This data documents the results of chamber modeling and chemical transport modeling of the contribution of Intermediate Volatility Organic Compounds to mobile-source organic aerosol formation in California. The data show that IVOCs make up a significant fraction of the total source of secondary organic aerosol in urban environments and that mobile sources make up only about one third to half of the total IVOC emissions. Other urban sources of IVOCs were explored. These data are visualized and presented in the figures published in a peer-reviewed manuscript (with corresponding title) in Atmospheric Chemistry and Physics. The raw CMAQ output data are backed up and preserved on the ATMOS supercomputing system at the National Computing Center in Durham, North Carolina. The file location on the ASM server is: /asm/MOD3DEV/bmurphy/Models/cmaq/CMAQ_Ben/Projects/quanyang_181212/data. This dataset is associated with the following publication: Lu, Q., B. Murphy, M. Qin, P.J. Adams, Y. Zhao, H. Pye, C. Efstathiou, C. Allen, and A. Robinson. Simulation of organic aerosol formation during the CalNex study: updated mobile emissions and secondary organic aerosol parameterization for intermediate-volatility organic compounds. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 20(7): 4313–4332, (2020).

This data documents the results of chamber modeling and chemical transport modeling of the contribution of Intermediate Volatility Organic Compounds to mobile-source organic aerosol formation in California. The data show that IVOCs make up a significant fraction of the total source of secondary organic aerosol in urban environments and that mobile sources make up only about one third to half of the total IVOC emissions. Other urban sources of IVOCs were explored. These data are visualized and presented in the figures published in a peer-reviewed manuscript (with corresponding title) in Atmospheric Chemistry and Physics. The raw CMAQ output data are backed up and preserved on the ATMOS supercomputing system at the National Computing Center in Durham, North Carolina. The file location on the ASM server is: /asm/MOD3DEV/bmurphy/Models/cmaq/CMAQ_Ben/Projects/quanyang_181212/data. This dataset is associated with the following publication: Lu, Q., B. Murphy, M. Qin, P.J. Adams, Y. Zhao, H. Pye, C. Efstathiou, C. Allen, and A. Robinson. Simulation of organic aerosol formation during the CalNex study: updated mobile emissions and secondary organic aerosol parameterization for intermediate-volatility organic compounds. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 20(7): 4313–4332, (2020).

Data contains CMAQ code, VCPy code, CMAQ input files, and output files used in the work of Pennington et al.

Composition and structural information of the nitrogen containing aromatic compounds emitted from cookstove combustion.

Volume concentrations of secondary organic aerosol (SOA) are measured in 139 steady-state, single precursor hydrocarbon oxidation experiments after passing through a temperature controlled inlet. The response to change in temperature is well predicted through a feedforward Artificial Neural Network. The most parsimonious model, as indicated by Akaike’s Information Criterion, Corrected (AIC,C), utilizes 11 input variables, a single hidden layer of 4 tanh activation function nodes, and a single linear output function. This model predicts thermal behavior of single precursor aerosols to less than ± 5%, which is within the measurement uncertainty, while limiting the problem of overfitting. Prediction of thermal behavior of SOA can be achieved by a concise number of descriptors of the precursor hydrocarbon including the number of internal and external double bonds, number of methyl- and ethyl- functional groups, molecular weight, number of ring structures, in addition to the volume of SOA formed, and an indicator of which of four oxidant precursors was used to initiate reactions (NOx photo-oxidation, photolysis of H2O2, ozonolysis, or thermal decomposition of N2O5). Additional input variables, such as, chamber volumetric residence time, relative humidity, initial concentration of oxides of nitrogen, reacted hydrocarbon concentration, and further descriptors of the precursor hydrocarbon, including carbon number, number of oxygen atoms, and number of aromatic ring structures, lead to over fit models, and are unnecessary for an efficient, accurate predictive model of thermal behavior of SOA. This work indicates that predictive statistical modeling methods may be complementary to descriptive techniques for use in parameterization of air quality models. This dataset is associated with the following publication: Offenberg, J., M. Lewandowski, T. Kleindienst, K. Docherty, J. Krug, T. Riedel, D. Olson, and M. Jaoui. Predicting Thermal Behavior of Secondary Organic Aerosols. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(17): 9911-9919, (2017).

Volume concentrations of secondary organic aerosol (SOA) are measured in 139 steady-state, single precursor hydrocarbon oxidation experiments after passing through a temperature controlled inlet. The response to change in temperature is well predicted through a feedforward Artificial Neural Network. The most parsimonious model, as indicated by Akaike’s Information Criterion, Corrected (AIC,C), utilizes 11 input variables, a single hidden layer of 4 tanh activation function nodes, and a single linear output function. This model predicts thermal behavior of single precursor aerosols to less than ± 5%, which is within the measurement uncertainty, while limiting the problem of overfitting. Prediction of thermal behavior of SOA can be achieved by a concise number of descriptors of the precursor hydrocarbon including the number of internal and external double bonds, number of methyl- and ethyl- functional groups, molecular weight, number of ring structures, in addition to the volume of SOA formed, and an indicator of which of four oxidant precursors was used to initiate reactions (NOx photo-oxidation, photolysis of H2O2, ozonolysis, or thermal decomposition of N2O5). Additional input variables, such as, chamber volumetric residence time, relative humidity, initial concentration of oxides of nitrogen, reacted hydrocarbon concentration, and further descriptors of the precursor hydrocarbon, including carbon number, number of oxygen atoms, and number of aromatic ring structures, lead to over fit models, and are unnecessary for an efficient, accurate predictive model of thermal behavior of SOA. This work indicates that predictive statistical modeling methods may be complementary to descriptive techniques for use in parameterization of air quality models. This dataset is associated with the following publication: Offenberg, J., M. Lewandowski, T. Kleindienst, K. Docherty, J. Krug, T. Riedel, D. Olson, and M. Jaoui. Predicting Thermal Behavior of Secondary Organic Aerosols. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(17): 9911-9919, (2017).

VCPy predicts organic emission from volatile chemical products. Data here includes year 2017 emissions by sub product use category (sub PUC) and total for the United States. In addition, the VCPy model code is linked.

Dataset containing the composition and structural description of nitroaromatic compounds from biomass burning emissions. This dataset is associated with the following publication: Xie, M., X. Chen, M. Hays, and A. Holder. Composition and light absorption of N-containing aromatic compounds in organic aerosols from laboratory biomass burning. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 19(5): 2899-2915, (2018).

Dataset containing the composition and structural description of nitroaromatic compounds from biomass burning emissions. This dataset is associated with the following publication: Xie, M., X. Chen, M. Hays, and A. Holder. Composition and light absorption of N-containing aromatic compounds in organic aerosols from laboratory biomass burning. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 19(5): 2899-2915, (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).