Preparation of a novel phosphorus removal filler and optimization of phosphate removal adsorption bed process

doi:10.11949/j.issn.0438-1157.20181054

Abstract

Abstract:

To solve the problems of easy loss of materials and excessive system pressure drop caused by the small particle size of the existing phosphorus removal adsorbent, the application of the adsorption phosphorus removal process in practical engineering is realized. In this study, polyurethane filler was used as carrier, water-soluble polyurethane was used as medium, and hydrated calcium silicate was loaded onto polyurethane filler to make supported phosphorus removal filler. Effect of prepared methods on phosphate removal efficiency of the phosphorus removal filler was studied to obtain the optimum preparation conditions. The change of microstructure and chemical groups of hydrated calcium silicate before and after loading onto polyurethane carriers was revealed by scanning electron microscope (SEM) and Fourier transform infrared spectrometer (FTIR). Effect of operation parameters on phosphate removal efficiency of adsorption bed using phosphorus removal filler as packing materials was investigated through single factor experiment. Based on the results obtained from the single factor experiment, an ideal experimental design was carried out based on central composite design (CCD) with response surface methodology (RSM). The results showed that, the optimum conditions for the preparation of phosphorus removal filler were 50 ml waterborne polyurethane with concentration of 100 g/L, and the hydrated calcium silicate dosage of 12 g. SEM and FTIR observations showed that the pore structure and the chemical groups of hydrated calcium silicate changed slightly after loading onto the filler. The variance analysis of the predication model indicated that HRT(X ₁), influent ρ (PO₄ ^3--P)(X ₂), temperature(X ₃), initial pH(X ₄) and the interaction between X ₁ X ₂, X ₁ X ₄, X ₂ X ₃ and X ₂ X ₄ had significant influence on the response value(P<0.05) while the interaction between X ₁ X ₃ had non-significant impacts on the response value. The optimum conditions obtained were HRT 79.77 min, influent ρ(PO₄ ^3--P) 1.70 mg/L, temperature 34.04℃ and initial pH 9.68. Under the optimized conditions, the phosphate removal efficiency of the adsorption bed was found to be 93.46%.

Key words: novel phosphorus removal filler, phosphate removal adsorption bed, response surface methodology (RSM), process optimization

摘要：

为解决现有除磷吸附剂粒径小造成的材料易流失和系统压降过大等问题，以实现吸附除磷工艺在实际工程中的应用，以聚氨酯填料为载体，水溶性聚氨酯为介质，将水化硅酸钙负载到聚氨酯填料上制成负载型除磷填料。研究了制备条件对除磷填料除磷效果的影响，采用扫描电子显微镜（SEM）和傅里叶变换红外光谱仪（FTIR）观察分析了负载前后水化硅酸钙微观结构及化学基团的变化；利用除磷填料作为除磷吸附床的滤料，研究了运行条件对吸附床除磷效果的影响。在此基础上，利用响应曲面法研究了除磷吸附床磷酸盐去除率和各变量之间的关系，并对工艺参数进行了优化。结果表明，水性聚氨酯溶液的浓度和用量分别为100 g/L和50 ml，水化硅酸钙的质量为12 g的条件下所制备的除磷填料除磷效果最好；SEM和FTIR分析结果显示，水化硅酸钙负载前后其孔隙结构和化学基团没有明显的变化；预测模型的方差分析结果表明，HRT(X ₁)、进水ρ(PO₄ ^3--P)(X ₂)、温度(X ₃)、初始pH(X ₄)以及X ₁ X ₂，X ₁ X ₄，X ₂ X ₃，X ₂ X ₄的交互作用均对磷酸盐的去除具有显著影响 (P＜0.05)，但X ₁ X ₃的交互作用对磷酸盐的去除影响不显著。通过预测模型获得的最佳运行条件为：HRT为79.77 min，进水ρ(PO₄ ^3--P)为1.70 mg/L, 温度为34.04℃，pH为9.68。在该条件下，反应器对磷酸盐的去除率可以达到93.46%。

关键词: 新型除磷填料, 除磷吸附床, 响应曲面法, 运行参数优化

CLC Number:

X 52

Qian ZHANG, Xiangyang LIU, Wang CHEN, Heng WU, Pengying XIAO, Fangying JI, Chen LI, Haiming NIAN. Preparation of a novel phosphorus removal filler and optimization of phosphate removal adsorption bed process[J]. CIESC Journal, 2019, 70(3): 1099-1110.

