Abstract

Microcystis spp. is the most common and problematic species during cyanobacterial bloom. This study employed Microcystis aeruginosa for coagulation experiments. Effects of polyaluminum chloride (PAC), cationic polyacrylamide (CPAM), and pH value on cyanobacterial removal at exponential and decline phases by coagulation were investigated by measuring chlorophyll a. A mathematical model between factors and response variables was established using response surface methodology (RSM). Results showed that factors of CPAM dosage, PAC dosage, and pH value could strongly affect the removal ratio of Microcystis at both exponential and decline phases. RSM revealed that the order of influence factors on the removal of chlorophyll a was CPAM > PAC > pH for Microcystis at the exponential phase, and these orders of CPAM > PAC > pH (PAC coagulation) and CPAM > PAC > pH (CPAM coagulation) were for Microcystis at the decline phase. It suggested that the growth phase of cyanobacteria was also quite important to optimize the coagulation process. Besides, a fitted model was developed, and it could well predict the removal ratio of chlorophyll a by coagulation with various treatments. The model recommended dosages of CPAM (3.72 mg/L) and PAC (10.23 mg/L) for Microcystis at the exponential phase with a pH value of 8.25, and dosages of CPAM (5.98 mg/L) and PAC (17.81 mg/L) were for Microcystis at the decline phase with a pH value of 8.21. Overall, these results would provide a technical guideline of combining PAC and CPAM to treat cyanobacteria at exponential and decline phases.

HIGHLIGHTS

  • Effects of PAC, CPAM, and pH differed for Microcystis at exponential and decline phases.

  • Interaction between PAC and CPAM dosages was significant during coagulation.

  • Fitted models could well predict the actual removal ratio of Microcystis by coagulation.

  • The removal ratio of Microcystis reached 82.49–94.38% with optimized dosages of PAC and CPAM.

INTRODUCTION

Cyanobacterial bloom has become one of the major environmental problems in lakes and reservoirs worldwide (Liu & Yang 2012; O'Neil et al. 2012). In recent years, many countries have reported that the occurrence of cyanobacterial blooms in resource waters posed a problem for the safety of drinking water. For example, a severe Microcystis bloom broke out in Taihu Lake (China) in 2007, resulting in a water crisis for 2 million residents (Zhang et al. 2010). In 2014, toxic cyanobacterial bloom also occurred in Erie Lake (America), and more than 60 people became sick after swallowing the polluted drinking water (Wolf et al. 2017).

In drinking water treatment plants, coagulation is a common treatment to remove cyanobacterial cells in resource waters. Iron salts (e.g., ferric sulfate) or aluminum salts (e.g., aluminum sulfate) are often used as common coagulants to remove cyanobacterial cells (Gonzalez-Torres et al. 2014). In comparison with these common inorganic flocculants, polyaluminum chloride (PAC) is an inorganic polymer flocculant with a large molecular weight, and thus, it has a better flocculating performance attributed to its strong capacity of adsorption and interparticle bridging. Besides, cationic polyacrylamide (CPAM) is an organic macromolecular polymer to aid the coagulation process even with a low dosage, but its high cost always limits application. In recent years, combining PAC and CPAM has been employed in sludge dewatering (Ma et al. 2013; Wang et al. 2019; Wu et al. 2019), microplastics (Zhou et al. 2020), landfill leachate (Shen et al. 2014), slightly polluted source waters (Zhou et al. 2012; Hu et al. 2014), pickle wastewater treatment (Yang et al. 2017), and flue-gas desulfurization wastewater (Zhao 2019). However, there are few reports on cyanobacterial removal by combining PAC and CPAM to improve cyanobacterial removal by coagulation.

When a successive cyanobacterial bloom broke out in resource waters, pH would rise and it even reached 9–10 during cell growth (Visser et al. 2016). Compared with cyanobacteria at the exponential phase, cell viability would strikingly decline, and cellular structures (e.g., gas vesicles and photosynthetic apparatus) were destroyed at the decline phase (Li et al. 2020). Besides, the concentration of extracellular organic matter (EOM) became increased, and its composition was also changed (Henderson et al. 2008; Leloup et al. 2013; Pivokonsky et al. 2014; Li et al. 2020). These changed factors may affect cyanobacterial removal by coagulation. Consequently, in this study, cyanobacteria at exponential and decline phases were prepared for coagulation experiments. Effects of CPAM dosage, PAC dosage, and pH value on cyanobacterial removal were investigated by measuring chlorophyll a. Additionally, a quadratic polynomial mathematical model was established by the response surface design method, aiming to provide a detailed guideline of combining PAC and CPAM to treat cyanobacteria-laden waters.

