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  • Title: China 6 moving average window method for real driving emission evaluation: Challenges, causes, and impacts.
    Author: Wang Y, Yin H, Wang J, Hao C, Xu X, Wang Y, Yang Z, Hao L, Tan J, Wang X, Ge Y.
    Journal: J Environ Manage; 2022 Oct 01; 319():115737. PubMed ID: 35982557.
    Abstract:
    The light-duty moving average window (MAW) method, used for China 6 real driving emission (RDE) calculation, is quite complex with various boundaries. Previous research noticed that the MAW might underestimate the calculation results, while the reasons for this underestimation haven't been studied systematically. With 29 vehicles tested in 10 cities and different boundaries applied for calculation, this study quantitively analyzed the problem, causes, and impacts of the light-duty MAW method. The instantaneous utilization factor (IUF) is proposed for reason analysis. The current MAW method could weaken the supervision of real driving tests as more than 75% of the tests underestimated MAW results, with the largest underestimation being around 100%. The data exclusion could lead to biased MAW results. But without the exclusion, the MAW result couldn't always get an increase due to the IUF and window weighting factor variation. With the extended factors removed, the MAW result bias is significantly reduced. The MAW will lead to a lower IUF of the data at the start/end of the tests, and when the cold-start data is considered, this low utilization must be noticed. The effect from the data exclusion, extended factors, and the window characteristics are closely coupled and they should be taken into consideration simultaneously to consummate the calculation method. The current drift-check progress couldn't effectively monitor the portable emission measurement system (PEMS), especially during the tests. The MAW result might lead to unreasonable emission limits and the emission inventory. Relevant policy based on these results might be implausible.
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