Key Takeaways & Executive Findings
- •• • The proposed framework enables stabilization assessment under data-scarce conditions, using AT4 (aerobic respiration rate) as a key biological stability metric, which is critical for aged landfills where historical data are often incomplete. • • Spatial analysis revealed that stabilization degree varies significantly with depth and horizontal location; waste age correlates with higher degradation, but leachate recirculation of membrane concentrate (high salinity) inhibits microbial activity, slowing stabilization in affected zones. • • LandGEM model predictions, combined with methane generation patterns, indicate that none of the four zones (A, B, C, D) had reached full stabilization; predicted completion times range from 1 year (Zone A) to 17 years (Zone D), providing a temporal roadmap for management. • • The study proposes a three-pronged management strategy: zoned gradient management, targeted control of lag zones, and dynamic planning, which translates scientific findings into actionable engineering practices for transitioning from passive remediation to proactive control.
Abstract
Scientific assessment and prediction of the stabilization process in aged municipal solid waste (MSW) landfills are critical for reliable risk evaluation and remediation decision-making. Existing methods often fail under data-scarce conditions and lack temporal predictive capability. This study establishes a 'spatial characterization–temporal prediction' framework to address these gaps. The methodology integrates grid-based sampling, laboratory analysis of biological stability indicators (AT4), and LandGEM model simulations to assess current stabilization states and predict completion timelines. Applied to a landfill in southwest China, results reveal significant spatial heterogeneity in waste stabilization, strongly correlated with waste age and influenced by leachate recirculation of membrane concentrate. None of the landfill zones had reached full stabilization; predicted times to completion were: Zone D (17 years), Zone C (13 years), Zone B (8 years), and Zone A (1 year). Based on these findings, a systematic management strategy is proposed, including zoned gradient management, targeted control of lag zones, and dynamic planning. This study provides a theoretical basis for site-specific management and serves as a reference for similar landfills.
1. Introduction
Municipal solid waste (MSW) landfills remain a primary disposal method due to their cost-effectiveness and operational simplicity. However, as landfills age, system degradation and pollutant migration pose increasing environmental risks. The stabilization process—where organic waste undergoes biological degradation to achieve mineralization, gas production cessation, and settlement—is a key indicator of environmental impact. Accurate assessment of stabilization degree and prediction of completion time are essential for risk management and operational planning. Yet, existing methods often rely on extensive monitoring data (e.g., settlement rates, leachate and gas data), which are typically unavailable or unreliable in aged landfills with poor historical records.
This study addresses this bottleneck by developing a 'spatial characterization–temporal prediction' framework that integrates field sampling, laboratory analysis of AT4 (aerobic respiration rate), and LandGEM modeling. This approach allows for systematic evaluation even when data are scarce, and it provides predictive capability for future stabilization timelines. Applied to a landfill in southwest China, the framework successfully identified spatial heterogeneity in stabilization and predicted completion times for different zones, enabling targeted management strategies. This methodology offers a practical solution for similar aged landfills, bridging the gap between scientific assessment and engineering decision-making.
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LIU Xin, LIANG Jianing, ZHANG Ya, LONG Tao, BAI Hao, YUE Dongbei (2026). Assessment Methodology and Application for Stabilization Process of Aged Municipal Solid Waste Landfills. Chinese Journal of Environmental Engineering. https://doi.org/10.12030/j.cjee.202510018
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Frequently Asked Questions
How does the proposed framework handle the lack of historical data in aged landfills?
The framework relies on field sampling and laboratory analysis of AT4 (aerobic respiration rate) and other waste characteristics, which do not require historical monitoring data. Spatial distribution is assessed via grid-based sampling, and temporal prediction is achieved using the LandGEM model with parameters derived from waste composition and age. This approach is robust even when historical records are incomplete.
What is the significance of AT4 as a biological stability indicator in this context?
AT4 measures the aerobic respiration rate, which correlates with the biodegradable organic matter content. Lower AT4 values indicate higher stabilization. In this study, AT4 was used to map spatial heterogeneity in stabilization, identifying zones where degradation is lagging due to factors like leachate recirculation. This allows for targeted intervention.
How does leachate recirculation of membrane concentrate affect the stabilization process?
The study found that leachate recirculation, particularly of membrane concentrate with high salinity, inhibits microbial activity and worsens the degradation environment. This significantly slows the stabilization process in affected zones, as evidenced by higher AT4 values and longer predicted completion times (e.g., Zone D at 17 years).
Can the LandGEM model predictions be considered reliable for long-term planning?
LandGEM is a widely used model for methane generation, and its parameters were calibrated using site-specific waste composition and age data. The predictions provide a reasonable estimate of stabilization timelines, but they should be updated as new data become available. The framework emphasizes dynamic planning to accommodate uncertainties.
What are the practical implications of the predicted stabilization times for landfill management?
The predicted times (1–17 years) allow managers to prioritize zones requiring immediate attention (e.g., Zone A) versus those needing long-term monitoring (e.g., Zone D). This supports zoned gradient management, where resources are allocated based on stabilization status, and helps in planning for final cover or site reuse.
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