Digitalization is a key focus in transformation of environmental and process engingeering world in the recent years. One of the main derivatives of this transformation is the concept of Digital Twin (DT). DTs are virtual replicas of physical systems that can mimic the operation of the systems in real-time. Their applications in environmental context can be for drinking water systems, water resource recovery facilities, air quality systems, sewer networks, etc. The main elements that characterise a DT can be different depending on its application and specific objective. However, some that can be generally mentioned are integration with other parts of the system, using real-time data, recalibration/validation of the models, having a two-directional flow of information between models and physical systems, and being capable of predicting the state of the system for the near future. DTs can be operation-focused relying on (near) real-time data from the physical system or they can be used as a discision support tool for design, planning, construction and investment purposes. On the way of developing DT for a physical system, some challenges are present that need to be tackled. Choosing a right level of complexity for the models (mechanistic, data-driven or hybrid models) , data requirements and their quality, handling uncertainties, automatic model calibration/validation, trust in operational staff and managers to use and rely on DTs, are some examples of these challenges. This session will focus on DTs and their applications to environmental systems. It emphasizes on real case applications of DT for different environmental sectors (e.g. drinking water, wastewater, air quality, etc.) and on the attempts to overcome the existing challenges for DT development.