AutoQA4Env has been presented by Najmeh Kaffashzadeh in the virtual EGU conference session on atmospheric composition variability and trends. Many scientific and statistical efforts are devoted to developing advanced analytic tools or methods, but a better quantification of trend and uncertainty cannot be achieved without proper data quality control (QC). Automated QC tools are needed to allow better use of existing data, for example in the machine learning applications of the IntelliAQ project. The presentation discusses the challenges involved and presents a methodology for automated QC and its integration into the workflow used for the TOAR-database.