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Data-driven estimation of nitric oxide emissions from global soils based on dominant vegetation covers
Authors:Xingshuai Tian  Yulong Yin  Kai He  Ruonan Qiu  Jiahui Cong  Zihan Wang  Huitong Yu  Zhong Chen  Yiyan Chu  Hao Ying  Zhenling Cui
Institution:1. College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China;2. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Abstract: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.
Keywords:background nitric oxide emissions  data-driven models  dominate vegetation covers  global soils  impact factors  soil nitric oxide emissions
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