Environmental Sustainability & Health Institute, Technological University Dublin, Dublin, Ireland.
Environmental Sustainability & Health Institute, Technological University Dublin, Dublin, Ireland; School of Business, Maynooth University, Co. Kildare, Ireland.
Environ Res. 2024 Dec 15;263(Pt 3):120247. doi: 10.1016/j.envres.2024.120247. Epub 2024 Oct 28.
Food waste (FW) is a growing problem globally, with around 13% of food lost from harvest to retail, and another 17% wasted by retailers, households, and the food service sector. In high-income countries, consumer-level FW, primarily originates from private households and the food service sector, forming the largest waste stream in the food supply chain. Despite extensive research on FW, there is still a lack of knowledge about its geographic distribution, sources, spatial locations, and volume, impeding effective waste management strategies. Geospatial analysis of FW examines geographic variations in FW generation with respect to consumer demographic, behaviour, and socioeconomic factors. To date, a comprehensive review of the application of geospatial analysis to consumer-level food waste generation is not available in the scientific literature. This study aims to identify existing studies employing spatial analysis of FW generation at the consumer-level, encompassing households, commercial (non-industrial) and the food service sector within high-income region. Using the PCC (Population, Concept, Context) review protocol, 14 relevant studies were identified, delineated into three spatial scales: local (29%, n = 4), regional (42%, n = 6), and national (29%, n = 4). Methodologies included spatial autocorrelation (n = 2), spatial cluster analysis (n = 2), and geospatial analysis integrating non-spatial data with spatial datasets (n = 8) at various geographic levels. This review evaluated the advantages and disadvantages of these spatial techniques and their effectiveness in analysing FW generation. Only one study focused on household FW incorporating socioeconomic and demographic characteristics of consumers. The low number of identified studies highlights a significant knowledge gap in the assessment of spatial associations between FW generation and associated drivers/predictors. Improved FW data and indices are essential for analysing FW patterns across different demographics or regions, identifying hotspots, and mapping FW data using geographic information system (GIS) at multiple scales, thus permitting increasingly bespoke waste reduction interventions and strategies based on spatial insights.
食物浪费（FW）是一个全球性的日益严重的问题，从收获到零售过程中损失了约 13%的食物，零售商、家庭和食品服务部门又浪费了 17%的食物。在高收入国家，消费者层面的 FW 主要来自私人家庭和食品服务部门，是食品供应链中最大的废物来源。尽管对 FW 进行了广泛的研究，但人们对其地理分布、来源、空间位置和数量仍然知之甚少，这阻碍了有效的废物管理策略的制定。FW 的地理空间分析研究了 FW 生成在消费者人口统计学、行为和社会经济因素方面的地理变化。迄今为止，科学界尚未对消费者层面 FW 生成的地理空间分析应用进行全面综述。本研究旨在确定现有的在高收入地区对消费者层面食物浪费生成进行空间分析的研究，涵盖家庭、商业（非工业）和食品服务部门。使用 PCC（人口、概念、背景）审查方案，确定了 14 项相关研究，将其划分为三个空间尺度：局部（29%，n=4）、区域（42%，n=6）和国家（29%，n=4）。方法包括空间自相关（n=2）、空间聚类分析（n=2）以及将非空间数据与空间数据集相结合的地理空间分析（n=8），在不同的地理层面进行分析。本综述评估了这些空间技术的优缺点及其在分析 FW 生成方面的有效性。只有一项研究侧重于包含消费者社会经济和人口统计特征的家庭 FW。所确定的研究数量较少，这突出表明在评估 FW 生成与相关驱动因素/预测因素之间的空间关联方面存在重大知识差距。改进 FW 数据和指标对于分析不同人口统计学或地区的 FW 模式、识别热点以及使用地理信息系统（GIS）在多个尺度上绘制 FW 数据至关重要，从而可以根据空间洞察力实施越来越定制化的减少废物干预措施和策略。
