scholarly journals Polycyclic Aromatic Hydrocarbon Concentration Levels on the Korean Peninsula between 2006 and 2008

2010 ◽  
Vol 10 ◽  
pp. 20-37 ◽  
Author(s):  
Hang Thi Nguyen ◽  
Ki-Hyun Kim ◽  
C.-J. Ma ◽  
J.-M. Oh
Keyword(s):  
Polycyclic Aromatic Hydrocarbon ◽  
Aromatic Hydrocarbon ◽  
Fossil Fuels ◽  
Anthropogenic Activities ◽  
Data Sets ◽  
Polycyclic Aromatic Hydrocarbon Concentration ◽  
Land Use Types ◽  
Polycyclic Aromatic ◽  
Different Levels ◽  
Concentration Levels

Concentrations of seven polycyclic aromatic hydrocarbon (PAH) compounds — benzo(a)anthracene (BaA), chrysene (CHRY), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene (BkF), dibenz(a,h)anthracene (DahA), indeno(1,2,3-cd)pyrene (I123P), and benzo(a)pyrene (BaP) — in air were measured as the sum of gas and particle fractions at 32 monitoring stations dispersed across Korea during a 2-year period (February 2006 to January 2008). The data sets were collected at intervals of 1 day (24 h) per month from each monitoring station. According to our analysis, the spatial distribution of PAH is distinguished by manmade activities between different land use types. Evaluation of total PAH (T-PAH) concentration levels, which were derived by summing up all individual compounds, revealed that the T-PAH value varied on the order of commercial (4.85 ± 4.40 ng m-3) rural (4.42 ± 2.73 ng m-3), industrial (4.27 ± 1.79 ng m-3), greenland (3.09 ± 3.86 ng m-3), and background (2.60 ± 2.54 ng m-3) areas. The PAH values, when compared across seasons, tend to peak consistently during the winter (or spring) due to the active consumption of fossil fuels. The overall results of this study confirm that the pollution status of PAH compounds are clearly discernible not only between areas with different levels of anthropogenic activities, but also between periods with changes in environmental conditions.

scholarly journals Learning mid-IR emission spectra of polycyclic aromatic hydrocarbon populations from observations

2019 ◽  
Vol 632 ◽  
pp. A84 ◽  
Author(s):  
S. Foschino ◽  
O. Berné ◽  
C. Joblin
Keyword(s):  
Polycyclic Aromatic Hydrocarbon ◽  
Aromatic Hydrocarbon ◽  
Spectral Data ◽  
Spectral Resolution ◽  
Large Data ◽  
Chemical Diversity ◽  
Large Data Sets ◽  
Data Sets ◽  
Data Set ◽  
Polycyclic Aromatic

Context. The James Webb Space Telescope (JWST) will deliver an unprecedented quantity of high-quality spectral data over the 0.6−28 μm range. It will combine sensitivity, spectral resolution, and spatial resolution. Specific tools are required to provide efficient scientific analysis of such large data sets. Aims. Our aim is to illustrate the potential of unsupervised learning methods to get insights into chemical variations in the populations that carry the aromatic infrared bands (AIBs), more specifically polycyclic aromatic hydrocarbon (PAH) species and carbonaceous very small grains (VSGs). Methods. We present a method based on linear fitting and blind signal separation (BSS) for extracting representative spectra for a spectral data set. The method is fast and robust, which ensures its applicability to JWST spectral cubes. We tested this method on a sample of ISO-SWS data, which resemble most closely the JWST spectra in terms of spectral resolution and coverage. Results. Four representative spectra were extracted. Their main characteristics appear consistent with previous studies with populations dominated by cationic PAHs, neutral PAHs, evaporating VSGs, and large ionized PAHs, known as the PAHx population. In addition, the 3 μm range, which is considered here for the first time in a BSS method, reveals the presence of aliphatics connected to neutral PAHs. Each representative spectrum is found to carry second-order spectral signatures (e.g., small bands), which are connected with the underlying chemical diversity of populations. However, the precise attribution of theses signatures remains limited by the combined small size and heterogeneity of the sample of astronomical spectra available in this study. Conclusions. The upcoming JWST data will allow us to overcome this limitation. The large data sets of hyperspectral images provided by JWST analysed with the proposed method, which is fast and robust, will open promising perspectives for our understanding of the chemical evolution of the AIB carriers.

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