Nitrous oxide emissions from 2008 to 2012 for agricultural lands in the conterminous United States

The soil N2O emissions data for the conterminous United States were generated by the DayCent ecosystem model using the crop and land-use histories for survey locations in the USDA-NRCS National Resources Inventory (NRI). The model also requires weather and soils data. Daily maximum/minimum temperature and precipitation data are based on gridded weather data from the PRISM Climate Data product. Soils data are obtained from Soil Survey Geographic Database (SSURGO). See Del Grosso et al. (2022) and US-EPA (2020) for more details about the simulations. Atmospheric inversions were conducted using the CarbonTracker Langrage framework (Nevison et al. 2018). These results provide total N2O fluxes for the domain using atmospheric observations and an inverse modeling, and are compared to the DayCent emissions to confirm seasonal patterns, particularly the role of freeze-thaw events in driving pulses of N2O emissions from agricultural lands.

美国本土的土壤氧化亚氮（N₂O）排放数据集由DayCent生态系统模型生成，该模型依托美国农业部-自然资源保护服务局（USDA-NRCS）国家资源清查（NRI）中调查点位的作物与土地利用历史数据运行。模型运行还需依赖气象与土壤数据：其中逐日最高、最低气温与降水数据取自PRISM气候数据产品的网格化气象资料，土壤数据则获取自土壤调查地理数据库（Soil Survey Geographic Database, SSURGO）。有关该模拟的更多细节可参见Del Grosso等人（2022）以及美国环境保护署（US-EPA, 2020）的相关研究。本研究采用CarbonTracker Langrage框架（Nevison等人，2018）开展大气反演实验，通过大气观测数据与反演模型计算得到研究区域的总氧化亚氮通量，并将其与DayCent模型的模拟排放结果进行对比，以验证其季节变化特征，尤其是冻融事件对农田土壤氧化亚氮排放脉冲的驱动作用。