Rayleigh based concept to track NOx emission sources in urban areas of China.

Schematic of the nitrate evolution with the sampling days during haze period (A), which was controlled by the Rayleigh fractionation model (B). • The δ15N-NO 3 - values of PM 2.5 in Beijing-Tianjin-Shijiazhuang ranged from -3.1‰ to +11.4 ‰. • Rayleigh fractionation model was used to track NO x emission sources. • δ15N-NO 3 - and the corresponding p-NO 3 - were negatively correlated during the haze period. • Non-fossil NO x and fossil NO x contributed equally to NO 30 - in PM 2.5. Despite the implementation of some effective measures to control emissions of nitrogen oxides (NO x = NO + NO 2) in recent years, the ambient NO x concentration in urban cities of China remains high. Therefore, a quantitative understanding of NO x emission sources is critical to developing effective mediation policies. In the present study, the dual isotopic compositions of nitrate (p -NO 3 −) in fine-particle aerosol (PM 2.5) collected daily at a regional scale (Beijing-Tianjin-Shijiazhuang) were measured to better constrain the NO x emission sources. The specific focus was on a typical haze episode that occurred simultaneously in the three urban cities (October 22–29, 2017). It was found that the nitrogen isotopic values of nitrate in PM 2.5 (hereafter as δ15N-NO 3 −) ranged widely from −3.1‰ to + 11.4‰, with a mean value of 3.5 ± 3.7‰. Furthermore, a negative relationship between the δ15N-NO 3 − values and the corresponded p -NO 3 − concentrations during the haze period was observed. This implied the preferential formation of 15N-enriched NO 3 − into a fine-particle aerosol. Taking a different approach to previous publications, the Rayleigh fractionation model was used to characterize the initial isotopic signatures of ambient NO x. After accounting for the δ15N difference between p -NO 3 − and the source NO x , the estimated initial δ15N-NO x ranged from −20‰ to 0‰, which indicated a cosniderable contribution of non-fossil fuel emissions. The individual contributions of potential sources were further quantified using the Bayesian mixing model, revealing that NO x from coal or natural gas combustion, vehicle exhausts, biomass burning, and the microbial activity contributed 17.9 ± 11.4%, 29.4 ± 19.6%, 29.1 ± 18.9% and 23.5 ± 12.7% to NO 3 − in PM 2.5 , respectively. These results highlighted that tightening controls of gaseous NO x emissions from non-fossil sources may represent an opportunity to mitigate PM 2.5 pollution in urban cities of China. [ABSTRACT FROM AUTHOR]