Biogas production is a relevant component in renewable energy systems. The paper addresses modeling approaches from an energy system, as well as from a process optimization, point of view. Model approaches of biogas production show different levels of detail. They can be classified as white, gray, and black box, or bottom-up and top-down approaches. On the one hand, biogas modeling can supply dynamic information on the anaerobic digestion process, e.g., to predict biogas yields or to optimize the anaerobic digestion process. These models are characterized by a bottom-up approach with different levels of detail: the comprehensive ADM1 (white box), simplifications and abstractions of AD models (gray box), or highly simplified process descriptions (black box). On the other hand, biogas production is included in energy system models. These models usually supply aggregated information on regional biogas potentials and greenhouse gas emissions. They are characterized by a top-down approach with a low level of detail. Most energy system models reported in literature are based on black box approaches. Considering the strengths and weaknesses of the integration of detailed and deeply investigated process models in energy system models reveals the opportunity to develop dynamic and fluctuating business models of biogas usage.

This study quantifies energy consumption and tank-to-wheel (TTW) emissions of urban buses under varying traffic conditions and passenger loads in Osnabrück, Germany, to support emission-aware route assessment in sustainable mobility applications. Exemplary bus trajectories were modeled on a representative 6.17 km route of line M5 (18 m articulated bus; diesel and battery-electric) within a 22.31 km² traffic net using the Simulation of Urban MObility (SUMO) software, and were calibrated with traffic sensor data. To assess the influence of trajectories in different traffic situations, three different 90 min scenarios were compared (morning peak, noon, night). Trajectory-based energy consumption and greenhouse gas emissions were compared by using the SUMO-implemented emission models HBEFA and PHEMlight, as well as data from the literature. Both diesel and electric buses showed variations in energy consumption depending on the traffic conditions, with generally lower energy consumption for electric propulsion. Temporal differences in the TTW emissions of the diesel bus were modest, with slightly higher morning values, while spatial analysis showed PM peaks in pedestrian zones, NO_x peaks during acceleration phases, and CO₂ increases after stops and in low-speed areas. The results provide spatially resolved TTW factors for integration into routing applications, excluding upstream and non-exhaust processes in line with the defined system boundary.

This paper presents a mobile application to encourage sustainable travel in urban areas as a proof-of-concept for user-centred sustainable urban transport. The app provides real-time route evaluation based on the environmental impact of different transport modes and local sensor monitoring feedback. Its core feature is an ecological route assessment using life cycle assessment calculations. Users receive quantitative feedback on their carbon footprint and a mobility score ranging from one (worst, red) to five (best, green). Providing both ecological and time-based navigation assessments, the app generates a comprehensive ecological footprint based on individual behaviour, raising awareness of United Nations climate targets. To increase its appeal, the app integrates a quest model offering vouchers from local partners (e.g., half-priced coffee) and competitions (e.g., complete the most journeys under 5 km by bike or on foot per week). A user-centred development process involving multiple test groups and a physical mock-up has been used to optimize the user interface, concept, and gamification elements. The app will be extended to include location-based quests and interactive chat quizzes. The project addresses key aspects of sustainable individual mobility and could be adapted for other cities, universities, or regions.