Abstract
Food waste is a growing public concern because the food production and distribution exert enormous pressure on natural resources such as land, water and energy, and leads to significant environmental, societal and economic impacts. Thus, the European Commission has aimed to reduce to 50% the total amount of discarded edible food waste by 2020 within the European Union (EU) Member States. Reliable data on food waste and a better understanding of the food waste generation patterns are crucial for planning the avoidable food waste reduction and an environmental sound treatment of unavoidable food waste. Although, food waste composition carries relative information, no attempt was made to analysis food waste composition as compositional data. Thus the relationship between food waste fractions has been analysed by mean of Pearson correlation test and log-ratio analysis. The food waste data was collected by sampling and sorting residual household waste in Denmark. The food waste was subdivided into three fractions: (1) avoidable vegetable food waste, (2) avoidable animal-derive food waste, and (3) avoidable food waste. The correlation was carried out using: (a) the amount of food waste (kg per household per week), (b) percentage composition of food waste based on the total food waste, and (c) percentage composition of food waste based on the total residual household waste. The Pearson correlation test showed different results when different datasets are used, whereas the log-ratio analysis showed the same results for all the three datasets.
Info
Conference Abstract, 2015
UN SDG Classification
DK Main Research Area
Science/Technology
