镁改性增强小麦秸秆生物炭对镉的吸附能力：表面络合模型研究

doi:10.16258/j.cnki.1674-5906.2024.04.012

生态环境学报 ›› 2024, Vol. 33 ›› Issue (4): 617-625.DOI: 10.16258/j.cnki.1674-5906.2024.04.012

• 研究论文【环境科学】 • 上一篇下一篇

镁改性增强小麦秸秆生物炭对镉的吸附能力：表面络合模型研究

王室苹(), 李梅, 安娅, 秦好丽^*()

贵州师范大学化学与材料科学学院，贵州贵阳 550025

收稿日期:2024-03-25 出版日期:2024-04-18 发布日期:2024-05-31
通讯作者: *秦好丽。E-mail: hollyqin@126.com
作者简介:王室苹（1999年生），女（苗族），硕士研究生，主要从事重金属钝化剂研究。E-mail: wang_shiping_apple@163.com
基金资助:
国家自然科学基金项目(41967003);贵州省自然科学基金项目(20201Y182);贵州师范大学学术新苗项目(2020)

The Effect of Magnesium Modification on Enhancing Cadmium Adsorption Capacity of Wheat Straw Biochar: A Surface Complexation Modeling Approach

WANG Shiping(), LI Mei, AN Ya, QIN Haoli^*()

School of Chemistry and Materials Science, Guizhou Normal University, Guiyang 550025, P. R. China

Received:2024-03-25 Online:2024-04-18 Published:2024-05-31

摘要/Abstract

摘要：

近年来研究改性生物炭有效去除水中重金属成为热门，但使用表面络合模型从微观探讨生物炭对镉的吸附机理鲜见报道。通过MgCl₂与小麦秸秆生物炭（WB）共热解制备镁改性生物炭（MgWB）。SEM-EDS、FTIR和BET等表征显示镁成功接枝到生物炭，Mg的质量分数增加了3.97%，生物炭表面新增Mg-O峰且-OH、-C-O峰增强，镁改性未改变小麦秸秆的条状管道主体结构但比表面积降低9.94%。293－313 K的等温吸附曲线表明改性前后生物炭的吸附行为均符合Langmuir模型，MgWB在313 K时最大饱和吸附密度（3.50 μmol·m^-2）是WB的3.7倍。Boehm滴定实验显示改性使总酸性官能团增加13.4%，其中代表高、中、低亲和型官能团的羟基、内酯基、羧基浓度分别增加4.28%、8.92%和0.178%。电位滴定曲线显示镁改性导致生物炭的pH_pzc从9.2降为5.3，不同pH条件下Cd²⁺的吸附边实验中WB和MgWB吸附率达90%所需pH分别为9和6，结果表明吸附平衡所需pH值与pH_pzc有关，且pH_pzc的改变会导致生物炭表面位点类型在不同pH条件下的镉吸附差异。利用非静电表面络合模型NEM、以广义复合法进行拟合，最佳参数计算的位点分布曲线显示WB和MgWB的吸附贡献主要为高亲和型位点，该位点与Cd²⁺的吸附态浓度达到最高值所对应的pH分别为10和7；模型拟合参数pK_a和pK_≡SOCd+表明镁改性导致生物炭表面官能团的质子化能力降低，与Cd²⁺的络合能力增强。镁改性可以丰富生物炭表面官能团，通过增加表面位点浓度和降低pH_pzc有效改善生物炭对重金属的吸附。本研究在使用非静电表面络合模型拟合中将表面位点类型的吸附贡献与pH_pzc结合讨论微观吸附机理，为生物炭-重金属的相互作用提供了一种新的量化手段。

关键词: 生物炭, Cd, 镁改性, 非静电表面络合模型, 表面酸碱性质, 吸附, 小麦秸秆

Abstract:

The removal of cadmium (Cd) from water using modified biochar is a growing area of research. However, studies on the adsorption mechanism of Cd on biochar at the micro-level using Surface Complexation Models (SCM) are scarce. This study investigated the effectiveness of magnesium-modified wheat straw biochar (MgWB) for cadmium (Cd²⁺) adsorption and explored the underlying mechanisms using SCM. MgWB exhibited a 3.97% increase in the Mg mass fraction and a 9.94% decrease in the specific surface area compared to those of unmodified biochar (WB). The isothermal adsorption curves revealed the adherence of biochar to the Langmuir model before and after modification. The maximum adsorption capacity of MgWB (3.50 μmol·m⁻²) at 313 K was found, 3.7 times higher than that of WB. Boehm titration showed a 13.4% increase in total acidic functional groups upon modification. The high-, medium-, and low-affinity functional groups, represented by hydroxyl, lactone, and carboxyl groups, increased by 4.28, 8.92, and 0.178%, respectively. Potentiometric titration curves demonstrated a reduction in the biochar's pH_pzc from 9.2 to 5.3 with magnesium addition. Furthermore, the pH required for 90% adsorption of WB and MgWB in Cd²⁺ adsorption experiments was observed at pH 9 and 6, respectively, suggesting a correlation between the adsorption equilibrium pH and pH_pzc alterations, impacting Cd adsorption by biochar surface sites across varying pH conditions. Non-electrostatic surface complexation modeling (NEM) revealed that high-affinity sites dominate Cd²⁺ adsorption for both WB and MgWB. MgWB exhibited a lower pH for peak adsorption than WB, indicating stronger complexation with Cd²⁺ owing to the reduced surface protonation. This study demonstrated that magnesium modification enhances Cd²⁺ adsorption by enriching the surface functional groups, lowering pH_pzc, and promoting stronger complexation. The combined analysis of surface site types and pH_pzc using NEM provides a novel quantitative approach for understanding biochar-metal interactions.

