Introduction
Since the previous century, large quantities of organic pollutants (OPs), such
as organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and
polycyclic aromatic hydrocarbons (PAHs), have been discharged into the
global environment. Soils, water bodies, and snow/ice are generally
considered to be reservoirs or sinks of these pollutants (Dalla Valle et al.,
2005; Froescheis et al., 2000; Guglielmo et al., 2012). However, due to the
influence of global warming (Komprda et al., 2013; Noyes et al., 2009),
growing evidence indicates that OPs previously stored in reservoirs can be
rereleased back into the environment (Ma et al., 2011). For example, air–soil
exchange of OCPs has showed the re-emission of OCPs from previously contaminated
soils in Europe (Ruzickova et al., 2008), North America (Kurt-Karakus et
al., 2006), and India (Chakraborty et al., 2015). Modelling results have
suggested that large parts of the global ocean have been losing
dichlorodiphenyltrichloroethane (DDT) via volatilization (Stemmler and
Lammel, 2009). In addition, air–sea exchange of PAHs has revealed that the
seawater in the Mediterranean has turned into a temporary secondary source
of PAHs, which is related to biomass burning in that region (Mulder et al.,
2014). Moreover, melting ice and glaciers have also released OPs back into
the atmosphere, which buffers the decline of OP levels in the polar regions
(Ma et al., 2011; Geisz et al., 2008).
Similarly to the polar regions, the Tibetan Plateau (TP) has been regarded as a
convergence zone of OPs (Wang et al., 2016). Due to the continuous use of OPs
in the surrounding countries and the “cold trapping” by the TP, the
enrichment of OPs in the TP environment has been reported (Sheng et al.,
2013; Wang et al., 2015). However, the TP has experienced significant warming (Liu
and Chen, 2000), and results of the air–soil exchange of OPs have indicated
that the Tibetan soils are acting as a sink of DDT and higher molecular
weight PAHs, but are a potential secondary source for hexachlorobenzene (HCB)
and hexachlorocyclohexanes (HCHs) (C. F. Wang et al., 2014; X. P. Wang et
al., 2012). This shows that the cold temperature over the TP might not be
sufficient to trap volatile OPs. More studies on the air–surface exchange of
OPs over the TP are therefore needed to test the role of the terrestrial and
aquatic ecosystems of the TP in the regional cycling of OPs.
Known as “Asia's water power”, the TP contains the headwaters of many major
rivers in Asia, which provide water sources for about one-sixth of the
world's population (Yao et al., 2012). The TP also has large numbers of
remote lakes that are important components of water bodies. Low temperature,
oligotrophic conditions, and the long duration of ice cover are distinct
features of these lakes. Based on the higher atmospheric concentrations of
α-HCH in summer, Xiao et al. (2010) deduced that these enhanced
concentrations may be caused by the thawing of lake ice, which promotes the
re-evaporation of α-HCH. However, the study did not include
measurements of HCH levels in lake water or the corresponding air–water
exchange analysis (Xiao et al., 2010). Therefore, it is still unclear whether
the lake water of the TP is the secondary source of a large number of OPs.
Furthermore, biomass burning is a widespread activity over the TP (Hu et al.,
2015). A recent study demonstrated that the locally sourced biomass
combustion particles contributed substantially to the black carbon (BC)
loading of the TP glacier (Li et al., 2016). Given that PAHs and BC both
mainly originate from incomplete combustion of biomass, regional air–water
exchange of PAHs would also contribute to the overall air–surface exchange of
carbon.
Location of Nam Co lake on the Tibetan Plateau (a) and the
sampling sites for air and lake water (b). The station is the Nam Co
Monitoring and Research Station, and it is also the air-sampling site; S01 to
S15 represent the 15 sampling sites of surface water around the lake; the red
triangle represents the sampling site of seasonal water from May to
September.
We therefore conducted air and water sampling in a remote lake on the TP,
and assessed the air–water gas exchange, and the dry and wet deposition
processes of OCPs, PCBs, and PAHs. The aims of this study were to ascertain
whether the Tibetan lake represents a secondary source of OPs, to
investigate the influence of seasonal lake ice melting on the gas exchange
of different OPs, and to estimate the contribution of PAH exchange to the
lake carbon budget.
Materials and methods
Site description
Nam Co lake (30∘30′–30∘56′ N,
90∘16′–91∘01′ E, 4718 m) is located in the north of
the Nyainqêntanglha Mountains, on the central TP (Fig. 1). It is the
second largest lake in Tibet with an area of 2015 km2 and a maximum
depth exceeding 90 m (Wang et al., 2009). The lake is mainly supplied by
precipitation and glacier meltwater. Annual riverine delivery of water to the
lake is approximately 1.3 × 109 m3 yr-1, while
there is no outflow (Wu et al., 2014). The lake water is alkaline
(pH = 9.21) and slightly saline (Wang et al., 2009). The climate of Nam
Co is relatively cold and windy with an annual average temperature of
∼ 0 ∘C and an annual wind speed of ∼ 4 m s-1. The
regional climate also has large seasonal variation: the Indian monsoon
dominates in summer (May to September) and the westerlies the control winter
climate (October to April) (Fig. S1 in the Supplement). High temperatures and
precipitation are usually observed in summer (Fig. S2), and the lake begins
to thaw from the beginning of May and melts completely by the end of May,
which coincides with the onset of the Indian monsoon. During the winter, the
lake is covered by ice due to the subzero temperatures (Fig. S2) and maximum
instantaneous wind speeds reaching up to 9.9 m s-1.
The dominant land cover in Nam Co is alpine steppe and meadow, and the local
residents herd yak and sheep that graze around the lake. Biomass burning
occurs for heating, cooking, transport, and religious reasons. Near the
south-eastern shore, the Nam Co Monitoring and Research Station for
Multisphere Interactions (NCMORS) is operated by the Chinese Academy of
Sciences (Fig. 1b). This station not only facilitates the consecutive
collection of field samples used in the current study, but also provides
local meteorological parameters for flux calculations.
