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<p>This study quantified methane emissions from two Indonesian landfills—Griyomulyo and Sekoto—using four models: IPCC, LandGEM, Afvalzorg, and the Thailand Model. LandGEM and Thailand allowed full manual input of DOC, L₀, and k, making them suitable for Tier 2 use. In contrast, the IPCC model restricted input, limiting adaptability. Site-specific values—DOC (0.17 at Griyomulyo; 0.16 at Sekoto), L₀ (94.88 and 76.84 m<sup>3</sup> CH₄/Mg), and k (0.006 and 0.055&#xa0;yr⁻<sup>1</sup>)—were used to improve reliability. In 2025, Griyomulyo’s modeled emissions ranged from 6,414.12&#xa0;Mg/year (Thailand) to 9,952.37&#xa0;Mg/year (Afvalzorg), while field measurements showed only 47.65&#xa0;Mg/year, indicating substantial overestimation. Sekoto’s estimates ranged from 2,399.59 to 4,795.97&#xa0;Mg/year. The average surface flux at Griyomulyo was 0.73&#xa0;g/m<sup>2</sup>/h, slightly above global reference levels. IPCC and LandGEM showed the most significant deviations. A regional <i>k</i> value database was developed using Thompson’s rainfall-based equation, applying data from 164 stations across 38 provinces. Grouping analysis produced three climate zones (K1–K3) with average <i>k</i> values of 0.10, 0.06, and 0.08, aligning with IPCC defaults. This study demonstrates the value of integrating field data with adaptable models. It provides a practical foundation for establishing a nationally relevant methane inventory system in Indonesia, addressing data gaps and reporting needs.</p>

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Comparative study of methane emission quantification in Indonesian landfills

  • 期刊论文

  • 发表日期：

    2025年10月12日

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  • Nita Citrasari,
  • Ngurah Adi Mahendra Gautama,
  • Diptya Adinda Larasati,
  • Kholifatul Istiqomah,
  • Dwi Ratri Mitha Isnadina,
  • Sucipto Hariyanto,
  • Bimastyaji Surya Ramadan,
  • Indriyani Rachman,
  • Toru Matsumoto

摘要

This study quantified methane emissions from two Indonesian landfills—Griyomulyo and Sekoto—using four models: IPCC, LandGEM, Afvalzorg, and the Thailand Model. LandGEM and Thailand allowed full manual input of DOC, L₀, and k, making them suitable for Tier 2 use. In contrast, the IPCC model restricted input, limiting adaptability. Site-specific values—DOC (0.17 at Griyomulyo; 0.16 at Sekoto), L₀ (94.88 and 76.84 m3 CH₄/Mg), and k (0.006 and 0.055 yr⁻1)—were used to improve reliability. In 2025, Griyomulyo’s modeled emissions ranged from 6,414.12 Mg/year (Thailand) to 9,952.37 Mg/year (Afvalzorg), while field measurements showed only 47.65 Mg/year, indicating substantial overestimation. Sekoto’s estimates ranged from 2,399.59 to 4,795.97 Mg/year. The average surface flux at Griyomulyo was 0.73 g/m2/h, slightly above global reference levels. IPCC and LandGEM showed the most significant deviations. A regional k value database was developed using Thompson’s rainfall-based equation, applying data from 164 stations across 38 provinces. Grouping analysis produced three climate zones (K1–K3) with average k values of 0.10, 0.06, and 0.08, aligning with IPCC defaults. This study demonstrates the value of integrating field data with adaptable models. It provides a practical foundation for establishing a nationally relevant methane inventory system in Indonesia, addressing data gaps and reporting needs.