E_{e x, input} o r E_{e x, sun} = {C A}_{a} I_{t} [1 - \frac{4}{3} (\frac{T_{amb} + 273}{T_{sun}}) + \frac{1}{3} {(\frac{T_{amb} + 273}{T_{sun}})}^{4}]

(8)

Where, $T_{sun}$ is the maximum sun temperature which is assumed to be 6000 K and $E_{e x, sun}$ stands for input exergy in form of solar radiation from sun.

The exergy efficiency $η_{e x}$ of the designed system is calculated as the evaporated water exergy from absorber divided by the inlet exergy from sun²⁷

η_{e x} = \frac{E_{e x, output}}{E_{e x, input}} = \frac{E_{e x, evaporation}}{E_{e x, sun}}

(9)

The exergy efficiency of the total system for whole day is computed as²⁸

η_{e x, total} = \frac{E_{e x, output, total}}{E_{e x, input, total}}

(10)

Pollutant removal analysis

The removal efficiency of pollutant from the system is calculated in terms of initial and final parameter⁷

Pollutant removal efficiency = \frac{P_{i} - P_{f}}{P_{o}} \times 100

(11)

Where, initial pollutant parameter is denoted by $P_{i}$ and final pollutant parameters are represented by $P_{f}$ after treatment from solar desalination system.

Economic analysis

The main objective of all solar desalination system is to increase the distillate (freshwater) output and reduce the cost of its productivity per liter (CPL). Therefore, to examine the CPL from the designed system the unit is economically examined and the procedures for economic analysis for all test cases are calculated as follows²⁹

The first annual cost (FAC) of the designed solar desalination system is governed by²⁰

FAC = CRF \times C C

(12)

Where, CRF and CC are the capital recovery factor and capital cost of the designed solar desalination system, respectively.

The capital recovery factor which is estimated from³

CRF = \frac{i {(1 + i)}^{n}}{{(1 + i)}^{n} - 1}

(13)

Where, i is the annual rate of interest which is fixed by the local governments and n denotes the life time of solar desalination in years which is assumed to be 15 years.³⁰

The annual salvage value (ASV) of the solar desalination system is computed by³¹

ASV = SFF \times S

(14)

Where, SFF represents the sinking fund factor for a desalination system and S represents the salvage value of the solar desalination. S is computed by³

S = 0.2 \times C C

(15)

SFF is computed by³¹

SFF = \frac{i}{{(1 + i)}^{n} - 1}

(16)

The annual maintenance cost (AMC) is supposed to be 10% and is computed as³¹

AMC = 0.1 \times FAC

(17)

The total annual cost is calculated as³¹

TAC = FAC + AMC - ASV

(18)

Lastly, the cost per liter (CPL) of the distillate/freshwater yield is determined by³¹

CPL = \frac{TAC}{P_{d, annual}}

(19)

Where, $P_{d, annual}$ represents the average annual water productivity.

Results and discussion

This section presents a comprehensive discussion of various results obtained during the experimental analysis. Based on the experimental data, energy, exergy and pollutant removal efficiency of the system has been evaluated with the help of set of equations (2) to (10). In this section various input and output parameters such as solar radiation, distillate output productivity, effect of depth and different temperature approaches on absorber has also been presented and discussed for different tests.

Variation in solar radiation and ambient temperature

The variations in solar radiation and ambient temperature versus time for Test 1–3 and Test 4–6 are well presented through Figure 4(a) and (b) respectively. Each test was carried out on different days with different environmental conditions.

Figure 4.

Solar radiation and ambient temperature fluctuations verses time during different test (a) Test 1–3 (b) Test 4–6.

It can be clearly observed from Figure 4(a) that solar radiation was found almost constant during selected days for test-1 to test-3. It can be seen that some dramatic fluctuations in solar radiation was observed between 0900 to 0920 hrs, 1100 to 1130 hrs and 1500 to 1600 hrs, during test-2. This trend in solar radiation is noticed because of the clouds during that particular interval of time. The highest value of solar radiation for test-1, test-2 and test-3 was 879.0 W/m² at 1220 hrs, 993.6 W/m² at 10:35 and 918 W/m² at 1150 hrs respectively.

