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Article

How to Minimize the Impact of Biochar on Soil Salinity in Drylands? Lessons from a Data Synthesis †

1
College of Resources and Environment, Anhui Agricultural University, Hefei 230036, China
2
Changzhou Agricultural Comprehensive Technology Extension Center, Changzhou 213002, China
3
Tea Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650051, China
4
Changzhou Agricultural Accounting Service Center, Changzhou 213132, China
5
School of Agriculture and Environment, Massey University, Private Bag 11222, Palmerston North 4442, New Zealand
*
Author to whom correspondence should be addressed.
This article is derived from Chao Kong’s thesis
These authors contributed equally to this work.
Agronomy 2025, 15(11), 2609; https://doi.org/10.3390/agronomy15112609 (registering DOI)
Submission received: 10 October 2025 / Revised: 3 November 2025 / Accepted: 5 November 2025 / Published: 13 November 2025
(This article belongs to the Section Farming Sustainability)

Abstract

Biochar application in dry regions holds promise for improving soil properties, but its impact on soil salinity remains controversial. To evaluate the short-term effect of biochar on soil salinity under dry conditions, we conducted a meta-analysis of 149 observations from 40 peer-reviewed publications conducted in Mediterranean, arid, and semi-arid climates, or under simulated dry/saline conditions. Overall, biochar addition significantly increased soil electrical conductivity (EC) by 34.63% compared to controls. However, this effect was highly dependent on pedoclimatic conditions, soil pH, biochar feedstock types, pH and EC, irrigation practices, and management factors. The most substantial increases in salinity occurred when applying biochar produced from high-ash feedstocks (e.g., seafood shell powder, peanut shell), at high application rates (>20 t ha−1), to soils with low initial organic carbon content, or in the absence of a leaching fraction. In contrast, the use of biochar made from low-ash ligneous materials at rates ≤ 20 t ha−1 did not significantly increase soil EC. Random forest analysis identified biochar EC, initial soil EC, and biochar pH as the most influential factors. We conclude that the risk of biochar-induced salinization in drylands can be effectively minimized by selecting appropriate lower-EC biochar, applying it at moderate application rates, and implementing irrigation with a leaching fraction. These findings provide critical guidelines for the sustainable implementation of biochar technology in water-scarce environments.

1. Introduction

Biochar is a carbon-rich, porous material derived from the pyrolysis of organic matter and applied to soil to amend its properties. Biochar technology is currently being promoted as a promising agricultural strategy due to its demonstrated ability to enhance soil properties while simultaneously mitigating climate change [1,2,3,4]. A recent study has demonstrated that long-term application of biochar (for at least four years) can not only enhance crop yields by 11%, but also reduce methane and nitrous oxide emissions by 14% and 21%, respectively, while increasing soil organic carbon content by 53% [4]. For soils in dry environments, the interest in using biochar resides in the fact that it may help, in some instances, to increase soil water retention and decrease soil salinity [5,6]. Indeed, as a low-density, porous particulate material, when added to soil, biochar may alter soil physical properties [7]. Whether biochar has an impact on soil water retention depends on the relative differences in these properties between the biochar and the receiving soil, as well as its particle size, application rate, and depth of application. This explains the contrasting results in the literature, with either an increase [8,9,10], no effect [11,12], or a decrease in soil water holding capacity upon biochar addition [13]. In general, the greatest increases in soil water retention caused by biochar application have been observed with biochar produced from hardwood, and when added to soils with a low water-holding capacity [8,14].
Contradictory results have also been reported on the effect of biochar on soil salinity. Some studies have all described a decrease in soil salinity after the application of biochar [15,16,17], while other studies have reported a distinct increase in salinity, especially when biochar is applied at high rates [18,19,20,21]. The influence of biochar on soil salinity depends primarily on the type of biochar, its initial content of soluble salts, application rate, soil properties (texture, pH, organic carbon, and electrical conductivity), plus irrigation water quality, and irrigation practices in terms of a leaching fraction [22,23,24]. The test most widely used to determine soil salinity is the measurement of the soil-solution electrical conductivity (EC) [25]. It is based on the principle that an increase in the concentration of dissolved salts causes an increase in the ability of the soil solution to conduct an electrical current. Previous studies have ascribed the reduction in soil EC with biochar amendments to (i) an increase in water retention within biochar pores, resulting in a dilution of soil salinity; (ii) the retention of salts within biochar through either adsorption on the biochar surfaces or physical entrapment within fine pores; and (iii) a decrease in the soil bulk density and an increase in the soil hydraulic conductivity, which facilitates the leaching of salts when a leaching fraction is applied [16,26,27,28,29]. However, other studies have observed an increase in soil EC caused by the contribution of soluble salts in the ash fraction of biochar [30,31]. Given this complexity, it is critical to holistically evaluate the net effect of biochar on soil salinity, especially in water-scarce arid regions.
This study conducted a meta-analysis using EC as the proxy to evaluate the effect of biochar on soil salinity under Mediterranean, arid, and semi-arid climatic conditions, as well as under simulated dry and saline conditions in glasshouse or incubation chamber experiments. We hypothesized that: (1) biochar would increase soil salinity in arid regions; and (2) the effects would vary with application conditions. The findings are expected to contribute to a better understanding of how biochar influences soil properties in arid environments, thereby informing practical guidelines for its standardized application.

