Yaling Li

Global dietary transitions confront the dual challenge of reconciling nutrition equity with environmental sustainability. This study evaluates three equity-centered dietary transitions scenarios grounded in country-specific dietary recommendations across 181 countries: CP (current patterns), LP (low-emission substitutions, e.g. poultry replacing ruminants), and HP (high-emission alternatives), to quantify emission dynamics and assess alignment with Paris Agreement temperature targets. Business-as-usual trends (BAU) result in cumulative food-related emissions of 1768 Gt CO ₂ e between 2020 and 2100. While CP reduces this to 1411 Gt CO ₂ e, achieving only marginal alignment with the 2 °C limit, LP achieves a 37% reduction to 1113 Gt CO ₂ e, ensuring robust compatibility with the 2 °C target. In contrast, HP emissions surpass even BAU levels. Central to the LP pathway, we propose an equity-centered allocation framework that differentiates mitigation obligations and emission allowances based on deviations from national dietary guidelines. Countries with excessive intakes, particularly of animal-source foods, are thus assigned stringent obligations (e.g. USA: 58.85 Gt CO ₂ e; China: 131.10 Gt CO ₂ e). Conversely, those with inadequate nutritional intake are allocated safeguarded allowances (e.g. Nigeria: 25.63 Gt CO ₂ e; Ethiopia: 24.94 Gt CO ₂ e), scaled to population size to uphold nutritional rights. However, even under this optimized pathway, the residual emission budget for non-food sectors is constrained to a narrow range of 407–818 Gt CO ₂ e. This severe constraint renders the 1.5 °C target unattainable through dietary shifts alone, underscoring the imperative for coordinated cross-sectoral decarbonization integrated with equity-centered policies.

This study aims to estimate the value of El Niño-Southern Oscillation (ENSO) forecasting to China’s agricultural sector. This study applies the Weibull distribution to model crop yields under different ENSO phases. Under the framework of Bayesian decision theory, this research pioneers the application of China’s Agricultural Sector Model to translate the yield effects resulting from ENSO variations into economic effects. Results show that ENSO exerts noticeable and heterogeneous effects on crop yields over selected crops across different regions. In addition, ENSO forecasting is useful for farmers’ cropping decisions and positively impacts economic surplus. The findings present that the value of this information is generally positive and rises with improved forecast accuracy, with the value of perfect forecasting estimated to be as substantial as CNY 3168 million. However, the value of ENSO forecasting is relatively small in the context of China’s tremendous agricultural output. This study is the first to evaluate the value of ENSO forecasting to China’s agriculture sector and has critical implications for the promotion of a Chinese ENSO forecast system.