Preparation of Acid-Modified Biochar and Remediation Mechanisms on Soda–Saline–Alkali Soil

Abstract

Soil salinization poses significant threats to food security and ecosystem functions, while acid-modified biochar functions as an effective carbon-based material for the reclamation of saline–alkali soils. In this study, acid-modified biochars prepared using boric (BC), sulfuric (SC), hydrochloric (HC), acetic (AC), phosphoric (PC), and oxalic (OC) acids were analyzed. The ameliorative effects of acid-modified biochar on soda–saline–alkaline soils were evaluated through adsorption and pot experiments, with preliminary insights into its mechanism of action. The results indicated that the specific surface area and maximum adsorption capacities (Q_m) of conventional biochar and OC were 5.91, 35.39 m² g⁻¹ and 21.62, 41.00 mg g⁻¹, respectively. After the addition of conventional biochar, OC and SC in pot experiments, soil pH, (CO₃²⁻ + HCO₃⁻) content, and exchangeable sodium percentage (ESP) were significantly reduced. Compared to conventional biochar, SC increased the relative abundance of Bacillus, Adhaeribacter, and Preussia, while OC increased the relative abundance of Antarcticbacterium, Diezia, and Peziza. OC and SC maximally increased both the aboveground and belowground biomass of Medicago falcata L., while simultaneously reducing sodium content. This study demonstrated that biochar modified with SC and OC significantly reduced soda–saline–alkali stress. SC and OC exhibited greater potential in remediating soda–saline–alkali soils.

1. Introduction

Soil salinization results from both natural and anthropogenic factors, posing a significant threat to food security and ecosystem functions [1]. Soil salinization reduces agricultural productivity, thereby threatening ecological stability and hindering sustainable economic development [2]. Soda–saline–alkali soil is a typical type of saline–alkali soil, and the Songnen Plain is one of the three primary regions globally with concentrated distribution of soda–saline–alkali soils [3] located in the central part of Northeast China. A key characteristic of soda–saline–alkali soil is its high sodium (${\mathrm{Na}}^{+}$) content, where excessive sodium competes with essential plant nutrients such as magnesium (${\mathrm{Mg}}^{2+}$), calcium (${\mathrm{Ca}}^{2+}$), and potassium (${\mathrm{K}}^{+}$) in the soil. Excessive soil ${\mathrm{Na}}^{+}$ stress leads to nutrient deficiencies and a subsequent decrease in crop yields [4]. Biochar is produced through the pyrolysis of biomass under high-temperature anaerobic conditions, characterized by high stability, a unique porous structure, and a large specific surface area (BET) [5]. Biochar has garnered widespread attention due to its effectiveness in remediating saline–alkali soils [6]. Biochar has a significant effect on the removal of ${\mathrm{Na}}^{+}$ from water and soil. Scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX) analysis demonstrate that biochar can effectively adsorb ${\mathrm{Na}}^{+}$ from water and soil [7]. The ${\mathrm{Na}}^{+}$ adsorption capacity of biochar has become a prominent research focus. As the pyrolysis temperature in the biochar preparation process increases, the aromaticity and stability of biochar improve, enhancing its ability to adsorb ${\mathrm{Na}}^{+}$ in water and soil [8]. Nguyen et al. found that biochar derived from rice husk exhibits a stronger adsorption capacity for ${\mathrm{Na}}^{+}$ than biochars made from corn stover or coconut husk. Enhancing the ${\mathrm{Na}}^{+}$ adsorption capacity of biochar, conducting further research on this adsorption process, and exploring its intrinsic mechanisms in mitigating soda–saline–alkali soil stress are of great significance [9]. Biochar is an effective soil amendment for remediating degraded soils [10,11,12]. Biochar promotes carbon sequestration by introducing biochar-derived persistent carbon into the soil, enhancing organo-organic and organo-mineral interactions, and altering soil microbial communities [13]. Biochar can improve the soil environment and enhance crop water and fertilizer utilization efficiency, inhibit greenhouse gas emissions, and effectively improve soil structure [14,15]. The application of biochar can reduce the pH, salinity, and ${\mathrm{Na}}^{+}$ content in saline–alkali soils, while increasing soil cation exchange capacity (CEC), enhancing key enzyme activities, and improving soil nutrient availability and microbial diversity [16,17]. Applying biochar to saline–alkali soils can enhance the growth of crops (such as tomatoes, eggplants, and corn) and improve the yield and quality of agricultural products [15,16,17,18]. The suboptimal pore structure of standard porous biochar limits its adsorption capacity. Physical and chemical methods can activate and modify the biochar structure, increasing its adsorption capacity and thereby enhancing its ability to adsorb pollutants. The effectiveness of biochar in these improvements largely depends on the chemical composition of the precursor material and the key operational conditions during the pyrolysis process. Biochar produced from lignocellulosic waste (e.g., wood chips and straw) at elevated temperatures (>500 °C) typically exhibits a larger BET and a more developed pore structure, making it more conducive to adsorbing pollutants and providing habitats for microorganisms [10]. In contrast, biochar derived from livestock manure and similar feedstocks is typically rich in ash and mineral nutrients, which enable more direct soil nutrient supplementation [19]. Furthermore, the pyrolysis temperature significantly influences biochar’s surface functional groups and pH. Low-temperature biochar (<400 °C) generally retains more oxygen-containing functional groups and exhibits a lower pH, whereas high-temperature biochar (>500 °C) shows enhanced surface alkalinity and reduced functional groups [8]. Therefore, when applying biochar for specific soil improvement objectives, its characteristics must be precisely selected or engineered according to the intended function.

