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32 results for “Climate policy”
Survey data on climate policy in three countries (Peru, Ghana, Philippines) within the project "Sustainable Middle Classes in Middle Income Countries: Transforming Carbon Consumption Patterns (SMMICC)"
<p>The unprecedented growth of the new middle classes in middle income developing countries implies a strong growth in both consumption and carbon emissions. The research project Sustainable Middle Classes in Middle Income Countries (SMMICC) investigates the drivers of carbon consumption choices of the new middle classes and policy options to decrease their carbon footprints, including the implementation of carbon taxes</p> <p>The research of the authors generated quantitative data on the acceptability of carbon taxes in three countries (Peru, Ghana, Philippines).</p> <p> </p> <p><strong>The data is provided in the following formats:</strong></p> <p>- 2024-07-26_malerba_10.5281/zenodo.12662722_ghana.csv<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_peru.csv<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_philippines.csv</p> <p>- 2024-07-26_malerba_10.5281/zenodo.12662722_ghana.dta<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_peru.dta<br>- 2024-07-26_malerba_10.5281/zenodo.12662722_philippines.dta</p> <p>Additionally, the codebooks on variables of questionnaire and political parties in each country are attached in a csv format.</p>
Climate Policy Database
<p><strong>Recommended Citation</strong></p> <p><strong>Citing this version</strong></p> <pre><code>NewClimate Institute, Wageningen University and Research &amp; PBL Netherlands Environmental Assessment Agency. (2024). Climate Policy Database. DOI: 10.5281/zenodo.154329464</code></pre> <p><strong>Citing all CPDB versions</strong></p> <pre><code>NewClimate Institute, Wageningen University and Research &amp; PBL Netherlands Environmental Assessment Agency. (2016). Climate Policy Database. DOI: 10.5281/zenodo.7774109</code></pre> <p><strong>Peer reviewed publication</strong></p> <p><strong>Description</strong></p> <p>The <a href="http://www.climatepolicydatabase.org">Climate Policy Database</a> (CDPB) is an open, collaborative tool to advance the data collection of the implementation status of climate policies. This project is funded by the European Union H2020 ELEVATE and ENGAGE projects and was, in its previous phase, funded under CD-Links. The database is maintained by NewClimate Institute with support from PBL Netherlands Environmental Assessment Agency and Wageningen University and Research.</p> <p>Although the CPDB exists since 2016, annual versions of the database have only been stored since 2019. </p> <p>The Climate Policy Database is updated periodically. The latest version of the database can be downloaded on the CPDB website or accessed through a <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fpypi.org%2Fproject%2Fcpdb-api%2F&data=05%7C01%7C%7C49011f9a98bd4ff09fa708db92950abd%7C585861118d7348a084329a4ebaecc491%7C1%7C0%7C638264941080639305%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=S7DUrVJOMBNLT1gOB8S7%2FcnlWqFw8z6mBD3wHI%2F9krY%3D&reserved=0">Python API</a>. Each year, we also create a static database, which is included here for version control.</p>
Data and code for: "Improving the relevance of paleontology to climate change policy"
<p>Data and code for the article: "Improving the relevance of paleontology to climate change policy". [Link here]</p>
Climate Policy Modelling Protocol
<p>This protocol includes current energy and climate policies for major economies, and details the instruments, targets and sectors for each policy. It provides a detailed list of climate policies as well as their quantification (following the Integrated Assessment Modelling Community (IAMC) conventions where possible). The final goal is to translate climate policies into energy and climate model input, and facilitate policy impact projections on greenhouse gas emissions.</p> <p>Climate policy on the national level, is defined as the result of climate policy formulation and climate policy implementation that encompasses aspirational goals not secured by legislation, national targets that are secured by legislation, and policy instruments designed to implement these targets. Only implemented policies are included in this protocol, and are defined as policies adopted by the government through legislation or executive orders, and non-binding targets backed by effective policy instruments.