2021
DOI: 10.1016/j.apr.2021.101095
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Wet scavenging process of particulate matter (PM10): A multivariate complex network approach

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Cited by 15 publications
(3 citation statements)
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“…In our fault estimation simulation, the actuator fault is considered, and thus Φ j,t = B j,t for each node. Then, the parameters of the fault estimator can be determined according to ( 39)- (43). Furthermore, Assumption 3 can be verified with Let us consider the following faults for the first and third nodes:…”
Section: Illustrationsmentioning
confidence: 99%
See 1 more Smart Citation
“…In our fault estimation simulation, the actuator fault is considered, and thus Φ j,t = B j,t for each node. Then, the parameters of the fault estimator can be determined according to ( 39)- (43). Furthermore, Assumption 3 can be verified with Let us consider the following faults for the first and third nodes:…”
Section: Illustrationsmentioning
confidence: 99%
“…With the increase of system scales in modern industrial processes, complex networks have been gaining momentum since they can be used to characterize the interactions between different nodes. Complex networks have been successfully applied to the modeling of various systems such as smart grid [9], particulate matter [43], maritime traffic [2], epidemic spread [36], and mutual funds [7]. In a complex network, the dynamics of every node is affected by its neighboring nodes, and the interconnections between different nodes are reflected in the coupling relationships.…”
Section: Introductionmentioning
confidence: 99%
“…Many studies have already shown that Barbados (see Figure 1) is the first Caribbean island impacted by dust outbreaks (Prospero et al, 1970;Chiapello et al, 2005;Zuidema et al, 2019). Dry deposition (gravitational settling) and wet deposition (precipitation and cloud sweeping) are the two main processes that will remove these mineral dust from the atmosphere (Schepanski, 2018;Plocoste et al, 2021a). In other words, the further one moves away from the African coast, the lower the concentrations of PM 10 linked to mineral dust.…”
Section: Seasonal Analysismentioning
confidence: 99%