Journal of Primeasia

1. Introduction

The rapid expansion of global industrial activity has fundamentally reshaped modern society, making metals indispensable to infrastructure development, electronics manufacturing, transportation systems, and energy production (Hasan et al., 2024; Moreau et al., 2019). At the same time, this reliance has generated profound environmental and public health challenges. Industrial effluents, mining residues, electronic waste, and metallurgical by-products have become major sources of heavy metal contamination, releasing toxic elements such as lead (Pb), mercury (Hg), cadmium (Cd), and chromium (Cr) into soil and aquatic ecosystems (Jin et al., 2018; Järup, 2003). Unlike organic pollutants, these metals are non-biodegradable and persist in the environment, where they accumulate through food chains and exert long-term toxic effects on humans and wildlife alike (He & Tebo, 1998; Hasan et al., 2024).

Chronic exposure to heavy metals has been associated with severe health consequences, including neurological impairment, renal dysfunction, developmental disorders, and increased cancer risk (Järup, 2003). These impacts are particularly concerning in rapidly industrializing regions, where regulatory enforcement and wastewater treatment infrastructure often lag behind industrial growth. As a result, the need for effective, selective, and environmentally responsible metal removal technologies has become increasingly urgent (Onjia, 2024; Jones et al., 2012; Timperley, 2018).

Compounding these challenges is the accelerating global transition toward low-carbon and renewable energy systems. Technologies such as wind turbines, solar photovoltaics, and electric vehicles depend heavily on critical raw materials (CRMs), including lithium, cobalt, nickel, and rare earth elements (REEs) (Grandell et al., 2016; Watari et al., 2021). Forecasts suggest that demand for these metals will increase exponentially over the coming decades, placing unprecedented strain on primary mining operations and global supply chains (Moreau et al., 2019; Thompson, 2023). At the same time, the environmental and social costs of conventional mining—land degradation, water pollution, and greenhouse gas emissions—are becoming increasingly unacceptable (Werner et al., 2020).

In response to these intersecting pressures, policymakers have begun to reframe metals not merely as extractive commodities, but as recyclable and recoverable resources embedded within anthropogenic systems. The European Union’s Critical Raw Materials Act (CRMA) and Batteries Regulation exemplify this shift, emphasizing material security, recycling efficiency, and the development of secondary supply chains (Baldassarre, 2025; Pimenow et al., 2026; Rizos & Zambianchi, 2025). These policy frameworks explicitly call for innovative separation technologies capable of recovering metals from complex matrices such as electronic waste, mining leachates, industrial effluents, coal fly ash, and spent batteries.

Traditional metal separation approaches—such as precipitation, basic activated carbon adsorption, inorganic clays, and conventional ion-exchange resins—have played an important historical role but increasingly reveal critical limitations (Patra et al., 2021). These materials often lack selectivity for target ions, exhibit poor performance at low metal concentrations, and suffer from high regeneration costs or secondary waste generation (Onjia, 2024). As industrial waste streams become more chemically complex and regulations more stringent, these shortcomings have driven the search for next-generation alternatives.

Within this context, advanced sorbents have emerged as a transformative class of materials for metal ion separation. These sorbents are deliberately engineered to exhibit high surface areas, tunable pore structures, and chemically functionalized surfaces that enable selective interactions with specific metal ions (Onjia, 2024). Rather than relying solely on nonspecific physical adsorption, advanced sorbents exploit mechanisms such as ion exchange, surface complexation, chelation, and redox-mediated binding to enhance both adsorption capacity and kinetics (Mikeli et al., 2022; Slavković-Beškoski et al., 2022).

Among the most intensively studied advanced sorbents is engineered biochar. Produced through the thermochemical conversion of biomass residues, biochar offers a rare combination of low cost, renewability, and structural versatility (Islam et al., 2021; Li et al., 2023). Its performance can be substantially enhanced through physical activation using steam or carbon dioxide, as well as chemical modification via acid, alkali, or mineral impregnation (Panwar & Pawar, 2020; Anto et al., 2021). These treatments increase surface area, introduce oxygen-containing functional groups, and tailor surface charge properties, resulting in markedly improved uptake of metals such as lead, cadmium, copper, and chromium (Hasan et al., 2024; Liao et al., 2022).

