These files have been prepared for the paper entitled "Comparative ozone production sensitivity to NOx and VOCs in Quito, Ecuador and Santiago, Chile" submitted to Atmospheric Chemistry and Physics in March, 2025. Authors: María Cazorla1, Melissa Trujillo1, Rodrigo Seguel2,3, Laura Gallardo2,3 1Universidad San Francisco de Quito USFQ, Instituto de Investigaciones Atmosféricas, Quito, Ecuador2Center for Climate and Resilience Research (CR2), Universidad de Chile, Santiago, Chile3Departamento de Geofísica, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Santiago, ChileThis dataset belongs to a comparative analysis of ozone production rates in Quito, Ecuador and Santiago, Chile. Preprint available at: https://doi.org/10.5194/egusphere-2024-3720 Here we provide the MATLAB code and files used to run the model. Additionally, files can be found in the path: Photochemical_Model_Quito_Santiago>Quito Input Files F0AM, at https://observaciones-iia.usfq.edu.ec/Filesinput_scl.mat: complete dataset with 10-minute resolution of meteorological and air quality variables for Santiago.MX50_minmax.mat: complete dataset with 10-minute resolution of VOCs (percentile 50) for Santiago.Santiago_model.m: model run, use with input_scl.mat, MX50_minmax.mat, and mcm_subset.m. This is an executable file for the F0AM (Framework for 0-D Atmospheric Modeling) (Wolfe et al., 2016)mcm_subset.m: MCMv331 mechanism with all the chemical species used. This mechanism is called in Santiago_model.m. The chemical mechanistic information was taken from the Master Chemical Mechanism, MCM v3.3.1 (Bloss et al., 2005; Jenkin et al., 1997, 2003, 2015; Saunders et al., 2003), via website: www.mcm.york.ac.uk. ReferencesBloss, 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.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.

These files have been prepared for the paper entitled "Comparative ozone production sensitivity to NOx and VOCs in Quito, Ecuador and Santiago, Chile" submitted to Atmospheric Chemistry and Physics in March, 2025. Authors: María Cazorla1, Melissa Trujillo1, Rodrigo Seguel2,3, Laura Gallardo2,3 1Universidad San Francisco de Quito USFQ, Instituto de Investigaciones Atmosféricas, Quito, Ecuador2Center for Climate and Resilience Research (CR2), Universidad de Chile, Santiago, Chile3Departamento de Geofísica, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Santiago, ChileThis dataset belongs to a comparative analysis of ozone production rates in Quito, Ecuador and Santiago, Chile. Preprint available at: https://doi.org/10.5194/egusphere-2024-3720 Here we provide the MATLAB code and files used to run the model. Additionally, files can be found in the path: Photochemical_Model_Quito_Santiago>Quito Input Files F0AM, at https://observaciones-iia.usfq.edu.ec/Filesinput_scl.mat: complete dataset with 10-minute resolution of meteorological and air quality variables for Santiago.MX50_minmax.mat: complete dataset with 10-minute resolution of VOCs (percentile 50) for Santiago.Santiago_model.m: model run, use with input_scl.mat, MX50_minmax.mat, and mcm_subset.m. This is an executable file for the F0AM (Framework for 0-D Atmospheric Modeling) (Wolfe et al., 2016)mcm_subset.m: MCMv331 mechanism with all the chemical species used. This mechanism is called in Santiago_model.m. The chemical mechanistic information was taken from the Master Chemical Mechanism, MCM v3.3.1 (Bloss et al., 2005; Jenkin et al., 1997, 2003, 2015; Saunders et al., 2003), via website: www.mcm.york.ac.uk. ReferencesBloss, 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.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.