MATERIALS AND METHODS

Cyanobacterial culture

Microcystis aeruginosa FACHB-915 was purchased from the Institute of Hydrobiology, Chinese Academy of Sciences. It was cultured in BG11 medium at 28 °C under constant light flux (35 μmol/m·s) with a 12:12 h light–dark cycle in an incubation cabinet equipped with a cold light source, light-emitting diode (GXZ-280C; China), as described in Li et al. (2020). Microcystis cells at exponential and decline phases were prepared for coagulation experiments. Prior to coagulation, cyanobacterial solutions were carried out with a dilution of 1:3, and associated water quality parameters are shown in Table 1.

Table 1

Water quality parameters of Microcystis solutions

ParametersExponential phaseDecline phase
Culture time (days) 25–30 65–70 
Cell density (cells/L) 0.9 × 106–1.5 × 106 2.9 × 106–3.5 × 106 
pH 8.2 ± 0.2 9.2 ± 0.2 
Chlorophyll a content (μg/L) 45.0 ± 2.0 74.0 ± 3.0 
Phycocyanin (μg/L) 2,100 ± 100 3,800 ± 150 
Turbidity (NTU) 110 ± 2.0 170 ± 5.0 
ParametersExponential phaseDecline phase
Culture time (days) 25–30 65–70 
Cell density (cells/L) 0.9 × 106–1.5 × 106 2.9 × 106–3.5 × 106 
pH 8.2 ± 0.2 9.2 ± 0.2 
Chlorophyll a content (μg/L) 45.0 ± 2.0 74.0 ± 3.0 
Phycocyanin (μg/L) 2,100 ± 100 3,800 ± 150 
Turbidity (NTU) 110 ± 2.0 170 ± 5.0 

Reagents and instruments

PAC (Al2O3 > 28%, Sinopharm reagent) was prepared as a stock solution with a concentration of 5.0 g/L, and it was diluted to a 500 mg/L solution for coagulation experiments. CPAM (molecular weight of 12 million, ion degree of 15%) was purchased from a company (Tianjin Dingshengxin Chemical Co. Ltd) and prepared as a stock solution with a concentration of 2.50 g/L. Then, it was diluted to 500 mg/L for coagulation experiments. Additionally, a flow cytometry (FACS Verse, USA), ultrapure water (Millipore Pty Ltd, USA), a fluorometer (FluoroQuik, USA), and a desktop pH meter (UTO, China) were also employed for experiments.

Experimental protocols

A cyanobacterial solution of 50 mL was transferred into a 100 mL conical flask, and its pH value was adjusted to 6.2–10.2 using 0.1 mol/L NaOH and 0.1 mol/L HCl. Coagulation experiments were carried out with magnetic stirring at the same temperature of 22 ± 2 °C. Various dosages of PAC (2.0–40.0 mol/L) were added to the cyanobacterial solution with rapid mixing at specific intervals. Then, CPAM (1.2–20 mol/L) was added, and these solutions were stirred continuously during the coagulation process (250 rpm/min, 1 min; 150 rpm/min, 4 min; 50 rpm/min, 15 min) with six magnetic agitators and kept motionless for 40 min. Finally, Microcystis samples were taken for the measurements of chlorophyll a. A total of 17 treatment matrices were conducted based on single-factor experiments and selected three influencing factors such as CPAM dosage, PAC dosage, and pH value. High and low levels were determined by the response value, and then these experiments were performed using the Box–Behnken design (BBD) form (Tables 2 and 3). Finally, response surface methodology (RSM) was employed to analyze these experimental data.

Table 2

Variables and levels for BBD experimental design

EncodingExponential phase
Decline phase
FactorsLevel
FactorsLevel
− 101− 101
A CPAM (mg/L) 1.2 3.0 4.8 CPAM (mg/L) 4.0 6.5 9.0 
B PAC (mg/L) 5.0 9.0 13 PAC (mg/L) 10.0 15.0 20.0 
C pH 7.2 8.2 9.2 pH 7.2 8.2 9.2 
EncodingExponential phase
Decline phase
FactorsLevel
FactorsLevel
− 101− 101
A CPAM (mg/L) 1.2 3.0 4.8 CPAM (mg/L) 4.0 6.5 9.0 
B PAC (mg/L) 5.0 9.0 13 PAC (mg/L) 10.0 15.0 20.0 
C pH 7.2 8.2 9.2 pH 7.2 8.2 9.2 
Table 3

