Abstract
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.
Highlights
Quantifying the magnitude and trend of anthropogenic air pollutants and greenhouse gas (GHG) emissions from China is of great importance because of their negative impact on the environment and their significant contribution to global emission budgets
Different approaches were developed for these parameters: (1) county-level vehicle population was estimated by citylevel Gompertz functions, which were adjusted by countylevel socio-economic status; (2) province-level technology distribution was calculated by provincial vehicle stock and survival functions and (3) monthly county-level emission factors were simulated by the international vehicle emission (IVE) model using China’s on-road vehicle emission corrections and county-level meteorological corrections
By developing a set of approaches to estimate, for the first time, the vehicle emissions for each county, and introducing the vehicle kilometers traveled (VKT) allocation weights to assign county emissions into grids, our proposed methodology overcomes the common weakness of previous methods, such as, neglecting the geographical differences in crucial parameters of vehicle emissions and using surrogates that are weakly related to vehicle activities to allocate vehicle emissions
Summary
Quantifying the magnitude and trend of anthropogenic air pollutants and greenhouse gas (GHG) emissions from China is of great importance because of their negative impact on the environment and their significant contribution to global emission budgets. The other method estimates emissions at provincial level and allocates total emissions to counties or grids based on surrogates, such as Gross domestic product (GDP) (Cai and Xie, 2007), population density (Wei et al, 2008), or road density (Streets et al, 2003; Ohara et al, 2007; Zhang et al, 2009), by assuming a linear relationship between the surrogates and vehicle emissions of counties or grids within a province These studies often apply national averages for key parameters (such as, technology distributions and vehicle emission factors) to estimate provincial emissions, which can introduce significant errors in the spatial distribution of emissions. There are two important objectives to improve the accuracy and resolution of the vehicle emission inventory of China: (1) to increase the spatial resolution of the key influencing factors of emissions and (2) to develop a gridding method in which the surrogates are strongly related to vehicle activity. The article is organized as follows: in Sect. 2 we describe the methods to determine the countylevel parameters for calculating county-level vehicle emissions and to allocate the emissions onto grids; in Sect. 3 we analyze the results of key parameters, county-level vehicle emissions and gridded emissions; in Sect. 4 we evaluate the new allocation method by comparing with previous methods and by conducting sensitivity analyses for key assumptions; in Sect. 5 we discuss the main uncertainties of the inventory method and the step of future work
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