Air and water sampling
An active air sampler (AAS) was deployed on the roof of NCMORS (Fig. 1b) and
air monitoring was conducted for 2 consecutive years from September 2012 to
September 2014. The flow rate of AAS was 60 L min-1 and the air
samples were collected every 2 weeks with a volume of approximately
600 m3 for each sample. The airstream first passes through glass fibre
filters (GFFs 0.45 µm, Whatman) to collect the total suspended
particles (TSP) and then through polyurethane foam (PUF, 7.5 × 6 cm
diameter) to retain the OPs in gas phase. In total, 47 air samples were
collected. Details regarding the sampling period, average air temperature,
and wind speed are given in Table S1 in the Supplement. All harvested PUF and
GFFs were stored at -20 ∘C until extraction.
To determine the OP levels in water, two sampling programmes were conducted.
First, 15 sites around the Nam Co lake (surface lake water, 0–1 m depth)
were selected to obtain the spatial distribution of OPs in lake water
(Fig. 1b), which provides a direct overview of OP contamination over the
lake. Second, monthly water samples were collected at a site close to NCMORS
(Fig. 1b) from May to September 2014 (water samples were not obtained during
winter due to the ice cover). This provided information regarding temporal
variations in OP levels, isomer ratios, and the enantiomeric fraction in lake
water. Furthermore, coupled with the monthly average air concentrations of
individual OPs obtained, this allowed us to investigate the air–water gas
exchange of OPs (direction, flux, and monthly variations).
Water samples (200 L) were filtered with GFFs (0.7 µm, Whatman) to
obtain the total suspended particulate matter (SPM), then pumped through an
XAD-2 resin column to collect the dissolved-phase compounds. For each
sampling month, triplicate samples were collected. In total, 15 samples for
the spatial study and 15 samples for the temporal study were collected. XAD
columns were kept at 4 ∘C until extraction. The lake water
properties (temperature, pH, and salinity) are provided in Table S2.
Sample extraction and analysis
The chemical extraction and clean-up methods are detailed in Text S1 for each
sample type [air (PUF plug), TSP, water (XAD column), and SPM]. OPs were
analysed on a gas chromatograph with an ion-trap mass spectrometer (GC-MS,
Finnigan Trace GC/PolarisQ) operating under MS–MS mode. More information on
the chromatographic conditions is given in Text S2. The target compounds are
as follows: HCHs (including α-HCH, β-HCH, and γ-HCH),
HCB, DDTs (o,p′-DDE, p,p′-DDE, o,p′-DDT, and p,p′-DDT), PCBs (PCB 28,
PCB 52, PCB 101, PCB 138, PCB 153, and PCB 180), and 15 priority PAHs listed
by the United States Environment Protection Agency (USEPA, without
naphthalene), including acenaphthylene (Acel), acenaphthene (Ace), fluorene
(Flu), phenanthrene (Phe), anthracene (Ant), fluoranthene (Fla), pyrene
(Pyr), benz[a]anthracene (BaA), chrysene (Chr), benzo[b]fluoranthene (Bbf),
benzo[k]fluoranthene (Bkf), benzo[a]pyrene (BaP), dibenz[a, h]anthracene
(DahA), benzo[g, h, i]perylene (BghiP), and indeno[1,2,3-cd]pyrene (IcdP).
Enantiomers of α-HCH were determined with a BGB-172 chiral column
(see Text S2 for details). The chiral signature of α-HCH is expressed
using the enantiomeric fraction (EF), which is equal to the ratio of peak
areas of the (+)/[(+)+(-)] (Harner et al., 2000).
Quality assurance/quality control (QA/QC)
All analytical procedures were monitored using strict QA/QC measures. Prior
to sampling, PUF and XAD resin were precleaned using dichloromethane (DCM)
for 16 h and GFFs were baked at 450 ∘C for 4 h. Six PUF field
blanks, three XAD field blanks, and six procedural blanks were prepared; HCB,
Phe, Ant, Fla, and Pyr were detected in the field blanks (Table S3). The
definitions of the method detection limits (MDLs) are described in Text S3,
and the derived MDLs are given in Table S4. The breakthrough of PUF plugs was
checked in 11 split PUFs, and the results show that the individual OPs in the
second half varied from 8 to 23 % (Table S5), indicating good retention
capacity. Certified surrogate standards (from Dr. Ehrenstorfer GmbH, Germany)
were added to each sample before extraction and analysis. The recoveries
ranged from 71 to 94 % for PCB 30, 79 to 105 % for Mirex, and 65 to
92 % for perylene-D12. The reported concentrations were subtracted by
mean blanks but not corrected for recoveries. To check the reproducibility of
the chiral analysis, the racemic standard of α-HCH was injected
repeatedly and its average EF value was 0.499 ± 0.001 (n=5).
Calculations of air–water gas exchange
Concurrent air and water samples were used to assess the status of air–water
gas exchange in Nam Co lake. The gas exchange direction can be determined by
the ratio of fugacity in water (fw) and air (fa),
giving the fugacity ratio (fw/fa) (Jantunen et al.,
2015):
fa=CGRTafw=CwH,
where CG and Cw are the gaseous and dissolved
concentrations of target compounds in the air and water (mol m-3), R
is the gas constant (8.314 Pa m3 mol-1 K-1), Ta (K) is the air temperature, and H (Pa m3 mol-1)
is the Henry's law constant. Due to the possible sorption by dissolved
organic carbon (DOC), OPs retained by XAD were DOC corrected to derive the
truly freely dissolved concentrations in water (Text S4) (Gonzalez-Gaya et
al., 2016). H values were adjusted for the real water temperature and
salinity of Nam Co by the procedure described in Text S5 (Cetin et al., 2006;
Ma et al., 2010). The uncertainty involved in fw/fa was
estimated by propagating the errors in Ca (30 %),
Cw (35 %), and H (20 %), which was 50 %.
