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5 results for “UNFCCC”
UNFCCC country-submitted greenhouse gas emissions data until 2024-07-05
<p>Dataset containing all greenhouse gas emissions data submitted by countries under climate change convention (including CRF data) as published by the UNFCCC secretariat at 2024-07-05.</p>
Uncertainties from the UNFCCC National Inventory Reports (submission 2017)
<p><strong>Summary:</strong></p> <p>This data repository contains the uncertainties of the national greenhouse-gas inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC). We extracted the data from the National Inventory Reports (NIR) submitted in 2017 covering the emission from 2015. We use the data in our study on "Estimating the uncertainty of the greenhouse gas extensions in Multi-Regional Input-Output analysis" submitted to the Journal of Earth System Science Data (ESSD): <a href="https://essd.copernicus.org/preprints/essd-2023-473/">https://essd.copernicus.org/preprints/essd-2023-473/</a></p> <p><strong>Background:</strong></p> <p>NIRs are only available in pdf-format which makes accessing them from computer impossible. Against this background, we extracted the uncertainty tables from the Annex of the NIR pdf documents in a semi-automated way using a set of Python and R scripts. To bring the uncertainty into a common format, manual data cleaning and adjustments were necessary due to different structuring and processing of uncertainty data by the parties. </p> <p><strong>Data: </strong></p> <p>We brought the data into the format provided in the IPCC 2006 guidelines (Volume 1, Chapter 3). The guidelines distinguish two approaches to uncertainty quantification, tier 1 based on analytical error propagation, and tier 2 based on Monte-Carlo simulations. For each, tier 1 and tier 2 uncertainties, the IPCC 2006 guidelines provide a distinct table template, a screenshot of which can be found in this repository under <a href="../api/records/10037714/draft/files/IPCC2006_table3-2/content">IPCC2006_table3-2</a> and <a href="../api/records/10037714/draft/files/IPCC2006_table3-3/content">IPCC2006_table3-3</a>.</p> <p>Accordingly we provide two different data sets: </p> <ul> <li><a href="../api/records/10037714/draft/files/tier1.csv/content">tier1.csv</a> containing the Tier 1 uncertainties structured according to Table 3.2 of the IPCC 2006 guidelines (see <a href="../api/records/10037714/draft/files/IPCC2006_table3-2/content">IPCC2006_table3-2</a>)</li> <li><a href="../api/records/10037714/draft/files/tier2.csv/content">tier2.csv </a>containing the Tier 2 uncertainties structured according to Table 3.2 of the IPCC 2006 guidelines (see <a href="../api/records/10037714/draft/files/IPCC2006_table3-3/content">IPCC2006_table3-3</a>)</li> </ul> <p>Compared to the table templates from the IPCC 2006 guidelines we added three identifying columns to each dataset: </p> <ul> <li><strong>party</strong>: Name of the party</li> <li><strong>year</strong>: Inventory year (2015 for all items)</li> <li><strong>LULUCF</strong>: if emissions from Land use, land-use change, and forestry (LULUCF) are included (<em>incl</em>) or excluded (<em>excl</em>) in the inventory. Background: parties often publish two versions of the uncertainty table: One including emissions from Land use, land-use change, and forestry (LULUCF), one excluding.</li> </ul> <p>Moreover, we split the column <strong>A </strong>into two columns <strong>category </strong>and <strong>classification </strong>and renamed the original column <strong>A </strong>into <strong>A_raw</strong>. </p> <p> </p>
Correspondence table between UNFCCC CRF and EXIOBASE industry sectors
<p>This repository contains a correspondence table (CT) that maps the UNFCCC Common Reporting Format (CRF) to the EXIOBASE v3 industry classification. The CT was compiled for our study on "Estimating the uncertainty of the greenhouse gas emission accounts<br>in Global Multi-Regional Input-Output analysis" submitted to the Journal of Earth System Science Data (ESSD): <a href="https://essd.copernicus.org/preprints/essd-2023-473/">https://essd.copernicus.org/preprints/essd-2023-473/</a></p> <p>In the UNFCCC CRF (2019 revision) emission sources are grouped in <strong>categories</strong> and <strong>classifications</strong>, in a hierarchical order. The highest ranked categories - also called sectors - are 1) Energy, 2) Industrial Processes and Product Use, 3) Agriculture, 4) Land use, land-use change, and forestry (LULUCF), 5) Waste and 6) Other. Those sectors are further broken down into sub-categories, e.g. 1.A.1.a.i. The sub-categories of the sectors Energy, Agriculture and LULUCF are further broken down by the classification. The classification distinguishes different fuel types (in case of emission from "Energy') and animal types (in case of emissions from "Agriculture"). Like the categories, the classification also follows a hierarchical structure.