3.1 Textile wastewater characterization
The Physico-chemical characterization of textile wastewaters was done by the standard protocol given in APHA manual. Sample was collected with method of discrete sampling at different location from Textile industry in or near Varanasi, India. The result of textile wastewater characterization conferred in Table 1 indicates that values of pH, colour, temperature, total dissolved solid (TDS), total suspended solid (TSS), alkalinity (Carbonate), total nitrogen(ammonia), total nitrogen (Nitrate), total Phosphorus, Biological oxygen demand (BOD), Dissolved oxygen(DO) and Chemical oxygen demand (COD). BOD content is high (67.2 mg/L) in the case of acid orange textile wastewater and in all the textile dyes the nitrogen content (ammonia + nitrate) is low. Table 3 shows that the values of pH, TSS, TDS, Nitrogen (ammonia) and Phosphorus (phosphate) found for acid yellow wastewater used in this study were 8.1, 63 mg/L, 120 mg/L, 0.32 mg/L and 1.4 mg/L. However, COD and BOD are 296 mg/L and 28.8 mg/L respectively. The values of pH, TSS, TDS, Nitrogen (ammonia) and Phosphorus (phosphate) obtained for acid yellow wastewater used in this study were 8.2, 74 mg/L, 132 mg/L, 0.18 mg/L and 3.8 mg/L. However, COD and BOD are 288 mg/L and 33.6 mg/L respectively. The values of pH, TSS, TDS, Nitrogen (ammonia) and Phosphorus (phosphate) obtained for acid orange wastewater used in this study were 8.1, 43 mg/L, 135 mg/L, 0.38 mg/L and 2.3 mg/L. However, COD and BOD are 272 mg/L and 67.2 mg/L respectively.
Table 1: Physicochemical characterization of textile wastewater (Acid Yellow, Acid Orange and Basic pink dye).
S.N.
|
Parameter
|
Acid Yellow 17 dye
|
Acid Orange 7 Dye
|
Basic Pink Dye
|
1.
|
Colour(660nm)
|
Yellow (0.024)
|
Orange (0.032)
|
Dark Pink (0.045)
|
2.
|
pH
|
8.1
|
8.1
|
8.2
|
3.
|
Temperature
|
350C
|
350C
|
380C
|
4.
|
Total suspended solids
|
63mg/L
|
43mg/L
|
74mg/L
|
5.
|
Total dissolved solids
|
120mg/L
|
135mg/L
|
132mg/L
|
6.
|
Alkalinity(carbonate)
|
69.6mg/L
|
52.8mg/L
|
76.8 mg/L
|
7.
|
Nitrogen (ammonia)
|
0.32mg/L
|
0.38mg/L
|
0.18mg/L
|
8.
|
Nitrogen (Nitrate)
|
0.85mg/L
|
0.12mg/L
|
0.225mg/L
|
9.
|
Phosphate
|
1.4mg/L
|
2.3mg/l
|
3.8mg/L
|
10.
|
Dissolved oxygen
|
10.8mg/L
|
16mg/L
|
12.8mg/L
|
11.
|
BOD
|
28.8mg/L
|
67.2mg/L
|
33.6mg/L
|
12.
