The underappreciated role of nonvolatile cations on aerosol ammonium-sulfate molar ratios

Weber, R. J.

doi:10.5194/acp-2017-737

Cited by 25 publications

(41 citation statements)

References 25 publications

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“…The first two possibilities are unlikely, given the agreement of predicted ammonium and sulfate with previous studies (Park et al, 2006;Hand et al, 2012;Blanchard et al, 2013a, b;Kim et al, 2015;Saylor et al, 2015), and the relative insensitivity of pH to ammonia and sulfate Silvern et al, 2017). However, NVCs, if inappropriately distributed in PM 2.5 , can exert significant biases on pH (Meskhidze et al, 2003;Karydis et al, 2016;Guo et al, 2017b). Indeed, offline calculations of aerosol pH excluding the influence of NVCs mitigates most of the predicted positive trend of 0.6 pH units per decade when all the aerosol species are considered ( Fig.…”

Section: Model Evaluation Of Phmentioning

confidence: 69%

“…Therefore, if a model is for any reason biased in its prediction of aerosol pH, it may be preconditioned towards nitrate prediction biases. The sensitivity to pH biases is strongest when the aerosol lies in the pH sensitivity window, which is often the case for atmospheric aerosol (Guo et al, , 2017bBougiatioti et al, 2016). When below this pH sensitivity window, aerosol nitrate is almost nonexistent and relatively insensitive to emissions (and pH biases); when above the window, almost all nitrate resides in the aerosol phase and directly responds to NO x emission controls.…”

Section: Introductionmentioning

confidence: 97%

“…Reconciling the nitrate substitution paradox requires a careful examination of aerosol thermodynamics and the conditions under which nitrate partitioning to the aerosol is favored. Meskhidze et al (2003) and later Guo et al (2016) showed that, for aerosol nitrate formation to occur, aerosol pH needs to exceed a certain characteristic value (depending on the temperature and the amount of liquid water it ranges between a pH of 1.5 and 3; Guo et al, 2017b). If aerosol pH is therefore high enough (typically above a pH of 2.5 to 3), a behavior consistent with nitrate substitution emerges, because any inorganic nitrate forming from NO x chemistry mostly resides in the aerosol phase.…”

Section: Introductionmentioning

confidence: 99%

“…Although aerosol models are evaluated in terms of their ability to predict the concentration of aerosol species (including across size), no studies to date focus on their ability to predict aerosol pH across size, even though it is known to potentially vary up to 6 units (Fang et al, 2017;Bougiatioti et al, 2016;Li et al, 2017). Evaluation of models in this context is challenging, since there is no established data set of aerosol acidity -although that is rapidly changing, with pH estimates derived from a combination of observations and models (e.g., Guo et al, 2015Guo et al, , 2017bBougiatioti et al, 2016;Song et al, 2018). Furthermore, given that most of this pH variability occurs in the PM 1 to PM 2.5 range (Fang et al, 2017), it is quite likely that model assumptions on how aerosol species interact within a mode (degree of internal mixture) may lead to pH prediction biases that drive model behavior, especially for particles in the 1-2.5 µm range.…”

Section: Introductionmentioning

confidence: 99%

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Understanding nitrate formation in a world with less sulfate

et al. 2018

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Abstract. SO2 emission controls, combined with modestly increasing ammonia, have been thought to generate aerosol with significantly reduced acidity for cases in which sulfate is partially substituted by nitrate. However, neither expectation agrees with decadal observations in the southeastern USA, suggesting that a fundamentally different response of aerosol pH to emissions changes is occurring. We postulate that this nitrate substitution paradox arises from a positive bias in aerosol pH in model simulations. This bias can elevate pH to a level at which nitrate partitioning is readily promoted, leading to behavior consistent with nitrate substitution. CMAQ simulations are used to investigate this hypothesis; modeled PM2.5 pH using 2001 emissions compare favorably with pH inferred from observed species concentrations. Using 2011 emissions, however, leads to simulated pH increases of one unit, which is inconsistent with observations from that year. Nonvolatile cations (K+, Na+, Ca+2, and Mg+2) in the fine mode are found to be responsible for the erroneous predicted increase in aerosol pH of about 1 unit on average over the USA. Such an increase can induce a nitrate bias of 1–2 µg m−3, which may further increase in future projections, reaffirming an otherwise incorrect expectation of a significant nitrate substitution. Evaluation of predicted aerosol pH against thermodynamic analysis of observations is therefore a critically important, but overlooked, aspect of model evaluation for a robust emissions policy.

