High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets

<p>On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple dat...

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Bibliographic Details
Main Authors: D. Yang, S. Zhang, T. Niu, Y. Wang, H. Xu, K. M. Zhang, Y. Wu
Format: Article
Language:English
Published: Copernicus Publications 2019-07-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/19/8831/2019/acp-19-8831-2019.pdf
Description
Summary:<p>On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple datasets extracted from the extensive road traffic monitoring network that covers the entire municipality of Beijing, China (16&thinsp;400&thinsp;km<span class="inline-formula"><sup>2</sup></span>). We employed the EMBEV-Link model under various traffic scenarios to capture the significant variability in vehicle emissions, temporally and spatially, due to the real-world traffic dynamics and the traffic restrictions implemented by the local government. The results revealed high carbon monoxide (CO) and total hydrocarbon (THC) emissions in the urban area (i.e., within the Fifth Ring Road) and during rush hours, both associated with the passenger vehicle traffic. By contrast, considerable fractions of nitrogen oxides (<span class="inline-formula">NO<sub><i>x</i></sub></span>), fine particulate matter (PM<span class="inline-formula"><sub>2.5</sub></span>) and black carbon (BC) emissions were present beyond the urban area, as heavy-duty trucks (HDTs) were not allowed to drive through the urban area during daytime. The EMBEV-Link model indicates that nonlocal HDTs could account for 29&thinsp;% and 38&thinsp;% of estimated total on-road emissions of <span class="inline-formula">NO<sub><i>x</i></sub></span> and PM<span class="inline-formula"><sub>2.5</sub></span>, which were ignored in previous conventional emission inventories. We further combined the EMBEV-Link emission inventory and a computationally efficient dispersion model, RapidAir<sup>®</sup>, to simulate vehicular <span class="inline-formula">NO<sub><i>x</i></sub></span> concentrations at fine resolutions (10&thinsp;m&thinsp;<span class="inline-formula">×</span>&thinsp;10&thinsp;m in the entire municipality and 1&thinsp;m&thinsp;<span class="inline-formula">×</span>&thinsp;1&thinsp;m in the hotspots). The simulated results indicated a close agreement with ground observations and captured sharp concentration gradients from line sources to ambient areas. During the nighttime when the HDT traffic restrictions are lifted, HDTs could be responsible for approximately 10&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula"><sup>−3</sup></span> of <span class="inline-formula">NO<sub><i>x</i></sub></span> in the urban area. The uncertainties of conventional top-down allocation methods, which were widely used to enhance the spatial resolution of vehicle emissions, are also discussed by comparison with the EMBEV-Link emission inventory.</p>
ISSN:1680-7316
1680-7324