최원찬 Wonchan Choi , 최동혁 Donghyuk Choi

DOI:10.9786/kswm.2026.43.1.1

Abstract

Domestic sewage sludge management is undergoing a paradigm shift due to the saturation of sewage treatment capacity and the enforcement of resource recovery policies. This study aims to address statistical discontinuities in national data by constructing a 3-Model 2-Stage Ensemble GRU model that integrates three learning periods (Long, Mid, Short). To ensure model interpretability, SHAP (Shapley Additive Explanations) was applied to identify key influencing factors. Based on the Act on the Promotion of Production and Utilization of Biogas and national policy roadmaps, future prediction scenarios were established through 2050. SHAP analysis revealed that the determinants of sludge generation have shifted from past policy regulations to current physical infrastructure capacity. Treatment methods such as fuelization and landfilling were distinctly associated with infrastructure supply and regulatory costs, respectively. Scenario analysis showed that under the Policy_Strong scenario, which assumes an active increase in the anaerobic digestion input rate to 80% by 2050, the total sludge generated is projected to decrease significantly to 4.18 million tons, compared with 4.53 million tons in the Base scenario. Furthermore, while the Combined_Max scenario (which combines strong policy with aggressive infrastructure investment) achieved the highest fuelization rate, it also entailed a trade-off, with an increase in low-grade recycling products resulting from the quantitative expansion of infrastructure. Consequently, this study proposes a strategy of “Structural Reduction and Qualitative Upgrading,” combining source reduction with high-quality energy recovery as the optimal pathway for sustainable sludge management.

Key Words

Sewage sludge, Ensemble GRU, Time-series forecasting, Explainable AI, SHAP, Sustainable sludge management

권수민 Su-min Kwon , 천승민 Seung-min Cheon , 이채은 Chae-eun Lee , 황선진 Sun-jin Hwang

DOI:10.9786/kswm.2026.43.1.14

Abstract

CO₂ absorption, a key carbon capture and utilization (CCU) technology for achieving carbon neutrality, requires large amounts of freshwater, thereby limiting its sustainability. This study presents a fundamental investigation aimed at developing Seawater-Based Carbon Capture (SBCC) technology through a comparative analysis of CO₂ absorption characteristics in freshwater and seawater. CO₂ absorption amount and capacity were evaluated in artificial seawater using NaOH as the absorbent, with pH maintained between 10 and 13. Additionally, changes in Mg²⁺ and Ca²⁺ concentrations were analyzed to assess the precipitation of MgCO₃ and CaCO₃ during CO₂ absorption in seawater. Seawater exhibited higher CO₂ absorption amounts than freshwater at all pH levels, primarily due to enhanced CO₂ dispersion resulting from salinity, which increased the specific surface area available for absorption. At pH 12, the total CO₂ absorption amount in seawater was approximately 24% higher than that in freshwater. CO₃^2- precipitation occurred during CO₂ absorption in artificial seawater. Above pH 11, precipitates, presumed to be Na2CO₃, increased due to the common-ion effect of Na⁺ and the greater NaOH demand required to maintain the elevated pH. At pH 13, CO₃^2⁻ precipitates accounted for approximately 34% of the total absorbed CO₂, raising concerns about potential clogging in future SBCC system operations. Therefore, considering both CO₂ absorption efficiency and precipitation behavior, a pH around 12 appears optimal for SBCC operation. However, at the same pH, seawater exhibited a relatively lower absorption capacity than freshwater, likely due to increased NaOH consumption caused by CO₃^2⁻ and OH⁻ precipitation reactions with Mg²⁺ and Ca²⁺. In conclusion, while seawater offers advantages in CO₂ absorption, further research is necessary to control precipitation and enhance absorption capacity to advance SBCC technology.

Key Words

Seawater, CO₂ absorption, Common-ion effect, Clogging

임노현 Noh-hyun Lim , 김유경 Yukyeong Kim , 김한비 Hanbi Kim

DOI:10.9786/kswm.2026.43.1.24

Abstract

This study aims to address structural inconsistencies among global upcycling certification schemes and to propose an integrated model that enhances international alignment. Six certification schemes (IGSC v1, KS H 1303, KEIA, Upcycled Certified®, UPMADE®, SGS) were structurally compared using a reproducible coding framework. The analysis revealed that heterogeneous content thresholds, inconsistent environmental performance metrics, and varying chain-of-custody (CoC) requirements hinder the mutual recognition of upcycled claims. To overcome these limitations, we propose a three-stage integrated model that links tiered content criteria (Quantitative), screening-level environmental indicators (Qualitative), and traceability requirements (Verification). Unlike previous studies, this model incorporates a verification process within the certification structure to ensure data integrity. A case study using coffee grounds confirmed the model’s applicability for SMEs, classifying the product as Level B (12% upcycled content) and identifying gaps in formal CoC documentation. Thus, this study contributes to establishing a functional equivalence framework for global upcycling standards.

Key Words

Upcycled product, Certification, Verification, Chain of custody, CoC, International alignment