Introduction
Mercury (Hg) is a globally distributed hazardous metal and is well known for
its long-range transport, environmental persistence and toxicity (Kim et al.,
2009; Selin, 2009; Schleicher et al., 2015). Hg is emitted to the atmosphere
through natural and anthropogenic processes or reemission of previously
deposited legacy Hg. It has three operationally defined forms: gaseous
elemental Hg (GEM), reactive gaseous Hg (RGM) and particle-bound Hg (PBM)
(Selin, 2009). In general, GEM (> 90 % of the total Hg in
atmosphere) is fairly stable and can be transported globally, whereas RGM is
rapidly deposited from the atmosphere in wet and dry deposition, and PBM is
assumed to be transported more regionally (Selin, 2009; Fu et al., 2012).
Recent measurements of PBM in several rural and urban areas have shown that Hg
associated with particulate matter (PM) of size < 2.5 µm
(PM2.5-Hg) has typical concentrations < 100 pg m-3 in
background atmospheric environments (Liu et al., 2007; Fu et al., 2008; Kim
et al., 2012), but exceeds 300 pg m-3 in contaminated regions (Xiu et
al., 2009; Zhu et al., 2014). PM2.5-Hg is of particular concern because,
once inhaled, both Hg and its vectors might have adverse effects on human
beings.
Mercury has seven stable isotopes (196Hg, 198Hg, 199Hg, 200Hg, 201Hg, 202Hg and 204Hg) and its isotopic ratios in
the nature have attracted much interest in recent years (Yin et al., 2010;
Hintelmann and Zheng, 2012; Blum et al., 2014; Cai and Chen, 2016). Previous
studies have reported both mass-dependent fractionation (MDF,
δ202Hg) and mass-independent fractionation (MIF, primarily
observation of odd atomic weighed Hg isotopes, Δ199Hg and
Δ201Hg) of Hg isotopes in environments (Hintelmann and Lu, 2003;
Jackson et al., 2004, 2008; Bergquist and Blum, 2007; Gratz et al., 2010;
Chen et al., 2012; Sherman et al., 2012). The nuclear volume effect (NVE)
(Schauble, 2007) and magnetic isotope effect (MIE) (Buchachenko, 2009) are
thought to be the main causes for odd-MIF (Bergquist and Blum, 2007; Gratz et
al., 2010; Wiederhold et al., 2010; Sonke, 2011; Chen et al., 2012; Ghosh et
al., 2013; Eiler et al., 2014). Theoretical and experimental data suggested a
Δ199Hg / Δ201Hg ratio about 1.6 for NVE (Zheng and
Hintelmann, 2009, 2010b), and a Δ199Hg / Δ201Hg ratio
mostly between 1.0 and 1.3 for MIE as a result of photolytic reductions under
aquatic (and atmospheric) conditions (Zheng and Hintelmann, 2009, 2010a;
Malinovsky et al., 2010; Wiederhold et al., 2010; Sonke, 2011; Ghosh et al.,
2013; Eiler et al., 2014). Over the past decade, studies have indicated that Hg
isotope ratios are useful for differentiating Hg sources in terrestrial
samples, such as sediments (Jackson et al., 2004; Feng et al., 2010; Ma et
al., 2013), soils (Biswas et al., 2008; Zhang et al., 2013a) and biota
(Sherman et al., 2013; Yin et al., 2013; Jackson, 2015), and for
distinguishing potential biogeochemical processes that Hg had undergone
(Jackson et al., 2013; Sherman et al., 2013; Yin et al., 2013; Masbou et al.,
2015). Up to now, several studies have reported Hg isotopic compositions in
atmospheric samples (Zambardi et al., 2009; Gratz et al., 2010; Chen et al.,
2012; Sherman et al., 2012, 2015; Demers et al., 2013, 2015a; Rolison et al.,
2013; Fu et al., 2014, 2016; Yuan et al., 2015; Das et al., 2016; Enrico et
al., 2016). These studies reported large variations in Δ199Hg and
δ202Hg values for GEM (ranging from -0.41
to 0.06 ‰ for Δ199Hg,
and from -3.88 to 1.43 ‰ for
δ202Hg) (Zambardi et al., 2009; Gratz
et al., 2010; Sherman et al., 2010; Rolison et al., 2013; Yin et al., 2013;
Demers et al., 2015b; Das et al., 2016; Enrico et al., 2016; Fu et al., 2016)
and for Hg in precipitation (from 0.04 to 1.16 ‰ for
Δ199Hg, and from -4.37
to 1.48 ‰ for δ202Hg) (Gratz et al., 2010; Chen et al., 2012; Sherman et
al., 2012, 2015; Demers et al., 2013; Wang et al., 2015b; Yuan et al., 2015).
In addition, recent studies have found MIF of even Hg isotopes (even-MIF,
Δ200Hg) in natural samples mainly related to the atmosphere,
rendering Hg a unique heavy metal having “three-dimensional” isotope
systems (Chen et al., 2012).
While Hg isotopes in both GEM and RGM have drawn much attention, those of
PBM are comparably less studied in the literature. Indeed, only several prior
studies have focused on Hg isotopes in PBM. Rolison et al. (2013) reported,
for the first time,
δ202Hg (of -1.61 to -0.12 ‰) and Δ199Hg values (of 0.36 to 1.36 ‰) for PBM from the Grand
Bay area in the USA, and the ratios of Δ199Hg / Δ201Hg
close to 1 that was thought to be derived from in-aerosol photoreduction.
Huang et al. (2015) measured Hg isotope ratios for two PM2.5 samples
taken from Guiyang, China, with δ202Hg of -1.71
and -1.13 ‰ and Δ199Hg of 0.21 and 0.16 ‰. Das et al. (2016)
measured Hg isotopic compositions of PBM in PM10 from Kolkata, eastern
India, and found negative MDF and varied values of Δ199Hg between
-0.31 and 0.33 ‰. These studies showed that the Hg isotope
approach could be developed for tracking the sources and pathways of Hg
species in the atmosphere.