</p> <p>Parties report their emissions to the UNFCCC at different levels of resolution depending on national characteristics and data availability. </p> <p>Here, we provide two tables: </p> <ul> <li><a href="../api/records/10046372/draft/files/correspondence_CRFdetailed_to_EXIOBASE_root.xlsx/content">correspondence_CRFdetailed_to_EXIOBASE_root.xlsx</a>: Lists the correspondences only for the most detailed level (with regard to both category and classfication).</li> <li><a href="../api/records/10046372/draft/files/correspondence_CRFdetailed_to_EXIOBASE_coherent.xlsx/content">correspondence_CRFdetailed_to_EXIOBASE_coherent.xlsx</a>: List the correspondences for all levels (automatically compiled from the 'root' table).</li> </ul> <p><strong>Collaboration in checking, revising and refining the correspondence table is appreciated. Please contact me if you have a revised version so that I can upload it to this repository. </strong></p> <p> </p> <p> </p> <p> </p>
GHG data from inverse models and UNFCCC national inventories v0.1
<p><strong>GHG (CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O) data from inverse models and UNFCCC national inventories</strong></p> <p>This dataset contains 5 datasets, including GHG data from inverse models and UNFCCC national inventories in the top emitter countries:</p> <p>- <strong>CO2_inversion_1990-2019</strong>: annual CO<sub>2</sub> flux from from 6 inversion models in three sectors:</p> <ul> <li>'land flux (all land)' -> land flux from all land </li> <li>'land flux (managed land)' -> land flux from managed land</li> <li>'land flux (managed land + lateral adjustment)' -> land flux from managed land by adjusting the lateral flux</li> </ul> <p>- <strong>CH4_inversion_2000-2017</strong>: CH<sub>4</sub> flux from from 10 in-situ inversion (2000-2017) and 11 satellite inversion (2010-2017) models from four sectors:</p> <ul> <li>'anthropogenic (method x)' -> anthropogenic emissions from managed land. x could be 1, 2, 3.1 and 3.2, representing different methods to calculate the emissions in this sector:</li> <li>'fossil' -> emissions from the fossil sector</li> <li>'agriculture & waste' -> emissions from the agriculture and waste sector combined</li> <li>'biomass burning' -> emissions from biomass burning</li> </ul> <p>- <strong>N2O_inversion_1997-2016</strong>: anthropogenic N<sub>2</sub>O emissions from from 3 models.</p> <p>- <strong>Inventory_1990-2019</strong>: inventory data collecting from UNFCCC national inventories. The classification of sectors is corresponding with the inversion data files for each gas specie.</p> <p>- <strong>Inventory_1990-2019_IPCC</strong>: inventory data collecting from UNFCCC national inventories in IPCC category.</p> <ul> </ul>
Raw Dataset for UNFCCC SBSTA Ocean Dialogue Submission Analysis
<p>This raw dataset accompanies the manuscript titled "A New Way Forward for Ocean Climate Policy as Reflected in the UNFCCC Ocean and Climate Change Dialogue Submissions", submitted by co-authors to the journal Climate Policy. </p> <p>In order to evaluate the Ocean Dialogue submissions, we identified key themes reflected in the text and defined subtopics within each theme. Each of the 47 submissions was independently reviewed by two of the co-authors (typically one natural scientist and one with expertise in law or policy). Reviewers recorded the number of times each theme was mentioned within a submission. Totals for each submission were averaged across the two reviewers, to decrease biases from individual-level differences in annotation. The averaged counts are presented in two tables. Table OD 1 for Party submissions and Table OD2 for non Party submissions. The Non-Party acronyms are explained in Figure 1 of the manuscript text. In Table OD1, Party submissions are indicated as coming from Annex 1 Parties (i.e. More highly developed economies), Non-Annex 1 Parties, or representing Group Submissions (see UNFCCC website for further description of differentiation between Annex 1 and non-Annex 1 Parties: https://unfccc.int/parties-observers). The last table (OD Submission Length) shows the total page count for each of the 47 Ocean Dialogue submissions analyzed, ordered from shortest to longest. </p>
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