Abstract. Particle water and pH are predicted using meteorological observations (relative humidity (RH), temperature (T)), gas/particle composition, and thermodynamic modeling (ISORROPIA-II). A comprehensive uncertainty analysis is included, and the model is validated. We investigate mass concentrations of particle water and related particle pH for ambient fine-mode aerosols sampled in a relatively remote Alabama forest during the Southern Oxidant and Aerosol Study (SOAS) in summer and at various sites in the southeastern US during different seasons, as part of the Southeastern Center for Air Pollution and Epidemiology (SCAPE) study. Particle water and pH are closely linked; pH is a measure of the particle H+ aqueous concentration and depends on both the presence of ions and amount of particle liquid water. Levels of particle water, in turn, are determined through water uptake by both the ionic species and organic compounds. Thermodynamic calculations based on measured ion concentrations can predict both pH and liquid water but may be biased since contributions of organic species to liquid water are not considered. In this study, contributions of both the inorganic and organic fractions to aerosol liquid water were considered, and predictions were in good agreement with measured liquid water based on differences in ambient and dry light scattering coefficients (prediction vs. measurement: slope = 0.91, intercept = 0.5 μg m−3, R2 = 0.75). ISORROPIA-II predictions were confirmed by good agreement between predicted and measured ammonia concentrations (slope = 1.07, intercept = −0.12 μg m−3, R2 = 0.76). Based on this study, organic species on average contributed 35% to the total water, with a substantially higher contribution (50%) at night. However, not including contributions of organic water had a minor effect on pH (changes pH by 0.15 to 0.23 units), suggesting that predicted pH without consideration of organic water could be sufficient for the purposes of aqueous secondary organic aerosol (SOA) chemistry. The mean pH predicted in the Alabama forest (SOAS) was 0.94 ± 0.59 (median 0.93). pH diurnal trends followed liquid water and were driven mainly by variability in RH; during SOAS nighttime pH was near 1.5, while daytime pH was near 0.5. pH ranged from 0.5 to 2 in summer and 1 to 3 in the winter at other sites. The systematically low pH levels in the southeast may have important ramifications, such as significantly influencing acid-catalyzed reactions, gas–aerosol partitioning, and mobilization of redox metals and minerals. Particle ion balances or molar ratios, often used to infer pH, do not consider the dissociation state of individual ions or particle liquid water levels and do not correlate with particle pH.

Isoprene significantly contributes to organic aerosol in the southeastern United States where biogenic hydrocarbons mix with anthropogenic emissions. In this work, the Community Multiscale Air Quality model is updated to predict isoprene aerosol from epoxides produced under both high- and low-NOx conditions. The new aqueous aerosol pathways allow for explicit predictions of two key isoprene-derived species, 2-methyltetrols and 2-methylglyceric acid, that are more consistent with observations than estimates based on semivolatile partitioning. The new mechanism represents a significant source of organic carbon in the lower 2 km of the atmosphere and captures the abundance of 2-methyltetrols relative to organosulfates during the simulation period. For the parametrization considered here, a 25% reduction in SOx emissions effectively reduces isoprene aerosol, while a similar reduction in NOx leads to small increases in isoprene aerosol.

Several models were used to describe the partitioning of ammonia, water, and organic compounds between the gas and particle phases for conditions in the southeastern US during summer 2013. Existing equilibrium models and frameworks were found to be sufficient, although additional improvements in terms of estimating pure-species vapor pressures are needed. Thermodynamic model predictions were consistent, to first order, with a molar ratio of ammonium to sulfate of approximately 1.6 to 1.8 (ratio of ammonium to 2× sulfate, RN/2S ≈ 0.8 to 0.9) with approximately 70% of total ammonia and ammonium (NHx) in the particle. Southeastern Aerosol Research and Characterization Network (SEARCH) gas and aerosol and Southern Oxidant and Aerosol Study (SOAS) Monitor for AeRosols and Gases in Ambient air (MARGA) aerosol measurements were consistent with these conditions. CMAQv5.2 regional chemical transport model predictions did not reflect these conditions due to a factor of 3 overestimate of the nonvolatile cations. In addition, gas-phase ammonia was overestimated in the CMAQ model leading to an even lower fraction of total ammonia in the particle. Chemical Speciation Network (CSN) and aerosol mass spectrometer (AMS) measurements indicated less ammonium per sulfate than SEARCH and MARGA measurements and were inconsistent with thermodynamic model predictions. Organic compounds were predicted to be present to some extent in the same phase as inorganic constituents, modifying their activity and resulting in a decrease in [H+]air (H+ in μgm−3 air), increase in ammonia partitioning to the gas phase, and increase in pH compared to complete organic vs. inorganic liquid–liquid phase separation. In addition, accounting for nonideal mixing modified the pH such that a fully interactive inorganic–organic system had a pH roughly 0.7 units higher than predicted using traditional methods (pH = 1.5 vs. 0.7). Particle-phase interactions of organic and inorganic compounds were found to increase partitioning towards the particle phase (vs. gas phase) for highly oxygenated (O : C≥0.6) compounds including several isoprene-derived tracers as well as levoglu-cosan but decrease particle-phase partitioning for low O: C, monoterpene-derived species.