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Section: Model Evaluation Of Phmentioning

confidence: 69%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Understanding nitrate formation in a world with less sulfate

et al. 2018

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“…It is also assumed that the particles were internally mixed, and that pH did not vary 30 with size. Mixing state of the nonvolatile cations can also affect pH, but the effect on predicted fine particle pH is small if a minor fraction of nonvolatile sulfate is internally mixed with the nonvolatile cations (Guo et al, 2017b), however, it can add uncertainty to predicted nitric acid partitioning (discussed below). Since there is no data on the mixing state and the mass concentrations (or mole fractions) of nonvolatile cations are generally small (discussed below, 5 see Table S1), internal mixing is assumed in the following analysis.…”

Section: Thermodynamic Modelingmentioning

confidence: 99%

Effectiveness of Ammonia Reduction on Control of Fine Particle Nitrate

Guo¹,

Otjes²,

Schlag³

et al. 2018

Preprint

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Abstract. In some regions, reducing aerosol ammonium nitrate (NH 4 NO 3 ) concentrations may substantially improve air quality. This can be accomplished by reductions in precursor emissions, such as nitrogen oxides (NO x ) to lower nitric acid (HNO 3 ) that partitions to the aerosol, or reductions in ammonia (NH 3 ) to lower particle pH and keep HNO 3 in the gas phase. Using the ISORROPIA-II thermodynamic aerosol model and detailed observational datasets, we explore 25 the sensitivity of aerosol NH 4 NO 3 to gas phase NH 3 and NO x controls for a number of contrasting locations, including Europe, the US, and China. NO x control is always effective, whereas the aerosol response to NH 3 control is highly nonlinear and only becomes effective at a thermodynamic "sweet spot". The analysis provides a conceptual framework and fundamental evaluation on the relative value of NO x versus NH 3 control. We find that regardless of the 30 locations examined, it is only when ambient particle pH drops below approximately 3 that NH 3 reduction leads to an effective response in PM 2.5 mass. The required amount of NH 3 reduction to efficiently decrease NH 4 NO 3 at different sites is assessed. Owing to the linkage between NH 3 emissions and agricultural productivity, substantial NH 3 reduction required in some locations

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Simulation of airborne trace metals in fine particulate matter over North America

Martin

Henderson

et al. 2019

Atmospheric Environment

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Trace metal distributions are of relevance to understand sources of fine particulate matter (PM 2.5 ), PM 2.5 -related health effects, and atmospheric chemistry. However, knowledge of trace metal distributions is lacking due to limited ground-based measurements and model simulations. This study develops a simulation of 12 trace metal concentrations (Si, Ca, Al, Fe, Ti, Mn, K, Mg, As, Cd, Ni and Pb) over continental North America for 2013 using the GEOS-Chem chemical transport model. Evaluation of modeled trace metal concentrations with observations indicates a spatial consistency within a factor of 2, an improvement over previous studies that were within a factor of 3-6. The spatial distribution of trace metal concentrations reflects their primary emission sources. Crustal element (Si, Ca, Al, Fe, Ti, Mn, K) concentrations are enhanced over the central US from anthropogenic fugitive dust and over the southwestern U.S. due to natural mineral dust. Heavy metal (As, Cd, Ni and Pb) concentrations are high over the eastern U.S. from industry. K is abundance in the southeast from biomass burning and high concentrations of Mg is observed along the coast from sea spray. The spatial pattern of PM 2.5 mass is most strongly correlated with Pb, Ni, As and K due to their signature emission sources. Challenges remain in accurately simulating observed trace metal concentrations. Halving anthropogenic fugitive dust emissions in the 2011 National Air Toxic Assessment (NATA) inventory and doubling natural dust emissions in the default GEOS-Chem simulation was necessary to reduce biases in crustal element concentrations. A fivefold increase of anthropogenic emissions of As and Pb was necessary in the NATA inventory to reduce the national-scale bias versus observations by more than 80 %, potentially reflecting missing sources.

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The underappreciated role of nonvolatile cations on aerosol ammonium-sulfate molar ratios

Cited by 25 publications

References 25 publications

Understanding nitrate formation in a world with less sulfate

Understanding nitrate formation in a world with less sulfate

Effectiveness of Ammonia Reduction on Control of Fine Particle Nitrate

Simulation of airborne trace metals in fine particulate matter over North America

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