Key words: biochar, Cd, magnesium modification, non-electrostatic surface complexation model, surface acid-base properties, adsorption, wsheat straw

中图分类号:

王室苹, 李梅, 安娅, 秦好丽. 镁改性增强小麦秸秆生物炭对镉的吸附能力：表面络合模型研究[J]. 生态环境学报, 2024, 33(4): 617-625.

WANG Shiping, LI Mei, AN Ya, QIN Haoli. The Effect of Magnesium Modification on Enhancing Cadmium Adsorption Capacity of Wheat Straw Biochar: A Surface Complexation Modeling Approach[J]. Ecology and Environment, 2024, 33(4): 617-625.

图/表 10

图1 生物炭的SEM-EDS

Figure 1 SEM-EDS of biochar

图2 生物炭的FTIR图

Figure 2 FTIR of Biochar

表1 生物炭的表面物理和化学参数

Table 1 Surface physical and chemical parameters of biochar

参数	WB	MgWB
比表面积/(m²·g^-1)	56.09	50.51
孔体积/(cm³·g^-1)	0.11	0.13
平均孔径/nm	7.788	10.641
低亲和型官能团/(mmol·g^-1)	0.041	0.042
中亲和型官能团/(mmol·g^-1)	0.159	0.209
高亲和型官能团/(mmol·g^-1)	0.360	0.384
总酸性官能团/(mmol·g^-1)	0.560	0.635

表2 Cd2+在WB和MgWB的上的吸附等温线参数

Table 2 Isotherm parameters of Cd2+ adsorption on WB and MgWB

热力学模型	参数	WB			MgWB
热力学模型	参数	293 K	303 K	313 K	293 K	303 K	313 K
Langmuir	K_L	0.002	0.002	0.003	0.001	0.001	0.002
	q_m	0.882	0.928	0.925	2.661	3.292	3.501
	r²	0.995	0.996	0.994	0.998	0.997	0.995
Freundlich	K_F	0.027	0.044	0.058	2.517	3.205	5.087
	N_f	0.441	0.401	0.357	0.501	0.494	0.449
	r²	0.978	0.965	0.945	0.979	0.965	0.947

图3 生物炭对Cd2+的等温线吸附 n=3。下同

Figure 3 Isotherm adsorption of Cd2+ by biochar

图4 生物炭表面电荷密度（μmol·m-2）随pH的变化曲线符号：实验数据；曲线：SCM拟合

Figure 4 Curve of surface charge density (μmol·m-2) of biochar with pH

表3 由SCM拟合电位滴定曲线得到的参数

Table 3 Parameters obtained by SCM fitting potentiometric titration curve

参数	位点类型	WB	MgWB
Q/(μmol·m^-2)	B₁	6.42	7.61
	B₂	2.83	4.15
	B₃	0.74	0.83
pK_a1	B₁	9.2	3.5
	B₂	4.1	2.6
	B₃	3.2	2.1
pK_a2	B₁	10.5	9.1
	B₂	6.5	6.8
	B₃	4.5	5.8

图5 不同Cd2+初始浓度条件下生物炭的吸附边实验

Figure 5 Adsorption edge experiments of biochar under different initial concentrations of Cd2+

表4 通过SCM拟合得到在生物炭上形成Cd2+配合物的结合常数

Table 4 Binding Constants for the Formation of Cd2+ Complexes on Biochar Obtained through SCM Fitting

样品	c₀/ (μmol·L^-1)	pK_≡SOCd⁺
样品	c₀/ (μmol·L^-1)	B₁	B₂	B₃
WB	20	1.5	2.5	3
WB	200	1.9	2.8	3.5
MgWB	20	1.1	2.1	2.2
MgWB	200	1.5	2.2	2.5

图6 生物炭位点分布及Cd2+吸附形态分布情况

Figure 6 Distribution of Biochar Sites and the Distribution of Cd2+ Adsorption Morphologies

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镁改性增强小麦秸秆生物炭对镉的吸附能力：表面络合模型研究

The Effect of Magnesium Modification on Enhancing Cadmium Adsorption Capacity of Wheat Straw Biochar: A Surface Complexation Modeling Approach

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