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.

Comprehensive assessment of the utilization of manure in China's croplands based on national farmer survey data.

China's rapid increase in mass excreta and its environmental discharge have attracted substantial attention. However, cropland as a main destination of excreta utilization has not been extensively evaluated. Here, a national survey was used to assess the utilization of manure in croplands across China. The data included the inputs of manure nitrogen (N), phosphorus (P), and potassium (K) for cereals, fruits, vegetables, and other crops, along with the manure proportion of total N, P, and K inputs at the county level. The results showed that the manure N, P, and K inputs were 6.85, 2.14, and 4.65 million tons (Mt), respectively, constituting 19.0%, 25.5%, and 31.1% of the total N, P, and K, respectively. The spatial distribution of the manure proportion of total inputs was lower in Eastern China and higher in Western China. The results provide a detailed description of the utilization of manure nutrients in agricultural areas throughout China, which will serve as basic support for policymakers and researchers involved in future agricultural nutrient management in China.

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.