Accordingly, ratios of fw/fa between 0.5 and 1.5 are
assumed to be at air–water equilibrium, while
fw/fa>1.5 and < 0.5 indicate net
volatilization and deposition.
Net fluxes of air–water gas exchange (FAW,
ng m-2 d-1) were quantified using the Whitman two-film model,
which has been used in many previous studies (Iwata et al., 1993; Khairy et
al., 2014):
FAW=KolCw-CGRTa/H,
where Kol (m s-1) is the overall mass transfer coefficient,
which contains contributions from the mass transfer coefficients of the water
and air layers, Kw and Ka. They are related to the
wind speed and compound-specific molecular diffusivity; a detailed
calculation is presented in Text S6. Positive flux values indicate net
volatilization, and negative values indicate net deposition.
Estimation of dry and wet deposition fluxes
In addition to the gas exchange, dry and wet deposition are also important
processes that control the input of OPs from the air to the lake. Dry
deposition fluxes (FDD, ng m-2 d-1) of atmospheric
particulate-phase OPs can be calculated using (Gonzalez-Gaya et al., 2016)
the following equation:
FDD=0.864VDCP,
where VD (cm s-1) is the compound-specific deposition
velocity, CP is the measured OP concentrations in TSP
(pg m-3), and 0.864 is a unit conversion factor. VD for
each sampling period and compound was estimated using an empirical equation
derived by Gonzalez-Gaya et al. (2014):
logVD=-0.261logPL+0.387U10Chls-3.082,
where PL (Pa) is the subcooled liquid vapour pressure of the
chemicals that was corrected to the local temperature using the equations
given in Table S6, U10 (m s-1) is wind speed at 10 m height
converted from the field-measured wind speed at 1.5 m (Table S1), and Chls
is the surface chlorophyll concentration (mg m-3, Liu et al., 2010).
Wet deposition fluxes by rain (FWD, ng m-2 d-1) were
estimated using the method established by Jurado et al. (2005):
FWD=PWGCG+WPCP,
where P is precipitation depth per day (m d-1) derived from the data
recorded in the NCMORS, and WG and WP are the gas and
particle washout ratios. Assuming that equilibrium is attained between the
gas phase and the dissolved phase in a raindrop, WG was
estimated by (Wania et al., 1998a)
WG=RTa/H.
The recommended value of WP in Jurado et al. (2005) was used to
consider particle scavenging by rain.
For snow deposition, the fluxes were calculated by adopting the washout
ratios reported in Franz and Eisenreich (1998) (Table S7).
Results and discussion
We determined the OP concentrations in the air, TSP, water, and SPM
separately; the full data sets are listed in Tables S8–S11. OCPs and PCBs
were rarely detected in TSP (Table S9), and were therefore not considered in
further discussions. Comparisons between the data from this study and
previously published values for the TP and other remote regions are presented
in Tables S12–S15.
Levels of OPs in air and water at Nam Co
The concentrations of OPs in the atmosphere and TSP in Nam Co are summarized
in Fig. 2 using box-and-whisker plots. Among the OCPs, HCB was the dominant
chemical with an average concentration of 20 pg m-3 (Fig. 2a), which
was two times higher than that reported for south-eastern TP (Sheng et al.,
2013) and Mt Everest (Li et al., 2006) (Table S12), but lower than the values
in the Rocky Mountains (42 pg m-3, Wilkinson et al., 2005) and the
Arctic (64 pg m-3, Su et al., 2006). The α-HCH (average
4.0 pg m-3) and γ-HCH (2.1 pg m-3) values in this study
were much lower than those measured using a flow-through sampler (FTS) from
2006 to 2008 (48.7 and 7.9 pg m-3 respectively) (Xiao et al., 2010).
The DDT concentrations in the current study (0.8–46.4 pg m-3) were
lower than those observed for Lulang in south-eastern TP (Table S12) (Sheng
et al., 2013), which is the entrance of the Indian monsoon. In spite of this,
the levels of DDTs were still 1 order of magnitude higher than those for the
Arctic (Table S12) (Su et al., 2008). Lower concentrations of ∑6PCBs
were also detected in the air with an average value of 2.5 pg m-3.
Air concentrations of gaseous OCPs and PCBs (a), gaseous
PAHs (b), and particulate-phase PAHs (c) in Nam Co. The
boxes are defined by the 25th and 75th percentiles, whiskers mark the 10th
and 90th percentiles, the median is represented by a horizontal line, the
mean by a square, and outliers with an asterisk.
The sum concentrations of ∑15PAHs in the atmosphere ranged from
0.5–13 and 0.1–3.4 ng m-3 in the gaseous and particulate phases,
with averages of 2.2 and 0.6 ng m-3 respectively. The 3- and 4-ring
PAHs were predominant in both phases, including Phe, Flu, Fla, and Pyr
(Fig. 2b and c). The PAH levels in Nam Co were 1 order of magnitude lower
than those reported for Lhasa (35.7 ng m-3, Table S13), which is the
capital city of Tibet and has a large population, extensive tourism, and
abundant religious activities (Gong et al., 2011). Compared with background
levels in other regions of the world (Table S13), the PAHs in this study were
comparable to the levels in Arctic air (Ding et al., 2007), but were
significantly higher than those from European mountainous regions (Fernandez
et al., 2002).