BBD experimental design and results

Serial no.Removal ratio of chlorophyll a (%)
Exponential phase
Decline phase
Level
Measurement resultsLevel
Measurement results
ABCABC
1.2 5.0 8.2 28.78 4.0 10.0 8.2 31.43 
4.8 5.0 8.2 54.49 9.0 10.0 8.2 38.99 
1.2 13.0 8.2 35.56 4.0 20.0 8.2 83.67 
4.8 13.0 8.2 75.56 9.0 20.0 8.2 92.36 
1.2 9.0 7.2 38.44 4.0 15.0 7.2 49.25 
4.8 9.0 7.2 42.22 9.0 15.0 7.2 47.62 
1.2 9.0 9.2 16.22 4.0 15.0 9.2 46.46 
4.8 9.0 9.2 56.11 9.0 15.0 9.2 67.54 
3.0 5.0 7.2 53.33 6.5 10.0 7.2 29.05 
10 3.0 13.0 7.2 46.76 6.5 20.0 7.2 89.52 
11 3.0 5.0 9.2 27.89 6.5 10.0 9.2 46.61 
12 3.0 13.0 9.2 52.22 6.5 20.0 9.2 87.74 
13 3.0 9.0 8.2 78.00 6.5 15.0 8.2 82.12 
14 3.0 9.0 8.2 79.20 6.5 15.0 8.2 81.71 
15 3.0 9.0 8.2 85.44 6.5 15.0 8.2 83.66 
16 3.0 9.0 8.2 78.58 6.5 15.0 8.2 82.79 
17 3.0 9.0 8.2 78.83 6.5 15.0 8.2 82.01 
Serial no.Removal ratio of chlorophyll a (%)
Exponential phase
Decline phase
Level
Measurement resultsLevel
Measurement results
ABCABC
1.2 5.0 8.2 28.78 4.0 10.0 8.2 31.43 
4.8 5.0 8.2 54.49 9.0 10.0 8.2 38.99 
1.2 13.0 8.2 35.56 4.0 20.0 8.2 83.67 
4.8 13.0 8.2 75.56 9.0 20.0 8.2 92.36 
1.2 9.0 7.2 38.44 4.0 15.0 7.2 49.25 
4.8 9.0 7.2 42.22 9.0 15.0 7.2 47.62 
1.2 9.0 9.2 16.22 4.0 15.0 9.2 46.46 
4.8 9.0 9.2 56.11 9.0 15.0 9.2 67.54 
3.0 5.0 7.2 53.33 6.5 10.0 7.2 29.05 
10 3.0 13.0 7.2 46.76 6.5 20.0 7.2 89.52 
11 3.0 5.0 9.2 27.89 6.5 10.0 9.2 46.61 
12 3.0 13.0 9.2 52.22 6.5 20.0 9.2 87.74 
13 3.0 9.0 8.2 78.00 6.5 15.0 8.2 82.12 
14 3.0 9.0 8.2 79.20 6.5 15.0 8.2 81.71 
15 3.0 9.0 8.2 85.44 6.5 15.0 8.2 83.66 
16 3.0 9.0 8.2 78.58 6.5 15.0 8.2 82.79 
17 3.0 9.0 8.2 78.83 6.5 15.0 8.2 82.01 

Analytical methods

Chlorophyll a concentration was measured by a two-channel fluorometer (AmiScience, USA). The removal ratio of chlorophyll a was estimated by the following equation.
formula
(1)
where RE% is the removal ratio of chlorophyll a via coagulation; Z1 is the chlorophyll a concentration before coagulation and Z2 is the chlorophyll a concentration after coagulation.

RSM has been widely used to establish a continuous variable surface model, aiming to evaluate these factors that may affect the coagulation process and interactions of these factors, and to determine the best level scope. RSM only required few experimental tests, and thus, it could save manpower and material resources (Li et al. 2015). In this study, this method was employed to optimize the application of combining PAC and CPAM to remove cyanobacteria by the coagulation process.

Statistics analysis

Three parallel experiments were conducted, and these data were analyzed using Excel 2017. Meanwhile, all data were statistically analyzed using Student's t-test, and a significant difference was defined at P < 0.05. The figures and tables were analyzed with Origin 2017 and Design-Expert 11.

RESULTS AND DISCUSSION

Single-factor experiments

Effect of CPAM on Microcystis removal by coagulation

Figure 1 shows that Microcystis at the exponential phase is easier to remove than that at the decline phase after dosing with the same initial dosage of CPAM (Figure 1). When the initial dosage of CPAM increased from 1.2 to 6.0 mg/L, the removal ratio of chlorophyll a at the exponential phase increased from 9.3 to 89.1%, but the removal ratio at the decline phase was only 8.7% (Figure 1). When the initial dosage of CPAM increased to 9.0 mg/L, the removal ratio of chlorophyll a significantly increased to 82.1% (Figure 1).

