Temporally resolved ammonia emission inventories: Current estimates, evaluation tools, and measurement needs

Abstract

We evaluate the suitability of a three‐dimensional chemical transport model (CTM) as a tool for assessing ammonia emission inventories, calculate the improvement in CTM performance owing to recent advances in temporally varying ammonia emission estimates, and identify the observational data necessary to improve future ammonia emission estimates. We evaluate two advanced approaches to estimating the temporal variation in ammonia emissions: a process‐based approach and an inverse‐modeled approach. These inventories are used as inputs to a three‐dimensional CTM, PMCAM x . The model predictions of aerosol NH 4 + concentration, NH x (NH x ≡ NH 3 + NH 4 + ) concentration, wet‐deposited NH 4 + mass flux, and NH 4 + precipitation concentration are compared with observations. However, it should be cautioned that errors in model inputs other than the ammonia emissions may bias such comparisons. We estimate the robustness of each of these amodel‐measurement comparisons as the ratio of the sensitivity to changes in emissions over the sensitivity to errors in the CTM inputs other than the ammonia emission inventory. We find the NH x concentration to be the only indicator that is sufficiently robust during all time periods. Using this as an indicator, the ammonia emission inventories with diurnal and seasonal variation improve the PMCAM x predictions in the summer and winter. In the United States, future efforts to improve the spatial and temporal accuracy of ammonia emission inventories are limited by a lack of a long‐term, widespread network of highly time‐resolved NH x measurements.