Articles | Volume 18, issue 21
https://doi.org/10.5194/gmd-18-8461-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-8461-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The SAPRC atmospheric chemical mechanism generation system (MechGen)
William P. L. Carter
CORRESPONDING AUTHOR
College of Engineering Center for Environmental Research and Technology (CE-CERT), University of California, Riverside, California 92521, USA
Jia Jiang
Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Zhizhao Wang
College of Engineering Center for Environmental Research and Technology (CE-CERT), University of California, Riverside, California 92521, USA
Atmospheric Chemistry Observations & Modeling Lab, NSF National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80301, USA
Kelley C. Barsanti
Atmospheric Chemistry Observations & Modeling Lab, NSF National Center for Atmospheric Research, P.O. Box 3000, Boulder, CO 80301, USA
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Atmos. Chem. Phys., 25, 199–242, https://doi.org/10.5194/acp-25-199-2025, https://doi.org/10.5194/acp-25-199-2025, 2025
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This paper describes the scientific basis for gas-phase atmospheric chemical mechanisms derived using the SAPRC mechanism generation system, MechGen. It can derive mechanisms for most organic compounds with C, H, O, or N atoms, including initial reactions of organics with OH, O3, NO3, and O3P or by photolysis, as well as the reactions of the various types of intermediates that are formed. The paper includes a description of areas of uncertainty where additional research and updates are needed.
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Chemical mechanisms describe the chemical processes in atmospheric models that are used to describe the changes in the atmospheric composition. Therefore, accurate chemical mechanisms are necessary to predict the evolution of air pollution and climate change. The article describes all steps that are needed to build chemical mechanisms and discusses the advances and needs of experimental and theoretical research activities needed to build reliable chemical mechanisms.
Yingnan Zhang, Likun Xue, William P. L. Carter, Chenglei Pei, Tianshu Chen, Jiangshan Mu, Yujun Wang, Qingzhu Zhang, and Wenxing Wang
Atmos. Chem. Phys., 21, 11053–11068, https://doi.org/10.5194/acp-21-11053-2021, https://doi.org/10.5194/acp-21-11053-2021, 2021
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We developed the localized incremental reactivity (IR) for VOCs in a Chinese megacity and elucidated their applications in calculating the ozone formation potential (OFP). The IR scales showed a strong dependence on chemical mechanisms. Both emission- and observation-based inputs are suitable for the MIR calculation but not the case under mixed-limited or NOx-limited O3 formation regimes. We provide suggestions for the application of IR and OFP scales to aid in VOC control in China.
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Prescribed burns are controlled fires used to prevent wildfires. Smoke emissions were measured to characterize emission factors and optical properties of black and brown soot particles. Brown particles were emitted at 7–14 times that of black particles and contributed 82 % of atmospheric absorption by particles for ultraviolet light and 23 % for total solar radiation. These findings will improve inventories and climate models for prescribed burns.
Karine Sartelet, Zhizhao Wang, Youngseob Kim, Victor Lannuque, and Florian Couvidat
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SSH-aerosol v2 simulates the evolution of primary and secondary pollutants via gas-phase chemistry, aerosol dynamics (including ultrafine particles), and intra-particle reactions. It uses a sectional approach for size and composition, includes a wall-loss module, and links gas-phase mechanisms of different complexity to secondary organic aerosol formation. Representation of particle phase composition allows viscosity and non-ideality to be taken into account.
William P. L. Carter, Jia Jiang, John J. Orlando, and Kelley C. Barsanti
Atmos. Chem. Phys., 25, 199–242, https://doi.org/10.5194/acp-25-199-2025, https://doi.org/10.5194/acp-25-199-2025, 2025
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This paper describes the scientific basis for gas-phase atmospheric chemical mechanisms derived using the SAPRC mechanism generation system, MechGen. It can derive mechanisms for most organic compounds with C, H, O, or N atoms, including initial reactions of organics with OH, O3, NO3, and O3P or by photolysis, as well as the reactions of the various types of intermediates that are formed. The paper includes a description of areas of uncertainty where additional research and updates are needed.
