Introduction
The study addresses the challenge of achieving Sustainable Development Goal 2 (SDG2) – ensuring universal access to safe and nutritious food in an environmentally sustainable way by 2030 – in the face of short-term shocks to the global food system. The Russia-Ukraine conflict serves as a case study, highlighting the significant disruption to global food supplies caused by this regional conflict. Russia and Ukraine are major exporters of key crops, and the conflict has resulted in export bans, sanctions, and disruptions to fertilizer supplies. These factors have led to increased food insecurity globally. While existing literature focuses on long-term shocks, this research aims to quantify and understand the impacts of short-term shocks and find solutions for optimizing food systems to mitigate both food shortages and environmental consequences. The paper introduces a novel shock-impact-response framework to model these effects.
Literature Review
The paper reviews existing literature on the impacts of the Russia-Ukraine conflict on global food security, noting various suggested solutions such as ending the war, dietary changes, expanding global production, and food system transformation. However, a gap exists in quantifying the environmental impacts of compensating for food shortages. This study addresses this gap by modeling the environmental consequences of different responses to the crisis.
Methodology
The study employs a three-step framework: (1) quantifying changes in food production and trade using an adaptive multi-regional input-output (AMRIO) model; (2) assessing the impact on cropland use and GHG emissions using a quasi-input-output (QIO) model; and (3) optimizing the location of global production using a multi-objective genetic algorithm (NSGA-II) to minimize GHG emissions, cropland use, and food transport costs. The AMRIO model simulates the impacts of different conflict scenarios by considering factors such as war duration, damage to Ukraine, sanctions on Russia, and the number of countries involved. The QIO model tracks changes in embodied cropland use and GHG emissions in global agricultural trade. The NSGA-II algorithm optimizes food production and trade patterns to achieve multiple objectives. The study considers nine dominant food products: rice, wheat, maize, barley, rye, beans, rapeseed, soybeans, and sunflower seed.
Key Findings
The key findings highlight the complex and multifaceted impacts of the Russia-Ukraine conflict on the global food system and its environmental footprint.
**Short-term impacts:** The conflict initially resulted in a 0.6–1.8% reduction in global production of the nine crops, with the most significant impact seen in Asia. Global food exports fell by 3.5–7.2%, and imports decreased even more drastically (4.3–9.3%). A food shortage of 53–130 million tons emerged, affecting primarily Asia, Africa, and Europe, with 360–490 million people facing nutrition security risks. Interestingly, there was a temporary decline in cropland use (3–11 million hectares) and GHG emissions (24–60 million tons of CO2) due to the conflict.
**Long-term impacts:** Agricultural recovery in the subsequent growing season led to a 2.4–3% increase in global production compared to the first year of the war, but this was still below pre-war levels. A 2–4% increase in GHG emissions and a 9–10% expansion of cropland were observed. The most substantial impact occurred in East Asia, Eastern Europe, and the east coast of the Americas. The analysis of embodied environmental impacts revealed that the war altered the transfer patterns of cropland use and GHG emissions through food trade, with Asia experiencing the most significant shifts.
**Optimization results:** The optimization of global food production and trade, using the NSGA-II algorithm, demonstrated that it is possible to reduce global GHG emissions by 1.7–2.7% and cropland use by 3.7–4.5% while maintaining food security. The study offers region-specific recommendations for increasing production of certain crops to meet shortages while minimizing environmental impacts. For instance, increasing barley production in France, maize production in the US, and soybean production in the USA were suggested as some examples.
Discussion
The findings demonstrate that even short-term regional shocks like the Russia-Ukraine war can have far-reaching global consequences on both food security and environmental sustainability. The initial decrease in cropland use and GHG emissions highlights the complex interactions within the global food system. However, the post-war recovery period resulted in increased environmental pressure, underscoring the need for optimized agricultural practices and trade policies. The successful optimization of the food supply chain using the NSGA-II algorithm demonstrates that it is feasible to mitigate both food shortages and environmental consequences simultaneously. This approach highlights the crucial role of strategic planning and international collaboration in building a more resilient and sustainable global food system.
Conclusion
The study provides a comprehensive assessment of the global environmental impacts of the Russia-Ukraine conflict on the food system. It highlights the need for a proactive and integrated approach to managing short-term shocks, emphasizing the importance of optimized food production and trade patterns. The developed framework can be applied to future scenarios to inform policy interventions aimed at ensuring food security and environmental sustainability. Future research could focus on extending the timeframe of the analysis and incorporating more granular data to achieve even higher levels of accuracy and relevance.
Limitations
The study acknowledges several limitations, including the reliance on publicly available data which could be incomplete or subject to delays; therefore the calibration and projection may have some level of uncertainty. The model does not incorporate all aspects of the complex global food system; hence, the results are illustrative and might not capture all the nuances of the situation. Future studies with more extensive and region-specific data could refine these analyses.
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