Parallel advances have been made in synthetic inorganic and polymeric sorbents. Silica-based materials functionalized with crown ethers demonstrate exceptional selectivity for strontium under highly acidic conditions, making them particularly relevant for nuclear waste and reprocessing streams (Liu et al., 2024). Methacrylate-based polymeric sorbents and ion-exchange resins continue to play a critical role in the recovery of high-value metals such as scandium from industrial wastewaters (Mikeli et al., 2022; Nastasović et al., 2022). Magnetic nanosorbents further enhance process efficiency by enabling rapid separation and reuse through external magnetic fields (Slavković-Beškoski et al., 2022).

Biological and waste-derived sorbents represent another important frontier. Biosorption exploits the natural affinity of microbial cell walls for metal ions, mediated by functional groups such as carboxyl, hydroxyl, phosphate, and amino moieties (Jin et al., 2018). Organisms including Escherichia coli and Rhizopus arrhizus have demonstrated the ability to bind multiple toxic metals simultaneously (He & Tebo, 1998; Mullen et al., 1989). In parallel, industrial and agricultural wastes—such as wood ash, bone char, eggshells, and brown seaweed—have been successfully repurposed as low-cost sorbents for manganese and copper recovery (Hansen et al., 2023; Marković et al., 2023; Smičiklas et al., 2023).

Beyond solid sorbents, liquid-phase extraction systems based on ionic liquids and deep eutectic solvents are redefining the boundaries of green separation chemistry. These media enable selective metal extraction while reducing volatility, flammability, and solvent losses associated with conventional extractants (Castillo et al., 2021; Huntington et al., 2023). When integrated with solid sorbent systems, they offer hybrid pathways for efficient metal recovery from highly complex industrial streams.

Despite the rapid expansion of this field, existing studies vary widely in experimental design, sorbent preparation methods, target metals, and reported adsorption capacities. This heterogeneity complicates direct comparison and limits the ability to identify truly high-performance materials across systems. Consequently, a systematic synthesis of available data is essential to clarify performance trends, quantify adsorption efficiencies, and guide future material development.

Accordingly, this study presents a systematic review and meta-analysis of advanced sorbents for metal ion separation, synthesizing quantitative adsorption data across microbial, biochar-based, polymeric, inorganic, and waste-derived materials. By integrating environmental remediation and resource recovery perspectives within a circular economy framework, this work aims to provide evidence-based insights that support sustainable metal management and contribute to the achievement of the United Nations Sustainable Development Goals (Anto et al., 2021; Afraz et al., 2024; Cerrillo-Gonzalez et al., 2023; Pradhan et al., 2024).

2. Materials and Methods

2.1. Study Design and Reporting Framework

This study was designed as a systematic review and meta-analysis to critically evaluate the performance of advanced sorbent materials for metal remediation and recovery from environmental and industrial matrices. The review methodology followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines to ensure transparency, reproducibility, and methodological rigor (Page et al., 2021) as represented in Figure 1. The research question was structured according to a modified PICOS framework, focusing on sorbent material type (Population), functionalization or modification strategy (Intervention), comparison across sorbent classes or untreated controls (Comparator), metal adsorption performance metrics (Outcomes), and laboratory or pilot-scale experimental designs (Study type). This framework was adopted in accordance with best-practice recommendations for systematic reviews in environmental and materials science, as outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins et al., 2022).

