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).

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).

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).

These data are extracted from output from the Community Multiscale Air Quality (CMAQ) model run with inputs and simulations generated by the EQUATES project. Pollutant concentrations are pulled from the model gridcell corresponding to Baltimore, Maryland, where the measurements for this study were taken. This dataset is associated with the following publication: Sapkota, S., P. Shekhar, B. Murphy, H. Pye, C. Hennigan, and M. El-Sayed. Seasonal Assessment of Secondary Organic Aerosol Formed through Aqueous Pathways in the Eastern United States. ACS Earth and Space Chemistry. American Chemical Society, Washington, DC, USA, 9(4): 876-887, (2025).

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).

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).

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).

This dataset contains data presented in the figures of the paper "On the implications of aerosol liquid water and phase separation for organic aerosol mass" published in Atmospheric Chemistry and Physics. It also links to the data archive of field observations. This dataset is associated with the following publication: Pye, H., B. Murphy, L. Xu, N. Ng, A. Carlton, H. Guo, R. Weber, P. Vasilakos, W. Appel, S. Budisulistiorini, J. Surratt, A. Nenes, W. Hu, J. Jimenez, G. saacman-VanWertz, P. Misztal, and A. Goldstein. On the implications of aerosol liquid water and phase separation for organic aerosol mass. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 17: 343-369, (2017).

This dataset contains data presented in the figures of the paper "On the implications of aerosol liquid water and phase separation for organic aerosol mass" published in Atmospheric Chemistry and Physics. It also links to the data archive of field observations. This dataset is associated with the following publication: Pye, H., B. Murphy, L. Xu, N. Ng, A. Carlton, H. Guo, R. Weber, P. Vasilakos, W. Appel, S. Budisulistiorini, J. Surratt, A. Nenes, W. Hu, J. Jimenez, G. saacman-VanWertz, P. Misztal, and A. Goldstein. On the implications of aerosol liquid water and phase separation for organic aerosol mass. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 17: 343-369, (2017).