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

Nature Communications - Tập 11 Số 1
Fanyuan Deng1, Zhaofeng Lv1, Lijuan Qi1, Xiaotong Wang1, Mengshuang Shi1, Huan Liu1
1State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China

Tóm tắt

AbstractEstimating 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.

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Tập 11 Số 1

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