Optimization of Ammonia Nitrogen Adsorption Performance of Ginger Straw Modified Biochar by Response Surface Method

doi:10.11924/j.issn.1000-6850.casb2024-0774

Abstract

Abstract:

The study aimed to optimize the preparation process of ginger straw modified biochar through the response surface method to enhance its adsorption performance of ammonia nitrogen, so as to provide a new material for solving the problem of agricultural nitrogen pollution. The adsorption performance of modified biochar on ammonia nitrogen was evaluated by adsorption experiments. Initially, single-factor experiments were conducted with factors such as carbonization temperature, carbonization time, concentration of phosphoric acid solution and liquid-solid ratio, and then response surface experiments were performed based on above findings. The results indicated that the optimal process condition was as followed: carbonization temperature of 615℃, carbonization time of 1.5 h, phosphoric acid concentration of 25%, liquid-solid ratio of 15 mL/g. Under this condition, the adsorption value of modified biochar to ammonia nitrogen was very close to the predicted value. This study effectively applied the response surface method to optimize the modification technology of biochar, and provided a new solution for managing nitrogen pollution in practical agricultural practices.

Key words: modified biochar, response surface method, process optimization, agricultural nitrogen pollution, ginger straw

HUANG Yaqi, LI Xiangping, DING Yu, FU Xinyi, LIAO Qinhong, ZHANG Wenlin. Optimization of Ammonia Nitrogen Adsorption Performance of Ginger Straw Modified Biochar by Response Surface Method[J]. Chinese Agricultural Science Bulletin, 2025, 41(16): 82-89.

Figures/Tables 6

References 27

[1]	LI Y J, FENG Y Q, ZHAO Y Y, et al. A review of the uptake and utilization of different forms of nitrogen and its effects on plant physiological metabolism[J]. Journal of agricultural science and technology, 2023, 25(2):128-139.
[2]	ZHANG Y J, REN W C, ZHU K Y, et al. Substituting readily available nitrogen fertilizer with controlled-release nitrogen fertilizer improves crop yield and nitrogen uptake while mitigating environmental risks: A global meta-analysis[J]. Field crops research, 2024,306:109221.
[3]	蔡媛媛, 王瑞琪, 王丽丽, 等. 华北平原不同施氮量与施肥模式对作物产量与氮肥利用率的影响[J]. 农业资源与环境学报, 2020, 37(4):503-510.
[4]	ASIF M, ZORA S, CEYLAN Y, et al. Nitrogen supply in combination of nitrate and ammonium enhances harnessing of elevated atmospheric CO₂ through improved nitrogen and carbon metabolism in wheat (Triticum aestivum)[J]. Crop and pasture science, 2020, 71(2):101-112.
[5]	YU C Q, HUANG X A, CHEN H, et al. Managing nitrogen to restore water quality in China[J]. Nature, 2019,567:516-520.
[6]	王萌, 耿润哲. 农业面源氮污染控制措施滞后效应形成机理与评估方法研究进展[J]. 生态学报, 2024, 44(8):3132-3141.
[7]	ZHOU Y W, QIN S, VERMA S, et al. Production and beneficial impact of biochar for environmental application: A comprehensive review[J]. Bioresource technology, 2021,337;125451.
[8]	张伟明, 修立群, 吴迪, 等. 生物炭的结构及其理化特性研究回顾与展望[J]. 作物学报, 2021, 47(1):1-18. doi: 10.3724/SP.J.1006.2021.02021
[9]	袁帅, 赵立欣, 孟海波, 等. 生物炭主要类型、理化性质及其研究展望[J]. 植物营养与肥料学报, 2016, 22(5):1402-1417.
[10]	LENG L, XIONG Q, YANG L, et al. An overview on engineering the surface area and porosity of biochar[J]. Science of the total environment,2021:144204.
[11]	许云翔, 何莉莉, 陈金媛, 等. 生物炭对农田土壤氨挥发的影响机制研究进展[J]. 应用生态学报, 2020, 31(12):4312-4320. doi: 10.13287/j.1001-9332.202012.021
[12]	陈温福, 张伟明, 孟军, 等. 农用生物炭研究进展与前景[J]. 中国农业科学, 2013, 46(16):3324-3333. doi: 10.3864/j.issn.0578-1752.2013.16.003
[13]	顾芳宁, 韩守新, 王瀚标, 等. 添加改性生物炭对黑土氮素吸附及淋溶特性的影响[J]. 西北农林科技大学学报:自然科学版, 2023, 51(10):97-106.
[14]	张伟明, 陈温福, 孟军, 等. 东北地区秸秆生物炭利用潜力、产业模式及发展战略研究[J]. 中国农业科学, 2019, 52(14):2406-2424. doi: 10.3864/j.issn.0578-1752.2019.14.003
[15]	董成, 陈智勇, 谢迎新, 等. 生物炭连续施用对农田土壤氮转化微生物及N₂O排放的影响[J]. 中国农业科学, 2020, 53(19):4024-4034. doi: 10.3864/j.issn.0578-1752.2020.19.015
[16]	KAMAU S, KARANJA N K, AYUKE F O, et al. Short-term influence of biochar and fertilizer- biochar blends on soil nutrients, fauna and maize growth[J]. Biology and fertility of soils, 2019, 55(7):661-673.
[17]	刘慧屿, 娄春荣, 韩英祚, 等. 秸秆生物炭与减量氮肥配施对玉米氮素利用率及土壤结构的影响[J]. 土壤通报, 2020, 51(5):1180-1188.
[18]	王敏鸽, 刘艺文, 张丹丹, 等. 鼠李糖脂改性生物炭对盐渍土小白菜抗性及氮素吸收的影响[J]. 干旱地区农业研究, 2022, 40(5):81-87.
[19]	LIU Z G, DAI Y H, WEN T Y, et al. Study on the effect of magnesium chloride-modified straw waste biochar on acidic soil properties[J]. Molecules. 2024; 29(14):3268.
[20]	AHMED M B, ZHOU J L, NGO H H, et al. Progress in the preparation and application of modified biochar for improved contaminant removal from water and wastewater[J]. Bioresource technology, 2016,214:836-851.
[21]	左昊, 徐康宁, 孟萍萍, 等. 硫酸改性小麦秸秆生物炭对氨氮吸附特性研究[J]. 应用化工, 2017, 46(7):1237-1242.
[22]	朱倩, 张乃明, 夏运生, 等. 5种活性生物炭对水体低浓度氮、磷吸附效果研究[J]. 生态环境学报, 2021, 30(12):2387-2394. doi: 10.16258/j.cnki.1674-5906.2021.12.014
[23]	XAGORARIS M, SKOURIA A, REVELOU P K, et al. Response surface methodology to optimize the isolation of dominant volatile compounds from monofloral Greek thyme honey using SPME-GC-MS[J]. Molecules, 2021, 26(12):3612.
[24]	石月, 彭湃, 刘艳丽, 等. 响应曲面法优化紫外-亚铁活化过硫酸盐降解水中噻虫啉研究[J]. 中国环境科学, 2021, 41(11):5135-5159.
[25]	吴丹萍, 李海红, 张田田. 响应面法优化ZnCl₂/AlCl₃改性生物炭吸附甲基紫工艺[J]. 功能材料, 2021, 52(3):3153-3159. doi: 10.3969/j.issn.1001-9731.2021.03.023
[26]	ZHANG B, CHEN J X, HE Z X, et al. Hydrothermal liquefaction of fresh lemon-peel: Parameter optimisation and product chemistry[J]. Renewable energy, 2019,143:512-519.
[27]	HERATH G A D, POH L S, NG W J. Statistical optimization of glyphosate adsorption by biochar and activated carbon with response surface methodology[J]. Chemosphere, 2019,227:533-540.