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Chemical mechanisms describe the chemical processes in atmospheric models that are used to describe the changes in the atmospheric composition. Therefore, accurate chemical mechanisms are necessary to predict the evolution of air pollution and climate change. The article describes all steps that are needed to build chemical mechanisms and discusses the advances and needs of experimental and theoretical research activities needed to build reliable chemical mechanisms.
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Vignesh Vasudevan-Geetha, Lee Tiszenkel, Zhizhao Wang, Robin Russo, Daniel Bryant, Julia Lee-Taylor, Kelley Barsanti, and Shan-Hu Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-2454, https://doi.org/10.5194/egusphere-2024-2454, 2024
Preprint archived
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Our laboratory experiments using two high-resolution mass spectrometers show that these OOMs can also form within the particle phase, in addition to gas-to-particle conversion processes. Our results demonstrate that particle-phase formation processes can contribute to the formation and growth of new particles in biogenic environments.
Christine Wiedinmyer, Yosuke Kimura, Elena C. McDonald-Buller, Louisa K. Emmons, Rebecca R. Buchholz, Wenfu Tang, Keenan Seto, Maxwell B. Joseph, Kelley C. Barsanti, Annmarie G. Carlton, and Robert Yokelson
Geosci. Model Dev., 16, 3873–3891, https://doi.org/10.5194/gmd-16-3873-2023, https://doi.org/10.5194/gmd-16-3873-2023, 2023
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The Fire INventory from NCAR (FINN) provides daily global estimates of emissions from open fires based on satellite detections of hot spots. This version has been updated to apply MODIS and VIIRS satellite fire detection and better represents both large and small fires. FINNv2.5 generates more emissions than FINNv1 and is in general agreement with other fire emissions inventories. The new estimates are consistent with satellite observations, but uncertainties remain regionally and by pollutant.
Chao Lin, Yunyi Wang, Ryozo Ooka, Cédric Flageul, Youngseob Kim, Hideki Kikumoto, Zhizhao Wang, and Karine Sartelet
Atmos. Chem. Phys., 23, 1421–1436, https://doi.org/10.5194/acp-23-1421-2023, https://doi.org/10.5194/acp-23-1421-2023, 2023
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Zhizhao Wang, Florian Couvidat, and Karine Sartelet
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Christos Stamatis and Kelley Claire Barsanti
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Qi Li, Jia Jiang, Isaac K. Afreh, Kelley C. Barsanti, and David R. Cocker III
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Chamber-derived secondary organic aerosol (SOA) yields from camphene are reported for the first time. The role of peroxy radicals (RO2) was investigated using chemically detailed box models. We observed higher SOA yields (up to 64 %) in the experiments with added NOx than without due to the formation of highly oxygenated organic molecules (HOMs) when
NOx is present. This work can improve the representation of camphene in air quality models and provide insights into other monoterpene studies.
Zachary C. J. Decker, Michael A. Robinson, Kelley C. Barsanti, Ilann Bourgeois, Matthew M. Coggon, Joshua P. DiGangi, Glenn S. Diskin, Frank M. Flocke, Alessandro Franchin, Carley D. Fredrickson, Georgios I. Gkatzelis, Samuel R. Hall, Hannah Halliday, Christopher D. Holmes, L. Gregory Huey, Young Ro Lee, Jakob Lindaas, Ann M. Middlebrook, Denise D. Montzka, Richard Moore, J. Andrew Neuman, John B. Nowak, Brett B. Palm, Jeff Peischl, Felix Piel, Pamela S. Rickly, Andrew W. Rollins, Thomas B. Ryerson, Rebecca H. Schwantes, Kanako Sekimoto, Lee Thornhill, Joel A. Thornton, Geoffrey S. Tyndall, Kirk Ullmann, Paul Van Rooy, Patrick R. Veres, Carsten Warneke, Rebecca A. Washenfelder, Andrew J. Weinheimer, Elizabeth Wiggins, Edward Winstead, Armin Wisthaler, Caroline Womack, and Steven S. Brown
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To understand air quality impacts from wildfires, we need an accurate picture of how wildfire smoke changes chemically both day and night as sunlight changes the chemistry of smoke. We present a chemical analysis of wildfire smoke as it changes from midday through the night. We use aircraft observations from the FIREX-AQ field campaign with a chemical box model. We find that even under sunlight typical
nighttimechemistry thrives and controls the fate of key smoke plume chemical processes.