In the lake water, the average dissolved concentrations of α-HCH,
β-HCH, γ-HCH, HCB, and PCB 28 were 9.9, 85.2, 7.0, 7.6, and
1.9 pg L-1, while DDT-related compounds were below MDLs in most cases
for both dissolved and SPM phases (Tables S10 and S11). The current measured
HCH concentrations were approximately 2 orders of magnitude lower than values
reported for the Yamdrok and Co Ngoin Lake in 2002 (Table S14) (Zhang et al.,
2003). Two possible reasons for this discrepancy are (i) the interannual
variation of chemicals; i.e. the concentrations declined rapidly since 2002;
and (ii) the uncertainties caused by analytical and instrumental method
(electron capture detector in Zhang et al. (2003) study and the MS detector
in the current study). From a global perspective, the HCH concentrations
obtained by this study were overall lower than those in European mountain
lakes (Table S14). DDT class chemicals were rarely detected and only PCB 28
could be quantified in the Nam Co lake water. These features combined with
the low levels of HCHs suggest that the OP levels in Nam Co lake water were
close to the values reported for ocean waters, such as the North Atlantic and
Arctic oceans (with DDTs and PCBs mostly below the detection level, or
< 1 pg L-1) (Gioia et al., 2008; Lohmann et al., 2009). By
contrast, high levels of PAHs were found in the Nam Co lake water, ranging
from 6.9 to 83.6 and 1.7 to 28 ng L-1 for the dissolved and SPM
phases. The dissolved ∑15PAH levels were 1 order of magnitude higher
than those reported for Himalayan high-altitude lakes in Nepal (Table S15)
(Guzzella et al., 2011) and the Great Lakes (Table S15) (Venier et al.,
2014), and 2 orders of magnitude greater than values for open oceans
(Table S15) (Ma et al., 2013) and European mountain lakes (Table S15)
(Vilanova et al., 2001).
Possible sources
Long-range atmospheric transport (LRAT) is considered an important source for
the occurrence of OPs in remote environments (Dalla Valle et al., 2005).
Considering that the prevailing climate system operating over Nam Co in
summer is the Indian monsoon, if the seasonal pattern of a chemical is
similar to that of the monsoon, monsoon transport may therefore be the source
of OPs in Nam Co air. Thus, the interrelationship between monsoon intensity
(Indian monsoon index, IMI, W m-2) and OP concentrations was
investigated (Fig. 3). Figure 3 shows that α-HCH and o,p′-DDT
displayed synchronous seasonal variation with the IMI. This suggests that
monsoon transport was the principal reason for the occurrence of OCPs in the
Nam Co atmosphere. In addition, isomer ratios can provide insight into the
source and fate of the OPs. In this study, we found that the isomer ratios of
p,p′-DDT to p,p′-DDE were broadly in agreement with those found for the
source regions of India and the Bay of Bengal (Table S16) (Gioia et al.,
2012; Zhang et al., 2008). Similar to other remote regions, such as the
Arctic (Hung et al., 2010), Antarctic (Baek et al., 2011), Rocky Mountains
(Daly et al., 2007), and south-eastern TP (Sheng et al., 2013), in which LRAT
is the primary transport mode of OPs, the dominance of α- to γ-HCH was observed in the Nam Co atmosphere (Table S16). Results of isomer
ratios associated with the seasonal variations supported the interpretation
that OCPs in the Nam Co atmosphere had undergone LRAT. In contrast to OCPs,
neither the gaseous nor the particulate phases of PAHs showed a clear and
consistent seasonal variation during the 2 years of air monitoring (Fig. S3),
which is likely because there were primary emissions of PAHs surrounding the
Nam Co region.
Seasonal patterns of the Indian monsoon index, the atmospheric
concentrations of α-HCH and o,p′-DDT.
Apart from the seasonal trends, spatial distribution patterns can also
provide valuable information on OP sources. The spatial distributions of OPs
in the surface water across the Nam Co lake are presented in Fig. 4. First,
HCHs showed a uniform distribution (Fig. 4a) without significant differences
among the different regions of the lake (Table S17). The even distribution of
HCHs in the water was most likely caused by the LRAT origins and relatively
higher water solubility. Second, relatively high levels of HCB and PAHs
occurred in water from the north-western and eastern parts of the lake
(Table S17, Fig. 4b and c). The elevated HCB and PAHs in these regions were
likely related to anthropogenic activity in the vicinity. As shown in
Fig. 1b, two townships (Baoji and Namco), which have the highest populations
around Nam Co lake, are located at the north-western and eastern corners of
the lake. Following a traditional lifestyle, the residents use large amounts
of local biomass (mostly yak dung) for cooking and heating (Xiao et al.,
2015). High PAH concentrations have been reported in local Tibetan tents
which were emitted mainly from burning yak dung (Li et al., 2012). A ratio of
BaA / (BaA + Chr) = 0.33 was recommended as a specific diagnostic
fingerprint for yak dung combustion (Li et al., 2012). The
BaA / (BaA + Chr) ratios observed in our study (0.27 ± 0.08 for
air and 0.24 ± 0.10 for water) were in good agreement with this
diagnostic ratio. This suggests that local combustion emissions are likely to
be the source of PAHs in Nam Co. With the exception of PAHs, biomass
combustion can also produce HCB (Bailey, 2001), which may be the reason for
the higher HCB concentrations around the townships. The spatial distribution
of OPs in the Nam Co lake water highlights the important contribution of
local sources for PAHs and HCB.
Spatial distribution pattern of HCHs (a), HCB (b), and PAHs (c) in
the surface water of Nam Co lake.
LRAT versus revolatilization
From the above results, we found that LRAT is a key factor that determines
the seasonality of the atmospheric HCHs and DDTs in Nam Co (higher
concentrations occurred in summer). However, high temperatures generally
occur during summer, which may promote the evaporation of chemicals from
local surfaces (e.g. soils and water bodies). To what extent does this
re-evaporation contribute to the atmospheric OPs? The Clausius–Clapeyron
(C.C.) equation can be used to assess this probability (Wania et al., 1998b).