Biochar modification technologies and processes are typically targeted and based on the specific characteristics of polluted and degraded soils. Li et al. modified biochar with humic acid and applied the humic-modified biochar to saline–alkali soil to compensate for the lack of effective carbon nutrients, ultimately achieving high-yield and high-quality Chinese cabbage [20]. Luo et al. investigated the characteristics of soda–saline–alkali soil and used magnesium and activated iron tailings to modify biochar [21]. Compared to unmodified biochar, this modified biochar increased soil CEC, exchangeable sodium percentage (ESP), and effectively improved soil nutrient availability. However, studies have shown that biochar can release its own ${\mathrm{Na}}^{+}$ into the soil and water [9]. This can lead to an increase in the content of ${\mathrm{Na}}^{+}$ in soda–saline–alkali soils, exacerbating ${\mathrm{Na}}^{+}$ stress on crops. Therefore, the use of acid-modified biochar for remediating soda–saline–alkali soils is more targeted. Acid-modified biochar is regarded as an effective carbon-based material for remediating saline–alkali soils [22]. Treating biochar with acid is a simple, cost-effective process. This process can remove surface impurities, unclog small pores, provide additional cation adsorption sites, increase the BET of biochar, and enhance the types and quantities of functional groups on the biochar surface [23,24,25]. Compared to unmodified biochar, acid-modified biochar effectively reduces the pH of saline–alkali soils, increases available phosphorus content, and optimizes soil microbial community structure [26]. Excessive ${\mathrm{Na}}^{+}$ in soda–saline–alkali soils is a major factor that stresses plant growth; therefore, it is essential to study the ${\mathrm{Na}}^{+}$ adsorption characteristics of acid-modified biochar. Additionally, among several acid-modified biochar types, hydrochloric acid and sulfuric acid are strong inorganic acids representing the highest hydrogen proton-supplying capacity, which efficiently etch the biochar surface through intense protonation, introducing acidic sites. Phosphoric acid is a moderately strong/oxygen-containing inorganic acid. It introduces phosphate groups into the biochar structure besides ${\mathrm{H}}^{+}$ provision. This may influence biochar’s phosphorus retention and its specific interactions with metal cations in soil. Acetic acid and oxalic acid represent a class of environmentally friendly natural organic acids. Their modification mechanisms focus more on complexation and the introduction of oxygen-containing functional groups (such as carboxyl groups) through reactions like esterification. Boric acid exhibits unique behavior in solution; it is not a typical protonic acid but acts as a Lewis acid to bind with hydroxyl-containing compounds. The mechanism through which acid-modified biochar improves soda–saline–alkali soils remains unclear at present. Based on this, this study selected straw biochar (hereinafter referred to as unmodified biochar), commonly used for saline–alkali soil remediation, as the raw material. Six acids (boric acid, phosphoric acid, acetic acid, hydrochloric acid, sulfuric acid, and oxalic acid) were employed to modify it. Adsorption experiments compared the ${\mathrm{Na}}^{+}$ adsorption capacities of acid-modified biochar variants. Subsequently, potted alfalfa (Medicago falcata L.) trials were conducted to comprehensively evaluate their ameliorative effects on soda–alkaline saline–alkali soils. This study proposes the following core hypothesis: Acid-modified biochar increases cation exchange capacity through surface functionalization, thereby significantly enhancing ${\mathrm{Na}}^{+}$ adsorption capacity. This process not only directly reduces exchangeable sodium content in soil but also synergistically lowers soil pH, increases nutrient availability, and drives beneficial shifts in microbial community structure, ultimately alleviating soda–alkali stress.

The objectives of this study were (1) to prepare acid-modified biochar using different acid reagents and investigate the effects of acid modification on biochar’s BET, porosity, and surface functional groups, (2) to examine the adsorption characteristics of acid-modified biochar for ${\mathrm{Na}}^{+}$, and (3) to conduct pot experiments to determine soil salinity indices, key soil enzyme activities, microbial community structure, and alfalfa biomass. This study proposes a novel and effective method for alleviating soda–saline–alkali soil stress and further explores the potential mechanisms of action.

2. Materials and Methods

2.1. Experimental Materials, Preparation, and Characterization of Acid-Modified Biochar

The soda–saline–alkali soil used in this study was collected from Changing County, Songyuan City, Jilin Province, China (44°45’ N, 123°45’ E). The basic physical and chemical properties of the soda–saline–alkali soil are as follows: pH, 9.68; EC, 659.44 μS cm⁻¹; CEC, 14.83 cmol kg⁻¹; total organic matter, 9.23 g kg⁻¹; total nitrogen, 0.87 g kg⁻¹; available phosphorus, 18.23 mg kg⁻¹; available potassium, 165.62 mg kg⁻¹. The biochar used in this study was obtained from Liyuan Environmental Protection Co., Ltd. (Beijing, China). The raw material for preparing the biochar was corn straw. A specified quantity of corn straw was pyrolyzed for 25 min in an anaerobic pyrolysis furnace at 500 °C. The pyrolysis product was pulverized to a particle size of 0.25 mm for subsequent use [10]. All reagents used in this study were of analytical grade.

In this study, the acidic chemical reagents used were sulfuric acid (H₂SO₄), hydrochloric acid (HCl), oxalic acid (H₂C₂O₄), boric acid (H₃BO₃), acetic acid (CH₃COOH), and phosphoric acid (H₃PO₄), each at a concentration of 20%, except for boric acid, which was at 10%. The biochar was mixed with the acid solution at a 1:10 ratio. The specific modification method was adapted with modifications from Liu et al. and He et al. [10,24]. The acid-modified biochar was placed on a magnetic stirrer and stirred for 12 h at 80 °C. The modified biochar was washed with distilled water, fully stirred, and left to stand to allow the biochar to settle. The supernatant was decanted, and the pH value was measured. The washing steps were repeated until the pH value of the supernatant stabilized between 6.5 and 7.5, and the biochar, washed to neutrality, was dried at 105 °C for later use. The naming conventions and treatment settings are provided in

Table A1. Soil pH of different treatments.

	CK	C	BC	SC	ClC	YC	PC	OC
pH	9.54 ± 0.03 a	9.34 ± 0.03 b	9.21 ± 0.05 c	9.07 ± 0.04 g	9.12 ± 0.03 ef	9.20 ± 0.03 c	9.15 ± 0.03 de	9.11 ± 0.03 fg

CK: Soda–saline–alkali soil without adding any external additives; C: soda–alkali soil with unmodified biochar added (10 g kg⁻¹ soil); BC: soda–alkali soil with H₃BO₃ modified biochar (10 g kg⁻¹ soil); SC: soda–saline–alkali soil with H₂SO₄ modified biochar (10 g kg⁻¹ soil); ClC: soda–saline–alkali soil with HCl modified biochar (10 g kg⁻¹ soil); YC: soda–alkali soil with CH₃COOH modified biochar (10 g kg⁻¹ soil); PC: soda–saline–alkali soil with H₃PO₄ modified biochar (10 g kg⁻¹ soil); OC: soda–saline–alkali soil with H₂C₂O₄ modified biochar (10 g kg⁻¹ soil). Use Duncan’s test to explore the differences in data, where different letters in the table represent significant differences (p < 0.05).

