Estimating food waste in Saudi Arabia and its safe valorization into biogas, fertilizer, and feed: the WFER model

Food waste represents a critical inefficiency in the national food system, with substantial implications for environmental sustainability and resource utilization. This study quantifies food waste in Saudi Arabia and explores its potential valorization into biogas, fertilizers, and animal feed using a probabilistic model named as the Waste to Feed, Fertilizer, and Energy Recovery (WFER) model. The model integrates national food consumption data, food loss rates, and technical conversion parameters for anaerobic digestion and thermal processing. A Monte Carlo simulation accounted for variability and uncertainty in food waste generation, energy recovery, and feed production while Bayesian updating improved model adaptability with new data. Findings indicate that 3.15 billion kg of food waste per year could yield 0.15 billion m³ of biogas and a net energy gain of 328 million kilowatt-hours. This potential is further reflected in the conversion of 2.3 billion kg of plant-based waste, which could produce 9.4 billion kg of livestock feed and support the nutritional needs of over 3.8 million animals annually. Refined grains and dairy contributed the most to biogas and feed production. The model’s estimates aligned with national field studies conducted by the General Food Security Authority (GFSA). The WFER model offers a comprehensive and adaptive approach, providing critical insights for national sustainability strategies, including greenhouse gas mitigation, enhanced resource efficiency, and advancement of circular economy goals through integrated food and energy system policies.

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Publication Details

Journal
Discover Sustainability
Published
2025-12-08
DOI
https://doi.org/10.1007/s43621-025-02040-9
Primary Topic
Food Waste Reduction and Sustainability
Type
article
Field-Weighted Citation Impact
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article

Estimating food waste in Saudi Arabia and its safe valorization into biogas, fertilizer, and feed: the WFER model

Omar Alhumaidan, Mohammed Abdullah Alsaif
Discover Sustainability
Food Waste Reduction and Sustainability
article

Estimating food waste in Saudi Arabia and its safe valorization into biogas, fertilizer, and feed: the WFER model

Omar Alhumaidan, Mohammed Abdullah Alsaif
article en

Abstract

Food waste represents a critical inefficiency in the national food system, with substantial implications for environmental sustainability and resource utilization. This study quantifies food waste in Saudi Arabia and explores its potential valorization into biogas, fertilizers, and animal feed using a probabilistic model named as the Waste to Feed, Fertilizer, and Energy Recovery (WFER) model. The model integrates national food consumption data, food loss rates, and technical conversion parameters for anaerobic digestion and thermal processing. A Monte Carlo simulation accounted for variability and uncertainty in food waste generation, energy recovery, and feed production while Bayesian updating improved model adaptability with new data. Findings indicate that 3.15 billion kg of food waste per year could yield 0.15 billion m³ of biogas and a net energy gain of 328 million kilowatt-hours. This potential is further reflected in the conversion of 2.3 billion kg of plant-based waste, which could produce 9.4 billion kg of livestock feed and support the nutritional needs of over 3.8 million animals annually. Refined grains and dairy contributed the most to biogas and feed production. The model’s estimates aligned with national field studies conducted by the General Food Security Authority (GFSA). The WFER model offers a comprehensive and adaptive approach, providing critical insights for national sustainability strategies, including greenhouse gas mitigation, enhanced resource efficiency, and advancement of circular economy goals through integrated food and energy system policies.

Discover SustainabilityVol. 6(1)
King Saud University (SA), Saudi Arabian Monetary Authority (SA)
Openalex Percentile: Top 56%
Food Waste Reduction and Sustainability
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