The large variation was observed during test-4 and test-6 was as almost negligible variation is noted during test-5. It has been observed that for sudden drop in solar radiation was observed during 1235 to 1300 hrs for period of 25 min during test-4.During test-6 fluctuation was observed during 1630 to 1700 hrs due to cloud effect. The highest value of solar radiation for test-4, test-5 and test-6 were 998.0 W/m² (at 1140 hrs), 935.8 W/m² (at 1350 hrs) and 968.8 W/m² (at 12:00 Noon) respectively.

The range of variation of ambient temperature for Test-1, Test 2, Test 3, Test 4, Test 5 and Test 6 were 22.9–34.0 °C, 25–37.5 °C, 25.9–37.3 °C, 24.4–36.0 °C, 25.3–36.9 °C and 25.5–38.1 °C respectively.

Solar desalination system temperatures for different tests

The distillate output and performance of PCB-SDS was greatly influenced by different system tempertaure nodes like wastewater $(T_{ww})$ , vapor $(T_{vap})$ and enlightened absorber surface $(T_{abs})$ temperature. It has been observed that the system temperature increases with increase in solar radiation. Solar radiation shows major impact on absorber wall temperature in relation to other parameters.³⁰ The absorbed radiation was directly transferred to the wastewater agitated on the internal surface under the effect of ebullition, which enhanced the coefficient of heat transfer and exchange in energy quantity. The exchange of energy in form of heat between wastewater and absorber increases the temperature and decrement in thermal capacity of wastewater was observed which causes increase evaporation rate.

The variation in wastewater $(T_{ww})$ , vapor $(T_{vap})$ and enlightened absorber surface $(T_{abs})$ temperature with time have been discussed in this section and the same is presented by Figure 5. Figure 5 shows the variation in different system tempertaure nodes like wastewater $(T_{ww})$ , vapor $(T_{vap})$ and enlighted absorber surface $(T_{abs})$ for test-1, test-2 and test-3 respectively.A rapid fall in enlighted absorber surface ( $T_{abs}$ ) was noticed during test-2 at 1345 hrs due to decrement in solar radiation at that particular time inetrval. The rate of formation of vapor was observed after 0800 hrs as englighted absorber surface ( $T_{Abs}$ ) temperature reaches (85.2 °C), wastewater $(T_{ww})$ temperaure was recorded as 70.7 °C and vapor $(T_{vap})$ tempertuare at that particular time was 71.4 °C for test-1. The increment in different temperature of system was observed early morning until 1400 hrs before declining with time. The highest englighted absorber surface ( $T_{Abs}$ ), wastewater ( $T_{ww}$ ) and vapor ( $T_{vap}$ ) temperature of 138.6 °C, 115 °C and 113.2 °C respectively were recorded at 1300 hrs. The highest enlightened absorber surface tempertaure ( $T_{abs}$ ) of 135.2 °C, wastewater temperature ( $T_{ww}$ ) of 113.2 °C and vapor temperature ( $T_{vap}$ ) of 112.9 °C was observed at 1400 hrs. The decrement in system temperture was observed after this point due to decrement in solar radiation. It was noteted that after this time,10°C decrease in all temperature of the system i.e. absorber surface tempertaure ( $T_{abs}$ ) of 123.1 °C, wastewater temperature ( $T_{ww}$ ) of 103 °C and vapor temperature ( $T_{vap}$ ) of 101.4 °C was observed at 1500 hrs.After this point temperatures profile of the system was observed to follow the decreasing order. The highest enlighted absorber surface temperature ( $T_{abs}$ ) of 140.0 °C, wastewater temperature ( $T_{ww}$ ) of 116.1 °C and vapor temperature ( $T_{vap}$ ) of 114.5 °C was observed at 1300 hrs for Test 3.