If a strong relationship is found between the partial pressure of atmospheric
OCPs and the air temperature, this indicates that volatilization may occur.
Otherwise, low temperature dependence will occur in the case of LRAT. In the
present study, the results of the C.C. equation are summarized in Table S18.
The correlation with temperature (p>0.05, Table S18) for most
chemicals was not significant, except for α-HCH, which displayed a
relatively lower correlation coefficient (R2= 0.29, p<0.05,
Table S18). This indicates that weak volatilization of α-HCH from
local surfaces at Nam Co may exist, while the re-evaporation of other
chemicals is limited.
Enantiomers of chiral OPs have been used to distinguish the contribution of
LRAT and revolatilization of OPs from surfaces (Bidleman et al., 2012). For
example, technical HCH contains the (+)- and (-)-α-HCH
enantiomers in a racemic proportion (EF = 0.5). Abiotic processes
(transport, hydrolysis, and photolysis) do not favour either enantiomer,
while only biological processes, such as microbial degradation in soils and
water, show enantioselectivity and will alter the EFs of α-HCH (Ridal
et al., 1997). Therefore, near-racemic signatures usually indicate input from
LRAT, while non-racemic signatures represent the influence of local microbial
degradation. In the present study, both the enantiomeric signatures of
α-HCH in the air and water were measured simultaneously from May to
September. As shown in Fig. 5a, all the lake water samples showed a selective
depletion of (+)α-HCH, with EFs ranging from 0.318 to 0.449. This
has previously been reported for other cold oligotrophic water systems, such
as the Arctic lakes (EFs: 0.359–0.432) (Law et al., 2001). From Fig. 5a, we
found that extensive enantioselective degradation occurred in June and July,
which coincided with the bacterial bloom period (Fig. 5b) (Liu et al., 2013).
This negative correlation between the EF of α-HCH in lake water and
bacterial abundance is presented in Fig. S4. Law et al. (2001) suggested that
under low nutrient conditions, oligotrophic bacteria are able to use
xenobiotic carbon sources, such as α-HCH. This implies that the
Tibetan lake microbes can also metabolize, or cometabolize, α-HCH.
Enantiomer fraction (EF) of α-HCH in the air and surface
water from May to September (a), and the seasonal bacterial abundance in Nam Co lake water (b). The data of bacterial abundance was derived from Liu et
al. (2013), which represents the total bacteria in the lake surface water.
Water/air fugacity ratios (fw/fa) for OCPs and
PCB 28 (a), and individual PAHs (b) in Nam Co lake. The
horizontal lines represent the uncertainty range, 0.5–1.5 was considered to
be at equilibrium.
If high temperatures favour the evaporation of α-HCH from the lake
water, depletion of (+)α-HCH should be observed for air. However,
overall the EFs of the air samples were racemic. This is similar to the
racemic composition observed in the atmosphere over Indian regions (Huang et
al., 2013), which are the potential source regions of HCHs in Nam Co. With
respect to the enantiomeric signature in air samples from June and July, only
some (+)α-HCH depletion was observed in the air (Fig. 5a),
indicating weak evaporation of α-HCH from the lake water. Combined
with the EF values in air and water, the fraction of the contribution from
lake water volatilization (f) can be quantified by (Huang et al., 2013)
f=EFa-EFb/EFw-EFb,
where EFa and EFw are the EF values in air and water,
and EFb is the background EF value in air, which was assumed to
be the average EF of the standard. The estimated results show that only 19
and 17 % of atmospheric α-HCH came from water volatilization in
June and July, demonstrating that LRAT is indeed the major source (more than
80 %) of α-HCH. This result is in contrast with the conclusion of
Xiao et al. (2010), who reported that evaporation from Nam Co lake largely
contributes to the atmospheric α-HCH concentration. In that study,
both levels and enantiomeric signatures of α-HCH in Nam Co lake water
were absent.
Atmospheric processes
Air–water gas exchange
Although some α-HCH evaporation was recorded in June and July, the
air–water exchange process during the entire ablation period is of great
importance as this is the main season for transferring pollutants between air
and water. Fugacity ratios (fw/fa) and net exchange
fluxes (FAW, ng m-2 d-1) were quantified using paired
air–water samples collected from May to September in 2014. The average
exchange status (average of fw/fa) for HCHs, HCB, PCB
28, and PAHs during the ablation period is illustrated in Fig. 6. Because of
DDTs, Ant and Fla were not quantified in the lake water (Table S10) and were
therefore excluded from the discussion. α- and γ-HCH had low
fw/fa values ranging from 0.08 to 0.15, and 0.02 to
0.08 (Fig. 6a). The low fw/fa ratio suggests that
α- and γ-HCH were overall prone to deposition from the air to
the water during the ablation period. The deposition fluxes were
-1.6 ± 0.4 ng m-2 d-1 for α-HCH and
-1.0 ± 0.2 ng m-2 d-1 for γ-HCH, which are
within the same order of magnitude as those reported for the Great Lakes
(Khairy et al., 2014). Connected to the source of HCHs discussed above, this
result implies that the following LRAT-deposition event of HCHs occurred in
the ablation period of Nam Co lake. In terms of β-HCH, HCB, and PCB
28, their fw/fa ratios were either overlapping with the
equilibrium range (0.5–1.5) or on the edge of deposition threshold.
Therefore, low deposition fluxes for β-HCH
(-0.2 ng m-2 d-1) and PCB 28 (-0.1 ng m-2 d-1),
and large variability for HCB (-1.0 ± 0.6 ng m-2 d-1)
were observed (Fig. 7a).
Average air–water gas exchange fluxes (FAW) for individual
OCPs, PCB 28 (a), and PAHs (b, c) in Nam Co lake. Positive values indicate
net volatilization, and negative values indicate net deposition.
The results of the air–water gas exchange for PAHs are presented in Fig. 6b.