China is one of the largest Hg emission countries in the world (Fu et al.,
2012; Zhang et al., 2015), with a total estimated anthropogenic Hg emission
of approximately 356 t in 2000 and 538 t in 2010 (Zhang et al., 2015). Coal
combustion, nonferrous metal smelting, and cement production are the dominant
Hg emission sources in China (collectively accounting for approximately over
80 % of the total Hg emission) (Zhang et al., 2015). Haze particles,
especially PM2.5, which are among the most serious atmospheric
pollutants in urban areas of China (Huang et al., 2014), are important carriers of Hg (Lin et al., 2015b; Schleicher et al., 2015). If
PM2.5 is emitted from the same source as Hg (Huang et al., 2014; Lin et
al., 2015b; Schleicher et al., 2015; Zhang et al., 2015), quantifying Hg
isotopes may provide direct evidence for the sources of both Hg and
PM2.5, as well as insight into the geochemical processes that they may
have undergone.
In this study, we attempted to identify the sources of PM2.5-Hg in
Beijing, the capital of China, using Hg isotopic composition coupled with
meteorological and other geochemical parameters. We selected Beijing as the
study site because, like many other Chinese megacities, Beijing has suffered
severe PM2.5 pollution (Huang et al., 2014; Gao et al., 2015) and is
considered as the most PBM polluted area in China (Schleicher et al., 2015).
In the past decade, only a few prior studies quantified the Hg
concentrations in PM2.5 samples collected from Beijing (Wang et al.,
2006; Zhang et al., 2013b; Schleicher et al., 2015), while no research
attempted to track its sources using the Hg isotope approach. The specific
objectives of this study were (1) to characterize the seasonal variation in
Hg isotope compositions in PM2.5 of Beijing and (2) to test the
effectiveness of the Hg isotope technique for tracking the sources of the
PM2.5-Hg.
Materials and methods
Field site and sampling method
Beijing (39.92∘ N and 116.46∘ E) has a population of over
21 million. It is located in a temperate warm zone with typical continental
monsoon climate. The northwestern part of the greater Beijing metropolitan area is
mountainous, while the southeastern part is flat. It has an average annual
temperature of about 11.6 ∘C, with a mean value of 24 ∘C
in summer and -2 ∘C in winter. In the summer, the wind blows mainly
from the southeast under the influence of the hot and humid East Asian monsoon, whereas
the cold and dry monsoon blows from Siberia and Mongolia in the winter. The
winter heating season in Beijing normally starts on 15 November and ends on
15 March.
PM2.5 was sampled from September 2013 to July 2014 using a high-volume
PM2.5 sampler placed on the roof of a building (approximately 8 m above the
ground) of the Institute of Atmospheric Physics, Chinese Academy of Sciences,
which is located between the north 3rd and 4th ring of Beijing. The
meteorological model showed that the arriving air masses were transported
mainly by two directions, with the northwest winds dominant in winter and
the southern winds mainly in summer. The sampling information is detailed in
the Supplement (see Table S1). The PM2.5 samples were collected
using a Tisch Environmental PM2.5 high-volume air sampler, which
collects particles at a flow rate of 1.0 m3 min-1 through a
PM2.5 size-selective inlet. As the particles travel through the size
selective inlet the larger particles are trapped inside of the inlet, while
the smaller-size (PM2.5) particles continue to travel through the
PM2.5 inlet and are collected on a pre-combusted (450 ∘C for
6 h) quartz fiber filter (Pallflex 2500 QAT-UP, 20 cm × 25 cm,
Pallflex Product Co., USA). The mass of PM2.5 on each filter was
measured using a gravimetric method by the mass difference before and after
sampling. The filters were conditioned in a chamber with a relative humidity
of about 48 % and a temperature of 20 ± 2 ∘C for about
24 h before and after sampling. A field blank was also collected during
sampling and the value (< 0.2 ng of Hg, n = 6) was negligible
(< 2 %) compared to the total Hg mass contained in the
PM2.5 samples. After sampling, each filter was recovered, wrapped with a
pre-combusted (to eliminate Hg) aluminum film, and packed in a sealed
plastic bag. The filters were brought back to the laboratory and stored at
-20 ∘C prior to analysis.
In order to better assign sources of Hg, we collected and measured 30 solid
samples of different materials that may be potential Hg (and PM2.5)
sources and that may contribute to PM2.5-Hg in Beijing. They included
(i) 8 samples (including feed coal powder, bottom ash, desulfurization
gypsum and fly ash) from two coal-fired power plants (from Hubei and Mongolia
provinces); (ii) 6 samples from a Pb–Zn smelting plant (including blast
furnace dust, dust of blast furnace slag, sintering dust, coke, return powder
and agglomerate); (iii) 10 samples from a cement plant (including coal
powder, raw meal, sandstone, clay, limestone, steel slag, sulfuric acid
residue, desulfurization gypsum and cement clinker), 6 of which have been
published previously (Wang et al., 2015b); (iv) 4 topsoil samples (surface
horizon: organics mixed with mineral matter, these samples are not natural
soil on typical soil profiles) from the Beijing center city (Olympic Park,
Beihai Park, the Winter Palace and Renmin University of China (RUC)) and 2
dust samples from RUC (one building roof dust and one road dust); (v) 1
total suspended particle (TSP; the sampling of TSP was carried out using an
in-house-constructed low-volume (about 1.8 m3 h-1) air sampler equipped
with a TSP inlet, and a pre-cleaned mixed fiber filter (47 mm) was used for
the TSP low-volume inlets) sample from the atmosphere of a rural area of Yanqing
district, northwest of Beijing; and (vi) 2 urban road dust, 2 suburban
road dust and 1 suburban topsoil samples from the city of Shijiazhuang, southwest
of Beijing. Though automobile exhaust might also be a contributing
source of PM2.5-Hg, we were not able to measure its Hg isotope ratios
due to its exceedingly low Hg concentration (Won et al., 2007).
