Introduction
Mercury (Hg) is an important environmental contaminant because of its cyclic
transport between air, water, soil and the biosphere and its tendency to
bioaccumulate in the environment as neurotoxic mono-methylated
(CH3Hg-) compounds (Driscoll et al., 2013).
While assessments of Hg burden in environmental compartments are rather
concordant, the fluxes between them are less well constrained (Selin, 2009)
and specifically concern land ecosystem–atmosphere exchange of Hg0
(Zhang et al., 2012). Hg in the biosphere is derived primarily from
atmospheric deposition (Grigal, 2003), where foliar uptake of Hg0 has
been recognized as a principal pathway for atmospheric Hg to enter
terrestrial ecosystems (Frescholtz et al., 2003; Niu et al., 2011; Obrist,
2007). In turn, the availability of soil (inorganic) mercury to aerial parts
of terrestrial plants is generally low and the uptake is mainly retained in
the root zone (Cavallini et al., 1999; Meng et al., 2010; Cui et al., 2014).
Accumulated Hg in foliage is transferred to soil reservoirs via plant
detritus (St Louis et al., 2001) or may partially be released back into the
atmosphere (Bash and Miller, 2009). In addition, Hg may enter the foliage by
recycling processes, releasing Hg0 from underlying soil surfaces
(Millhollen et al., 2006). In a review (Sommar et al., 2013a), the majority
of reported Hg0 flux measurements over terrestrial soils indicate net
emission in warmer seasons and near-zero fluxes at cold temperatures.
Soil–air Hg0 exchange is controlled by numerous factors including
physico-chemical properties of and abiotic/biotic processes in the soil,
meteorological conditions and atmospheric composition (Bahlmann et al., 2006;
Carpi and Lindberg, 1997; Engle et al., 2005; Fritsche et al., 2008a; Gustin,
2011; Rinklebe et al., 2010; Mauclair et al., 2008; Zhang et al., 2008). For
bare low Hg-containing soils, Briggs and Gustin (2013) proposed a conceptual
model in which the soil moisture regimes largely dictate the level of
Hg0 flux. The presence of vegetation has an effect on the Hg0
efflux from ground surfaces by modifying soil moisture by evapotranspiration
as well as reducing light penetration, soil temperature and air mixing.
At landscape scale, Hg0 net exchange measurements may be made directly,
using micrometeorological (MM) methods above vegetation canopies (Bash and
Miller, 2009; Baya and Van Heyst, 2010; Cobos et al., 2002; Converse et al.,
2010; Edwards et al., 2005; Fritsche et al., 2008b; Kim et al., 1995; Marsik
et al., 2005; Sommar et al., 2013b). As for numerous trace gases (Fowler et
al., 2009), the exchange fluxes of Hg0 vary in sign and magnitude
(bi-directional exchange). From MM-flux measurements covering larger temporal
scales, it is inferred that vegetated ecosystems can represent both a source
and a sink for Hg0 over shorter or longer periods, depending on the
atmospheric concentration, meteorology, substrates, climate conditions and
plant community composition (Bash and Miller, 2009; Converse et al., 2010;
Lee et al., 2000). However, related Hg0 flux measurements over managed
ecosystems, such as croplands, are sparse and only at best seasonally
resolved (Baya and Van Heyst, 2010). Broader seasonal flux data sets are
desirable, since the annual net Hg0 flux over an ecosystem may represent
a subtle balance between opposing processes (Lee et al., 2000). The
assessment of local Hg balances in agricultural regions is challenging, since
during a year, very different and contrasted conditions are observed from the
fallow period to the maximum development of a crop. The foliar uptake of
Hg0 by major staple grain crops has been studied at low–moderate (Niu
et al., 2011) and high exposure treatments of Hg0 vapor (Browne and
Fang, 1978; Du and Fang, 1982). The early work conducted on cereals at the
tillering stage suggested that assimilation of Hg0 increased with
Hg0 concentration, temperature and irradiation, and is controlled by
interior (mesophyll) resistances at optimal growing conditions. The study of
Niu et al. (2011) focusing on wheat and corn indicated a significant
correlation between foliage Hg content and the exposure level of airborne
Hg0 for their principal growing stages. In a further study, Niu et
al. (2014) showed that only a moderate level of Hg0 pollution in air
(∼ 20 ng m-3) was required to induce measurable physiological
stress on corn tissue.
China is the largest emitter of atmospheric Hg worldwide due to a rapid
expansion in fossil fuel combustion (one quarter of global coal combustion)
and increased industrialization, in contrast to significant reduction in
anthropogenic emissions in Europe and North America (Streets et al., 2005).
In addition, China is the world's leading producer and consumer of Hg (USGS,
2015). Using a broad set of [Hg0] / [CO]-ratio observations, Fu et
al. (2015) recently estimated the annual anthropogenic Hg0 emission in
mainland China to be approximately 1140 ton, which is significantly higher
than previously predicted by published emission inventories using activity
data (S. Wang et al., 2014). This inconsistency also inferred by Song et al. (2015) may
propagate into biased-low source strength estimates or missing source
categories in inventories. Since the elevated Hg deposition deriving from
anthropogenic sources tends to concentrate in labile pools, the potential for
high re-emission of Hg0 from impacted terrestrial ecosystems in China is
substantial (Fu et al., 2012; Smith-Downey et al., 2010). Investigations by
the dynamic flux chamber (DFC) technique have revealed comparatively high
Hg0 efflux from agricultural soils compared to soils in other types of
land use in China (Fu et al., 2008, 2012; Wang et al., 2006; Zhu et al.,
2011; Zhu et al., 2015a). Therefore, it may be hypothesized for related
croplands that Hg0 emissions from the soil surface, though plausibly (in
part) recaptured by uptake of the overlying canopy, at times have a major
contribution to the net Hg0 exchange, especially in scant or senescent
canopies. Micrometeorological measurements yielding the net flux from the
canopy surface, including both soil and plant exchanges, are thus required to
address the importance of cropland and other agro-ecosystems as sources/sinks
of Hg0. In an effort to investigate Hg0 uptake or emission from
crop vegetation and soil, we have conducted broad seasonal measurements of
field-scale Hg0 flux at three sites in distinctively different
agricultural regions of China with varying levels of Hg content in
agricultural soil. All the selected sites were located in a rural environment
without discernible adjacent anthropogenic Hg point sources. The
well-characterized and typical rotation croplands investigated include either
paddy or dry land cultivation only or a combination thereof over a year. We
focus on the four cash crops (rice, wheat, corn, and oilseed rape) accounting
for the bulk of the planting area in mainland China. In order to determine
the origin of fluxes, we combined large-scale above-canopy MM-method flux
techniques with small-scale automated DFC measurement at the canopy floor in
the field experiments. In this paper, we report on Hg0 flux measurements
in and above a farm field growing winter wheat and summer corn in rotation
during five campaigns (overall 87 sampling days) over the period May 2012 to
April 2013. The site is located on the central North China Plain (NCP,
between 32–40∘ N and 114–121∘ E), which is considered to
be China's granary (covering about 180 000 km2 of farmlands) with
about half and a third of the national wheat and corn production,
respectively (NBSC, 1998). Besides being a major agricultural base, the NCP
region is heavily populated and industrialized and suffers from serious
particulate and photochemical air pollution (L. T. Wang et al., 2014; Wen et
al., 2015). Forthcoming communications will deal with characteristics of
Hg0 fluxes measured over subtropical croplands growing either oilseed
rape or rice in rotation or rice as a single crop. Jointly, in these papers,
we present growing and non-growing season Hg0 flux patterns and diurnal
features. In addition, we address the role of crop vegetation as a
source/sink of Hg0 based on an analysis of the measured difference
between above-canopy and ground Hg0 fluxes. We also attempt to address
the impact of field management activities (e.g., harvest, tillering and
irrigation) and abrupt changes in environmental conditions (e.g., intensive
precipitation) on Hg0 gas exchange.
Seasonal variation in LAI (m2 m-2, yellow filled circles)
and canopy height (green filled diamonds) for 2012–2013 (in part). The
duration of the five flux sampling periods (with numbers given in consecutive
order) is indicated by magenta shaded boxes. The grey box resembles the time
duration of a field inter-comparison (IC) of chamber and micrometeorological
flux measurement techniques to quantify Hg0 flux (Zhu et al., 2015a).