张千, 刘向阳, 陈旺, 吴恒, 肖芃颖, 吉芳英, 李宸, 念海明. 新型除磷填料的制备及除磷吸附床运行参数的优化[J]. 化工学报, 2019, 70(3): 1099-1110.

Figures/Tables 13

Fig.1 Scheme of experimental device

Table 1 Operation parameters in each single factor experiment

Factor	Level
Factor	HRT/min	Influent ρ( $P O 4 3 -$ -P)/(mg/L)	Tempera-ture/℃	Initial pH
HRT/min	40—90	6	30	9
influent ρ( $P O 4 3 -$ -P)/(mg/L)	70	0.5—2.5	30	9
temperature/℃	70	6	17—40	9
initial pH	70	6	30	6—11

Table 1 Operation parameters in each single factor experiment

Factor	Level
Factor	HRT/min	Influent ρ( $P O 4 3 -$ -P)/(mg/L)	Tempera-ture/℃	Initial pH
HRT/min	40—90	6	30	9
influent ρ( $P O 4 3 -$ -P)/(mg/L)	70	0.5—2.5	30	9
temperature/℃	70	6	17—40	9
initial pH	70	6	30	6—11

Table 2 Variables and corresponding range of response surface methodology model

Code	Variable	Code level
Code	Variable	-α	-1	0	1	+α
X ₁	HRT/min	50	60	70	80	90
X ₂	influent ρ( $P O 4 3 -$ -P)/(mg/L)	0.5	1	1.5	2	2.5
X ₃	temperature/℃	16	23	30	37	44
X ₄	initial pH	7	8	9	10	11

Table 2 Variables and corresponding range of response surface methodology model

Code	Variable	Code level
Code	Variable	-α	-1	0	1	+α
X ₁	HRT/min	50	60	70	80	90
X ₂	influent ρ( $P O 4 3 -$ -P)/(mg/L)	0.5	1	1.5	2	2.5
X ₃	temperature/℃	16	23	30	37	44
X ₄	initial pH	7	8	9	10	11

Table 3 Orthogonal test results of phosphorus removal filter

Sample	ρ(waterborne polyurethane)/(g/L)	Volume of waterborne polyurethane/ ml	Dosage of hydrated calcium silicate/g	Phosphate removal rate/%
1	100	50	4	95.7
2	100	100	8	96.6
3	100	150	12	97.9
4	100	200	16	98.3
5	200	50	8	95.9
6	200	100	4	91.5
7	200	150	16	97.6
8	200	200	12	96.6
9	300	50	12	99.6
10	300	100	16	99.2
11	300	150	4	72.2
12	300	200	8	88.0
13	400	50	16	91.6
14	400	100	12	92.8
15	400	150	8	74.7
16	400	200	4	44.1
K ₁	388.5	382.8	303.5
K ₂	381.6	380.1	355.2
K ₃	359.0	342.4	386.9
K ₄	303.2	327	386.7
k ₁	97.1	95.7	75.9
k ₂	95.4	95.0	88.8
k ₃	89.8	85.6	96.7
k ₄	75.8	81.8	96.7
R	21.3	13.9	20.8
major-minor order of test factor		A>C>B
optimal level	A1	B1	C3
optimal combination		A1B1C3

Fig.2 Comparison of phosphorus removal efficiency between hydrated calcium silicate and phosphorus removal filler

Fig.3 SEM images of calcium silicate and calcium silicate supported on filter

Fig.4 Infrared spectra of calcium silicate hydrate before and after loading on carrier