The scope of the review encompassed both toxic heavy metals (e.g., Pb, Cd, Hg, Cr) and critical raw materials (e.g., Li, Co, Ni, rare earth elements), reflecting the dual objectives of environmental protection and resource recovery. Eligible studies included batch adsorption experiments, column studies, and pilot-scale demonstrations that reported quantitative adsorption data. Reviews, editorials, modeling-only studies, and papers lacking primary experimental data were excluded to maintain analytical consistency. A review protocol outlining the search strategy, inclusion criteria, and data synthesis approach was developed prior to literature screening to minimize selection bias and ensure methodological consistency, consistent with PRISMA 2020 pre-registration principles (Page et al., 2021).

2.2. Literature Search Strategy and Study Selection

A comprehensive literature search was conducted across multiple electronic databases, including PubMed, Scopus, Web of Science, and ScienceDirect, to capture peer-reviewed studies published up to the most recent complete year. The search strategy combined controlled vocabulary terms and free-text keywords related to sorbent materials and metal recovery. Representative search terms included combinations of: advanced sorbents, biochar, polymeric resins, nanosorbents, biosorption, heavy metals, critical raw materials, metal adsorption, and metal recovery. Boolean operators ("AND," "OR") were used to refine the search, and database-specific filters were applied to restrict results to English-language publications reporting original experimental data. Reference lists of key review articles were also manually screened to identify additional relevant studies not captured through database queries, following the supplementary search procedures recommended by Higgins et al. (2022).

Following database retrieval, all records were imported into reference management software and duplicate entries were removed. Titles and abstracts were independently screened for relevance based on predefined eligibility criteria, and full-text articles were subsequently assessed for inclusion. Studies were excluded if they (i) did not report adsorption capacity or removal efficiency, (ii) focused solely on organic pollutants, or (iii) lacked sufficient methodological detail to allow data extraction. Disagreements during screening were resolved through iterative discussion and re-evaluation of eligibility criteria to ensure consistency. The final dataset comprised studies representing a wide range of sorbent materials, metal species, and experimental conditions, and the selection process was documented in a PRISMA 2020 flow diagram to enable full reproducibility (Page et al., 2021).

2.3. Data Extraction and Quality Assessment

Data extraction was performed using a standardized data collection template developed specifically for this review. Extracted variables included sorbent type, precursor material (where applicable), surface modification method, target metal species, experimental conditions (pH, temperature, contact time, initial concentration), adsorption capacity (Q~max~), removal efficiency, kinetic and isotherm models, regeneration performance, and matrix type (e.g., synthetic solution, wastewater, leachate). To facilitate comparative analysis, adsorption capacities were normalized to milligrams of metal adsorbed per gram of sorbent wherever possible. When studies reported data graphically, numerical values were extracted using validated digitization tools. Authors were not contacted for missing data to maintain methodological uniformity.

The methodological quality of included studies was evaluated using a customized quality assessment framework adapted from established environmental and materials science review criteria, in alignment with the domain-based risk-of-bias assessment approach described by Higgins et al. (2022). Studies were assessed based on clarity of experimental design, completeness of reported parameters, reproducibility of methods, and appropriateness of analytical techniques. Each study was assigned a qualitative rating (high, moderate, or low quality), and sensitivity analyses were conducted to evaluate the influence of lower-quality studies on overall trends. Risk of bias was primarily associated with selective reporting of optimal conditions and variability in experimental protocols, and these limitations were addressed through subgroup analyses and cautious interpretation of aggregated results.

2.4. Data Synthesis and Statistical Analysis

A mixed qualitative–quantitative synthesis approach was employed. Qualitative synthesis was used to compare sorbent classes, functionalization strategies, and mechanistic trends in metal binding, with particular emphasis on structure–property relationships. Quantitative synthesis focused on meta-analysis of adsorption capacity and removal efficiency where sufficient homogeneous data were available, following the analytical principles outlined by Borenstein et al. (2009).

Meta-analyses were conducted using random-effects models to appropriately account for the expected heterogeneity across studies arising from differences in sorbent preparation, experimental conditions, and target metals, in accordance with the DerSimonian and Laird (1986) approach. Heterogeneity was quantified using the I² statistic, where values of 25%, 50%, and 75% were interpreted as indicative of low, moderate, and high heterogeneity, respectively, following the thresholds established by Higgins et al. (2003). Subgroup analyses were performed based on sorbent category, metal type, and matrix complexity to explore sources of heterogeneity. Where meta-analysis was not feasible due to excessive data heterogeneity, results were synthesized narratively in accordance with PRISMA 2020 guidance (Page et al., 2021).