Materials and methods
Site description
The Yucheng Comprehensive Experimental Station (YCES, 36∘57′ N,
116∘36′ E, managed by the Chinese Academy of Sciences)
experimental site is located on an alluvial plain in the lower reaches of the
Yellow River, Shandong province, China. There is a typical crop rotation of
winter wheat and summer corn in the region without fallow between the crops.
The annual mean air temperature and precipitation depth were
12.9 ± 0.8 ∘C and 528 ± 197 mm, respectively, for
2003–2012 (Bao et al., 2014). Due to the East Asia monsoon, the
precipitation pattern is largely asymmetric, with 60–70 % of the total
concentrated in July–August. The wheat-growing season (mean length:
237 ± 8 days) is characterized as dry, windy and with less
precipitation (108 ± 238 mm), whereas the corn-growing season (mean
length: 107 ± 7 days) is generally categorized as semi-humid and warm
temperate. The upper texture of farmland soil is a silty loam with a
volumetric soil water content at a field capacity of 0.44 m3 m-3
(Li et al., 2010). In the tillage layer, the soil organic content is
1.21 % and the pH value is about 7.9 (Tong et al., 2014). Especially for
winter wheat, precipitation does not meet crop water demand, so the cropland
is flood irrigated using groundwater during the pre-frost, jointing, and
shooting stages of wheat and prior to planting corn (typically
∼ 100 mm per turn). For the period of this field study (May 2012 to
April 2013, Fig. 1), the harvest and sowing dates of wheat were on 24 June
and 11 October, respectively. In turn, corn was planted on 28 June with a
density at 65 000 plants ha-1 and harvested on 5 October. Row spacing
was ∼ 25 cm and the direction was north–south. The total Hg (THg)
content in surface soils was uniform across the measurement fetch (mean:
45 ± 3 ng g-1, n= 29; Sommar et al., 2013b).
Micrometeorological flux measurements and calculations
The site was in the center of a flat ∼ 15 ha grain field and a minimum
fetch length of at least 130 m in all directions (Sommar et al., 2013b).
From a 6.5 m high flux tower erected permanently over a year-long period, MM
flux measurements were conducted. Sensible heat (HEC), latent
heat (λEEC) and CO2 fluxes
(FCO2EC) were measured by the eddy covariance (EC)
method using the instrumentation and protocol described in Sommar et
al. (2013b) and Zhu et al. (2015a, b). In order to diminish frequency
response errors, the EC sensor height was adjusted over time (2.1–4.2 m) to
keep a relative height between sensors and the canopy of at least
∼ 1.5 m during a campaign (Burba, 2013). The frequency response of the
sensor placement over the canopy was investigated by spectral analysis of
selected 10 Hz turbulence time series. Analogous to that reported in Sommar
et al. (2013b), there was over time little contribution from small eddies
occurring above 5 Hz, and instrumentation produced in general co-spectra
similar to the references (Kaimal et al., 1972).
Up to now, fast high-precision detectors for direct background Hg0 flux
measurements by the preferred EC method have not been available. A principal
alternative flux measurement approach is the relaxed eddy accumulation (REA)
technique (Businger and Oncley, 1990). As in EC, REA measurements are
performed at a single point above the surface, but the detector required in
EC is substituted by fast-response sampling valves. The inlet of an
Hg0–REA system was installed at the same height as the EC sensors, with
a horizontal displacement distance to the EC sensors of 20 cm. The design
and operation of the whole-air Hg0–REA system used in this study has
been described in detail by Sommar et al. (2013b). The REA system was
specifically adapted to an automatic Hg0 vapor analyzer (model 2537B,
Tekran Instruments Inc.) to measure fluxes and concentrations of Hg0. In
this system, upward and downward moving air created from eddies in the air
column are sampled and separated into reservoirs by the sampling valves.
Updraft and downdraft sampling conditions are dictated by
w>w¯+0.3σ¯w and w<w¯-0.3σ¯w, respectively, where w¯ is the 5 min running average of w and
σ¯w is the standard deviation of w over the same
interval. Hg0 flux (FREA) is determined over 20 min
sampling intervals following
FREA=βTs⋅σw⋅C↑‾-C↓‾︸ΔCREA,
where σw (m s-1) is the standard deviation of w, and
C↑‾ and C↓‾ are the
average mass concentrations of Hg0 (at standard temperature and
pressure) from updraft and downdraft samples corrected for dilution by zero
air injection, respectively (ng m-3). In turn, the empirical
dimensionless parameter βTs was calculated online for
each averaging period (20 min) according to
βTs=w′Ts′‾/σw⋅Ts↑‾-Ts↓‾,
where Ts is temperature measured by the sonic anemometer of the
EC system (K), w′Ts′‾ is the kinematic buoyancy flux
derived from EC (K m s-1) and Ts↑‾-Ts↓‾ (ΔTs,REA) is
the average Ts difference in between updraft and downdraft
samples (K). If the online calculated βTs deviated
outside a ±0.2 interval of the median, the overall median value (0.46)
was implemented in Eq. ().
Bulk canopy conductance for water vapor, gc (m s-1), was
estimated using a rearranged form of the Penman–Monteith equation (Dengel
and Grace, 2010):
gc=Δγ⋅HECλEEC-1⋅1/ga+ρa⋅cpγ⋅DaλEEC-1,
where Δ is the rate of the increase in saturation vapor pressure with
air temperature (kPa K-1), γ the psychrometric constant
(kPa K-1), ga is the aerodynamic conductance (m s-1),
ρa the density of dry air (mol m-3), cp the
specific heat of air (J mol-1 K-1), and Da the water vapor
saturation deficit (kPa). Aerodynamic conductance was estimated following
Thom (1975):
ga=κ2⋅u/lnz-d/z02,
where κ is the von Kármán constant (0.41) and u is the wind
speed measured at height z (m s-1). z0 is the surface roughness
(0.15⋅hc, where hc is the mean canopy height)
and d the zero plane displacement (0.67⋅hc). In
dry, daytime conditions most of the water vapor flux EEC would
derive from stomata, with only minor contributions from soil and leaf surface
evaporation. Consequently, we only choose daytime conditions (global
radiation > 100 W m-2) without the presence of a wet
canopy to calculate gc as a proxy for canopy stomatal
conductance. Most of the data were collected under favorable weather
conditions without rainfall and with sufficient global radiation. However, as
only a limited set of gc data was obtained from the winter
campaign due to wetness constraints and instrumentation malfunction, these
data were not included in any further evaluation (cf. Table 1).
Summary of turbulent Hg0 fluxes measured by the REA technique,
micrometeorological parameters measured by EC and auxiliary meteorological
and environmental observations (presented as 20 min averages) during the
five campaigns.
Variable
Unit
1 (2–18 May 2012)
2 (12–29 Jun 2012)
3 (29 Aug–17 Sep 2012)
4 (12–24 Jan 2013)
5 (1–24 April 2013)
Wheat, ∼ 65–70 cm, LAI ∼ 2.4–1.0
Wheat, ∼ 70 cm, LAI < 1.0
Corn, ∼ 255 cm, LAI ∼ 3.6–2.7
Wheat, ∼ 10 cm, LAI ∼ 0.4
Wheat, ∼ 30–35 cm, LAI ∼ 1.8–3.6
Range
Mean
Range
Mean
Range
Mean
Range
Mean
Range
Mean
(median)
(median)
(median)
(median)
(median)
Air temperature
∘C
9.7–30.1
20.4 (20.0)
13.4–38.1
26.9 (26.4)
8.5–33.7
21.1 (21.3)
-13.1–6.6
-2.2 (-2.3)
0.0–22.8
9.8 (9.8)
Soil temperature
∘C
14.7–26.3
19.9 (19.4)
18.9–32.9
26.6 (26.7)
17.5–26.7
22.0 (21.8)
-6.6–0.0
-1.5 (-0.8)
1.5–22.3
10.9 (10.4)
Air humidity
%
1.7–99.7
84.3 (90.7)
18.1–99.3
59.1 (59.9)
33.7–99.8
85.2 (92.4)
52.7–99.8
90.7 (95.1)
34.3–100
73.0 (74.5)
Global radiation
W m-2
0.6–1065.6
249.7 (54.4)
0.6–956.9
206.8 (45.6)
0.6–1010.6
176.2 (11.9)
0.6–428.1
57.1 (0.6)
0.6–890.6
158.4 (7.5)
Leaf wetness
%
3.5–100.0
42.8 (19.4)
2.4–100.0
19.9 (5.3)
5.9–100.0
59.4 (91.9)
5.9–100.0
89.5 (100.0)
2.4–100
37.0 (8.2)
Precipitation
mm
–
0.2
–
1.2
–
13.6
–
4.0
–
8.0
PAR photon flux
µE
1.2–1956.2
449.6 (91.6)
1.2–1826.2
414.0 (106.2)
1.2 -2021.2
350.3 (26.2)
1.2–778.7
104.5 (1.2)
1.2–1621
298 (13.7)
Soil water content
(% vol)
10.4–21.6
14.6 (14.0)
5.5–36.6
11.1 (8.1)
28.0 -30.5
29.0 (28.9)
4.6–14.6
6.4 (6.1)
5.3–8.8b
6.3 (6.1)b
Wind speed
m s-1
0.01 -4.08
1.32 (1.22)
0.01–7.24
2.00 (1.74)
0–6.08
1.00 (0.86)
0.01 -7.61
2.02 (1.67)
0.00–8.91
2.74 (2.60)
Friction velocity
m s-1
0.01–0.54
0.16 (0.15)
0.01–0.71
0.18 (0.17)
0–0.61
0.13 (0.10)
0.01–0.75
0.15 (0.12)
0.00–1.59
0.23 (0.19)
σw
m s-1
0.01–0.67
0.19 (0.19)
0.01–0.79
0.23 (0.23)
0.01–0.63
0.14 (0.12)
0.02–0.62
0.21 (0.19)
0.01–0.88
0.29 (0.27)
Bulk canopy
cm s-1
0–9.7
2.1(1.8)
0–2.3
0.5 (0.4)
0–8.9
2.1 (1.9)
–
–
0–9.3
1.9 (1.6)
conductancea
CO2 flux
µmol m-2s-1
-43.4–13.0
-7.7 (-1.7)
-12.5–9.4
-0.7 (0.7)
-45.3–10.9
-6.2 (-1.1)
-5.7–2.8
-0.4 (-0.1)
-40.3–11.1
-5.3 (0.1)
Latent heat flux
W m-2
-211.6–551.4
119.5 (36.1)
-41.4–381.3
31.0 (17.2)
-225.8–385.7
62.3 (18.5)
-179.6–268.2
6.1 (4.3)
-180.7–363.5
66.2 (36.1)
Sensible heat flux
W m-2
-139.8–144.1
-4.4 (-3.8)
-93.1–343.6
59.3 (2.7)
-111.8–216.7
13.3 (-0.4)
-116.1–178.3
1.7 (-0.2)
-243.9–167.6
11.6 (-2.9)
Ambient air Hg0 conc.
ng m-3
2.22–12.57
5.19 (4.94)
1.77–10.09
3.90 (3.59)
1.87–10.57
3.42 (3.31)
2.71–13.02
6.22 (6.24)
1.21–7.28
3.72 (3.39)
Above-canopy Hg0 flux
ng m-2h-1
-888.7–927.8
26.7 (13.4)
-491.8–467.6
16.5 (10.8)
-794.5–420.1
-11.8 (-6.1)
-1051.5–508.9
-11.6 (-6.7)
-926.6–483.5
17.3 (12.2)
Hg0deposition velocity
cm s-1
-2.06–1.82
-0.12 (-0.10)
-1.86–1.34
-0.04 (-0.02)
-1.19–1.50
0.10 (0.07)
-2.95–1.99
0.01 (0.04)
-2.03–1.88
-0.19 (-0.12)
Hg0 flux data coverage
%
–
74.0
–
82.2
–
86.1
–
83.0
–
51.3
Data with developed
%
–
68.9
–
75.2
–
67.7
–
70.9
–
68.0
turbulencec
Hg0flux data < MDL
%
–
54
–
61
–
57
–
59
–
64
Hg0 flux uncertainty
%
–
(32)
–
(28)
–
(36)
–
(35)
–
(29)
a Data for daytime when global radiation > 100
W m-2.b Data cover only the initial part of the campaign.c Flux data associated with turbulence quality classes 0 and 1.
Ancillary measurements
The REA-EC instrumentation was accompanied by an automatic weather station
(HOBO U30-NRC, Onset Computer Corp., USA) equipped with sensors for bulk air
(temperature and humidity) and surface soil (temperature and volumetric
moisture content) parameters and leaf wetness as well as sensors for global
radiation (300–1100 nm) and photosynthetically active radiation (PAR,
400–700 nm), respectively. The weather station stored data as 20 min
averages with the same time interval as the flux measurements. Crop leaf area
index (LAI) was measured using an area meter (LI-3100, LI-COR Biosciences)
weekly during the growing season. hc was recorded at the same
time interval. For the measurement campaigns with developed canopies (1–3;
See Table 1), concurrent measurements of both above-canopy Hg0 net
exchange by the REA system as well as canopy-floor air–soil exchange by a
dynamic flux chamber (DFC, Lin et al., 2012) were conducted with 20 min time
resolution. The setup and operation of the automatic DFC system have been
described elsewhere (Zhu et al., 2015a). Measurement results of air–soil
Hg0 flux are briefly provided here in connection with the discussion of
MM-derived Hg0 fluxes. Corn and wheat foliage samples were collected at
harvest stage and analyzed for THg content. Event-based Hg wet deposition and
precipitation amounts were measured at an adjacent site ∼ 400 m N of
the field site investigated. Methodological details concerning collection and
Hg analysis of foliage and precipitation samples have been described
elsewhere (Zhou et al., 2013).
Post-processing, correction methods and quality assessment of flux data
The 10 Hz EC flux raw data were post-processed and quality-controlled using
the open-source EddyPro 5.0 flux analysis software package (LI-COR
Biosciences Inc.). A series of standard data corrections were implemented as
described in Zhu et al. (2015a). Tests were applied on all 20 min fast time
series raw data to qualitatively assess turbulence for the assumptions
required (steady-state conditions and the fulfillment of similarity
conditions) for applying MM (e.g., the EC and REA methods). Following the
basic system of Mauder and Foken (2004), the resulting flux was marked with a
quality flag (either 0, 1 or 2, denoting high, moderate and low quality,
respectively).
The REA system enabled a mode (reference sampling) during which air is
sampled synchronously with both conditional inlets (with the dynamic deadband
as a threshold). Regularly during the field campaigns (every 72 h), the REA
system was operated in reference sampling mode to correct for minor bias
between the conditional channels in Eq. () following Sommar et
al. (2013b).
In turn, the relative uncertainty in the REA flux (σFREA/FREA) was quantified following Kramm et al. (1999):
σFREA/FREA=±σHEC/HEC2+σΔCREA/ΔCREA2+2⋅σΔTs,REA/ΔTs,REA2.
The procedures we deployed to assess uncertainty in the individual terms are
described in Zhu et al. (2015b). As the sampled air was not dried, derived
FREA was corrected for variations in the water vapor content of the air following
Lee (2000).
Results
Flux data coverage, detection limit and uncertainty level
Five separate flux measurement campaigns were conducted over the period May
2012 to April 2013. The time and duration of the campaigns are listed in
Table 1, which also include the flux data coverage for the individual
sampling periods. The total flux data coverage across the five campaigns was
∼ 73 %. Gaps in the measurements mainly resulted from power
failures, calibration/reference sampling periods and instrumentation
failures. Precipitation events leading to malfunction of the sonic anemometer
contributed ∼ 15 % of the missing data. Extreme imbalances in REA
updraft and downdraft sampling volumes on an undiluted basis could prevail
periodically during very calm wind conditions. This translates into
sub-optimal Hg mass loadings for analysis per sample concerning the channel
associated with small volumes, which potentially yield a biased determination
of ΔCREA (Zhu et al., 2015b). Data from 20 min periods
were not further processed when one of the REA channels was open for sampling
less than 10 % of the total time, which accounted for ∼ 12 % of
the missing data. Based on the quality flag of HEC data, the
percentage of flux data linked with moderate to high quality turbulence
during a campaign is given in Table 1. Overall, ∼ 70 % of flux data
belong to this category.
The precision of the REA system to resolve concentration differences (ΔCREA) under field conditions was derived from periods of reference
sampling and based on the standard deviation of the residuals
(σΔCREA) from orthogonal linear regression fitting
of the conditional sampling channel reference concentrations
Cref↑ vs. Cref↓ (Zhu et al.,
2015b). The ambient air Hg0 concentration (C) dependent relationship
(σΔCREA=0.057+0.016⋅C, ng m-3)
obtained from fitting data from all reference periods
(n= 921) was used to predict the method
detection limit (MDL) for each flux observation. Using this criterion, the
proportion of Hg0 flux data above the MDL was calculated for each
campaign and listed in Table 1. Fifty-seven percent of the Hg0 flux
measurements were above the MDL. For data integration, however, we choose to
use the complete data set since average fluxes may otherwise be
overestimated. The median of relative uncertainty in individual 20 min
Hg0 fluxes (derived by Eq. 5) is given for each campaign in Table 1. The
medians were constant (28–35 %) across the campaigns. On a diurnal
basis, relative uncertainty was generally largest during the hours after
sunrise, when sensible heat fluxes shifted direction and Hg0
concentration tended to fluctuate; cf. Zhu et al. (2015b).
Environmental conditions
Meteorological quantities measured for each campaign during the study period
are summarized in Table 1. Air temperature and precipitation were within the
range of mean values recorded for the site over the past decade (Bao et al.,
2014). However, specifically for the Hg0 flux measurement periods, the
precipitation frequency and total depth were sparse (in total 2.7 cm) and
did not notably influence soil moisture in any event. In 2012, wheat started
to elongate in late March and the peak in single-sided LAI (∼ 2.4)
appeared in early May and then progressively declined as leaves in the
under-layer turned yellow (Fig. 1). The weather during campaign 1 was
generally fair and moist with stable stratification predominant during the
night (z-d/L=ς>0.02, 78 % of the time;
L is the Okuhkov length), while near-neutral (37 % of the time) and
unstable (ς<-0.02, 45 % of the time) conditions were frequent
during daytime. The canopy was wet most nights due to dew condensation, while
soil moisture initially at 0.22 m3 m-3 showed a declining trend
over the period (Fig. 4a). Campaign 2 was characterized by warm (mean air
temperature 27 ∘C) and dry weather. Unstable conditions were
predominant (93 % of the time) during daytime, partially leading to free
convection (ς<-1). The senescent canopy was wet only on occasional
nights and the topsoil layer was consistently dry
(0.06–0.09 m3 m-3). At the end of a campaign, after wheat
harvest, the field was flood irrigated (Fig. 4b). The main growing period for
corn started after mid-July (DOY ∼ 200) and the maximum LAI ∼ 3.7
was attained during the second half of August (Fig. 1). The general
meteorological condition during campaign 3 was moist with periods of cloud
cover and isolated rain showers. Low wind prevailed the vast majority of the
time (mean 1.0 m s-1) and the canopy remained wet for protracted
periods (Fig. 4c). The lower turbulent exchange during those days is
represented by low values of σw (mean:
0.14 ± 0.10 m s-1), which has an impact on the REA flux (Eq. 1).
As shown in Table 1, the mean σw for the period was lower than for
any other campaign. Under the fully grown corn canopy, the topsoil remained
moist over time (∼ 0.28–0.31 m3 m-3). Hazy days with air
temperature below zero were frequent during campaign 4 over frozen ground
with dormant wheat. The site was under the influence of high-pressure systems
and the haze reduced surface solar radiation, thereby leading to a more
stable boundary layer with near-neutral or slightly stable (-0.02<ς<0.20) atmospheric stratification dominating during daytime (81 % of the
time), while air was prevailingly stable during the night (79 % of the
time). Snowfall occurred on 20 January and the ground was snow-covered
towards the end of the period.
In 2013, the peak in the
LAI for wheat was higher in magnitude (∼ 3.75) and occurred already in
late April. The weather conditions during campaign 5 featured
moderate-to-strong wind speeds during daytime and relatively low air humidity
without precipitation events. Mostly near-neutral or slightly unstable
conditions were encountered during daytime (81 % of the time). During two
campaigns, strong prevailing wind directions were present (campaign 2, SW;
campaign 3, SSE); for another two there was a prevailing direction with a
larger component of near-counter-current flow (campaign 4, SSW–N; campaign
5, SSW–NE), while the wind directions were more variable during campaign 3.
Ambient Hg0 concentrations
The NCP is one of the most heavily impacted regions in China in terms of
airborne Hg pollution and total Hg deposition fluxes (L. Wang et al., 2014).
Notwithstanding that YCES is in a rural area, the surrounding NCP region has
a high proportion of heavy and chemical industry clusters involving high
energy consumption provided by the foremost coal-fired power plants,
resulting in substantial Hg emissions into the air (Zhang et al., 2013). Hg
emission sources in rural districts include domestic and field burning of
crop residue (Huang et al., 2011) and illegal artisanal gold mining utilizing
mercury amalgamation (AMAP/UNEP, 2013; Hall et al., 2014).
Throughout the measurement periods, concentrations of Hg0 were
significantly variable (coefficient of variation: 27–33 % for the
individual campaigns). As listed in Table 1, the overall span of Hg0
observations ranged from background values infrequently below 2 ng m-3
to episodical peaks well above 10 ng m-3. The overall average
concentration of Hg0 for the measurement periods was 4.3 ng m-3,
which exceeds the highest seasonal average (3.5 ng m-3, summer)
measured at a rural site in the Beijing region (Zhang et al., 2013) and that
(2.7 ng m-3, winter) measured at the tip of Shandong peninsula (Ci et
al., 2011). Mean values fell
between 3.4 and 5.2 ng m-3 for the growing season individual campaigns
(1–3, 5). Campaign 4 in January 2013 with a mean Hg0 concentration of
6.2 ng m-3 was characterized by prolonged and severe haze pollution
episodes over the NCP region (L. T. Wang et al., 2014). Available data show
for the Jinan municipal area, circa 50 km southeast of the site, that hourly
averaged fine particulate (PM2.5) concentrations ranged between
∼ 100 and 600 µg m-2 over the duration of campaign 4
(J. Wang et al., 2014). The Hg0 (YCES) and PM2.5 concentration
(Jinan) time series have similar trends, implying that Hg0 at least in
part share sources with air PM2.5 pollution. For January 2013, there is
a contemporary atmospheric Hg data set collected in Qingdao (a major coastal
city, ∼ 340 km east) averaging 2.8 ± 0.9 ng m-3 for
Hg0 and 245 ± 174 pg m-3 for particulate-bound Hg (Zhang et
al., 2014), indicating that particulate-bound Hg (PBM) makes up a substantial
fraction of aerial Hg during the widespread winter haze.
Polar histograms of 20 min averaged 5∘ per bin Hg0
concentrations (ng m-3) classified into four magnitude levels (≤ 3, > 3–4, > 4–6 and ≥ 6 ng m-3).
The letter assigned to each pollution rose refers to the campaign number in
consecutive order (a = 1, b = 2, etc.).
Diurnal variation in above-canopy Hg0 flux (left panels) and
Hg0 concentrations during the five campaigns. Box horizontal border
lines represent the 25th and 75th percentiles from bottom to top, the
whiskers include the 10th and 90th percentiles, and the outliers (open
circles) encompass the 5th and 95th percentiles. The solid line in the box
represents the median.
Time series of the selected measurement data for the individual
campaigns at YCES in consecutive order (a–e). Panels from the top
downwards: air and below canopy surface soil temperature (∘C, maroon
and red solid lines, respectively) and global radiation (W m-2, yellow
solid line); event precipitation (mm, black solid line), relative humidity
(%, blue dotted line), canopy wetness (%, grey-blue solid line) and
soil water content (% volume of field capacity, blue dashed line); wind
speed (m s-1, olive solid line) and wind direction (∘, brown
open circles); smoothed Hg0 (ng m-2 h-1, black solid line)
and CO2 flux (µmol m-2 s-1, magenta solid line);
ambient air Hg0 concentration (ng m-3, grey filled circles) and
cumulative Hg0 flux (µg m-2, maroon filled circles).
Dates refer to China Standard Time (major ticks indicate midnight). Hg0
flux data were smoothed by a nine-point moving average, where the shaded grey
area represents its standard deviation. In Fig. 4b the blue arrow associated
with caption “Harvest” indicates the end of the wheat harvest that started
on 23 June.
Spearman's rank-order correlation coefficients between Hg0 flux
(REA method), Hg0 air concentration and other measured parameters.
Significance levels p< 0.01 and p< 0.001 are indicated by
italic and black bold-faced fonts, respectively.