2. Materials and Methods

2.1. Data Collection

We performed a literature search focused on peer-reviewed publications between 2010 and 2020 using the Web of Science (https://www.webofscience.com/, accessed on 27 January 2020) and Google Scholar. Publications were identified using the keywords ‘biochar’ OR ‘charcoal’ OR ‘char’ OR ‘pyrogenic carbon’ AND ‘soil salinity’ OR ‘salinity’ AND ‘Mediterranean’ OR ‘arid’ OR ‘semi-arid’ OR ‘glasshouse’ OR ‘incubation chamber’. We selected studies that reported biochar and soil properties, including EC of biochar and soil, for (i) a treatment that did not receive biochar, referred to as the ‘control’; and (ii) a treatment that only differed from the ‘control’ by the addition of biochar, where possible, and referred to as the ‘treatment’. Thus, if the control was fertilised, so was the treatment, and, where possible, in similar amounts of conventional fertiliser in both treatments. If one publication had treatments with different fertiliser rates, the more realistic scenario was chosen. In addition, the studies should have lasted a maximum of 1 year. Finally, 149 observations were obtained from an overall of 40 studies (Text S1), which met our criteria. The selected studies represented a range of geographical sites across 37 experimental locations in 14 different countries (Figure 1).
From the selected publications, data about climatic conditions, soil physical and chemical properties, experimental treatments, and analytical methods were extracted. The following categorical variables were classified into discrete groups: climate, texture, initial soil pH, initial soil organic carbon (OC), initial soil EC, type of feedstock, pyrolysis highest heating temperature (HHT), biochar pH, biochar EC, leaching fraction, biochar application rate, and the addition of fertiliser (Table 1). For data presented solely in graphical form, numerical values were extracted using GetData Graph Digitizer 2.22 [32].

2.2. Meta-Analysis

All statistical analyses and graphical representations were performed using MetaWin 2.0 software [32,40]. The effect size was calculated as the natural log-transformed response ratio (lnR):
l n R = l n   ( X E X C )
where XE and XC represent the mean value of the treatment and control, respectively. The mean effect sizes of each category and the 95% confidence intervals (95%CIs) were generated by bootstrapping (4999 iterations) using MetaWin 2.0 Statistical software [41].
A non-parametric function, based on the sample size and the number of replications, was used for weighting. We chose this function instead of the variance because many studies did not report a measure of variance for soil EC. The sample-size weight function used here was as follows:
W e i g h t   =   N E × N C N E + N C
where NE and NC represent the number of replicates of the experimental observation and the control observation within the same experimental conditions, respectively. A categorical random effects model was used to calculate the grouped effect sizes. The pooled variance of the EC was ≤0, for which the MetaWin 2.0 software automatically switched from a categorical random model to a categorical fixed model.
Graphically, the change in the EC is shown as a proportion of the control with the effect size exponentially transformed. Then, (explnR) − 1 was calculated and multiplied by 100 to obtain the percentage change [42]. The overall mean of the soil EC changes, either for each category or for the whole observation, was considered to be significantly different from the control if the 95%CIs did not overlap with zero (p < 0.05). For grouping, the relative changes in soil EC within each category were considered to be significant from one another if their 95%CIs did not overlap. A significant between-group heterogeneity (Qb) value (p < 0.05) suggests that the effect of the categorical variable was significantly different.