Materials and reagents
Materials and reagents used in this study were similar to those described in
a
previous study (Huang et al., 2015). A 0.2 M BrCl solution was prepared by
mixing the distilled concentrated HCl with pre-heated (250 ∘C,
12 h) KBr and KBrO3 powders. Two SnCl2 solutions of 20 and
3 % (wt) were prepared by dissolving in 1 M HCl and were used
for online reduction of Hg for concentration and isotope measurements,
respectively. A 20 % (wt) NH2OH ⚫ HCl solution was
used for BrCl neutralization.
Two international Hg standards NIST SRM 3133 and UM-Almaden were used as the
reference materials for Hg isotope analysis. NIST SRM 997 thallium
(20 ng mL-1 Tl in 3 % HNO3) was employed for mass bias
correction (Chen et al., 2010; Huang et al., 2015). Two other reference
materials, the solution Fluka 28 941 Hg
(TraceCERT®, Sigma-Aldrich) and the soil
GBW07405 (National Center for Standard Materials, Beijing, China), were used
as in-house isotope standards, and these were regularly measured for quality
control of Hg concentration and isotope measurements. It is worth noting that
Fluka 28 941 Hg is a standard different from ETH Fluka Hg (Jiskra et al.,
2012; Smith et al., 2015).
Isotopic composition analysis
Mercury bound to PM2.5 and solid source materials was released via a
dual-stage combustion protocol and was captured in a 5 mL 40 % acid
mixture (2:4:9 volumetric ratio of 10 M HCl, 15 M HNO3 and Milli-Q
water) (Huang et al., 2015). The detailed procedure is available in Huang et
al. (2015). In brief, the filter samples were rolled into a cylinder and
placed in a furnace quartz tube (25 mm OD, 22 mm ID, 1.0 m length), which
was located in two series of combustion tube furnaces (BTF-1200C-S, Anhui BEQ Equipment
Technology Ltd., China). The solid source samples were powdered, weighed and
put into a sample quartz tube (20 mm OD, 18 mm ID, 10 cm length), which was
capped with quartz wool (pre-cleaned at 500 ∘C) at both ends to
prevent particle emission. The sample tube was then placed into the large
quartz tube of the furnace. The samples were combusted through a
temperature-programmed routine in the dual-stage combustion and acid solution
trapping system. An aliquot (50 µL) of 0.2 M BrCl was added to the
above trapping solution to stabilize the Hg2+. The trapping solution
for each sample was diluted to a final acid concentration of about 20 %
and was stored at 4 ∘C for the subsequent Hg concentration and
isotope measurement. The accuracy and precision of the dual-stage combustion
protocol were evaluated by the analysis of the certified reference material
GBW07405 using the same digestion method. The detectable Hg in the
procedural blank (< 0.2 ng, n = 12) of this dual-stage
combustion method was negligible compared to the amount of total Hg
(> 5 ng) in both PM2.5 samples and procedural standards.
Mercury isotope analyses were performed on the MC-ICP-MS (Nu Instruments
Ltd., UK) at the State Key Laboratory of Environmental Geochemistry,
Institute of Geochemistry, China. The details of the analytical procedures
and the instrumental settings were given in previous studies (Huang et al.,
2015; Lin et al., 2015a; Wang et al., 2015b; Yuan et al., 2015). In brief, a
home-made cold-vapor generation system was coupled with an Aridus II
desolvating nebulizer for respective Hg and Tl introductions. The Faraday
cups were positioned to simultaneously collect five Hg isotopes and two Tl
isotopes, including 205Tl (H3), 203Tl (H1), 202Hg (Ax),
201Hg (L1), 200Hg (L2), 199Hg (L3), and 198Hg (L4). The
instrumental mass bias was double-corrected by both internal standard NIST
SRM 997 Tl and by sample-standard bracketing (SSB) using the international
standard NIST SRM 3133 Hg. The MDF of isotopes is represented by delta
(δ) notation in units of permil (‰) and defined as the
following equation (Blum and Bergquist, 2007):
δxHg(‰)=[xHg/198Hgsample/xHg/198HgNIST3133-1]×1000
where x = 199, 200, 201, and 202. MIF is reported as the deviation of a
measured delta value from the theoretically predicted value due to kinetic
MDF according to the following equation:
ΔxHg(‰)=δxHg-β×δ202Hg,
where the mass-dependent scaling factor β is of about 0.252, 0.5024 and
0.752 for 199Hg, 200Hg and 201Hg, respectively (Blum and
Bergquist, 2007).
The Fluka 28 941 Hg standard was carefully calibrated against the NIST SRM
3133 Hg and the long-term measurements yielded an average value of
-1.00 ± 0.13 ‰ (2 SD, n = 15) for δ202Hg,
with a precision similar to that (0.10 ‰, n = 114) obtained
for NIST SRM 3133 Hg. Our repeated measurements of UM-Almaden and GBW07405
had average δ202Hg, Δ199Hg and Δ201Hg values of
-0.60 ± 0.09, -0.01 ± 0.06 and
-0.03 ± 0.06 ‰ (2 SD, n = 18) and of
-1.77 ± 0.14, -0.29 ± 0.04 and
-0.32 ± 0.06 ‰ (2 SD, n = 6), respectively, consistent
with the data published in previous studies (Blum and Bergquist, 2007; Zheng
et al., 2007; Smith et al., 2008; Carignan et al., 2009; Zambardi et al.,
2009; Chen et al., 2010; Sherman et al., 2010; Wiederhold et al., 2010; Huang
et al., 2015). In this study, the 2 SD uncertainties (0.14, 0.04 and
0.06 ‰ for δ202Hg, Δ199Hg and Δ201Hg)
obtained for the soil reference GBW07405 were considered as the typical
external uncertainties for some PM2.5 samples that were measured only
once due to their limited mass. Otherwise, the uncertainties were calculated
based on the multiple measurements (Tables S1 and S2).