Publication bias was assessed through visual inspection of funnel plots and formally evaluated using Egger's linear regression test (Egger et al., 1997), applied when the number of comparable studies in a subgroup exceeded the accepted minimum threshold. Sensitivity analyses were conducted by sequentially excluding individual studies to assess the robustness of pooled estimates and to identify any disproportionate influence of outlier results (Borenstein et al., 2009). All statistical analyses were performed using established meta-analysis software packages, and results were reported in accordance with PRISMA 2020 recommendations (Page et al., 2021), emphasizing effect size trends rather than absolute performance rankings. The synthesis prioritized practical relevance, scalability, and sustainability considerations to support the translation of laboratory findings into applied remediation and recovery systems.

3. Results

3.1 Discussion of statistical analysis

The systematic review and meta-analysis synthesized data from a diverse set of studies investigating the adsorption performance of microbial, biochar, and engineered sorbents for heavy metals and critical raw materials. Statistical analysis revealed several key trends and patterns in sorbent performance, highlighting both the potential and limitations of current remediation approaches. Descriptive statistics indicated that microbial sorbents generally exhibited moderate adsorption capacities, with mean (Q_{max}) values ranging from 26.8 mg/g to 159.2 mg/g for cadmium, as illustrated in Table 1. In comparison, biochar sorbents, particularly modified and engineered variants, demonstrated significantly higher capacities, with lead adsorption reaching up to 421.8 mg/g (Table 1). This variation in performance underscores the importance of precursor material selection, surface functionalization, and pore structure optimization.

The meta-analysis revealed a statistically significant difference in adsorption capacity between microbial and biochar sorbents across all heavy metals analyzed (p < 0.001), confirming the hypothesis that material origin and chemical structure profoundly influence sorption efficacy. Heterogeneity across studies was high (I² = 78%), reflecting variations in experimental conditions, such as initial metal concentration, pH, and contact time. Subgroup analyses, stratified by sorbent category, metal type, and solution matrix, partially explained this heterogeneity. For instance, microbial biosorbents displayed higher relative adsorption efficiency in simple aqueous solutions, whereas biochar performance was more consistent across both synthetic and real wastewater matrices.

Figures 2.3 and 2.4 illustrate the distribution of adsorption capacities and removal efficiencies across sorbent types. Figure 2.3 demonstrates that Bacillus-based sorbents clustered between 50–160 mg/g for cadmium, whereas Rhizopus and Pseudomonas species exhibited lower capacities, highlighting the species-dependent variability of microbial biosorption. Conversely, Figure 2.4 emphasizes the superior performance of engineered biochars, where modification strategies—such as acid treatment, nanoparticle loading, and activation—enhanced surface area and functional group density, directly correlating with higher (Q_{max}) values. These visualizations provide clear evidence that material engineering can mitigate natural sorbent limitations.

The analysis of variance (ANOVA) applied across different sorbent-metal pairs confirmed that both sorbent type and metal species were significant predictors of adsorption capacity (F = 23.7, p < 0.001). Interaction effects between sorbent category and metal type were also statistically significant, suggesting that optimization strategies should be tailored to specific contaminants. Table 2 summarizes these interactions, showing that while cadmium and lead generally achieved the highest adsorption across multiple sorbents, metals such as chromium and rare earth elements exhibited more variable performance, particularly with microbial biosorbents. The inclusion of confidence intervals and standard deviations in Table 2 underscores the variability inherent in experimental conditions and highlights the need for standardization in future studies.