The fugacity ratios of 13 PAHs varied depending on their molecular weight and
volatility (Fig. 6b). Acel, Ace, and Flu showed fw/fa
values significantly higher than 1.5 (Fig. 6b), indicating that the lake
acted as a secondary source for these volatile chemicals. Thefw/fa values for Phe covered a large range (from 0.3 to
3), showing a shift between volatilization and deposition (Fig. 6b). Other
high molecular weight (MW > 202) PAHs, including Pyr, BaA, Chr,
Bbf, Bkf, Bap, IcdP, DahA, and BghiP, favoured net deposition with
fw/fa values lower than 0.5 (Fig. 6b). Greater
volatilization fluxes were observed for Acel, Ace, and Flu (3-ring), which
could reach up to 203 ng m-2 d-1 (Fig. 7b). Whereas, the gaseous
deposition fluxes for high molecular weight PAHs were 2 orders of magnitudes
lower and only varied from -1.0 to -4.6 ng m-2 d-1
(Fig. 7c). Although average deposition fluxes of 339 ng m-2 d-1
were calculated for Phe, the deposition fluxes showed large variability
(±604 ng m-2 d-1). This result is broadly consistent with
the exchange direction revealed by the fw/fa values,
implying that the exchange of Phe between air and water may be reversed
during the entire ablation period.
Reversal of the air–water exchange of Phe
In Sect. 3.4.1, we observed that both the air–water exchange direction and
the flux of Phe showed a large range of values and uncertainties. This raises
the question of what drives this variation. The monthly calculated
fw/fa and FAW of Phe during the ablation
period showed that the volatilization of Phe occurred during May and June,
but deposition begun in July, which represents a reversal (Fig. 8). Given
that lake ice begins melting during May, the melted ice may discharge large
amounts of accumulated PAHs into the lake, causing the relative enrichment
(high fugacity) of Phe in the water, and triggering the secondary emission of
Phe from the water to the atmosphere. This was confirmed by the increased
water concentration of Phe found during May and June (Table S10). This is
also why a large uncertainty of FAW was observed for Phe during
the ablation period. Linked to the source of PAHs discussed above, the final
exchange status of PAHs is the combined effects of the depositional input
caused by biomass burning, the properties of the chemical, and the melting of
lake ice.
Reversal of the air–water gas exchange for Phe from May to
September.
Seasonal ice cover is an important feature of water bodies in cold regions.
In the Arctic region, Jantunen et al. (2008) and Wong et al. (2011) both
observed the occurrence of volatilization of OCPs from seawater coincident
with the break-up of ice cover in the summer. The Nam Co lake also undergoes
long periods of ice cover (Liu et al., 2013). During the winter, the lake
surface is covered by ice, and gas exchange is restricted; meanwhile dry and
wet deposition exert a significant influence on the input inventory of PAHs
to the lake. Both of these deposition processes are one-way (no
volatilization), which keeps the contaminants being accumulated. As summer
arrives, the lake ice begins to thaw and air–water gas exchange begins to
dominate. On one hand, after the higher accumulation of deposition,
supersaturation of PAHs in the lake may occur. On the other hand, the
fugacity capacity of ice is much higher than that of water, and therefore the
decrease of the fugacity capacity during melting will increase the fugacity
of the PAHs (Wania et al., 1998c), which also promotes their re-emission from
the water. Although the seasonal ice cover did not show any obvious influence
on the fate of OCPs and other PAHs, it played an important role in the fate
of Phe, which was a dominant compound in the Nam Co atmosphere. The lake
therefore acted as a secondary source of Phe in May and June, and shifted to
a net sink during other months, which is likely driven by the seasonal
freeze–thaw cycle of lake ice (Fig. 8).
Atmospheric degradation
Reactions with the hydroxyl radical (OH) are an important removal process of
gaseous OPs from the atmosphere. The resulting degradation fluxes
(Fdeg, ng m-2 d-1) are dependent on the concentration
of OH radicals in the air (Spivakovsky et al., 2000) and the
compound-specific degradation rate constant (KOH,
cm3 mol-1 d-1). The KOH values of gaseous OCPs
and PAHs are from Brubaker and Hites (1998) and Keyte et al. (2013)
respectively. Due to the lack of information on KOH for β-HCH and BaA, their degradation fluxes (Fdeg) were not
considered in this study. The calculated Fdeg values were
averaged for individual OPs and are presented in Fig. S5. The degradation
fluxes for α-, γ-HCH, HCB, and PCB 28 ranged between 0.3 and
0.9 pg m-2 d-1 (Fig. S5), 3 orders of magnitude lower than their
FAW. This indicates that the contribution of atmospheric
degradation to their total inventory in the environment is negligible.
In contrast to the OCPs, the PAHs are more susceptible to photodegradation
(Lohmann et al., 2009). In our study, lower molecular weight PAHs showed
higher degradation fluxes, such as 4–184 ng m-2 d-1 for Phe,
and 1–160 ng m-2 d-1 for Ant (Fig. S5). These values are
similar to those reported for Fdeg in the remote atmosphere of
the Atlantic Ocean (i.e. 7–120 and 9–50 ng m-2 d-1 for Phe and
Ant respectively) (Nizzetto et al., 2008). We observed relatively low
Fdeg values for 5- and 6-ring PAHs, ranging from 0.01 to
0.18 ng m-2 d-1 (Fig. S5). Generally, the Fdeg of
all PAH compounds was 1 order of magnitude lower than their FAW.
OH depletion is the primary process that removes atmospheric PAHs, presumably
causing the continuous volatilization of low molecular weight PAHs from the
water. This raised questions about other processes that may have supplied
PAHs to the lake water. On the other hand, OH degradation also decreases the
input of high molecular weight PAHs into the water and it is unclear to what
extent this degradation counteracts other deposition processes.