Variable
2–18 May 2012
12–29 Jun 2012
29 Aug–17 Sep 2012
12–24 Jan 2013
1–24 Apr 2013
Ambient
Hg0
Ambient
Hg0
Ambient
Hg0
Ambient
Hg0
Ambient
Hg0
air Hg0
flux
air Hg0
flux
air Hg0
flux
air Hg0
flux
air Hg0
flux
Air temperature
0.15
-0.10
-0.44
0.04
0.30
-0.14
0.29
0.05
0.39
0.06
Soil temperature
-0.01
-0.13
-0.42
0.01
0.14
-0.22
0.17
0.03
0.21
0.11
Air humidity
0.12
0.19
0.19
-0.05
-0.01
0.17
-0.01
-0.10
-0.00
-0.21
Global radiation
0.20
-0.20
-0.18
0.07
0.28
-0.29
0.38
-0.16
0.04
0.19
Leaf wetness
0.07
0.14
0.28
0.01
-0.10
0.18
-0.14
0.05
0.18
-0.23
PAR photon flux
0.21
-0.19
-0.19
0.07
0.25
-0.27
0.38
-0.17
0.04
0.19
Soil water content
0.24
-0.19
-0.01
-0.07
-0.08
0.03
0.21
0.01
–
–
Wind speed
0.28
0.14
-0.23
0.35
0.17
-0.26
0.09
0.25
-0.26
0.37
Friction velocity
0.37
0.08
-0.21
0.29
0.22
-0.28
0.08
0.26
-0.37
0.13
Bulk canopy
0.28a
0.08a
-0.12a
0.23a
0.19 a
-0.14a
–
–
-0.23a
-0.33a
conductance
CO2 flux
-0.25
0.25
-0.02
0.01
-0.19
0.23
-0.23
0.17
-0.09
-0.12
Latent heat flux
0.21
-0.14
-0.28
0.00
0.21
-0.25
0.15
0.07
-0.14
0.07
Sensible heat flux
0.09
-0.24
-0.08
-0.10
0.28
-0.12
0.42
-0.29
0.19
0.05
Ambient air Hg0
–
-0.30
–
-0.03
–
-0.26
–
-0.35
–
-0.07
Hg0 flux
-0.30
–
-0.03
–
-0.26
–
-0.35
–
-0.07
–
a Data for daytime when global radiation > 100
W m-2.
All Hg0 concentration data sets showed positive skewness and kurtosis,
indicating a predominant influence of emission sources. In the panels of
Fig. 2, the directionality of Hg0 concentrations during the five
campaigns was investigated by plotting pollution roses. In general, Hg0
showed no manifest dependence on ground wind direction over the sampling
periods. However, during April 2013 (Fig. 2e), the significantly lower
Hg0 concentration associated with northeasterly wind directions was
tentatively identified as air masses arriving from northeastern China/Russian
far east via a slower passage over the Bohai Sea (Fig. S1 in the
Supplement. Diurnal Hg0 concentration
features for each of the campaigns are shown in Fig. 3. Distinct profiles,
which peaked during morning/daytime and reached a minimum at dusk/nighttime,
were representative for most campaigns. During these periods, Hg0
displayed a significant negative correlation with atmospheric stability
(Spearman's rank correlation, p < 0.01). This daily variation
pattern may reflect a limited importance of local ground-based Hg0
sources as no considerable level of Hg0 concentrations was observed to
build up within the shallow nocturnal boundary layer. First with the
development of the mixed layer, concentrations increased conceivably due to
mixing-in of more Hg0-rich air from aloft. This is indicative of the
intensity of regional Hg emission sources. In contrast, during the June
campaign, episodes of elevated Hg0 values occurred during series of
nights associated with slightly stable conditions and low wind speeds
(< 3 m s-1), but without a discernible dependence of wind
direction (Fig. 4b). All of this suggests that the peaks derive from
nocturnal in-field burning of crop residue occurring in the surrounding
countryside during the harvest season (Huang et al., 2011).
Cropland–atmosphere exchange of Hg0 and CO2
In order to research the Hg0 exchange between a cropland and the
atmosphere, it is necessary to understand the seasonal variation in key
environmental factors. For example, measured CO2 net exchange provided
valuable information about crop productivity and farmland ecosystem
respiration over time. In Table 1, a statistical summary of Hg0 and
CO2 net fluxes is given for the five sampling periods. Since both the
distribution of Hg0 fluxes and air concentrations deviated for several
of the campaigns significantly from normality (Shapiro–Wilk test,
p < 0.001), the median is supplied in Table 1 as an estimator of
central tendency. Moreover, the statistical dependence between variables was
assessed by non-parametric tests (Spearman's rank correlation, Table 2). Due
to a large spread in Hg0 flux data, numerical smoothing was in this
study performed on all data sets using a nine-point moving average (which
corresponds to an interval of 3 h) to reduce the variability and therefore
allow for a better visual interpretation of diurnal variations (Cobos et al.,
2002; Fritsche et al., 2008c). The associated time series of smoothed
Hg0 and CO2 fluxes are displayed in the composite Fig. 4. However,
since the smoothing procedure introduces data manipulation, smoothed data are
not used in any statistical treatments (such as correlation analysis,
Table 2) or in the calculation of cumulative fluxes (shown in Figs. 4 and 8).
Average and ranges of fluxes for the different measurement
periods
Previous studies of the wheat–corn rotation farmland at YCES evinced it to
be a significant sink of atmospheric CO2 during the main growing seasons
of winter wheat and corn (e.g., Li et al., 2006; Tong et al., 2014), which
for our study overlap with campaigns 1 (May) and 3 (August–September) and
the end part of campaign 5 (late April). Using the EC technique, mean
CO2 uptakes of 7.7, 6.2 and 6.7 µmol m-2 s-1 were
determined for each of these sampling periods (cf. Fig. 4a, c and e). For the
senescent wheat (campaign 2), CO2 uptake declined rapidly and in turn
ecosystem CO2 respiration progressively gained more importance
during daytime (with increased maximum temperatures), resulting in a mean
CO2 net exchange slightly below zero
(-0.7 µmol m-2 s-1). The average Hg0
above-canopy net flux was positive for the main growing season of winter
wheat until harvest (April: 17.3; May: 26.7; and June:
16.5 ng m-2 h-1), while slightly dry deposition of Hg0
predominated over the field, with a fully developed corn canopy
(August–September, mean flux -11.8 ng m-2 h-1). DFC
measurements underneath the developed canopies show significant Hg0 soil
emissions during daytime (Fig. 5). In more detail, mean air–soil Hg0
fluxes were more strongly evasive under the wheat canopy (May: 39.9; June:
31.5 ng m-2 h-1) than under the denser corn canopy
(August–September: 10.8 ng m-2 h-1). Sampling periods conducted
over wheat in early growing stages were characterized by near-zero mean
CO2 net flux (November: 0.5; January: -0.4; and early April:
-0.7 µmol m-2 s-1). As reported in Zhu et
al. (2015a), collocated MM and chamber flux measurement systems gauged
unanimously positive net Hg0 flux (mean range:
2.2–7.6 ng m-2 h-1) over the field during November. Hg0
fluxes during early April were also predominantly positive (mean:
19.5 ng m-2 h-1), while the cumulative Hg0 flux was
negative (mean: -11.6 ng m-2 h-1) for the winter period
(campaign 4) involving prolonged and severe haze air pollution episodes.
Diurnal variation in air–soil Hg0 flux measured by a DFC
underneath the developed canopies (upper: campaign 1; middle: 2; lower: 3):
Note the divergent axis scale for the plot in the middle panel. Box
horizontal border lines represent the 25th and 75th percentiles from bottom
to top, the whiskers include the 10th and 90th percentiles, and the outliers
(open circles) encompass the 5th and 95th percentiles. The solid line in the
box represents the median.
Local polynomial-smoothed diurnal curves of above-canopy (blue line)
and ground (maroon line) Hg0 flux during campaigns 1 (upper panel) and 3
(lower panel). Lines and envelopes depict mean and 90 % confidence
intervals. Note the divergent y axis scales for the plots.
Irrespective of sampling period, extreme values in net Hg0 exchange
(Table 1) were observed primarily during and after episodes when air with
highly elevated Hg0 concentration advected over the fetch. Although
highly dynamic, vertical fluxes of Hg0 were on average substantially
negative during such an event (cf. Fig. 4). On several occasions, the REA
system gauged significant emission fluxes during the immediate period
following a major Hg0 dry deposition event. This temporal development
also seen in other studies (Bash and Miller, 2007; Cobbett and Van Heyst,
2007) demonstrates the potential of deposited Hg0 to be promptly
recycled to the atmosphere.
During most of the sampling campaigns, above-canopy Hg0 flux followed a
discernible diurnal pattern, with the absolute magnitude of the flux being
largest during daytime periods and generally small at night (Fig. 3).
However, the cycle of prevailing developed and weak atmospheric turbulence
during day and night, respectively, was periodically disrupted by windy
conditions extending into dark hours, facilitating turbulent exchange (mostly
encountered in winter and spring campaigns; Fig. 3g and i).
Hg0 flux patterns during the main growing season
Although the REA measurements during the spring and summer campaigns indicate
the wheat cropland to be a continual net source of atmospheric Hg0, the
correlation (ρ, Spearman's rank-order correlation coefficient) between
Hg0 flux and other measured parameters varied significantly between the
individual campaigns (Table 2). In contrast to a well-defined diurnal pattern
in soil Hg0 efflux observed over the campaigns (Fig. 5), the average
profiles in above-canopy Hg0 flux were non-uniform at the diurnal
timescale. As shown in Fig. 3, Hg0 net fluxes above wheat canopies
before canopy closure (April) and during senescence (June) were positive
during daytime and from sunrise to noon, respectively, while at the anthesis
stage (May) composite flux data aligned to the early afternoon minimum with
mean deposition. The close agreement between the chamber and
micrometeorological estimates during field inter-comparison (Zhu et al.,
2015a) prompted us in the present study to interpret Hg0 in-canopy
fluxes from the difference between REA and DFC observations despite the fact
that the methods cover different spatial scales. For two of the campaigns (1
and 3) during the final vegetative stage of corn and wheat, ground and
above-canopy Hg0 fluxes displayed inversed daytime courses with near
mid-day maximum and minimum, respectively (Fig. 6). These data supported the
hypothesis that the active growing and developed cereal canopies acted as
a daytime sink of Hg0 and at least in part were able to offset the
concurrent emission from ground surfaces. During these periods, above-canopy
Hg0 flux was negatively correlated with air Hg0 concentration and
positively correlated with CO2 flux (Table 2). To examine temporal
variability of fluxes in more detail, specific observations for campaigns 1
and 3 are presented in succession below.
During daytime for a series of days with significant CO2 uptake (4–9
May), Hg0 dry deposition was predominant (Fig. 4a). From the middle of
the campaign and onwards, periods of above-canopy Hg0 emission become
more frequent than deposition during daytime. Such a trend in above-canopy
Hg0 flux is not reflected in ground Hg0 flux and may therefore be
related to in-canopy Hg0 source/sink characteristics. During the May
period, the mean Hg0 net fluxes were negative for the hours coincident
with the diurnal maximum in Hg0 concentration (Fig. 3a, b). Given the
indication for Hg0 uptake by the canopy when ambient concentrations were
elevated, lower Hg0 concentrations during the second phase of the period
together with an expected decline in Hg0 uptake with growth progression
(Du and Fang, 1983) may explain the result. The principal diel period of
Hg0 deposition did not concur with the peak canopy conductance during
morning hours, suggesting that foliar uptake of Hg0 is not limited by
periods of ample stomatal conductance. Instead, maximum mean Hg0
deposition during campaign 1 appeared in the early afternoon, which is in
concert with that of O3 observed in a contemporary study of wheat at
YCES (Zhu et al., 2015). Daytime deposition of Hg0 was also gauged over
fully leafed graminaceous plant canopies by Lee et al. (2000) and Fritsche et
al. (2008c) and attributed to plant biological activities such as
photosynthesis. Since net Hg0 fluxes were bi-directional with
atmospheric Hg0 concentrations appearing to play a significant role in
controlling flux, the response may be interpreted with the concept of an
Hg0 canopy compensation point (Bash and Miller, 2009; Ericksen and
Gustin, 2004; Hanson et al., 1995; Poissant et al., 2008). The apparent
compensation point calculated from linear regression (r= -0.32,
p < 0.001) was at ∼ 5.3 ng m-3 for May. However, it
is clear that the parameter is a composite term that is influenced by
component sources/sinks within the canopy as well as at the ground (Wright
and Zhang, 2015). In particular, air–soil Hg0 flux observations were
overall not linked to compensation point behavior (r= 0.07, p= 0.22),
but were largely governed by the effect of global radiation and soil
temperature (explaining 68.3 % of the variance in the total data;
stepwise multivariate regression).
Without much day-to-day variation, Hg0 dry deposition occurred during
daytime over the whole of campaign 3 (Fig. 4c). At the diurnal timescale,
Hg0 flux shows a shallow minimum
(∼ -40 ng m-2 h-1) over corn just before noontime,
coinciding with the peak in atmospheric Hg0 concentration (Fig. 3e, f).
Under the dense corn canopy structure the magnitude of daytime Hg0
efflux from soil was on average a factor of ∼ 3 lower compared to that
within the wheat canopy (Fig. 5) and may be attributed to a combination of
lower light transmission to the ground and profoundly dampened diurnal
courses in surface soil temperature (cf. Fig. 4). In addition, the entirely
moist surface soil may restrain Hg0 evasion by reducing its mobility
through the soil profile (Schlüter, 2000). The divergence in the dynamic
scale of the diurnal Hg0 fluxes observed at each vertical level (Fig. 6)
indicates that corn with a higher above-ground biomass is a weaker Hg0
sink (per leaf area) than wheat, as has previously been inferred from
controlled experiments (Browne and Fang, 1983; Niu et al., 2011). Hg0
uptake in cereals is plausibly associated with the enzymatic conversion of
Hg0 to HgII species within the
foliar cavity (Du and Fang, 1983). Transient Hg0 foliar uptake during
campaigns 1 and 3 (encompassing similar meteorological conditions, Table 1)
as calculated from the integrated imbalances between ground and above-canopy
fluxes during daytime was at 0.17 ± 0.08 and
0.46 ± 0.32 µg m-2 leaf area day-1, respectively.
The apparent canopy compensation point of ∼ 3.6 ng m-3 is lower
than that derived for the wheat during campaign 1. The discrepancy may in
part be explained by the greater positive responses in Hg0 uptake to
both light and temperature for wheat (C3 plant) compared to corn
(C4 plant) reported by Du and Fang (1982). Essentially, above-canopy
Hg0 dry deposition during campaign 1 was confined to the mid-day, which
was characterized by elevated Hg0 in addition to high temperatures and
irradiance. Individually all these parameters have been reported to
significantly promote Hg0 uptake by wheat (Du and Fang, 1982) and in
close association their combined effect appear required to offset the
substantial ground emission of Hg0.
The dynamics of Hg0 flux over wheat during the April and June campaigns
with net Hg0 emission prevailing during daytime and small nocturnal
median fluxes suggests a limited capacity of the canopy to recapture Hg0
efflux from the ground. Being a C3 plant, the foliar Hg0 uptake is
susceptible to light and temperature conditions (Du and Fang, 1982). Under
sub-optimal conditions with a low leaf temperature present in April (mean air
temperature 9.8 ∘C), resistances are accordingly increased and rates
of Hg0 net uptake by wheat foliage are presumably lower. Over the
senescent canopy, Hg0 flux showed frequently a profound short-term
temporal variability overlaid on a trend towards higher emission rates
(Fig. 4b). The changing physiological properties of wheat occurring after the
onset of senescence (Grossman-Clarke et al., 1999) together with crop water
stress might account for the disparity between early phase May and
June daytime Hg0 canopy-scale fluxes. A prominent feature of the average
diurnal pattern of the latter fluxes is the more largely Hg0 net
emission during the early morning (Fig. 3c). The temporary low Hg0
ground evasion (mean: 9.9 ± 25.0 ng m-2 h-1) indicates
that the episodical Hg0 emissions stem from above the ground (cf.
Fig. 5b). Owing to the dry conditions, we may exclude the possibility of
Hg0 deriving from evaporation of dew-wetted foliar surfaces. It is more
likely that the morning peak in Hg0 flux results from canopy release of
Hg0 (following the timing of maximum values of gc, and there
is an overall positive correlation between flux and gc,
ρ=0.23, p < 0.001) and venting of the canopy by increasing
wind speeds. For wheat, there is observational evidence for transpiration
flow transport of HgII species (Khozhina et al., 2001), which may
become chemically reduced when reaching mesophyll through electron transfer
schemes from the anti-oxidative defense system via ascorbate and potentially
emitted as Hg0 (Battke et al., 2005). In association with rapid decline
in canopy transpiration (Table 1) and enzymatic-mediated Hg0 oxidation
in mature wheat (Du and Fang, 1983), our result suggests a capacitance of
Hg0 storage within the substomatal cavity that is released when the
stomata are open. The fact that the morning peak in Hg0 emission occurs,
albeit with an elevated Hg0 concentration in the air, gives more
credibility to this hypothesis.
Hg0 flux patterns during the non-growing
season
For the periods with a near-zero CO2 net flux indicative of
non-significant plant growth, there is a marked difference between overall
Hg0 net emission occurring during late fall and early spring and net
deposition during mid-winter (Tukey–Kramer test, p < 0.01). The
experimental field with emerging wheat was relatively dry during these
sampling periods (soil moisture content at 5 cm depth of
0.06–0.17 m3 m-3). Without a significant canopy cover, the
farmland–atmosphere Hg0 net exchange gauged during these periods would
essentially derive from soil fluxes. In correspondence to air–soil Hg0
fluxes measured within the developed canopies during warmer seasons (Fig. 5),
field-scale Hg0 fluxes were during November associated with an average
diurnal profile featuring maximum emission near mid-day
(∼ 40 ng m-2 h-1; Fig. 9 in Zhu et al., 2015a). The higher
mean Hg0 fluxes observed during early April compared to November
(Sect. 3.4.1) may in part be linked to warming soil temperatures during the
former period (mean: 10.9 vs. 5.3 ∘C) given the similar level of
surface soil moisture. Numerous studies have shown that surface soil
temperature has a strong influence on relatively dry soil Hg0 efflux due
to its role in enhancing volatilization (Carpi and Lindberg, 1997; Gustin et
al., 1997; Poissant et al., 2004; Xiao et al., 1991). In the current study,
Hg0 dry deposition occurred more frequently than emission at daytime
(Fig. 3g) during the winter period with sub-zero ground temperatures
(Fig. 4d). In contrast to the late fall and early spring period, Hg0
fluxes were in winter significantly negatively correlated with Hg0
concentration (ρ=-0.35, p < 0.001). A better part of the
cumulative Hg0 flux occurred in a few distinct periods (13–15 and
22–24 January, Fig. 4d), whereas for the remainder
there was small day-to-day variation. These periods were characterized by
more extreme values in Hg0 and PM2.5 air pollution (Sect. 3.3). In
addition, snowfall samples collected had elevated Hg concentrations
(Sect. 3.5), suggesting enrichment by scavenging of Hg bound to aerosols. It
should be noted that Hg0 fluxes reported here for winter could represent
extremes rather than average seasonal conditions. As can be seen in Fig. 4d,
events of substantial Hg0 dry deposition were in general followed by a
period of net emission, suggesting frozen surfaces to be a transient sink for
atmospheric Hg0. Cobbett and Van Heyst (2007) also found that elevated
concentrations of Hg0 (> 10 ng m-3) resulted in
highly dynamic net Hg0 fluxes over agricultural soil below 0 ∘C
with dry deposition shifting to emission, whereas net exchange was
concomitantly low under ambient conditions.
Time series of latent heat flux (W m-2, red filled squares),
Hg0 flux (grey filled diamonds), wind direction (∘, yellow
filled circles), soil water content (% of field capacity, dashed dark blue
line) and leaf wetness (%, light blue solid line) measured during and
after field irrigation (26 June).
Flux responses to abrupt changes in environmental conditions
Hg0 flux data were examined for a discernible response to abrupt changes
in environmental conditions due to agricultural management operations (e.g.,
tilling and irrigation) and precipitation as such events have previously been
linked to increases in Hg0 emissions from soils (Bash and Miller, 2007;
Baya and Van Heyst, 2010; Gillis and Miller, 2000; Lindberg et al., 1999). In
June 2012, while the topsoil was substantially dry
(∼ 0.06 m3 m-3), wheat harvest (the fields making up our
primary fetch) started on 23 June and was completed the next day. The
harvesting had no discernible boosting effect on Hg0 concentration in
the air, while Hg0 air–surface exchange showed significant
bi-directional fluctuations during this period, yielding a surplus of
Hg0 emission (Fig. 4b). In turn, field flood irrigation was conducted on
26 June starting from the southern end of the field south of the eddy tower
(distance ∼ 130 m). The flooding of the southern field was completed
soon after noon (indicated by the ramp in soil moisture measured near the
flux tower, Fig. 7). During most of this irrigation period the REA flux
footprint falls outside the primary area. However, as wind gradually turned
towards southerlies (and increased from ∼ 2 to ∼ 4 m s-1),
the integrated flux signal derived increasingly from wetted field surfaces,
with good representativeness commencing at noon and following for a few hours
(90 % isopleth footprints predicted at 107 ± 43 m during this
period; concerning the models employed for this purpose, cf. Sommar et al.,
2013b). As seen in Fig. 7, Hg0 and water vapor fluxes jointly show
enhancement after the wind transition, indicating that volatilization of
Hg0 from soils occurred in response to field irrigation. After initial
spike-like features (> 300 ng m-2 h-1), there is a
decline in Hg0 flux over the time the irrigated field was upwind of the
measurement system (until ∼ 17:30). Similar observations have been made
from field and controlled laboratory experiments, where prompt and
substantial release of Hg0 from soils has been observed following
precipitation/irrigation provided the soil initially was quite dry (Bahlmann
et al., 2004; Lindberg et al., 1999; Song and Van Heyst, 2005). Possible
causes of the observed pattern include physical displacement of soil pore air
enriched in Hg0 and desorption of Hg0 loosely bound onto surfaces
as water percolates into the soil (Lindberg et al., 1999). Over the course of
the rest of campaign 2, the magnitude and variability in Hg0 flux were
substantially lower (minor emission flux predominant) than before irrigation
(Fig. 4b). In correspondence, Schroeder et al. (2005) found that persistent
rain and high soil moisture contents inhibit Hg evasion from soils, which
could be linked to restrictions in the replenishment of Hg0 towards the
soil surface due to low diffusivity through water-filled micropores
(Schlüter, 2000). Overall, precipitation events were scarce during the
flux measurement periods. During campaign 3, two substantial precipitation
events occurred on 2 and 7 September (cf. Fig. 4c), but none of the events
yielded any discernible enhancement in Hg0 emission (unanimously gauged
by REA and DFC). As aforementioned, surface soil was relatively moist during
this period, which may have acted as a controlling factor (Song and Van
Heyst, 2005).
Wet deposition Hg fluxes and mature crop foliar Hg
concentrations
For the study period with a precipitation depth of 51 cm, the
volume-weighted mean THg concentration in precipitation was
17.2 ng L-1, corresponding to a cumulated wet deposition flux of
8.8 µg Hg m-2 (Fig. 8). Maximum concentrations
(-113.3 ng L-1) were detected in event precipitation during winter.
However, ∼ 65 % of the THg wet deposition flux for the period
occurred during the summer months due to the largely asymmetric pattern in
annual precipitation (cf. Fig. 8 and Table S1 in the
Supplement). The large temporal variability and
range of concentrations among the samples (Table S1) correspond well to
observations at rural sites influenced by strong regional Hg combustion
sources (Keeler et al., 2006; Schwesig and Matzner, 2000).
The THg content in mature corn and wheat foliage associated with stands of a
dry leaf mass density of ∼ 0.5 kg m-2 was determined to be
36.4 ± 3.1 (n= 3) and 122.9 ± 13.9 ng g-1 dry weight
(n= 6), respectively. The observed foliar Hg level is comparable with the
results obtained from controlled exposure of corn and wheat to elevated
Hg0 concentrations in air (Niu et al., 2011). The higher Hg accumulation
in wheat compared to corn foliage aligns well with the differential Hg0
uptake inferred from Hg0 flux measurements (Sect. 3.4.2). Furthermore,
compartmentalized Hg analysis of mature corn plants shows the Hg content
increased in the order root (5.7 ± 1.1 ng g-1, n= 5) < stem (12.8 ± 3.5 ng g-1, n= 5) < foliage, which is indicative that vegetative uptake of
airborne Hg0 is primarily retained in cereal crop leafage. Worth
noticing is also the THg content in our wheat foliage samples exceeding the
maximum level (110 ng g-1 dry weight) in animal feeding material
(forage) issued by the European Union (EC, 2002). In addition, a survey of
heavy metals in wheat and corn crops grown in the study area by Lin et
al. (2010) has revealed Hg content in wheat grain at levels proximate to or
prevalently exceeding the Chinese tolerance limit for food (20 ng g-1
dry weight).