Sabrina Chee, Kelley Barsanti, James N. Smith, and Nanna Myllys
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Isaac Kwadjo Afreh, Bernard Aumont, Marie Camredon, and Kelley Claire Barsanti
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This is the first mechanistic modeling study of secondary organic aerosol (SOA) from the understudied monoterpene, camphene. The semi-explicit chemical model GECKO-A predicted camphene SOA yields that were ~2 times α-pinene. Using 50/50 α-pinene + limonene as a surrogate for camphene increased predicted SOA mass from biomass burning fuels by up to ~100 %. The accurate representation of camphene in air quality models can improve predictions of SOA when camphene is a dominant monoterpene.
Yingnan Zhang, Likun Xue, William P. L. Carter, Chenglei Pei, Tianshu Chen, Jiangshan Mu, Yujun Wang, Qingzhu Zhang, and Wenxing Wang
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We developed the localized incremental reactivity (IR) for VOCs in a Chinese megacity and elucidated their applications in calculating the ozone formation potential (OFP). The IR scales showed a strong dependence on chemical mechanisms. Both emission- and observation-based inputs are suitable for the MIR calculation but not the case under mixed-limited or NOx-limited O3 formation regimes. We provide suggestions for the application of IR and OFP scales to aid in VOC control in China.
Cited articles
Aumont, B., Szopa, S., and Madronich, S.: Modelling the evolution of organic carbon during its gas-phase tropospheric oxidation: development of an explicit model based on a self generating approach, Atmos. Chem. Phys., 5, 2497–2517, https://doi.org/10.5194/acp-5-2497-2005, 2005.
Bloss, C., Wagner, V., Jenkin, M. E., Volkamer, R., Bloss, W. J., Lee, J. D., Heard, D. E., Wirtz, K., Martin-Reviejo, M., Rea, G., Wenger, J. C., and Pilling, M. J.: Development of a detailed chemical mechanism (MCMv3.1) for the atmospheric oxidation of aromatic hydrocarbons, Atmos. Chem. Phys., 5, 641–664, https://doi.org/10.5194/acp-5-641-2005, 2005.
Carter, W. P. L.: A detailed mechanism for the gas-phase atmospheric reactions of organic compounds, Atmos.Environ. A, 24, 481–518, https://doi.org/10.1016/0960-1686(90)90005-8, 1990.
Carter, W. P. L.: Development of Ozone Reactivity Scales for Volatile Organic Compounds, J. Air Waste Manage., 44, 881–899, https://doi.org/10.1080/1073161X.1994.10467290, 1994.
Carter, W. P. L.: Documentation of the SAPRC-99 Chemical Mechanism for VOC Reactivity Assessment, Zenodo, https://doi.org/10.5281/zenodo.12600705, 2000.
Carter, W. P. L.: Development of the SAPRC-07 Chemical Mechanism, Atmos. Environ., 44, 5324–5335, https://doi.org/10.1016/j.atmosenv.2010.01.026, 2010a.
Carter, W. P. L.: Development of the SAPRC-07 Chemical Mechanism and Updated Ozone Reactivity Scales, Zenodo, https://doi.org/10.5281/zenodo.12601346, 2010b.
Carter, W. P. L.: Preliminary Documentation of the SAPRC-16 Mechanism, https://intra.engr.ucr.edu/~carter/SAPRC/16/S16doc.pdf (last access: 29 October 2016), 2016.
