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Part 1: Document Description
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Citation |
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Title: |
Methods used in Quantifying Green House Gas Emissions from the Food Systems |
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Identification Number: |
doi:10.7910/DVN/MSMALN |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2024-12-20 |
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Version: |
1 |
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Bibliographic Citation: |
Ngaiwi, Mary Eyeniyeh; Vanegas-Cubillos, Martha Cristina; Sylvester, Janelle Marie; Verchot, Louis Vincent; Castro-Nuñez, Augusto Carlos, 2024, "Methods used in Quantifying Green House Gas Emissions from the Food Systems", https://doi.org/10.7910/DVN/MSMALN, Harvard Dataverse, V1, UNF:6:Fshc+bkanYNbHHhywZn3bQ== [fileUNF] |
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Citation |
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Title: |
Methods used in Quantifying Green House Gas Emissions from the Food Systems |
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Identification Number: |
doi:10.7910/DVN/MSMALN |
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Authoring Entity: |
Ngaiwi, Mary Eyeniyeh (International Center for Tropical Agriculture - CIAT) |
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Vanegas-Cubillos, Martha Cristina (Bioversity International) |
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Sylvester, Janelle Marie (International Center for Tropical Agriculture - CIAT) |
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Verchot, Louis Vincent (International Center for Tropical Agriculture - CIAT) |
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Castro-Nuñez, Augusto Carlos (International Center for Tropical Agriculture - CIAT) |
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Producer: |
Bioversity International and the International Center for Tropical Agriculture |
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Date of Production: |
2024-02-18 |
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Grant Number: |
G199-CGIAR Fund INIT-32-Mitigate+: Research for Low-Emission Food Systems |
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Distributor: |
Harvard Dataverse |
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Distributor: |
Bioversity International and the International Center for Tropical Agriculture |
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Access Authority: |
Alliance Data Management |
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Depositor: |
Alliance Data Management |
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Date of Deposit: |
2024-02-26 |
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Date of Distribution: |
2024-02-18 |
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Holdings Information: |
https://doi.org/10.7910/DVN/MSMALN |
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Study Scope |
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Keywords: |
Agricultural Sciences, Earth and Environmental Sciences, low-emission development, Climate change mitigation, FOOD SYSTEMS, investments, estimations, GHG emissions, Americas, Multifunctional Landscapes, CGIAR Research Program on Climate Change, Agriculture and Food Security |
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Topic Classification: |
climate change mitigation |
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Abstract: |
This document encompasses the a collection of studies from literature that have used different methods to estimate greenhouse gas emissions from the different stages of the food system. <br><br> Methodology: We conducted a comprehensive review of 124 methods used in estimating greenhouse gas emissions from the food system. Through extensive debates and rounds of discussions, we categorized these methods into Inventory, Life cycle analysis, process based-models, input-output models, direct measurements, and remote sensing. The life cycle analysis (LCA) category focuses solely on evaluating the environmental impacts and services throughout the life cycle of a food system, estimating GHG emissions based on energy and material inputs/outputs. Inventories encompass methods such as IPCC tiers 1, 2, and 3, as well as bottom-up emissions estimation approaches. Process-based models consist of various components, including diet models, biophysical models for land use related to crops and livestock, IGES GHG calculation method, and the LandGEM model. Direct measurements involve techniques such as static chambers, Drager-tube techniques, and eddy covariance. The input-output (IO) method estimates GHG emissions by tracing inputs and outputs across the economy, capturing interconnections between sectors and providing insights into product emissions. Remote sensing is the utilization of satellite or aerial imagery and remote sensing technologies to monitor emissions across large geographic areas.<br><br> Methodology: We conducted a comprehensive review of 124 methods used in estimating greenhouse gas emissions from the food system. Through extensive debates and rounds of discussions, we categorized these methods into Inventory, Life cycle analysis, process based-models, input-output models, direct measurements, and remote sensing. |
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Time Period: |
2018-01-01-2023-01-05 |
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Date of Collection: |
2022-05-09-2022-10-10 |
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Country: |
Colombia |
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Kind of Data: |
emissions estimation methods |
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Kind of Data: |
Qualitative Data |
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Kind of Data: |
Climate Data |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Disclaimer: |
<p>The Alliance of Bioversity International and CIAT (hereinafter "the Alliance"), its partners, and the data authors have exercised utmost care in collecting and compiling the data. However, the data is provided "as is" without any express or implied warranty. Neither the Alliance, its partners, the data authors, nor any relevant funding agencies shall be held liable for any actual, incidental, or consequential damages arising from the use of this data.</p> <p>By utilizing the Alliance Dataverse, users explicitly acknowledge that the data may contain nonconformities, defects, or errors. No warranty is provided that the data will meet users' needs or expectations, nor that all nonconformities, defects, or errors can or will be corrected.</p> <p>Users are responsible for verifying the accuracy and suitability of the data for their intended use. It is strongly recommended that users refer to related publications as a baseline for their analysis whenever possible. This practice serves as an additional safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the respective Dataverse study.</p> |
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Other Study Description Materials |
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Label: |
01a. Dictionary_DATABASE_LITREVIEW.xlsx |
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Text: |
Methods for estimating food systems Emissions |
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Notes: |
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet |
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Label: |
02a. DATABASE_LITREVIEW.xlsx |
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Text: |
Methods for estimating food systems Emissions |
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Notes: |
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet |