Temporal characteristics of atmospheric ammonia and nitrogen dioxide over China based on emission data, satellite observations and atmospheric transport modeling since 1980

Abstract. China is experiencing intense air pollution caused in large part by anthropogenic emissions of reactive nitrogen (N r ). Atmospheric ammonia (NH 3 ) and nitrogen dioxide (NO 2 ) are the most important precursors for N r compounds (including N 2 O 5 , HNO 3 , HONO and particulate NO 3 − and NH 4 + ) in the atmosphere. Understanding the changes in NH 3 and NO 2 has important implications for the regulation of anthropogenic N r emissions and is a requirement for assessing the consequence of environmental impacts. We conducted the temporal trend analysis of atmospheric NH 3 and NO 2 on a national scale since 1980 based on emission data (during 1980–2010), satellite observation (for NH 3 since 2008 and for NO 2 since 2005) and atmospheric chemistry transport modeling (during 2008–2015). Based on the emission data, during 1980–2010, significant continuous increasing trends in both NH 3 and NO x were observed in REAS (Regional Emission inventory in Asia, for NH 3 0.17 and for NO x 0.16 kg N ha −1 yr −2 ) and EDGAR (Emissions Database for Global Atmospheric Research, for NH 3 0.24 and for NO x 0.17 kg N ha −1 yr −2 ) over China. Based on the satellite data and atmospheric chemistry transport model (CTM) MOZART-4 (Model for Ozone and Related chemical Tracers, version 4), the NO 2 columns over China increased significantly from 2005 to 2011 and then decreased significantly from 2011 to 2015; the satellite-retrieved NH 3 columns from 2008 to 2014 increased at a rate of 2.37 % yr −1 . The decrease in NO 2 columns since 2011 may result from more stringent strategies taken to control NO x emissions during the 12th Five Year Plan, while no control policy has focused on NH 3 emissions. Our findings provided an overall insight into the temporal trends of both NO 2 and NH 3 since 1980 based on emission data, satellite observations and atmospheric transport modeling. These findings can provide a scientific background for policy makers that are attempting to control atmospheric pollution in China. Moreover, the multiple datasets used in this study have implications for estimating long-term N r deposition datasets to assess its impact on soil, forest, water and greenhouse balance.