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Record W2267481813

How developing countries can benefit from policies to control climate change

2001· book-chapter· en· W2267481813 on OpenAlexaboutno aff
David Pearce

Bibliographic record

VenueUCL Discovery (University College London) · 2001
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsKyoto ProtocolGreenhouse gasDeveloping countryClimate changeGlobal warmingJoint ImplementationUnited Nations Framework Convention on Climate ChangeConventionClimate change mitigationClean Development MechanismBusinessNatural resource economicsInternational tradeEnvironmental resource managementEconomicsPolitical scienceEconomic growthEcology
DOInot available

Abstract

fetched live from OpenAlex

The Framework Convention on Climate Change (1992) and the Kyoto Protocol (1997) set the foundations for the global control of greenhouse gas emissions, and hence the control of global warming. While developing countries do not yet have emission reduction targets under the Protocol, they stand to gain by its provisions. First,global warming damage is unequally distributed and is likely to affect developing countries more than developed countries. Second, the Protocol’s provision for ‘joint implementation’ – a limited form of emissions trading – could greatly facilitate the transfer of clean and more efficient technology to the developing world.There are real prospects for mutual gain. Introduction: Developing countries and climate change The United Nations Framework Convention on Climate Change () of 1992 established that accelerated climate change, or ‘global warming,’ arising from the emission of ‘greenhouse gases’ () posed threats to human wellbeing and ecosystem integrity; that, while the nature of the threats remains very uncertain, action should be taken in advance of scientific certainty (the ‘precautionary principle’); that developed economies should take the lead in reducing emissions of , and that the ‘incremental cost’ of any actions taken by developing countries under the Convention should be met by the international community through a financing mechanism subsequently agreed to be the Global Environment Facility (GEF). The  emissions reduction targets set under the  were not legally binding, but centred on the return of industrialised countries’ emissions of CO2 in 2000 to 1990 levels. One matter of serious concern is that these voluntary targets for 2000 have not been met by many of the signatories. The Kyoto Protocol to the  was agreed to in December 1997 and is now open for ratification. In contrast to the 2000 targets, the Protocol set mandatory targets, binding international law, using the period from 2008 to 2012 as the first ‘commitment period.’ These targets are shown in Table 1. Countries with mandatory targets are the ‘Annex B’ countries—primarily, industrialised countries and the economies in transition (EITs). Under the Protocol, developing countries do 1 The relevant GHGs are: carbon dioxide (CO2), methane (CH4), nitrous oxides (N2O), chlorofluorocarbons (cfcs), hydrofluorocarbons (hfcs), perfluorocarbons (pfcs) and sulphur hexafluoride (SF6). CFCs are regulated under the Montreal Protocol on Protection of the Stratospheric Ozone Layer. 214     not have targets, although a few countries have subsequently adopted their own targets (e.g. Argentina). This reflects the agreement under the  that the primary responsibility for climate change rests with the developed economies, although it is increasingly recognised that the rate of growth of  emissions from developing countries means that they will soon be substantial ‘drivers’ of future rates of global warming. Since developing countries currently do not assume responsibility for climate change, and since their policy priorities lie in securing sustained economic and social development, policies towards climate change control would seem to hold out little benefit for them. However, this is not the case, and it is important to understand that developing countries can gain significant development advantages by participating in various mechanisms established under the  and the Kyoto Protocol. How can developing countries benefit from climate change control? There are essentially four ways in which developing countries can benefit from climate change control: 1. Some developing countries are especially threatened by climate change: notably, those that are vulnerable to sea level rise and those that are at risk from major weather events, such as hurricanes, which are expected to increase in frequency and severity. Thus, if rates of warming are reduced, these countries can expect to benefit, even if they take no direct action. 2. The  enabled ‘joint implementation’ () a process whereby a country with an emissions reduction target can reduce emissions in another country and count the emissions reduction against its own target. Under the Kyoto Protocol, several forms of joint implementation are permitted. There are guidelines for partnerships between countries with emission targets and between table 1 emissions reduction targets under the kyoto protocol and the eu burden sharing agreement country target % reduction from 1990 emissions levels of 6 ghgs between 2008 and 2012 + 8 – 6 + 10 – 6 – 8 – 8 0 1 – 8 – 7 –8 Australia Canada Iceland Japan Liechtenstein Monaco New Zealand Norway Switzerland United States European Union country all ghgs (2010) eu burden sharing Austria Belgium Denmark Finland France Germany Greece Ireland Italy Luxembourg Netherlands Portugal Spain Sweden U.K. – 13 – 7.5 – 21 0 0 – 21 + 25 + 13 – 6.5 – 28 – 6 + 27 + 15 + 4 – 12.5 – 20 domestic co2 target (2010) economies in transition Bulgaria Croatia Czech Republic Estonia Hungary Latvia Lithuania Poland Romania Russian Federation Slovakia Slovenia – 8 – 5 – 8 – 8 – 6 – 8 – 8 – 6 – 8 0 – 8 – 8

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.197
Teacher spread0.144 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2001
Admission routes1
Has abstractyes

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