Yeti 1.0: a generalized framework for constructing bottom-up emission inventories from traffic sources at road-link resolutions

Abstract

Abstract. This paper outlines the development and operation of Yeti, a bottom-up traffic emission inventory framework written in the Python 3 scripting language. A generalized representation of traffic activity and emission data affords a high degree of scalability and flexibility in the use and execution of Yeti, while accommodating a wide range of details on topological, traffic, and meteorological data. The resulting traffic emission data are calculated at a road-level resolution on an hourly basis. Yeti is initially applied to traffic activity and fleet composition data provided by the senate administration for the city of Berlin, which serves as the region of interest, where the Yeti-calculated emissions are highly consistent with officially reported annual aggregate levels, broken down according to different exhaust and non-exhaust emission modes. Diurnal emission profiles on select road segments show not only the dependence on traffic activities but also on road type and meteorology. These road-level emissions are further classified on the basis of vehicle categories and Euro emission classes, and the results obtained confirmed the observations of the city of Berlin and subsequent rectifications.