Figure 5.

Designed solar desalination temperatures, wind speed, ambient temperature and solar radiation during different tests (a) Test 1 (b) Test 2 (c) Test 3 (d) Test 4 (e) Test 5 (f) Test 6.

The same trend is followed during test-4, test-5 and test-6 respectively. The highest enlighted absorber surface ( $T_{abs}$ ) was recorded 125.5 °C, 137.5 °C and 141.4 °C for test-4, test-5 and test-6 respectively. Whereas, wastewater ( $T_{ww}$ ) temperature for test-4, test-5 and test-6 is reported as 118.7 °C, 117.3°Cand 119.8 °C respectively. And, highest vapor tempertaure ( $T_{vap}$ ) for test 4, test-5 and test-6 was recorded as 117.9 °C, 117 °C and 119.3 °C respectively.

The wind speed $(W_{S})$ , was observed and recorded during different tests. It has been found that wind speed doesnot significantly affect distillate output as solar radiation plays a major role in maintaing system temperature.Although, its impact is observed during test-2 but in present work the direct affect of wind speed is not accounted signifacntly. The wind speed ranges between 0.5–2.8 m/s, 0.9–5 m/s, 0.9–2.6 m/s, 0.7–3.1 m/s, 0.8–3 m/s and 0.6–3.9 m/s for test-1, test-2, test-3, test-4, test-5 and test-6 respecticely.

Distillate output/freshwater productivity for different tests

The main objective of the solar desalination (PCB-SDS) system is the production of portable water from industrial wastewater with maximum efficiency at low cost. Therefore, in present study with designed PCB-SDS,the variation in productivity (freshwater) at different depth with both type of wastewater is presented and discussed in this section.

The difference in freshwater production for all test cases is presented in Figure 6(a). Figure 6(a) indicate that the hourly production gradually increases from 0800 hrs until it reaches maximum between 1200–1400 hrs for different tests, before decreasing with time. The maximum hourly production rate was 970, 1040, 1050, 1110, 1060 and 1120 mL/hr during test-1, test-2, test-3, test-4, test-5 and test-6 respectively. Moreover, same trend has been observed during all tests in hourly fluctuations due to change in solar radiation intensity during that time period. It can be clearly observed from the figure that such situation occur in test-1 and test-4. This was due to decrement in solar radiation in the preceding hour as it decreased the absorber temperature which resulted in low evaporation temperature in next hour. The total daily distillate production for PCB-SDS was found minimum with test-1 and test-4, average productivity with test-2 and test-5, whereas the developed system gave maximum productivity with test-3 and test-6, which corrobates the temperatures at different depth as presented in Figure 5. This was due to the fact that after receiving solar radiation from concentrator at the lower surface of basin that results in high temperature.⁴ The low heat capacity was noted in low depth which resulted in low heat storage capacity whereas, higher water mass stores high energy. This results in high heat delivery to the water in absorber and resulted in high distillate yield. This was also due to the fact that on regular addition of water in basin with low water depth, require high heat to maintain boiling temperature whereas, with high depth this problem is rectify due to high heat storage. In comparison and as reported earlier low depth produces high distillate output.^32,33 Thus, author recommends that this system is suitable enough for utilization with high water mass which can be a solution in coming future for large industries. The figure also depict that the overall distillate productivity was lower with TDyWW due to low pollutant load than TDgWW. This reveals that depth of water in the absorber should always in between 50–60% of the total height of the absorber. Although, depth more than 60% also affects the output badly due to high initial start-up time of the system which leads to decrement in the efficiency.

Figure 6.

Evolution of the distillate output (a) hourly (b) accumulated with time for test-1, tes-2, test-3, test-4, test-5 and test-6.

