Updated loss factors and high-resolution spatial variations for reactive nitrogen losses from Chinese rice paddies.

Anthropogenic reactive nitrogen (Nr) loss has been a critical environmental issue. However, due to the limitations of data availability and appropriate methods, the estimation of Nr loss from rice paddies and associated spatial patterns at a fine scale remain unclear. Here, we estimated the background Nr loss (BNL, i.e., Nr loss from soils without fertilization) and the loss factors (the percentage of Nr loss from synthetic fertilizer, LFs) for five loss pathways in rice paddies and identified the national 1 × 1 km spatial variations using data-driven models combined with multi-source data. Based on established machine learning models, an average of 23.4% (15.3-34.6%, 95% confidence interval) of the synthetic N fertilizer was lost to the environment, in the forms of NH3 (17.4%, 10.9-26.7%), N2O (0.5%, 0.3-0.8%), NO (0.2%, 0.1-0.4%), N leaching (3.1%, 0.8-5.7%), and runoff (2.3%, 0.6-4.5%). The total Nr loss from Chinese rice paddies was estimated to be 1.92 ± 0.52 Tg N yr-1 in 2021, in which synthetic fertilizer-induced Nr loss accounted for 69% and BNL accounted for the other 31%. The hotspots of Nr loss were concentrated in the middle and lower regions of the Yangtze River, an area with extensive rice cultivation. This study improved the estimation accuracy of Nr losses and identified the hotspots, which could provide updated insights for policymakers to set the priorities and strategies for Nr loss mitigation.

Data-driven estimation of nitric oxide emissions from global soils based on dominant vegetation covers.

Soils are a major source of global nitric oxide (NO) emissions. However, estimates of soil NO emissions have large uncertainties due to limited observations and multifactorial impacts. Here, we mapped global soil NO emissions, integrating 1356 in-situ NO observations from globally distributed sites with high-resolution climate, soil, and management practice data. We then calculated global and national total NO budgets and revealed the contributions of cropland, grassland, and forest to global soil NO emissions at the national level. The results showed that soil NO emissions were explained mainly by N input, water input and soil pH. Total above-soil NO emissions of the three vegetation cover types were 9.4 Tg N year-1 in 2014, including 5.9 Tg N year-1 (1.04, 95% confidence interval [95% CI]: 0.09-1.99 kg N ha-1 year-1 ) emitted from forest, 1.7 Tg N year-1 (0.68, 95% CI: 0.10-1.26 kg N ha-1 year-1 ) from grassland, and 1.8 Tg N year-1 (0.98, 95% CI: 0.42-1.53 kg N ha-1 year-1 ) from cropland. Soil NO emissions in approximately 57% of 213 countries surveyed were dominated by forests. Our results provide updated inventories of global and national soil NO emissions based on robust data-driven models. These estimates are critical to guiding the mitigation of soil NO emissions and can be used in combination with biogeochemical models.

Cropland nitrous oxide emissions exceed the emissions of RCP 2.6: A global spatial analysis.

Nitrous oxide (N2O), as a potent greenhouse gas, must be limited to prevent the global temperature increasing by >2 °C. Cropland is the largest source of anthropogenic N2O emissions; however, earlier estimates for emissions and their exceedances still remain uncertainties. Here, we used a spatially explicit model to estimate cropland N2O emission in 2014 by refined grid-level crop-specific EFs and considered the background emission. We also sought to determine where N2O emissions exceed the "boundary" through analysis of spatial data from representative concentration pathway (RCP) 2.6. The global cropland N2O emission was 2.92 ± 0.59 Tg N yr-1, which far exceeds the 0.82 Tg N yr-1 boundary, over 90 % of cropland areas exceeded the boundary. Western Europe, Southeastern China, Pakistan, and the Ganges Plain exceeded the boundary by >2 kg N ha-1 yr-1. The boundary exceedances showed a positive linear response with respect to total cropland emission and a quadratic response to GDP per capita at the country level. Our study highlights the necessity of accurate estimations of spatial variations in cropland N2O emissions and evaluation of exceedances, to facilitate the development of more effective mitigation measures in different regions.

Bottom-up estimates of reactive nitrogen loss from Chinese wheat production in 2014.

Excessive use of synthetic nitrogen (N) for Chinese wheat production results in high loss of reactive N loss (Nr; all forms of N except N2) into the environment, causing serious environmental issues. Quantifying Nr loss and its spatial variations therein is vital to optimize N management and mitigate loss. However, accurate, high spatial resolution estimations of Nr from wheat production are lacking due to limitations of data generation and estimation methods. Here, we applied the random forest (RF) algorithm to bottom-up N application rate data, obtained through a survey of millions of farmers, to estimate the Nr loss from wheat production in 2014. The results showed that the average total Nr loss was 52.5 kg N ha-1 (range: 4.6-157.8 kg N ha-1), which accounts for 26.1% of the total N applied. The hotspots for high Nr loss are the same as those high applied N, including northwestern Xinjiang, central-southern Hebei, Shandong, central-northern Jiangsu, and Hubei. Our database could guide regional N management and be used in conjunction with biogeochemical models.

