scholarly journals Assessment of the Reduction in Vehicles Emissions by Implementing Inspection and Maintenance Programs

2020 ◽  
Vol 17 (13) ◽  
pp. 4730 ◽  
Author(s):  
José I. Huertas ◽  
Antonio E. Mogro ◽  
Alberto Mendoza ◽  
María E. Huertas ◽  
Rolando Ibarra
Keyword(s):  
Remote Sensing ◽  
Metropolitan Area ◽  
Urban Center ◽  
Single Measurement ◽  
Urban Centers ◽  
Vehicle Inspection ◽  
Vehicles Emissions ◽  
Current Mass ◽  
Inspection And Maintenance

To improve air quality in urban centers, vehicle Inspection and Maintenance (I/M) programs were created to identify highly polluting vehicles and force them to undergo mechanical maintenance. In this context, a methodology, based on a single measurement campaign using a Remote Sensing Device (RSD), is presented in this work to assess the reduction in vehicles emissions obtained from implementing I/M programs. As a case study, an RSD campaign was carried out in Mexico, specifically in Monterrey’s Metropolitan Area (MMA). Approximately 0.4% of the vehicles registered in this region were sampled under similar conditions to those found in I/M programs. The results obtained suggested that 39% of the vehicles would not comply with the current national regulations for circulating vehicles. Following a conservative scenario, the implementation of a vehicle I/M program in this urban center has the potential of reducing the current mass emissions of HC, CO and NO in approximately 69%, 42% and 28%, respectively.

scholarly journals Detecting and Analyzing Urban Centers Based on the Localized Contour Tree Method Using Taxi Trajectory Data: A Case Study of Shanghai

2021 ◽  
Vol 10 (4) ◽  
pp. 220
Author(s):  
Mengqi Sun ◽  
Hongchao Fan
Keyword(s):  
Urban Structure ◽  
Analysis Framework ◽  
Urban Center ◽  
Trajectory Data ◽  
Urban Centers ◽  
Transportation Economics ◽  
Contour Tree ◽  
Tree Method ◽  
Taxi Trajectory

Urban structure is of vital importance to urban planning, transportation, economics and other applications. Since detecting and analyzing urban centers is crucial for understanding urban structure, a large number of studies on urban center extraction have been performed. In this paper, we propose an analysis framework to identify urban centers by using taxi trajectory data. The proposed approach differs from previous methods by employing a novel way to simulate taxi trajectory data with the topographic surface. We extracted pick-up and drop-off spots from taxi trajectory data and employed the localized contour tree method to delineate the boundaries and hierarchies of urban centers. The experiments show that the proposed method can successfully detect urban centers and analyze their temporal patterns in different periods in Shanghai, China.

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