|
COD
|
296mg/L
|
272mg/L
|
288mg/L
|
Table 2: RSM table of Raw Material optimization for Chlorella Pyrenoidosa
|
Factor 1
|
Factor 2
|
Factor 3
|
Factor 4
|
Response 1
|
Response 2
|
Response 3
|
Response 4
|
Run
|
A:pH
|
B:Carbon Source
|
C:Nitrogen Source
|
D:Wastewater%
|
Biomass Productivity
|
Colour Removal
|
Nitrogen Removal
|
Phosphorus removal
|
|
|
g/L
|
g/L
|
|
g/L/day
|
%
|
%
|
%
|
1
|
5
|
0.4
|
0.2
|
20
|
0.58
|
41
|
71
|
42
|
2
|
11
|
0.4
|
0.2
|
20
|
0.61
|
42
|
72
|
44
|
3
|
8
|
0.3
|
0.65
|
40
|
0.89
|
60
|
88
|
59
|
4
|
5
|
0.2
|
0.2
|
20
|
0.66
|
48
|
75
|
48
|
5
|
5
|
0.4
|
0.5
|
60
|
0.78
|
58
|
85
|
59
|
6
|
5
|
0.4
|
0.5
|
20
|
0.98
|
62
|
89
|
63
|
7
|
2
|
0.3
|
0.35
|
40
|
0.41
|
42
|
70
|
45
|
8
|
5
|
0.2
|
0.2
|
60
|
0.64
|
51
|
79
|
53
|
9
|
8
|
0.3
|
0.05
|
40
|
0.86
|
54
|
80
|
52
|
10
|
14
|
0.3
|
0.35
|
40
|
0.38
|
35
|
60
|
36
|
11
|
8
|
0.3
|
0.35
|
40
|
1.2
|
72
|
98
|
70
|
12
|
8
|
0.3
|
0.35
|
0
|
0.19
|
30
|
60
|
29
|
13
|
11
|
0.2
|
0.5
|
20
|
0.52
|
46
|
73
|
47
|
14
|
8
|
0.3
|
0.35
|
40
|
1.34
|
69
|
95
|
70
|
15
|
5
|
0.2
|
0.5
|
60
|
0.59
|
45
|
71
|
44
|
16
|
11
|
0.4
|
0.2
|
60
|
0.66
|
48
|
70
|
47
|
17
|
11
|
0.2
|
0.2
|
20
|
0.71
|
51
|
80
|
54
|
18
|
5
|
0.2
|
0.5
|
20
|
0.65
|
48
|
73
|
48
|
19
|
11
|
0.2
|
0.5
|
60
|
0.59
|
44
|
71
|
44
|
20
|
11
|
0.4
|
0.5
|
60
|
0.56
|
43
|
69
|
43
|
21
|
8
|
0.5
|
0.35
|
40
|
0.99
|
65
|
91
|
66
|
22
|
8
|
0.3
|
0.35
|
40
|
1.1
|
69
|
94
|
70
|
23
|
8
|
0.1
|
0.35
|
40
|
0.7
|
64
|
92
|
62
|
24
|
8
|
0.3
|
0.35
|
40
|
1.26
|
68
|
95
|
69
|
25
|
5
|
0.4
|
0.2
|
60
|
0.66
|
49
|
76
|
50
|
26
|
11
|
0.2
|
0.2
|
60
|
0.65
|
48
|
74
|
51
|
27
|
8
|
0.3
|
0.35
|
80
|
0.59
|
43
|
71
|
45
|
28
|
11
|
0.4
|
0.5
|
20
|
0.56
|
41
|
69
|
40
|
29
|
8
|
0.3
|
0.35
|
40
|
0.98
|
64
|
91
|
65
|
30
|
8
|
0.3
|
0.35
|
40
|
1.4
|
71
|
97
|
72
|
Table 3: Removal efficiency of pollutant in three types of textile
Parameter
|
Removal Efficiency in Acid Yellow dye (%)
|
Removal Efficiency in
Acid Orange Dye (%)
|
Removal Efficiency in
Basic Pink Dye (%)
|
Nitrogen (ammonia)
|
91±3%
|
90±3%
|
91±1%
|
Phosphate
|
65±2%
|
60±1%
|
63±1%
|
COD
|
91±1%
|
94±2%
|
90 ±2%
|
Color removal
|
65±2%
|
59±5%
|
55±5%
|
3.2. Microalgae growth optimization and Kinetics Study
The microalgae culture was inoculated in the shake flask (250 ml) under light control for 10 days and allowed for the growth in Batch Mode operation, after that the growth and Biomass content is calculated. The graph of 2(a) shows the growth kinetics curve for the Chlorella pyrenoidosa, the results obtained by cultivating the Chlorella pyrenoidosa in the Bolds basal media (BBM). Lag phase occurred for 3 days and log phase occurred for 7 days for the Chlorella pyrenoidosa. The growth constant (µ) is 0.21 g/L/day and maximum growth rate constant (µmax) is 0.29 g/L/day.