Concentration measurements
A small fraction of each trapping solution (20 % acid mixture) was used
to measure the Hg concentration by cold-vapor atomic fluorescence spectroscopy (Tekran 2500,
Tekran® Instruments Corporation, CA), with a
precision better than 10 %. The recoveries of Hg for the standard
GBW07405 and 30 solid samples were in the acceptable range of 95 to
105 %, but no recovery of Hg for the PM2.5 samples was determined
due to limited availability of the samples. A 0.5 cm2 punch from each
filter sample was analyzed for organic and elemental carbon (OC / EC) with a
Desert Research Institute (DRI) model 2001 thermal–optical carbon analyzer
(Atmoslytic Inc., Calabasas, CA, USA) following the Interagency Monitoring of
Protected Visual Environments (IMPROVE) thermal evolution protocol (Wang et
al., 2005). The calculated uncertainties were ±10 % for the measured
OC and EC data. The concentrations of other elements (e.g., Al, Cd, Co, Pb,
Sb, Zn, K, Ca and Mg) were also measured for 14 of the PM2.5 samples and
16 of the selected potential source materials using ICP-MS or ICP-AES after
total acid (HNO3-HF-HClO4) digestion. A 1.5 cm2 punch from
each filter sample and about 0.05 g of solid material samples were
dissolved completely with HNO3-HF-HClO4. Note that, due to limited
mass of PM2.5 samples, nine PM2.5 samples were exhausted after isotope
analysis, and only 14 PM2.5 samples were analyzed for the other
elements. The soil standard GBW07405 was digested using the same protocol and
the measured concentrations of trace elements (TEs, including Hg) were
consistent with the certified values.
Results
General characteristics of PM2.5
The contents of PM2.5, OC and EC for the 23 samples are presented in
Table S1. The volumetric contents of PM2.5 ranged from 56 to
310 µg m-3 (average 120 ± 61 µg m-3),
and were higher in autumn than the three other seasons (Fig. 1). The
PM2.5 samples showed large variations in carbon concentrations, with OC
ranged from 2.8 to 42 µg m-3 and EC from 1.2 to
9.2 µg m-3, averaging 12 ± 9.6 and
3.7 ± 2.3 µg m-3, respectively. The OC and EC contents
in autumn (respective mean of 14 ± 11 and
4.9 ± 2.8 µg m-3, n = 6) and winter (mean of
19 ± 13 and 5.1 ± 2.3 µg m-3, n = 6) were
approximately doubled compared to those in spring (mean of 7.7 ± 1.4
and 2.5 ± 0.7 µg m-3, n = 6) and summer (mean of
5.9 ± 1.8 and 2.0 ± 0.5 µg m-3, n = 5).
Similar seasonal variation was also reported in a previous study (Zhou et
al., 2012). When converted to the mass concentrations, the OC and EC contents
were significantly (p < 0.01) higher in winter (mean of
170 ± 49 and 50 ± 8 µg g-1, n = 6) than in
other seasons (mean of 71 ± 18 and
25 ± 7.3 µg g-1, n = 17) (Table S1). Since EC
contents were closely correlated with OC (r2= 0.89,
p < 0.001), we discuss only EC contents in the following as an
indicator for the source of PM, because EC is a significant pollutant of
combustion source that is not readily modified by secondary processes in the
atmosphere.
Seasonal variations in PM2.5 (a) and elemental carbon
(b) contents, Hg concentrations (c) and Hg isotopic
ratios (d–f) of the PM2.5 samples. For each box plot, the
median is the 50th percentile and error bars extend from the 75th percentile to
the maximum value (upper) and from the 25th percentile to the minimum value
(lower). The small square in each box represents the seasonal mean value.
Seasonal variation in mercury concentration and isotopic
composition
PM2.5-Hg volumetric concentrations and isotopic compositions are shown
in Table S1. In general, the PM2.5-Hg concentrations ranged from 11 to
310 pg m-3, with an average value of 90 ± 80 pg m-3.
These values were comparable to those reported at a rural site of Beijing
(98 ± 113 pg m-3) (Zhang et al., 2013b), indoor PM2.5 of
Guangzhou (104 pg m-3) (Huang et al., 2012) and several southeastern
coastal cities (141 ± 128 pg m-3) of China (Xu et al., 2013),
but they were lower than those reported values for Guiyang
(368 ± 676 pg m-3) of China (Fu et al., 2011). From a global
perspective, our PM2.5-Hg contents were much higher than those reported
for urban areas of other countries such as Seoul in South Korea
(23.9 ± 19.6 pg m-3) (Kim et al., 2009), Gothenburg in Sweden
(12.5 ± 5.9 pg m-3) (Li et al., 2008) and Detroit in the USA
(20.8 ± 30.0 pg m-3) (Liu et al., 2007). The averaged
PM2.5-Hg values showed an evident seasonal variation, with relatively
higher value in winter (140 ± 99 pg m-3) and lower in summer
(22 ± 8.2 pg m-3) (see Figs. 1 and 2). Previous studies also
reported similar variation for Hg loads in atmospheric particles in Beijing
(Wang et al., 2006; Schleicher et al., 2015); for example, the highest value
of 2130 ± 420 pg m-3 was found in winter 2004, while lower
values were generally reported in summer (Wang et al., 2006; Schleicher et al., 2015).
