Variation of Absorption Ångström Exponent in Aerosols From Different Emission Sources

Aku Helin1, Aki Virkkula1, John Backman1, Liisa Pirjola2,3, Olli Sippula4,5, Päivi Aakko-Saksa6, Sampsa Väätäinen5, Fanni Mylläri7, Anssi Järvinen7, Matthew Bloss1, Minna Aurela1, Gert Jakobi8,9, Panu Karjalainen7, Ralf Zimmermann10,8,9, Jorma Jokiniemi5, Sanna Saarikoski1, Jarkko Tissari5, Topi Rönkkö7, Jarkko V. Niemi11, Hilkka Timonen1
1Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
2Department of Physics, University of Helsinki, Helsinki, Finland
3Department of Technology, Metropolia University of Applied Sciences, Helsinki, Finland
4Department of Chemistry, University of Eastern Finland, Joensuu, Finland
5Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, Finland
6VTT Technical Research Centre of Finland, Finland
7Aerosol Physics Laboratory, Physics Unit, Tampere University, Tampere University, Finland
8Helmholtz Virtual Institute for Complex Molecular Systems in Environmental Health Neuherberg Germany
9Joint Mass Spectrometry Centre, Cooperation Group “Comprehensive Molecular Analytics”, Helmholtz Zentrum München, Neuherberg, Germany
10Analytical Chemistry, Institute of Chemistry, University of Rostock, Rostock, Germany
11Helsinki Region Environmental Services Authority, Helsinki, Finland

Tóm tắt

Abstract

The absorption Ångström exponent (AAE) describes the spectral dependence of light absorption by aerosols. AAE is typically used to differentiate between different aerosol types for example., black carbon, brown carbon, and dust particles. In this study, the variation of AAE was investigated mainly in fresh aerosol emissions from different fuel and combustion types, including emissions from ships, buses, coal‐fired power plants, and residential wood burning. The results were assembled to provide a compendium of AAE values from different emission sources. A dual‐spot aethalometer (AE33) was used in all measurements to obtain the light absorption coefficients at seven wavelengths (370–950 nm). AAE470/950 varied greatly between the different emission sources, ranging from −0.2 ± 0.7 to 3.0 ± 0.8. The correlation between the AAE470/950 and AAE370‐950 results was good (R2 = 0.95) and the mean bias error between these was 0.02. In the ship engine exhaust emissions, the highest AAE470/950 values (up to 2.0 ± 0.1) were observed when high sulfur content heavy fuel oil was used, whereas low sulfur content fuels had the lowest AAE470/950 (0.9–1.1). In the diesel bus exhaust emissions, AAE470/950 increased in the order of acceleration (0.8 ± 0.1), deceleration (1.1 ± 0.1), and steady driving (1.2 ± 0.1). In the coal‐fired power plant emissions, the variation of AAE470/950 was substantial (from −0.1 ± 2.1 to 0.9 ± 1.6) due to the differences in the fuels and flue gas cleaning conditions. Fresh wood‐burning derived aerosols had AAE470/950 from 1.1 ± 0.1 (modern masonry heater) to 1.4 ± 0.1 (pellet boiler), lower than typically associated with wood burning, while the burn cycle phase affected AAE variation.

Từ khóa


Tài liệu tham khảo

10.1016/j.jaerosci.2018.09.005

Aakko‐Saksa P., 2016, Black carbon measurements using different marine fuels

10.1080/02786826.2017.1422236

10.5194/acp-6-3131-2006

10.5194/amt-10-5039-2017

10.1016/j.atmosenv.2017.09.014

10.1016/j.scitotenv.2019.135483

10.1080/02786820500421521

10.1029/2001jd000571

10.1002/jgrd.50171

10.1016/j.atmosenv.2016.09.002

10.5194/acp-17-7175-2017

10.1029/2017JD027818

10.5194/acp-15-3149-2015

10.1016/j.scitotenv.2017.08.263

10.5194/amt-10-2923-2017

10.3390/atmos8120234

10.5194/amt-10-1043-2017

10.5194/amt-8-1965-2015

10.1016/j.atmosenv.2018.09.033

10.5194/acp-19-11235-2019

10.1021/acs.est.5b03868

10.5194/acp-18-14653-2018

10.1002/2017gh000066

10.1016/j.atmosenv.2014.05.042

10.5194/acp-9-8007-2009

10.5194/acp-12-8271-2012

10.1016/j.atmosenv.2013.08.026

10.1016/j.atmosenv.2017.04.034

10.5194/amt-4-1409-2011

10.1016/j.envpol.2019.04.033

10.3390/atmos9010021

10.31083/j.jmcm.2018.01.004

10.5194/acp-7-5727-2007

10.1029/2004JD004999

10.5194/acp-12-6067-2012

10.5194/acp-17-8681-2017

10.1016/j.fuel.2018.06.056

10.5194/acp-18-17843-2018

10.5194/acp-10-4207-2010

10.5194/acp-12-3985-2012

10.5194/acp-13-10535-2013

10.5194/amt-4-445-2011

10.1021/cr5006167

10.1002/2015jd024718

10.5194/acp-18-6259-2018

10.1002/2014gl062443

10.1016/j.scitotenv.2017.11.053

10.5194/acp-17-4265-2017

10.1021/acs.est.5b03205

10.1016/j.jqsrt.2009.02.035

10.1016/j.apenergy.2015.05.115

F. Mylläri 2018 Tampere University of Technology

10.1016/j.combustflame.2016.10.027

10.1080/10962247.2018.1521349

10.1002/2014jd022970

10.1021/acs.est.5b04105

10.5194/acp-16-9549-2016

10.1007/s11356-017-8453-3

10.1021/ef502877c

10.1016/j.atmosenv.2018.03.018

10.1126/science.1133061

10.1021/es052080i

10.1080/02786826.2016.1261992

10.5194/acp-13-7683-2013

10.1021/es702253m

10.1016/j.atmosenv.2007.09.034

10.1016/j.atmosenv.2016.06.023

10.1007/s11356-016-6724-z

10.5194/acp-17-4769-2017

10.1016/j.jaerosci.2017.07.011

10.1016/j.atmosenv.2007.06.018

10.3390/atmos10120775

10.1016/j.scitotenv.2016.11.007

10.5194/amt-2020-438

10.5194/acp-18-289-2018

10.1038/srep43182

10.5194/acp-9-2035-2009

10.1016/j.atmosenv.2016.09.035

10.1016/j.scitotenv.2017.03.057

10.5194/acp-17-4229-2017