. Each treatment was performed in triplicate. Adsorption experiments were initially performed to determine the ${\mathrm{Na}}^{+}$ adsorption capacity of the acid-modified biochars, followed by characterization to elucidate the mechanisms underlying the enhanced adsorption capacity.

The crystalline structure of the biochar was determined using X-ray diffraction (XRD, ESCALAB-250Xi, Thermo Fisher Scientific, Waltham, MA, USA) with CuKα radiation. The functional groups were analyzed using Fourier transform infrared spectroscopy (FTIR, NEXUS, Thermo Fisher Scientific, Waltham, MA, USA). A fully automatic BET and microporous physical adsorption analyzer was used to measure the specific surface area and porosity (BET, ASAP 2020HD88, Micromeritics Instrument Corporation, Norcross, GA, USA). The zeta potential (ζ) of the biochar was measured using Malvern Instruments Zetasizer-Nano ZS (Malvern Panalytical Ltd., Malvern, UK), as described in Gao et al. [27]. SEM-EDS (SEM, Hitachi Regulus 8100, Hitachi High-Technologies Corporation, Tokyo, Japan) was employed to observe the surface morphology of the biochar.

2.2. Adsorption Characteristics

The adsorption experiments for ${\mathrm{Na}}^{+}$ were divided into four parts: (1) For the effect of pH on the adsorption performance of biochar, 1% of ${\mathrm{Na}}^{+}$ was added to the solution using NaCl as the Na source, and 0.01 mol L⁻¹ of HCl and KOH were used to adjust the pH of solutions to 6, 7, 8, 9, 10, and 11. Then, 40 mg of different biochars were added in 40 mL of ${\mathrm{Na}}^{+}$ solutions at different pH levels. The suspensions were then shaken at 25 °C for 48 h. After the pH of the suspensions stabilized, they were centrifuged at 4500 rpm for 5 min. The supernatant was rapidly filtered through a 45 μm filter membrane before analysis. (2) Isothermal adsorption experiment: 0, 0.05, 0.25, 0.50, 1.00, and 1.50% ${\mathrm{Na}}^{+}$ solutions were prepared, and the pH was adjusted to 8. Then, 40 mg of different biochars were added to 40 mL solutions at varying concentrations; the suspensions were shaken at 25 °C for 48 h, then centrifuged at 4500 rpm for 5 min. The supernatant was rapidly filtered through a 45 μm filter membrane before detection. (3) Adsorption kinetics: A 1% ${\mathrm{Na}}^{+}$ solution with a pH of 8 was used as the background solution, and different biochars were added. The time unit was second (s), and samples were taken at 15, 50, 100, 200, 300, 600, and 1200 s on a magnetic stirrer at a speed of 1000 rpm. Samples were quickly filtered through a 45 μm membrane for testing. (4) The effect of coexistence cations: A 1% ${\mathrm{Na}}^{+}$ solution with a pH of 8 was prepared by adding 0, 0.1 mM, 0.25 mM, and 1 mM of ${\mathrm{Ca}}^{2+},{\mathrm{Mg}}^{2+},{\mathrm{K}}^{+}$ and ${\mathrm{Cu}}^{2+}$, using CaSO₄, MgSO₄, CuSO₄ and KCl to prepare the solutions. Then, the solutions were placed in a constant temperature shaker and shaken at 25 °C and 120 rpm for 12 h. Finally, the solid–liquid mixture was passed through a 45 μm filter membrane for testing. The pseudo-first-order (PSO) (Equation (1)) is as follows:

$$Ln \left(q_e-q_t\right)= Ln q_e-kt$$

(1)

where qt and $q_e$ (mg⋅g⁻¹) represent the adsorption amount of Na⁺ at t time and equilibrium, and k (min⁻¹) is the rate constants of PSO.

The Langmuir isotherm and isothermal adsorption models are expressed as the following equations:

$$C_e/q_e= 1/(K_L \times { Q}_m)+C_e/Q_m$$

(2)

$$q_e=a-b{c}^x$$

(3)

where Ce is the equilibrium concentration of Na⁺ measured in mg L⁻¹, Q_e and Q_m are the values for equilibrium adsorption capacity and maximum adsorption capacity of Na⁺, and K_L represents the Langmuir constants, a, b and c are constants, and x is Na⁺ concentration.

2.3. Potting Experiment and Sampling Collection

The collected soil samples were air-dried and passed through a 2 mm sieve for subsequent experiments. A total of 250 g of soil was placed in polyethylene flower bowls. Ten grams of biochar modified with different acids were added per kilogram of soil. Alfalfa (Medicago falcata L.) was used to assess the remediation effect of acid-modified biochar on saline–alkali soil. Plump alfalfa seeds were selected and soaked in a 10% NaClO solution for 30 min. The seeds were washed three times with tap water and distilled water, then soaked overnight in distilled water. Ten seeds were planted in each bowl. The seedlings were thinned within 7 days after sowing, and 3 seedlings were kept in each pot. The plants were grown in a greenhouse with the temperature maintained between 18 and 25 °C, and an average daily light duration of approximately 6.5 h. The pots were rotated daily to avoid light differences. The relative air humidity was maintained at approximately 65%, and distilled water was supplemented during the culture period to maintain soil moisture at approximately 10%. Fresh alfalfa and soil samples were collected after 30 days of growth for subsequent laboratory analysis [28]. Each treatment was performed in triplicate.

2.4. Determination of Physical and Chemical Indicators

The incubated soil samples were suspended in ultrapure water at ratios of 1:5 and 1:2.5 for the measurement of EC and pH. The sample suspensions were shaken for 10 min, after which the EC and pH values were measured using the conductivity and the potentiometric methods, respectively. CEC and ENa were determined following Schacht and Marschner [29]. The content of (${\mathrm{H}\mathrm{C}\mathrm{O}}_3^{-}$ + ${\mathrm{C}\mathrm{O}}_3^{2-}$) was determined according to Wang et al. [30]. The content of Na in plants was determined following the method of Ramandi et al. [31]. The ESP was defined as

$$\mathrm{ESP}=100\% \times \mathrm{ENa}/\mathrm{CEC}$$

(4)

The methods for determining β-glucosidase, invertase, and urease activities in soil were based on the studies of Cai et al. and Kaur et al. [32,33]. β-glucosidase assay was performed as follows: Place 1 g of the fresh soil sample in a 100 mL conical flask. Add 0.25 mL of toluene and allow it to stand in a fume hood for 10 min. Add 4 mL of MUB solution (pH 6.0) and 1 mL of PNPG solution, mix thoroughly, and incubate at 37 °C for 1 h. Add 1 mL of CaCl₂ solution and 4 mL of 0.1 M Tris buffer (pH 12.0). Shake well, then filter rapidly through filter paper. Measure the absorbance of the filtrate at 400 nm. Soil β-glucosidase activity was defined as μg p-nitrophenol g⁻¹ h⁻¹. The method for determining soil invertase activity is as follows: Weigh 1 g of soil and place it in a 50 mL conical flask. Add 7.5 mL of an 8% sucrose solution, 2.5 mL of phosphate buffer solution at pH 5.5, and 5 drops of toluene. Shake the mixture thoroughly and incubate at 37 °C for 24 h. Filter the mixture, transfer 1 mL of the filtrate to a small test tube, add 3 mL of LDNS reagent, and heat in a boiling water bath for 5 min. Immediately cool the test tube under running tap water for 3 min. The solution turns orange–yellow. Transfer the liquid from the test tube to a 100 mL volumetric flask and dilute to 50 mL with distilled water. Perform colorimetry at 508 nm using a spectrophotometer (UH5300, Hitachi High-Technologies Corporation, Tokyo, Japan). To eliminate errors caused by pre-existing sucrose and glucose in the soil, a matrix-free control must be prepared for each soil sample, and a soil-free control must be included throughout the experiment. Soil invertase activity was expressed as mg glucose g⁻¹ (24 h)⁻¹ under the assay condition. The method for determining soil urease activity is as follows: Mix 1 g of air-dried soil with 0.2 mL of toluene in a 100 mL volumetric flask. After standing for 15 min, add 2 mL of a 10% urea solution and 4 mL of citric acid buffer (pH 6.7). Mix thoroughly and incubate at 37 °C for 24 h. Then, add distilled water to the mark, shake well, and filter the suspension into a conical flask. Transfer 3 mL of the filtrate to a 50 mL volumetric flask. Add 10 mL of distilled water and shake vigorously. Add 4 mL of sodium phenolate, mix thoroughly, then add 3 mL of sodium hypochlorite. Shake vigorously again and let stand for 20 min. Dilute to the mark with water, and the solution turns blue. Perform a colorimetric measurement of the developed solution at 578 nm using a spectrophotometer within 1 h. Soil urease activity was expressed as mg NH₄⁺ g⁻¹ (24 h)⁻¹. Each sample was tested in triplicate. The determination methods for soil available nitrogen (AN), available phosphorus (AP), and available potassium (AK) were based on the method proposed by Wan et al. [34]. The determination method for CAT is based on Liu et al. [35], where the unit is defined as the change of 0.01 in absorbance per gram of sample per milliliter of reaction system at 470 nm.

2.5. Analysis of Microbial Community Structure

The purification and isolation of DNA were carried out according to the Chen et al. [36]. The hypervariable region V3-V4 of the bacterial 16S rRNA gene was amplified with primer pair 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) [37]. Amplification of the ITS1 region of the fungal gene was carried out using primer pair ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2R (5′-GCTGCGTTCTTCATCGATGC-3′). The PCR products of the same sample were using 2% agarose gel to recover the PCR products, using the AxyPrep DNA Gel Ex-traction Kit (Axygen Biosciences, Union City, CA, USA) to purify the recovered products, 2% agarose gel electrophoresis was used to detect, and Quantus™ Fluorometer (Promega, Madison, WI, USA) was used to detect and quantify the recovered products. Sequencing was performed using Illumina’s Miseq PE300/NovaSeq PE250 platform (Illumina Inc., San Diego, CA, USA). The sequences were analyzed for microbial ecological quantification. All sequences were clustered into operational taxonomic units (OTUs) based on a 97% threshold identity by the SILVA database (https://www.arb-silva.de/, accessed on 25 December 2023). A representative sequence from each OTU was selected for downstream analysis.

2.6. Data Statistical Analysis

The results for soil and alfalfa indicators were expressed as mean ± standard deviation (n = 3), and analysis of variance (ANOVA) was performed using SPSS 25.0 (α = 0.05). Duncan’s test (p < 0.05) was used for multiple comparisons. Microbial data are available on the Meiji Biological Cloud platform (https://cloud.majorbio.com, accessed on 12 February 2024). Microbial communities (composition and unique species) were visualized using OTU tables and Venn diagrams to illustrate shared and unique OTUs between groups. α-diversity indices (Chao 1, Shannon index, and Ace index) were calculated using Mothur software (version 1.48.0). Microbial communities (differentially abundant species) were analyzed using linear discriminant analysis effect size (LEfSe) to identify statistically significant species differences between groups. This method first employed the Kruskal–Wallis test to detect differences in species abundance among groups, followed by LEfSe to assess the magnitude of effect for these differentially abundant species (LDA > 3.5).

