Articles | Volume 14, issue 18
Atmos. Chem. Phys., 14, 9787–9805, 2014

Special issue: East Asia emissions assessment (EA2)

Atmos. Chem. Phys., 14, 9787–9805, 2014

Research article 17 Sep 2014

Research article | 17 Sep 2014

High-resolution mapping of vehicle emissions in China in 2008

B. Zheng1, H. Huo2, Q. Zhang3, Z. L. Yao4, X. T. Wang1, X. F. Yang1, H. Liu1, and K. B. He1 B. Zheng et al.
  • 1State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
  • 2Institute of Energy, Environment and Economy, Tsinghua University, Beijing 100084, China
  • 3Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
  • 4School of Food and Chemical Engineering, Beijing Technology and Business University, Beijing 100048, China

Abstract. This study is the first in a series of papers that aim to develop high-resolution emission databases for different anthropogenic sources in China. Here we focus on on-road transportation. Because of the increasing impact of on-road transportation on regional air quality, developing an accurate and high-resolution vehicle emission inventory is important for both the research community and air quality management. This work proposes a new inventory methodology to improve the spatial and temporal accuracy and resolution of vehicle emissions in China. We calculate, for the first time, the monthly vehicle emissions for 2008 in 2364 counties (an administrative unit one level lower than city) by developing a set of approaches to estimate vehicle stock and monthly emission factors at county-level, and technology distribution at provincial level. We then introduce allocation weights for the vehicle kilometers traveled to assign the county-level emissions onto 0.05° × 0.05° grids based on the China Digital Road-network Map (CDRM). The new methodology overcomes the common shortcomings of previous inventory methods, including neglecting the geographical differences between key parameters and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions. The new method has great advantages over previous methods in depicting the spatial distribution characteristics of vehicle activities and emissions. This work provides a better understanding of the spatial representation of vehicle emissions in China and can benefit both air quality modeling and management with improved spatial accuracy.

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