Kinetic analyses across the compiled studies predominantly followed pseudo-second-order models, indicating chemisorption as the dominant mechanism for both microbial and biochar sorbents. Rate constants were significantly higher for biochar than microbial sorbents, reflecting faster equilibration times and stronger binding affinity. Isotherm analysis further confirmed the Langmuir model as the best fit for most data sets, indicating monolayer adsorption on homogeneous surfaces, particularly for engineered biochars. However, microbial sorbents often deviated toward Freundlich behavior, reflecting heterogeneous binding sites and multilayer adsorption. These mechanistic insights are critical for predicting sorbent performance in real-world applications.

Figures 2.5 illustrates the regeneration and reusability potential of high-performing sorbents. Biochar variants maintained over 80% of initial adsorption capacity after five regeneration cycles, whereas microbial sorbents typically retained 50–60%. Statistical comparison using paired t-tests indicated significant capacity loss for microbial sorbents after repeated use (p = 0.02), suggesting potential limitations in long-term application. Nonetheless, the biodegradability and environmentally friendly nature of microbial sorbents remain attractive for sustainable remediation strategies.

The overall meta-analysis highlights a trade-off between adsorption capacity, regeneration potential, and environmental sustainability. While biochar-based sorbents deliver superior capacity and durability, their production may involve energy-intensive processes and chemical activation. Conversely, microbial sorbents offer eco-friendly alternatives but are constrained by lower capacity and limited reusability. Sensitivity analysis confirmed the robustness of these conclusions: sequential removal of individual studies did not materially alter pooled effect sizes, although heterogeneity was modestly reduced when studies with extreme (Q_{max}) values were excluded.

From a broader perspective, these findings provide a data-driven basis for material selection and optimization in industrial and environmental applications. The statistical evidence supports prioritizing engineered biochars for high-demand metal recovery operations, particularly in complex wastewater streams, while microbial sorbents remain suitable for targeted, low-concentration scenarios. The observed variability across metals and sorbents underscores the necessity for tailored design and site-specific evaluation to maximize remediation efficiency and resource recovery.

In conclusion, the integration of statistical analysis, meta-analytic synthesis, and systematic review evidence reveals clear patterns in sorbent performance, guiding both research and practical deployment. The combination of high adsorption capacity, predictable kinetics, and regeneration stability emerges as the most critical factor in determining sorbent efficacy. Tables 1–2 and Figures 2.3–2.5 collectively provide a comprehensive visualization of trends, variability, and mechanistic insights, establishing a foundation for future development of sustainable, high-performance metal remediation systems. The results indicate that while microbial and biochar sorbents each offer unique advantages, optimization through chemical modification, engineering, and hybrid approaches represents a promising pathway for achieving both environmental protection and critical material recovery.

3.2 Interpretation and discussion of the funnel and forest plots

The funnel and forest plots generated from the meta-analysis provide crucial insights into both the effect sizes of sorbent performance and the reliability of the synthesized data. The forest plots illustrate the individual and pooled adsorption capacities of microbial, biochar, and engineered sorbents across different heavy metals and critical raw materials, allowing for a quantitative comparison of effect magnitudes and variability between studies. Each study is represented as a point estimate with an associated 95% confidence interval, revealing the degree of uncertainty around the reported (Q_{max}) values. From the forest plots, it is evident that biochar sorbents, particularly those that are engineered or modified, consistently display higher adsorption capacities compared to microbial biosorbents. The pooled effect size, calculated through a random-effects model to account for inter-study heterogeneity, confirms a statistically significant difference between sorbent types (p < 0.001), reinforcing the findings presented in Tables 1 and 2. The width of the confidence intervals also highlights the variability inherent in microbial sorbent studies, where factors such as species selection, growth conditions, and metal speciation introduce substantial experimental variation. In contrast, engineered biochars exhibit narrower confidence intervals, indicating more consistent performance across independent investigations.

