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Journal ArticleDOI

The importance of non-fossil sources in carbonaceous aerosols in a megacity of central China during the 2013 winter haze episode: A source apportionment constrained by radiocarbon and organic tracers

01 Nov 2016-Atmospheric Environment (Pergamon)-Vol. 144, pp 60-68

Abstract: To determine the causes of a severe haze episode in January 2013 in China, a source apportionment of different carbonaceous aerosols (CAs) was conducted in a megacity in central China (Wuhan, Hubei Province) by using the measurements of radiocarbon and molecular organic tracers. Non-fossil sources (e.g., domestic biofuel combustion and biogenic emissions) were found to be responsible for 62% ± 5% and 26% ± 8% of organic carbon (OC) and elemental carbon (EC) components by mass, respectively. Non-fossil sources contributed 57% ± 4% to total CAs in this large-scale haze event, whereas fossil-fuel sources were less dominant (43% ± 4%). The CAs were composed of secondary organic carbon (SOC; 46% ± 10%), primary fossil-fuel carbon (29% ± 4%) and primary biomass-burning carbon (25% ± 10%). Although SOC was formed mainly from non-fossil sources (70% ± 4%), the role of fossil precursors was substantial (30% ± 4%), much higher than at the global scale. Combined measurement of organic tracers and radiocarbon showed that most non-fossil SOC was probably derived from biomass burning during this long-lasting haze episode in central China.
Topics: Haze (54%), Total organic carbon (51%)

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1
The importance of non-fossil sources in carbonaceous aerosols in a megacity of central
China during the 2013 winter haze episode: A source apportionment constrained by
radiocarbon and organic tracers
Junwen Liu
a, b
, Jun Li
a, *
, Matthias Vonwiller
b, c
, Di Liu
a
, Hairong Cheng
d
, Kaijun Shen
a
, Gary Salazar
b
,
Konstantinos Agrios
b, c
, Yanlin Zhang
b, c, 1
, Quanfu He
a
, Xiang Ding
a
, Guangcai Zhong
a
, Xinming Wang
a
,
nke Szidat
b, **
, Gan Zhang
a
a State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of
Sciences, Guangzhou, 510640, China
b Department of Chemistry and Biochemistry & Oeschger Centre for Climate Change Research, University of Bern,
Berne, 3012, Switzerland
c Laboratory of Radiochemistry, Paul Scherrer Institute, Villigen-PSI, 5232, Switzerland
d Department of Environmental Engineering, School of Resource and Environmental Science, Wuhan University,
Wuhan, 430079, China
* Corresponding author. ** Corresponding author.
E-mail addresses: junli@gig.ac.cn (J. Li), szidat@dcb.unibe.ch (S. Szidat).
1 Now at Nanjing University of Information Science & Technology, Nanjing, 210044, China.
Accepted version
Published in
Atmospheric Environment 144 (2016) 60-68
http://dx.doi.org/10.1016/j.atmosenv.2016.08.068

2
Abstract
To determine the causes of a severe haze episode in January 2013 in China, a source
apportionment of different carbonaceous aerosols (CAs) was conducted in a megacity in central
China (Wuhan, Hubei Province) by using the measurements of radiocarbon and molecular
organic tracers. Non-fossil sources (e.g., domestic biofuel combustion and biogenic emissions)
were found to be responsible for 62% ± 5% and 26% ± 8% of organic carbon (OC) and elemental
carbon (EC) components by mass, respectively. Non-fossil sources contributed 57% ± 4% to total
CAs in this large-scale haze event, whereas fossil-fuel sources were less dominant (43% ± 4%).
The CAs were composed of secondary organic carbon (SOC; 46% ± 10%), primary fossil-fuel
carbon (29% ± 4%) and primary biomass-burning carbon (25% ± 10%). Although SOC was
formed mainly from non-fossil sources (70% ± 4%), the role of fossil precursors was substantial
(30% ± 4%), much higher than at the global scale. Combined measurement of organic tracers and
radiocarbon showed that most non-fossil SOC was probably derived from biomass burning
during this long-lasting haze episode in central China.

