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Abstract Atmospheric gaseous elemental mercury (GEM) concentrations in the Arctic exhibit a clear summertime maximum, while the origin of this peak is still a matter of debate in the community. Based on summertime observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and a modeling approach, we further investigate the sources of atmospheric Hg in the central Arctic. Simulations with a generalized additive model (GAM) show that long-range transport of anthropogenic and terrestrial Hg from lower latitudes is a minor contribution (~2%), and more than 50% of the explained GEM variability is caused by oceanic evasion. A potential source contribution function (PSCF) analysis further shows that oceanic evasion is not significant throughout the ice-covered central Arctic Ocean but mainly occurs in the Marginal Ice Zone (MIZ) due to the specific environmental conditions in that region. Our results suggest that this regional process could be the leading contributor to the observed summertime GEM maximum. In the context of rapid Arctic warming and the observed increase in width of the MIZ, oceanic Hg evasion may become more significant and strengthen the role of the central Arctic Ocean as a summertime source of atmospheric Hg. 

Abstract. Air quality models have not been able to reproduce the magnitude of theobserved concentrations of fine particulate matter (PM2.5) duringwintertime Chinese haze events. The discrepancy has been at least partlyattributed to low biases in modeled sulfate production rates, due to the lackof heterogeneous sulfate production on aerosolsin the models. In this study, we explicitly implement four heterogeneous sulfate formationmechanisms into a regional chemical transport model, in addition togas-phase and in-cloud sulfate production. We compare the model results withobservations of sulfate concentrations and oxygen isotopes, Δ17O(SO42-), in the winter of 2014–2015, the latter of whichis highly sensitive to the relative importance of different sulfateproduction mechanisms. Model results suggest that heterogeneous sulfateproduction on aerosols accounts for about 20 % of sulfate production inclean and polluted conditions, partially reducing the modeled low bias insulfate concentrations. Model sensitivity studies in comparison with theΔ17O(SO42-) observations suggest that heterogeneoussulfate 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 (Δ¹⁷O(SO₄²⁻)) 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 323µg m⁻³ with a mean of (141  ±  88 (1σ))µg m⁻³, with SO₄²⁻ representing 8–25% of PM_2.5 mass. The observed Δ¹⁷O(SO₄²⁻) varied from 0.1 to 1.6‰ with a mean of (0.9  ±  0.3)‰. Δ¹⁷O(SO₄²⁻) increased with PM_2.5 levels in October 2014 while the opposite trend was observed from November 2014 to January 2015. Our estimate suggested that in-cloud reactions dominated sulfate production on polluted days (PDs, PM_2.5  ≥  75µg 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 SO₂, chemical reaction kinetics calculations suggested S(IV) ( = SO₂ ⚫H₂O+HSO₃⁻  +  SO₃²⁻) oxidation by H₂O₂ 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 Δ¹⁷O(SO₄²⁻). Heterogeneous sulfate production via S(IV) oxidation by O₃ was estimated to contribute 21–22% of P_het on average. Heterogeneous sulfate production pathways that result in zero-Δ¹⁷O(SO₄²⁻), such as S(IV) oxidation by NO₂ in aerosol water and/or by O₂ 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 NO₂ and by O₂. Our local atmospheric conditions-based calculations suggest sulfate formation via NO₂ oxidation can be the dominant pathway in aerosols at high-pH conditions calculated assuming stable state while S(IV) oxidation by O₂ can be the dominant pathway providing that highly acidic aerosols (pH ≤ 3) exist. Our local atmospheric-conditions-based calculations illustrate the utility of Δ¹⁷O(SO₄²⁻) for quantifying sulfate formation pathways, but this estimate may be further improved with future regional modeling work.

 

With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic. 

Studies of wintertime air quality in the North China Plain (NCP) show that particulate‐nitrate pollution persists despite rapid reduction in NO_xemissions. 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 of¹⁷O 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_ychemistry 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 O₃concentrations. Our findings highlight a need to address uncertainties related to heterogeneous chemistry of NO₂in air‐quality models. The combined assessment of observations and model results suggest that N₂O₅uptake 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_2.5conditions. 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.