Calculating socially optimal nitrogen (N) fertilization rates for sustainable N management in China
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Updated: Jan 3, 2026

Microplot Design and Plant and Soil Sample Preparation for 15Nitrogen Analysis
Published on: May 10, 2020
Yulong Yin1, Hao Ying1, Yanfang Xue2
1Center for Resources, Environment and Food Security, China Agricultural University, Beijing 100193, China.
Abstract:
Current nitrogen (N) fertilization rates in China have incurred high social costs in the drive to achieve higher yields and economic returns. We conducted an intensive nation-wide investigation to estimate the socially optimal N rate (SOR) for Chinese maize, rice and wheat as a balance between crop productivity, farm income, ecological health and human health. The social cost of N impacts (SCN) was calculated based on 2210 field observations reported in 264 publications. The estimated SCN for three cereal crops grown in China was in the range $142-218 ha-1 at medium N fertilization rates (173-204 kg N ha-1). The net benefits of N use were calculated as the differences between private profitability and the SCN. The minimum N application rate with maximized net benefit was estimated as the SOR calculated from data compiled from 27,476 on-farm year-site trials. The average SOR was in the range 149-160 kg ha-1; values in this range were 18.1-23.7% lower than the privately optimal N rate (POR). The yield losses associated with implementation of the SOR were not significant (p < 0.01) compared with the yield of POR implementation. The POR calculates the minimum N application required to maximize private profitability, i.e., traditional N recommended practice. Compared with the POR, implementation of SOR reduced reactive N losses by 17.8-39.0%, and the SCN by 18.8-30.9%. Finally, we simulated the SOR at the county level for each soil type based on data collected from no-N control plots yields and maximum achieved yields (p < 0.01). Thus, we estimated the SOR at the Chinese county level for three cereal crops using direct on-farm measurements. This study provide updated estimates of optimizing N management to simultaneously address production and pollution problems in China and other similar regions of the world.
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