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

Yang, Daoyuan; Zhang, Shaojun; Niu, Tianlin; Wang, Yunjie; Xu, Honglei; Zhang, K. Max; Wu, Ye

doi:https://doi.org/10.5194/acp-19-8831-2019

Articles | Volume 19, issue 13

https://doi.org/10.5194/acp-19-8831-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-19-8831-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 13

Research article

|

11 Jul 2019

Research article |

| 11 Jul 2019

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

Daoyuan Yang, Shaojun Zhang, Tianlin Niu, Yunjie Wang, Honglei Xu, K. Max Zhang, and Ye Wu

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Final revised paper (published on 11 Jul 2019)
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Preprint (discussion started on 18 Feb 2019)
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Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review of ACP-2019-32', Anonymous Referee #2, 18 Mar 2019
RC2: 'overall comments', Anonymous Referee #3, 09 Apr 2019
AC1: 'Authors' response document to the review comments', Ye Wu, 19 Apr 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Ye Wu on behalf of the Authors (19 Apr 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (02 May 2019) by Chul Han Song

RR by Anonymous Referee #2 (08 May 2019)

RR by Anonymous Referee #1 (15 May 2019)

Suggestions for revision or reasons for rejection

Yang et al. manuscript discussed an important issue of on-road mobile source emissions estimation based on the real-world traffic data. Overall, I think it is a good paper to be published after a few improvements. Based on my review, I would like to share a few comments and suggestions with authors.

1. While this paper covers well on on-road vehicle emissions from running exhaustion process, it lacks on addressing another critical vehicle emissions from evaporative processes which occur from on-road and oﬀ-network. Although authors mentioned in the manuscript that their study is limited to cover evaporative emissions due to the spatial coverage issue, it is very important to cover the evaporative emissions since they could contribute up to 30-40% of total emissions from vehicles depending on the regions. At least authors can provide more detail information on why they are estimating evaporative emissions other than spatial coverage issue.
2. Mobile source emissions, especially in a megacity like Beijing, are known to be a signiﬁcant contributor of not only primary but secondary air pollution. Chemical characteristics of hydrocarbon emissions from mobile sources are very important to correctly understand secondary formation. I suggest authors to describe relationship between THC to NMVOCs at least, and more preferably include some level of discussion on major chemical species emissions by vehicle type.
3. It would be nice to see the ﬂow diagram ﬁgure of EMBEV-Link (Core-programs/modules with inputs and outputs) to understand the model structure better.
4. It also shows why high-resolution activity data like hourly average speed, traﬃc density and VKT by each link can enhance the quality of hourly emissions. However, the hourly average speed calculated by congestion by link could also provide a biased speed-sensitive emissions since there should be more than a single speed value to present the traﬃc pattern during the congestion. The average speed would be most frequent speed during the traﬃc hour but there are higher and lower speed to be considered. Authors can easily ﬁnd several journal papers that describe the importance of using average speed distribution factors by speed bins instead of a single average speed value. Although there is a merit to their approach to compute hourly average speed value, I think it should also mention about the future study on comparing the results against to the average speed distribution factors.
5. Although authors pointed out the importance of NOx emissions from HDT outside of Five Rings, it does not mention the sensitivity of diesel engine to local meteorological condition. It is a known fact that NOx from diesel vehicle shows a signiﬁcant dependency to local ambient temperature and humidity. While covering this section will be out of scope of paper at this point, I think it is important for authors at least to mention its potential local meteorological condition impacts to NOx emissions from HDT as well and what might be the impacts from it.
6. It is also not within the scope of this paper but it should consider to mention about how the EMBEV-Link can be updated to implemented to support photochemical modeling system other than a dispersion modeling system.

Referee Report: PDF

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ED: Publish subject to minor revisions (review by editor) (22 May 2019) by Chul Han Song

AR by Ye Wu on behalf of the Authors (04 Jun 2019) Author's response Manuscript

ED: Publish as is (13 Jun 2019) by Chul Han Song

AR by Ye Wu on behalf of the Authors (14 Jun 2019) Manuscript

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Short summary

Our work developed a high-resolution emission inventory (EMBEV-Link) with extensive traffic data covering the entire city of Beijing, which mapped the heterogeneity of road emissions associated with traffic dynamics. Nonlocal trucks accounted for substantial emissions (e.g., ~ 30 % of NO_x), though they are missing in previous inventories. EMBEV-Link can support fine-grained dispersion modeling (e.g., 1 m × 1 m at hotspots) and mitigate the uncertainty in top-down emission mapping.