Carter, W. P. L.: Documentation of the SAPRC-22 Mechanisms, Zenodo, https://doi.org/10.5281/zenodo.12601488, 2023.
Carter, W. P. L.: SAPRC Mechanism Generation System for the Atmospheric Reactions of Volatile Organic Compounds in the Presence of NOx, https://intra.engr.ucr.edu/~carter/MechGen/ (last access: 25 July 2025), 2025a.
Carter, W. P. L.: SAPRC-07 and SAPRC-11 Chemical Mechanisms, Test Simulations, and Environmental Chamber Simulation, Fileshttps://www.cert.ucr.edu/~carter/SAPRC/SAPRCfiles.htm (last access: 25 July 2025), 2025b.
Carter, W. P. L. and Atkinson, R.: Atmospheric chemistry of alkanes, J. Atmos. Chem., 3, 377–405, https://doi.org/10.1007/BF00122525, 1985.
Carter, W. P. L. and Heo, G.: Development of Revised SAPRC Aromatics Mechanisms, https://intra.engr.ucr.edu/~carter/SAPRC/saprc11.pdf (last access: 12 April 2012), 2012.
Carter, W. P. L. and Heo, G.: Development of revised SAPRC aromatics mechanisms, Atmos. Environ., 77, 404–414, https://doi.org/10.1016/j.atmosenv.2013.05.021, 2013.
Carter, W. P. L., Jiang, J., Orlando, J. J., and Barsanti, K. C.: Derivation of atmospheric reaction mechanisms for volatile organic compounds by the SAPRC mechanism generation system (MechGen), Atmos. Chem. Phys., 25, 199–242, https://doi.org/10.5194/acp-25-199-2025, 2025a.
Carter, W. P. L., Wang, Z., and Jiang, J.: SAPRC/MechGen: MechGenv1.1, Zenodo [code], https://doi.org/10.5281/zenodo.16622705, 2025b.
Curtis, P.: LambdaMOO Programmer's Manual, https://lambda.moo.mud.org/pub/MOO/ProgrammersManual_toc.html (last access: 11 August 2025), 1997.
Ervens, B., Rickard, A., Aumont, B., Carter, W. P. L., McGillen, M., Mellouki, A., Orlando, J., Picquet-Varrault, B., Seakins, P., Stockwell, W. R., Vereecken, L., and Wallington, T. J.: Opinion: Challenges and needs of tropospheric chemical mechanism development, Atmos. Chem. Phys., 24, 13317–13339, https://doi.org/10.5194/acp-24-13317-2024, 2024.
Finlayson-Pitts, B. J. and Pitts Jr., J. N.: Chemistry of the Upper and Lower Atmosphere: Theory, Experiments, and Applications, in: 1st Edn., Elsevier, ISBN 978-0-12-257060-5, 1999.
Fox, K.: MOO-Cows FAQ, https://www.moo.mud.org/moo-faq/ (last access: 11 August 2025), 2004.
Gao, C. W., Allen, J. W., Green, W. H., and West, R. H.: Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms, Comput. Phys. Commun., 203, 212–225, https://doi.org/10.1016/j.cpc.2016.02.013, 2016.
Green, W. H.: Chapter 5 – Automatic generation of reaction mechanisms, in: Computer Aided Chemical Engineering, vol. 45, edited by: Faravelli, T., Manenti, F., and Ranzi, E., Elsevier, 259–294, https://doi.org/10.1016/B978-0-444-64087-1.00005-X, 2019.
Jenkin, M. E., Saunders, S. M., and Pilling, M. J.: The tropospheric degradation of volatile organic compounds: a protocol for mechanism development, Atmos. Environ., 31, 81–104, https://doi.org/10.1016/S1352-2310(96)00105-7, 1997.
Jenkin, M. E., Saunders, S. M., Wagner, V., and Pilling, M. J.: Protocol for the development of the Master Chemical Mechanism, MCM v3 (Part B): tropospheric degradation of aromatic volatile organic compounds, Atmos. Chem. Phys., 3, 181–193, https://doi.org/10.5194/acp-3-181-2003, 2003.
