4.2 Article

Evaluation of the Relationship between Meteorological Variables and NOx Emission Factors Based on Plume-Chasing Measurements

期刊

ACS ES&T ENGINEERING
卷 3, 期 3, 页码 417-426

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsestengg.2c00317

关键词

PEMS; mobile measurements; vehicle-induced turbulence; nitrogen oxides; emission calculation

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A relationship between meteorological variables and the accuracy of nitrogen oxide emission factors (EFchasing) was developed. An effective ratio concept was proposed to evaluate this relationship and was found to be independent of calculation approaches. The effective ratio can be used to identify erroneous measurements and improve the accuracy of EFchasing.
A relationship that links the accuracy of nitrogen oxide emission factors (NOx EFs) calculated from chasing measurements (EFchasing) to meteorological variables was developed. To quantitatively evaluate this relationship, we postulated an effective ratio concept based on the momentum wake theory. The effective ratio is considered a function of meteorological variables in the vehicle wake. A mobile platform was used to characterize NOx EFs by following tested vehicles that were installed with a portable emission measuring system (PEMS) on a restricted driving track. The relationship was evaluated based on 172 plume-chasing measurements that were conducted under various operating scenarios such as different tested vehicle speeds and vehicle types. Two calculation approaches (i.e., baseline vs rolling minimum) were used to calculate EFchasing and benchmark against NOx EF from PEMS (EFPEMS). A consistent positive linear relationship (slope similar to 28, p < 0.01) is found between the effective ratio and the relative error of EFchasing under all operating scenarios and is independent of calculation approaches. This is evidence that the effective ratio could be a good parameter that quantifies the relative deviation of EFchasing and is independent of calculation approaches. Based on this relationship, the effective ratio can be further used to identify erroneous chasing measurements and improve the accuracy of EFchasing.

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