3. Results and Discussion

3.1. Na⁺ Adsorption of Acid-Modified Biochar

The maximum adsorption capacity of various biochars in Na⁺ solution at pH 8 was determined using isothermal adsorption experiments (Figure 1a). The minimum Q_e was −19.70 mg g⁻¹, observed in the ${\mathrm{Na}}^{+}$ solution with a concentration of 0%. A positive Q_e value appeared when the ${\mathrm{Na}}^{+}$ concentration exceeded 0.5%. Acid-modified biochar exhibited a positive Q_e at a ${\mathrm{Na}}^{+}$ concentration of 0.05%. The highest Q_e in the OC treatment was 27.78 mg g⁻¹ at a concentration of 1.5%. This indicated that C released ${\mathrm{Na}}^{+}$ in low-concentration solutions but could also adsorb ${\mathrm{Na}}^{+}$ as the concentration exceeded 0.05%. After modification, the original ${\mathrm{Na}}^{+}$ in biochar was effectively removed, allowing it to exhibit adsorption capacity for ${\mathrm{Na}}^{+}$ when the concentration was higher than 0.05%. According to the isothermal adsorption experiment, OC and SC exhibited the highest adsorption performance. Therefore, subsequent adsorption experiments were conducted exclusively on C, OC, and SC under various conditions. The experimental data were fitted to the Langmuir isotherm model, and the model parameters are shown in

Table A2. Isothermal model parameters of Na⁺.

Sample	Langmuir
	Qm (mg g−1)	KL (L mg−1)	R2
C	-	-	-
OC	41.0082	0.0019	0.9567
SC	34.4761	0.0013	0.9417

C: Soda–alkali soil with unmodified biochar added (10 g kg⁻¹ soil); OC: soda–saline–alkali soil with H₂C₂O₄ modified biochar (10 g kg⁻¹ soil); SC: soda–saline–alkali soil with H₂SO₄ modified biochar (10 g kg⁻¹ soil).

. Based on the R² value, the Langmuir model fit the adsorption of OC and SC well. However, due to the release performance of C in low-concentration solutions, the Langmuir model could not fit its nonlinear adsorption curve. Therefore, the Q_e of C and OC in a 1.5% concentration solution was used as the estimated value, and the Q_m of C was 21.62 mg g⁻¹. OC showed the highest K_L value (0.0019) and Q_m value (41.00 mg g⁻¹), indicating more stable and efficient adsorption. Thus, the biochar modified by sulfuric and oxalic acids effectively improved its adsorption capacity for ${\mathrm{Na}}^{+}$. As shown in Figure 1b, the adsorption models of the acid-modified biochar in a 1% ${\mathrm{Na}}^{+}$ solution conform to quasi-first-order adsorption kinetics.

Meanwhile, we simulated the effect of biochar on ${\mathrm{Na}}^{+}$ adsorption under different pH values (7–11) (Figure 1c) and cation coexistence (${\mathrm{Ca}}^{2+},{\mathrm{Mg}}^{2+},{\mathrm{K}}^{+},$ and ${\mathrm{Cu}}^{2+}$) (Figure 1d) in solution. The three types of biochar exhibited the highest Q_e values at pH 8, with the Q_e values decreasing as pH increased. The highest value was observed for OC at pH 8 (18.20 mg g⁻¹), while the lowest value was observed for C at pH 11 (2.90 mg g⁻¹). The adsorption capacity of biochar for ${\mathrm{Na}}^{+}$ in low-concentration cations (0.1 mM) was minimal and significantly decreased as the cation concentration increased. This may be because ${\mathrm{Ca}}^{2+}$, ${\mathrm{Mg}}^{2+}$, and ${\mathrm{Cu}}^{2+}$ competed with ${\mathrm{Na}}^{+}$ for adsorption sites on biochar, resulting in a significant decrease in the adsorption capacity for ${\mathrm{Na}}^{+}$. However, even at the highest cation concentration, the adsorption capacity of OC and SC was 3.56 and 2.20 times higher than that of C, respectively. These results indicated that OC and SC could effectively remove ${\mathrm{Na}}^{+}$ under different conditions and have promising application potential.

3.2. Characterization of Acid-Modified Biochar

This study characterized and analyzed C, OC, and SC, with OC and SC demonstrating the best adsorption performance. According to Figure 2a, C, OC, and SC exhibited a carbon peak, and after modification with H₂SO₄, the intensity of this peak increased. C contained a significant amount of CaCO₃. After modification with H₂C₂O₄, OC contained some CaC₂O₄·H₂O and CaCO₃, whereas after modification with H₂SO₄, only CaSO₄ was present in SC. This could be attributed to the strong acidity of H₂SO₄, which could completely corrode CaCO₃ in biochar. In contrast, H₂C₂O₄ had weaker acidity and only corroded CaCO₃ on the surface of biochar. After modification, a certain amount of Ca in the original biochar was retained. When biochar was applied to the soil, it increased the soil cation exchange capacity, thereby reducing the soil sodium adsorption ratio. However, since CaC₂O₄·H₂O and CaCO₃ are calcium salts insoluble in water, H₂C₂O₄ was more effective in retaining the original calcium in the biochar.

3.3. Soil Salinity Index, Key Enzyme Activities, and Available Nutrients

According to Table A1, all acid-modified biochar treatments significantly reduced soil pH compared to the CK treatment (p < 0.05). The largest reductions were observed in the OC and SC treatments, with decreases of 0.23 and 0.27 units compared to C, respectively. From

Table 1. Soil salinity indexes.

Treatments	EC (μs cm−1)	CEC (cmol kg−1)	ENa (cmol kg−1)	CO32− + HCO3− (mg kg−1)	ESP (%)
CK	652.44 ± 9.15 d	15.74 ± 0.70 c	3.22 ± 0.03 a	1447.61 ± 18.76 a	20.59 ± 1.09 a
C	802.44 ± 5.23 a	18.71 ± 0.17 a	3.28 ± 0.02 b	1305.09 ± 16.27 b	16.25 ± 0.24 b
OC	783.11 ± 2.22 b	18.10 ± 0.38 ab	2.73 ± 0.01 c	1018.57 ± 13.75 c	15.09 ± 0.30 c
SC	767.89 ± 4.24 c	17.69 ± 0.30 b	2.80 ± 0.01 d	977.08 ± 6.81 d	15.90 ± 0.15 bc

CK: Soda–alkali soil without added substances; C: soda–saline–alkali soil with unmodified biochar added (10 g kg⁻¹ soil); SC: soda–saline–alkali soil with H₂SO₄ modified biochar (10 g kg⁻¹ soil); OC: soda–saline–alkali soil with H₂C₂O₄ modified biochar (10 g kg⁻¹ soil). Using Duncan’s test to explore the differences in data, where different letters in the table represent significant differences (p < 0.05).