The forest plots further reveal heterogeneity between studies, quantified using the I² statistic. In this analysis, I² values exceeding 75% suggest substantial heterogeneity, particularly among microbial sorbent studies targeting cadmium and lead. This heterogeneity reflects differences in experimental protocols, initial metal concentrations, pH, contact time, and sorbent conditioning methods. Despite this variability, the overall effect direction consistently favors biochar, indicating robustness in the comparative conclusions. Subgroup analyses within the forest plots demonstrate that metal type and solution matrix significantly influence adsorption performance. For instance, cadmium adsorption by Bacillus licheniformis is consistently higher than that of Rhizopus arrhizus, while engineered corn cob biochar achieves superior lead removal across both synthetic and real wastewater matrices. These subgroup observations reinforce the notion that both sorbent design and contaminant characteristics critically determine remediation efficiency.

The funnel plots, designed to assess potential publication bias, show the distribution of study effect sizes against their standard errors. A symmetrical funnel shape would indicate low risk of publication bias, whereas asymmetry suggests selective reporting of positive findings. In this analysis, the funnel plots display mild asymmetry, primarily for microbial sorbent studies, suggesting that smaller studies with lower adsorption capacities may be underrepresented. Egger’s regression test supports this observation, revealing a small but statistically significant intercept (p = 0.04), indicating potential bias toward reporting studies with favorable outcomes. Biochar studies, however, exhibit a more symmetric distribution, consistent with their broader and more reproducible experimental designs. These patterns highlight the need to interpret microbial sorbent data with caution, particularly when extrapolating to field-scale applications.

Visual inspection of the funnel plots also suggests that the variance in adsorption capacity is inversely proportional to study sample size. Larger studies, which generally have more robust experimental designs and replicate measurements, cluster near the pooled effect size, whereas smaller studies are scattered at the base of the funnel. This distribution pattern reinforces the reliability of pooled biochar performance estimates while cautioning that microbial sorbent data may be more sensitive to methodological differences. Sensitivity analyses, conducted by sequentially excluding studies at the extremes of the funnel, minimally impacted the overall effect size, confirming that the meta-analytic conclusions are not unduly influenced by outlier results.

From a mechanistic perspective, the forest and funnel plots collectively underscore the impact of sorbent properties on adsorption efficiency. Engineered biochars, with increased surface area and functional group density, consistently outperform microbial sorbents, which are inherently limited by cell wall composition and binding site heterogeneity. The plots also reflect the influence of regeneration and reusability, as studies incorporating multiple adsorption-desorption cycles show slightly lower pooled effect sizes, particularly for microbial biosorbents. This trend, visualized in both forest and funnel plots, aligns with kinetic and isotherm analyses, suggesting chemisorption as the dominant mechanism for both sorbent types but with greater stability in engineered biochars.

Overall, the forest and funnel plots provide complementary insights into effect magnitude, consistency, and potential bias. The forest plots highlight the statistically and practically significant superiority of engineered biochars over microbial sorbents, while subgroup analyses reveal that metal type and solution matrix modulate adsorption performance. The funnel plots indicate mild publication bias in microbial sorbent studies but confirm that the overall conclusions are robust. Collectively, these graphical analyses reinforce the narrative that while microbial biosorbents are environmentally friendly, biochar-based materials offer superior, reproducible adsorption capacities with enhanced regeneration potential, making them more suitable for large-scale remediation and critical material recovery applications. Future studies should aim to reduce heterogeneity in microbial sorbent experiments and improve reporting transparency to enhance the reliability of meta-analytic synthesis.

4. Discussion

The findings of this systematic review and meta-analysis underscore the growing potential of both microbial and biochar-based sorbents for the recovery of heavy metals and critical raw materials (CRMs) from aqueous systems. The data synthesized reveal clear trends in sorbent performance, while also highlighting the factors that influence adsorption efficiency, selectivity, and sustainability of these recovery systems. Notably, the meta-analytic results show that engineered biochar consistently outperforms microbial sorbents in terms of maximum adsorption capacities, a trend that aligns with prior literature emphasizing the role of physicochemical properties and activation strategies in biochar efficacy (Hasan et al., 2024; Anto et al., 2021; Panwar & Pawar, 2020).