Figure 7 present a cross-correlation between the total accumulated mass flow rate of distillate water in mL/day from designed PCB-SDS with textile industry wastewater and different test cases. Figure 6(b) confirms the highest distillate productivity from PCB-SDS actually increases significantly over increasing depth of wastewater. The maximum distillate yield was 8330 mL/day for test-6 from developed system was achieved. Moreover, minimum distillate water collected daily was achieved by (test-1) and was found to be 5485 mL/day.The review of some previous work with summary of their other efficiency is presented in Table 9. Comparing the concentrator type of solar desalination with the present study shows that PCB-SDS has quite good performance with a nearly equal time period. The parabolic dish based still produces 6112 mL/day whereas;³⁴ parabolic concentrator coupled single slope, solar still produces 3500 mL/day¹ and 6675 mL/h m² was produced from parabolic trough solar desalination system.³⁵ In order to compare other systems all the effective meteorological, geographical, and technical parameters are mandatory.

Figure 7.

Daily water distillate water (freshwater) production for different tests.

Efficiency of the system

In this particular section, assessment of the designed PCB-SDS based on energy, exergy and pollutant removal efficiency of the system is discussed. The assessment of the desalination system in terms of energy and exergy efficiency is an important parameter to develop and increase the system performance and decrease the losses. The pollutant removal efficacy of the system describes the capability of the system to be used in industry and the quality of water to match the high standards for future use in different applications

Energy efficiency

In this section, energy efficiency for eachtesthas beenevaluated and its variation with corresponding depth is presented through Figure 8. It can be seen that total energy efficiency of the developed system operated for 60% depth attained highest value of 51.93% for test-6. While for 40% and 20% depth the highest energy efficiency of 46.48% for test-5, 43.38% for test-4. The energy efficiency of the developed system operated for TDyWW and TDgWW was found best at depth of 60%. Thus, 60% depth is an optimum depth among selected depths for wastewater treatment. The lowest values of energy efficiency i.e. 39.83%, 45.69% and 49.45% were obtained for test-1 (20% depth), test-2 (40% depth) and test-3 (60% depth) respectively. It can be noticed that energy efficiency escalates progressively since morning till attaining its greatest value in mid afternoon and then starts declining gradually till sunset. It can be noticed that energy efficiency of the designed system increased with increase in depth of distillate output. It was because of higher energy storage capacity with higher depths. Figure 8 depicts that energy efficiency of developed system operated for 60% depth was higher in comparison of same system worked for 20% and 40% depth. It is due to the fact that high depth stores high energy in comparison to 20% and 40%. This can also be due to the change in absorber position according to sun direction while tracking. Low depth in basin does not allow much solar energy to transfereffectively as wastewater in basin is not uniform and changes frequently on changing the direction of dish and absorber according the sun.

Figure 8.

Comparison of average daily energy and exergy efficiency of designed PCB-SDS for different test cases (depths).

Exergy efficiency

The daily average exergy efficiency of the PCB-SDS for all test cases is illustrated in Figure 8. Exergy output for all test cases increases gradually to reach its utmost value in afternoon and again starts declining till it reaches zero in late evening. Figure 8 indicates that the daily average exergy efficiency of test-3 and test-6 was greater than the other test cases. Moreover, the daily average exergy of the PCB-SDS with test-6 was greater than test-3. Such findings can be attributed to the noticeable rise in absorber temperature and distillate output productivity as stated previously for the PCB-SDS with test-6 and accordingly enhances the evaporative exergy rate as compared to the designed system with test-5, test-4, test-3, test-2 and test-1. The daily average exergy efficiency of the PCB-SDS for test-1 and test-4 was 3.69% and 4.12% respectively and 4.25% and 4.42% for test-2 and test-5 respectively with an increase of about 4.59% and 4.8% for test-3 and test-6 respectively. However, the average exergy efficiency of the PCB-SDS for test-3 and test-6 was found maximum due to highest distillate output.

For better understanding, the abovementioned results, a breakdown of distillate output, energy and exergy efficiency of the designed system are presented through Table 9 with comparison from other previous literatures.

