The paper compares the emissions from vehicles including ICEVs (internal combustion engine vehicles) with equivalent emissions from BEVs (battery electric vehicles). Additionally, it analyzes the available source research and the specific energy mix for Poland based on carbon. Mathematical calculations estimate air pollutant emissions. To carry out the analysis and calculations, data were provided by the manufacturers of electricity consumption in the case of vehicles equipped with electric motors and the COPERT model for internal combustion engines. Air pollutants are considered: CO₂, NO_x, SO_x, CO, and Total Suspended Particles (TSP). In addition to exhaust emissions, all solids emissions from road abrasion and tire and brake wear are also considered. The emission of pollutants is estimated based on the emission factors using the average mileage in Polish conditions. The paper compares emissions for three scenarios considering electric vehicles, combustion engine cars, and hybrid cars. Analyses show that introducing cars with electric engines into traffic at the expense of withdrawing vehicles with internal combustion engines is not favorable in Polish conditions. The analysis indicates that CO, CO_2, and TSP emissions have decreased, while NO_x and SO_x emissions have increased.

This article compares the equivalent emissions from battery electric vehicles (BEVs) with those of internal combustion engines vehicles (ICEVs) and and hybrid vehicles (HV). The considerations focused on the dependence of the equivalent emission from electric cars on the official/national Polish energy mix (which is still mainly based on hard coal). The results of mathematical simulations of the impact of the fuel type on pollutants’ emissions are presented. The article also focuses on the effects of the fuel used in internal combustion engines vehicles (LPG, CNG, petrol, diesel, hydrogen) and the official/national Polish energy mix for battery electric vehicles on carbon dioxide (CO2), nitrogen oxides (NOX), particulate matter (PM), carbon monoxide (CO) and sulphur dioxide (SO2) emissions.

The road transport sector is a key source of carbon dioxide and air pollutants. Mathematical modeling is frequently used to assess the sector’s contribution to the total national emissions budget (inventory). The present article focuses on studying the impacts of the fuel used (LPG, CNG, gasoline, diesel, and biofuel), the Euro standard, and the structure of vehicles on CO₂, NO_X, and PM2.5 emissions. This paper presents the results of mathematical simulations of the influence of the fuel type and Euro standards on pollutant emissions. Two scenarios were considered in terms of the effect on CO₂, NO_X, and PM2.5 emissions: one focused on changing the current fleet and introducing Euro 6/VI vehicles, and the second scenario focused on cities adding low-pollution zones (only Euro 6 vehicles and PHEVs, HEVs, and BEVs entering the city). The results of the simulations showed that Euro 6/IV vehicles emit significantly less PM2.5 and NO_X, and biofuels can substantially contribute to reducing emissions.

Using the standardised SORT, the article analyses instantaneous energy consumption and recuperation processes in an electric bus. The test includes three scenarios: SORT 1 (heavy urban traffic), SORT 2 (mixed driving conditions), and SORT 3 (suburban routes), enabling precise assessment of the energy efficiency of vehicles while eliminating environmental variables. The recuperation system significantly enhances energy efficiency, though its effectiveness varies based on the driving scenario. Modelling methods were compared as follows: linear regression, KNN algorithms, and neural networks, achieving a high fit (R² > 90%). While KNN and neural networks were better at reproducing nonlinearities, they indicated the need for additional variables and time delays to enhance accuracy. The article sets itself apart by incorporating predictive models and examining recuperation efficiency across various scenarios. It emphasizes the importance of combining SORT results with real operational data and developing adaptive energy management systems. The results indicate the potential for optimizing electric buses for public transport, including route planning and further improving recuperation technology, which can significantly reduce energy consumption and greenhouse gas emissions.

Assessing vehicle emissions is crucial for understanding their environmental impact and developing effective emission reduction strategies. This article discusses modern research tools that combine traditional laboratory measurements on chassis dynamometers with advanced theoretical models. Probabilistic methods, including stochastic processes based on Markov and semi-Markov chains, are important tools for modelling driving cycles, considering the variability of road conditions and driver behaviour. The article also presents mathematical approaches to emission data analysis, considering both the states of the technical system and the transitions between them, which allows for precise modelling of real vehicle operating conditions. Ultimately, the synergy of experimental measurements with computational modelling offers a more complete and accurate tool for assessing pollutant emissions, which is crucial in global efforts to improve air quality.

The progression of passenger vehicles is progressing, and regulations are continually being revised, resulting in a decrease in car exhaust emissions. The European Commission has revised the RDE test procedure to include exhaust emissions during a cold start, as part of package 3. The article carried out simulations using COPERT software, which uses tests based on WLTP, assuming ambient temperatures from -10◦C to +20◦C, at intervals of 5◦C. This paper aims to present the results of mathematically modelling the influence of ambient temperature on the cold-start emissions of carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOC), hydrocarbons (treated as Volatile organic compounds - VOC), total particulate matter (TSP) and particle number (PN) in passenger cars and light-duty vehicles. The modelling results show that a change in ambient temperature significantly affects carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOC), hydrocarbons (treated as Volatile organic compounds - VOC), total particulate matter (TSP) and particle number (PN) in cold-start emissions.