Shown are relationships between Δ199Hg and
δ202Hg (a) and Δ201Hg (b) for 23
PM2.5 samples. The gray areas are the ranges of Hg isotope compositions
of potential source materials.
Seasonal variations were also observed for Hg isotopic compositions (see
Figs. 1 and 2 and Table S1). The δ202Hg values ranged from -2.18
to 0.51 ‰ (average -0.71 ± 0.58 ‰, 1 SD,
n = 23), with the lowest value of -2.18 ‰ found on
29 June 2014 (in summer), whereas the highest of 0.51 ‰ was found on
30 September 2013 (in autumn). Interestingly, all samples displayed a large
Δ199Hg variation from -0.53 to 0.57 ‰ (mean of
0.05 ± 0.29 ‰). Unlike δ202Hg, the lowest
Δ199Hg value (-0.53 ‰) was found in autumn (on
30 September 2013), whereas the highest value (0.57 ‰) was observed
in spring (23 April 2014). Positive even-MIF of Hg isotope was also determined
in all PM2.5-Hg, with Δ200Hg ranging from 0.02 to
0.17 ‰, averaging 0.09 ± 0.04 ‰ (Table S1). Three
previous studies reported negative δ202Hg (from -3.48 to
-0.12 ‰) but significantly positive Δ199Hg (from
-0.31 to 1.36 ‰) for atmospheric particles (Rolison et al., 2013;
Huang et al., 2015; Das et al., 2016).
Mercury content and isotope ratios in potential source materials
As showed in Table S2, the Hg concentrations of the potential source
materials ranged widely from 0.35 to 7747 ng g-1, with an
exceptionally high value of 10 800 ng g-1 for the sintering dust
collected by the electrostatic precipitator in a smelting plant. Though the
topsoil and road dust samples generally displayed relatively lower Hg
concentrations (e.g., 23 to 408 ng g-1, Table S2), the topsoil
collected from Beihai Park in the 2nd ring of Beijing had an exceptionally
high Hg content of 7747 ng g-1. It is worth noting that these data were
comparable to the mass-based Hg concentrations (150 to 2200 ng g-1
with a mean value of 720 ng g-1) for the 23 PM2.5 samples
(Table S1).
The potential source materials also had a large variation in Hg isotope
compositions (Figs. 2 and 3 and Table S2), with δ202Hg ranging from
-2.67 to 0.62 ‰ (average -0.98 ± 0.79 ‰, 1 SD,
n = 30), while Δ199Hg ranged from -0.27 to 0.18 ‰
(mean -0.03 ± 0.11 ‰) and Δ200Hg values ranged from
-0.04 to 0.11 ‰ (mean 0.02 ± 0.04 ‰).
Comparison of isotopic compositions between the selected potential
source materials and the PM2.5 samples. The δ202Hg values of PM2.5-Hg are within the ranges of the source
materials, but the Δ199Hg values are out of the range,
suggesting contribution from other unknown sources or MIF during atmospheric
processes.
Discussion
Previous studies have demonstrated that coal combustion, cement plant and
non-ferrous metal smelting were main sources of Hg in the atmosphere (Streets
et al., 2005; Zhang et al., 2015), respectively contributing about 47, 18.5 and 17.5 %
of total anthropogenically emitted Hg in China(Zhang et al.,
2015). In particular, certain events, such as large-scale biomass burning in
autumn and excessive coal combustion in the winter heating season, might also
have overprinted the concentration of PM2.5-Hg and its isotope
composition. In addition to the possible direct emission from the above
anthropogenic sources, atmospheric processes may have impacted the
PM2.5-Hg isotopic composition, particularly during the long-range
transportation of PM2.5-Hg (and thus a long residence time of about a few days
to weeks) in the atmosphere (Lin et al., 2007). These potential sources and
possible process effects are discussed in the following sections.
Evidence for strong anthropogenic contribution
Anthropogenic emission as the main PM2.5-Hg contributing sources is
evidenced by the enrichment factor (EF) of Hg (and other metals), which was a
commonly used geochemical indicator for quantifying the enrichment/depletion
of a targeted element in environmental samples (Gao et al., 2002; Song et
al., 2012; Chen et al., 2014; Mbengue et al., 2014; Lin et al., 2015b). The
EF of a given element was calculated using a double normalization (to the
less reactive element Al here) and the upper continental crust (UCC) (Rudnick
and Gao, 2003) was chosen as the reference (see details in the Supplement).
Al is well adapted to this normalization as it usually has no anthropogenic
origin and is not readily modified by secondary processes in the atmosphere,
and thus was widely used for enrichment calculation in atmospheric pollution
studies (Gao et al., 2002; Waheed et al., 2011; Mbengue et al., 2014; Lin et
al., 2015b). The calculated results showed (Table S4) high EF(Hg) values for
the 14 PM2.5 samples, ranging from 66 to 424 with an average value of
228 ± 134 (1 SD, n = 14), indicating that PM2.5-Hg
pollution was serious (characterized by significant Hg enrichment) in
Beijing. As it is a TE, Hg concentration is generally low in natural terrestrial
reservoirs (e.g., 50 ppb in UCC) (Rudnick and Gao, 2003). Similar to the UCC,
the topsoil was also mainly composed of aluminosilicates with relatively low
Hg concentrations (Table S2). Thus, high EF(Hg) values probably imply a
strong anthropogenic contribution to Hg in PM2.5. This could be
confirmed by very high EF(Hg) values (up to 226 000, Table S4) determined,
for example, in three potential source materials collected from the smelting
plant. The high EF(Hg) values also emphasize the importance of studying toxic
metals such as Hg (and other heavy metals) in atmospheric particles while
assessing the potential threat of hazes on human health.
The strong anthropogenic contribution may be also supported by the
relationships between Hg and other particulate components in PM2.5.
