DeustoTech - Fundación Deusto, Avda. Universidades, 24, 48007, Bilbao, Spain; Facultad Ingeniería, Universidad de Deusto, Avda. Universidades, 24, 48007, Bilbao, Spain.
DeustoTech - Fundación Deusto, Avda. Universidades, 24, 48007, Bilbao, Spain; Facultad Ingeniería, Universidad de Deusto, Avda. Universidades, 24, 48007, Bilbao, Spain.
J Environ Manage. 2019 Mar 15;234:512-524. doi: 10.1016/j.jenvman.2018.11.037. Epub 2019 Jan 14.
The Food and Agriculture Organization of the United Nations estimated that about 1.3 billion tons of food produced for human consumption was lost or wasted globally. Thus, the reduction of the current food loss and waste along the agrifood chain is becoming a priority, both for optimization of resources and reduction waste generation costs. For this purpose, the first step is to quantify the food wastage generation to be able to identify corrective measures. However, in spite of the considerable efforts already undertaken to establish common methodologies to measure the food wastage at different geographical scales, there are still some gaps and inconsistencies. In this regard, the information gathering is labour-intensive because of the different actors involved. The creation of new methodologies and tools capable of automatically identifying these agents would be of great value so as to subsequently apply the more appropriates quantification methodologies. This work aims at providing a new methodology to facilitate this process thanks to the previous identification and classification of the potential food wastage generators. As a result, it provides baseline information for one of the earliest steps of the food wastage quantification process, which is the establishment of the scope of the food wastage inventory. The baseline data needed is taken from the Statistical classification of economic activities in the European Community (NACE), particularly from the most disaggregated level called "classes". This information has been combined with data from the trading income tax at municipal scale thanks to the use of Geographic Information Systems (GIS) and the common codes for NACE classes, generating a visual tool for the localization of points with potential of food-wastage generation and their weight of each economic activity over the agrifood chain. The proposed methodology has been implemented for the real case of the municipality of Zamudio (Spain) and it has allowed the identification of the different entities linked with economic activities that are potential generators of food wastage, the weight of each activity over the entire agrifood chain, and the geographical location of these entities in the territory. Furthermore, this methodology was used to compare the nature and number of these activities in another municipality (Karrantza, Spain) and it has also been applied to the entire region of the Basque Country (Spain).
联合国粮食及农业组织估计,全球生产供人类消费的食物中有约 13 亿吨损失或浪费。因此,沿农业食品链减少当前的粮食损失和浪费正成为当务之急,这既是为了优化资源,也是为了减少浪费产生的成本。为此,第一步是量化粮食浪费的产生,以便能够确定纠正措施。然而,尽管已经为在不同地理尺度上衡量粮食浪费制定共同方法做出了相当大的努力,但仍存在一些差距和不一致之处。在这方面,由于涉及不同的行为者,信息收集工作非常繁琐。创建能够自动识别这些行为者的新方法和工具将具有巨大的价值,以便随后应用更合适的量化方法。这项工作旨在通过先前对潜在粮食浪费产生者的识别和分类,提供一种新的方法来促进这一过程。其结果是,为粮食浪费量化过程的最早步骤之一提供了基准信息,即建立粮食浪费清单的范围。所需的基准数据来自欧洲共同体经济活动的统计分类(NACE),特别是来自称为"类别"的最细化级别。这些信息与得益于使用地理信息系统(GIS)和 NACE 类别的通用代码的市级贸易所得税数据相结合,生成了一个用于定位具有粮食浪费产生潜力的点及其在农业食品链上每个经济活动的权重的可视化工具。所提出的方法已在西班牙 Zamudio 市的实际案例中实施,并能够识别与经济活动相关的不同实体,这些实体是粮食浪费的潜在产生者,每个活动在整个农业食品链中的权重,以及这些实体在该地区的地理位置。此外,该方法用于比较另一个市镇(西班牙的Karrantza)的这些活动的性质和数量,并且已经应用于整个巴斯克地区(西班牙)。