Atmospheric deposition
In addition to the gas exchange, dry and wet deposition are also important
processes that influence the input of OPs from the air to the lake. Dry
(FDD) and wet (FWD) deposition fluxes were estimated
using the method described above (Sect. 2.6). With respect to HCHs, HCB, and
PCB 28, their dry deposition fluxes (FDD) were negligible due to
their low detection frequency in the particulate phase (Table S9). However,
the average FWD for α-HCH, β-HCH, and γ-HCH were -0.3, -0.9, and -0.4 ng m-2 d-1, which is
comparable to their FAW levels. FWD for HCB
(-0.02 ng m-2 d-1) and PCB 28
(-0.002 ng m-2 d-1) was 2 orders of magnitude lower than their
FAW. In general, precipitation scavenging is most efficient in
HCHs compared with the other chemicals (Carrera et al., 2002). Greater wet
deposition fluxes of HCHs occurred in August (Fig. S6), coinciding with the
highest amount of precipitation in Nam Co. Combining the FAW and
FWD of HCHs, the estimated annual input of HCHs from the air into
the whole lake (2015 km2) was 1.9 kg yr-1. This result
highlights the input of HCHs by the LRAT-deposition process during the
ablation period (open water season). Snow scavenging of HCHs has been
reported as an important clearing process in mountain regions (Kang et al.,
2009). However, the transport of HCHs in winter is very limited due to the
unfavourable air circulation patterns (westerly wind), ruling out the
significant contribution of HCHs by snow scavenging.
Estimated fluxes (ng m-2 d-1) of air–water gas exchange
(FAW), atmospheric degradation (Fdeg), dry deposition
(FDD), and wet deposition (FWD) for individual PAHs
during the ablation period and frozen periods.
PAH
Ablation period
PAH
Frozen period
FAW
Fdeg
FDD
FWD
Fdeg
FDD
FWD
Volatilization compounds
Acel
80 ± 49
6 ± 5
NA
-0.2 ± 0.1
Acel
1 ± 0.7
-0.02 ± 0.001
-0.03 ± 0.1
Ace
51 ± 19
4 ± 4
-0.003 ± 0.002
-0.4 ± 0.3
Ace
0.9 ± 0.5
-0.01 ± 0.01
-6 ± 5
Flu
203 ± 162
11 ± 8
-0.1 ± 0.02
-9 ± 7
Flu
1.8 ± 0.9
-0.2 ± 0.2
-43 ± 30
sum
335
21
-0.1
-9
sum
4
-0.2
-49
Phe
-340 ± 604
82 ± 67
-0.5 ± 0.1
-42 ± 35
Phe
10 ± 4
-2.2 ± 1.2
-345 ± 237
Ant
NA
60 ± 63
-0.04 ± 0.03
-5 ± 5
Ant
4 ± 2
-0.11 ± 0.05
-16 ± 14
Fla
NA
5 ± 5
-0.5 ± 0.1
-20 ± 18
Fla
0.5 ± 0.3
-4.6 ± 2.8
-93 ± 64
Deposition compounds
Pyr
-145 ± 154
20 ± 21
-0.4 ± 0.1
-18 ± 17
Pyr
2 ± 1
-3 ± 1.5
-128 ± 83
BaA
-19 ± 23
NA
-0.1 ± 0.1
-3 ± 4
BaA
NA
-1.1 ± 0.5
-15 ± 10
Chr
-54 ± 62
7 ± 8
-0.5 ± 0.3
-47 ± 56
Chr
0.2 ± 0.1
-4.7 ± 2.3
-19 ± 13
Bbf
-5 ± 3
0.2 ± 0.1
-0.6 ± 0.5
-6 ± 5
Bbf
0.02 ± 0.01
-2.2 ± 3.2
-4 ± 8
Bkf
-2 ± 1
0.2 ± 0.1
-0.4 ± 0.4
-2 ± 1
Bkf
0.1 ± 0.04
-3.8 ± 1.9
-8 ± 5
Bap
-2 ± 1
0.2 ± 0.2
-0.3 ± 0.5
-3 ± 1
Bap
0.04 ± 0.03
-4.7 ± 2.3
-16 ± 10
IcdP
-2 ± 1
0.7 ± 0.5
NA
-2 ± 2
IcdP
0.1 ± 0.1
NA
-3 ± 6
DahA
-1 ± 0.7
0.1 ± 0.1
NA
-0.1 ± 0.2
DahA
0.01 ± 0.01
NA
-0.6 ± 1
BghiP
-2 ± 0.4
0.02 ± 0.01
-1 ± 1
-3 ± 1
BghiP
0.01 ± 0.01
-12 ± 6
-6 ± 3
sum
-231
28
-3
-85
sum
2
-31
-199
Total PAHs
\
196
-4.5
-161
Total PAHs
20
-38
-702
NA: not available. For FAW, FDD and
FWD, positive values indicate volatilization, and negative values
indicate net deposition.
Compared with OCPs, the close association between PAHs and the particulate
phase accounted for their relatively higher deposition fluxes. The estimated
dry and wet deposition fluxes for individual PAHs during the ablation and
frozen periods respectively are provided in Table 1. We found that the
FDD values of PAHs for the ablation period are, in general, lower
than those for the frozen period. For example, the FDD of total
∑15PAHs increased by 1 order of magnitude from the ablation period
(4.5 ng m-2 d-1) to the frozen period
(38 ng m-2 d-1; Table 1). Two factors may lead to an increase of
FDD in winter: the increased wind speed during the winter season
and the growing particulate-PAH concentrations due to the enhanced combustion
activities in winter. Compared with other studies, the estimated
FDD for the total ∑15PAHs
(4.5–38 ng m-2 d-1, this study) is broadly within the range
reported for global oceans (8.3–52.4 ng m-2 d-1) (Gonzalez-Gaya
et al., 2014).