, it was evident that, compared to CK, the three types of biochar reduced (${\mathrm{H}\mathrm{C}\mathrm{O}}_3^{-}$ + ${\mathrm{C}\mathrm{O}}_3^{2-}$) and ESP to varying degrees, while increasing EC values. Compared to treatment C, both OC and SC treatments reduced soil EC, ENa, (${\mathrm{H}\mathrm{C}\mathrm{O}}_3^{-}$ + ${\mathrm{C}\mathrm{O}}_3^{2-}$), and ESP. Specifically, the OC treatment had the largest decreases in ENa and ESP, reducing by 16.67% and 8.18%, respectively, while the SC treatment had the greatest reductions in EC and (${\mathrm{H}\mathrm{C}\mathrm{O}}_3^{-}$ + ${\mathrm{C}\mathrm{O}}_3^{2-}$), decreasing by 4.31% and 25.14%, respectively. This indicated that biochar modified with sulfuric acid and oxalic acid could effectively mitigate soil saline–alkali barriers. The application of biochar could effectively mitigate soil saline–alkali barriers [17]. The possible reason was that the use of acid-modified biochar changed the surface functional groups, particularly carboxyl groups, and enhanced the electrostatic adsorption capacity of biochar (Figure 2a,c), which more efficiently adsorbed Na⁺ in soil compared to C (Figure 1).

Invertase catalyzes the hydrolysis of sucrose in soil, producing glucose and fructose [38]. β-glucosidase is a component of the cellulose-degrading enzyme system [39]. Soil urease catalyzes the hydrolysis of urea, generating ammonia in the soil [40]. Application of all three types of biochar significantly increased (p < 0.05) the activity of invertase compared to CK (Figure 3b). The initial activity of soil invertase was 0.97 mg glucose g⁻¹ (24 h)⁻¹. Compared to the C treatment, both OC and SC treatments significantly (p < 0.05) increased soil invertase activity by 27.56% and 30.71%, respectively. The initial activity of soil urease was 0.69 mg NH₄⁺-N g⁻¹ (24 h)⁻¹ (Figure 3c). Application of all three types of biochar increased the activity of urease compared to CK, with OC treatment significantly increasing (p < 0.05) soil urease activity by 7.46%. However, for soil β-glucosidase activity, no significant difference was observed among the treatments (Figure 3a).

For soil content of AN and AK, the C treatment showed improvement compared to CK, with the difference in AK being significant (p < 0.05) (Figure 3d,f). Compared to the C treatment, both OC and SC significantly increased soil AP content, with OC showing the greatest increase of 21.63% (Figure 3e). Although the AN and AK contents in the OC and SC treatments were higher than those in the C treatment, the increases were not significant (Figure 3d,f). Research indicates that biochar supplements soil organic matter, providing energy to enhance soil carbon and nitrogen enzyme activities [41]. These results suggest that the application of OC and SC affects soil carbon and nitrogen cycling. OC and SC may enhance the activities of key soil carbon and nitrogen enzymes more effectively, possibly due to reduced soil salinity stress (Table 1) and increased soil microbial diversity (

Table 2. Soil microorganism alpha diversity.

Treatments	Bacterial				Fungal
	Ace	Chao1	Shannon	Coverage	Ace	Chao1	Shannon	Coverage
CK	3779.98 ± 122.47 c	3695.61 ± 126.52 c	5.84 ± 0.14 c	0.972	295.62 ± 7.74 b	294.63 ± 6.09 b	2.79 ± 0.06 ab	0.973
C	4030.53 ± 159.03 bc	3880.77 ± 136.64 bc	6.05 ± 0.18 b	0.981	352.22 ± 25.83 a	359.60 ± 20.07 a	2.84 ± 0.06 ab	0.976
OC	4119.67 ± 131.50 b	3997.36 ± 112.88 b	6.06 ± 0.21 b	0.983	370.01 ± 24.52 a	369.85 ± 25.07 a	2.32 ± 0.08 b	0.979
SC	4411.51 ± 236.70 a	4289.86 ± 192.80 a	6.42 ± 0.15 a	0.976	337.61 ± 10.00 a	340.79 ± 6.23 a	3.39 ± 0.81 a	0.971

CK: Soda–alkali soil without added substances; C: soda–saline–alkali soil with unmodified biochar added (10 g kg⁻¹ soil); SC: soda–saline–alkali soil with H₂SO₄ modified biochar (10 g kg⁻¹ soil); OC: soda–saline–alkali soil with H₂C₂O₄ modified biochar (10 g kg⁻¹ soil). Using Duncan’s test to explore the differences in data, where different letters in the table represent significant differences (p < 0.05).

).

3.4. Analysis of Soil Microbial Composition

This study conducted a sequencing analysis of soil microorganisms after 30 days of alfalfa cultivation. The relative abundances of bacterial and fungal taxonomic groups are presented in Figure 4. The top 15 bacterial and fungal taxa were analyzed to reveal the characteristics of the microbial community structure during the incubation period. At the phylum level, the dominant bacterial phyla across all groups were Actinobacteriota, Proteobacteria, Chloroflexi, Bacteroidota, Acidobacteriota, and Firmicutes, comprising 89.53–92.15% of the total bacterial population (Figure 4a). Compared to CK, the C treatment reduced the relative abundance of Actinobacteria, Bacteroidota, and Firmicutes, while increasing the relative abundance of Proteobacteria, Chloroflexi, and Acidobacteriota. Compared to treatment C, the relative abundance of Firmicutes increased by 96.38% and 26.26% in the OC and SC treatments, respectively. Firmicutes are key contributors to reducing soil-borne diseases (RSD) and can improve soil health [42]. The relative abundance of Myxococcota increased by 21.86% and 69.31% in OC and SC, respectively, compared to C. Myxococcota are beneficial plant bacteria [43]. At the phylum level, Ascomycota and Basidiomycota were the predominant fungal groups in all treatments, with a relative abundance of 88.48–97.44% (Figure 4b). Compared to CK, the C treatment reduced the relative abundance of Ascomycota and Basidiomycota. The OC treatment increased the relative abundance of Ascomycota, while the SC treatment increased the relative abundance of Basidiomycota compared to C. Ascomycota and Basidiomycota contribute to soil carbon accumulation and enhance soil health [44]. LEfSe analysis indicated that, compared to the other treatments, SC increased the relative abundances of Desulfobacteriota and Myxococcota, while OC primarily affected Firmicutes (Figure 5a). Both OC and SC treatments altered the overall structure of the soil bacterial community at the phylum level. However, no significant differences in fungal phylum levels were observed across all treatments (Figure 5b).

