The article "Predicting Environmental Concentrations of Nanomaterials for Exposure Assessment - A Review" by Arturo A. Keller, Yuanfang Zheng, Antonia Praetorius, Joris T.K. Quik, and Bernd Nowack provides a comprehensive overview of the advancements in predicting environmental concentrations of nanomaterials (ENPs) for exposure and risk assessment. The authors highlight the evolution of Material Flow Analyses (MFAs) and Environmental Fate Models (EFMs) from initial studies in 2008 to more sophisticated models that consider engineered nanoparticle (ENP) size distribution, form, dynamic release, and better-informed release factors. MFAs provide input for EFMs, which generate estimates of particle flows and concentrations in various environmental compartments. While MFA models offer valuable insights into ENP release, they do not account for fate processes such as aggregation, transformation, dissolution, or corona formation. EFMs, on the other hand, account for these processes to a varying degree. These models can be categorized into individual compartment models and spatially-resolved watershed models, with the latter focusing on water and sediment compartments. The article discusses the challenges in validating MFA and EFM models against observed data, the need for robust analytical techniques to quantify ENP properties in complex matrices, and the potential role of machine learning in addressing these challenges. It also reviews the development of bioaccumulation models to predict internal concentrations in exposed organisms based on predicted environmental concentrations (PECs). The authors emphasize the importance of considering both intrinsic and extrinsic properties of ENPs, such as size, shape, solubility, and environmental conditions, to understand their behavior and fate in the environment. They highlight the need for more comprehensive data on ENP production and the environmental release of ENPs, as well as the limitations of current analytical methods for detecting ENPs in environmental samples. Overall, the article provides a detailed review of the current state of ENP exposure assessment, identifies gaps in knowledge, and offers suggestions for future research and applications.The article "Predicting Environmental Concentrations of Nanomaterials for Exposure Assessment - A Review" by Arturo A. Keller, Yuanfang Zheng, Antonia Praetorius, Joris T.K. Quik, and Bernd Nowack provides a comprehensive overview of the advancements in predicting environmental concentrations of nanomaterials (ENPs) for exposure and risk assessment. The authors highlight the evolution of Material Flow Analyses (MFAs) and Environmental Fate Models (EFMs) from initial studies in 2008 to more sophisticated models that consider engineered nanoparticle (ENP) size distribution, form, dynamic release, and better-informed release factors. MFAs provide input for EFMs, which generate estimates of particle flows and concentrations in various environmental compartments. While MFA models offer valuable insights into ENP release, they do not account for fate processes such as aggregation, transformation, dissolution, or corona formation. EFMs, on the other hand, account for these processes to a varying degree. These models can be categorized into individual compartment models and spatially-resolved watershed models, with the latter focusing on water and sediment compartments. The article discusses the challenges in validating MFA and EFM models against observed data, the need for robust analytical techniques to quantify ENP properties in complex matrices, and the potential role of machine learning in addressing these challenges. It also reviews the development of bioaccumulation models to predict internal concentrations in exposed organisms based on predicted environmental concentrations (PECs). The authors emphasize the importance of considering both intrinsic and extrinsic properties of ENPs, such as size, shape, solubility, and environmental conditions, to understand their behavior and fate in the environment. They highlight the need for more comprehensive data on ENP production and the environmental release of ENPs, as well as the limitations of current analytical methods for detecting ENPs in environmental samples. Overall, the article provides a detailed review of the current state of ENP exposure assessment, identifies gaps in knowledge, and offers suggestions for future research and applications.