These files have been prepared for the paper entitled "Comparative ozone production sensitivity to NOx and VOCs in Quito, Ecuador and Santiago, Chile" submitted to Atmospheric Chemistry and Physics in March, 2025. Authors: María Cazorla1, Melissa Trujillo1, Rodrigo Seguel2,3, Laura Gallardo2,3 1Universidad San Francisco de Quito USFQ, Instituto de Investigaciones Atmosféricas, Quito, Ecuador2Center for Climate and Resilience Research (CR2), Universidad de Chile, Santiago, Chile3Departamento de Geofísica, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Santiago, ChileThis dataset belongs to a comparative analysis of ozone production rates in Quito, Ecuador and Santiago, Chile. Preprint available at: https://doi.org/10.5194/egusphere-2024-3720Here we provide the MATLAB code and files used to run the model. Additionally, files can be found in the path: Photochemical_Model_Quito_Santiago>Quito Input Files F0AM, at https://observaciones-iia.usfq.edu.ec/ Filesinput_uio.mat: complete dataset with 10-minute resolution of meteorological and air quality variables for Quito. MX50_UIO.mat: complete dataset with 10-minute resolution of VOCs (percentile 50) for Quito.Quito_model.m: model run, use with input_uio.mat, MX50_UIO.mat, and mcm_subset.m. This is an executable file for the F0AM (Framework for 0-D Atmospheric Modeling) (Wolfe et al., 2016).mcm_subset.m: MCMv331 mechanism with all the chemical species used. This mechanism is called in Quito_model.m. The chemical mechanistic information was taken from the Master Chemical Mechanism, MCM v3.3.1 (Bloss et al., 2005; Jenkin et al., 1997, 2003, 2015; Saunders et al., 2003), via website: www.mcm.york.ac.uk. ReferencesBloss, 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.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.

These files have been prepared for the paper entitled "Comparative ozone production sensitivity to NOx and VOCs in Quito, Ecuador and Santiago, Chile" submitted to Atmospheric Chemistry and Physics in March, 2025. Authors: María Cazorla1, Melissa Trujillo1, Rodrigo Seguel2,3, Laura Gallardo2,3 1Universidad San Francisco de Quito USFQ, Instituto de Investigaciones Atmosféricas, Quito, Ecuador2Center for Climate and Resilience Research (CR2), Universidad de Chile, Santiago, Chile3Departamento de Geofísica, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Santiago, ChileThis dataset belongs to a comparative analysis of ozone production rates in Quito, Ecuador and Santiago, Chile. Preprint available at: https://doi.org/10.5194/egusphere-2024-3720Here we provide the MATLAB code and files used to run the model. Additionally, files can be found in the path: Photochemical_Model_Quito_Santiago>Quito Input Files F0AM, at https://observaciones-iia.usfq.edu.ec/ Filesinput_uio.mat: complete dataset with 10-minute resolution of meteorological and air quality variables for Quito. MX50_UIO.mat: complete dataset with 10-minute resolution of VOCs (percentile 50) for Quito.Quito_model.m: model run, use with input_uio.mat, MX50_UIO.mat, and mcm_subset.m. This is an executable file for the F0AM (Framework for 0-D Atmospheric Modeling) (Wolfe et al., 2016).mcm_subset.m: MCMv331 mechanism with all the chemical species used. This mechanism is called in Quito_model.m. The chemical mechanistic information was taken from the Master Chemical Mechanism, MCM v3.3.1 (Bloss et al., 2005; Jenkin et al., 1997, 2003, 2015; Saunders et al., 2003), via website: www.mcm.york.ac.uk. ReferencesBloss, 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.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.

Model results and emission dataset that was used to produce the data presented in the manuscript by Daskalakis et al., submitted in GRL in May 2023.

Model results and emission dataset that was used to produce the data presented in the manuscript by Daskalakis et al., submitted in GRL in May 2023.

Mineral dust aerosols play a major role in present and past climates. To date, we rely on climate models for estimates of dust fluxes to calculate the impact of airborne micronutrients on biogeochemical cycles. Here we provide a new global dust flux data set for Holocene and Last Glacial Maximum (LGM) conditions based on observational data. A comparison with dust flux simulations highlights regional differences between observations and models. By forcing a biogeochemical model with our new data set and using this model's results to guide a millennial-scale Earth System Model simulation, we calculate the impact of enhanced glacial oceanic iron deposition on the LGM-Holocene carbon cycle. On centennial timescales, the higher LGM dust deposition results in a weak reduction of <10 ppm in atmospheric CO2 due to enhanced efficiency of the biological pump. This is followed by a further ~10 ppm reduction over millennial timescales due to greater carbon burial and carbonate compensation.