水平	因素
水平	X₁/℃	X₂/h	X₃/%	X₄/(mL/g)
-1	500	1	20	10
0	600	1.5	30	15
1	700	2	40	20

水平	因素
水平	X₁/℃	X₂/h	X₃/%	X₄/(mL/g)
-1	500	1	20	10
0	600	1.5	30	15
1	700	2	40	20

方差来源	平方和	自由度	均方差	F值	P值
模型	1279.48	14	91.39	11.73	<0.0001
X₁	114.33	1	114.33	14.67	0.0018
X₂	5.11	1	5.11	0.6557	0.4316
X₃	99.53	1	99.53	12.77	0.0031
X₄	4.53	1	4.53	0.5809	0.4586
X₁X₂	12.74	1	12.74	1.64	0.2217
X₁X₃	2.02	1	2.02	0.2588	0.6189
X₁X₄	5.02	1	5.02	0.6439	0.4357
X₂X₃	41.80	1	41.80	5.36	0.0362
X₂X₄	3.03	1	3.03	0.3886	0.5431
X₃X₄	1.03	1	1.03	0.1322	0.7216
X₁²	835.88	1	835.88	107.27	<0.0001
X₂²	274.10	1	274.10	35.18	<0.0001
X₃²	127.69	1	127.69	16.39	0.0012
X₄²	23.49	1	23.49	3.01	0.1044
残差	109.09	14	7.79
失拟项	96.35	10	9.64	3.03	0.15

方差来源	平方和	自由度	均方差	F值	P值
模型	1279.48	14	91.39	11.73	<0.0001
X₁	114.33	1	114.33	14.67	0.0018
X₂	5.11	1	5.11	0.6557	0.4316
X₃	99.53	1	99.53	12.77	0.0031
X₄	4.53	1	4.53	0.5809	0.4586
X₁X₂	12.74	1	12.74	1.64	0.2217
X₁X₃	2.02	1	2.02	0.2588	0.6189
X₁X₄	5.02	1	5.02	0.6439	0.4357
X₂X₃	41.80	1	41.80	5.36	0.0362
X₂X₄	3.03	1	3.03	0.3886	0.5431
X₃X₄	1.03	1	1.03	0.1322	0.7216
X₁²	835.88	1	835.88	107.27	<0.0001
X₂²	274.10	1	274.10	35.18	<0.0001
X₃²	127.69	1	127.69	16.39	0.0012
X₄²	23.49	1	23.49	3.01	0.1044
残差	109.09	14	7.79
失拟项	96.35	10	9.64	3.03	0.15