Will China comply with its 2020 carbon intensity commitment?

At the Conference of the Parties held in Copenhagen in 2009 (COP15), the Chinese government announced its 2020 commitment to reduce the carbon intensity of the Chinese economy to 40–45% of its 2005 level. A number of analysts have criticised this target, indicating that these reductions can be achie...

ver descrição completa

Detalhes bibliográficos
Autores: Cansino Muñoz-Repiso, José Manuel, Román Collado, Rocío, Rueda Cantuche, José Manuel
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Recursos:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/150430
Acesso em linha:https://hdl.handle.net/11441/150430
https://doi.org/10.1016/j.envsci.2014.11.004
Access Level:acceso abierto
Palavra-chave:Air emission accountability
Greenhouse gases
Multi-sectorial analysis
Input–output analysis
China
id ES_fc6cfdafdab8b624653e823ea9ffaea9
oai_identifier_str oai:idus.us.es:11441/150430
network_acronym_str ES
network_name_str España
repository_id_str
spelling Will China comply with its 2020 carbon intensity commitment?Cansino Muñoz-Repiso, José ManuelRomán Collado, RocíoRueda Cantuche, José ManuelAir emission accountabilityGreenhouse gasesMulti-sectorial analysisInput–output analysisChinaAt the Conference of the Parties held in Copenhagen in 2009 (COP15), the Chinese government announced its 2020 commitment to reduce the carbon intensity of the Chinese economy to 40–45% of its 2005 level. A number of analysts have criticised this target, indicating that these reductions can be achieved without the implementation of any active climate change policy. In this paper, we test this argument using a combined input–output based econometric projection approach and the World Input–Output Database (WIOD). Our results show that the projected carbon intensity for 2020 is likely to be 50% lower than the carbon intensity of 2005, without additional active climate change policy measures performed by the Chinese government. On top of it, our study indicates that the total volume of CO2 emissions would be by 2020 seven times the volume of the year 2005.Elsevier SCI LTDAnálisis Económico y Economía Política2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/150430https://doi.org/10.1016/j.envsci.2014.11.004reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésEnvironmental Science & Policy, 47 (March 2015), 108-117.https://doi.org/10.1016/j.envsci.2014.11.004info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1504302026-06-17T12:51:07Z
dc.title.none.fl_str_mv Will China comply with its 2020 carbon intensity commitment?
title Will China comply with its 2020 carbon intensity commitment?
spellingShingle Will China comply with its 2020 carbon intensity commitment?
Cansino Muñoz-Repiso, José Manuel
Air emission accountability
Greenhouse gases
Multi-sectorial analysis
Input–output analysis
China
title_short Will China comply with its 2020 carbon intensity commitment?
title_full Will China comply with its 2020 carbon intensity commitment?
title_fullStr Will China comply with its 2020 carbon intensity commitment?
title_full_unstemmed Will China comply with its 2020 carbon intensity commitment?
title_sort Will China comply with its 2020 carbon intensity commitment?
dc.creator.none.fl_str_mv Cansino Muñoz-Repiso, José Manuel
Román Collado, Rocío
Rueda Cantuche, José Manuel
author Cansino Muñoz-Repiso, José Manuel
author_facet Cansino Muñoz-Repiso, José Manuel
Román Collado, Rocío
Rueda Cantuche, José Manuel
author_role author
author2 Román Collado, Rocío
Rueda Cantuche, José Manuel
author2_role author
author
dc.contributor.none.fl_str_mv Análisis Económico y Economía Política
dc.subject.none.fl_str_mv Air emission accountability
Greenhouse gases
Multi-sectorial analysis
Input–output analysis
China
topic Air emission accountability
Greenhouse gases
Multi-sectorial analysis
Input–output analysis
China
description At the Conference of the Parties held in Copenhagen in 2009 (COP15), the Chinese government announced its 2020 commitment to reduce the carbon intensity of the Chinese economy to 40–45% of its 2005 level. A number of analysts have criticised this target, indicating that these reductions can be achieved without the implementation of any active climate change policy. In this paper, we test this argument using a combined input–output based econometric projection approach and the World Input–Output Database (WIOD). Our results show that the projected carbon intensity for 2020 is likely to be 50% lower than the carbon intensity of 2005, without additional active climate change policy measures performed by the Chinese government. On top of it, our study indicates that the total volume of CO2 emissions would be by 2020 seven times the volume of the year 2005.
publishDate 2015
dc.date.none.fl_str_mv 2015
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/150430
https://doi.org/10.1016/j.envsci.2014.11.004
url https://hdl.handle.net/11441/150430
https://doi.org/10.1016/j.envsci.2014.11.004
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Environmental Science & Policy, 47 (March 2015), 108-117.
https://doi.org/10.1016/j.envsci.2014.11.004
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier SCI LTD
publisher.none.fl_str_mv Elsevier SCI LTD
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869425421282443264
score 15.300719