Enhanced mitigation in nutrient surplus driven by multilateral crop trade patterns

The projected 50–100% growth in global food demand by 2050 necessitates increased crop planting and fertilizer use. However, excess nitrogen (N) and phosphorus (P) from fertilizers cause environmental problems like groundwater contamination, freshwater eutrophication, and tropospheric pollution. The United Nations has established Sustainable Development Goals to address global nutrient management. Research has focused on N and P emissions, environmental fate, spatiotemporal evolution, and pollution control. The concept of nutrient surplus (NS or PS), reflecting inputs exceeding crop needs, and nutrient surplus footprint (NSF or PSF), incorporating environmental risk and crop gain, have gained attention. Nutrient use efficiency is crucial for controlling excess nutrients. This study investigates the spatiotemporal evolution of nutrient surplus footprint at multinational scales and the response of nutrient surplus to multilateral crop trading patterns (MCTs). The research uses an integrated nutrient surplus footprint evaluation model (INSFEM), examines the response mechanisms of nutrient surplus to current crop trade patterns, and identifies the most suitable projected trade patterns for mitigating environmental stress and maximizing economic return. The study focuses on China and five Central Asian countries due to their food security challenges, severe N- and P-related environmental problems, the potential for strengthening crop trade cooperation, and the availability of data. This research aims to contribute to sustainable agricultural development and environmental protection policies.

Many studies have investigated nitrogen and phosphorus emissions from agricultural activities, their fate and transport in the environment, spatiotemporal evolution, and pollution control at global or regional scales. Some researchers have used the nutrient footprint tool to understand the lifecycle process of N and P. Recently, nutrient surplus (NS or PS) and nutrient surplus footprint (NSF or PSF) have received attention as indicators of potential environmental risks. While previous work explored nutrient emissions and footprints, the impact of multilateral crop trading patterns on nutrient surplus remains unclear. This gap in understanding hinders the development of effective policies for balancing food production and environmental protection.

This study proposes an integrated nutrient surplus footprint evaluation model (INSFEM) to calculate N and P surplus footprints for a multilateral crop trade (MCT) system. The model assesses the spatiotemporal evolution of NSF and PSF in China and five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) from 1992 to 2018 using data on 144 crops aggregated into 12 classifications. The model considers nutrient inputs (synthetic fertilizer, animal manure, atmospheric deposition, and biological fixation) and outputs (crop harvesting). Nutrient surplus is calculated as the difference between inputs and outputs. Nutrient surplus footprint is the ratio of nutrient surplus to nutrient harvested. The study examines the relationship between NSF, PSF, and net crop trade amount/structure using linear regression analysis. It also investigates virtual N and P flows due to crop trade and their impact on nutrient surplus mitigation or enhancement. To project future scenarios, the study designs four types of trade patterns: (1) varying trade amounts (increasing or decreasing by 50%, 100%, and 150%), (2) adjusting trade structures of fruits and vegetables (increasing or decreasing proportions), (3) a linear programming model maximizing system benefit (OP1), and (4) a bilevel programming model maximizing system benefit and minimizing inequality of water-land benefits (OP2). The planning horizon is 2020–2034, divided into three 5-year periods. The models consider market competition, resource transfer, and virtual nutrient flows. Data sources include the Food and Agriculture Organization of the United Nations (FAO), the International Fertilizer Industry Association (IFA), and the Data Center for Resources and Environmental Science, Chinese Academy of Sciences.

The INSFEM analysis reveals that China has significantly higher NSF and PSF than the Central Asian countries. Spatially, high footprints are concentrated in eastern and southern China and parts of Turkmenistan and Uzbekistan. Temporally, footprints increased consistently from 1992 to 2018, especially in China, Turkmenistan, and Uzbekistan. Maize is a major contributor to high footprints. Linear regression analysis shows a strong relationship between NSF and PSF and both trade amount and structure. Past crop trade between China and Central Asian countries generally led to surplus enhancement, although some mitigation was observed. Scenarios with increased trade amounts (TV1-TV3) significantly mitigate N and P surpluses in China, transitioning from enhancement to mitigation. Adjusting trade structure (TS1-TS6) has a weaker effect, mainly impacting P surplus enhancement. Optimal multilateral crop trade models (OP1 and OP2) show the most effective nutrient surplus mitigation. OP1, maximizing system benefit, leads to a substantial transition from N surplus enhancement to mitigation and a significant reduction in P surplus. OP2, incorporating water-land benefit inequality, shows similar but less dramatic mitigation due to fairness constraints.

The findings highlight the potential of optimal multilateral crop trade to mitigate nutrient surpluses. Simply increasing trade volume is effective, but optimal models that consider resource allocation and economic factors are more efficient. The results suggest that carefully designed crop trade policies can significantly reduce environmental risks associated with excess nutrient runoff while supporting food security. The difference in mitigation levels between OP1 and OP2 emphasizes the tradeoff between environmental benefits and equity considerations in policy design.

This study demonstrates that optimal multilateral crop trade patterns are effective in mitigating nitrogen and phosphorus surpluses. While increasing trade volume alone provides benefits, models that optimize both economic benefit and resource equity yield the most significant reductions in nutrient surplus. Future research should focus on validating these findings at a global scale, incorporating high-resolution data, and considering the interaction between nutrient surplus and climate change.

The study's scope is limited to China and five Central Asian countries. The model uses national-scale data, potentially limiting the accuracy of spatial analysis. The generalizability of the INSFEM to other regions and global-scale trading systems requires further investigation. The impact of climate change and other factors on nutrient surplus was not explicitly modeled.