Isotopic Analysis of NH4+ Collected Using Active Samplers: Insights from Urban Beijing Field Measurements

Active collection methods such as ChemComb Speciation Cartridge samplers (CCSCs) are considered more accurate for determining the isotopic composition of ammonia (NH) and particulate ammonium (NH) (i.e., δN(NH) and δN(NH)), especially in ambient air. However, the discrepancy in δN(NH) values are unknown between speciated particle samples collected using lab-verified CCSCs with different filter types (Teflon, cellulose, and glass fiber) and particles samples collected separately without gas-particle speciation and a backup/breakthrough filter. In this study, we deployed two CCSCs to collect speciated NH, and an EPA-approved Spiral Ambient Speciated Sampler (SASS) side-by-side to collect ambient NH and to compare their δN(NH) values in urban Beijing during summer 2019. The initial δN(NH) values were derived from δN(NH) values for speciated NH based on theoretical estimation of isotopic fractionation that could occur during NH gas-to-particle conversion, or field-based isotopic fractionation, measured δN(NH) values and observed NH partitioning during NH and NH speciation. The results show that the mean δN(NH) values retained in Teflon filters were 10.2 ± 8.4‰ (n=7) and 12.4 ± 4.1‰ (n=7) for CCSCs A and CCSCs B, respectively. In contrast, the measured δN(NH) values in SASS quartz filters were 15.9 ± 2.5‰ (n=7). The higher δN(NH) values observed in particle samples collected using SASS can be attributed to a positive bias resulting from NH volatilization. Additionally, this study revealed that the initial δN(NH) values, derived using theoretically derived isotopic fractionation, were 5.6‰ and 10.1‰ lower compared to the initial δN(NH) values derived using field-based isotopic fractionation in CCSCs A and B, respectively. These findings underscore the significance of using acid-coated backup filters in active sampling systems to effectively capture volatilized NH. Additionally, they highlight the necessity of utilizing field-based isotopic fractionation to accurately predict initial δN(NH) values, thereby reducing uncertainties in source apportionment of NH in ambient air. This approach is essential for obtaining reliable isotopic data for understanding the sources and processes contributing to NH in the atmosphere.