2.3. Statistical Analysis

The statistical analysis was conducted in R 4.2.2 software, and the “random forest” package was implemented for the aforementioned analyses. All figures in this study were created with OriginPro 2025 (OriginLab Corporation, Northampton, MA, USA).

3. Results

3.1. Effects of Biochar on the Grand Mean

Biochar application resulted in a significant grand-mean increase of 34.63% in soil EC (bootstrap 95%CIs: 22.85–48.80%, n = 149) relative to the control (Figure 2a). The variables that had the greatest influence on soil salinity were related to the biochar properties of the type of feedstock, pH, and EC, plus the initial soil properties of pH, along with the irrigation practices relating to the leaching fraction, as well as biochar application rate, and climatic conditions (Figure 2b–f).

3.2. Effects of Climatic Conditions and Irrigation Practices

Soils under simulated dry and saline environments in greenhouse and chambers showed the greatest increase in EC as affected by biochar (mean: 51.65%; bootstrap 95%CIs: 31.43–77.69%, n = 74), followed by those under arid and semi-arid climates (mean: 30.03%; bootstrap 95%CIs: 17.74–44.49%, n = 54). There was no significant increase in soil salinity responses in soils under Mediterranean climates (Figure 2b). As expected, previous studies without the leaching fraction caused a larger and significant (p < 0.05) increase in soil EC (mean: 46.06%; bootstrap 95%CIs: 30.46–65.02%, n = 110), compared to those with a leaching fraction (mean: 6.75%; bootstrap 95%CIs: −5.03–20.31%, n = 74) (Figure 2e). In fact, the application of the leaching fraction contributes to maintaining lower soil salinity levels.

3.3. Effects of Initial Soil Properties

Application of biochar to soils with loam (mean: 25.09%; bootstrap 95%CIs: 12.00–41.32%, n = 48) and sandy texture (mean: 47.55%; bootstrap 95%CIs: 29.80–71.13%, n = 83) increased soil EC, as compared with the control (Figure 2c). But it did not increase that of clay soils (mean: −1.27%; bootstrap 95%CIs: −26.73–35.20%, n = 16). No significant differences were observed between the textural classes (Figure 2c). Lower initial soil pH values (pH ≤ 6.5) were associated with a larger response in soil salinity to biochar addition (mean: 52.51%; bootstrap 95%CIs: 28.46–83.84%, n = 59) compared with the control. For soils with an initial pH > 6.5 (mean: 22.20%; bootstrap 95%CIs: 12.09–34.29%, n = 90) (Figure 2c), there was also a significant effect. The differences in salinity response between pH groups (pH ≤ 6.5 vs. pH > 6.5) were significant between each other (p < 0.05). The application of biochar to soils with low OC (≤5 g kg−1) and OC contents ranging from 5 to 10 g kg−1 resulted in significant increases in soil EC (mean: 52.61% and 34.85%; bootstrap 95%CIs: 36.06–72.40% and 18.36–55.38%, n = 51 and 68, respectively) as compared with the control (Figure 2c). The application to soils with OC values > 10 g kg−1 showed no significant increase in soil EC. Biochar application increased soil EC when added to soils with initial EC ≤ 0.4 dS m−1 (mean: 44.21%; bootstrap 95%CIs: 26.03–67.85%, n = 74) compared with the control (Figure 2c), and a similar situation occurred for soils with an EC > 0.4 dS m−1 (mean: 23.93%; bootstrap 95%CIs: 11.72–38.77%, n = 75). No significant differences between soil EC groups (EC ≤ 0.4 dS m−1 vs. >0.4 dS m−1) were detected.

