Comparison of the Real Emissions of Domestic Passenger Cars with the IVE Model

Introduction: From an environmental and human health perspective, air quality management and pollution control from mobile and stationary sources are critically important. Estimating air pollution emissions from vehicles and other mobile sources is a key tool in this field. Given the diversity in vehicle performance under different conditions, this estimation presents significant challenges for researchers and industry professionals. Therefore, the use of accurate and reliable tools for conducting these estimations is essential. In the compilation of national air pollution emission inventories, the International Vehicle Emissions (IVE) modeling software is utilized as a primary tool. This comprehensive software can estimate pollutant emissions from vehicles and other mobile sources, aiding in the development of pollution inventories.
Material and Methods: To investigate pollutant emission levels more accurately, this study involved a comparison between data from the IVE model and measured data from zero-kilometer domestic passenger car emissions. These measurements were conducted using the ISQI laboratory dynamometer test and adhering to Euro 4 emission standards and the New European Driving Cycle (NEDC).
Results and Discussion: The comparison between dynamometer chassis emission test data from domestic vehicles and IVE model-generated data indicates significant differences in emission levels in some cases, highlighting that the IVE model is not closely aligned with reality and requires necessary modifications. Except for one instance where NOx emissions were equivalent with the Quick vehicle, other results showed NOx emissions ranging from 0.01 to 0.05, with the model displaying 0.03. Regarding CO, emissions ranged from 0.26 to 0.96, while the model displayed 0.48. Similarly, HC emissions ranged from 0.03 to 0.08, matching the model's result of 0.03. It is evident that the IVE model cannot accurately reflect real emission values in some instances and requires serious modifications to enhance accuracy in estimating these values.
Conclusion: Managers and decision-makers in air quality and environmental fields should carefully consider research and experimental results. Based on emission analysis, it is clear that the IVE model is not closely aligned with reality and relies on hypothetical conditions for estimating pollutant values, making it unreliable. Necessary improvements are required in the IVE model to enhance assessment quality and performance in air quality and environmental management. Developing approaches and solutions based on accurate and transparent data are crucial and can significantly improve air quality management and pollution reduction. Therefore, the use of accurate and up-to-date data for assessing air pollution from mobile and stationary sources is critically important and requires modification and improvement of the models used for more accurate emission estimations.