Jiang, J., Carter, W. P. L., Cocker III, D. R., and Barsanti, K. C.: Development and Evaluation of a Detailed Mechanism for Gas-Phase Atmospheric Reactions of Furans, ACS Earth Space Chem., 4, 1254–1268, https://doi.org/10.1021/acsearthspacechem.0c00058, 2020.
Jiang, J., Wang, Z., Barsanti, K. C., and Carter, W. P. L.: SAPRC MechGen Github Website, https://github.com/SAPRC/MechGen (last access: 30 July 2025), 2025.
Kaduwela, A., Luecken, D., Carter, W., and Derwent, R.: New directions: Atmospheric chemical mechanisms for the future, Atmos. Environ., 122, 609–610, https://doi.org/10.1016/j.atmosenv.2015.10.031, 2015.
Kirchner, F.: The chemical mechanism generation programme CHEMATA – Part 1: The programme and first applications, Atmos. Environ., 39, 1143–1159, https://doi.org/10.1016/j.atmosenv.2004.09.086, 2005.
Li, Q., Jiang, J., Afreh, I. K., Barsanti, K. C., and Cocker III, D. R.: Secondary organic aerosol formation from camphene oxidation: measurements and modeling, Atmos. Chem. Phys., 22, 3131–3147, https://doi.org/10.5194/acp-22-3131-2022, 2022.
Liu, M., Grinberg Dana, A., Johnson, M. S., Goldman, M. J., Jocher, A., Payne, A. M., Grambow, C. A., Han, K., Yee, N. W., Mazeau, E. J., Blondal, K., West, R. H., Goldsmith, C. F., and Green, W. H.: Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation, J. Chem. Inf. Model., 61, 2686–2696, https://doi.org/10.1021/acs.jcim.0c01480, 2021.
Postel, J. and Reynolds, J.: Telnet Protocol Specification, https://datatracker.ietf.org/doc/html/rfc854 (last access: 11 August 2025), 1983.
RMG: RMG-Reaction Mechanism Generator, https://rmg.mit.edu (last access: 11 October 2025), 2025.
Saunders, S. M., Jenkin, M. E., Derwent, R. G., and Pilling, M. J.: Protocol for the development of the Master Chemical Mechanism, MCM v3 (Part A): tropospheric degradation of non-aromatic volatile organic compounds, Atmos. Chem. Phys., 3, 161–180, https://doi.org/10.5194/acp-3-161-2003, 2003.
Venecek, M. A., Cai, C., Kaduwela, A., Avise, J., Carter, W. P. L., and Kleeman, M. J.: Analysis of SAPRC16 chemical mechanism for ambient simulations, Atmos. Environ., 192, 136–150, https://doi.org/10.1016/j.atmosenv.2018.08.039, 2018.
Vereecken, L. and Nozière, B.: H migration in peroxy radicals under atmospheric conditions, Atmos. Chem. Phys., 20, 7429–7458, https://doi.org/10.5194/acp-20-7429-2020, 2020.
Wikipedia: LambdaMOO, https://en.wikipedia.org/wiki/LambdaMOO (last access: 11 August 2025), 2025.
Wolfe, G. M., Marvin, M. R., Roberts, S. J., Travis, K. R., and Liao, J.: The Framework for 0-D Atmospheric Modeling (F0AM) v3.1, Geosci. Model Dev., 9, 3309–3319, https://doi.org/10.5194/gmd-9-3309-2016, 2016.
Short summary
The SAPRC Atmospheric Chemical Mechanism Generation System (MechGen) generates explicit chemical reaction mechanisms for organic compounds. MechGen has been used for decades in the development of the widely used SAPRC mechanisms. This paper, detailing the software system, and a companion paper, detailing the chemical basis, represent the first complete documentation of MechGen. This paper includes examples and instructions for generating explicit and reduced mechanisms.
The SAPRC Atmospheric Chemical Mechanism Generation System (MechGen) generates explicit chemical...