3.4. Effects of Biochar Properties

The type of biochar feedstock was key in determining the effect of biochar application on soil salinity, with the biochar produced from high-ash materials such as seafood shell powder, and peanut shell (mixed material) causing the largest increase in EC (mean: 274.6%; bootstrap 95%CIs: 56.65–771.8%, n = 5), compared to the control (Figure 2d). Biochar produced from green waste, animal and human waste, cereal residues, and ligneous material also increased soil salinity when compared with the control. Biochar produced at temperatures ≤ 400 °C and 400 °C to 550 °C significantly increased soil EC (mean: 53.11% and 29.28%; bootstrap 95%CIs: 29.96–883.03% and 13.64–49.74%, n = 58 and 69, respectively) compared with the control (Figure 2d). No significant increase was detected in the other HHT classes (>550 °C). Yet, no significant differences were detected between HHT groups (HHT ≤ 400 °C vs. 400 °C–550 °C vs. >550 °C). Biochar with a pH > 9.0 tended to exacerbate the increase in soil salinity (mean: 39.22%; bootstrap 95%CIs: 25.12–56.35%, n = 92) to a greater extent than biochar with a pH ≤ 9.0 (mean: 13.39%; bootstrap 95%CIs: 2.81–27.28%, n = 51) (Figure 2d). As expected, as compared with the control, biochar with EC values > 2.0 dS m−1 caused a larger and significant (p < 0.05) increase in soil EC with a mean of 38.99% (bootstrap 95CIs: 20.83–61.82%) (Figure 2d). In contrast, biochar with EC values ≤ 2.0 dS m−1 also elevated soil salinity, though to a lesser extent, with a mean increase of 20.35% (bootstrap 95CIs: 11.19–31.35%).

3.5. Effects of Biochar Application Rates and Simultaneous Addition of Other Amendments

Biochar application rates > 20 t ha−1 always caused a significant increase in soil EC, with no significant differences found between the classes of 20–40, 40–80, and >80 t ha−1 (Figure 2f). Biochar application rates ≤ 20 t ha−1 did not affect soil salinity in this meta-analysis (mean: 7.33%; bootstrap CI: −4.30–20.86%, n = 47). The addition of either only biochar (mean: 37.26%; bootstrap 95%CIs: 24.02–53.84%, n = 97), or biochar + IF (mean: 31.44%; bootstrap 95%CIs: 9.45–64.65%, n = 48) and biochar + IF + OA (mean: 64.05%; bootstrap 95%CIs: 52.63–76.32%, n = 2) increased the soil EC (Figure 2f). Interestingly, biochar + OA did not affect soil salinity in this meta-analysis (mean: −1.03%; bootstrap 95%CIs: −14.29–14.29%, n = 2).

3.6. Relationship Between the Effects of Bochar and Environmental Factors

The linear regression analysis revealed that the promotive effect of biochar application on soil salinity decreased significantly with increasing the initial soil pH, soil organic carbon content, and initial soil salinity levels (Figure 3a–c). In contrast, this promotive effect was significantly strengthened with the higher biochar pH and EC values (Figure 3e,f). Moreover, no significant relationship was observed between the effect of biochar on soil salinity and either the HHT or the biochar application rate (Figure 3d,g).
According to the random forest analysis, the relative importance of the factors affecting soil salinity was ranked as follows: biochar EC > initial soil EC > biochar pH > soil organic carbon content > initial soil pH (p < 0.05, Figure 4).

4. Discussion

4.1. Is the Type of Recipient Soil Important?

Given that our dataset only considered the previous studies on the short-term effects of biochar (≤1 year), it may be possible that initial soil EC (as influenced by climatic conditions) was more important than the climate itself during the experiment. The combined application of biochar and leaching irrigation was shown to facilitate leaching of soluble salts out of the soil profile [43]. Thus, the fact that soils with the leaching fraction did not result in an increase in EC with biochar application, as opposed to soils without the leaching fraction, was expected (Figure 2e).
Clay soils apparently buffered any increase in salinity added with the biochar, which could be explained by their larger cation exchange capacity (CEC) compared with sandy and loamy [44]. For different initial soil EC, the promoting effect of biochar addition on soil salinity was greater in soil with an initial EC ≤ 0.4 dS m−1 than in soil with an initial EC > 0.4 dS m−1 (Figure 1 and Figure 2). The possible reason was that for soils with initial EC > 0.4 dS m−1, after biochar addition, low soluble salts, such as phosphorus or sulphates, might already be saturated and thus unable to precipitate with cations from more soluble salts [31,45].
Soils in arid environments tend to have low OC because of limited plant growth and the higher rate of evaporation compared with precipitation, which restrains leaching. And, in some instances, soil EC can be high where the parent material was originally a seabed or has arisen due to poor irrigation management [46,47]. The results obtained from our meta-analysis imply that the drier the environment, the lower the soil OC and the poorer the soil leaching (Figure 2). Consequently, the higher the impact of biochar on soil salinity (Figure 3).
It is noteworthy that biochar application significantly increased soil EC in soils with initial pH ≤ 6.5, and this promotive effect was greater than in soils with initial pH values > 6.5. This observation is key to understanding the overall results, as most soils in our database had a pH > 6.5. This prevalence is typical of poorly leached soils in dry regions where evaporation exceeds precipitation. Yet, the study included some soils with pH values ≤ 6.5, from wetter regions with average annual precipitation > 1000 mm. They had an initial low EC and then were subjected to simulated dry and saline conditions under glasshouse and incubation chambers. Values of pH influence the solubility of salts and, thus, this could explain the patterns observed. Yet, it should be noted that soils with a pH > 6.5 generally had a higher EC than soils with a pH ≤ 6.5, due to poor leaching. The fact that the addition of biochar to soils with initial OC concentrations > 10 g kg−1 did not affect soil salinity, as opposed to soils with an initial OC concentration ≤ 5 g kg−1 or between 5 and 10 g kg−1, could be explained by the fact that these soils have a higher CEC, thus they probably had a higher ability to buffer those cations that had been added [17].