3
1. Introduction
A severe and long-lasting haze episode, with an extremely elevated PM
2.5
(aerodynamic diameter
< 2.5 µm) concentration (the hourly concentration up to ~1000 µg/m3) (Uno et al., 2014),
occurred in January 2013 in central and eastern China. Because a high PM
2.5
loading can cause a
reduction in visibility, climate changes, and human respiratory-cardiovascular diseases
(Brunekreef and Holgate, 2002; Menon et al., 2002; Deng et al., 2008; Wang et al., 2014b), many
concerns were raised by the public, government, and scientists. Numerous investigations have
been performed to determine the characteristics of this air pollution crisis. He et al. (2014)
identified a new haze formation mechanism regarding the conversion of SO
2
to sulfate, and
reported that the impact of motor vehicle on air quality was underestimated in the Beijing-
Tianjin-Hebei Region. Using an aerodyne aerosol chemical speciation monitor, Sun et al. (2014)
found that stagnant meteorological conditions, coal combustion, secondary production, and
regional transport were the main factors leading to the formation of this haze in Beijing. Wang et
al. (2014a) called on the government to establish a regional joint framework for mitigation of the
severe air pollution based on their model evaluations. Currently, most of these studies have been
conducted in northern China, specifically in Beijing, and have focused on the analysis of
chemical concentrations. Measurements of more-specific-sources tracers (i.e., isotopes and
organic tracers) during this haze period are still scarce.
Carbonaceous aerosols (CAs) are important major components of PM
2.5
. However, CAs are
poorly understood because of their vast number of emission sources, various physicochemical
properties, and heterogeneous distribution in time and space. Total CAs values are generally
expressed in terms of total carbon (TC), which contains organic carbon (OC) and elemental
carbon (EC). EC is a primary carbon species that is derived solely from the incomplete
combustion of carbon-containing materials. Ambient OC is a mixture of primary organic carbon

4
(POC), which is emitted from various combustion processes, and secondary organic carbon
(SOC), which is formed through the oxidation of volatile organic compounds (VOCs) (Pöschl,
2005; Calvo et al., 2013). In addition, a large fraction of SOC can be formed from the chemical
reactions of POC (Robinson et al., 2007). OC can be further separated into water-soluble organic
carbon (WSOC) and water-insoluble organic carbon (WIOC). These carbon particles in the
atmosphere have two sources: fossil fuel (FF, e.g., from traffic exhaust, coal combustion,
industry) and non-fossil (NF, e.g., from open/forest fire, biofuel burning, biogenic emission)
emissions. Their unambiguous source apportionment has been conducted in recent years by the
measurements of radiocarbon (
14
C) (Gustafsson et al., 2009, Szidat et al., 2009; Chen et al., 2013;
Liu et al., 2013; Huang et al., 2014; Liu et al., 2014; Zotter et al., 2014a; Andersson et al., 2015;
Zhang et al., 2015). This radioisotope (half-life = 5730 years) enables a distinction between FF
and NF sources because
14
C is absent in FF, but present at the current ambient level in NF
materials.
14
C analyses of aerosols have seldom been reported in China due to the complexity of
experimental procedures and the need for a specific analysis facility. Chen et al. (2013) first
systematically investigated the
14
C signals of EC (or black carbon) in Beijing, Shanghai, and
Xiamen, and found that 83-86% of EC was associated with FF combustion during the 2009-2010
winter, with the remainder derived from biomass burning (BB). Zhang et al. (2015) analyzed the
14
C levels of OC and EC in four Chinese cities Beijing, Xi'an, Guangzhou, and Shanghaieand
found that the contributions of FF sources to OC and EC were 35-49% and 57-80%, respectively,
in January 2013. Andersson et al. (2015) found that during this haze period FF sources on
average contributed 74%, 68% and 68% to EC in Beijing, Shanghai and Guangzhou,
respectively. Liu et al. (2014) showed that the contribution of FF in OC and EC was 37% and
71% in Guangzhou during November 2012 to January 2013, respectively. A newly updated
China emission inventory showed that the coal used in power plants is 8300 Gg, 28,000 Gg,

