The transportation of dangerous goods (TDG) is a critical component of economic systems, especially in regions such as the Western Balkans (WB), where infrastructure and regulatory frameworks face significant challenges. This study assesses the current state of transportation of dangerous goods in Albania, Montenegro, Bosnia and Herzegovina, and Kosovo*, focusing on the alignment of national regulations with international standards such as the ADR agreement. Using a structured questionnaire distributed to 847 stakeholders, key barriers are identified, including inadequate infrastructure, insufficient training, limited oversight and low public awareness. Statistical analyses, including paired t-tests, reveal significant differences in perceptions across the countries surveyed, indicating inequalities in implementation and enforcement. Despite these challenges, there are opportunities to close gaps through targeted investments in infrastructure, increased training programs, stricter compliance and regional cooperation. The findings underscore the need for comprehensive data collection systems and advanced risk assessment tools to improve safety and efficiency. This study contributes to a deeper understanding of TDG issues in the WB countries and provides actionable recommendations for policy makers and practitioners to promote safer and more sustainable practices. The region can improve its TDG framework by addressing these challenges and ensuring economic growth and public safety while minimizing environmental risks.

This research aims to examine the traffic noise levels and to improve the performances of the Calculation of Road Traffic Noise model (C.R.T.N.) by applying the statistical multiple linear regression approach. Research methods included traffic noise level measurements with a noise measuring device in an urban area, using a sampling method in different periods. An evaluation of the measured data and prediction results was performed. Based on the predicted values of the C.R.T.N. model and coefficient of determination (R2), multi-linear regression was carried out to determine statistically significant parameters. The obtained multi-linear regression equation defined a new form of C.R.T.N. model. When applying the new improved version based on the C.R.T.N. model, higher accuracy of prediction is achievable. It can be seen that by applying multi-linear regression, the obtained prediction values are acceptably equated with field measurements in the chosen research environment. So, in this way, the differences between the predicted values of the noise level and the values measured in the field were minimized. Finally it can be concluded that when applying the new improved version based on the C.R.T.N. model, higher accuracy of prediction is achievable.