Dissimilatory nitrate reduction to ammonium (DNRA) conserves soil nitrogen (N), whereas denitrification and anaerobic ammonium oxidation (anammox) can result in soil N loss. Despite biochar’s potential to modulate N cycling pathways, its effects on dissimilatory nitrate reduction in alkaline paddy soils remain poorly characterized. Using 15N tracer pairing techniques in soil slurries, we quantified denitrification, anammox, and DNRA rates in soils to 80 cm depth that had received surface annual application of 0.05 t/ha of rice straw biochar. We then partitioned nitrate reduction pathways and identified associated microbial communities. Denitrification showed the greatest variability in rates, proportional contribution and community composition, indicating its dominant role in partitioning nitrate reduction pathways in both surface and deep layers. Random forest and structural equation modeling identified the edaphic factors of soil pH, SOC/NO3⁻ ratio, and Fe2+ concentration as key drivers. In surface layers, biochar amendment optimized these parameters, stimulating both denitrification and DNRA rates. In deep layers, however, biochar progressively elevated pH above optimal thresholds and lowered SOC/NO3⁻ ratio, further suppressing napA gene abundance and denitrification rates while increasing DNRA rates and proportions. Our findings demonstrate that long-term biochar amendment promotes DNRA and suppresses denitrification and anammox in deep alkaline paddy soil. These results provide mechanistic evidence for biochar’s role in conserving soil N through depth-dependent modulation of microbial N cycling pathways in alkaline paddy systems.
Biochar acts as a rhizosphere interface engineer, reshaping physical, chemical, and biological gradients across the root–soil–microorganism continuum. Physically, it enhances aggregation by 13.9–18.9 Highlights
Effective amelioration of acidic soils with biochar is critical for mitigating soil degradation and promoting sustainable agriculture, yet this requires robust mechanistic understanding and predictive modeling. This review synthesizes the key biogeochemical pathways by which biochar neutralizes soil acidity and enhances soil pH buffering capacity. We identify critical data gaps—notably the overlooked relative contributions of organic and inorganic alkalis—that currently limit the predictive performance of artificial intelligence (AI) models. A statistical literature analysis reveals that ensemble learning algorithms, particularly Random Forest, are predominant across various application scenarios, such as crop yield prediction, due to their robustness against overfitting and their capacity for feature importance ranking. However, no single algorithm is universally optimal. The choice of algorithm depends on several factors, including the amount of available data, the complexity of the problem, and the computational resources. Both multi-source data fusion and multi-model ensembling can enhance the predictive performance of AI models when appropriately configured. Future data fusion should prioritize integrating remote sensing with proximal sensor, multi-modal microbial, and imaging-chemical data to elucidate interactions across the biochar–soil–microbe–plant continuum. In conclusion, the predictive accuracy for biochar’s performance in acidic soil amelioration can be enhanced by: (1) integrating sensing technologies to develop new methods with high resolution and low detection limits; (2) applying AI while ensuring model interpretability and avoiding overclaims of causality; (3) constructing benchmark datasets to expand the usability of biochar data; (4) improving the representation of microbial responses to biochar in AI models; and (5) strengthening interdisciplinary collaboration among soil scientists, model developers, and sensing technology experts.
Anaerobic ammonium oxidation (anammox) process constitutes an energy-efficient nitrogen removal pathway critical for sustainable wastewater treatment. Anammox bacteria possess extracellular electron transfer capabilities relevant to their metabolism and potential interactions within microbial consortia. Enhanced electron transfer has been associated with anammox bacteria enrichment and improved nitrogen removal efficiency. Biochar addition has been reported to enhance electron transfer in anammox systems. This review summarizes the current understanding of biochar-induced electron transfer mechanisms during anammox processes. The proposed mechanisms include: (1) extracellular-polymeric-substance-mediated enrichment of redox-active compounds that facilitate biofilm-mediated electron transfer, (2) direct interspecies electron transfer through conductive biochar networks, and (3) mediated interspecies electron transfer via redox-active functional groups on biochar surfaces. Future research should integrate machine learning with mechanistic investigations to improve the prediction of biochar performance and guide the rational design of biochar materials. Such research efforts may provide a framework for optimizing electron transfer pathways and for future validation in scalable anammox systems.
Pathogenic microorganism transport through sandy soils and engineered sand filtration systems represents a significant groundwater contamination risk; biochar amendment of these media offers a sustainable retention strategy. This study investigated the sorption and transport of Escherichia coli (E. coli) CN-13 in saturated sand columns amended with biochar derived from malt spent rootlets (MSRB) pyrolyzed at 850 °C. Batch experiments were conducted to quantify inactivation and adsorption kinetics under varying ionic strengths (1 and 150 mM KCl). E. coli inactivation was best described by the Weibull model, while adsorption kinetics and isotherms followed the pseudo-first-order (PFO) and Freundlich models, respectively. Increasing ionic strength was found to hinder adsorption capacity, likely due to electrostatic shielding and increased competition for active sorption sites. Column transport experiments demonstrated that amending sand with MSRB significantly enhanced bacterial retention, with removal efficiencies increasing from 17.8
Integrated nutrient and field management is key to farmland soil health, but evaluation frameworks for improving soil quality index (SQI) through combined organic amendments under reduced nitrogen (N) input are still limited. Hence, we conducted a three-period field experiment to examine the effects of green manure (GM) and its synergy with biochar (GB) on SQI under reduced N input. Results were as follows: (1) GM and GB rapidly and persistently improved the SQI by 66.67–116.67
The removal of antibiotics from water using sustainable and cost-effective methods remains an environmental challenge. In this study, cotton-stalk biochar (CBC) was used as a substrate and waste eggshells as a calcium source to prepare a β-cyclodextrin-functionalized adsorbent (Ca@CBC/β-CD) via microwave-assisted crosslinking. The obtained material was used for tetracycline (TC) removal from water. Experimental results showed that Ca@CBC/β-CD exhibited the best adsorption performance at approximately pH = 6, and the adsorption kinetics were well described by the pseudo-second-order model. The adsorption isotherm followed the Langmuir model, with the maximum adsorption capacity increasing from 142.36 mg g−1 at 25 °C to 161.91 mg g−1 at 45 °C. The adsorbent also showed good tolerance to common coexisting ions and retained about 84–86
