Evaluating ammonia (NH3) predictions in the NOAA National Air Quality Forecast Capability (NAQFC) using in situ aircraft, ground-level, and satellite measurements from the DISCOVER-AQ Colorado campaign

Abstract

The U.S. National Oceanic and Atmospheric Administration (NOAA) is responsible for forecasting elevated levels of air pollution within the National Air Quality Forecast Capability (NAQFC). The current research uses measurements gathered in the DISCOVER-AQ Colorado field campaign and the concurrent Front Range Air Pollution and Photochemistry Experiment (FRAPPE) to test performance of the NAQFC CMAQ modeling framework for predicting NH3. The DISCOVER-AQ and FRAPPE field campaigns were carried out in July and August 2014 in Northeast Colorado. Model predictions are compared with measurements of NH3 gas concentrations and the NH4+ component of fine particulate matter concentrations measured directly by the aircraft in flight. We also compare CMAQ predictions with NH3 measurements from ground-based monitors within the DISCOVER-AQ Colorado geographic domain, and from the Tropospheric Emission Spectrometer (TES) on the Aura satellite.In situ aircraft measurements carried out in July and August of 2014 suggest that the NAQFC CMAQ model underestimated the NH3 concentration in Northeastern Colorado by a factor of ∼2.7 (NMB = −63%). Ground-level monitors also produced a similar result. Average satellite-retrieved NH3 levels also exceeded model predictions by a factor of 1.5–4.2 (NMB = −33 to −76%). The underestimation of NH3 was not accompanied by an underestimation of particulate NH4+, which is further controlled by factors including acid availability, removal rate, and gas-particle partition. The average measured concentration of NH4+ was close to the average predication (NMB = +18%).Seasonal patterns measured at an AMoN site in the region suggest that the underestimation of NH3 is not due to the seasonal allocation of emissions, but to the overall annual emissions estimate. The underestimation of NH3 varied across the study domain, with the largest differences occurring in a region of intensive agriculture near Greeley, Colorado, and in the vicinity of Denver. The NAQFC modeling framework did not include a recently developed bidirectional flux algorithm for NH3, which has shown to considerably improve NH3 modeling in agricultural regions. The bidirectional flux algorithm, however, is not expected to obtain the magnitude of this increase sufficient to overcome the underestimation of NH3 found in this study. Our results suggest that further improvement of the emission inventories and modeling approaches are required to reduce the bias in NAQFC NH3 modeling predictions.