[{"@context":"http:\/\/schema.org\/","@type":"Dataset","identifier":"https:\/\/doi.org\/10.17043\/kontkanen-2022-cluster-growth-1","@id":"https:\/\/doi.org\/10.17043\/kontkanen-2022-cluster-growth-1","name":"Atmospheric molecular cluster growth data","description":"This data set contains output data from the Atmospheric Cluster Dynamics Code (ACDC) model, which simulates the clustering of atmospheric vapours and the growth of these clusters by further molecular and cluster-cluster collisions.\r\n\r\nThe data can be used for predictions of the production of new secondary particles from clustering and condensation of atmospheric vapours. It can be used for e.g. benchmarking or evaluating parameterizations of new particle formation (NPF) processes.\r\n\r\nThe data is output of a computational process model, and hence does not represent a specific time period or location. Simulation sets are calculated for a two-component system containing a quasi-unary inorganic compound corresponding to a mixture of sulfuric acid (SA) and ammonia (NH\u2083) or dimethylamine (DMA) and an organic compound. Data are provided for 18 simulations.","url":"http:\/\/bolin.su.se\/data\/kontkanen-2022-cluster-growth-1","keywords":["Atmosphere","Aerosols","Particle","Growth","K\u00f6hler","Earth science > Atmosphere > Aerosols > Organic particles"],"creator":{"@type":"Person","name":"Jenni Kontkanen"},"citation":"Kontkanen J, Olenius T, Kulmala M, Riipinen I (2018) Exploring the potential of nano-K\u00f6hler theory to describe the growth of atmospheric molecular clusters by organic vapors using cluster kinetics simulations. Atmos. Chem. Phys. 18:13733\u2060\u200a\u2013\u200a\u206013754. doi:10.5194\/acp-18-13733-2018\r\n\r\nOlenius T, Riipinen I (2017) Molecular-resolution simulations of new particle formation: Evaluation of common assumptions made in describing nucleation in aerosol dynamics models. Aerosol Sci. Tech. 51:397\u2060\u200a\u2013\u200a\u2060408. doi:10.1080\/02786826.2016.1262530\r\n\r\nMcGrath MJ et al. (2012) Atmospheric Cluster Dynamics Code: a flexible method for solution of the birth-death equations. Atmos. Chem. Phys. 12:2345\u2060\u200a\u2013\u200a\u20602355. doi:10.5194\/acp-12-2345-2012","license":"https:\/\/opendatacommons.org\/licenses\/by\/","isAccessibleForFree":true,"includedInDataCatalog":{"@type":"DataCatalog","name":"Bolin Centre for Climate Research, Stockholm University","identifier":"https:\/\/bolin.su.se\/data\/","url":"https:\/\/bolin.su.se\/data\/"},"distribution":{"@type":"DataDownload","encodingFormat":"application\/zip","contentUrl":"https:\/\/bolin.su.se\/data\/data\/kontkanen-2022-cluster-growth-1.zip"},"size":48524392058,"isBasedOn":"Kontkanen J, Olenius T, Kulmala M, Riipinen I (2018) Exploring the potential of nano-K\u00f6hler theory to describe the growth of atmospheric molecular clusters by organic vapors using cluster kinetics simulations. Atmos. Chem. Phys. 18:13733\u2060\u200a\u2013\u200a\u206013754. doi:10.5194\/acp-18-13733-2018\r\n\r\nOlenius T, Riipinen I (2017) Molecular-resolution simulations of new particle formation: Evaluation of common assumptions made in describing nucleation in aerosol dynamics models. Aerosol Sci. Tech. 51:397\u2060\u200a\u2013\u200a\u2060408. doi:10.1080\/02786826.2016.1262530\r\n\r\nMcGrath MJ et al. (2012) Atmospheric Cluster Dynamics Code: a flexible method for solution of the birth-death equations. Atmos. Chem. Phys. 12:2345\u2060\u200a\u2013\u200a\u20602355. doi:10.5194\/acp-12-2345-2012","temporalCoverage":"\/"}]