| Literature DB >> 32619842 |
R Aldaco1, D Hoehn2, J Laso2, M Margallo2, J Ruiz-Salmón2, J Cristobal2, R Kahhat3, P Villanueva-Rey4, A Bala5, L Batlle-Bayer5, P Fullana-I-Palmer5, A Irabien2, I Vazquez-Rowe3.
Abstract
Improving the food supply chain efficiency has been identified as an essential means to enhance food security, while reducing pressure on natural resources. Adequate food loss and waste (FLW) management has been proposed as an approach to meet these objectives. The main hypothesis of this study is to consider that the "strong fluctuations and short-term changes" on eating habits may have major consequences on potential FLW generation and management, as well as on GHG emissions, all taking into account the nutritional and the economic cost. Due to the exceptional lockdown measures imposed by the Spanish government, as a consequence of the emerging coronavirus disease, COVID-19, food production and consumption systems have undergone significant changes, which must be properly studied in order to propose strategies from the lessons learned. Taking Spain as a case study, the methodological approach included a deep analysis of the inputs and outputs of the Spanish food basket, the supply chain by means of a Material Flow Analysis, as well as an economic and comprehensive nutritional assessment, all under a life cycle thinking approach. The results reveal that during the first weeks of the COVID-19 lockdown, there was no significant adjustment in overall FLW generation, but a partial reallocation from extra-domestic consumption to households occurred (12% increase in household FLW). Moreover, the economic impact (+11%), GHG emissions (+10%), and the nutritional content (-8%) complete the multivariable impact profile that the COVID-19 outbreak had on FLW generation and management. Accordingly, this study once again highlights that measures aimed at reducing FLW, particularly in the household sector, are critical to make better use of food surpluses and FLW prevention and control, allowing us to confront future unforeseen scenarios.Entities:
Keywords: COVID-19; Eating habits; Food loss waste (FLW); GHG emissions; Life cycle assessment (LCA); Nutritional impact
Mesh:
Year: 2020 PMID: 32619842 PMCID: PMC7319639 DOI: 10.1016/j.scitotenv.2020.140524
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 10.753
Fig. 1Overview of the functionality and system boundaries of the Spanish food system influenced by the COVID-19 pandemic.
Spanish production and consumption scenarios.
| Code | Time frame | Mix consumption (%) | Electricity mix (a) | |
|---|---|---|---|---|
| Household | Extra-domestic | |||
| P1 | Weeks 11–15, 2019 | 86.1 | 13.9 | Mostly fossil fuels |
| P2 | Week 11, 2020 | 86.1 (b) | 13.9 (b) | Mostly non-fossil fuels |
| Weeks 12–15, 2020 | 100 (c) | 0 (c) | ||
(a) Detailed information about the electricity mix is included in Table S1 of the SM. (b) Extra-domestic consumption was available for most of week 11, excepting the (c) Weeks 12–15.
Food purchase rates during weeks 11–15 of COVID-19 and the same period of 2019 (kg/cap-week).
| Food category | March 2019 | April 2019 | Week 11 | Week 12 | Week 13 | Week 14 | Week 15 |
|---|---|---|---|---|---|---|---|
| Eggs | 0.183 | 0.184 | 0.233 | 0.190 | 0.238 | 0.238 | 0.292 |
| White meat | 0.395 | 0.375 | 0.355 | 0.347 | 0.372 | 0.355 | 0.395 |
| Red meat | 0.626 | 0.615 | 0.672 | 0.642 | 0.702 | 0.669 | 0.681 |
| Fresh fish | 0.302 | 0.298 | 0.268 | 0.265 | 0.270 | 0.262 | 0.266 |
| Frozen fish | 0.099 | 0.098 | 0.103 | 0.100 | 0.104 | 0.102 | 0.122 |
| Processed fish | 0.111 | 0.119 | 0.137 | 0.093 | 0.100 | 0.090 | 0.101 |
| Dairy | 2.260 | 2.282 | 2.554 | 2.068 | 2.270 | 2.173 | 2.302 |
| Cereals | 0.885 | 0.872 | 1.062 | 0.905 | 0.934 | 0.922 | 1.043 |
| Sweets | 0.458 | 0.460 | 0.511 | 0.454 | 0.507 | 0.496 | 0.548 |
| Pulses | 0.272 | 0.267 | 0.417 | 0.325 | 0.304 | 0.277 | 0.278 |
| Vegetable fats | 0.296 | 0.316 | 0.424 | 0.318 | 0.339 | 0.303 | 0.351 |
| Roots and tubers | 0.539 | 0.551 | 0.559 | 0.567 | 0.589 | 0.582 | 0.605 |
| Vegetables | 1.840 | 1.777 | 1.854 | 1.743 | 1.840 | 1.786 | 1.883 |
| Fruits | 1.755 | 1.716 | 1.739 | 1.787 | 1.894 | 1.893 | 1.936 |
| Beverages | 1.191 | 1.198 | 0.581 | 0.630 | 0.640 | 0.826 | 0.898 |
Fig. 2Overall FLW during pre-COVID-19 (P1) and COVID-19 scenarios (P2). (a) Total amount of FLW and food consumption; (b) FLW nutritional assessment; (c) FLW economic assessment; (d) FLW greenhouse gas (GHG) assessment.
Fig. 3Assessment of food categories during pre-COVID-19 (P1) and COVID-19 (P2a) scenarios. (a) Total amount of FLW and food consumption; (b) FLW nutritional assessment; (c) FLW economic assessment; (d) FLW greenhouse gas (GHG) assessment.
Fig. 4Holistic FLW assessment during pre-COVID-19 (P1) and COVID-19 (P2) scenarios. (a) Total amount of FLW and food consumption; (b) FLW nutritional assessment; (c) FLW economic assessment; (d) FLW greenhouse gas (GHG) assessment.
Parameters and alternative scenarios evaluated in the sensitivity analysis.
| Code | Time frame | Parameter | Baseline value | Modified value |
|---|---|---|---|---|
| M1 | COVID-19 | FLW generation in households | (a) | +20% |
| M2 | COVID-19 | FLW generation in households | (a) | −20% |
| M3 | COVID-19 | FLW generation in distribution | (a) | −20% |
(a) FLW factors based on Gustavsson et al. (2011).
Fig. 5Sensitivity analysis for the considered scenarios during the COVID-19 outbreak: (M1) increase of 20% in the generation of FLW in households; (M2) reduction of 20% in the generation of FLW in households; (M3) losses in distribution and sales decrease by 20%.