Isotope-based source apportionment of nitrogen-containing aerosols: A case study in an industrial city in China

Due to the local emissions and transportations of air pollution from the most polluted regions such as the North China Plain and Yangtze Delta metropolitan, Xuzhou is becoming one of the most polluted cities in East China. The sources and formation processes of nitrogen-containing aerosols are therefore very complex. Two continuous aerosol measurement campaigns were conducted in this industrial city during the wintertime and summertime of 2016, to investigate the chemical compositions and potential sources of total nitrogen (TN, including 89% inorganic nitrogen and 11% organic nitrogen) in PM_2.5. Abrupt enhancements of nitrogen-containing aerosols (e.g., NO₃^- and NH₄⁺) were found in the winter, and nitrate became as a dominant contributor in high pollution days (e.g., PM_2.5 > 150 μg m^-3). Nitrogen oxidation ratios (NOR) correlated significantly with aerosol liquid water content (ALWC), which was estimated by ISORPROPIA-II model. This suggested heterogeneous process might be an important pathway in nitrate formation during the high PM_2.5 days. The nitrogen isotope composition (δ¹⁵N) in TN varied from -1.3 to +13.2‰ with a mean value of 6.9 ± 3.6‰ during the wintertime. An isotope-based source apportionment approach was then developed using a Bayesian isotope mixing model (SIAR) with chemical compositions as an important constrain, which improved accuracy and reduced the overall uncertainties in estimations of TN sources. From this optimized model, we identified six major sources including NH₃ from combustion-related emissions (49%), NH₃ derived from animal wastes (6%), NH₃ from urban volatilization (3%), NO_x derived from coal combustion (33%), NO_x from biomass burning (5%) and NO_x from vehicles (3%). Our results demonstrated that ambient NO_x was dominated by coal combustion. Since NO_x and NH₃ are important precursors for ammonium nitrate aerosols, controlling of combustion related NO_x and NH₃ emissions might be an important way to reduce PM_2.5 levels in this region.