Rivers are vital water sources for humans and homes for aquatic organisms. Conversely, they are well known as the route of plastics into the ocean. Despite being the world’s number one emitter of riverine plastics into the ocean, microplastics (MPs), or plastic particles less than 5 mm, in the Philippines’ rivers are relatively unexplored. Water samples were collected from six sampling stations along the river channel of the Cagayan de Oro River, one of the largest rivers in Northern Mindanao, Philippines. The extracted microplastics’ abundance, distribution, and characteristics were analyzed using a stereomicroscope and Fourier transform infrared spectroscopy (FTIR). The results showed a mean concentration of 300 items/m³ of MPs dominated by blue-colored (59%), fiber (63%), 0.3–0.5 mm (44%), and polyacetylene (48%) particles. The highest concentration of microplastics was recorded near the mouth of the river, and the lowest was in the middle area. The findings indicated a significant difference in MP concentration at the sampling stations. This study is the first assessment of microplastic in a river in Mindanao. The results of this study will aid in formulating mitigation strategies for reducing riverine plastic emissions.

This study presents a novel polyurethane-activated carbon composite (PACC) as an effective and sustainable adsorbent for treating lead-ion-contaminated waters. The PACC was characterized using Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDX), Fourier Transform Infrared Spectroscopy (FTIR), Brunauer, Emmett, and Teller (BET) surface area analyzer, X-ray Diffraction (XRD), and Thermogravimetric Analyzer (TGA) to evaluate its physicochemical and thermal properties. Furthermore, the PACC was employed in an experimental column adsorption setup to investigate its adsorption performance and to develop a dynamic method suitable for industrial implementation. Parameters such as bed height (50, 100, 150 mm), flow rate (4, 6, 8 mL min⁻¹), pH (2, 4, 6), and initial metal-ion concentrations (10, 50, 100 mg L⁻¹) were examined. The experimental data exhibited strong agreement with the Thomas and Yoon–Nelson models (R² ≥ 0.96), indicating efficient adsorption mechanisms. Remarkably, the used adsorbent has the potential for facile regeneration without substantial loss in capacity. The PACC demonstrated excellent adsorption performance for lead ions in aqueous solutions in a fixed-bed column system. Thus, the novel PACC material holds the potential for scalable application in industrial settings to address water pollution challenges, especially in regions with uncontrolled effluent discharge.

Mangroves are essential carbon reserves, and their role in carbon sequestration is remarkable. However, anthropogenic pressures such as aquaculture development threatened this highly susceptible ecosystem. Thus, the need to rehabilitate abandoned aquaculture ponds is a must to offset the ecological losses over the economic gains derived from these mangrove land-use changes. Thus, we chose a reforestation site of a once heavily utilized fishpond devastated by a tsunami in the late 1970s in Zamboanga del Sur, Philippines. We then established a similar study plot in a nearby natural mangrove forest as a point of reference. We determined the heterogeneity in vegetation and estimated the aboveground and soil carbon storage capacities. We also examined the distinct changes in species composition and zonation from the seaward towards the landward zones. About 30 years after the abandoned fishpond rehabilitation, we found the tree density of the Rhizopora mucronata Lamk. and Avicenia marina (Forsk.) Vierh-dominated reforestation site was higher (271 trees ha⁻¹) compared to that of the Rhizophora apiculata Blume-dominated natural stand (211 trees ha⁻¹) (p < 0.05). The total aboveground biomass at the natural mangrove forest was 202.02 Mg ha⁻¹, which was close to that of the reforestation site (195.19 Mg ha⁻¹) (p > 0.05). The total aboveground C in the natural mangrove forest was 90.52 Mg C ha⁻¹, while that of the reforestation site was 87.84 Mg C ha⁻¹ (p > 0.05). Surprisingly, the overall soil C content at the natural forest of 249.85 Mg C ha⁻¹ was not significantly different from that of the reforestation site with 299.75 Mg C ha⁻¹ (p > 0.05). There was an increasing soil C content trend as the soil got deeper from 0–100 cm (p < 0.05). The zonation patterns established across the landward to seaward zones did not affect the aboveground and soil carbon estimates (p > 0.05). Our study highlights the effectiveness of abandoned fishpond rehabilitation and calls for continuous restoration of the remaining abandoned aquaculture ponds in the country because of their ability to sequester and store carbon. Lastly, their potential to store huge amounts of carbon that will counterbalance anthropogenic CO₂ emissions is likewise highlighted.

In spite of their importance, mangroves are still threatened by a significant reduction in global forest cover due to conversion to non-forest land uses. To implement robust policies and actions in mangrove conservation, quantitative methods in monitoring mangrove attributes are vital. This study intends to study the trend in mangrove resource mapping using remote sensing (RS) to determine the appropriate methods and datasets to be used in monitoring the distribution, aboveground biomass (AGB), and carbon stock (CS) in mangroves. A meta-analysis of several research publications related to mangrove resource mapping using RS in the Philippines has been conducted. A database was constructed containing 59 peer-reviewed articles selected using the protocol search, appraisal, synthesis, analysis, report (PSALSAR) framework and preferred reporting items for systematic reviews and meta-analysis (PRISMA). The study clarified that support vector machine (SVM) has shown to be more effective (99%) in discriminating mangroves from other land cover. Light detection and ranging (LiDAR) data also has proven to give a promising result in overall accuracy in mangrove-extent mapping (99%), AGB, and CS estimates (99%), and even species-level mapping (77%). Medium to low-resolution datasets can still achieve high overall accuracy by using appropriate algorithms or predictive models such as the mangrove vegetation index (MVI). The study has also found out that there are still few reports on the usage of high-spatial-resolution datasets, most probably due to their commercial restrictions.

The 2030 global agenda for sustainable development integrates social, economic, and environmental dimensions, emphasizing peace, human rights, gender equality, and women’s empowerment. The SDG framework, consisting of 17 goals, 169 targets (SDTs), and 231 indicators (SDIs), forms a complex, interconnected network that necessitates extensive research. Despite prior studies on SDG interlinkages, the integration of Climate Change (CC), Sustainable Forest Management (SFM), and Information and Communication Technology (ICT), collectively known as CSI Nexus, remains underexplored. This study addresses this gap by identifying SDTs aligned with CC, SFM, and ICT (CSI) and analyzing their linkages within the SDG framework using a systems thinking approach. The objectives are to (1) investigate and identify SDTs connected with the CSI Nexus and (2) assess the significant relationship between and among CC, SFM, and ICT. The primary method involves a simplified meta-analysis and systems thinking approach incorporating content analysis, network visualization, affiliation matrix mapping, frequency distributions, and Spearman’s rho correlation. Results reveal 56 SDTs directly connected within CC + SFM + ICT, 16 within CC + SFM, one within SFM + ICT, and 51 within ICT + CC. The analysis indicates CC is significantly associated with SFM, while ICT has no significant association with CC and SFM, asserting minimal influence of ICT and SFM on the SDG 2030 framework. This research provides significant insights for decision-makers and stakeholders, contributing as a science-informed guide for priority-setting, policy coherence, and decision-making supporting the 2030 Sustainable Development Goals across sectors.