Figure 4a and b show very good correlations between PM2.5-Hg
concentration and the volumetric concentrations of PM2.5 and EC, with
correlation coefficients (r2) of 0.40 and 0.80, respectively. It is
well known that atmospheric pollution due to the high concentrations of
PM2.5 and EC mainly results from anthropogenic emissions (Gao et al.,
2015; Lin et al., 2015b). PM2.5-Hg also displayed linear relationships
with trace metals. Figure 4c and d show the examples with Co and Zn
(r2 of 0.74 and 0.44, respectively, p < 0.01). High metal
contents in atmospheric particles are generally related to human activities.
For example, combustion and smelting release large amount of TEs into the
atmosphere (Xu et al., 2004; Nzihou and Stanmore, 2013). The fact that all
PM2.5 samples displayed very high EFs for “anthropophile” elements
(elements were generally enriched by human activities) (Chen et al., 2014)
such as Cd, Cu, Pb, Sb, Se, Tl and Zn (ranging from 10 to 20 869, Table S4)
clearly illustrated the anthropogenic contribution to these elements in
PM2.5. As a result, fine atmospheric particles in Beijing were strongly
enriched in Hg and other TEs, which was likely caused by elevated
anthropogenic activities.
Plots of the volumetric Hg concentration versus PM2.5 content
(a), EC content (b), and concentrations of Co (c)
and Zn (d) for the PM2.5 samples. In both (c) and
(d), only 14 PM2.5 samples are shown with Co and Zn data sets,
because 9 PM2.5 samples were exhausted after isotope and OC / EC
analyses, and only those 14 PM2.5 samples were analyzed for the other elements.
Isotopic overprint of potential anthropogenic Hg sources
Hg isotopic signatures may further indicate that human activities contributed
to a large proportion of PM2.5-Hg. In this study, all samples displayed
a large variation in δ202Hg (from -2.18 to 0.51 ‰,
Table S1), similar to those values (from -2.67 to 0.62 ‰, Table S2)
determined for the particulate materials from potential sources such as coal
combustion (average -1.10 ± 1.20 ‰, 1 SD, n = 8),
smelting (-0.87 ± 0.82 ‰, 1 SD, n = 6) and cement
plants (-1.42 ± 0.36 ‰, 1 SD, n = 10), as demonstrated
in Figs. 2 and 3. This similarity might indicate the emission of these
anthropogenic sources as the possible contributing sources of PM2.5-Hg.
Though the anthropogenic samples collected in this study could not cover the
whole spectrum of anthropogenic contributions, previous studies reported a
similar δ202Hg range (from -3.48 to 0.77 ‰) for
potential source materials worldwide (Biswas et al., 2008; Estrade et al.,
2011; Sun et al., 2013, 2014; Yin et al., 2014; Wang et al., 2015b; Das et
al., 2016). In fact, most PM2.5 samples possessed Δ199Hg
similar to those determined in above-mentioned particulate materials (-0.27
to 0.04 ‰, Figs. 2 and 3) in this study, suggesting these
anthropogenic emission as the major sources of PM2.5-Hg.
Interestingly, Hg isotope compositions were correlated well with the elements
such as Co, Ni and Sb (here the mass ratio of a particular element to aluminum was used to
cancel out the dilution effect by major mineral phase), as shown in Fig. 5a
and b for the example of Co. These correlations might indicate that Hg and
some other metals had common provenance, likely from anthropogenic
combustion, as discussed above. A careful investigation of the correlations
amongst metal elements, along with Hg isotopic data, further indicated
anthropogenic source category. The principal component analysis (PCA) of Hg
and other TEs (see Table S5) demonstrated that likely four factors might
control the variance of the entire data set over four seasons. In accordance
with the above discussion, these four factors were likely a mixture of coal
combustion and nonferrous metal smelting (characterized by high contents of
Pb, Rb, Se, Zn, Tl, Cr and Cd), cement production (enriched in Ca, Sr, Al and
Mg), traffic emission and biomass burning, with their contributions estimated
to be about 39, 24, 23, and 7 % (Table S5).
Correlations between Hg isotopic composition (δ202Hg and
Δ199Hg) and Co / Al (a, b) and EC / Al (c, d) elemental mass ratios. In all cases, δ202Hg values are
positively, and Δ199Hg values negatively,
correlated with the Co / Al and EC / Al ratios.
As a result, the Hg isotopic compositions may potentially suggest that coal
combustion, smelting and cement plants were major sources of PM2.5-Hg.
The higher EF(Hg) values and the detail investigation of elemental data
supported this hypothesis. However, without careful characterization of
potential sources, we are unable to quantify the contribution from each
source at this stage. It is worth noting that Fig. 6a and b show that
δ202Hg increased with EF(Hg) (r2 = 0.55), whereas Δ199Hg decreased with EF(Hg) (r2= 0.36). These correlations may suggest that the large isotope
variation in PM2.5-Hg might be mainly controlled by two end members with
contrasting δ202Hg and Δ199Hg. The end Δ199Hg
values of correlations, however, could not be explained by the above-defined
anthropogenic sources, which generally had insignificant odd-MIF. The
contribution from additional sources or possible processes was thus needed to
explain the extreme Δ199Hg values. Accordingly, the
δ202Hg and Δ199Hg exhibited contrast relationships with
the EC / Al ratios (Fig. 5c and d). As relatively higher EC contents were
generally derived from coal combustion and biomass burning (Zhang et al.,
2008; Saleh et al., 2014), these two non-point emission sources might account
for the Δ199Hg end values.
