Opportunities for AgrI-Food Chains to become Energy-Smart
Opportunities for AgrI-Food Chains to become Energy-Smart
复制标题
农业食品链实现能源智能型的机遇
DOI：
10.1016/j.ecolecon.2014.02.020
复制
发表时间：
2015
影响因子：
7
通讯作者：
Stefania Bracco
中科院分区：
文献类型：
--
作者：
R. Sims;A. Flammini;Manas Puri;Stefania Bracco
生态足迹（EF）是人类对生物生产性土地需求的指标，生物生产性土地是一种重要但有限的资源，其使用与环境负担相关。在本文中，我们比较了三种计算国家EF的方法：a）以全球足迹网络（GFN）账户为代表的过程分析； b) 标准环境扩展多区域输入输出模型（EE-MRIOM）； c) 混合 EE-MRIOM。过程分析考虑了所选产品的国内生产总量和国际贸易总量。标准 EE-MRIOM 进一步考虑了所有交易产品的上游足迹，但可用数据集中相关产品的分辨率较低。这里评估的混合 EE-MRIO 方法通过环境扩展追踪物理单位中的主要生物质产品。我们的结果表明，标准 MRIO 模型可能由于分辨率低和数据质量差而引入显着误差。混合 MRIO 方法比标准 MRIO 方法提供更准确的结果，因为它更详细地应用来自其他来源的数据。流程分析低估了进出口的足迹，因为它忽略了服务和其他产品的贸易以及分析中包含的产品的上游流动。
The ecological footprint (EF) is an indicator of human requirements on bio-productive land, an essential but limited resource, which use is related to environmental burden. In this article, we compare three methods for calculating national EF: a) the process analysis represented by Global Footprint Network (GFN) accounts; b) a standard environmentally extended multi-regional input–output model (EE-MRIOM); and c) a hybrid EE-MRIOM. The process analysis accounts for total domestic production and international trade of selected products. A standard EE-MRIOM further accounts for the upstream footprint of all traded products, but has a low resolution of relevant products in available datasets. The hybrid EE-MRIO method assessed here traces the primary biomass products in physical units through environmental extensions. Our results show that the standard MRIO model might introduce a significant error due to low resolution and poor data quality. The hybrid MRIO approach provides more accurate results than the standard MRIO method since it applies data from additional sources on a more detailed level. The process analysis underestimates the footprint of imports and exports as it ignores trade in services and other products as well as the upstream flows of products included in the analysis.
影响因子：
--
作者：
C. Wan;W. I. Ismail;A. Yahya;S. M. Bockari-Gevao
通讯作者：
C. Wan;W. I. Ismail;A. Yahya;S. M. Bockari-Gevao