Fig.5 Influence of operation parameters on phosphorus removal performance of phosphorus removal adsorption bed

Table 4 Factors and levels for central composite design

Standard order	X ₁	X ₂	X ₃	X ₄	$P O 4 3 -$ -P removal efficiency /%
Standard order	X ₁	X ₂	X ₃	X ₄	Measured value	Predicted value
22	70	1.5	44	9	91.00	90.37
17	50	1.5	30	9	78.12	78.79
8	80	2	37	8	88.84	89.47
5	60	1	37	8	86.58	85.90
9	60	1	23	10	85.87	85.23
2	80	1	23	8	86.82	86.90
18	90	1.5	30	9	92.48	91.31
16	80	2	37	10	92.59	92.73
3	60	2	23	8	73.58	72.73
12	80	2	23	10	88.94	89.61
24	70	1.5	30	11	91.12	90.85
19	70	0.5	30	9	86.02	85.54
28	70	1.5	30	9	91.02	91.01
25	70	1.5	30	9	91.01	91.01
13	60	1	37	10	88.99	89.76
14	80	1	37	10	88.59	88.67
7	60	2	37	8	78.54	79.26
30	70	1.5	30	9	90.95	91.01
23	70	1.5	30	7	83.96	83.73
10	80	1	23	10	86.99	87.54
1	60	1	23	8	80.99	81.37
4	80	2	23	8	86.59	86.34
6	80	1	37	8	87.09	88.03
27	70	1.5	30	9	91.03	91.01
29	70	1.5	30	9	91.02	91.01
21	70	1.5	16	9	82.59	82.71
26	70	1.5	30	9	91.00	91.01
20	70	2.5	30	9	80.99	80.97
15	60	2	37	10	86.59	85.75
11	60	2	23	10	78.89	79.22

Table 4 Factors and levels for central composite design

Standard order	X ₁	X ₂	X ₃	X ₄	$P O 4 3 -$ -P removal efficiency /%
Standard order	X ₁	X ₂	X ₃	X ₄	Measured value	Predicted value
22	70	1.5	44	9	91.00	90.37
17	50	1.5	30	9	78.12	78.79
8	80	2	37	8	88.84	89.47
5	60	1	37	8	86.58	85.90
9	60	1	23	10	85.87	85.23
2	80	1	23	8	86.82	86.90
18	90	1.5	30	9	92.48	91.31
16	80	2	37	10	92.59	92.73
3	60	2	23	8	73.58	72.73
12	80	2	23	10	88.94	89.61
24	70	1.5	30	11	91.12	90.85
19	70	0.5	30	9	86.02	85.54
28	70	1.5	30	9	91.02	91.01
25	70	1.5	30	9	91.01	91.01
13	60	1	37	10	88.99	89.76
14	80	1	37	10	88.59	88.67
7	60	2	37	8	78.54	79.26
30	70	1.5	30	9	90.95	91.01
23	70	1.5	30	7	83.96	83.73
10	80	1	23	10	86.99	87.54
1	60	1	23	8	80.99	81.37
4	80	2	23	8	86.59	86.34
6	80	1	37	8	87.09	88.03
27	70	1.5	30	9	91.03	91.01
29	70	1.5	30	9	91.02	91.01
21	70	1.5	16	9	82.59	82.71
26	70	1.5	30	9	91.00	91.01
20	70	2.5	30	9	80.99	80.97
15	60	2	37	10	86.59	85.75
11	60	2	23	10	78.89	79.22