4.2. Selection and Application of a Biochar to Dryland Soils

Our meta-analysis clearly demonstrated that biochar application had a relatively minor impact on soil EC when biochar itself had an initial EC ≤ 2 dS m−1, was produced from ligneous materials with low ash content, and was applied at rates ≤ 20 t ha−1. This limited effect is primarily attributable to the lower loading of soluble salts. Soluble salts in biochar are found in its ash fraction, and this is mostly influenced by the type of feedstock from which the biochar is produced [48], with the ligneous materials having the smallest ash contents among all feedstocks used for the production of biochar (Figure 2d). The ash fraction is enriched with inorganic non-crystalline amorphous compounds and poorly to well-crystallized mineral constituents [49,50,51]. These are predominantly metal carbonates, silicates, phosphates, sulphates, chlorides, and oxy-hydroxides [49,52]. Among these, chlorides and sulphate salts are those that contribute the most to salinity.
Although the main meta-analysis suggested that biochar produced at temperatures ≤ 550 °C (≤400 °C and 400–550 °C) increased soil salinity, unlike that produced at higher HHT (>550 °C) (Figure 2d), further analysis revealed that this trend was an artifact caused by confounding factors. Specifically, biochar in the ≤400 °C and 400–550 °C categories was predominantly produced from intermediate to relatively high-ash feedstocks, whereas biochar produced at >550 °C typically had very low ash content. To address this limitation, the analysis was refined to compare the effect size of biochar derived from ligneous material and cereal residue across three HHT ranges (≤400 °C, 400–550 °C, >550 °C) (Table 2). We then found that there was a significant promoting effect of biochar application on soil salinity at medium and low HHT (≤400 °C and 400–550 °C), while the average effect in the higher HHT (>550 °C) category was not significant. When considering the cereal feedstocks by grouping them at HHT of ≤400 °C, 400–550 °C, and >550 °C, we found that as the HHT increased, the effect of biochar on soil salinity shifted from promoting to an inhibitory trend. This could be explained by the fact that when cereal feedstocks were pyrolysed at high temperatures, some of the salts became more insoluble. Carbonates became metal oxides, and the CO2 of carbonates was lost, thus decreasing the effect of biochar on soil salinity [53]. Additionally, it may be that data limitations prevented an unbiased determination of the influence of production conditions on the effect of biochar application on soil salinity.

