Performance of Back-Trajectory Statistical Methods and Inverse Modeling Method in Locating Emission Sources

• Main Authors: Saito, Takuya (Author), Park, Sunyoung (Author), Li, Shanlan (Author), Yokouchi, Yoko (Author), Fang, Xuekun (Contributor), Prinn, Ronald G (Contributor)
• Other Authors: Massachusetts Institute of Technology. Center for Global Change Science (Contributor), Prinn, Ronald (Contributor)
• Format: Article
• Language: English
• Published: American Chemical Society (ACS), 2019-02-28T16:48:47Z.
• Subjects: Article
• Online Access: Get fulltext

 Back-trajectory statistical methods, for example, potential source contribution functions (PSCF) and concentration-weighted trajectory (CWT) methods, have been widely used in previous studies to locate emission source regions of air pollutants or greenhouse gases. Inverse modeling methods have been developed and used in an increasing number of applications. To this date, there are no comparisons of performance between back-trajectory statistical and inverse modeling methods. This study evaluates the performance of PSCF, CWT, and inverse modeling methods by taking advantage of precisely known locations of trifluoromethane (CHF3; HFC-23) sources. Results show poor performance of the PSCF and CWT methods and good performance of the inverse modeling method. This study suggests that in studies with the purpose of locating emission source regions the PSCF and CWT methods should be applied with caution in future studies and that the inverse modeling method is encouraged to be used much more widely. Keywords: emission source; FLEXPART; HYSPLIT; inverse modeling; source attribution; trajectory; Trajectory statistical methods