Literature DB >> 16620907

Comparison of spatiotemporal distribution patterns of NO2 between four different types of air quality monitoring stations.

Hang Thi Nguyen1, Ki-Hyun Kim.   

Abstract

The concentration data of nitrogen dioxide (NO(2)), obtained from four different types of air quality monitoring (AQM) stations in Korea (i.e., urban traffic (A), urban background (B), suburban background (C), and rural background (D)), were explored to evaluate the fundamental facets of its distribution and behavior. As there are many distinctions between these four types of AQM stations, the observed NO(2) values were clearly distinguished from each other. It is found that the average NO(2) concentrations from all A stations exhibit notably high values within the range of 24.8 (Gwangju) to 54.6 ppb (Seoul), while those of all B stations change from 19.6 (Ulsan) to 34.7 ppb (Seoul). Similarly, large differences were also observed from NO(2) values measured between C and D type stations. The NO(2) values of the former were from 16.5 (Jeonbuk) to 30.2 ppb (Gyunggi), while the latter from 4.3 (Gyeongbuk) to 8.7 ppb (Gyunggi). Although their annual patterns are rather complicated to explain, the results by and large reflected the changes in the conditions of the surrounding environment. When the results are compared across seasons, most stations (A, B, and D types) tend to exhibit their maximum values in the winter followed by spring, fall, and summer. The results of this study confirm that the distribution patterns of NO(2) are fairly sensitive enough to reflect the basic characteristics of its source processes in association with such factors as the intensity of anthropogenic activity or population density.

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Year:  2006        PMID: 16620907     DOI: 10.1016/j.chemosphere.2006.02.061

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  1 in total

1.  The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

Authors:  Audrius Dėdelė; Auksė Miškinytė
Journal:  Environ Monit Assess       Date:  2015-08-21       Impact factor: 2.513

  1 in total

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