4.3. Limitations and Looking Forward

The novelty of this meta-analysis lies in its relatively systematic assessment and elucidation of the short-term effects of biochar application on soil salinity in drylands (Figure 2), and the results were consistent with our hypotheses [54]. Nevertheless, caution is warranted, as the use of biochar should be standardized to avoid potential adverse effects on agricultural sustainability, despite its promising benefits. In addition, to ensure accurate interpretation of the findings and to guide future research, several limitations must be acknowledged. First, the dataset was constrained by the relatively short duration (≤1 year) of the included studies, limiting the understanding of long-term biochar-derived salinity dynamics. Over extended periods, processes such as repeated irrigation, mineral weathering, and biochar aging may alter the solubility, mobility, and bioavailability of salt ions, potentially moderating or exacerbating salinity impacts [4]. Second, while practical, the reliance on EC as the sole salinity indicator fails to capture the full ionic composition or speciation of salts (e.g., Na+, Cl, SO42−), which differentially affect plant physiology and soil structure [55]. Future studies should integrate ion chromatography or complementary metrics such as the sodium adsorption ratio (SAR) for a more nuanced risk assessment [56]. Third, the available data on biochar types and production conditions remain limited. The influence of HHT appears confounded by feedstock type and ash content, underscoring the need for more systematic, multifactorial experiments that decouple these variables [57]. Fourth, this meta-analysis could not fully account for the role of soil microbial communities and root–biochar interactions in modulating salt dynamics (Figure 2). Emerging evidence suggests that biochar could influence microbial-mediated processes such as nutrient cycling and exopolysaccharide production, which may enhance soil aggregation and salt tolerance in plants [58].
Looking forward, the integration of biochar into sustainable dryland agriculture demands a systems approach that aligns material science with agronomic practice. First, there is a critical need to establish a standardized biochar classification framework, which should take into account not only the raw materials and pyrolysis products, but also the ash composition, acid-base buffering potential, and hydrophobicity. Such a framework would enable predictive modeling of biochar–soil interactions under varying climatic and edaphic conditions. Second, the potential of “customized biochar” should be investigated to reduce inherent salt content while enhancing salt adsorption capacity through pre- or post-treatment processes (such as washing, acid modification, or mineral enrichment) [59,60]. For instance, biochar functionalized with calcium compounds could simultaneously ameliorate sodicity and mitigate salinity risks. Third, precise irrigation strategies (such as cyclic leaching or subsurface drip irrigation) need to be implemented. These strategies can not only optimize salt leaching but also simultaneously save water resources, as water resources are scarce in arid regions. Fourth, combining biochar with organic amendments (e.g., compost, manure) showed promise in neutralizing salinity impacts in the present meta-analysis (Figure 2f), suggesting synergistic soil-remediation pathways. Future field trials should test integrated amendment systems under real-world farming scenarios, accounting for crop type, salinity tolerance, and economic viability.
As climate change intensifies aridity and salinization pressures in many regions, biochar applications must be evaluated within broader frameworks of carbon sequestration, water security, and food resilience. Interdisciplinary collaborations among biochar scientists, hydrologists, agronomists, and policymakers will be essential to translate mechanistic insights into scalable, context-specific solutions. By addressing these research gaps and advancing a holistic understanding of biochar–soil–water interactions, we can harness the potential of biochar as a tool for climate-smart agriculture without compromising soil health in some of the world’s most vulnerable ecosystems [61].

5. Conclusions

This meta-analysis demonstrated that biochar application generally increased soil salinity in drylands, with an average rise of 34.63% in EC. However, this effect was strongly modulated by biochar properties, application management, and initial soil conditions. The risk of soil salinization was highest when using biochar produced from high-ash feedstocks (e.g., seafood shell powder, peanut shell), applied at rates exceeding 20 t ha−1, or added to soils with low initial organic carbon. Crucially, the implementation of a leaching fraction during irrigation can effectively mitigate this salinity increase. Therefore, to minimize the impact of biochar on soil salinity in arid and semi-arid regions, we recommend the use of low-ash biochar derived from ligneous materials, application at moderate rates (≤20 t ha−1), and the adoption of irrigation practices that include a leaching fraction. Additionally, we also suggest that future research should focus on the long-term ecological effects of biochar application. These findings provide essential guidelines for the safe and sustainable implementation of biochar technology in dryland agriculture.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15112609/s1, Text S1: Lists of the previous studies in this meta-analysis. References [62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96] are cited in the Supplementary Materials.

Author Contributions

Conceptualization, C.K.; methodology, H.Y., B.F., and C.K.; validation, Y.D.; formal analysis, X.S. (Xinyue Song); investigation, H.Y., B.F., and C.K.; resources, C.K.; software, X.S. (Xiaojing Sun), and X.S. (Xiaoyue Song); data curation, C.K.; writing—original draft preparation, H.Y., B.F., and C.K.; writing—review and editing, X.L., G.G., D.B., and C.K.; visualization, H.Y., B.F., and C.K.; supervision, C.K.; project administration, C.K.; funding acquisition, H.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (42307389).