Growth curve (Fig. 2(b)) of Chlorella pyrenoidosa in Acid yellow 17 dye, Acid orange 7 dye and Basic pink dye textile wastewater in composition of 10% of wastewater and BBM 90%, the biomass productivity is 0.98 ± 0.3 g/L/day, 0.96 ± 0.2 g/L/day, 1.2 ± 0.3 g/L/day respectively. As the nitrogen content is textile wastewaters is very low and the for the microalgae growth nitrogen content is very important, hence different types of nitrogen source is used like sodium Nitrate (NaNO3), ammonium nitrate (NH4NO3), ammonium chloride (NH4Cl) and urea (NH2CONH2) in the concentration 0.2 g/L, 0.4 g/L,0.4 g/L and 0.2 g/L respectively. The biomass productivity is 0.75 ± 0.2 g/l/day in all the sources showed in Fig. 2(c). Hence nitrogen content is enriched by urea. Urea is low cost source having the high biomass productivity. The physicochemical characteristics of textile wastewater is highly fluctuating but it is comparable and within range as reported [8]. However, the components of textile wastewaters vary as per the raw materials and ingredients used in textile manufacturing. Nitrogen (Ammonia) and Nitrogen (Nitrate) in textile wastewaters are generally low, hence external nitrogen source is required. Low Nitrogen content has an added advantage as it enhances the lipid productivity in the Microalga biomass but low nitrogen content also affects the growth of microalgae. The urea is best nitrogen source for the textile wastewater as it is cheap and easily available. The maximum biomass density 0.79 g/l/day found in the case of Ammonium nitrate (NH4NO3). Similarly, the carbon source is also optimized using different carbon source like Sodium carbonate (Na2CO3), Sodium bi-carbonate (NaHO3), and Potassium Bi-carbonate (KHO3), the biomass productivity is 0.4 ± 0.1, 0.2 ± 0.05, 0.2 ± 0.05 g/L/day respectively. The maximum biomass productivity found in the case of sodium carbonate (Fig. 2(d)).
The biomass concentration of algae reaches to approximately 6 g/l by around 8th day after having a lag phase of 2 days from the day of inoculation in BBM while in the textile wastewaters (Acid yellow, Acid orange and Basic pink) when inoculated by the acclimatized algal species operated for 10 days monitoring the algal growth, in 20% dyes mixed with 10% BBM, the graph elevated to maximum of around 1 g/l biomass concentration on 8th day for pink dye treatment and around 10 g/l biomass concentration on around 8th day of yellow and orange dye which shows a significant increase in growth compared to BBM only. Biomass concentrations were optimized by various nitrogen sources where a number of nitrogen sources were exposed with algae for comparative analysis. The biomass concentrations were found increasing with NH4NO3 in comparison to NaNO3, NH4Cl and Urea but it was interesting to find out that Urea which did not show rise in graph initially (lag phase is long) but showed significant growth during log phase, not only this Urea is found to be the most cheapest Nitrogen source to be used (around 10 Rs/ kg) and very easily available. Amongst the various Carbon sources used for optimization, Sodium bicarbonate was found showing maximum biomass concentration 3.5 g/l on 5th day which was considerably higher with respect to Sodium Carbonate and Potassium bicarbonate with biomass concentration of 2 g/l on 5th and 6th day respectively.
