Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Volatility of source apportioned wintertime organic aerosol in the city of Athens
https://orcid.org/0000-0001-8085-9795
AbstractThe volatility distribution of ambient organic aerosol (OA) and its components was measured during the winter of 2013 in the city of Athens combining a thermodenuder (TD) and a High Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS). Positive Matrix Factorization (PMF) analysis of both the ambient and the thermodenuder AMS-spectra resulted in a four-factor solution for the OA, namely: hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking OA (COA), and oxygenated OA (OOA). The thermograms of the four factors were analyzed and the corresponding volatility distributions were estimated using the volatility basis set (VBS). All four factors included compounds with a wide range of effective volatilities from 10 to less than 10−4 μg m−3 at 298 K. Almost 40% of the HOA consisted of low-volatility organic compounds (LVOCs) with the semi-volatile compounds (SVOCs) representing roughly 30%, while the remaining 30% consisted of extremely low volatility organic compounds (ELVOCs). BBOA was more volatile than the HOA factor on average, with 10% ELVOCs, 40% LVOCs, and 50% SVOCs. 10% of the COA consisted of ELVOCs, another 65% LVOCs, and 50% SVOCs. Finally, the OOA was the least volatile factor and included 40% ELVOCs, 25% LVOCs, and 35% SVOCs. Combining the volatility distributions and the O:C ratios of the various factors, we placed our results in the 2D-VBS analysis framework of Donahue et al. (2012). HOA and BBOA are in the expected region but also include an ELVOC component. COA is in similar range as HOA, but on average is half an order of magnitude more volatile. The OOA in these wintertime conditions had a moderate O:C ratio and included both semi-volatile and extremely low volatility components. The above results are sensitive to the assumed values of the effective vaporization enthalpy and the accommodation coefficient. A reduction of the accommodation coefficient by an order of magnitude or the reduction of the vaporization enthalpy by 20 kJ mol−1 results in the increase of the average volatility by half an order of magnitude.
HighlightsThe volatility distribution of ambient organic aerosol components was measured.Fresh biomass burning OA was the most volatile on average.Oxygenated OA was the least volatile on average.Cooking and biomass burning OA had intermediate average volatility.All included some extremely low volatility and semi-volatile compounds.
Volatility of source apportioned wintertime organic aerosol in the city of Athens
https://orcid.org/0000-0001-8085-9795
AbstractThe volatility distribution of ambient organic aerosol (OA) and its components was measured during the winter of 2013 in the city of Athens combining a thermodenuder (TD) and a High Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS). Positive Matrix Factorization (PMF) analysis of both the ambient and the thermodenuder AMS-spectra resulted in a four-factor solution for the OA, namely: hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking OA (COA), and oxygenated OA (OOA). The thermograms of the four factors were analyzed and the corresponding volatility distributions were estimated using the volatility basis set (VBS). All four factors included compounds with a wide range of effective volatilities from 10 to less than 10−4 μg m−3 at 298 K. Almost 40% of the HOA consisted of low-volatility organic compounds (LVOCs) with the semi-volatile compounds (SVOCs) representing roughly 30%, while the remaining 30% consisted of extremely low volatility organic compounds (ELVOCs). BBOA was more volatile than the HOA factor on average, with 10% ELVOCs, 40% LVOCs, and 50% SVOCs. 10% of the COA consisted of ELVOCs, another 65% LVOCs, and 50% SVOCs. Finally, the OOA was the least volatile factor and included 40% ELVOCs, 25% LVOCs, and 35% SVOCs. Combining the volatility distributions and the O:C ratios of the various factors, we placed our results in the 2D-VBS analysis framework of Donahue et al. (2012). HOA and BBOA are in the expected region but also include an ELVOC component. COA is in similar range as HOA, but on average is half an order of magnitude more volatile. The OOA in these wintertime conditions had a moderate O:C ratio and included both semi-volatile and extremely low volatility components. The above results are sensitive to the assumed values of the effective vaporization enthalpy and the accommodation coefficient. A reduction of the accommodation coefficient by an order of magnitude or the reduction of the vaporization enthalpy by 20 kJ mol−1 results in the increase of the average volatility by half an order of magnitude.
HighlightsThe volatility distribution of ambient organic aerosol components was measured.Fresh biomass burning OA was the most volatile on average.Oxygenated OA was the least volatile on average.Cooking and biomass burning OA had intermediate average volatility.All included some extremely low volatility and semi-volatile compounds.
Volatility of source apportioned wintertime organic aerosol in the city of Athens
https://orcid.org/0000-0001-8085-9795
AbstractThe volatility distribution of ambient organic aerosol (OA) and its components was measured during the winter of 2013 in the city of Athens combining a thermodenuder (TD) and a High Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS). Positive Matrix Factorization (PMF) analysis of both the ambient and the thermodenuder AMS-spectra resulted in a four-factor solution for the OA, namely: hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking OA (COA), and oxygenated OA (OOA). The thermograms of the four factors were analyzed and the corresponding volatility distributions were estimated using the volatility basis set (VBS). All four factors included compounds with a wide range of effective volatilities from 10 to less than 10−4 μg m−3 at 298 K. Almost 40% of the HOA consisted of low-volatility organic compounds (LVOCs) with the semi-volatile compounds (SVOCs) representing roughly 30%, while the remaining 30% consisted of extremely low volatility organic compounds (ELVOCs). BBOA was more volatile than the HOA factor on average, with 10% ELVOCs, 40% LVOCs, and 50% SVOCs. 10% of the COA consisted of ELVOCs, another 65% LVOCs, and 50% SVOCs. Finally, the OOA was the least volatile factor and included 40% ELVOCs, 25% LVOCs, and 35% SVOCs. Combining the volatility distributions and the O:C ratios of the various factors, we placed our results in the 2D-VBS analysis framework of Donahue et al. (2012). HOA and BBOA are in the expected region but also include an ELVOC component. COA is in similar range as HOA, but on average is half an order of magnitude more volatile. The OOA in these wintertime conditions had a moderate O:C ratio and included both semi-volatile and extremely low volatility components. The above results are sensitive to the assumed values of the effective vaporization enthalpy and the accommodation coefficient. A reduction of the accommodation coefficient by an order of magnitude or the reduction of the vaporization enthalpy by 20 kJ mol−1 results in the increase of the average volatility by half an order of magnitude.
HighlightsThe volatility distribution of ambient organic aerosol components was measured.Fresh biomass burning OA was the most volatile on average.Oxygenated OA was the least volatile on average.Cooking and biomass burning OA had intermediate average volatility.All included some extremely low volatility and semi-volatile compounds.
Volatility of source apportioned wintertime organic aerosol in the city of Athens
Louvaris, Evangelos E. (Autor:in) / Florou, Kalliopi (Autor:in) / Karnezi, Eleni (Autor:in) / Papanastasiou, Dimitrios K. (Autor:in) / Gkatzelis, Georgios I. (Autor:in) / Pandis, Spyros N. (Autor:in)
Atmospheric Environment ; 158 ; 138-147
24.03.2017
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
When Damages Are Apportioned, Everyone Loses
| ASCE | 2021
Unexpected changes in source apportioned results derived from different ambient VOC metrics
| Elsevier | 2024
Damages for late construction apportioned
Wiley | 1981