We quantify the source contributions to surface PM2.5 (fine particulate matter) pollution over North China from January 2013 to 2015 using the GEOS-Chem chemical transport model and its adjoint with improved model horizontal resolution (1/4°× 5/16°) and aqueous-phase chemistry for sulfate production. The adjoint method attributes the PM2.5 pollution to emissions from different source sectors and chemical species at the model resolution. Wintertime surface PM2.5 over Beijing is contributed by emissions of organic carbon (27% of the total source contribution), anthropogenic fine dust (27%), and SO 2 (14%), which are mainly from residential and industrial sources, followed by NH 3 (13%) primarily from agricultural activities. About half of the Beijing pollution originates from sources outside of the city municipality. Adjoint analyses for other cities in North China all show significant regional pollution transport, supporting a joint regional control policy for effectively mitigating the PM2.5 air pollution. use the nested-grid GEOS-Chem CTM and its adjoint model with a horizontal resolution of 1/4°× 5/16°to examine the sources of PM2.5 pollution over North China, and we interpret the source attribution results based on emission sectors, chemical species, and local versus regional transport influences.

Abstract. Bidirectional air-surface exchange of ammonia (NH 3 ) has been neglected in many air quality models. In this study, we implement the bidirectional exchange of NH 3 in the GEOS-Chem global chemical transport model. We also introduce an updated diurnal variability scheme for NH 3 livestock emissions and evaluate the recently developed MASAGE_NH 3 bottom-up inventory. While updated diurnal variability improves comparison of modeled-to-hourly in situ measurements in the southeastern USA, NH 3 concentrations decrease throughout the globe, up to 17 ppb in India and southeastern China, with corresponding decreases in aerosol nitrate by up to 7 µg m −3 . The ammonium (NH + 4 ) soil pool in the bidirectional exchange model largely extends the NH 3 lifetime in the atmosphere. Including bidirectional exchange generally increases NH 3 gross emissions (7.1 %) and surface concentrations (up to 3.9 ppb) throughout the globe in July, except in India and southeastern China. In April and October, it decreases NH 3 gross emissions in the Northern Hemisphere (e.g., 43.6 % in April in China) and increases NH 3 gross emissions in the Southern Hemisphere. Bidirectional exchange does not largely impact NH + 4 wet deposition overall. While bidirectional exchange is fundamentally a better representation of NH 3 emissions from fertilizers, emissions from primary sources are still underestimated and thus significant model biases remain when compared to in situ measurements in the USA. The adjoint of bidirectional exchange has also been developed for the GEOS-Chem model and is used to investigate the sensitivity of NH 3 concentrations with respect to soil pH and fertilizer application rate. This study thus lays the groundwork for future inverse modeling studies to more directly constrain these physical processes rather than tuning bulk unidirectional NH 3 emissions.

Water is a ubiquitous and abundant component of atmospheric aerosols. It influences light scattering, the hydrological cycle, atmospheric chemistry, and secondary particulate matter (PM) formation. Despite the critical importance of aerosol liquid water, mass concentrations are not well-known. Using speciated ion and meteorological data from the Southeastern Aerosol Research and Characterization network, we employ the thermodynamic model ISORROPIAv2.1 to estimate water mass concentrations and evaluate trends from 2001 to 2012 in urban and rural locations. The purpose of this study is to better understand the historical trends of aerosol liquid water in the southeast U.S. in the context of improved air quality and recently noted reductions in particulate organic carbon (OC). Aerosol water mass concentrations decrease by ∼79% from 2001 to 2012 in the region. Decreases are more prominent in rural than in urban areas. Fractional contribution of water to PM also decreases during the same time period, and this is consistent with recently noted improvements in visibility. These findings agree with the hypotheses that aerosol liquid water facilitates formation of biogenic secondary organic aerosol (SOA) and that biogenically derived SOA is modulated in the presence of anthropogenic perturbations.