Discussion
Hg0 exchange between atmosphere and grain croplands
Measurements over the wheat–corn rotational cropland on the NCP show that
each of the vegetation and soil exchange processes is important in defining
net Hg0 fluxes. The emergence of a canopy layer creates a sink for
atmospheric Hg, while the canopy cover reduces the potential of underlying
soil to act as an Hg0 source. Our data also indicate that besides
vegetation density (LAI) and the physical plant structure, the type of
cultivated cereal crop has an effect on Hg0 gas exchange by
species-specific foliage uptake rates. Nevertheless, the chamber measurement
taken here evinced that ground Hg0 emissions within developed crop
canopies are substantial in the warmer season. Regardless of growing stage,
Hg0 uptake by wheat canopies is not equal to cumulatively offsetting the
Hg0 efflux from ground surfaces (April–June mean Hg0 net flux:
20.0 ng m-2 h-1). Flux data available in this study over corn
indicate that the fully grown, dense canopy can dominate the Hg0
exchange process, resulting in daytime net deposition. For the early growing
stages of corn not measured in this study, MM flux measurements by Cobos et
al. (2002) and Baya and Van Heyst (2010) over non-contaminated soils (THg:
∼ 25 and ∼ 50 ng g-1, respectively) quantified net
Hg0 emission as prevailing (mean flux: 9.7 and
15.2 ng m-2 h-1). Considering the whole micrometeorological
Hg0 flux data set collected over the full-year 2012–2013 study period
(using REA during campaigns 1–5 and MBR during IC in November, Zhu et al.,
2015a) yields an overall mean Hg0 evasion flux of
7.1 ng m-2 h-1, accounting for nearly 5700 individual Hg0
flux observations. Although there are substantial periods over the 2012–2013
study when flux measurements were not conducted, it appears that the
wheat–corn rotational cropland investigated constitutes a net source of
atmospheric Hg0 on an annual basis. Any definite estimate of annual
Hg0 flux is however not feasible due to the large uncertainty inherent
in such an attempt at extrapolation. Before a robust estimate can be
constructed, other factors such as the degree of inter-annual variability
must also be considered. Nevertheless, the direction and magnitude of the
mean Hg0 flux measured at our site agree well with that
(6.3 ng m-2 h-1) reported by Baya and Van Heyst (2010) for
Hg0 exchange over a soybean–corn cropland (November–April and June).
For croplands, the study of Baya and Van Heyst (2010) is the only one found
in the literature of temporal extent comparable with our study. Although
spanning across seasons, their reported Hg0 flux data however only
marginally target seasons with substantial crop canopy closure. There are
growing seasonal studies of Hg0 net exchange over biomes predominantly
vegetated by stands of non-cereal graminaceous plants. Lee et al. (2000)
reported for a fetch of growing salt meadow cord grass a trend from net
emission during the period before complete leaf-out (mean:
1.8 ng m-2 h-1) to predominant dry deposition during the full
foliage stage (mean: -3.3 ng m-2 h-1). In correspondence to
our study, Smith and Reinfelder (2009) observed significant daytime Hg0
deposition over a fully grown canopy (Phragmites australis)
coinciding with elevated ambient air concentrations.
Time series (May 2012–May 2013) of (a) above-canopy
(blue-shaded bars) and air–soil Hg0 flux (red-shaded bars) cumulated
for each sampling campaign and (b) of event-measured (shaded bars,
right axis) and THg wet deposition flux cumulated over the period (dotted
blue line shaded down to the abscissa, left axis).
The magnitude of average mid-day Hg0 dry deposition over fully grown
wheat and corn (Fig. 6) could be reproduced using a single-layer modeling
approach (Wesely and Hicks, 1977) with a total leaf conductance
parameterization to Hg0 according to Lindberg et al. (1992) and input of
average mid-day observations of conductances ga
(3.5 cm s-1) and gc (2.1 cm s-1) together with C
(4.1–6.6 ng m-3). Associated cereal foliar Hg0 uptake rates
estimated by combined REA and DFC measurements compare in magnitude
(∼ 7–19 ng m-2 leaf area h-1) favorably with observations
for aspen foliage in controlled gas-exchange systems operated at moderately
elevated Hg0 concentrations (Ericksen and Gustin, 2004; Ericksen et al.,
2003). The periods with consistent daytime imbalances between above- and
under-canopy flux during the early phases of campaign 1 (wheat) and campaign
3 (corn) explain up to ∼ 20 % and ∼ 50 % of the quantity
of Hg accumulated by the mature foliage of wheat and corn, respectively. This
indicates a relatively high contribution of the mercury load to the cereal
occurring during its final vegetative stage. In many circumstances, our
micrometeorological flux estimates appear better suited to addressing the
magnitude of the net cropland–atmosphere exchange and not ideal in
combination with DFC for constraining vegetative Hg0 uptake as the
ground surface is the major source of Hg0 emission. Nonetheless,
controlled experiments (Niu et al., 2011) envisaged ongoing assimilation of
atmospheric Hg0 by winter wheat during its extensive period of leaf
production for which we have limited REA and DFC flux data coverage.
Implications for estimation of a local Hg budget
Besides Hg0 air–surface exchange focused on in this study, Hg input
through dry deposition of other atmospheric Hg forms (gaseous oxidized
mercury, GOM, and particulate-bound mercury, PBM) and bulk THg wet deposition
are potentially important pathways in the local Hg cycle. Projecting the
scale of THg wet deposition to Hg0 soil emission predominant over the
vast majority of the year (Fig. 8), it is unlikely that wet deposition even
on a short-term basis could provide support for the magnitude of
volatilization observed at YCES. Given that the top soil horizon has a
uniform and low THg content, it is also unlikely that its inherent Hg pool
can sustain substantial losses to the atmosphere via Hg0 volatilization
without continual replenishment. We therefore hypothesize that Hg input from
a combined removal of atmospheric GOM and PBM constitutes the major
deposition pathway to this site. High ratios of PBM2.5 (Hg bound to
PM2.5) to GOM as well as of PBM2.5 to Hg0 are characteristic
of atmospheric Hg in the NCP region (Zhang et al., 2013). In China, there is
a paucity of observational Hg dry deposition studies. However, a high
dry-to-wet Hg deposition ratio has been inferred from studies of Chinese
forested ecosystems (Fu et al., 2015; Wang et al., 2009). Predicted total Hg
deposition to the site area using simulations by the GEOS-Chem model is
elevated and on the order of 80–100 µg m-2 yr-1
(L. Wang et al., 2014), which would in theory quantitatively allow for a
reasonably high Hg0 efflux from agricultural soils in the NCP region.
This presupposes that a significant portion of HgII species
deposited to the ecosystem is labile towards reduction to Hg0, which
then should be extensively re-emitted back into the atmosphere. In the
literature, there is support for the hypothesis that contemporary deposited
Hg to a larger extent than the ambient Hg pool in terrestrial ecosystems is
recycled to the atmosphere via surface photo-reduction and re-volatilization
(Eckley et al., 2013; Ericksen et al., 2005; Graydon et al., 2006, 2012;
Hintelmann et al., 2002). The observed abrupt pulse in Hg0 emissions
from dry soil in response to flood irrigation (Sect. 3.4.4) suggests the
seasonal presence of an ample pool of Hg0 in the upper soil horizon.
Soil characteristics present at YCES such as a low level of organic matter
(Edwards and Howard, 2013; Fu et al., 2012; Sigler and Lee, 2006), clayey
components (Biester et al., 2002) and high alkalinity (Landa, 1978; Xin and
Gustin, 2007; Yang et al., 2007) appear to facilitate Hg0 formation,
which in association with prevalent residual porosity allows for Hg0
mobility towards the soil–air interface and losses to air. The differential
magnitude of Hg0 soil efflux measured under developed canopies with
moist and dry soil, respectively, indicates that the combined level of
precipitation/irrigation is one of the most important seasonal variables that
control the magnitude of Hg0 emission from the ground at the site.