Pollutant removal efficiency

To determine the removal efficiency of the designed system both types of processed wastewater were passed through the designed solar still to determine the potentiality of system. The significant physio-chemical parameters including pH, TDS, COD and hardness for both process wastewaters are given in Table 4.

Table 4.

Pollutants reduction from dyeing wastewater (TDyWW) and degumming wastewater (TDgWW) at different depth ratio during test 1–6.

Parameters		Depth (%)
		20 (Test 1)		40 (Test 2)		60 (Test 3)
		Final	R*	Final	R*	Final	R*
Dyeing wastewater (TDyWW)
pH*	8.62 ± 0.16	7.13 ± 0.08	17.6	7.12 ± 0.08	17.7	7.12 ± 0.07	17.8
TDS	3884.7 ± 16.7	60.8 ± 5.9	98.4	28.04 ± 6.2	99.2	27.63 ± 0.05	99.2
COD	11363.4 ± 61.6	2590.5 ± 10.6	77.2	2545.8 ± 24.2	77.5	2218.8 ± 34.6	80.4
Hardness	1118.4 ± 55.6	14.48 ± 1.2	98.6	13.96 ± 1.7	98.7	13.27 ± 1.4	98.8
Degumming wastewater (TDgWW)
pH*	12.22 ± 0.15	7.91 ± 0.04	35.2	7.66 ± 0.06	37.3	7.46 ± 0.08	38.9
TDS	4755.1 ± 23.6	419.3 ± 4.6	91.1	406.59 ± 3.2	91.4	174.94 ± 4.5	96.3
COD	22367.3 ± 73.5	4541 ± 44.7	79.6	4413.2 ± 48.5	80.2	3438.7 ± 99.9	84.6
Hardness	1305.3 ± 24.2	126.84 ± 4.8	90.2	126.08 ± 4.6	90.3	120.67 ± 5.4	90.7

*Except pH, all values are in mg/L; R*= Reduction (%).

Results showed that both processed wastewater have positive removal efficiency in terms of selected parameters. Based on pH results for both wastewaters, it was found that the condensate quality meets the potable water (discharge water) quality and is depicted through Table 3.

The maximum removal of TDS was found with test-3 and test-6 i.e. 60% brine depth with both selected samples. The TDS in degumming wastewater decreased from 4755 mg/L to 419.3 mg/L. In dyeing wastewater, TDS decreased from 3885 mg/L to 27.6 mg/L.

Furthermore, COD for both types of wastewater was found that quality of output is not severely affected by input quality. This shows that the increase in input COD doesn’t affect the output values. It was observed that using designed solar still for the textile industry wastewater taken from source, the COD of the degumming wastewater decreased from 22367 mg/L to 3439 mg/L and that the COD of the dyeing wastewater decreased from 11363 mg/L to 2219 mg/L with test-3 and test-6 i.e. 60% brine depth. In both samples, it has been observed that the removal efficiency of COD is highest for both the wastewater (TDgWW and TDyWW) with test-3 and test-6 i.e. 60% brine depth. This shows that the system works more efficiently between 40–60% depth ratio (test-2, test-3, test-5 and test-6).

The hardness of the degumming wastewater decreased from 1305 to 120.7 mg/L at maximum side, whereas, for dyeing wastewater reduces from 1118 mg/L to 13.3 mg/L.

The removal efficiency of the heavy metals was also examined for both wastewaters. Because, it causes many health related issues like cancer, skin, allergic etc. Both wastewaters were examined before and after treatment in terms of heavy metal and found that designed system capable of removing heavy metal too from the wastewater. It was observed that heavy metal removal is maximum upto 90–95% for all the selected metals. The samples were digested before and after treatment before analysis through ICP, the reduction observed for both the wastewater i.e. TDgWW and TDyWW were given in Figure 9.

Figure 9.

Heavy metal removal efficiency for degumming and dyeing wastewaters after desalination.

