New methodology for facilitating food wastage quantification. Identifying gaps and data inconsistencies.

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).

Identification of influencing municipal characteristics regarding household waste generation and their forecasting ability in Biscay.

The planning of waste management strategies needs tools to support decisions at all stages of the process. Accurate quantification of the waste to be generated is essential for both the daily management (short-term) and proper design of facilities (long-term). Designing without rigorous knowledge may have serious economic and environmental consequences. The present works aims at identifying relevant socio-economic features of municipalities regarding Household Waste (HW) generation by means of factor models. Factor models face two main drawbacks, data collection and identifying relevant explanatory variables within a heterogeneous group. Grouping similar characteristics observations within a group may favour the deduction of more robust models. The methodology followed has been tested with Biscay Province because it stands out for having very different municipalities ranging from very rural to urban ones. Two main models are developed, one for the overall province and a second one after clustering the municipalities. The results prove that relating municipalities with specific characteristics, improves the results in a very heterogeneous situation. The methodology has identified urban morphology, tourism activity, level of education and economic situation as the most influencing characteristics in HW generation.