Search Results (2)

Phosphorus (P) pollution is a leading cause of water eutrophication, and metal-modified biochar is an effective adsorbent with the ability to alter the migration capacity of phosphorus. This study uses bamboo as the raw material to prepare metal-modified biochar (ZFCO-BC) loaded with Fe and Ca under N₂ conditions at 900 °C, and investigates its adsorption characteristics for phosphate. Batch experimental results show the adsorption capacity of the ZFCO-BC gradually increases (from 4.0 to 69.1 mg/g) as the initial phosphate concentration increases (from 2 to 900 mg/L), mainly through multilayer adsorption. Additionally, as the pH increases from 1 to 7, the adsorption capacity of the ZFCO-BC climbs to reach its maximum value of 48.4 mg/g with an initial phosphate concentration of 150 mg/L. At this pH, phosphate primarily exists as H₂PO₄⁻ and HPO₄²⁻, which both readily react with Fe³⁺ and Ca²⁺ in the biochar. Furthermore, the addition of CO₃²⁻, HCO₃⁻, NO₃⁻, SO₄²⁻, F⁻, and Cl⁻ each affect the removal rate of phosphate by less than 10%, indicating the ZFCO-BC has a highly efficient and selective phosphate adsorption capacity. A multi-column adsorption experiment designed to achieve long-term and efficient phosphorus removal treated 275.5 pore volumes (PVs) of water over 366 h. The cyclic adsorption–desorption experiment results show that 0.5 M NaOH can effectively leach phosphate from the ZFCO-BC. Observations at the molecular level from P K-edge XANES spectra confirm the removal of low-concentration phosphate is primarily dominated by electrostatic attraction, while the main removal mechanism for high-concentration phosphate is chemical precipitation. This study demonstrates that ZFCO-BC has broad application prospects for phosphate removal from wastewater and as a potential slow-release fertilizer in agriculture. Full article

Forest degradation has been most frequently defined as an anthropogenic reduction in biomass compared with reference biomass in extant forests. However, so-defined “degraded forests” may widely vary in terms of recoverability. A prolonged loss of recoverability, commonly described as a loss of resilience, poses a true threat to global environments. In Bornean logged-over forests, dense thickets of ferns and vines have been observed to cause arrested secondary succession, and their area may indicate the extent of slow biomass recovery. Therefore, we aimed to discriminate the fern thickets and vine-laden forests from those logged-over forests without dense ferns and vines, as well as mapping their distributions, with the aid of Landsat-8 satellite imagery and machine learning modeling. During the process, we tested whether the gray-level co-occurrence matrix (GLCM) textures of Landsat data and Sentinel-1 C-band SAR data were helpful for this classification. Our study sites were Deramakot and Tangkulap Forest Reserves—commercial production forests in Sabah, Malaysian Borneo. First, we flew drones and obtained aerial images that were used as ground truth for the supervised classification. Subsequently, a machine-learning model with a gradient-boosting decision tree was iteratively tested in order to derive the best model for the classification of the vegetation. Finally, the best model was extrapolated to the entire forest reserve and used to map three classes of vegetation (fern thickets, vine-laden forests, and logged-over forests without ferns and vines) and two non-vegetation classes (bare soil and open water). The overall classification accuracy of the best model was 86.6%; however, by combining the fern and vine classes into the same category, the accuracy was improved to 91.5%. The GLCM texture variables were especially effective at separating fern/vine vegetation from the non-degraded forest, but the SAR data showed a limited effect. Our final vegetation map showed that 30.7% of the reserves were occupied by ferns or vines, which may lead to arrested succession. Considering that our study site was once certified as a well-managed forest, the area of degraded forests with a high risk of loss of resilience is expected to be much broader in other Bornean production forests. Full article