Figure 1

Effect of CPAM dosage on the removal ratio of chlorophyll a for Microcystis at exponential and decline phases.

Figure 1

Effect of CPAM dosage on the removal ratio of chlorophyll a for Microcystis at exponential and decline phases.

Charge neutralization is one of the mechanisms of cyanobacterial removal at both exponential and decline phases by CPAM coagulation. Previous studies have revealed that cyanobacterial cells at the decline phase exhibited higher zeta potential than those at the exponential phase (Henderson et al. 2008; Shi et al. 2016). Therefore, cyanobacteria at the decline phase required higher dosages of CPAM to achieve the same removal ratio of cyanobacterial cells.

Effect of PAC on Microcystis removal by coagulation

Figure 2 shows that Microcystis at the exponential phase are still more easily removed than that at the decline phase, similar to the results of CPAM. Dosing with the initial PAC of 13.0 mg/L, the removal ratio of chlorophyll a was about 69.1%. To promote the coagulation efficiency, PAC dosage increased to 18.0 mg/L, and the removal ratio of chlorophyll a reached up to 80% (Figure 2). Overall, the removal ratio of chlorophyll a was mainly dependent on the dosages of PAC for Microcystis at both exponential and decline phases (Figure 2).

Figure 2

Effect of PAC dosage on the removal ratio of chlorophyll a for Microcystis at exponential and decline phases.

Figure 2

Effect of PAC dosage on the removal ratio of chlorophyll a for Microcystis at exponential and decline phases.

Similar to CPAM coagulants, the hydrolysis form of PAC was high-density positively charged substances (Zhang et al. 2018; Guo et al. 2019). Except for charge neutralization with Microcystis cells, the adsorption, bridging, and netting may further contribute to remove Microcystis cells by coagulation. Besides, Microcystis cells at the decline phase may release more EOMs and exhibited higher electronegativity than those at the exponential phase, leading to an increase in PAC consumption.

Effect of pH on Microcystis removal by coagulation

Figure 3 shows that various pH values of 7.2, 8.2, 9.2, and 10.2 are used for coagulation experiments, and CPAM and PAC dosages of 4.0 and 13.0 mg/L are employed to treat Microcystis at exponential and decline phases, respectively. At pH values of 7.2–9.2, the removal ratio of chlorophyll a at the exponential phase was higher than a pH value of 10.2 after CPAM and PAC coagulation (Figure 3). In contrast, for Microcystis at the decline phase, the highest removal ratio of chlorophyll a was gained at pH values of 8.2 and 9.2 by CPAM and PAC coagulation, respectively. These results were consistent with previous studies, in that they have noted that pH played an important role in PAC coagulation, since coagulants have different hydrolysis products at various conditions of pH (Duan & Gregory 2003; Hu et al. 2006).

Figure 3

Effect of pH on the removal ratio of chlorophyll a for Microcystis at exponential and decline phases.

Figure 3

Effect of pH on the removal ratio of chlorophyll a for Microcystis at exponential and decline phases.

ANOVA of the proposed model

The removal ratio of chlorophyll a was used as the response value of the model, and all experimental results are shown in Table 3. The variance analysis of the BBD for the experimental data was conducted using the Design ExpertV11 software, and these results are shown in Table 4. The F-values and P-values showed that there were significant correlations between these factors and response values. Table 4 shows that P-values of the two models are below 0.0001, indicating that the fitted model was highly significant and the model could be used for subsequent optimization design. The P-value of misfit (lack of fit) was more than 0.05, suggesting that it was not significant and the model could fit these data well.

Table 4

Analysis of variance for the model

ProjectExponential phase
Decline phase
F-valuesP-valuesF-valuesP-values
Model 44.20 <0.0001 1,056.10 <0.0001 
A 81.73 <0.0001 187.89 <0.0001 
B 14.21 0.0070 6,335.6 <0.0001 
C 5.48 0.0518 159.73 <0.0001 
AB 2.79 0.1388 0.38 0.5590 
AC 17.82 0.0039 152.14 <0.0001 
BC 13.06 0.0086 110.36 <0.0001 
LOF 3.20 0.1453 1.94 0.2652 
R2 0.9827 0.9993 
 0.9605 0.9983 
 0.7967 0.9926 
AP 20.727 90.487 
CV% 7.84 1.39 
ProjectExponential phase
Decline phase
F-valuesP-valuesF-valuesP-values
Model 44.20 <0.0001 1,056.10 <0.0001 
A 81.73 <0.0001 187.89 <0.0001 
B 14.21 0.0070 6,335.6 <0.0001 
C 5.48 0.0518 159.73 <0.0001 
AB 2.79 0.1388 0.38 0.5590 
AC 17.82 0.0039 152.14 <0.0001 
BC 13.06 0.0086 110.36 <0.0001 
LOF 3.20 0.1453 1.94 0.2652 
R2 0.9827 0.9993 
 0.9605 0.9983 
 0.7967 0.9926 
AP 20.727 90.487 
CV% 7.84 1.39 

LOF, lack of fit; R2, coefficient of determination; , adjusted coefficient of determination; , predicted coefficient of correlation; AP, signal-to-noise ratio; CV, coefficient of variation.