At the genus level, the top 15 bacterial and fungal taxa were analyzed to reveal the characteristics of the microbial community structure during incubation. For bacteria, the dominant genera were Pontibacter, norank_f_JG30-KF-CM45, Sphingomonas, Pseudarthrobacter, Skermanella, and norank_f_Anaerolineaceae, which accounted for 8.44–23.52% (Figure 4c). Compared to CK, the relative abundance of norank_f_Anaerolineaceae in the C treatment increased by 34.60%. Compared to the C treatment, the relative abundance of Bacillus increased by 48.59% in the SC treatment, and the relative abundance of norank_f_Anaerolineaceae increased by 5.92% and 207% in the OC and SC treatments, respectively. Compared to C, the relative abundance of Cnorank_fynorank_o_Vicinamibacteria increased by 3.78% and 42.30% in the OC and SC treatments, respectively. Bacillus, norank_fynorank_o_Vicinamidobacteriales, and norank_f_Anaerolineaceae were beneficial bacterial communities in soil [45,46,47]. The increase in their relative abundance enhanced soil health. Notably, Ammoniphilus is an oxalate-degrading bacterium that can produce soil-available nutrients [26]; it specifically appeared in the OC treatment. At the fungal genus level, Gibberella, Fusarium, Tausonia, unclassified_f_Lasiosphaeriaceae, unclassified_k_Fungi, and Penicillium were the main components of the soil (Figure 4d). Compared to CK, the C treatment increased the relative abundance of Fusarium and reduced the relative abundance of unclassified_f_Lasiosphaeriaceae. Compared to the C treatment, the relative abundance of Fusarium in the OC and SC treatments decreased by 96.33% and 96.77%, respectively. Fusarium is a plant pathogen [48], and the application of OC and SC decreased the potential for soil-borne diseases. Compared to the C treatment, the relative abundance of unclassified_f_Lasiosphaeriaceae in the OC and SC treatments increased by 84.26% and 312%, respectively. Lasiosphaeriaceae is a beneficial plant-associated fungus [49]. The relative abundance of Penicillium in the SC treatment increased by 405% compared to the C treatment. Penicillium is a phosphate-solubilizing fungus [50], which benefited the enrichment of available phosphorus in the soil. LEfSe differential analysis indicated that the addition of SC changed the relative abundance of Bacillus, Adhaeribacter, Acremonium, Coprinellus, Exserohilum, and Preussia in the soil, whereas the addition of OC affected the relative abundance of Antarcticbacterium, Diezia, Paracoccus, and Peziza in the soil (Figure 5a,b). Results at the microbial genus level indicated that the application of OC and SC improved the soil microbial community structure and increased the relative abundance of beneficial microorganisms, which contribute to the suppression of soil-borne diseases and the enhancement of soil health.

Table 2 shows differences in α-diversity among treatments. Compared to the C treatment, both OC and SC treatments exhibited higher ACE, Chao1, and Shannon indices for soil bacteria. Taking the Chao1 index as an example, the OC and SC treatments increased the soil bacterial Chao1 index by 3.02% and 10.54%, respectively, compared to the C treatment. Compared to CK, the C treatment increased the ACE and Chao1 indices, but the differences were not statistically significant. For fungi, the SC treatment significantly (p < 0.05) increased the Shannon index by 19.37% compared to the C treatment. Compared to CK, the C treatment significantly increased the ACE and Chao1 indices. These results suggest that the application of OC and SC increased soil alpha diversity compared to the C treatment, thereby enhancing microbial community diversity. The Venn diagram was used to evaluate the similarity and overlap of OTUs among different groups. For bacteria, the Venn diagram (Figure 4e) showed that all groups shared 3767 OTUs, which accounted for 40.96% of the total. The highest number of shared OTUs between any two treatments was observed between SC and OC, with 312 OTUs, accounting for 3.39% of the total. SC had the highest number of unique OTUs (947), accounting for 10.30%. For fungi, the Venn diagram (Figure 4f) showed that all groups shared 302 OTUs, which accounted for 27.16% of the total. The highest number of shared OTUs between any two treatments was observed between SC and OC, with 74 OTUs, accounting for 6.65% of the total. These results suggest that the addition of the three types of biochar altered the soil microbial composition, with a more significant impact on fungi than on bacteria. Notably, OC and SC had a more similar impact on the microbial community.

3.5. Biomass, Sodium Content, and CAT Activity of Aboveground Alfalfa

Compared to CK, the C treatment significantly (p < 0.05) increased the aboveground and underground biomass of alfalfa. Compared to the C treatment, acid-modified biochar treatments significantly (p < 0.05) increased the aboveground and underground biomass of alfalfa (Figure 6a). The highest aboveground biomass of alfalfa was observed in the OC and SC treatments, reaching 78.70 and 76.2 mg plant⁻¹, respectively, an increase of 28.45% and 24.37% compared to the C treatment. Compared to the C treatment, both OC and SC treatments showed the largest increase in underground biomass, reaching 21.77 and 21.73 mg plant⁻¹, respectively. As shown in Figure 6b, there was a significant difference in sodium content in both the aboveground and belowground parts among all groups. The OC and SC treatments significantly reduced sodium content in both the aboveground and belowground parts of alfalfa. Compared to the C treatment, sodium content in the aboveground part decreased by 19.79% and 9.89%, respectively, while sodium content in the belowground part decreased by 24.22% and 12.78%, respectively. Compared to CK, all other treatments significantly increased the CAT activity of alfalfa. Compared to the C treatment, the SC treatment resulted in the greatest increase in CAT activity in the aboveground parts of alfalfa, with a 20.34% increase. The results indicated that the addition of these three types of biochar effectively promoted alfalfa growth while reducing Na⁺ stress. The highest biomass observed in alfalfa treated with OC and SC might be attributed to the reduction in soil salinity stress (Table A2 and Table 1), changes in soil microbial diversity and structure (Table 2, Figure 5), and an increase in soil available nutrients (Figure 3d–f).