3.3. Statistical Optimization Study
ANOVA model is calculated for biomass productivity, The Model F-value of 9.68 implies the model is significant. P-values estimated 0.0001 which is not as much as 0.0500 designate significance of model terms. Relative to the pure error, the Lack of Fit F-value of 0.50 implies that Lack of Fit is not significant. The Predicted R² of 0.6404 is in realistic agreement with the adjusted R² of 0.8073; i.e. the alteration is a reduced amount from 0.2. Precision measures the signal to noise ratio. It is desirable to get a ratio greater than 4. The obtained proportion of 9.623 specifies a signal which is adequate. ANOVA model is calculated for colour removal, the Model F-value of 20.64 indicates the model is significant. P-values found 0.0001 which is a lesser amount of 0.0500 point towards the significance of model terms. Relative to the pure error the Lack of Fit F-value of 1.98 indicates the Lack of Fit is not significant. The Predicted R² of 0.7561 is in reasonable agreement with the Adjusted R² of 0.9035; i.e. the difference is less than 0.2. Adeq Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. The obtained ratio of 14.205 indicates an adequate signal. ANOVA is calculated for Nitrogen removal, The Model F-value of 17.25 suggests the significance of the model. P-values calculated 0.0001 which is a smaller amount than 0.0500 indicates the significance of model terms. Relative to the pure error the Lack of Fit F-value of 3.02 indicates that the Lack of Fit is not significant. The Predicted R² of 0.6991 is in rational agreement with the Adjusted R² of 0.9035; i.e. the variance is less than 0.2. Adeq Precision processes the signal to noise ratio. A ratio more than 4 is desirable. The obtained proportion of 13.65 designates signal which is adequate. ANOVA is calculated for Phosphorus removal, The Model F-value of 16.87 infers the model is significant. The significance of the model terms is indicated by P-values found 0.0001 which is less than 0.0500. Relative to the pure error the Lack of Fit F-value of 3.67 implies the Lack of Fit is not significant. The Predicted R² of 0.7561 is in judicious agreement with the Adjusted R² of 0.69; i.e. the variance is less than 0.2. Adeq Precision processes the signal to noise ratio. A ratio heigher than 4 is desirable. The obtained proportion of 13.02 indicates an adequate signal.
Then optimized value for various parameter like pH, carbon source, Nitrogen source and wastewater % used for the biomass productivity, colour removal, Nitrogen removal, and Phosphorus removal are 8.431 ± 0.6, 0.29 ± 0.1 g/L, 0.2 ± 0.05 g/L and 38.90 ± 5% respectively. Obtained optimized results for biomass productivity, colour removal, Nitrogen removal, Phosphorus removal are 1.13 ± 0.2 g/L/Day, 65 ± 2%, 91 ± 3%, 65 ± 1% respectively as given the figure( 3 ).
Surface plots obtained from the RSM optimization for biomass productivity with correlation effect of Carbon source and pH, Nitrogen Source and pH, wastewater% and pH, Carbon Source and Nitrogen Source, wastewater% and Carbon source and Wastewater% and Nitrogen source are represented in the figure (4). The optimized value of pH, carbon source, Nitrogen source and wastewater % are 8.431 ± 0.6, 0.29 ± 0.1 g/L, 0.2 ± 0.05 g/L and 38.90 ± 5% respectively.
Surface plots obtained from the RSM optimization for Colour removal efficiency% with correlation effect of Carbon source and pH, Nitrogen Source and pH, wastewater% and pH, Carbon Source and Nitrogen Source, wastewater% and Carbon source and Wastewater% and Nitrogen source are represented in the figure (5). The optimized value of pH, carbon source, Nitrogen source and wastewater % are 8.431 ± 0.6, 0.29 ± 0.1 g/L, 0.2 ± 0.05 g/L and 38.90 ± 5% respectively.
Surface plots obtained from the RSM optimization for Nitrogen removal efficiency % with correlation effect of Carbon source and pH, Nitrogen Source and pH, wastewater% and pH, Carbon Source and Nitrogen Source, wastewater% and Carbon source and Wastewater% and Nitrogen source are represented in the figure (6). The optimized value of pH, carbon source, Nitrogen source and wastewater % are 8.431 ± 0.6, 0.29 ± 0.1 g/L, 0.2 ± 0.05 g/L and 38.90 ± 5%
Surface plots obtained from the RSM optimization for Phosphorus removal efficiency % with correlation effect of Carbon source and pH, Nitrogen Source and pH, wastewater% and pH, Carbon Source and Nitrogen Source, wastewater% and Carbon source and Wastewater% and Nitrogen source are represented in the figure (7).
The optimized value of pH, carbon source, Nitrogen source and wastewater % are 8.431 ± 0.6, 0.29 ± 0.1 g/L, 0.2 ± 0.05 g/L and 38.90 ± 5% respectively.