Few researcheshas reported the treatment of textile industry wastewater through solar and algae as sustainable approach. And, reported with TDS, COD and other parameters removal with efficient reduction but when compared with the present study the efficiency is low. Manenti et al.⁵ treated the real textile industry dyeing wastewater with solar assisted advanced oxidation processes (AOP) and resulted with 69% reduction in COD. Pathak et al.,³⁶ worked with Chlorella pyrenoidosa an algal species for reduction of different parameters for dye removal and finds that 50% removal in TDS was reported after 15 days which is insignificant in compare with the present study. Pathak et al.,³⁷ in another study worked with the same algal species for textile wastewater and finds about 67.8% reduction in BOD, 85%, 81.6% and 36.3% reduction is find with total dissolved solids, nitrate and phosphate respectively. This is still low in compare with the present study. The present study when compared with different available literature (Table 5) find more effective than other renewable treatment system (solar or algal species). The reduction find with AOP is less and algal treatment of the wastewater requires more time as compared with the solar combined system.

Table 5.

Comparative analysis of wastewater parameters for textile industry with various renewable based techniques with current study.

S. No.	Wastewater	Treatment method	Parameter	Removal	Time required	Reference
1.	Textile (Dye)	Phycoremediation	pH	8.5	15 Days	³⁷
			TDS	85
			Alkalinity	56
			Phosphate	36.3
			Nitrate	81.6
			Chloride	86
2.	Textile (Dye)	Up flow packed bed bioreactor (Fungi based)	Decolorization	98.2	3 Days	³⁸
2.	Textile (Dye)	Up flow packed bed bioreactor (Fungi based)	COD	69.8	3 Days	³⁸
3.	Textile (Dye)	Solar PV-based Electrolysis	TDS	89.2	Several hours to Days	⁷
			COD	80.6
			Hardness	90.7
			Total Nitrogen	93.6
			Phosphorous	81.3
4.	Textile (Dye)	Solar Desalination	pH	7.12	In hours	Present study
			TDS	99.2
			COD	80.4
			Hardness	98.8
5.	Textile (Degumming)	Solar Desalination	pH	7.46	In Hours	Present study
			TDS	96.3
			COD	84.6
			Hardness	90.7

Hence, the treatment results showed that the system was capable enough for treatment of industrial wastewater and could be able to decrease the energy required during conventional treatment methods in less time.

Economic analysis

The economic analysis of any solar system is a major parameter in designing the system. The cost of any solar desalination system is entirely depending on the distillate output productivity. Hence, to analyse the economics behind the designed solar desalination system (cost analysis) is performed in this section. In this regard, it was concluded that selection of place of installation directly affects the overall system operation cost as well. The distillate output produced from designed PCB-SDS was usually considered as a function of variable cost. As, function of capital and amortization cost fixed cost of the system is calculated. It was found that there is relation between variable costs of the systems and operating and maintenance cost of the designed PCB-SDS.³⁹ The economic parameters are calculated on the basis of Indian situation and presented through Table 6.

Table 6.

Parameters for economic calculation of Indian markets.^30,40

S. No.	Parameters	Value
1.	Interest Rate, (i)	9%
2.	Life period, (n)	15 years
3.	Rate of inflation	3%
4.	Daily solar radiation (Average)	5.91 (kWh/m²/day)

The system was installed in Katra (Shri Mata Vaishno Devi University,), (J&K) India (Latitude 32.9915°N,Longitude 74.9318°E) where it was assumed that system operates and produce distillate output for 300 days in a year.⁴¹ Table 7 illustrate the cost investment for construction of PCB-SDS. Table 8 illustrate the detailed cost analysis of the designed PCB-SDS for distillate output in dollar per liter ($/L).

Table 7.

Capital cost investment of the designed PCB-SDS.