The decision coefficients (R2) of the two models were 0.9827 and 0.9993, indicating that there was sufficient consistency between the model prediction and the experimental results (Figure 4). The correction decision coefficients were 0.9605 and 0.9983, demonstrating that the two models can explain the response changes of 96.05 and 99.83% of the data, respectively (Table 4). The difference value of the determination coefficient (R2) and the adjusted determination coefficient were less than 0.2, suggesting that the model held sufficient useful signals, high reliability, and model precision (Table 4). Moreover, it also demonstrated that the model was sufficient to explain the removal ratio of chlorophyll a by CPAM, PAC, and pH, and there were no other significant influencing factors to affect the process (Table 4). The signal-to-noise ratio (AP > 4) further indicated that the fitted models could be used to predict and analyze the removal ratio of chlorophyll a under different conditions (Table 4).

Figure 4

A comparison of experimental data vs. predicted data on the removal ratio of chlorophyll a based on RSM.

Figure 4

A comparison of experimental data vs. predicted data on the removal ratio of chlorophyll a based on RSM.

Table 4 shows that these values of F(A) = 81.73, F(B) = 14.21, and F(C) = 5.48 are for Microcystis at the exponential phase, while F(B) = 6,335.6, F(A) = 187.89, and F(C) = 159.73 are for Microcystis at the decline phase. The results suggested that the order of influence on the removal of chlorophyll a was different. For Microcystis at the exponential phase, the order was CPAM > PAC > pH, and the orders of CPAM > PAC > pH (PAC coagulation) and CPAM > PAC > pH (CPAM coagulation) were for Microcystis at the decline phase.

RSM of the model

RSM analysis could directly reflect these influences and the interaction of these factors (PAC, CPAM, and pH) on the removal ratio of chlorophyll a. The projection (contour) of the response surface was a complete ellipse or saddle shape, indicating that the interaction of these factors was significant. In general, the contour arrangement was closer, and the influence of the factors on the removal ratio of chlorophyll was greater.

Figure 5(a)–5(c) show an approximate complete ellipticity for Microcystis at the exponential phase. P(AC) (0.0039) and P(BC) (0.0086) were less than 0.05, indicating that there was a significant interaction between CPAM and PAC or CPAM and pH. In contrast, Figure 5(d)–5(f) show a completely elliptic for Microcystis at the decline phase. The corresponding P(AC) was below 0.0001 and showed that the interaction between CPAM and PAC was also significant. These results of analysis of variance (ANOVA) and RSM of other factors could not be confirmed, and thus, there was no obvious interaction between these factors.

Figure 5

Response surface of chlorophyll a removal ratio for exponential and decline phases: (a–c) show the exponential response surface diagram; (d–f) show the decline response surface diagram.

Figure 5

Response surface of chlorophyll a removal ratio for exponential and decline phases: (a–c) show the exponential response surface diagram; (d–f) show the decline response surface diagram.

The comparison analysis of Microcystis at exponential and decline phases found that all the PAC axis direction was steeper, and the contour line arrangement was denser. It indicated that the influence of PAC on the removal ratio of chlorophyll a for Microcystis at the decline phase was greater than that at the exponential phase (Figure 5). Figure 5(e) and 5(f) show that CPAM and PAC carry positive charges to remove Microcystis via electrical neutralization. However, pH values of water affecting the Microcystis removal at the decline phase were greater than CPAM, indicating that its mechanism of coagulation was quite different.

During cyanobacterial growth, EOMs would be one of the main factors to affect coagulation (Takaara et al. 2010; Vandamme et al. 2012; Garzon-Sanabria et al. 2013). The cell density of cyanobacterial cells at the exponential phase was low (Pivokonsky et al. 2014; Li et al. 2020), and its positive external charge was lower than the decline phase. Hence, the required dosages of CPAM and PAC were lower for Microcystis at the exponential phase than that at the decline phase by coagulation. Besides, at the decline phase, cyanobacterial cells would release EOMs. The EOMs contained amounts of polysaccharides at pH > 7.5. Among these EOMs, β-hydroxyl acid and γ-hydroxyl acid (β- and γ-COOH) could be fully dissociated, resulting in a large amount of negative charge in the solution aggregation (Safarikova et al. 2013). Consequently, the EOMs held a low zeta potential (Qu et al. 2012). Meanwhile, the negatively charged lipopolysaccharides (LPS) were also produced by cyanobacteria at the decline phase (Garzon-Sanabria et al. 2013). During coagulation, polynucleated Al-hydroxyl polymers were produced by the hydrolysis of PAC [Al]7(OH)17]4+ [Al]13(OH)34]5+ direct action (Duan & Gregory 2003), and it is first neutralized by the negatively charged LPS in the EOMs. It could well explain the increased consumption of CPAM and PAC for the removal of Microcystis at the decline stage by coagulation.

