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Top-down vs. bottom-up approaches for enhancing railway emission inventories in the Czech Republic: Towards a hybrid method for national and regional applications

A new study compares approaches to railway emission modelling in the Czech Republic and proposes a hybrid method for more accurate national and regional CO₂ and NOₓ inventories.

Summary

The aim of this article is to compare two approaches to estimating emissions from railway transport in the Czech Republic—top-down and bottom-up—and to assess their suitability for national and regional emission inventories. The article focuses on CO2 and NOx emissions, of which transport in the Czech Republic is a significant producer.

The top-down method, used in the original Transport Research Centre (CDV) emission model and based on aggregated fuel consumption data and Tier 1 emission factors, provides results consistent with national fuel consumption statistics, but shows low emission factor accuracy and produces unreliable regional emission allocations. These shortcomings motivated the development of a more advanced methodological solution. In contrast, the bottom-up approach uses detailed activity data on train operations together with Tier 2 emission factors, enabling more accurate spatial allocation of emissions; however, its total emissions may deviate from official fuel consumption statistics.

Based on an analysis of both methods, a hybrid approach was proposed for the national railway emission inventory, combining the advantages of both methods—the accuracy of bottom-up calculations and the consistency of top-down data. The hybrid method improves the national and regional railway emission inventory, enhances the quality of data for national and international reporting and publications, and supports more effective strategic planning in the railway sector.

Citation

Leoš Pelikán, Ivo Dostál, Zuzana Kačmárová, Anna Tišlerová, Blanka Hablovičová, Top-down vs. bottom-up approaches for enhancing railway emission inventories in the Czech Republic: Towards a hybrid method for national and regional applications, Atmospheric Environment: X, Volume 30, 2026, 100468, ISSN 2590-1621, https://doi.org/10.1016/j.aeaoa.2026.100468.

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