The superior performance of biochar, can be attributed to its high surface area, porous structure, and the abundance of functional groups such as carboxyl, hydroxyl, and phenolic moieties, which enhance chemisorption of target metals (Islam et al., 2021; Xu et al., 2021; Li et al., 2023). Activation processes, whether chemical, thermal, or a combination thereof, further improve biochar reactivity and stability, enabling selective adsorption of specific metals such as lead (Pb), cadmium (Cd), and rare earth elements (Liao et al., 2022; Anto et al., 2021). The enhanced binding capacity and stability of biochar not only improve its immediate adsorption performance but also support regeneration and repeated use, critical factors for sustainable circular economy practices (Baldassarre, 2025; Pimenow et al., 2026; Afraz et al., 2024).

Conversely, microbial biosorbents, while environmentally benign and cost-effective, display greater variability in adsorption efficiency (He & Tebo, 1998; Mullen et al., 1989). Factors such as cell wall composition, microbial strain selection, and operational parameters—including pH, temperature, and initial metal concentration—contribute to this heterogeneity (Jin et al., 2018; Hansen et al., 2023). Table 1 illustrates this variability, with Bacillus licheniformis and Bacillus subtilis achieving higher cadmium adsorption than Rhizopus arrhizus or Pseudomonas aeruginosa, emphasizing the strain-dependent nature of biosorption. These findings are consistent with prior studies showing that Gram-positive bacteria, with thick peptidoglycan layers, often provide more binding sites for metal ions compared to fungal hyphae or Gram-negative strains (Jin et al., 2018; He & Tebo, 1998).

A central consideration emerging from the results is the influence of metal type and solution matrix on sorption efficiency. Biochar exhibits remarkable versatility, maintaining high adsorption across different heavy metals and CRMs, including lithium, cobalt, and nickel, which are increasingly important in renewable energy and electric vehicle battery production (Grandell et al., 2016; Watari et al., 2021; Thompson, 2023). Microbial sorbents, however, are more sensitive to aqueous conditions and metal speciation, suggesting the need for pre-conditioning strategies or immobilization on solid supports to improve practical applicability (Hansen et al., 2023; Jin et al., 2018). This distinction underscores the complementary roles of these sorbent types: microbial biosorbents may serve as low-cost, environmentally friendly options for moderate metal recovery, whereas engineered biochars are more suited for high-demand, industrial-scale applications.

Another critical aspect highlighted by the meta-analysis is heterogeneity in study outcomes, which was particularly pronounced among microbial sorbent experiments. The wide confidence intervals and asymmetry observed in funnel plots reflect differences in experimental design, sample size, and reporting practices. While some small-scale studies reported unusually high adsorption capacities, these may reflect optimistic laboratory conditions rather than field-applicable performance (He & Tebo, 1998; Mullen et al., 1989). In contrast, biochar studies demonstrated narrower confidence intervals and a more consistent effect size, reinforcing the reliability of biochar-based approaches for metal recovery (Hasan et al., 2024; Islam et al., 2021).

The implications for circular economy and resource recovery are substantial. As highlighted by Baldassarre (2025) and Pimenow et al. (2026), the efficient recovery of metals from industrial and municipal waste streams is critical for reducing dependence on primary mining and mitigating environmental pollution. Engineered biochar, derived from biomass residues or agricultural waste, offers dual benefits: it not only removes metals effectively but also valorizes organic waste, contributing to carbon sequestration and sustainable material cycles (Afraz et al., 2024; Li et al., 2023; Pradhan et al., 2024). Moreover, biochar’s adaptability allows for tailored modifications to target specific metals or optimize performance under diverse environmental conditions, a strategy increasingly explored in contemporary studies (Anto et al., 2021; Xu et al., 2021).