PAC plays a major role in coagulation with two hydrolysis products. One is the oligomeric substances of Al(OH)2+, Al(OH)2+, and Al(OH)3, and the other is the polymeric matter of Al7, Al13, and Al30 (Duan & Gregory 2003). Among these hydrolysis products, polynuclear Al-polymers are the main components in the flocculation process, since they had high charge density. During the coagulation process, the negatively charged EOMs and cyanobacterial cells could be neutralized rapidly, and cyanobacterial cells are easily adsorbed when the zeta potential became zero. CPAM is a long-chain organic polymer, and it has COO–, –CONH2, –NH–, and other active groups that can collect small colloids to form large particles (Zheng et al. 2016). These positive groups are likely to capture negatively charged cyanobacterial cells and form adsorption bridges, but a competitive flocculation occurs between two cyanobacterial cells in the presence of PAC. The coexistence of PAC resulted in the inhibition of coagulation by mutual restriction between long CPAM chains, and its excess is not conducive to the expansion of the polymer chain structure (Ma et al. 2013; Yu et al. 2019). These characteristics may well explain that the effect of PAC on cyanobacterial removal was greater than CPAM (Figure 5(e) and 5(f)).

Model validation

RSM showed that the maximum removal ratio of chlorophyll a had a better range of process parameters. Using the optimization function of the Design-Expert 11 software, the quadratic regression equation was first-order, and the parameter combination of the maximum removal ratio of chlorophyll a under constraint conditions could be obtained. Considering the high pH value of cyanobacteria-laden waters, pH values (8.0–9.0) were selected from the optimized process for the practical verification tests. These measured values were compared with the predicted values of the model, as shown in Table 5. Table 5 shows that the relative deviation between the predicted values of the model and experimental values is 2.01%, demonstrating that the two models could well reflect the effects of the three factors on the removal ratio of chlorophyll a for Microcystis cells at both exponential and decline phases.

Table 5

Predicted values of models and experimental values at optimum conditions

Regression equationCPAM (mg/L)PAC (mg/L)pHForecast (%)Measured values (%)Relative deviation (%)
Exponential phase Chlorophyll a removal ratio (%) = 80.01 + 13.67A + 5.7B − 3.54C + 3.57AB + 9.03AC + 7.73BC − 19.11A2 − 12.31B2 − 22.65C2 3.72 10.23 8.25 83.52 82.49 1.25 
4.77 10.21 8.17 76.47 74.96 2.01 
Decline phase Chlorophyll a removal ratio (%) = 82.46 + 4.46A + 25.9B + 4.11C + 0.282AB + 5.68AC − 4.84BC − 15.68A2 − 5.17B2 − 14.06C2 5.98 17.81 8.21 93.75 94.38 0.67 
6.66 18.19 8.83 92.51 90.83 1.85 
Regression equationCPAM (mg/L)PAC (mg/L)pHForecast (%)Measured values (%)Relative deviation (%)
Exponential phase Chlorophyll a removal ratio (%) = 80.01 + 13.67A + 5.7B − 3.54C + 3.57AB + 9.03AC + 7.73BC − 19.11A2 − 12.31B2 − 22.65C2 3.72 10.23 8.25 83.52 82.49 1.25 
4.77 10.21 8.17 76.47 74.96 2.01 
Decline phase Chlorophyll a removal ratio (%) = 82.46 + 4.46A + 25.9B + 4.11C + 0.282AB + 5.68AC − 4.84BC − 15.68A2 − 5.17B2 − 14.06C2 5.98 17.81 8.21 93.75 94.38 0.67 
6.66 18.19 8.83 92.51 90.83 1.85 

When a cyanobacterial bloom has an outbreak, the pH value of resource waters will be 8.0–9.0. Combining with the model verification in Table 5, the dosages of CPAM and PAC for Microcystis at the exponential phase are 3.72 and 10.23 mg/L, respectively, and the removal ratio of Microcystis cells could reach up to 83.52%. In this treatment, the relative deviation of the model fitting was low, and medicament was small. Therefore, this treatment was recommended to treat Microcystis at the exponential phase. To achieve the same removal ratio of Microcystis at the decline phase, the dosages of CPAM and PAC increased to 5.98 and 17.81 mg/L, respectively, and these dosages were recommended to treat Microcystis at the decline phase (Table 5).