S. No.	Item	Cost (US $)
1.	Absorber Material	53.3
2.	Reflector (Concentrator)	66.6
3.	Adjustable Wheels	2.41
4.	DC Pump	2.4
5.	Heat Exchanger	2.13
6.	Pipes (Inlet, Outlet and Heat Exchanger)	18.66
7.	Valves	1.3
8.	Tanks (Inlet and Cooled water)	8
9.	Mild steel stand	33.3
10.	Insulation Material	1.6
11.	Paint	2.6
12.	Adjustable Ball	6.6
13.	Construction cost	40
14.	Miscellaneous	36.6
Total		275.5

Table 8.

Cost analysis of the designed PCB-SDS.

S. No.	Item	Cost (US $)
1.	Capital cost, (P)	275.5
2.	Salvage Value, (S)	55.02
3.	Capital Recovery Cost, (CRF)	0.12
4.	Sinking Fund Factor, (SFF)	0.034
5.	Fixed Annual Cost, (FAC)	34.17
6.	Annual Salvage Cost, (ASV)	1.36
7.	Annual Maintenance and Operating Cost, (AMC)	3.41
8.	Total Annual Cost, (TAC)	36.21
9.	Annual Fresh Water Productivity, (Liter)	2490
10.	Cost per Liter of Distillate Output, US $	0.014
11.	Pay Back Period	2.8 Years

Here, in this section while calculating the per liter distillate output production from PCB-SDS test-6 was taken into consideration due to high distillate output. The comparison between the present distillate output, efficiency in terms of energy and exergy with previous literature was illustrated through Table 9.

Table 9.

Comparison of the previous work and the present work.

S. No.	Solar desalination system	Total distillate output productivity (mL/m²/day)	Efficiency		Fresh water cost ($/Liter)	Reference
S. No.	Solar desalination system	Total distillate output productivity (mL/m²/day)	Energy	Exergy	Fresh water cost ($/Liter)	Reference
1.	Parabolic Concentrator based solar desalination system (PCB-SDS)	8330	51.83%	4.8%	0.21	Present Work
2.	Conventional solar still	4480	32.59%	2.2%	0.0211	Hassan³
3.	Tubular solar still with parabolic concentrator	3530	28.54%	---	0.024	Elashmawy³⁰
4.	Conventional solar Still with phase change material with mesh steel wool fiber (CSS-PCM-SWF)	3685	39.1%	13%	0.05	Yousef and Hassan⁴²
5.	Solar Still with parabolic trough collector	8530	22.96%	7.258%	0.0207	Hassan³
6.	Solar still with FPC-PTC-PLGB	6036	16.24%	---	0.22	Madiouli et al.⁴³

It was observed from present work that distillate output was high and cost was lower than the previously designed systems this was due to high solar radiation in Jammu and Kashmir region of India. The cost of per liter distillate output productivity is 0.014$ this was due high productivity, cheap material, construction and labours cost.

Conclusion

The performance of the concentrator based desalination system filled with textile industry wastewater has been experimentally investigated. Thus on the obtained results a conclusion can be drawn that solar desalination can prove to be economical and affective system for industrial wastewater treatment. Distillate output of the system was found to be in the range of 5485–8330 mL/Day. The energy and exergy efficiency varied in the range of 39.83–51.93% and 3.69–4.8% respectively.The processed wastewaters showed 80–85% COD removal efficiency, ≅90% TDS and hardness removal. The cost per liter of distillate output produced from designed PCB-SDS is found to be 0.014 $/L.

Challenges and future recommendation

The current experimental work is relatively unique in terms of using textile processing steps wastewater. There are many improvements which are needed to be integrated in the current system for improved efficiency and its application in real industry. According, to the present study following recommendations can be drawn for its usefulness in future applications:

The system should be integrated with advance tracking units with photovoltaic panels to fulfil required electrical power.

The reflector materials can be improved for much more reflectivity.

The system should be installed at the point of wastewater generation to reduce the dependency on conventional treatment plants and reduction in overall treatment cost.

Highlights

Performance of parabolic concentrator based solar desalination system was analysed

Real textile industry wastewater taken from was utilized for treatment

High depth shows increased distillate output productivity and removal efficiency

The energy and exergy efficiency varies in the range of 39.8-51.9% and 3.6-4.8%

Pollutant removal efficiency was obtained in range of 77-90%.

