The potential to sequester carbon by tree species in tropical regions such as Bangladesh is promising in regard to carbon sequestration (CS) potentiality and reducing CO2 emissions. This study focuses on perennial tree species within 488 hectares of Bangladesh Agricultural University (BAU) to assess the CS and to produce a C stock map for BAU. To compute the green and dry weight, weight of C and CO2 sequestration in the tree, a simplified methodology from the National Computational Science Institute of the Shodor Education Foundation was applied. A total of 27,543 trees comprising 424 species were taken into consideration, dividing the whole study area into four segments. B. ceiba and L. acidissima received the maximum and minimum green, dry, and C weight values. The topmost five carbon stock accumulating trees are M. longifolium (264,768 kg yr−1), S. mahagoni (257,290), A. lebbeck (118,310), M. indica (78,906), and T. grandis (51,744) whilst A. lebbeck is the major C stock accumulating tree within BAU. The top five CS potential are found for B. ceiba (181 kg), A. columnaris (139 kg), S. siamea (116 kg), F. elastica (113 kg), and F. religiosa (83 kg). To reveal the prospects of tree species in Bangladesh for emission reduction, the CS potential could be incorporated with the C trading scheme of the CDM (clean development mechanism) of the Kyoto Protocol.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.