Redirigiendo al acceso original de articulo en 16 segundos...
Inicio  /  Atmósfera  /  Vol: 27 Núm: 2 Par: 0 (2014)  /  Artículo
ARTÍCULO
TITULO

Inference of surface concentrations of nitrogen dioxide (NO2) in Colombia from tropospheric columns of the ozone measurement instrument (OMI)

JOHN FREDDY GRAJALES    
ASTRID BAQUERO-BERNAL    

Resumen

For the first time, maps of surface concentration of nitrogen dioxide (NO2) are presented for the Colombian territory. NO2 surface concentrations for the year 2007 are inferred based on two sources of tropospheric NO2 column data: (1) a simulation using a three-dimensional global model (GEOS-Chem) and (2) measurements made by the ozone monitoring instrument (OMI) onboard the NASA Aura satellite. Results show monthly averages between 0.1 and 6 ppbv. We compare these inferred values to corrected ground measurements of NO2. We find correlation coefficients of up to 0.91 between the inferred data and the corrected observational data. A significant source of NO2 is biomass burning, which can be diagnosed by data of fire radiative power (FRP) from the Monitoring of Atmospheric Composition and Climate (MACC) reanalysis. We find a close relationship between high values of inferred NO2 surface concentrations and biomass burning for a large area which encompasses the departments of Caquetá, Meta, Guaviare, Vichada, and Putumayo.

 Artículos similares

       
 
Hegazy Rezk, A. G. Olabi, Mohammad Ali Abdelkareem, Ali Alahmer and Enas Taha Sayed    
The use of green hydrogen as a fuel source for marine applications has the potential to significantly reduce the carbon footprint of the industry. The development of a sustainable and cost-effective method for producing green hydrogen has gained a lot of... ver más

 
Chunyi Zhang, Zheshan Yuan, Huan Li, Jiongran Wen, Shengkai Zheng and Chengwei Fei    
To enhance the accuracy and efficiency of reliability analysis for an aero-engine vectoring exhaust nozzle (VEN), a multi-extremum adaptive fuzzy network (MEAFN) method is developed by absorbing an adaptive neuro-fuzzy inference system (ANFIS) into the m... ver más
Revista: Aerospace

 
Shenghan Zhou, Tianhuai Wang, Linchao Yang, Zhao He and Siting Cao    
This paper aims to build a Self-supervised Fault Detection Model for UAVs combined with an Auto-Encoder. With the development of data science, it is imperative to detect UAV faults and improve their safety. Many factors affect the fault of a UAV, such as... ver más
Revista: Aerospace

 
Anete Vagale    
Autonomous surface vehicles need to be at least as safe as conventional vessels, if not safer, when navigating on waters. With a great deal of navigation algorithms for surface vessels out there, the safety of their produced paths is questionable, and, i... ver más

 
Xin Li, Cheng Wang, Haijuan Ju and Zhuoyue Li    
Aiming at the problems of low efficiency and poor accuracy in conventional surface defect detection methods for aero-engine components, a surface defect detection model based on an improved YOLOv5 object detection algorithm is proposed in this paper. Fir... ver más
Revista: Applied Sciences