Abstract
Abstract. This paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near-real-time traffic data on road segments to develop a vehicle emission inventory with high temporal–spatial resolution (HTSVE) for the Beijing urban area. To simulate real-world vehicle emissions accurately, the road has been divided into segments according to the driving cycle (traffic speed) on this road segment. The results show that the vehicle emissions of NOx, CO, HC and PM were 10.54 × 104, 42.51 × 104 and 2.13 × 104 and 0.41 × 104 Mg respectively. The vehicle emissions and fuel consumption estimated by the model were compared with the China Vehicle Emission Control Annual Report and fuel sales thereafter. The grid-based emissions were also compared with the vehicular emission inventory developed by the macro-scale approach. This method indicates that the bottom-up approach better estimates the levels and spatial distribution of vehicle emissions than the macro-scale method, which relies on more information. Based on the results of this study, improved air quality simulation and the contribution of vehicle emissions to ambient pollutant concentration in Beijing have been investigated in a companion paper (He et al., 2016).
Highlights
Air pollutants from gases to particulates in megacities are associated with a mixture of various sources, including primary/secondary and natural/anthropogenic sources, and air pollution has become a major human health concern (An et al, 2013)
The purpose of this paper is to develop a high temporal– spatial resolution vehicle emission (HTSVE) inventory for Beijing based on local emission factors and NRT traffic data using a bottom-up methodology
Which indicates that HTSVE can better depict vehicle emissions in temporal and spatial trends. Both a bottom-up methodology using local emission factors and NRT traffic data are applied to estimate the emissions of on-road vehicles in the Beijing urban core area
Summary
Air pollutants from gases to particulates in megacities are associated with a mixture of various sources, including primary/secondary and natural/anthropogenic sources, and air pollution has become a major human health concern (An et al, 2013). Emissions from human activities and natural processes can react with ozone and light to form secondary pollutants, which are more difficult to analyse. Driven by rapid industrialization and urbanization, Beijing, the capital city of China, has received extensive global attention regarding its contribution to the atmospheric environment. Numerical model simulation is a very effective tool for proportionally estimating contributions to air pollution from various sources under certain atmospheric conditions (Cheng et al, 2007; Wang and Xie, 2009). The accuracy of emission source inventory is the key to air quality numerical simulation. There are differing opinions in quantitative research regarding the pollution contribution
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