Footnotes

Declaration of conflicting interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Atin K Pathak

VV Tyagi

Atin K Pathak received his M. Tech Energy and Environment Engineering from Baba Saheb Bhimrao Ambedkar University, Lucknow, India in 2015. He is recipient of DST-INSP IRE (JRF and SRF) under the Inspire fellowship scheme from DST, GoI. At present, he is working on the following research topics: the wastewater treatment through solar energy, wastewater treatment technologies and bioenergy. He is pursuing his Ph. D. from School of Energy Management, Shri Mata Vaishno Devi University, Katra, J&K, India.

VV Tyagi is working as Head, School of Energy Management, Shri Mata Vaishno Devi University, Katra, J&K, India. He is actively working in the research area of Solar Thermal Energy Storage Systems, Phase Change Materials Development & Applications, Solar Wastewater Treatment systems, Energy Policy and P V/Thermal Hybrid Systems. He did his Ph. D. from School of Energy & Environment Studies (SEES), Devi Ahilya University, Indore (M.P.), India and further worked as a Post Doctorate Research Fellow at different places (UMP EDAC, University of Malaya, Malaysia; Centre for Energy Studies, Indian Institute of Technology, Delhi, India and National Institute of Solar Energy (NISE), Ministry of New and Renewable Energy (Govt. of India)). He has published more than 130 research papers in reputed peer reviewed SCI International Journals and Invited as a keynote speaker in National/International conferences. Dr. Tyagi has more than 12500 citations of his published research papers with 35 h-index in his credit. He is also supervising several numbers of students at Master and Ph.D. level. He is also serving as an editorial board member for six reputed International Journals.

Sanjeev Anand is working as Assistant Professor at School of Energy Management, Shri Mata Vaishno Devi University, Katra, J&K, India. He received his Ph. D. from School of Energy Management, Shri Mata Vaishno Devi University, Katra, J&K, India. His area of research is energy efficiency of building, heat and mass transfer, energy and exergy analyses and has many publications in the conferences and journal of international repute. He is life member of Solar Energy Society of India and member of Indian Society of Heating Refrigeration and Air conditioning Engineers and ASHRAE. He is supervising more than twenty five students at Master and 03 students at Ph.D. level.

Richa Kothari is the Associate Professor at Department of Environmental Sciences, Central University of Jammu, Jammu, (J&K), India. She is WARI Fellow (IUSST F) at Robert B. Daugherty Water for Food Institute, University of Nebraska-Lincoln, Lincoln, USA. She has more than 15 years of teaching and research experience at Amity University, Noida (U.P.), Babasaheb Bhimrao Ambedkar University (Central University), Lucknow (U.P.). Dr. Kothari has been actively involved in research in the areas of algal-based biofuel production, biohydrogen production and utilization of renewable energy for wastewater treatment. She is also recipient of prestigious research fellowship from Ministry of New and Renewable Energy (MNRE) and Council of Scientific and Industrial Research (CSIR). Dr. Kothari has published more than 90 research papers/book chapters in reputed international peer-reviewed (SCI/Scopus) journals with high impact factor and supervised several M.Sc., M.Phil., M.Tech. and Ph.D. students. She has written a textbook titled Environmental Science for Undergraduates and edited three books i.e. Emerging Energy Alternatives for Sustainable Environment (2016), Environmental Biotechnology: For Sustainable Future (2019) and Algal Biofuel: Sustainable Solution (2020) and with National and International publishers. She has more than 3305 citations with h-index 23 and i-10 index 37. She also guided 05 research students and 04 are in process. She also guided more than 60 post-graduate students of M.Sc. and M.Tech. She is also the editorial board member for well reputed SCI/Scopus journals. She has delivered several keynote/invited lectures at different countries (Malaysia, South Africa, USA, India).

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