Abstract. Air quality models have not been able to reproduce the magnitude of the observed concentrations of fine particulate matter (PM2.5) during wintertime Chinese haze events. The discrepancy has been at least partly attributed to low biases in modeled sulfate production rates, due to the lack of heterogeneous sulfate production on aerosols in the models. In this study, we explicitly implement four heterogeneous sulfate formation mechanisms into a regional chemical transport model, in addition to gas-phase and in-cloud sulfate production. We compare the model results with observations of sulfate concentrations and oxygen isotopes, Δ17O(SO42-), in the winter of 2014–2015, the latter of which is highly sensitive to the relative importance of different sulfate production mechanisms. Model results suggest that heterogeneous sulfate production on aerosols accounts for about 20 % of sulfate production in clean and polluted conditions, partially reducing the modeled low bias in sulfate concentrations. Model sensitivity studies in comparison with the Δ17O(SO42-) observations suggest that heterogeneous sulfate formation is dominated by transition metal ion-catalyzed oxidation of SO2.

Abstract. Discerning mechanisms of sulfate formation during fine-particle pollution (referred to as haze hereafter) in Beijing is important for understanding the rapid evolution of haze and for developing cost-effective air pollution mitigation strategies. Here we present observations of the oxygen-17 excess of PM 2.5 sulfate ( 17 O(SO 2− 4 )) collected in Beijing haze from October 2014 to January 2015 to constrain possible sulfate formation pathways. Throughout the sampling campaign, the 12-hourly averaged PM 2.5 concentrations ranged from 16 to 323 µg m −3 with a mean of (141 ± 88 (1σ )) µg m −3 , with SO Our estimate suggested that in-cloud reactions dominated sulfate production on polluted days (PDs, PM 2.5 ≥ 75 µg m −3 ) of Case II in October 2014 due to the relatively high cloud liquid water content, with a fractional contribution of up to 68 %. During PDs of Cases I and III-V, heterogeneous sulfate production (P het ) was estimated to contribute 41-54 % to total sulfate formation with a mean of (48 ± 5) %. For the specific mechanisms of heterogeneous oxidation of SO 2 , chemical reaction kinetics calculations suggested S(IV) (= SO 2 q H 2 O + HSO − 3 + SO 2− 3 ) oxidation by H 2 O 2 in aerosol water accounted for 5-13 % of P het . The relative importance of heterogeneous sulfate production by other mechanisms was constrained by our observed 17 O(SO 2− 4 ). Heterogeneous sulfate production via S(IV) oxidation by O 3 was estimated to contribute 21-22 % of P het on average. Heterogeneous sulfate production pathways that result in zero-17 O(SO 2− 4 ), such as S(IV) oxidation by NO 2 in aerosol water and/or by O 2 via a radical chain mechanism, contributed the remaining 66-73 % of P het . The assumption about the thermodynamic state of aerosols (stable or metastable) was found to significantly influence the calculated aerosol pH (7.6 ± 0.1 or 4.7 ± 1.1, respectively), and thus influence the relative importance of heterogeneous sulfate production via S(IV) oxidation by NO 2 and by O 2 . Our local atmospheric conditions-based calculations suggest sulfate formation via NO 2 oxidation can be the dominant pathway in aerosols at high-pH conditions calculated assuming stable state while S(IV) oxidation by O 2 can be the dominant pathway providing that highly acidic aerosols (pH ≤ 3) exist. Our local atmospheric-conditions-based calculations illustrate the utility of 17 O(SO 2− 4 ) for quantifying sulfate forPublished by Copernicus Publications on behalf of the European Geosciences Union. 5516 P. He et al.: Isotopic constraints on heterogeneous sulfate production in Beijing haze mation pathways, but this estimate may be further improved with future regional modeling work.

Abstract. The rapid mass increase of atmospheric nitrate is a critical driving force for the occurrence of fine-particle pollution (referred to as haze hereafter) in Beijing. However, the exact mechanisms for this rapid increase of nitrate mass have not been well constrained from field observations. Here we present the first observations of the oxygen-17 excess of atmospheric nitrate (Δ17O(NO3-)) collected in Beijing haze to reveal the relative importance of different nitrate formation pathways, and we also present the simultaneously observed δ15N(NO3-). During our sampling period, 12 h averaged mass concentrations of PM2.5 varied from 16 to 323 µg m−3 with a mean of (141±88(1SD)) µg m−3, with nitrate ranging from 0.3 to 106.7 µg m−3. The observed Δ17O(NO3-) ranged from 27.5 ‰ to 33.9 ‰ with a mean of (30.6±1.8) ‰, while δ15N(NO3-) ranged from −2.5 ‰ to 19.2 ‰ with a mean of (7.4±6.8) ‰. Δ17O(NO3-)-constrained calculations suggest nocturnal pathways (N2O5+H2O/Cl- and NO3+HC) dominated nitrate production during polluted days (PM2.5≥75 µg m−3), with a mean possible fraction of 56–97 %. Our results illustrate the potentiality of Δ17O in tracing nitrate formation pathways; future modeling work with the constraint of isotope data reported here may further improve our understanding of the nitrogen cycle during haze.

Studies of wintertime air quality in the North China Plain (NCP) show that particulate‐nitrate pollution persists despite rapid reduction in NOx emissions. This intriguing NOx‐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 NOy chemistry and [PM2.5] 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 [Ox,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‐NOx‐high‐PM2.5 conditions. Nitrate production rates may continue to increase as long as [O3] increases despite reduction in [NOx], creating a negative feedback that reduces the effectiveness of air pollution mitigation.

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