Access to a timely physical distribution is an important determinant of urban freight transportation. In the context of Internet of Things, emergent sustainability performances of logistics operations are affected by the components of the supply chain, including containers, information protocols, open hubs and marketplaces. The future freight transportation, inspired by the digital internet, can evolve into a physical-internet-enabled scenario, subject to many promises of addressing global logistics sustainability grand challenge. Meanwhile, carbon trading system should be continuously adopted to elucidate production and emission. Among this interaction between infrastructural and behavioral aspects, logistics system design and management must be handled in marketplace-oriented logistics networks, provided that transportation re-sources, if not properly managed, might in practice jeopardizes both the mobility of goods, profits of enterprises as well as the eventual efficiency of the public sector. The deliveries are in a sensitive nature to decreased quality of service when they experience excessive waiting times for being transported to downstream plants. Integrating the carbon trading system into the physical internet simulation of a multi-agent orientation may help technologically forecast logistics benefits. However, we admitted few simulation modelling efforts have been established for addressing sustainability issues in the era of supply chain digitalization. System design and management of physical-internet-enabled transportation understood from emergent behaviors (from decision making autonomy) and metrics (as outputs of operation), especially enabled by the coordination, collaboration and cooperation of many market actors, are rarely present. This study aims at the development and implementation of a virtual carbon trading agenda in the physical-internet-enabled transportation scenario, using multiagent modelling and simulation. Agent-based simulation is considered suitable in this context, for creating a risk-free environment to explore the system contingencies and autonomous decision-makings. Simulation experiments confirm that there is a need to identify a tolerable number of actors presenting in a marketplace as well as the variation of logistical flows in case the paradigm is the Clean Development Mechanism (CDM).