The main objective of this study is to examine the influence of the transport system on CO2 emission levels. To achieve this goal, first, identify existing interrelationships between transport performance indicators and CO2 emissions was established, and the direction and degree of impact of significant performance indicators of the transport system on emissions were assessed. Next, based on analysis and synthesis of the literature - both domestic and foreign - factors that have the greatest influence on the level of CO2 emissions were identified and systematized. Assuming that there are causal relationships between the amount of CO2 emissions and the performance of the transport system, three hypotheses were put forward. To test the hypotheses, two models - end-to-end regression and regressions with effects - were considered to characterize the dependence of CO2 emissions on transport system performance. Model testing was conducted to choose the best model for analysis. It was found that the fixed-effects regression model is preferable to the random-effects and end-to-end regression models with regard to identifying and assessing the transport system indicators that can be managed to improve environmental conditions in various regions of the Russian Federation.
The complicated geopolitical situation has become a factor in domestic tourism development in the Russian Federation. A significant number of objects of tourist interest have generated increased competition between Russian regions to attract tourists. A necessary condition for increasing tourist flow is the development of tourist infrastructure, including transport. The authors used various types of transport in the vast majority formation of tourist products, as well as in independent tourism. The purpose of this study is to analyse the relationships between tourist flow dynamics and the transportation system development indexes of St. Petersburg and the Leningrad region. Comparative, correlation and regression analyses showed a strong positive correlation between tourist flow and passenger transport by buses and suburban railway transport (especially in St. Petersburg). The study confirmed the problem of data reliability and availability for analysing tourist flow within the St. Petersburg agglomeration, although the palace suburbs, which are popular with tourists, are located within agglomeration boundaries. To solve the problem of tracking tourist flows when using transport in the agglomeration, the authors propose the development and implementation of a transport tourist map with advanced functionality. This digital tool application will allow not only the reliable tracking of tourist flows but also the optimization of the transport system of the St. Petersburg agglomeration. In addition, the analysis of tourist flow dynamics should be used to increase the positive effects of tourism development and reduce the negative effects of overtourism in achieving the sustainable development goals of St. Petersburg and the Leningrad region.