Reducing Food Loss and Associated Greenhouse Gas Emissions Using a Dynamic Shelf Life Approach

Area of Science:

• Environmental Science
• Food Science
• Supply Chain Management

Background:

• The integration of Internet of Things (IoT) sensors with dynamic shelf life (DSL) systems provides real-time visibility into perishable goods.
• The full life-cycle trade-offs of these technologies, including environmental impacts and food loss reduction, are not yet fully understood.

Purpose of the Study:

• To develop a process-based life cycle framework to evaluate the trade-offs of IoT-DSL systems in China's fresh food chains.
• To quantify avoided food loss and waste, and sensor-embedded climate burdens associated with IoT-DSL deployment.

Main Methods:

• A kinetic quality-degradation model and Monte Carlo simulations were employed.
• A process-based life cycle framework was developed to assess environmental impacts and food loss across China's fresh food supply chains.

Main Results:

• IoT-DSL systems extended average shelf life by 8.1-13.8% for fruits, dairy, and vegetables.
• Large-scale deployment could avert 17.32 ± 3.65 Mt yr-1 of food waste and achieve a net reduction of 51.00 ± 10.38 Mt CO2-eq yr-1.
• Sensor fabrication was identified as the primary contributor to environmental impacts, highlighting the need for eco-design and e-waste recovery.

Conclusions:

• IoT-DSL technology offers substantial potential for reducing food waste and associated greenhouse gas emissions in China's food supply chain.
• Upstream impacts from sensor production necessitate sustainable manufacturing practices and effective e-waste management.
• Future innovations in food technology and dietary shifts can further enhance mitigation potential.