</p> <p>To compose the protocol, first a selection of climate policies with potentially high impact in terms of emission reductions is performed by the policy teams of PBL and NewClimate (<a href="https://www.climatepolicydatabase.org/">Climate Policy Database</a>), and translated into model input indicators. Then, with the help of (inter)national experts and partners, an evaluation round of the selected policies is performed, before finalizing the complete policy list. Policy instruments are represented in the integrated assessment models as explicit as possible, but simplification is sometimes necessary; replicating the impact on greenhouse gas emissions and the energy system transformation is considered as the most important factor. </p> <p>It should be noted that the policy environment is constantly changing, thus policy changes with a possibly high impact may occur between protocol updates that are not included in certain versions. Under ELEVATE, the protocol received major updates in terms of standardization of policy and target variable names and units - according to IAMC conventions, to facilitate use from all Integrated Assessment Models in the community.</p>
Sensitivity of the global agricultural sector to changes in climate policy - EU countries compared to the rest of the world
<p>The files contain data from the FAOSTAT database used in the article: DOI:10.2478/oszn-2023-0012</p> <p>File content:<br>Agricultural emissions data for the period 1961-2020<br>Population data for 1950-2020<br>Production value from agriculture for the period 1961-2020<br>Agricultural area for the period 1961-2020</p> <p>The layout of the tables and the description of the columns is the same as the FAOSTAT database methodology</p>
Making predictions for geoscience and climate policy workshop results
<p>This provides the data files and basic plotting and interpretation for results for predictions made in a series of workshops run in 2024, with predictions made for 2024, 2050, 2100 and 5o years after net zero. The workshop results are found in the files "EGU_Prediction-making workshop questions cleaned.csv" and "RGS_...", the code expects these to be in a folder denoted "data". More details can be found in the README.txt. Updates to this codebase can be found in <a href="https://github.com/Rlamboll/ClimatePredictionsWorkshop">https://github.com/Rlamboll/ClimatePredictionsWorkshop.</a></p> <p> </p>
Increased transparency in accounting conventions could benefit climate policy
<p>Datasets of emissions from 1750-2020 and spreadsheet of calculations supporting the manuscript: Wedderburn-Bisshop, G. 2025 <span>Increased transparency in accounting conventions could benefit climate policy</span></p> <p> </p> <h1>Abstract</h1> <p>Greenhouse gas accounting conventions were first devised in the 1990’s to assess and compare emissions. Several assumptions were made when devising these conventions that remain in practice, however recent advances offer potentially more consistent and inclusive accounting of greenhouse gases. We apply these advances, namely: gross accounting of CO<sub>2</sub> sources; linking land use emissions with sectors; using Effective Radiative Forcing (ERF) rather than Global Warming Potentials (GWPs) to compare emissions; including both heating and cooling emissions, and including loss of additional sink capacity (LASC). We compare these results with conventional accounting and find that this approach boosts perceived carbon emissions from deforestation, and finds agriculture, the most extensive land user, to be the leading emissions sector and to have caused 60% (32%-87%) of ERF change since 1750. We also find that fossil fuels are responsible for 17% of ERF, a reduced contribution due to masking from cooling co-emissions. We test the validity of this accounting and find it useful for determining sector responsibility for present-day warming and for framing policy responses, while recognising the dangers of assigning value to cooling emissions, due to health impacts and future warming.</p>
Data and code: Climate policy accelerates structural changes in energy employment
<p>The file contains code to create the figures used in main text and supplementary information of the paper <strong>Climate policy accelerates structural changes in energy employment</strong>.</p> <p>To run the RMD file and see the resulting figures, press Knit on R studio (requires the package knitr), or else see the attached HTML file, already created through such a process.</p>
U.S. cities increasingly integrate justice into climate planning and create policy tools for climate justice (Diezmartínez & Short Gianotti, 2022) - Data and code