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed at the corresponding authors. We would like to thank the anonymous reviewers for their valuable comments on the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Experimental locations of the 40 studies included in this meta-analysis. Note: The map lines represent study areas and do not necessarily reflect official national boundaries.
Figure 1. Experimental locations of the 40 studies included in this meta-analysis. Note: The map lines represent study areas and do not necessarily reflect official national boundaries.
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Figure 2. Percentage changes in soil salinity in response to biochar additions, shown for each categorical level relative to the control. The red dotted line represents the overall mean change in soil salinity among all studies. Numbers on the right vertical axis represent the number of pairwise comparisons for each category. A significant between-group heterogeneity (Qb) value (p < 0.05) indicates a statistically significant effect of the categorical variable. EC, electrical conductivity; HHT, pyrolysis highest heating temperature; OC, organic carbon; BC, biochar; BC + IF, biochar + inorganic fertiliser; BC + OA, biochar + organic amendment; BC + IF + OA, biochar + inorganic fertiliser + organic amendment. “Unknown” indicates that no classification information was provided in the selected studies.
Figure 2. Percentage changes in soil salinity in response to biochar additions, shown for each categorical level relative to the control. The red dotted line represents the overall mean change in soil salinity among all studies. Numbers on the right vertical axis represent the number of pairwise comparisons for each category. A significant between-group heterogeneity (Qb) value (p < 0.05) indicates a statistically significant effect of the categorical variable. EC, electrical conductivity; HHT, pyrolysis highest heating temperature; OC, organic carbon; BC, biochar; BC + IF, biochar + inorganic fertiliser; BC + OA, biochar + organic amendment; BC + IF + OA, biochar + inorganic fertiliser + organic amendment. “Unknown” indicates that no classification information was provided in the selected studies.
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Figure 3. Relationships between the effect size (lnR) of biochar application on soil salinity with initial soil properties (ac), initial biochar properties (df), and management factors (g). EC, electrical conductivity; HHT, pyrolysis highest heating temperature. The shaded areas represent the 95% confidence intervals (95% CIs).
Figure 3. Relationships between the effect size (lnR) of biochar application on soil salinity with initial soil properties (ac), initial biochar properties (df), and management factors (g). EC, electrical conductivity; HHT, pyrolysis highest heating temperature. The shaded areas represent the 95% confidence intervals (95% CIs).
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Figure 4. Relative importance of initial soil properties (soil pH, soil organic carbon, and soil EC), initial biochar properties (biochar pH, biochar EC, and HHT), and biochar application rate on soil salinity. EC, electrical conductivity; HHT, pyrolysis highest heating temperature. Significant levels are: *, p < 0.05; **, p < 0.01; ***, p < 0.001. R2 indicates the fraction of variance explained.
Figure 4. Relative importance of initial soil properties (soil pH, soil organic carbon, and soil EC), initial biochar properties (biochar pH, biochar EC, and HHT), and biochar application rate on soil salinity. EC, electrical conductivity; HHT, pyrolysis highest heating temperature. Significant levels are: *, p < 0.05; **, p < 0.01; ***, p < 0.001. R2 indicates the fraction of variance explained.
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Table 1. Categorical variables and their groups and ranges in this meta-analysis.
Table 1. Categorical variables and their groups and ranges in this meta-analysis.
Categorical VariableGroups and RangesNotes
(i) Experimental Climate① Arid & Semi-arid
② Mediterranean
③ Greenhouse & Chambers
(ii) Soil texture① Loam
② Sandy
③ Clay
④ Unknown
(iii) Initial soil pH① ≤6.5
② >6.5
-
