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Record W2890359606

Sustainability impact assessment of climate change mitigation policies – A case study in Mexico

2018· article· en· W2890359606 on OpenAlexfundno aff
Andrea Cuesta

Bibliographic record

VenueAaltodoc (Aalto University) · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
FundersConsejo Nacional de Ciencia y TecnologíaAalto-YliopistoCanadian Institute for Theoretical Astrophysics
KeywordsSustainabilityClimate changeEnvironmental planningEnvironmental impact assessmentEnvironmental resource managementEnvironmental scienceNatural resource economicsPolitical scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

The design, adoption, and implementation of climate policies by governments all around the world has increased in the past decades. The growing popularity of these types of policies comes as a response to the severe and irreversible impacts climate change poses to people and ecosystems, in addition to the influences from international accords such as the Paris Agreement and the Sustainable Development Goals (SDGs). Thus, climate policies are considered to be the most appropriate approach to mitigate the effects of climate change. However, these policies bear the risk of causing inadvertent impacts on humankind if they fail to be assessed in terms of the three dimensions (environmental, social, and economic) of sustainable development.
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\nThus, the aim of this thesis is to identify as well as assess the positive and negative impacts of a climate policy on the three dimensions of sustainable development. The climate policy that serves as a case study, is focused on energy retrofits of public buildings in the State of Jalisco, Mexico.
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\nThe author followed the Sustainable Development Guidance, developed by the Initiative for Climate Action Transparency (ICAT) as a tool to identify relevant impacts as well as qualitatively and quantitatively assess the policy. Furthermore, environmental impacts were determined through an LCA, including both in-jurisdiction impacts (i.e. state-wide) as well as out-of-jurisdiction impacts (i.e. rest of the world). Alternatively, impacts within the social and economic dimensions were only assessed locally.
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\nThe results revealed that the greatest positive environmental impacts, affecting Mexico, occurred as a result of a decrease in usage of the national energy mix, both in terms of electricity generated from the photovoltaic panels and the reduction in electricity consumption from the LED lamps. However, negative environmental impacts also took place outside Mexican borders, mainly related to the raw material extraction and manufacturing of the aforementioned technologies. The implementation of the policy yielded savings of 1,071,223 kWh corresponding to MX$2,525,365. Furthermore, the policy had a positive impact on climate change awareness of civil servants and public acceptance of energy retrofits.
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\nBased on the research results, this thesis recommends integrating social, economic as well as other environmental impact categories (in addition to greenhouse gas emissions) in impact assessments of climate policies. It is also recommended to adopt a life cycle thinking approach when accounting for these impacts as well as to disaggregate the results based on different life cycle stages. Other recommendations are proposed: (i) the inclusion of end-of-life strategies in climate policies; (ii) the development of a climate change and/or a sustainable development governmental fund to avoid rebound effects as well as to support other like-minded projects; and (iii) the incorporation of new requirements in tendering processes which support an efficient use of materials as well as include environmental and social considerations as guiding principles.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.292
Teacher spread0.276 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2018
Admission routes1
Has abstractyes

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