Table 5 Analysis of variance(ANOVA) for regression model

Source	Sum of squares	df	Mean square	F value	P value
Model	691.57	13	53.20	101.47	<0.0001
X ₁	235.25	1	235.25	448.70	<0.0001
X ₂	31.33	1	31.33	59.75	<0.0001
X ₃	88.01	1	88.01	167.87	<0.0001
X ₄	76.11	1	76.11	145.17	<0.0001
X ₁ X ₂	65.21	1	65.21	124.37	<0.0001
X ₁ X ₃	11.56	1	11.56	22.05	0.0002
X ₁ X ₄	10.37	1	10.37	19.78	0.0004
X ₂ X ₃	3.98	1	3.98	7.59	0.0141
X ₂ X ₄	6.89	1	6.89	13.14	0.0023
X ₁ ²	60.86	1	60.86	116.08	<0.0001
X ₂ ²	103.05	1	103.05	196.56	<0.0001
X ₃ ²	34.15	1	34.15	65.14	<0.0001
X ₄ ²	23.70	1	23.70	45.21	<0.0001
residual	8.39	16	0.52
lack of fit	8.38	11	0.76	918.35	<0.0001
pure error	4.150×10^-3	5	8.300×10^-4

Fig.6 Contour and response surface plots for interaction effects of HRT, influent P O 4 3 - -P concentration, temperature and initial pH on phosphate removal efficiency

Table 6 Optimization results for phosphate maximum removal efficiency

Solution No.	HRT/min	Influent ρ( $P O 4 3 -$ -P)/(mg/L)	Temperature/℃	Initial pH	Phosphate removal efficiency/%	Desirability
1	79.77	1.70	34.04	9.68	93.46	1.000
2	79.75	1.70	33.98	9.68	93.4579	1.000
3	79.90	1.70	34.01	9.67	93.4578	1.000
4	79.97	1.71	34.01	9.67	93.4576	1.000
5	79.48	1.70	34.15	9.69	93.4573	1.000
6	76.75	1.70	33.87	9.69	93.4572	1.000
7	80.00	1.69	32.80	9.59	93.4221	0.998
8	80.00	1.70	33.80	9.27	93.3107	0.992

Table 6 Optimization results for phosphate maximum removal efficiency

Solution No.	HRT/min	Influent ρ( $P O 4 3 -$ -P)/(mg/L)	Temperature/℃	Initial pH	Phosphate removal efficiency/%	Desirability
1	79.77	1.70	34.04	9.68	93.46	1.000
2	79.75	1.70	33.98	9.68	93.4579	1.000
3	79.90	1.70	34.01	9.67	93.4578	1.000
4	79.97	1.71	34.01	9.67	93.4576	1.000
5	79.48	1.70	34.15	9.69	93.4573	1.000
6	76.75	1.70	33.87	9.69	93.4572	1.000
7	80.00	1.69	32.80	9.59	93.4221	0.998
8	80.00	1.70	33.80	9.27	93.3107	0.992

Fig.7 Phosphate removal performance of adsorption bed during continuous operation

