Environmental protection is becoming increasingly important in the maritime sector, particularly in the port area. Both sectors have a significant impact on the environment due to activities such as cargo handling, road and rail traffic and marine vessel operations. One of the significant aspects of port operations is emissions to the atmosphere. However, building atmospheric emission inventories in ports is a challenging task that includes intensive data collection campaigns as well as significant financial investments in data processing and analysis. This assists the decision-makers to undertake timely corrective actions and curb adverse impacts. However, current methodologies for building emission inventories have a considerable time lag since emissions are evaluated weeks or months after they have occurred. This paper aims at solving this issue by providing a methodology for building air emission inventories in real-time using IoT data sources with an emphasis on building comprehensive emission inventories in an automated fashion. To validate the approach, an atmospheric emission inventory was built based on Internet of Things (IoT) data for the port of Piraeus. The results indicate that nitrogen oxides (NOX) emissions are prevalent during both operating phases of vessels, followed by sulphur oxides (SOX) emissions. Non-methane volatile organic compounds (NMVOC) and particulate matter (PM) emissions are considerably lower. Emissions during hotelling time are on average 7.1 time higher than the emission generated during the vessel manoeuvring time. In the discussion section, the advantages and constraints of the approach are given with guidelines for further refinement of the proposed methodology. © 2023, The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University.