CONCLUSIONS

This study demonstrated that factors of CPAM dosage, PAC dosage, and pH value could strongly affect the removal ratio of Microcystis at both exponential and decline phases. Furthermore, the growth phase of cyanobacteria was a key role in the order of influence factors during the coagulation process by combining PAC and CPAM. To achieve the same removal ratio of Microcystis, dosages of CPAM and PAC should be higher at the decline phase than that at the exponential phase. Consequently, dosages of CPAM (3.72 mg/L) and PAC (10.23 mg/L) were recommended to treat Microcystis at the exponential phase with a pH value of 8.25, and dosages of CPAM and PAC were 5.98 and 17.81 mg/L for Microcystis at the decline phase with a pH value of 8.21. These results would provide important technical parameters for cyanobacterial coagulation at exponential and decline phases by combining PAC and CPAM.

FUNDING

This work was supported by the Fujian Natural Science Foundation Project (no. 2020J01417), the Science and Technology Project of Water Resources Department of Fujian Province (no. MSK201711), the Science and Technology Major Project of Xiamen (no. 3502Z201710), the National Training Program of Innovation and Entrepreneurship for Undergraduates (no. 201910397006), and the Fujian University Student Innovation Training Project (no. S202010397033).

DATA AVAILABILITY STATEMENT

Data cannot be made publicly available; readers should contact the corresponding author for details.

