2020 journal article

Characterization of the Global Sources of Atmospheric Ammonia from Agricultural Soils

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 125(3).

co-author countries: United States of America 🇺🇸
Source: Web Of Science
Added: April 6, 2020

Abstract Global ammonia (NH 3 ) emissions to the atmosphere are projected to increase in the coming years with the increased use of synthetic nitrogen fertilizers and cultivation of nitrogen‐fixing crops. A statistical model (NH 3 _STAT) is developed for characterizing atmospheric NH 3 emissions from agricultural soils and compared to the performance of other global and regional NH 3 models (e.g., Emission Database for Global Atmospheric Research, Magnitude and Seasonality of Agricultural Emissions, MIX, and U.S. Environmental Protection Agency). The statistical model was developed from a multiple linear regression between NH 3 emission and the physicochemical variables. The model was evaluated for 2012 NH 3 emissions. The results indicate that, in comparison to other data sets, the model provides a lower global NH 3 estimate by 58%, (NH 3 _STAT: 13.9 Tg N yr −1 ; Emission Database for Global Atmospheric Research: 33.0 Tg N yr −1 ). We also performed a region‐based analysis (United States, India, and China) using the NH 3 _STAT model. For the United States, our model produces an estimate that is a ~1.4 times higher in comparison to the Environmental Protection Agency. Meanwhile, the NH 3 _STAT estimate for India shows NH 3 emissions between 0.8 and 1.4 times lower when compared to other data sets. A lower estimate is also seen for China, where the model estimates NH 3 emissions 0.4 to 5 times lower than other data sets. The difference in the global estimates is attributed to the lower estimates in major agricultural countries like China and India. The statistical model captures the spatial distribution of global NH 3 emissions by utilizing a simplified approach compared to other readily available data sets. Moreover, the NH 3 _STAT model provides an opportunity to predict future NH 3 emissions in a changing world.