Estimating NH.sub.3 emissions from agricultural fertilizer application in China using the bi-directional CMAQ model coupled to an agro-ecosystem model

Atmospheric ammonia (NH.sub.3) plays an important role in atmospheric aerosol chemistry. China is one of the largest NH.sub.3 emitting countries with the majority of NH.sub.3 emissions coming from agricultural practices, such as fertilizer application and livestock production. The current NH.sub.3 emission estimates in China are mainly based on pre-defined emission factors that lack temporal or spatial details, which are needed to accurately predict NH.sub.3 emissions. This study provides the first online estimate of NH.sub.3 emissions from agricultural fertilizer application in China, using an agricultural fertilizer modeling system which couples a regional air quality model (the Community Multi-scale Air Quality model, or CMAQ) and an agro-ecosystem model (the Environmental Policy Integrated Climate model, or EPIC). This method improves the spatial and temporal resolution of NH.sub.3 emissions from this sector. We combined the cropland area data of 14 crops from 2710 counties with the Moderate Resolution Imaging Spectroradiometer (MODIS) land use data to determine the crop distribution. The fertilizer application rates and methods for different crops were collected at provincial or agricultural region levels. The EPIC outputs of daily fertilizer application and soil characteristics were input into the CMAQ model and the hourly NH.sub.3 emissions were calculated online with CMAQ running. The estimated agricultural fertilizer NH.sub.3 emissions in this study were approximately 3 Tg in 2011. The regions with the highest modeled emission rates are located in the North China Plain. Seasonally, peak ammonia emissions occur from April to July. Compared with previous researches, this study considers an increased number of influencing factors, such as meteorological fields, soil and fertilizer application, and provides improved NH.sub.3 emissions with higher spatial and temporal resolution.