REFERENCES

Duan
J.
Gregory
J.
2003
Coagulation by hydrolysing metal salts
.
Advances in Colloid and Interface Science
100–102
,
475
502
.
Garzon-Sanabria
A. J.
Ramirez-Caballero
S. S.
Moss
F. E. P.
Nikolov
Z. L.
2013
Effect of algogenic organic matter (AOM) and sodium chloride on Nannochloropsis salina flocculation efficiency
.
Bioresource Technology
143
,
231
237
.
Gonzalez-Torres
A.
Putnam
J.
Jefferson
B.
Stuetz
R. M.
Henderson
R. K.
2014
Examination of the physical properties of Microcystis aeruginosa flocs produced on coagulation with metal salts
.
Water Research
60
,
197
209
.
Guo
J. Y.
Wen
X. Y.
Jia
X. J.
Guo
Z. H.
Xu
J. J.
2019
Preparation of magnetic chitosan and improvement of dewatering performance of sludge
.
China Environmental Science
39
(
7
),
2944
2952
.
Henderson
R. K.
Baker
A.
Parsons
S. A.
Bruce
J.
2008
Characterisation of algogenic organic matter extracted from cyanobacteria, green algae and diatoms
.
Water Research
42
(
13
),
3435
3445
.
Hu
C.
Liu
H.
Qu
J.
Rut
J.
2006
Coagulation behavior of aluminum salts in eutrophic water: significance of Al13 species and pH control
.
Environmental Science & Technology
40
(
1
),
325
331
.
Hu
W. C.
Wu
C. D.
Jia
A. Y.
Liang
W. L.
2014
Enhanced coagulation for treating slightly polluted algae-containing surface water combining polyaluminum chloride (PAC) with diatomite
.
Desalination and Water Treatment
56
(
6
),
1698
1703
.
Leloup
M.
Nicolau
R.
Pallier
V.
Yéprémian
C.
Feuillade-Cathalifaud
G.
2013
Organic matter produced by algae and cyanobacteria: quantitative and qualitative characterization
.
Journal of Environmental Sciences
25
(
6
),
1089
1097
.
Li
L.
Zhang
S.
He
Q.
Hu
X. B.
2015
Application of response surface methodology in experiment design and optimization
.
Research and Exploration in Laboratory
34
(
8
),
41
45
.
Liu
J. G.
Yang
W.
2012
Water sustainability for China and beyond
.
Science
337
(
6095
),
649
650
.
Ma
J. W.
Liu
J. W.
Cao
R.
Yue
J. B.
2013
Sludge dewaterability with combined conditioning using Fenton's reagent and CPAM
.
Environmental Science
34
(
9
),
3538
3543
.
Ministry of Environmental Protection of the People's Republic of China (MEPPRC)
2017
Water Quality – Determination of Chlorophyll a-Spectrophotometric Method. HJ 897-2017
.
O'Neil
J. M.
Davis
T. W.
Burford
M. A.
Gobler
C. J.
2012
The rise of harmful cyanobacteria blooms: the potential roles of eutrophication and climate change
.
Harmful Algae
14
,
313
334
.
Pivokonsky
M.
Safarikova
J.
Baresova
M.
Pivokonska
L.
Kopecka
I.
2014
A comparison of the character of algal extracellular versus cellular organic matter produced by cyanobacterium, diatom and green alga
.
Water Research
51
,
37
46
.
Safarikova
J.
Baresova
M.
Pivokonsky
M.
Kopecka
I.
2013
Influence of peptides and proteins produced by cyanobacterium Microcystis aeruginosa on the coagulation of turbid waters
.
Separation and Purification Technology
118
,
49
57
.
Shen
L. F.
Sun
B. S.
Zhang
Y.
2014
Research on the pretreatment of landfill leachate using composite coagulant of polyaluminium chloride and polyacrylamide
.
Industrial Water Treatment
34
(
2
),
59
61
.
Shi
W.
Tan
W.
Wang
L.
Pan
G.
2016
Removal of Microcystis aeruginosa using cationic starch modified soils
.
Water Research
97
,
19
25
.
Vandamme
D.
Foubert
I.
Fraeye
I.
Muylaert
K.
2012
Influence of organic matter generated by Chlorella vulgaris on five different modes of flocculation
.
Bioresource Technology
124
,
508
511
.
Visser
P. M.
Verspagen
J. M. H.
Sandrini
G.
Stal
L. J.
Matthijs
H. C. P.
Davis
T. W.
Paerl
H. W.
Huisman
J.
2016
How rising CO2 and global warming may stimulate harmful cyanobacterial blooms
.
Harmful Algae
54
,
145
159
.
Wang
H. F.
Hu
H.
Wang
H. J.
Zeng
R. J.
2019
Combined use of inorganic coagulants and cationic polyacrylamide for enhancing dewaterability of sewage sludge
.
Journal of Cleaner Production
211
,
387
395
.
Wolf
D.
Georgic
W.
Klaiber
H. A.
2017
Reeling in the damages: harmful algal blooms' impact on Lake Erie's recreational fishing industry
.
Journal of Environmental Management
199
,
148
157
.
Yang
H. M.
Gu
J. H.
Zhang
D. H.
Ouyang
J.
Ran
M.
2017
Analysis of flocculant PAC and PAM in the treatment of pickled cabbage wastewater
.
Journal of Civil, Architectural & Environmental Engineering
39
(
04
),
95
101
.
Yu
W.
Wen
Q.
Yang
J.
Xiao
K.
Zhu
Y.
Tao
S.
Lv
Y.
Liang
S.
Fan
W.
Zhu
S.
Liu
Bi.
Hou
H.
Hu
J.
2019
Unraveling oxidation behaviors for intracellular and extracellular from different oxidants (HOCl vs. H2O2) catalyzed by ferrous iron in waste activated sludge dewatering
.
Water Research
148
,
60
69
.
Zhang
X.
Chen
C.
Ding
J.
Ding
J.
Hou
A.
Li
Y.
Niu
Z.
Su
X.
Xu
Y.
Laws
E. A.
2010
The 2007 water crisis in Wuxi, China: analysis of the origin
.
Journal of Hazardous Materials
182
(
1–3
),
130
135
.
Zhang
P.
Zhao
D.
Wang
Y. L.
2018
Preparation and structural characterization of polyaluminum magnesium titanium chloride
.
Research of Environmental Sciences
31
(
12
),
2155
2162
.
Zhao
P. F.
2019
Analysis and optimization of flocculation effect of polyaluminium chloride polyacrylamide
.
Journal of Liaoning Shihua University
39
(
2
),
37
41
.
Zheng
Y. Y.
Jiang
J.
Sun
Q. Y.
Liu
C.
2016
Effect of different molecular weight and ionic strength of CPAM on sludge dewaterability
.
Acta Scientiae Circumstantiae
36
(
8
),
2947
2954
.
Zhou
Z.
Yang
Y.
Li
X.
Gao
W.
Liang
H.
Li
G.
2012
Coagulation efficiency and flocs characteristics of recycling sludge during treatment of low temperature and micro-polluted water
.
Journal of Environmental Sciences
24
(
6
),
1014
1020
.
Zhou
G.
Wang
Q.
Li
J.
Li
Q.
Zhang
J.
2020
Removal of polystyrene and polyethylene microplastics using PAC and FeCl3 coagulation: performance and mechanism
.
Science of the Total Environment
752
,
141837
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY-NC-ND 4.0), which permits copying and redistribution for non-commercial purposes with no derivatives, provided the original work is properly cited (http://creativecommons.org/licenses/by-nc-nd/4.0/).