Literature DB >> 18522112

Using aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions to particulate matter.

Jisca Sandradewi1, Andre S H Prévôt, Sönke Szidat, Nolwenn Perron, M Rami Alfarra, Valentin A Lanz, Ernest Weingartner, Urs Baltensperger.   

Abstract

A source apportionment study was performed for particulate matter in the small village of Roveredo, Switzerland, where more than 70% of the households use wood burning for heating purposes. A two-lane trans-Alpine highway passes through the village and contributes to the total aerosol burden in the area. The village is located in a steep Alpine valley characterized by strong and persistent temperature inversions during winter, especially from December to February. During two winter and one early spring campaigns, a seven-wavelength aethalometer, high volume (HIVOL) samplers, an Aerodyne quadrupole aerosol mass spectrometer (AMS), an optical particle counter (OPC), and a Sunset Laboratory OCEC analyzer were deployed to study the contribution of wood burning and traffic aerosols to particulate matter. A linear regression model of the carbonaceous particulate mass in the submicrometer size range CM(PM1) as a function of aerosol light absorption properties measured by the aethalometer is introduced to estimate the particulate mass from wood burning and traffic (PM(wb), PM(traffic)). This model was calibrated with analyses from the 14C method using HIVOL filter measurements. These results indicate that light absorption exponents of 1.1 for traffic and 1.8-1.9 for wood burning calculated from the light absorption at 470 and 950 nanometers should be used to obtain agreement of the two methods regarding the relative wood burning and traffic emission contributions to CM(PM1) and also to black carbon. The resulting PM(wb) and PM(traffic) values explain 86% of the variance of the CM(PM1) and contribute, on average, 88 and 12% to CM(PM1), respectively. The black carbon is estimated to be 51% due to wood burning and 49% due to traffic emissions. The average organic carbon/total carbon (OC/TC) values were estimated to be 0.52 for traffic and 0.88 for wood burning particulate emissions.

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Year:  2008        PMID: 18522112     DOI: 10.1021/es702253m

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  20 in total

Review 1.  Why air quality in the Alps remains a matter of concern. The impact of organic pollutants in the alpine area.

Authors:  P Schroeder; C A Belis; J Schnelle-Kreis; R Herzig; A S H Prevot; M Raveton; M Kirchner; M Catinon
Journal:  Environ Sci Pollut Res Int       Date:  2013-09-18       Impact factor: 4.223

2.  Measured Wavelength-Dependent Absorption Enhancement of Internally Mixed Black Carbon with Absorbing and Nonabsorbing Materials.

Authors:  Rian You; James G Radney; Michael R Zachariah; Christopher D Zangmeister
Journal:  Environ Sci Technol       Date:  2016-07-14       Impact factor: 9.028

3.  Characteristics and source apportionment of winter black carbon aerosols in two Chinese megacities of Xi'an and Hong Kong.

Authors:  Qian Zhang; Zhenxing Shen; Zhi Ning; Qiyuan Wang; Junji Cao; Yali Lei; Jian Sun; Yaling Zeng; Dane Westerdahl; Xin Wang; Linqing Wang; Hongmei Xu
Journal:  Environ Sci Pollut Res Int       Date:  2018-10-02       Impact factor: 4.223

4.  Characteristics and source apportionment of black carbon aerosols over an urban site.

Authors:  T A Rajesh; S Ramachandran
Journal:  Environ Sci Pollut Res Int       Date:  2017-02-10       Impact factor: 4.223

5.  Temporal and spatial variations of PM2.5 organic and elemental carbon in Central India.

Authors:  Rakesh Kumar Sahu; Shamsh Pervez; Judith C Chow; John G Watson; Suresh Tiwari; Abhilash S Panicker; Rajan K Chakrabarty; Yasmeen Fatima Pervez
Journal:  Environ Geochem Health       Date:  2018-03-30       Impact factor: 4.609

6.  High abundances of dicarboxylic acids, oxocarboxylic acids, and α-dicarbonyls in fine aerosols (PM2.5) in Chengdu, China during wintertime haze pollution.

Authors:  Xiao-Dong Li; Zhou Yang; Pingqing Fu; Jing Yu; Yun-Chao Lang; Di Liu; Kaori Ono; Kimitaka Kawamura
Journal:  Environ Sci Pollut Res Int       Date:  2015-04-28       Impact factor: 4.223

7.  Solar absorption by elemental and brown carbon determined from spectral observations.

Authors:  Ranjit Bahadur; Puppala S Praveen; Yangyang Xu; V Ramanathan
Journal:  Proc Natl Acad Sci U S A       Date:  2012-10-08       Impact factor: 11.205

8.  Determination of wood burning and fossil fuel contribution of black carbon at Delhi, India using aerosol light absorption technique.

Authors:  S Tiwari; A S Pipal; A K Srivastava; D S Bisht; G Pandithurai
Journal:  Environ Sci Pollut Res Int       Date:  2014-09-14       Impact factor: 4.223

9.  Impact of Restrictive Measures during the Covid-19 Pandemic on Aerosol Pollution of the Atmosphere of the Moscow Megalopolis.

Authors:  O B Popovicheva; M A Chichaeva; N S Kasimov
Journal:  Her Russ Acad Sci       Date:  2021-06-10       Impact factor: 0.560

10.  Impacts of COVID-19 on Black Carbon in Two Representative Regions in China: Insights Based on Online Measurement in Beijing and Tibet.

Authors:  Yue Liu; Yinan Wang; Yang Cao; Xi Yang; Tianle Zhang; Mengxiao Luan; Daren Lyu; Anthony D A Hansen; Baoxian Liu; Mei Zheng
Journal:  Geophys Res Lett       Date:  2021-06-03       Impact factor: 4.720

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