Abstract. Particle water and pH are predicted using thermodynamic modeling (with ISORROPIA-II), meteorological observations (RH, T), and gas/particle composition. A comprehensive uncertainty analysis is included and the model validated with ammonia partitioning. The method is applied to predict mass concentrations of particle water and related particle pH for ambient fine mode aerosols sampled in a relatively remote Alabama forest during the Southern Oxidant and Aerosol Study (SOAS) in summer, and at various sites in the southeastern US, during different seasons, as part of the Southeastern Center for Air Pollution and Epidemiology (SCAPE) study. Particle water and pH are closely linked; pH is a measure of the particle H+ aqueous concentration, and so depends on both the presence of ions and amount of particle liquid water. Levels of particle water, in-turn, are determined through water uptake by both the ionic species and organic compounds. Particle ion balances, often used to infer pH, do not consider either the dissociation state of individual ions, nor particle liquid water levels and so do not necessarily correlate with particle pH. Thermodynamic calculations based on measured ion concentrations can predict both pH and liquid water, but do not consider contributions of organic species to liquid water and so may also be biased. In this study, contributions of both inorganic and organic fractions to aerosol liquid water were considered and predictions were in good agreement with measured liquid water based on differences in ambient and dry light scattering coefficients (prediction vs. measurement: slope = 0.91, intercept = 0.45 μg m−3, R = 0.87). ISORROPIA-II predictions were evaluated by reproducing the observed gas-particle partitioning of NH3. Based on this study, organic species on average contributed 35% to the total water, with a substantially higher contribution (63%) at night. The mean pH predicted in the Alabama forest (SOAS) was 0.94 ± 0.59 (median 0.93). Not including contributions of organic water has a minor effect on pH (changes pH by 0.15 to 0.23 units). pH diurnal trends followed liquid water and were driven mainly by variability in RH; in SOAS nighttime pH was near 1.5 and during day 0.5. pH ranged from 0.5 to 2 in summer and 1 to 3 in the winter at other sites. The systematically low levels of predicted pH in the southeast may have important ramifications, such as significantly influencing acid-catalyzed reactions, gas-aerosol partitioning, and mobilization of redox metals and minerals.

We use the Global Modelling Initiative (GMI) chemical transport model with a cloud droplet parameterisation adjoint to quantify the sensitivity of cloud droplet number concentration to uncertainties in predicting CCN concentrations. Published CCN closure uncertainties for six different sets of simplifying compositional and mixing state assumptions are used as proxies for modelled CCN uncertainty arising from application of those scenarios. It is found that cloud droplet number concentrations (N_d) are fairly insensitive to the number concentration (N_a) of aerosol which act as CCN over the continents (∂lnN_d/∂lnN_a ~10–30%), but the sensitivities exceed 70% in pristine regions such as the Alaskan Arctic and remote oceans. This means that CCN concentration uncertainties of 4–71% translate into only 1–23% uncertainty in cloud droplet number, on average. Since most of the anthropogenic indirect forcing is concentrated over the continents, this work shows that the application of Köhler theory and attendant simplifying assumptions in models is not a major source of uncertainty in predicting cloud droplet number or anthropogenic aerosol indirect forcing for the liquid, stratiform clouds simulated in these models. However, it does highlight the sensitivity of some remote areas to pollution brought into the region via long-range transport (e.g., biomass burning) or from seasonal biogenic sources (e.g., phytoplankton as a source of dimethylsulfide in the southern oceans). Since these transient processes are not captured well by the climatological emissions inventories employed by current large-scale models, the uncertainties in aerosol-cloud interactions during these events could be much larger than those uncovered here. This finding motivates additional measurements in these pristine regions, for which few observations exist, to quantify the impact (and associated uncertainty) of transient aerosol processes on cloud properties