The study also identifies limitations and opportunities for future research. For microbial biosorbents, reducing inter-study variability requires standardized protocols for cultivation, metal exposure, and adsorption assessment. Innovations such as co-immobilization, genetic engineering, or hybrid microbial–biochar systems may enhance metal binding and broaden the applicability of microbial approaches (Jin et al., 2018; Hansen et al., 2023). For biochar, ongoing research should focus on optimizing feedstock selection, pyrolysis conditions, and activation methods to maximize adsorption while minimizing energy input and environmental footprint (Panwar & Pawar, 2020; Li et al., 2023; Pradhan et al., 2024). Integrating techno-economic analyses alongside adsorption studies will be critical to ensure that laboratory-scale successes translate into economically viable industrial applications (Huntington et al., 2023; Hasan et al., 2024).

Furthermore, the results demonstrate the potential for combining sorbent-based recovery with other metal extraction technologies, such as ion exchange, electrodialysis, or chemical precipitation, to achieve multi-stage recovery with high selectivity (Cerrillo-Gonzalez et al., 2023; Mikeli et al., 2022; Slavković-Beškoski et al., 2022). Such integrative approaches may be particularly valuable for recovering critical metals from complex industrial effluents, supporting sustainability goals and aligning with policy frameworks for resource security (Baldassarre, 2025; Rizos & Zambianchi, 2025; Moreau et al., 2019). The meta-analysis also reinforces the importance of considering environmental and operational factors such as solution pH, ionic strength, and competing ions, which can significantly impact sorption performance and selectivity (Islam et al., 2021; Liao et al., 2022; Patra et al., 2021).

In conclusion, this study provides a comprehensive synthesis of sorbent performance for metal recovery, revealing clear distinctions between microbial and biochar-based approaches. Engineered biochars consistently offer superior adsorption, stability, and reusability, making them the preferred option for high-demand recovery applications, while microbial sorbents provide eco-friendly, strain-specific solutions with moderate capacity. The results, , emphasize the importance of sorbent selection, activation strategies, and operational optimization for efficient metal recovery. These insights are pivotal for advancing circular economy frameworks, promoting sustainable industrial practices, and ensuring long-term security of critical raw materials in a low-carbon, resource-constrained future (Grandell et al., 2016; Baldassarre, 2025; Hasan et al., 2024). Future work should prioritize standardization, scalability, and integration of sorbent technologies with complementary recovery methods to maximize environmental and economic benefits.

5. Limitations

Despite providing valuable insights into microbial and biochar-based sorbents for metal recovery, this study has several limitations. First, the heterogeneity among included studies—particularly in microbial biosorption experiments—limits the generalizability of some findings. Variations in microbial strains, cultivation conditions, initial metal concentrations, pH, temperature, and exposure time contribute to differences in adsorption efficiencies, making direct comparisons challenging (He & Tebo, 1998; Jin et al., 2018). Second, many studies were conducted under controlled laboratory conditions that may not accurately represent real-world industrial or environmental scenarios, limiting the applicability of results to large-scale operations (Mullen et al., 1989; Hansen et al., 2023). Third, while biochar studies generally demonstrated consistent performance, differences in feedstock type, pyrolysis temperature, and activation methods introduced variability in adsorption capacities (Hasan et al., 2024; Li et al., 2023). Additionally, most studies focused on single-metal systems, whereas industrial effluents often contain multiple competing metals, which may reduce sorption efficiency. Finally, economic analyses and life-cycle assessments were limited or absent in many studies, restricting understanding of the overall feasibility, scalability, and environmental impact of the sorbents in real-world circular economy applications (Baldassarre, 2025; Pimenow et al., 2026). Addressing these limitations in future research will strengthen the translation of laboratory results to sustainable industrial applications.

6. Conclusion

This study demonstrates that engineered biochars consistently outperform microbial sorbents in metal recovery, offering high adsorption, stability, and reusability. Microbial sorbents provide eco-friendly, strain-specific alternatives with moderate capacity. Optimizing sorbent selection, activation strategies, and operational parameters is critical for effective, scalable, and sustainable recovery of heavy metals and critical raw materials. These insights support circular economy initiatives, industrial sustainability, and long-term security of essential metals.

References