Food waste end-of-life management for the United States: Parameterized life cycle inventory datasets.

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Data in Brief Pub Date : 2024-11-24 eCollection Date: 2024-12-01 DOI:10.1016/j.dib.2024.111174
Kyle McGaughy, Ben Morelli, Abby Martell, James Santa Ana, Wesley W Ingwersen
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引用次数: 0

Abstract

A life cycle inventory (LCI) dataset for food waste management was developed using secondary data from scientific literature and government reports. EPA reports on food waste management were used as the basis for collecting literature to review. Unit process parameters from the reviewed literature are compiled and combined with engineering calculations to generate LCI for food management pathways. Both the literature values and engineering calculations are reviewed and documented with notes indicating any potential limitations in the dataset. The Excel-based inventory model includes pathways for anaerobic digestion, composting - windrow and aerated static pile, landfilling, and incineration. The model includes default parameter value selections, but the inventory may also be generated using user-specified parameter values. The model includes site-specific unit process models that do not have default parameter values pre-selected. Users can specify parameter values within these unit processes to generate LCI data for the food waste management pathways in line with their project scope. Site-specific unit processes include options such as biogas and landfill gas utilization and treatment of compost and digestate. This dataset and model can be used to generate LCI for evaluating food waste management in a comprehensive life cycle assessment study.

美国的食物垃圾报废管理:参数化生命周期清单数据集。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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