From consumption to capacity: demand-oriented forecasting of cold storage needs for a net-zero UK food chain.

Achieving net-zero emissions in the UK food supply chain requires accurate forecasting tools to guide infrastructure planning and identify potential mitigation pathways. This study proposes a demand- oriented, time-series forecasting approach that estimates future cold storage requirements based on household consumption of chilled and frozen foods. Consumption data have been retrieved from the 2024 edition of the UK Family Food Dataset provided by DEFRA, comprising last 50 years of longitudinal data. Model selection follows the Box-Jenkins methodology to identify optimal Autoregressive Integrated Moving Average (ARIMA) model configurations across nine major cooling food categories. By shifting from traditional supply-side extrapolation to consumption-driven forecasting, this research introduces a novel framework grounded in consumer behaviour. The resulting projections offer a robust empirical basis for anticipatory cold chain capacity planning, reducing the risk of overcapacity and associated emissions, and supporting more adaptive, demand-responsive decarbonization strategies in line with national climate targets.