Analysis of road traffic noise in an urban area in Croatia using different noise prediction models

Abstract

Abstract Road traffic noise is the second largest environmental stressor in urban areas in Europe after air pollution. The harmful effects of noise arise mainly from the stress response it triggers in the human body, which can have significant consequences for physical and mental health. Therefore, the use of a reliable noise prediction model is an important prerequisite for the quality assessment of a number of residents exposed to excessive noise levels and for the selection of appropriate noise mitigation measures. In this study, the analysis of road traffic noise in an urban street in the narrower centre of the Croatian capital Zagreb was performed using four noise prediction models: "RLS-90", "RLS-19", “NMPB-Routes-96 (SET-RA-CERTU-LCPC-CSTB)”, and “CNOSSOS-EU”. LimA V2021 noise prediction software was used for the analysis, and the noise modelling results were validated with short-term noise measurements. The main objective of the research presented in the article was to test the “CNOSSOS-EU” method, recently introduced in Croatian noise control practice, and to gain initial insights into which of the aforementioned noise prediction models is the most reliable for the assessment of road traffic noise in urban environments in Croatia. A comparison of the noise modelling results with the results of short-term noise measurements has shown that the German national calculation methods “RLS-90” and “RLS-19” as well as the “CNOSSOS-EU” method provide significantly more accurate noise predictions than the “NMPB-Routes-96 (SETRA-CERTU-LCPC-CSTB)” method.