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 µg m−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 levoglucosan but decrease particle-phase partitioning for low O : C, monoterpene-derived species. This dataset is associated with the following publication: Pye, H., W. Appel, H. Foroutan, A. Zuend, J. Fry, G. Isaacman-VanWertz , N.L. Ng, A. Goldstein, S. Capps, and L. Xu. Coupling of organic and inorganic aerosol systems and the effect on gas–particle partitioning in the southeastern US. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 18: 357-370, (2018).

The relationship between the oxidation state and relative volatility of secondary organic aerosol (SOA) from the oxidation of a wide range of hydrocarbons is investigated using a fast-stepping, scanning thermodenuder interfaced with a high resolution time-of-flight aerosol mass spectrometer (AMS). SOA oxidation state varied widely across the investigated range of parent hydrocarbons but was relatively stable for replicate experiments using a single hydrocarbon precursor. On average, unit mass resolution indicators of SOA oxidation (e.g., AMS f43 and f44) are consistent with previously reported values. Linear regression of H:C vs O:C obtained from parameterization of f43 and f44 and elemental analysis of high resolution spectra in Van Krevelen space both yield a slope of ~0.5 across different SOA types. A similar slope was obtained for a distinct subset of toluene/NOx reactions in which the integrated oxidant exposure was varied to alter oxidation. The relative volatility of different SOA types displays similar variability and is strongly correlated with SOA oxidation state (OSC). On average, relatively low oxidation and volatility were observed for aliphatic alkene (including terpenes) and n-alkane SOA while the opposite is true for mono- and polycyclic aromatic hydrocarbon SOA. Effective enthalpy for total chamber aerosol obtained from volatility differential mobility analysis is also highly correlated with OSC indicating a primary role for oxidation levels in determining the volatility of chamber SOA. Effective enthalpies for chamber SOA are substantially lower than those of neat organic standards but are on the order of those obtained for partially oligomerized glyoxal and methyl glyoxal. This dataset is associated with the following publication: Docherty, K., E. Corse, M. Jaoui, J. Offenberg, T. Kleindienst, J. Krug, T. Riedel, and M. Lewandowski. Trends in the oxidation and relative volatility of chamber-generated secondary organic aerosol. AEROSOL SCIENCE AND TECHNOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 52(9): 992-1004, (2018).

This research used data mining approaches to better understand factors affecting the formation of secondary organic aerosol (SOA). Although numerous laboratory and computational studies have been completed on SOA formation, it is still challenging to determine factors that most influence SOA formation. Experimental data were based on previous work described by Offenberg et al. (2017), where volume concentrations of SOA were measured in 139 laboratory experiments involving the oxidation of single hydrocarbons under different operating conditions. Three different data mining methods were used, including nearest neighbor, decision tree, and pattern mining. Both decision tree and pattern mining approaches identified similar chemical and experimental conditions that were important to SOA formation. Among these important factors included the number of methyl groups, the number of rings and the presence of dinitrogen pentoxide (N2O5). This dataset is associated with the following publication: Olson, D., J. Offenberg, M. Lewandowski, T. Kleindienst, K. Docherty, M. Jaoui, J.D. Krug, and T. Riedel. Data mining approaches to understanding the formation of secondary organic aerosol. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 252: 118345, (2021).

This research used data mining approaches to better understand factors affecting the formation of secondary organic aerosol (SOA). Although numerous laboratory and computational studies have been completed on SOA formation, it is still challenging to determine factors that most influence SOA formation. Experimental data were based on previous work described by Offenberg et al. (2017), where volume concentrations of SOA were measured in 139 laboratory experiments involving the oxidation of single hydrocarbons under different operating conditions. Three different data mining methods were used, including nearest neighbor, decision tree, and pattern mining. Both decision tree and pattern mining approaches identified similar chemical and experimental conditions that were important to SOA formation. Among these important factors included the number of methyl groups, the number of rings and the presence of dinitrogen pentoxide (N2O5). This dataset is associated with the following publication: Olson, D., J. Offenberg, M. Lewandowski, T. Kleindienst, K. Docherty, M. Jaoui, J.D. Krug, and T. Riedel. Data mining approaches to understanding the formation of secondary organic aerosol. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 252: 118345, (2021).

Data set contains CMAQ model output for Look Rock, Tennessee and Centreville, Alabama during summer 2013. This dataset is associated with the following publication: Liu, J., L. Russell, G. Ruggeri, S. Takahama, M. Claflin, P. Ziemann, H. Pye, B. Murphy, L. Xu, N. Ng, K. McKinney, S. Hapsari Budisulistiorini, T. Bertram, A. Nenes, and J. Surratt. Regional Similarities and NOx‐Related Increases in Biogenic Secondary Organic Aerosol in Summertime Southeastern United States. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 123(18): 10,620-10,636, (2018).

