Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Impacts of typical atmospheric dispersion schemes on source inversion
Abstract Accurate source inversion for sudden air pollution accidents (SAPAs) relies on forward dispersion models, and the dispersion parameter scheme is the key factor for modeling performance. However, the impacts of different schemes on source inversion have yet to be investigated. In this study, the performance of source inversion based on four empirical power-law dispersion schemes—BRIGGS, SMITH, Pasquill-Gifford (P-G), and Chinese National Standard (CNS) schemes—was evaluated using the data set from the 1956 Prairie Grass experiment. The inversion performance of each dispersion scheme was assessed with both single (source strength) and multiple (source strength and location) unknown source parameters under six different atmospheric stability classes (A, B, C, D, E, and F) and the schemes exhibited substantially different performances. With a single unknown source parameter, the four schemes demonstrated excellent robustness. The estimation results of BRIGGS, P-G, and CNS exhibited comparable accuracy to similar average absolute relative deviations (ARD, 33.3–37.5%) and better accuracy than SMITH. The CNS scheme performed the best (37.6%) in unstable atmospheric conditions (A, B, and C), P-G and BRIGGS were comparable and performed the best (26.3% and 25.4%, respectively) in neutral atmospheric conditions (D), and the four schemes exhibited similar performances (28.3–31.3%) in stable atmospheric conditions (E and F). When location was also unknown, the source strength accuracy ranking was P-G (31.6%) > SMITH (43.2%) > CNS (50.6%) > BRIGGS (80.1%); however, the robustness of the P-G, SMITH, and CNS schemes was poor. Further analysis revealed that the differences in the schemes' inversion errors were significantly higher than those of algorithms from previous studies, which implies that scheme selection had a greater influence on source inversion than the algorithm selection. The results of this study can improve our understanding of the factors that influence source inversion.
Highlights BRIGGS, P-G and CNS had comparable accuracy and better than SMITH for only Q0 inversion. Accuracy was P-G > SMITH > CNS > BRIGGS, however, BRIGGS was the most robust for Q0 when inversing (Q0, x0, y0). The four schemes had various performances under different dispersion conditions.
Impacts of typical atmospheric dispersion schemes on source inversion
Abstract Accurate source inversion for sudden air pollution accidents (SAPAs) relies on forward dispersion models, and the dispersion parameter scheme is the key factor for modeling performance. However, the impacts of different schemes on source inversion have yet to be investigated. In this study, the performance of source inversion based on four empirical power-law dispersion schemes—BRIGGS, SMITH, Pasquill-Gifford (P-G), and Chinese National Standard (CNS) schemes—was evaluated using the data set from the 1956 Prairie Grass experiment. The inversion performance of each dispersion scheme was assessed with both single (source strength) and multiple (source strength and location) unknown source parameters under six different atmospheric stability classes (A, B, C, D, E, and F) and the schemes exhibited substantially different performances. With a single unknown source parameter, the four schemes demonstrated excellent robustness. The estimation results of BRIGGS, P-G, and CNS exhibited comparable accuracy to similar average absolute relative deviations (ARD, 33.3–37.5%) and better accuracy than SMITH. The CNS scheme performed the best (37.6%) in unstable atmospheric conditions (A, B, and C), P-G and BRIGGS were comparable and performed the best (26.3% and 25.4%, respectively) in neutral atmospheric conditions (D), and the four schemes exhibited similar performances (28.3–31.3%) in stable atmospheric conditions (E and F). When location was also unknown, the source strength accuracy ranking was P-G (31.6%) > SMITH (43.2%) > CNS (50.6%) > BRIGGS (80.1%); however, the robustness of the P-G, SMITH, and CNS schemes was poor. Further analysis revealed that the differences in the schemes' inversion errors were significantly higher than those of algorithms from previous studies, which implies that scheme selection had a greater influence on source inversion than the algorithm selection. The results of this study can improve our understanding of the factors that influence source inversion.
Highlights BRIGGS, P-G and CNS had comparable accuracy and better than SMITH for only Q0 inversion. Accuracy was P-G > SMITH > CNS > BRIGGS, however, BRIGGS was the most robust for Q0 when inversing (Q0, x0, y0). The four schemes had various performances under different dispersion conditions.
Impacts of typical atmospheric dispersion schemes on source inversion
Mao, Shushuai (Autor:in) / Lang, Jianlei (Autor:in) / Chen, Tian (Autor:in) / Cheng, Shuiyuan (Autor:in) / Wang, Chuanda (Autor:in) / Zhang, Junfeng (Autor:in) / Hu, Feng (Autor:in)
Atmospheric Environment ; 232
25.04.2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch