Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach
Climate action plans, with goals for carbon neutrality of cities, often rely on estimates of urban forest biomass and related annual carbon sequestration balanced against citywide carbon emissions. For these estimates to be successful, there is a need both for accurate quantification of urban tree p...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/22292
- Acceso en línea:
- https://doi.org/10.1016/j.jclepro.2020.120420
https://repository.urosario.edu.co/handle/10336/22292
- Palabra clave:
- Budget control
Lithium compounds
Optical radar
Urban growth
Waste management
Wood
Accurate quantifications
Allometric equations
Carbon neutralities
Carbon sequestration
Field measurement
Light detection and ranging
Missing value imputation
Urban trees
Forestry
Carbon sequestration
I-tree
IPCC waste model
Lidar
Missing value imputation
Urban tree growth
Urban tree inventory
- Rights
- License
- Abierto (Texto Completo)
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81641d18-b764-4cdd-b8ca-a0c8f84b60bf-12d7c8bf2-67a1-46d2-a8e0-b82768ad86d9-13545fc8a-49ec-4ade-9304-a7c45177a29d-15d1a9b94-7954-4191-873f-95a265b72de5-12020-05-25T23:56:00Z2020-05-25T23:56:00Z2020Climate action plans, with goals for carbon neutrality of cities, often rely on estimates of urban forest biomass and related annual carbon sequestration balanced against citywide carbon emissions. For these estimates to be successful, there is a need both for accurate quantification of urban tree populations and structure, and consideration of the net carbon sequestered when the fate of wood waste is factored in. This study provides a novel approach to providing a full city tree inventory for the city of Meran in northern Italy, using a combination of Light Detection and Ranging (LiDAR) and field techniques. Allometric equations, and the i-Tree application quantified the carbon storage in Meran as 8923 and 9213 Mg respectively, with an average carbon storage of 13.5 t/ha (5.47 kg C/m2). The percentage of traffic emissions sequestered annually is 0.61% falling to 0.17% when all emissions are considered. Differences between end-of-life wood management techniques were revealed, with burning with energy recovery for electricity being the most efficient with a carbon emissions/input ratio of 0.5. Landfill was the least efficient with a ratio of 121.9. The fate of this end-of-life wood has significant implications for carbon budget calculations in cities worldwide. © 2020 Elsevier Ltdapplication/pdfhttps://doi.org/10.1016/j.jclepro.2020.1204209596526https://repository.urosario.edu.co/handle/10336/22292engElsevier LtdJournal of Cleaner ProductionVol. 256Journal of Cleaner Production, ISSN:9596526, Vol.256,(2020)https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079123875&doi=10.1016%2fj.jclepro.2020.120420&partnerID=40&md5=9ec9123cd37cff4859f41d3a0dc83085Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURBudget controlLithium compoundsOptical radarUrban growthWaste managementWoodAccurate quantificationsAllometric equationsCarbon neutralitiesCarbon sequestrationField measurementLight detection and rangingMissing value imputationUrban treesForestryCarbon sequestrationI-treeIPCC waste modelLidarMissing value imputationUrban tree growthUrban tree inventoryTotal urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approacharticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Speak, AndrewEscobedo, Francisco J.Russo, AlessioZerbe, Stefan10336/22292oai:repository.urosario.edu.co:10336/222922022-05-02 07:37:20.340542https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach |
title |
Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach |
spellingShingle |
Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach Budget control Lithium compounds Optical radar Urban growth Waste management Wood Accurate quantifications Allometric equations Carbon neutralities Carbon sequestration Field measurement Light detection and ranging Missing value imputation Urban trees Forestry Carbon sequestration I-tree IPCC waste model Lidar Missing value imputation Urban tree growth Urban tree inventory |
title_short |
Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach |
title_full |
Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach |
title_fullStr |
Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach |
title_full_unstemmed |
Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach |
title_sort |
Total urban tree carbon storage and waste management emissions estimated using a combination of LiDAR, field measurements and an end-of-life wood approach |
dc.subject.keyword.spa.fl_str_mv |
Budget control Lithium compounds Optical radar Urban growth Waste management Wood Accurate quantifications Allometric equations Carbon neutralities Carbon sequestration Field measurement Light detection and ranging Missing value imputation Urban trees Forestry Carbon sequestration I-tree IPCC waste model Lidar Missing value imputation Urban tree growth Urban tree inventory |
topic |
Budget control Lithium compounds Optical radar Urban growth Waste management Wood Accurate quantifications Allometric equations Carbon neutralities Carbon sequestration Field measurement Light detection and ranging Missing value imputation Urban trees Forestry Carbon sequestration I-tree IPCC waste model Lidar Missing value imputation Urban tree growth Urban tree inventory |
description |
Climate action plans, with goals for carbon neutrality of cities, often rely on estimates of urban forest biomass and related annual carbon sequestration balanced against citywide carbon emissions. For these estimates to be successful, there is a need both for accurate quantification of urban tree populations and structure, and consideration of the net carbon sequestered when the fate of wood waste is factored in. This study provides a novel approach to providing a full city tree inventory for the city of Meran in northern Italy, using a combination of Light Detection and Ranging (LiDAR) and field techniques. Allometric equations, and the i-Tree application quantified the carbon storage in Meran as 8923 and 9213 Mg respectively, with an average carbon storage of 13.5 t/ha (5.47 kg C/m2). The percentage of traffic emissions sequestered annually is 0.61% falling to 0.17% when all emissions are considered. Differences between end-of-life wood management techniques were revealed, with burning with energy recovery for electricity being the most efficient with a carbon emissions/input ratio of 0.5. Landfill was the least efficient with a ratio of 121.9. The fate of this end-of-life wood has significant implications for carbon budget calculations in cities worldwide. © 2020 Elsevier Ltd |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-05-25T23:56:00Z |
dc.date.available.none.fl_str_mv |
2020-05-25T23:56:00Z |
dc.date.created.spa.fl_str_mv |
2020 |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1016/j.jclepro.2020.120420 |
dc.identifier.issn.none.fl_str_mv |
9596526 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/22292 |
url |
https://doi.org/10.1016/j.jclepro.2020.120420 https://repository.urosario.edu.co/handle/10336/22292 |
identifier_str_mv |
9596526 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationTitle.none.fl_str_mv |
Journal of Cleaner Production |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 256 |
dc.relation.ispartof.spa.fl_str_mv |
Journal of Cleaner Production, ISSN:9596526, Vol.256,(2020) |
dc.relation.uri.spa.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079123875&doi=10.1016%2fj.jclepro.2020.120420&partnerID=40&md5=9ec9123cd37cff4859f41d3a0dc83085 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.acceso.spa.fl_str_mv |
Abierto (Texto Completo) |
rights_invalid_str_mv |
Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Elsevier Ltd |
institution |
Universidad del Rosario |
dc.source.instname.spa.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1814167673969311744 |