Dataset contains supplementary information (model inputs and/or outputs and literature values) for Section 4.1 (idealized acidity calculations), Section 4.2 (box model calculations of pH for ambient conditions), Section 7.1 (observed aerosol pH values), Section 7.2 (observed cloud pH values), and Section 8.1 (CMAQ hemispheric predictions). This dataset is associated with the following publication: Pye, H., A. Nenes, B. Alexander, A. Ault, M. Barth, S. Clegg, J. Collett, K. Fahey, C. Hennigan, H. Herrmann, M. Kanakidou, J. Kelly, I. Ku, V.F. McNeill, N. Riemer, T. Schaefer, G. Shi, A. Tilgner, J. Walker, T. Wang, R. Weber, J. Xing, R. Zaveri, and A. Zuend. The Acidity of Atmospheric Particles and Clouds. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 20(8): 4809–4888, (2020).

Links point to the NOAA data archive of observational data and the supplement of the article which this data supports. No model data was uploaded due to its size. All updates to CMAQ used in this work are available in the public release of CMAQv5.1 (available through github or the CMAS Center). This dataset is associated with the following publication: Pye , H., D. Luecken , L. Xu, C.M. Boyd, N.L. Ng, K. Baker , B.R. Ayres, J. Bash , K. Baumann, W.P.L. Carter, E. Edgerton, J.L. Fry, B. Hutzell , D. Schwede , and P.B. Shepson. Modeling the current and future role of particulate organic nitrates in the southeastern United States. Environmental Science & Technology Letters. American Chemical Society, Washington, DC, USA, 49(24): 14195-14203, (2015).

Dataset is a link to the publically available CMAQ v5.1 model code. The following update was also implemented: https://github.com/USEPA/CMAQ/blob/5.2/CCTM/docs/Release_Notes/AH3OPJ_IEPOX_update.md. This dataset is associated with the following publication: Carlton, A., H. Pye, K. Baker, and C. Hennigan. Additional Benefits of Federal Air-Quality Rules: Model Estimates of Controllable Biogenic Secondary Organic Aerosol. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(16): 9254–9265, (2018).

Dataset is a link to the publically available CMAQ v5.1 model code. The following update was also implemented: https://github.com/USEPA/CMAQ/blob/5.2/CCTM/docs/Release_Notes/AH3OPJ_IEPOX_update.md. This dataset is associated with the following publication: Carlton, A., H. Pye, K. Baker, and C. Hennigan. Additional Benefits of Federal Air-Quality Rules: Model Estimates of Controllable Biogenic Secondary Organic Aerosol. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 52(16): 9254–9265, (2018).

The effect of acidity and relative humidity on bulk isoprene aerosol parameters has been investigated in several studies, however few measurements have been conducted on individual aerosol compounds. The focus of this study has been the examination of the effect of acidity and relative humidity on secondary organic aerosol (SOA) chemical composition from isoprene photooxidation in the presence of nitrogen oxide (NOx). A detailed characterization of SOA at the molecular level was also investigated. Experiments were conducted in a 14.5 m3 smog chamber operated in flow mode. Based on a detailed analysis of mass spectra obtained from gas chromatography-mass spectrometry of silylated derivatives in electron impact and chemical ionization modes, and ultra-high performance liquid chromatography/electrospray ionization/time-of-flight high resolution mass spectrometry, and collision-induced dissociation in the negative ionization modes, we characterized not only typical isoprene products, but also new oxygenated compounds. A series of nitroxy-organosulfates (OS) were tentatively identified on the basis of high resolution mass spectra. Under acidic conditions, the major identified compounds include 2-methyltetrols (2MT), 2-methylglyceric acid (2MGA) and 2MT-OS. Other products identified include epoxydiols, mono- and dicarboxylic acids, other organic sulfates, and nitroxy- and nitrosoxy-OS. The contribution of SOA products from isoprene oxidation to PM2.5 was investigated by analysing ambient aerosol collected at rural sites in Poland. Methyltetrols, 2MGA and several organosulfates and nitroxy-OS were detected in both the field and laboratory samples. The influence of relative humidity on SOA formation was modest in non-acidic seed experiments, and stronger under acidic seed aerosol. Total secondary organic carbon decreased with increasing relative humidity under both acidic and non-acidic conditions. While the yields of some of the specific organic compounds decreased with increasing relative humidity others varied in an indeterminate manner from changes in the relative humidity. This dataset is associated with the following publication: Nestorowicz, K., M. Jaoui, K. Rudzinski, M. Lewandowski, T. Kleindienst, G. Spolnik, W. Danikiewicz, and R. Szmigielski. Chemical Composition of Isoprene SOA Under Acidic and Non-Acidic Conditions: Effect of Relative Humidity. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 18(4): 18101-18121, (2018).