3.4. Analysis of pollutant removal
Potential of microalgae in degrading specific pollutants are being studied. Microalgae has been reported for degradation of large number of micropollutants, p-chlorophenol collected from a site where water contaminated with a number of aromatic pollutants can be degraded at a rate of 10 mg/L/day by Chlorella vulgaris and Coenochloris pyrenoidosa[9].
The analysis of parameters including COD, ammonia, colour and phosphorus were examined with respect to the methodology described in APHA (2000) at the beginning as well as at the end of the run. The composition contained by textile wastewater are found to be complicated containing heavy metals [10], dyes, salts [11] and reagents [12]. Many procedures have been employed absorption with activated carbon, ion exchange, electrochemical destruction, and filtration by membrane, ozonation and irradiation [13]. Cultivation of algae in textile effluents uses carbon, nitrogen and phosphorous and other nutrients for its growth. During the process of bioconversion, the microalgae uses dyes and CO2 as their carbon sources and finally transform them into metabolites moreover these algae can equally be employed as bio sorbent as the dyes hold the potential to absorb onto their surface.
As can be seen in the graph shown in Fig. 8 (a) COD concentration was ranging from 250–300 mg/L for all the three dyes i.e. acid yellow, acid orange and basic pink on day 0 but as the growth continues a steady fall in the graph can be seen, as soon as it reaches the 8th day the COD level drops down to 50 mg/L which shows that Chlorella pyrenoidosa is efficient enough to remove COD. On the contrary when the same study was performed with phosphorus, the level of phosphorus in acid yellow and acid orange was around 2.5 mg/L while in basic pink it was around 4.0 mg/L way higher than the other two but as the growth reaches between 4 to 6 days the graph falls down to 1.0 mg/L which confirms the efficiency of the alga in removing phosphorus as can be seen in Fig. 8 (b). Figure 8 (c) shows removal of ammonia where the level for the three dyes having ammonia were as high as 14–16 mg/L which experiences a steep fall in the graph and falls down to 2 mg/L at around 8th day of inoculation. The removal of colour was studied for the three dyes which were ranging from 0.09 to 0.10 on the day 0 but the intensity of colour was significantly decreased to the level of 0.05 on the fifth day and fell down to 0.04 on the 9th day of inoculation confirming the ability of Chlorella pyrenoidosa in removing colour of the dyes successfully.
The efficiency of nitrogen (ammonia) removal, Nitrogen (nitrate) removal, COD removal, colour removal, and phosphorus removal in three types textile wastewaters (acid yellow dye containing textile wastewater, acid orange dye containing textile wastewater, basic pink dye containing textile wastewater) is explained in the form of bar chart given in figure (9).
A very little variation in nitrogen (ammonia) removal efficiency in acid yellow dye containing textile wastewater (91 ± 3%), acid orange dye containing textile wastewater (90 ± 3%), and basic pink dye containing textile wastewater (91 ± 1%). A small variation found in nitrogen (Nitrate) removal efficiency in acid yellow dye containing textile wastewater (79 ± 2%), acid orange dye containing textile wastewater (68 ± 3%), and basic pink dye containing textile wastewater (70 ± 4%).
A very little or negligible variation in Phosphate removal reported, efficiency in acid yellow dye containing textile wastewater (65 ± 2%), acid orange dye containing textile wastewater (60 ± 1%), and basic pink dye containing textile wastewater (63 ± 1%). However a minor variation in COD removal efficiency in acid yellow dye containing textile wastewater (91 ± 1%), acid orange dye containing textile wastewater (94 ± 2%), and basic pink dye containing textile wastewater (90 ± 2%). A small decrease observed in color removal efficiency in acid yellow dye containing textile wastewater (65 ± 2%), acid orange dye containing textile wastewater (59 ± 5%), and basic pink dye containing textile wastewater (55 ± 5%) respectively.
The efficiency of nitrogen (ammonia) removal, Nitrogen (nitrate) removal, COD removal, colour removal, and phosphorus removal in three types textile wastewaters (acid yellow dye containing textile wastewater, acid orange dye containing textile wastewater, basic pink dye containing textile wastewater) is explained in the form of bar chart given in Table (3).