5
85,000 Gg, 80,000 Gg, 35,000 Gg, in Beijing (north China), Shanghai (east China), Guangdong
(south China, the capital is Guangzhou), Shanxi (west China, the capital is Xi'an) and Hubei
(central China, the capital is Wuhan), and the corresponding value for residential solid biomass is
880 Gg, 0 Gg, 22,000 Gg, 14,000 Gg and 26,000 Gg, respectively (Wang et al., 2012). These
results indicate that biomass used for residential burning in Hubei seems higher than Guangdong,
especially than Beijing and Shanghai. Given this difference of energy consumption pattern
among different regions in China, the key sources of this haze episode probably is region-
dependent. Previous
14
C-related studies also have displayed this difference. For example, the
contribution of FF sources to OC in Beijing was 58% (Zhang et al., 2015), whereas it was <40%
in Guangzhou on average (Liu et al., 2014; Zhang et al., 2015). Thus, this large-scale haze crisis
was very likely caused by the convergence of materials from numerous point sources in regions
with different sources. More
14
C-related studies are urgently needed to accurately and
quantitatively elucidate the emission sources of CAs during such a regional haze crisis. On other
hand, the sources of WSOC and WIOC differ markedly from those of EC (Liu et al., 2014). Thus,
determination of the
14
C isotopic signals of various carbon species is necessary to obtain a better
understanding of haze pollution characteristics and sources.
The haze phenomenon in China is very complex. First, Chinese cities are at the developmental
stage of industrialization and urbanization, with a large demand for FF energy. Second, biofuel is
a very common energy source in rural and suburban areas, in which ~50% of the Chinese
population lives. Third, little is known about the evolution of SOC and its precursor VOCs,
especially the relative contributions of FF and NF sources to SOC. Consequently, controversial
results regarding the PM
2.5
sources in China have been published. One group reported that the
annual contributions of coal and biomass combustion to PM
2.5
in Beijing were 7% and 6%
(Zheng et al., 2005), respectively, whereas higher corresponding contributions (14-19% and 11-

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Cites background from "The importance of non-fossil source..."

  • ...Comparable annual ffossil(EC) was reported at an urban site of Beijing (79 ± 6% (Zhang et al., 2015b); 82 ± 7% (Zhang et al., 2017)) and a background receptor site of Ningbo (77 ± 15% (Liu et al., 2013))....

    [...]


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Additional excerpts

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Abstract: Aerosols are of central importance for atmospheric chemistry and physics, the biosphere, climate, and public health. The airborne solid and liquid particles in the nanometer to micrometer size range influence the energy balance of the Earth, the hydrological cycle, atmospheric circulation, and the abundance of greenhouse and reactive trace gases. Moreover, they play important roles in the reproduction of biological organisms and can cause or enhance diseases. The primary parameters that determine the environmental and health effects of aerosol particles are their concentration, size, structure, and chemical composition. These parameters, however, are spatially and temporally highly variable. The quantification and identification of biological particles and carbonaceous components of fine particulate matter in the air (organic compounds and black or elemental carbon, respectively) represent demanding analytical challenges. This Review outlines the current state of knowledge, major open questions, and research perspectives on the properties and interactions of atmospheric aerosols and their effects on climate and human health.

1,623 citations


Additional excerpts

  • ...Ambient OC is a mixture of primary organic carbon (POC), which is emitted from various combustion processes, and secondary organic carbon (SOC), which is formed through the oxidation of volatile organic compounds (VOCs) (Pöschl, 2005; Calvo et al., 2013)....

    [...]

  • ...%) reported in other cities around the world (Pöschl, 2005; Ho et al., 2006; Cao et al., 2007; Zhao et al., 2013)....

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Abstract: Most primary organic-particulate emissions are semivolatile; thus, they partially evaporate with atmospheric dilution, creating substantial amounts of low-volatility gas-phase material. Laboratory experiments show that photo-oxidation of diesel emissions rapidly generates organic aerosol, greatly exceeding the contribution from known secondary organic-aerosol precursors. We attribute this unexplained secondary organic-aerosol production to the oxidation of low-volatility gas-phase species. Accounting for partitioning and photochemical processing of primary emissions creates a more regionally distributed aerosol and brings model predictions into better agreement with observations. Controlling organic particulate-matter concentrations will require substantial changes in the approaches that are currently used to measure and regulate emissions.

1,403 citations


Additional excerpts

  • ...Consequently, in 24-h samples, the use of FF-derived WSOC (WSOCf) and FF-derived WIOC (WIOCf) as proxies for the estimation of SOC (OCf_sec) and POC (OCf_pri), respectively, would be feasible and reasonable....

    [...]

  • ...Ambient OC is a mixture of primary organic carbon (POC), which is emitted from various combustion processes, and secondary organic carbon (SOC), which is formed through the oxidation of volatile organic compounds (VOCs) (Pöschl, 2005; Calvo et al., 2013)....

    [...]

  • ...Since the formation and evolution of SOC is a continuous aging process (Robinson et al., 2007; Kroll and Seinfeld, 2008), this “FF-derived water-insoluble SOC” probably can be attributed to the less oxidation degree during a short time in an arid atmosphere....

    [...]

  • ...Thus, POC derived from FF combustion can reasonably be considered to be waterinsoluble....

    [...]

  • ...Thus, FF-derived POC and SOC could be estimated as follows: OCf pri = WIOC x (1 - fc) (3) and OCf sec = WSOC x (1 - fc) (4) Source apportionment was achieved according to the approaches described above (Fig....

    [...]