Soil pH measured in distilled water (1:1, 1:2.5, 1:5, 1:10, 1:20), CaCl2 (1:2, 1:2.5, 1:5), and KCl (1:2, 1:2.5, 1:5) was converted to soil:water = 1:2.5 [33,34,35].
-
The initial soil pH(1:2.5) ranged from 3.9 to 10.2.
(iv) Initial soil OC① ≤5 g kg−1
② 5–10 g kg−1
③ >10 g kg−1
④ Unknown
-
When total C was reported in acidic soil, the values were considered as OC.
-
Initial soil OC ranged from 0.44 to 70 g kg−1.
(v) Initial soil EC① ≤0.4 dS m−1
② >0.4 dS m−1
-
Soil EC measured in distilled water (1:1, 1:2.5, 1:5, 1:10, 1:20) was converted to soil:water = 1:5 at 25 °C [36,37].
-
The initial soil EC(1:5) ranged from 0.02 to 217 dS m−1.
(vi) Type of feedstock① Ligneous materials
② Animal and human wastes
③ Cereal residues
④ Green waste
⑤ Mixed materials
⑥ Unknown
-
Ligneous materials included coniferous and deciduous wood residues, peanut hull, coconut shell, bamboo, and cotton stalk.
-
Animal and human waste included cattle feedlot manure, cattle dung, poultry litter, farm-yard manure, and sewage sludge.
-
Cereal residues included maize cobs, rice husk, miscanthus, and straw.
-
Green waste included plant pruning and grass clippings collected from parks, gardens, and agricultural fields.
(vii) Pyrolysis highest heating temperature (HHT)① ≤400 °C
② 400–550 °C
③ >550 °C
④ Unknown
-
Biochar produced using a traditional kiln was allocated in the group of 550–700 °C (http://www.fao.org/docrep/X5328E/x5328e07.htm, accessed on 27 January 2020).
-
HHT classes have been established based on the changes in the chemical structure of biochar as HHT increases [38].
(viii) Biochar pH① ≤9.0
② >9.0
③ Unknown
(ix) Biochar EC① ≤2 dS m−1
② >2 dS m−1
③ Unknown
-
Biochar EC measured in distilled water (1:1, 1:2.5, 1:5, 1:10, 1:20) was converted to solid:water = 1:10 at 25 °C [36,37,39].
-
Biochar EC(1:10) ranged from 0.011 to 110 dS m−1
(x) Leaching fraction① Without the leaching fraction
② With the leaching fraction
(xi) Biochar application rate① ≤20 t ha−1 yr−1
② 20–40 t ha−1 yr−1
③ 40–80 t ha−1 yr−1
④ >80 t ha−1 yr−1
(xii) Treatments① BC
② BC + IF
③ BC + OA
④ BC + IF + OA
Note: soil OC, soil organic carbon; EC, electrical conductivity; BC, biochar; BC + IF, biochar + inorganic fertiliser; BC + OA, biochar + organic amendment; BC + IF + OA, biochar + inorganic fertiliser + organic amendment. “Unknown” indicates that no classification information was provided in the selected studies.
Table 2. Proportional changes (mean, and lower and upper 95%CIs) in soil salinity caused by biochar additions over the control for biochar with different feedstocks and pyrolysis highest heating temperatures (HHTs).
Table 2. Proportional changes (mean, and lower and upper 95%CIs) in soil salinity caused by biochar additions over the control for biochar with different feedstocks and pyrolysis highest heating temperatures (HHTs).
CategoryGroups of HHTnChange (%)Lower 95CIs (%)Upper 95CIs (%)
Ligneous material≤400 °C1419.234.2238.00
400–550 °C4119.635.9436.07
>550 °C136.46−3.0216.92
Cereal residue≤400 °C2738.8319.2062.94
400–550 °C2216.51−6.8547.24
>550 °C2−12.81−16.93−8.48
Note: n indicates the number of pairwise comparisons on which the statistic is based.
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Yu, H.; Feng, B.; Dong, Y.; Song, X.; Sun, X.; Song, X.; Li, X.; Guo, G.; Bai, D.; Kong, C. How to Minimize the Impact of Biochar on Soil Salinity in Drylands? Lessons from a Data Synthesis. Agronomy 2025, 15, 2609. https://doi.org/10.3390/agronomy15112609

AMA Style

Yu H, Feng B, Dong Y, Song X, Sun X, Song X, Li X, Guo G, Bai D, Kong C. How to Minimize the Impact of Biochar on Soil Salinity in Drylands? Lessons from a Data Synthesis. Agronomy. 2025; 15(11):2609. https://doi.org/10.3390/agronomy15112609

Chicago/Turabian Style

Yu, Haiyang, Biyun Feng, Yuanyuan Dong, Xinyue Song, Xiaojing Sun, Xiaoyue Song, Xiaojing Li, Guomei Guo, Dezhi Bai, and Chao Kong. 2025. "How to Minimize the Impact of Biochar on Soil Salinity in Drylands? Lessons from a Data Synthesis" Agronomy 15, no. 11: 2609. https://doi.org/10.3390/agronomy15112609

APA Style

Yu, H., Feng, B., Dong, Y., Song, X., Sun, X., Song, X., Li, X., Guo, G., Bai, D., & Kong, C. (2025). How to Minimize the Impact of Biochar on Soil Salinity in Drylands? Lessons from a Data Synthesis. Agronomy, 15(11), 2609. https://doi.org/10.3390/agronomy15112609

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