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Estimating carbon sequestration in orchards of semi-arid tropics: A modeling approach.

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Title: Estimating carbon sequestration in orchards of semi-arid tropics: A modeling approach.
Authors: Siddesh, R1,2 (AUTHOR), Pathak, H.1,3 (AUTHOR), Chavan, S.B.1 (AUTHOR) sangramc8@gmail.com, Kakade, V.D.1 (AUTHOR), Salunkhe, S.S.4 (AUTHOR), Uthappa, A.R.5 (AUTHOR), Paul, N.1 (AUTHOR), Halli, H.M.1 (AUTHOR), Reddy, K.S.1 (AUTHOR)
Source: Biomass & Bioenergy. Mar2026, Vol. 206, pN.PAG-N.PAG. 1p.
Subjects: Carbon sequestration, Orchards, Allometric equations, Mango, Coconut, Pomegranate, Biomass estimation, Arid regions
Geographic Terms: India
Abstract: Carbon mapping through allometric equations and default factors offers a precise, non-destructive approach for quantifying biomass and carbon stocks, essential for greenhouse gas mitigation in agroecosystems. Despite the significant potential of fruit orchards to mitigate greenhouse gas emissions and enhance carbon sequestration, few studies have focused on developing allometric models specifically for these systems. Hence, this study focuses on carbon sequestration potential, along with allometry model and conversion factors, for mango, coconut, and pomegranate orchards established on degraded lands. Biomass components were destructively sampled, sorted, dried, and analyzed. Among the species, mango exhibited the highest biomass, followed by pomegranate and coconut. Default factors were developed for non-destructive biomass estimation under the IPCC Tier-II methodology. Average carbon content was 42.01 % (mango), 42.73 % (pomegranate), and 39.84 % (coconut). The total carbon stock was highest in mango orchards (28.30 Mg C ha−1), followed by pomegranate and coconut. Similarly, mango recorded the highest carbon sequestration rate (3.37 Mg C ha−1 yr−1), with comparatively lower rates in pomegranate and coconut. Collar diameter was identified as the most reliable predictor for mango and pomegranate biomass, while DBH2 × H was optimal for coconut. The Gompertz model best fitted the mango and pomegranate data, while the Chapman model was optimal for coconut, as confirmed by independent validation and standard model selection criteria. These findings highlight the role of fruit-based systems in supporting India's Nationally Determined Contribution (NDC) targets by enhancing carbon stocks (aiming to create an additional 2.5–3 billion tonnes of CO 2 equivalent sink by 2030), reducing GHG emission intensity (by 45 % of GDP by 2030), and unlocking carbon credit potential under changing climate conditions. To realize this potential, robust, species- and site-specific MRV protocols is essential, as their accuracy determines carbon payments and the achievement of realistic mitigation goals. [Display omitted] • Developed allometric models for mango, coconut, and pomegranate for precise biomass estimation. • Mango exhibits the highest carbon sequestration (3.77 MgC/ha/yr), followed by pomegranate and coconut. • Generated default factors like R/S ratios, wood density, BEF and carbon content for carbon management. • Supports Monitoring Reporting Verification protocols for non-destructive carbon assessment at regional and national scales. • Study aligns with India's GROW initiative and Green Credit Program for land degradation nutrality [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Carbon mapping through allometric equations and default factors offers a precise, non-destructive approach for quantifying biomass and carbon stocks, essential for greenhouse gas mitigation in agroecosystems. Despite the significant potential of fruit orchards to mitigate greenhouse gas emissions and enhance carbon sequestration, few studies have focused on developing allometric models specifically for these systems. Hence, this study focuses on carbon sequestration potential, along with allometry model and conversion factors, for mango, coconut, and pomegranate orchards established on degraded lands. Biomass components were destructively sampled, sorted, dried, and analyzed. Among the species, mango exhibited the highest biomass, followed by pomegranate and coconut. Default factors were developed for non-destructive biomass estimation under the IPCC Tier-II methodology. Average carbon content was 42.01 % (mango), 42.73 % (pomegranate), and 39.84 % (coconut). The total carbon stock was highest in mango orchards (28.30 Mg C ha−1), followed by pomegranate and coconut. Similarly, mango recorded the highest carbon sequestration rate (3.37 Mg C ha−1 yr−1), with comparatively lower rates in pomegranate and coconut. Collar diameter was identified as the most reliable predictor for mango and pomegranate biomass, while DBH2 × H was optimal for coconut. The Gompertz model best fitted the mango and pomegranate data, while the Chapman model was optimal for coconut, as confirmed by independent validation and standard model selection criteria. These findings highlight the role of fruit-based systems in supporting India's Nationally Determined Contribution (NDC) targets by enhancing carbon stocks (aiming to create an additional 2.5–3 billion tonnes of CO 2 equivalent sink by 2030), reducing GHG emission intensity (by 45 % of GDP by 2030), and unlocking carbon credit potential under changing climate conditions. To realize this potential, robust, species- and site-specific MRV protocols is essential, as their accuracy determines carbon payments and the achievement of realistic mitigation goals. [Display omitted] • Developed allometric models for mango, coconut, and pomegranate for precise biomass estimation. • Mango exhibits the highest carbon sequestration (3.77 MgC/ha/yr), followed by pomegranate and coconut. • Generated default factors like R/S ratios, wood density, BEF and carbon content for carbon management. • Supports Monitoring Reporting Verification protocols for non-destructive carbon assessment at regional and national scales. • Study aligns with India's GROW initiative and Green Credit Program for land degradation nutrality [ABSTRACT FROM AUTHOR]
ISSN:09619534
DOI:10.1016/j.biombioe.2025.108610