Implementation of a dynamical NH3 emissions parameterization in CMAQ for improving PM2.5 simulation in Taiwan

Abstract Ammonia (NH3) is an important precursor of inorganic fine particulate matter (PM2.5). Without specific information on the temporal variation in NH3 emissions, a simplified temporal variation in NH3 emissions is often used in chemical transport models. To better characterize NH3 emissions in an air quality model simulation for Taiwan, a dynamical NH3 emissions parameterization was applied to improve the temporal profile of NH3 emissions from livestock operations, synthetic nitrogen fertilizers, and standing crops. The Community Multiscale Air Quality (CMAQ) modeling simulation with a fixed NH3 emissions rate (the CONST experiment) presents a large positive bias in simulated nitrate and NH3, particularly during the nighttime and winter months. On the other hand, the CMAQ simulation with a dynamical NH3 emissions approach (the DYN experiment) improves the diurnal and seasonal variations and reduces the simulated bias. Moreover, according to the Taiwan emissions inventory, NH3 emissions from sewage accounts for a large portion (37%) of total NH3 emissions in Taiwan. The CMAQ simulation with the dynamical NH3 emissions approach and with a reduced level of NH3 emissions from sewage (the DYN1 experiment) was conducted to assess the possibility that the existing Taiwan emissions inventory may overestimate sewage NH3 emissions. The evaluations with observed NH3, nitrate, and ammonium wet deposition concentrations indicate that the DYN1 experiment performs better than the CONST and DYN experiments.