Bottom-Up Analysis for Carbon Emissions from Urban Passenger and Freight Transport Sectors

Abstract

Road mobile sources are a significant contributor to urban carbon emissions in China. Given China's goal of achieving carbon neutrality by 2060, accurately estimating carbon emissions and their influencing factors is crucial. This study conducted a bottom-up analysis of carbon emissions from passenger and freight vehicles at the city level, utilizing categorical LMDI decomposition models with high-resolution urban vehicle data and the localized MOVES model. The LMDI models assessed the impact of six factors, focusing on microscopic traffic activities such as passenger/freight volume and turnover, vehicle ownership, mileage, carbon emission rate, vehicle types, and fuel types. The key factors influencing passenger and freight emissions were per capita vehicle turnover and freight volume, respectively. Additionally, decoupling analysis using the Tapio model revealed differing trends for passenger and freight transport, providing a scientific foundation for formulating targeted transportation management countermeasures.

Keywords: Road Mobile Source, Carbon Emission, MOVES, LMDI, Tapio