<p>This repository contains datasets and coding corresponding to the journal article titled "U.S. cities increasingly integrate justice into climate planning and create policy tools for climate justice". We include:</p> <ul> <li>DataRegressionAnalysis.csv <ul> <li>CSV file with data used for regression analysis. This file can be used directly to run R code provided in this repository.</li> </ul> </li> <li>QualitativeCodingResults.nvp <ul> <li>NVivo project with all results for the qualitative coding of urban climate action plans.</li> <li>This file also contains all climate action plans analyzed in this research.</li> </ul> </li> <li>QualitativeCodingResults_Summary.xlsx <ul> <li>Excel file with a results summary for the qualitative coding of urban climate action plans.</li> </ul> </li> <li>RegressionAnalysis.Rmd <ul> <li>Rmd file with R code used for regression analysis. </li> </ul> </li> <li>RegressionAnalysis_KnitOutput.html <ul> <li>Knit output from R code with regression analysis results, html format.</li> </ul> </li> <li>RegressionAnalysis_KnitOutput.pdf <ul> <li>Knit output from R code with regression analysis results, PDF format.</li> </ul> </li> </ul>
Code and data used in "A Tool for Air Pollution Scenarios (TAPS v1.0) to enable global, long-term, and flexible study of climate and air quality policies"
<p>Data and code for Tool for Air Pollution Scenarios (TAPS v1.0) as submitted to Geoscientific Model Development for publication. See the enclosed README and full user manual (https://github.com/watkin-mit/TAPS/wiki) for more information. </p>
Fig.6 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy
Fig.6. CO2 emissions in Latvia by sources in 2016, CO2 kt eq (Source: Created by authors after National GHG inventories).
Fig.2 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy
Fig.2. Scheme of LFSRI Silava changes in forest resources projections process based on Nation Forest Inventory data (Source: LFSRI Silava).
Fig.1 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy
Fig.1. Policy documents affecting the Climate Change Mitigation policy of the Forest sector by 2020.
Dataset for the climate-related financial policy index (CRFPI)
<p>Data on the climate-related financial policy index (CRFPI) - comprising the global climate-related financial policies adopted globally and the bindingness of the policy - are provided for 74 countries from 2000 to 2020. The data include the index values from four statistical models used to calculate the composite index as described in D’Orazio and Thole 2022. The four alternative statistical approaches were designed to experiment with alternative weighting assumptions and illustrate how sensitive the proposed index is to changes in the steps followed to construct it. The index data shed light on countries’ engagement in climate-related financial planning and highlight policy gaps in relevant policy sectors.</p> <p> </p>
Data from: The impacts of climate change, energy policy, and traditional ecological practices on future firewood availability for Diné (Navajo) People
<p>These data are part of a data portal that accompanies the special issue 'Climate change adaptation needs a science of culture,' published in Philosophical Transactions of the Royal Society B in 2023. To access the data portal, please visit <a href="https://doi.org/10.5061/dryad.bnzs7h4h4"><strong>https://doi.org/10.5061/dryad.bnzs7h4h4</strong></a>.</p> <p>The files consist of the code of an agent-based model (ABM) in a NetLogo, detailed documentation of the ABM in a standard format, and a table of data exported from the simulation experiment reported on in the paper. By downloading the Netlogo file, one could not only rerun the experiment we report on and recreate the data table but toggle parameters or edit the model to explore other dynamics.</p>
Data from: The impacts of climate change, energy policy, and traditional ecological practices on future firewood availability for Diné (Navajo) People
Open the record for dataset details and reuse information.
American Policy Conflict in the Hothouse: Exploring the Politics of Climate Inaction and Polycentric Rebellion
<p>Supporting data to Figure 6 in the forthcoming publication "American Policy Conflict in the Hothouse: Exploring the Politics of Climate Inaction and Polycentric Rebellion" in Energy Research & Social Science (ERSS). Dataset provides insight into the components used to create Figure 6 and assess state-level policy contributions to carbon dioxide emission reductions (2002-2030).</p>
Fig.5 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy
Fig.5. Projections of harvest rate in the "business as usual" scenario (Source: LFSRI Silava).
Fig.4 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy
Fig.4. Projections of harvest rate in the Latvia's FRL scenario (Source: LFSRI Silava).
Fig.3 in Reaching The Climate Objectives Of Forest Management In Latvia Within The Scope Of European Climate Policy
Fig.3. Net GHG emissions in forest lands, including afforestation (Source: LFSRI Silava).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.