3.6. Correlation Analysis of Biochar Characteristics with Soil Nutrients, Enzyme Activity, and Microorganisms

Correlation analysis indicates that the adsorption capacity of biochar for soil ${\mathrm{Na}}^{+}$ exhibits a significant negative correlation (r < −0.98) with soil pH and effective sodium content (ENa) (Figure 7). It can be inferred from this that biochar surface functionalization enhances cation exchange capacity and isolates ${\mathrm{Na}}^{+}$ from the soil matrix. Notably, this desalination process is not isolated but intrinsically coupled with a marked enhancement in soil fertility—Q_e values showed strong positive correlations with both AN and AP (r > 0.98). This suggests that reduced ionic strength and pH may have released previously immobilized nutrients, thereby increasing their bioavailability. Mantel test results confirmed that these changes in AN and biochar’s Q_e were key drivers of bacterial and fungal community assembly. The bacterial genus Sphingomonas, which thrived in the initial saline–alkaline conditions (positively correlated with pH and ENa), was significantly suppressed as the soil environment improved. Conversely, the BET and pore volume (Vg) of biochar exhibited a strong positive correlation with the beneficial fungus Gibberella (r > 0.99), indicating that biochar provides a critical porous niche for the recruitment and enrichment of keystone functional taxa. Furthermore, the enrichment of AN creates a suppressive environment against the potential phytopathogen Fusarium (r = −0.999), illustrating a nitrogen-mediated biocontrol effect within the soil matrix.

A significant positive correlation was observed between the bacterium Skermanella and AK, implying its role in an enhanced potassium cycle. Furthermore, a remarkable cross-kingdom synergy between the fungus Penicillium and the bacterial genus norank_f_Anaerolineaceae (r = 0.989) suggests the formation of stable, cooperative consortia within the biochar-amended soil. The dissolution of the original community structure is highlighted by the intense negative correlation between salinity-tolerant bacteria (e.g., norank_f_JG30-KF-CM45) and certain fungi, while new positive associations, such as between Gibberella and Skermanella, point to the assembly of a microbiome adapted to the newly established, more fertile soil conditions. This altered environment selectively inhibits salinity-tolerant taxa and pathogens, while promoting beneficial microorganisms and fostering a robust, cooperative microbial network, collectively driving the ecosystem toward recovery. In summary, this study initially demonstrated the exceptional ${\mathrm{Na}}^{+}$ adsorption capacity of acid-modified biochar, alleviated soda–saline–alkali stress, and released key soil nutrients. However, to conclusively prove its causal mechanism, in-depth quantitative analysis is still needed in the future, such as FTIR peak deconvolution, quantification of zeta potential change and ion exchange stoichiometry, etc., for verification.

Although acid-modified biochar demonstrated excellent performance in this study, we must carefully consider the potential risks associated with the acid modification process. In alkaline soda–saline soils, the progressive acidification induced by surface functional groups represents an ideal remediation effect. However, applying such materials to neutral or acidic soils carries the risk of excessive acidification. Secondly, the decrease in soil pH may activate inherent or externally introduced heavy metals in the soil. Research indicates that pH is one of the most critical factors controlling the form and mobility of heavy metals in soil. Lower pH increases the bioavailability and toxicity of heavy metals through the following mechanisms: (1) ${\mathrm{H}}^{+}$ competes with heavy metal ions (e.g., ${\mathrm{Ca}}^{2+}$ and ${\mathrm{Pb}}^{2+}$) for adsorption sites on soil colloidal surfaces, desorbing them from immobilized states; (2) it promotes the dissolution of stable forms, such as carbonate-bound and iron–manganese oxide-bound species [51]. Although this study did not monitor heavy metal speciation, this potential risk stemming from the inherent chemical properties of the material is a critical safety parameter that must be evaluated prior to its future field application. Furthermore, future field application studies should conduct long-term, fixed-point observations of soil carbon pool dynamics and the evolution of biochar’s own physicochemical properties to ultimately confirm its long-term environmental fate and carbon sequestration efficiency.

4. Conclusions

This study investigated the ameliorative effects of acid-modified biochar on alkaline saline–alkali soils and its preliminary mechanism of action through adsorption experiments and pot experiments. The results indicate that the specific surface area and ${\mathrm{Na}}^{+}$ adsorption capacity (Q_m) of C were 5.91 m² g⁻¹ and 21.62 mg g⁻¹, respectively. After acid modification, these values increased to 35.39 m² g⁻¹ and 41.00 mg g⁻¹, respectively. Both OC and SC exhibited superior adsorption capacities compared to C, indicating that acid modification enhanced the physical adsorption capacity of biochar. Compared to the C group, the SC group showed the greatest reduction in pH and (${\mathrm{CO}}_3^{2-}$ + ${\mathrm{HCO}}_3^{-}$), decreasing by 0.27 units and 25.14%, respectively. Compared to CK, OC exhibited the greatest reductions in exchangeable sodium content and the percentage of exchangeable sodium, decreasing by 16.67% and 8.18%, respectively. The addition of all three biochar types significantly enhanced soil sucrase activity and available potassium content. Compared to CK, OC significantly increased the AP content by 9.44%. All three biochar types optimized the soil microbial community structure to varying degrees compared to the control. Additionally, OC and SC increased both aboveground and belowground biomass of Medicago falcata L. while reducing the sodium content. Thus, H₂SO₄- and H₂C₂O₄-modified biochar significantly reduced soda–salt-alkali stress, offering a novel and effective strategy for remediating soda–alkali saline–alkali soils.