Integrating crop redistribution and improved management towards meeting China's food demand with lower environmental costs.

China feeds 19.1% of the world's population with 8.6% of the arable land. Here we propose an integrated approach combining crop redistribution and improved management to meet China's food demand in 2030. We simulated the food demand, estimated the national crop production through the productivity of the top 10% of producers in each county, and optimized the spatial distribution of 11 groups of crop types among counties using the data of the top producers. Integrating crop redistribution and improved management increased crop production and can meet the food demand in 2030, while the agricultural inputs (N and P fertilizers and irrigation water) and environmental impacts (reactive N loss and greenhouse gas emissions) were reduced. Although there are significant socio-economic and cultural barriers to implementing such redistribution, these results suggest that integrated measures can achieve food security and decrease negative environmental impacts. County-specific policies and advisory support will be needed to achieve the promises of combining optimization strategies.

Evaluation of variation in background nitrous oxide emissions: A new global synthesis integrating the impacts of climate, soil, and management conditions.

Robust global simulation of soil background N2 O emissions (BNEs) is a challenge due to the lack of a comprehensive system for quantification of the variations in their magnitude and location. We mapped global BNEs based on 1353 field observations from globally distributed sites and high-resolution climate and soil data. We then calculated global and national total BNE budgets and compared them to the IPCC-estimated values. The average BNE was 1.10, 0.92, and 0.84 kg N ha-1  year-1 with variations from 0.18 to 3.47 (5th-95th percentile, hereafter), 0.20 to 3.44, and -1.16 to 3.70 kg N ha-1  year-1 for cropland, forestland, and grassland, respectively. Soil pH, soil N mineralization, atmospheric N deposition, soil volumetric water content, and soil temperature were the principle significant drivers of BNEs. The total BNEs of three land use types was lower than IPCC-estimated total BNEs by 0.83 Tg (1012  g) N year-1 , ranging from -47% to 94% across countries. The estimated BNE with cropland values were slightly higher than the IPCC estimates by 0.11 Tg N year-1 , and forestland and grassland lower than the IPCC estimates by 0.4 and 0.54 Tg N year-1 , respectively. Our study underlined the necessity for detailed estimation of the spatial distribution of BNEs to improve the estimates of global N2 O emissions and enable the establishment of more realistic and effective mitigation measures.

A steady-state N balance approach for sustainable smallholder farming.

Hundreds of millions of smallholders in emerging countries substantially overuse nitrogen (N) fertilizers, driving local environmental pollution and global climate change. Despite local demonstration-scale successes, widespread mobilization of smallholders to adopt precise N management practices remains a challenge, largely due to associated high costs and complicated sampling and calculations. Here, we propose a long-term steady-state N balance (SSNB) approach without these complications that is suitable for sustainable smallholder farming. The hypothesis underpinning the concept of SSNB is that an intensively cultivated soil-crop system with excessive N inputs and high N losses can be transformed into a steady-state system with minimal losses while maintaining high yields. Based on SSNB, we estimate the optimized N application range across 3,824 crop counties for the three staple crops in China. We evaluated SSNB first in ca. 18,000 researcher-managed on-farm trials followed by testing in on-farm trials with 13,760 smallholders who applied SSNB-optimized N rates under the guidance of local extension staff. Results showed that SSNB could significantly reduce N fertilizer use by 21 to 28% while maintaining or increasing yields by 6 to 7%, compared to current smallholder practices. The SSNB approach could become an effective tool contributing to the global N sustainability of smallholder agriculture.

Safeguarding Food Supply and Groundwater Safety for Maize Production in China.

Quantifying sustainable nitrogen (N) management at the national scale is critical for developing targeted policies and strategies to simultaneously achieve food security and groundwater protection. In this study, we report county-scale optimization scenarios for Chinese maize production and evaluate their outcomes for safeguarding food supply and groundwater safety. First, we performed random forest regression modeling to simulate in situ NO3- leaching based on a meta-analysis that integrates climate, soil, water, and N balance parameters. The NO3- leaching was then mapped for 1406 counties based on data compiled from 2.89 million farmer surveys. Average NO3- leaching during the maize growth season was estimated to be 27.6 kg N ha-1, and 56% of counties had groundwater whose nitrate concentrations exceeded drinking water safety levels during 2005-2014. The top 5% farmers in each county produced not only more grain but also greater NO3- leaching. Scenario analysis of potential management changes found that when these top producers combined optimal N management practices, national N use in Chinese maize system was reduced by 25%, from 9.1 to 6.9 Mt, while maize production increased by 6.1%. Modeled NO3- leaching was 0.58 Mt, which was 31% lower than groundwater safety levels and 53% lower than the current leaching amount. This study provides evidence that integrated crop and N management practices implemented at the county level safeguard both maize crop food security and enhance environment sustainability.