Dominant contribution from coal combustion in winter
High EC content in winter PM2.5 might result from additional coal
combustion during the heating season, when coal was widely used in both
suburban communities and rural individual families (Wang et al., 2006; Song
et al., 2007; Schleicher et al., 2015). This additional coal burning could
considerably increase Hg and EC emission, explaining the relatively higher
PM2.5-Hg (1340 ng g-1, p < 0.01) and carbon contents
(Table S1). In this study, both δ202Hg (mean
-0.71 ± 0.37 ‰) and Δ199Hg
(-0.08 ± 0.11 ‰, 1 SD, n = 6) values for winter PM2.5
samples were consistent with those in coal (average
δ202Hg values of -0.73 ± 0.33 ‰ and Δ199Hg of -0.02 ± 0.08 ‰) from northeastern China (Yin et al., 2014), possibly supporting
the above conclusion. In addition to EC contents, the Zn / Al ratio may provide
information for PM from industrial (e.g., metal smelting) emission sources. In
the Zn / Al vs. EC diagram (Fig. 7), all winter samples displayed a linear
relationship (r2= 0.94) different from the samples of other seasons.
Compared to the data of other seasons, the volumetric EC concentrations
varied greatly in winter, whereas the Zn / Al ratio of the same season
remained stable. This variation may be derived from the emission of coal
burning, which is characterized by high carbon content but relatively low Zn
concentration (Nzihou and Stanmore, 2013; Saleh et al., 2014). This again highlights the dominant contribution from coal combustion. The
backward trajectory calculated by the Hybrid Single Particle Lagrangian
Integrated Trajectory (HYSPLIT) model (Fig. S1 in the Supplement) showed the
dominant northwestern wind in winter. In this case, the fact that the
transported air masses were derived from the background region (less
populated and underdeveloped) could potentially explain both the lower
volume-based concentrations of Hg, TEs (e.g., Zn) and EC (Fig. 7) and the
higher mass-based contents of Hg, TEs (e.g., Zn) and EC (Table S1 in the
Supplement) in some winter samples. The dilution by this background air could
also explain the comparable EC content in winter and autumn (Figs. 1 and 7).
Correlations between Hg isotopic composition (δ202Hg and
Δ199Hg) and Hg enrichment factor EF(Hg) (a, b). The
δ202Hg value is positively correlated with the EF(Hg), while the
Δ199Hg value is negatively correlated with the EF(Hg).
Important biomass burning input in autumn
Biomass burning that often occurred in northern China might be the cause of
relatively higher EC volumetric concentrations in autumn PM2.5. The
HYSPLIT model (Fig. S2) showed that, unlike the winter PM2.5, the
samples collected in autumn were strongly impacted by northward wind. Biomass
burning that occurred in the south of Beijing during the autumn harvesting season
could transport a large amount of EC (and Hg) to Beijing, adding a potential
source to PM2.5-Hg. Though biomass burning is not an important source in
an annual time scale (from PCA estimation), it may display major contribution
in a short time period in autumn. Previous studies showed that this source
might account for 20 to 60 % of PM2.5 in Beijing during peak days of
biomass burning (Zheng et al., 2005a, b). Isotopically, PM2.5 collected
in the arriving air masses from south was characterized by significantly
negative Δ199Hg values (from -0.54 to -0.29 ‰),
whereas samples collected in the northwestern wind event exhibited
Δ199Hg values close to zero or slightly positive, indicating a
negative Δ199Hg signature in biomass burning emission Hg. Our newly
obtained data on Hg isotopes from biomass burning showed negative
Δ199Hg (which will be published in the future), supporting our
hypothesis. Moreover, prior studies have generally reported negative
Δ199Hg values for biological samples including foliage (about
-0.37 ‰), rice stem (about -0.37 ‰) and litter (about
-0.44 ‰) (Demers et al., 2013; Yin et al., 2013; Jiskra et al.,
2015), even down to -1.00 ‰ for some lichen (Carignan et al.,
2009). The odd-MIF signature may be conserved during complete biomass burning
as this process would not produce any mass-independent fractionation (Sun et
al., 2014; Huang et al., 2015).
Correlations between Zn / Al ratios and EC contents suggest
seasonal characteristics of PM2.5 sources with seasonally unique Δ199Hg signatures (in ‰).
Interestingly, the autumn PM2.5 had a Zn / Al versus EC correlation
(r2= 0.37) distinctly different from the winter samples, as well as
from spring and summer samples (Fig. 7). This difference may imply another
carbon-enriched contribution in autumn other than coal combustion. In fact,
the high occurrence of biomass burning in the south (Hebei and Henan
provinces) may lead to the EC content (volume-based) increasing in autumn air
mass. Thus, the high EC air mass input from biomass burning could explain the
different trend which defined by autumn PM2.5, while the above-discussed
contribution from industries (mainly smelting) could explain the higher Zn
(at a given EC content) in summer samples. Though most samples with high EC
could result from biomass burning, two autumn samples displaying relatively
low EC could be caused by the dilution from northern background air mass
(Fig. S2), as demonstrated by the HYSPLIT model.
Contribution from long-range-transported PM2.5-Hg
Besides the dominant contribution from local or regional emissions,
long-range-transported Hg might impact on PM2.5-Hg in Beijing (Han et
al., 2015; Wang et al., 2015a). As shown in Figs. 1 and 2 and Table S1, the
six spring PM2.5 samples and the one early summer sample had much high
Δ199Hg (from 0.14 to 0.57 ‰, mean of
0.39 ± 0.16 ‰, 1 SD, n = 7) and Δ200Hg values
(from 0.08 to 0.12 ‰, mean of 0.10 ± 0.01 ‰, 1 SD,
n = 7). These high values could not be explained by the above-defined
anthropogenic contributors having generally negative or close to zero MIF
(Figs. 2 and 3), yet another contribution or fractionation during atmospheric
processing is needed to explain all data sets. The long-range-transported
PM2.5 may be such contributor in addition to the direct local or
regional anthropogenic emission (Han et al., 2015; Wang et al., 2015a).
