LCA of long life structures and products like cars, planes, infrastructure or buildings are currently performed on a static approach. That includes that the time aspect is not further considered and one single point in time is chosen as reference. This is in case of the production phase an adequate and meaningful assumption as the production period is usually short. But regarding the use phase the time related boundary conditions change so that the LCA results show a more and more dynamic progress. Regarding the end-of-life phase it can be stated that the boundary conditions after a long life time could differ seriously and in case of a big relevance of this life cycle step it is required to adjust the modeling accordingly. The time dimension and the dynamic development of general boundary conditions, legal boundaries, technologies, technical parameters, supply chains and technical systems lead to a variability in the material and energy flow system which influences the LCI results. The impacts to environment depend on emission time, chemical fate and other dynamic effects which influence the LCIA results additionally to the dynamic LCI. So the LCA interpretation should include in addition to the classical steps also an overall consideration of time dynamic aspects in the goal and scope definition, technical system, LCI and LCIA as well as time aspects in the interaction of the different LCA phases. Based on previous own work on parameterized modeling, time series and future scenarios as well as LCA of buildings within the German Sustainable Building Certification System the presentation show temporal influences on LCA and compare static and dynamic modeling approaches. Especially changes within the use phase of a building are analyzed and presented. Using the ZUB-Office-Building in Kassel, Germany, as an example the whole Life Cycle including construction (structural shell of building, roof, floor finish, insulation, plaster, coating, electrical installations, outdoor facilities), use phase (refurbishment, energy supply) and EoL is considered. The results are calculated based on continuous functions for technical parameters (e.g. energy demand, grid mix, district heating supply, ...) over a life-time of 50 years.