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Assessing regional and global environmental footprints and value added of the largest food producers in the world

机译:评估世界上最大的食品生产商的区域和全球环境足迹和增值

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摘要

This research aims to provide important insights regarding the environmental and socioeconomic impacts of the world's largest food producing countries based on four sustainability metrics: energy use, carbon footprint, value-added and compensation of employees by low, medium and high-skill groups. World Input-Output Database is used as a detailed and intercountry and sector economic database. To compare the results between global databases, Eora and EXIOBASE are also used for comparative analysis. Three statistical analysis techniques such as Mann-Kendal trend test, matching index and k-means clustering algorithm are applied to provide a further insight from the analysis. The results are presented for three categories: regional on-site, regional supply chain, and global supply chain. The agriculture industry has the largest environmental footprints in food supply chains. Based on the Mann-Kendall trend test, there is a statistically significant trend in carbon, energy, and employment indicators. The maximum value of the matching-index of the overall impact (0.92) is achieved between the EXIOBASE and WIOD databases. China and USA are positioned in different clusters based on total sustainability performance when using different MRIO databases.
机译:本研究旨在为基于四项可持续性指标的全球最大的食品生产国家的环境和社会经济影响提供重要见解:低,中高技能群体的能源使用,碳足迹,增值和员工赔偿。世界输入输出数据库被用作详细和跨部门和部门的经济数据库。为了比较全球数据库之间的结果,EORA和EXIOBASE也用于比较分析。三种统计分析技术如曼肯纳趋势试验,匹配指数和k均值聚类算法应用于提供来自分析的进一步洞察力。结果呈现为三类:区域现场,区域供应链和全球供应链。农业产业拥有粮食供应链中最大的环境足迹。基于Mann-Kendall趋势试验,碳,能源和就业指标存在统计上显着的趋势。在ExioBase和Wiod数据库之间实现了总影响的匹配索引(0.92)的最大值。当使用不同的MRIO数据库时,中国和美国在不同的可持续发展性能范围内定位。

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