References 30

1	Song X Y , Pan Y Q , Wu Q , et al . Phosphate removal from aqueous solutions by adsorption using ferric sludge[J]. Desalination, 2011, 280(1): 384-390.
2	Yan L G , Xu Y Y , Yu H Q , et al . Adsorption of phosphate from aqueous solution by hydroxy-aluminum, hydroxy-iron and hydroxy-iron-aluminum pillared bentonites[J]. Journal of Hazardous Materials, 2010, 179(1): 244-250.
3	郭照冰, 陈天, 陈天蕾, 等 . 铁盐改性废弃蛋壳对水中磷的吸附特征研究[J]. 中国环境科学, 2011, 31(4): 611-615.
	Guo Z B , Chen T , Chen T L , et al . Phosphorus adsorption behaviors on iron-coated wasted eggshell in aqueous solution [J]. China Environmental Science, 2011, 31(4): 611-615.
4	柳飞, 张延一, 严玉鹏, 等 . 不同结构有机磷在(氢)氧化铝表面的吸附与解吸特征[J]. 环境科学, 2013, 34(11): 4482-4489.
	Liu F , Zhang Y Y , Yan Y P , et al . Sorption and desorption characteristics of different structures of organic phosphorus onto aluminum ( oxyhydr) oxides [J]. Environmental Science, 2013, 34(11): 4482-4489.
5	Suzuki K , Tanaka Y , Kuroda K , et al . Removal and recovery of phosphorous from swine wastewater by demonstration crystallization reactor and struvite accumulation device[J]. Bioresource Technology, 2007, 98(8): 1573-1578.
6	Zhang X , Lin H , Hu B . The effects of electrocoagulation on phosphorus removal and particle settling capability in swine manure[J]. Separation and Purification Technology, 2018, 200: 112-119.
7	Oehmen A , Lemos P C , Carvalho G , et al . Advances in enhanced biological phosphorus removal: from micro to macro scale[J]. Water Research, 2007, 41(11): 2271-2300.
8	Jiang L , Wang M , Wang Y , et al . The condition optimization and mechanism of aerobic phosphorus removal by marine bacterium Shewanella sp[J]. Chemical Engineering Journal, 2018, 345: 611-620.
9	Arias C A , Brix H . Phosphorus removal in constructed wetlands: can suitable alternative media be identified?[J]. Water Science and Technology, 2005, 51(9): 267-273.
10	蔡冬蓉, 徐炎华 . 浮萍对富营养化水体中磷的去除规律[J]. 农业工程学报, 2011, 27(S2): 187-190.
	Cai D R , Xu Y H . Phosphorus removal rules of duckweed plants in eutrophication water [J]. Transactions of the CSAE, 2011, 27(S2): 187-190.
11	张岩, 崔丽娟, 李伟, 等 . 基于水流模型的串联式水平潜流湿地除磷效果分析[J]. 农业工程学报, 2014, 30(19): 174-181.
	Zhang Y , Cui L J , Li W , et al . Analysis on phosphorus removal in series horizontal subsurface flow constructed wetland based on hydraulic model [J]. Transactions of the CSAE, 2014, 30(19): 174-181.
12	唐朝春, 刘名, 陈惠民, 等 . 吸附除磷技术的研究进展[J]. 水处理技术, 2014, 40(9): 1-7+12.
	Tang C C , Liu M , Chen H M , et al . Research progress of phosphorus removal from wastewater by adsorption technology [J]. Technology of Water Treatment, 2014, 40(9): 1-7+12.
13	Du X , Han Q , Li J , et al . The behavior of phosphate adsorption and its reactions on the surfaces of Fe–Mn oxide adsorbent[J]. Journal of the Taiwan Institute of Chemical Engineers, 2017, 76: 167-175.
14	Mahardika D , Park H S , Choo K H . Ferrihydrite-impregnated granular activated carbon (FH@GAC) for efficient phosphorus removal from wastewater secondary effluent[J]. Chemosphere, 2018, 207: 527.
15	关伟, 吉芳英, 陈晴空, 等 . 水化硅酸钙的制备及磷回收性能表征[J]. 功能材料, 2012, 43(23): 3286-3290.
	Guan W , Ji F Y , Chen Q K , et al . Preparation and phosphorus recovery performance of calcium silicate hydrate [J]. Functional Materials, 2012, 43(23): 3286-3290.
16	孙华, 郑红, 马鸿, 等 . 沉淀硅酸钙晶种法回收实际污水中磷[J]. 化工矿物与加工, 2014, 43(10): 23-26+47.
	Sun H , Zheng H , Ma H , et al . Recovery of phosphorus in wastewater by crystal seed method of calcium silicate [J]. Industrial Minerals and Processing, 2014, 43(10): 23-26+47.
17	王鑫永, 陈雪初, 何圣兵, 等 . 水化硅酸钙回收污水中磷的试验研究[J]. 工业用水与废水, 2011, 42(4): 51-54.
	Wang X Y , Chen X C , He S B , et al . Recovery of phosphorus from wastewater by calcium silicate hydrate [J]. Industrial Water and Wastewater, 2011, 42(4): 51-54.
18	刘焱, 张怡, 王世和, 等 . 复合除磷材料在污水处理厂二沉池出水除磷中的应用[J]. 给水排水, 2009, 45(4): 40-43.
	Liu Y , Zhang Y , Wang S H , et al . Application of phosphorus removal composite material in the dephosphorization process of WWTP secondary sedimentation tank effluent [J]. Water and Wastewater Engineering, 2009, 35(4): 40-43.
19	张美兰, 何圣兵, 陈雪初, 等 . 天然沸石和硅酸钙滤床的脱氨除磷效能[J]. 水处理技术, 2007, 33(11): 71-74.
	Zhang M L , He S B , Chen X C , et al . Removal of ammonia and phosphate by filtration bed packed with natural zeolite and calcium silicate [J]. Technology of Water Treatment, 2007, 33(11): 71-74.
20	郑俊, 马露露, 刘宝河 . 多孔硅酸钙滤料吸附床除磷试验研究[J]. 环境污染与防治, 2013, 35(8): 28-32.
	Zheng J , Ma L L , Liu B H . Study on the removal of phosphorus by porous calcium silicate adsorption bed [J]. Environmental Pollution and Control, 2013, 35(8): 28-32.
21	李品君 . 微孔硅酸钙的制备及其污水除磷性能研究[D]. 合肥: 安徽工业大学, 2012.
	Li P J . Preparation of microporous calcium silicate and its studies on removal of phosphor in waste water [D]. Hefei: Anhui University of Technology, 2012.
22	马露露 . 多孔硅酸钙滤料应用于市政污水深度除磷的实验研究[D]. 合肥: 安徽工业大学, 2013.
	Ma L L . Research on advanced dephosphorization from municipal sewage by porous calcium silicate [D]. Hefei: Anhui University of Technology, 2013.
23	张连科, 杨冬梅, 韩剑宏, 等 . 硅酸钙处理富营养化湖水中总磷的实验研究[J]. 无机盐工业, 2013, 45(11): 41-43.
	Zhang L K , Yang D M , Han J H , et al . Study on removal of total phosphorus from eutrophic lake water by calcium silicate [J]. Inorganic Chemistry Industry, 2013, 45(11): 41-43.
24	程朝阳, 赵诗惠, 吕亮, 等 . 基于ABR-MBR组合工艺优化反硝化除磷性能的研究[J]. 环境科学, 2016, 37(11): 4282-4288.
	Cheng C Y , Zhao S H , Lyu L , et al . Optimization of denitrifying phosphorus removal performance based on ABR-MBR combination process[J]. Environmental Science, 2016, 37(11): 4282-4288.
25	韩芸, 许松, 董涛, 等 . 碳源类型、温度及电子受体对生物除磷的影响[J]. 环境科学, 2015, 36(2): 590-596.
	Han Y , Xu S , Dong T , et al . Effect of carbon source type, temperature and electron acceptor on biological phosphorus removal[J]. Environmental Science, 2015, 36(2): 590-596.
26	Li W , Zhang H Y , Sun H Z , et al . Influence of pH on short-cut denitrifying phosphorus removal[J]. Water Science and Engineering, 2018, (1): 17-22.
27	吕景花, 袁林江, 张婷婷 . 响应面法优化厌氧上清液除磷的研究[J]. 中国环境科学, 2014, 34(1): 72-77.
	Lyu J H , Yuan L J , Zhang T T . Optimization of phosphorus removal by anaerobic supernatant by response surface methodology [J]. China Environmental Science, 2014, 34(1): 72-77.
28	Bashar R , Gungor K , Karthikeyan K G , et al . Cost effectiveness of phosphorus removal processes in municipal wastewater treatment[J]. Chemosphere, 2018, 197: 280.
29	赵桂瑜, 周琪, 秦琴 . 干渣吸附处理含磷污水的研究[J]. 农业环境科学学报, 2007, 26(3): 925-928.
	Zhao G Y , Zhou Q , Qin Q . Phosphorus removal from wastewater by adsorption on blast furnace slag [J]. Journal of Agro-Environment Science, 2007, 26(3): 925-928.
30	石磊 . 水化硅酸钙的除磷及磷回收特性研究[D]. 重庆: 重庆大学, 2012.
	Shi L . Study on the characteristics of removing and reusing phosphorus by calcium silicate hydrate [D]. Chongqing: Chongqing University, 2012.

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