The HYSPLIT calculation showed that the arriving air masses of these samples
generally came from a long distance (mainly from the north and northwest,
Figs. S3 and S4), suggesting a contribution of long-range transportation,
given the residence time of PM2.5-Hg (days to weeks) (Lin et al., 2007).
Unfortunately, we were not able to collect and analyze the typical
long-range-transported Hg in this study. Previous studies have reported that
long-range-transported Hg might exhibit relatively higher Δ199Hg (up to
1.16 ‰) due to the extensive photolysis reaction (Chen et al., 2012;
Wang et al., 2015b; Yuan et al., 2015). In fact, the samples with
significantly positive Δ199Hg were collected during a period (at
least 3 days before sampling) with long daily sunshine (> 8.8 h)
for Beijing and adjacent regions (Table S1). Such climate conditions might be
favorable for photoreduction of atmospheric Hg2+, which preferentially
enriches odd isotopes in solution or aerosols. The fact that the background
TSP sample from the Yanqing region had higher Δ199Hg
(0.18 ‰, Table S2) than PM2.5 samples collected at the same
time in the center of Beijing might suggest higher odd-MIF values for long-range-transported Hg, since the local Hg emission is very limited in this rural
area. Moreover, the higher Δ200Hg values (from 0.08 to
0.12 ‰, Table S1) determined in these samples may also indicate the
contribution of long-range transportation, since even-MIF was thought to be a
conservative indicator of upper atmosphere chemistry (Chen et al., 2012; Cai
and Chen, 2016). Since the locally emitted PM2.5-Hg (having lower or
close to zero Δ199Hg and Δ200Hg) mainly resided and
accumulated in the atmospheric boundary layer (generally < 1000 m),
and thus could be largely scavenged by precipitation (Yuan et al., 2015), the
higher Δ199Hg values (from 0.06 to 0.14 ‰; see Table S1)
for PM2.5 sampled after precipitation event supported the contribution
of long-range transport to PM2.5-Hg. Finally, as the background
PM2.5 with little input from anthropogenic activities is likely
characterized by low contents of trace metals (such as Zn) and organic matter
(Song et al., 2007; Zhou et al., 2012), the long-range transport contribution
could also explain PM2.5 samples with relatively low EC content and
Zn / Al ratio in Fig. 7.
Possible process effects on transported PM2.5-Hg
The atmospheric processes such as secondary aerosol production, adsorption
(and desorption) and redox reactions may induce a redistribution of Hg among
GEM, RGM and PBM and simultaneously fractionate Hg isotopes in PM2.5,
possibly resulting in a difference of Hg isotopic composition between
PM2.5 and source materials. Up to now, Hg isotopic fractionation has
rarely been reported for Hg redistribution and secondary aerosol formation in the
atmosphere. However, the fact that the contents of secondary organic carbon
(see detailed calculation in the Supplement) had no correlation
(r2 < 0.09, p > 0.18) with either
δ202Hg or Δ199Hg may imply a limited
effect of such processes. Previous studies have showed limited adsorption of
Hg0 on atmospheric particles (Seigneur et al., 1998). More importantly,
according to the experiments conducted under aqueous conditions, the
adsorption/desorption and precipitation of Hg2+ may only induce very
small MIF of Hg isotopes (Jiskra et al., 2012; Smith et al., 2015), in
contrast with our observation. Therefore, the effect of adsorption or
precipitation was probably limited to MIF of Hg isotopes in PM2.5. In this study, all 23 PM2.5 samples defined a straight
line in Fig. 2 with a Δ199Hg / Δ201Hg slope of about
1.1, consistent with the results of the Hg2+ photoreduction experiment
(Bergquist and Blum, 2007; Zheng and Hintelmann, 2009), suggesting a possible
effect of photochemical reduction during PM2.5-Hg transport.
Potentially, the enrichment of odd isotopes in reactants (here particles)
during these processes can explain the positive Δ199Hg in spring
and summer samples. However, most samples collected in autumn and winter
displayed significant negative Δ199Hg values (down to
-0.54 ‰, Figs. 1, 2, 4 and 5, and Table S1). Therefore, the
photoreduction of divalent Hg species cannot explain the total variation in
Hg isotope ratios determined in all samples, especially the odd-MIF.
Moreover, the inverse relationship (r2= 0.45, p < 0.01)
between Δ199Hg and δ202Hg was inconsistent with the
experimental results of photoreduction that generally showed positive
correlation for the residual Hg pool (here particles) (Bergquist and Blum,
2007; Zheng and Hintelmann, 2009). All these arguments suggest that these
processes may not be the major mechanism to produce large, even contrasting, Hg
isotope variation in Hg-enriched fine atmospheric particles. A recent study
reported Hg, isotopic fractionation during Hg0 oxidation showed a
positive relationship between Δ199Hg and
δ202Hg for Cl-initiated oxidation but a negative
relationship for Br-initiated oxidation. Though our PM2.5 samples also
displayed a decrease in Δ199Hg with δ202Hg
(Fig. 2), similar to the Br-initiated oxidation, they had a
Δ199Hg / Δ201Hg ratio (1.1) lower than that
(1.6 ± 0.3) of Br-initiated oxidation, and much lower than that
(1.9 ± 0.2) of Cl-initiated oxidation (Sun et al., 2016). Though we
cannot exclude the contribution of Hg0 oxidation to PM2.5-Hg, given
the fact that halogen-initiated oxidation would not largely occur in in-land
atmospheric boundary layer, oxidation would not be a dominant controlling
factor causing the seasonal variation in Hg isotopes in PM2.5 particles.
We thus suggest that the contributions from different sources may be the
better scenario to explain the seasonal variation in Hg isotopic
compositions we measured for the PM2.5 samples.