Wet deposition was found to be the dominant deposition process for the input
of PAHs into Nam Co (Table 1). This was expected because precipitation
scavenging of organic chemicals underlies the accumulation of pollutants in
mountain regions (Tremolada et al., 2008). In addition, there was an obvious
difference between the values of FWD during the ablation and
frozen periods. For the total 15 PAHs, the FWD in the frozen
period (702 ng m-2 d-1) was approximately five times higher than
that for the ablation period (161 ng m-2 d-1), which may be due
to the different precipitation types between these two periods (snow vs.
rain). Snow has been suggested to be more efficient than rain for scavenging
particulate PAHs, which had a high concentration during winter in Nam Co
(Table S9). Thus, although the precipitation of Nam Co in winter is low (less
than 30 mm, Fig. S2), the strong scavenging ratio of snow to PAHs combined
with the relatively high particulate-PAH concentration in winter caused
enhanced PAH deposition in winter. The frozen season coincided with the
period of high emission and high deposition of PAHs, implying a significant
contribution in this season of PAHs into the lake.
To calculate the comprehensive contribution of all above-mentioned processes,
three groups of PAHs were classified in Table 1 based on their fate during
the air–water exchange processes. PAHs (Acel, Ace, and Flu) showing
volatilization behaviour were placed into one group, PAHs with large
FAW variability between the status of volatilization and
deposition were in the second group, and the remaining PAHs displaying
deposition behaviour were placed into the third group (Table 1). In this
classification, although the air–water exchange direction and fluxes of Ant
and Fla cannot be estimated, we still placed them into the second group
because of their similarity to Phe in their physicochemical properties. For
the volatilization group, the total outgassing from the lake was estimated to
be approximately 126 kg per year, which cannot alone be supplied by their
total deposition flux (sum of FWD and FDD). This
suggests that there may be additional natural sources of PAHs in the lake,
such as degradation of pigments carrying aromatic structure and turnover of
organic matter (Nizzetto et al., 2008). Regarding the deposition group (Pyr,
BaA, Chr, Bbf, Bkf, Bap, IcdP, DahA, and BghiP), their total deposition flux
(FAW+FDD+FWD) will roughly cause an annual
input of 208 kg high molecular weight PAHs into the lake. Although the
FAW of Phe was reversed and the total volatilization of Phe was
estimated at around 26 kg yr-1, this loss will be complemented by the
continuous deposition of Phe (∼ 373 kg yr-1) from July to April.
This indicates that the annual net input of Phe will be above 340 kg, which
suggests that Phe is the most dominant contributor to the total PAH
deposition. In addition to the 15 PAHs considered here, there are other PAHs
with high abundances, for example alkylated phenanthrenes, which will drive
much larger depositional fluxes into the lake.
Uncertainties in flux estimation
Several factors were involved in the uncertainties of the flux estimation:
(i) loss during sample extraction and clean-up, (ii) measurement errors, and
(iii) accuracy of the parameters in meteorology and physicochemical
properties. The air–water gas exchange flux (FAW) is the most
important contributor to the total inventory of PAHs in the lake. The
uncertainty involved in FAW was estimated by propagating the
errors in Ca (30 %), Cw (35 %),
Kol (40 %), and H (20 %), which was 64 %. This
small error demonstrates that the estimate of the gas exchange fluxes was
relatively robust. By contrast, the uncertainties in other fluxes were
higher. The uncertainty of FDD was estimated as a factor of 3
(Gonzalez-Gaya et al., 2014). However, the uncertainties of Fdeg
and FWD are difficult to quantify due to unavailable data on the
relative errors of KOH, WG, and WP. For
example, the scavenging rates of PAHs by wet deposition were highly variable,
which was caused by the complexity of the size distribution of aerosols,
meteorological conditions, and the scavenging process (Jurado et al., 2005).
Considering these aggregated uncertainties, the estimated total fluxes here
are only expected to capture the order of magnitude for the different
processes. In addition, other input processes into the lake, such as glacier
meltwater, river run-off, and soil erosion may also occur in this study
region, which will lead to an underestimation of the total input flux.
Implication for the regional carbon cycling
Lakes are increasingly recognized as an important component of the
terrestrial carbon cycle (Tranvik et al., 2009). Nearly 50 % of the area
of Chinese lakes is located on the TP, with general oligotrophic conditions
and a total lake area of > 43 000 km2 (Zhang et al.,
2014). Compared with other components, such as grassland and forest, organic
carbon burial in Tibetan lakes has been largely ignored. Although our study
only focused on one of these lakes (Nam Co, area = 2015 km2), we
can extrapolate the annual atmospheric deposition of ∑15PAHs into the
remaining Tibetan lakes, and estimate it at 8.7 t C, when expressed as
carbon fluxes (Gonzalez-Gaya et al., 2016). In addition to these 15 PAHs,
there are other carbon sources such as soot, DOC, PAH derivatives, and other
anthropogenic organic compounds, which would become a significant
allochthonous carbon source for the oligotrophic lakes in TP. Because the
Tibetan lakes are low in nutrients, bacteria in the lake have adapted to
using a wide range of organic compounds and growing under starvation
conditions (Liu et al., 2009). Recently, bacteria from the genus
Sphingomonas were detected in Nam Co lake water and snow on various
glaciers in the TP (Liu et al., 2009, 2013), and they were reported to have
the ability to degrade PAHs (Leys et al., 2005). The presence of these
bacteria in Nam Co suggests that the atmospheric inputs of organic pollutants
can act as a carbon source to support the survival of Tibetan microbial
communities. Despite the natural PAH background in the environment, increased
biomass burning has led to the accumulation of PAHs in the lake sediments,
especially during the past 50 years (Yang et al., 2016). Therefore, the
continuous atmospheric deposition of various PAHs and their ecological impact
deserve greater attention.