Heterogeneous Nitrate Production Mechanisms in Intense Haze Events in the North China Plain

Studies of wintertime air quality in the North China Plain (NCP) show that particulate-nitrate pollution persists despite rapid reduction in NO_x emissions. This intriguing NO_x-nitrate relationship may originate from non-linear nitrate-formation chemistry, but it is unclear which feedback mechanisms dominate in NCP. In this study, we re-interpret the wintertime observations of ¹⁷O excess of nitrate (∆¹⁷O(NO₃⁻)) in Beijing using the GEOS-Chem (GC) chemical transport model to estimate the importance of various nitrate-production pathways and how their contributions change with the intensity of haze events. We also analyze the relationships between other metrics of NO_y chemistry and [PM_2.5] in observations and model simulations. We find that the model on average has a negative bias of −0.9‰ and −36% for ∆¹⁷O(NO₃⁻) and [O_x,major] (≡ [O₃] + [NO₂] + [p-NO₃⁻]), respectively, while overestimating the nitrogen oxidation ratio ([NO₃⁻]/([NO₃⁻] + [NO₂])) by +0.12 in intense haze. The discrepancies become larger in more intense haze. We attribute the model biases to an overestimate of NO₂-uptake on aerosols and an underestimate in wintertime O₃ concentrations. Our findings highlight a need to address uncertainties related to heterogeneous chemistry of NO₂ in air-quality models. The combined assessment of observations and model results suggest that N₂O₅ uptake in aerosols and clouds is the dominant nitrate-production pathway in wintertime Beijing, but its rate is limited by ozone under high-NO_x-high-PM_2.5 conditions. Nitrate production rates may continue to increase as long as [O₃] increases despite reduction in [NO_x], creating a negative feedback that reduces the effectiveness of air pollution mitigation.