Dataset Information

A big data approach to improving the vehicle emission inventory in China.

ABSTRACT: Estimating truck emissions accurately would benefit atmospheric research and public health protection. Here, we developed a full-sample enumeration approach TrackATruck to bridge low-frequency but full-size vehicles driving big data to high-resolution emission inventories. Based on 19 billion trajectories, we show how big the emission difference could be using different approaches: 99% variation coefficients on regional total (including 31% emissions from non-local trucks), and ± as large as 15 times on individual counties. Even if total amounts are set the same, the emissions on primary cargo routes were underestimated in the former by a multiple of 2-10 using aggregated approaches. Time allocation proxies are generated, indicating the importance of day-to-day estimation because the variation reached 26-fold. Low emission zone policy reduced emissions in the zone, but raised emissions in upwind areas in Beijing's case. Comprehensive measures should be considered, e.g. the demand-side optimization.

SUBMITTER: Deng F

PROVIDER: S-EPMC7271216 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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A big data approach to improving the vehicle emission inventory in China.

Deng Fanyuan F Lv Zhaofeng Z Qi Lijuan L Wang Xiaotong X Shi Mengshuang M Liu Huan H

Nature communications 20200603 1

Estimating truck emissions accurately would benefit atmospheric research and public health protection. Here, we developed a full-sample enumeration approach TrackATruck to bridge low-frequency but full-size vehicles driving big data to high-resolution emission inventories. Based on 19 billion trajectories, we show how big the emission difference could be using different approaches: 99% variation coefficients on regional total (including 31% emissions from non-local trucks), and ± as large as 15 ...[more]

PMID: 32493934

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Project description:In China, the corresponding control directives for volatile organic compounds (VOCs) have been based on primary emissions, rarely considering reactive speciation. To seek more effective VOCs control strategies, we investigated 107 VOC species in a typical coastal city (Beihai) of South China, from August to November 2018. Meanwhile, a high-resolution anthropogenic VOCs monthly emission inventory (EI) was established for 2018. For source apportionments (SAs) reliability, comparisons of source structures derived from positive matrix factorization (PMF) and EI were made mainly in terms of reaction losses, uncertainties and specific ratios. Finally, for the source-end control, a comprehensive reactivity control index (RCI) was established by combing SAs with reactive speciation profiles. Ambient measurements showed that the average concentration of VOCs was 26.38 ppbv, dominated by alkanes (36.7%) and oxygenated volatile organic compounds (OVOCs) (29.4%). VOC reactivity was estimated using ozone formation potential (52.35 ppbv) and propylene-equivalent concentration (4.22 ppbv). EI results displayed that the entire VOC, OFP, and propylene-equivalent emissions were 40.98 Gg, 67.98 Gg, and 105.93 Gg, respectively. Comparisons of source structures indicated that VOC SAs agreed within ±100% between two perspectives. Both PMF and EI results showed that petrochemical industry (24.0% and 33.0%), food processing and associated combustion (19.1% and 29.2%) were the significant contributors of anthropogenic VOCs, followed by other industrial processes (22.2% and 13.3%), transportation (18.9% and 12.0%), and solvent utilization (9.1% and10.5%). Aimed at VOCs abatement according to RCI: for terminal control, fifteen ambient highly reactive species (predominantly alkenes and alkanes) were targeted; for source control, the predominant anthropogenic sources (food industry, solvent usage, petrochemical industry and transportation) and their emitted highly reactive species were determined. Particularly, with low levels of ambient VOC and primary emissions, in this VOC and NOx double-controlled regime, crude disorganized emission from food industry contributed a high RCI.

Dataset Information

A big data approach to improving the vehicle emission inventory in China.

Publications

A big data approach to improving the vehicle emission inventory in China.

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