遇见数据集

Input-Output Global Hybrid Analysis of Agricultural Primary Production (IO-GHAAP) Database

收藏
Zenodo2023-09-28 更新2026-05-26 收录
数据链接:
官方服务:

资源简介:

A commonly used method to examine the relationship between global water consumption and production is input--output analysis. However, between approximately 70% and 90% of freshwater consumption occurs in agricultural primary production, which is often represented by only a small percentage of the total number of sectors in input-output databases. In addition, the assessment of the impact of water consumption is usually carried out at the national level. <br> Therefore, the primary objective of the Input-Output Global Hybrid Analysis of Agricultural Primary Production (IO-GHAAP) approach was to improve assessments of water use and its impacts in input-output analysis. <br> To achieve this objective, a global spatial model of agricultural primary production <em>MapSPAM</em> (IFPRI, 2019) was integrated into the existing input-output database <em>GLORIA</em> (Lenzen et al., 2017, 2021) via prorating. The resulting IO-GHAAPP approach includes (1) a disaggregated input-output database and novel environmental extensions for freshwater consumption and scarcity. The IO-GHAAPP database consists of 150 categories and 164 regions, resulting in a total of 24,600 region-category combinations. Forty-two of the categories are dedicated to agricultural primary production (28%). In comparison, the source input--output data consist of 120 categories and 164 regions, resulting in a total of 19,680 region-category combinations, of which 14 are dedicated to agricultural primary production (12%). <strong>Please cite as:</strong> Bunsen, Jonas, Vlad Coroamă, and Matthias Finkbeiner. 2023. ‘Input-Output Global Hybrid Analysis of Agricultural Primary Production (IO-GHAAPP) Database’. <em>Sustainability</em> 15 (2). https://doi.org/10.3390/su15129351. <strong>References:</strong> IFPRI. 2019. ‘Global Spatially-Disaggregated Crop Production Statistics Data for 2010 Version 2.0’. Harvard Dataverse. https://doi.org/10.7910/DVN/PRFF8V. Lenzen, Manfred, Arne Geschke, Muhammad Daaniyall Abd Rahman, Yanyan Xiao, Jacob Fry, Rachel Reyes, Erik Dietzenbacher, et al. 2017. ‘The Global MRIO Lab - Charting the World Economy’. <em>Economic Systems Research</em> 29 (2): 158–86. https://doi.org/10.1080/09535314.2017.1301887. Lenzen, Manfred, Arne Geschke, James West, Jacob Fry, Arunima Malik, Stefan Giljum, Llorenç Milà i Canals, et al. 2021. ‘Implementing the Material Footprint to Measure Progress towards Sustainable Development Goals 8 and 12’. <em>Nature Sustainability</em>, December. https://doi.org/10.1038/s41893-021-00811-6.

提供机构:
Zenodo
创建时间:
2023-04-28
二维码
社区交流群
二维码
科研交流群
商业服务