Dynamic flux chambers (DFCs) and micrometeorological (MM) methods are
extensively deployed for gauging air–surface Hg

The absolute precision in Hg

The volatility of atomic mercury (Hg

The preferred MM technique, eddy covariance (EC), a direct flux measurement
method without any applications of empirical constants, requires a fast
response (

Most studies that investigated Hg

The instrumentation setup, quality control measures and a full site
description have been described in the Part I paper (Zhu et al., 2015).
Briefly, two field campaigns were performed in late autumn 2012 (IC
no. 1, bare ploughed soil fetch, 4–24 November, DOY
309–329) and spring 2013 (IC no. 2, low-standing wheat canopy, 16–25 April,
DOY 106–115) over agricultural fields inside Yucheng Comprehensive
Experimental Station (YCES) located on the North China Plain
(^{®} 1110) coupled with the respective
automated Tekran^{®} model 2537B Hg vapor
analyzer (Tekran Instruments Corp.). Accumulated updraft and downdraft and
two-height level air were sampled in sequences of 10 min intervals (two
5 min samples). The TDFC and NDFC were operated in tandem at a flow rate of
15 L min^{®}
model 1115).

Approximately 15 % of the measurement periods were dedicated to
calibrations, blank testing and other QA ^{™} 5.0 flux analysis
software package (LI-COR Biosciences Inc.). To indicate periods of limited
turbulent mixing, all the individual flux data were flagged using the basic
0-1-2 system scale scheme described in Mauder and Foken (2004), where class 2
indicates a hard flag (low data quality). The data assigned for high (Flag 0)
and moderate (Flag 1) turbulence quality (with respect to sensible heat flux)
corresponded to 55 and 81 % of the flux observations during IC no. 1 and IC
no. 2, respectively (66 % in total). Periods when horizontal wind
approached the sampling tower within the immediate

Error is a single value indicating the difference between an individual
measurement and the true quantity being measured. In practice, an observed
measurement error is the difference between the observed value and a
reference value (Ellison and Williams, 2012). For measurement (

Multiple Tekran^{®} 2537 mercury vapor analyzers
were deployed in this study. For each analyzer, a pre-filtered sample air
stream is passed through a gold cartridge that traps Hg by amalgamation,
which then is thermo-desorbed and detected by atomic fluorescence
spectrophotometry. The instrument utilizes two gold cartridges in parallel,
with alternating operation modes (sampling and desorbing/analyzing in a
Hg-free Ar stream)
on a pre-defined time base of 5 min to allow for continuous operation. The
instrument is equipped with an internal permeation source (secondary
standard, VICI Metronics Inc., Paulsbo, USA) that can be invoked
automatically to perform two-point calibrations with a span value of

The uncertainty in concentration measurement depends on the individual
uncertainties in the sample volume, the peak integration and the field
calibration procedure. The sample volume is derived from an internal mass
flow controller (MFC, Bronkhorst High-Tech B. V., Ruurlo, Netherlands) and
reported exclusively within

All the examined flux techniques rely on measurement of Hg

Since a single 2537B does not have the ability to analyze samples from two
channels synchronously, the calculation of concentration difference is based
on temporally intermittent concentration measurement. This means that
uncertainties in

The MM and DFC techniques rely on entirely independent principles. Even at
the high air exchange rates (

DFC measurement of Hg

Predictive regression models are developed for each of the chamber types
(Lin et al., 2010):

Overall fits (correlation coefficient,

Concerning the NDFC approach, the uncertainty in the last term
(

There are several errors in the MM flux measurements, especially for the REA
technique. In general, the sources include source/sink characteristic
(footprint variability), turbulent transport and instrumentation factors
(Businger, 1986). Turbulent Hg

Using error propagation theory on Eq. (3), uncertainties associated with the
REA-derived fluxes can be calculated by Eq. (12):

However, the first term was demonstrated to give an insignificant
contribution to the combined uncertainty (see Sect. 4.2). Excluding the
contribution from

The REA system is potentially affected by lag-time bias and the attenuation
of high-frequency concentration fluctuations in the tube flow that leads to
an underestimation of turbulent fluxes. These effects were evaluated
following Moravek et al. (2013) and the results are reported in Sect. 4.2.
Theoretically,

In practice, bias exists due to departures from a 0 mean vertical wind speed
(

The AGM flux is computed as the product of transfer velocity (

The relative uncertainty in

Similar to the assessment of

The uncertainty in concentration measurements of the three collocated Tekran
2537Bs was calculated from the uncertainty in volume and calibration
measurements. Sample volumes derived from independent techniques are found to
be within

Frequency distribution of DFC flux bias (

Box-whisker plots of diurnal flux bias measured with two DFCs. The
box boundaries represent 25th and 75th percentiles from bottom to top, and
whiskers indicate 10th and 90th percentiles of Hg

Field blanks determined in connection with regular flux measurement periods
were consistently low for both DFCs (TDFC:
0.2

Estimated Hg

Notes: for MM techniques, bias and uncertainties are given as
fractional values (percent) of the flux representing the median

The lag-time bias due to unsynchronized conditional sampling (Baker et al.,
1992) is estimated at

The evaluation of the effectiveness of the applied conditional sampling
filter (Sect. “REA method”) is applied to data flagged for high-quality
turbulence (Flag 0,

Scatterplot of the

The relative uncertainty in

Scatterplot of fractional uncertainty in sensible heat flux
(

The uncertainty and bias in

Results from conditional channel inter-comparison using the REA
reference sampling mode (slope: 1.051; intercept:

Inspection of residuals of the orthogonal fit plotted as a function of
sampling time (record number) showed homoscedastic features. In Fig. 7, the
residuals that approximately align with a Gaussian distribution are plotted
as a function of Hg

The last term in Eq. (13) was assessed from the sonic temperature measurement
resolution (root mean square) of 0.025 K for standard settings of CSAT-3
(

Histogram of residuals obtained after correcting the channel data
for bias with orthogonal linear regression (right). Scatterplot of residuals
versus Hg

Scatterplot of concentrations from lower and upper level sampling
lines during side-by-side measurement. The linear fit derives from orthogonal
regression. The

The primary bias in the MBR and AGM flux is caused by the potential sampling
artifact for determining concentration gradients. Extended periods of
side-by-side measurements (gas sampling inlets were brought to one height in
the same lateral proximity as during regular gradient sampling) were
conducted. The comparison between the collocated lines used for two-level
gradient sampling is based on sequential concentration data. For a further
investigation, cross-interpolation was used as an imputation method to fill
up missing values in the time-concentration series. Orthogonal linear
regression indicated that a bias existed between the sampling lines (Fig. 8),
where the longer sampling tube (upper level) is biased low by 4.1 %. The
remaining scatter (residual) distribution followed a Gaussian distribution
and was homoscedastic with respect to sampling time and concentration. Hence,

Individual

Relationship between fractional uncertainty in momentum
flux (

Based on the

Turbulent Hg

The level of the detection limit obtained in this study (0.064 ng m

Table 1 summarizes the uncertainty in MM and DFC flux methods in our
inter-comparison. The relative uncertainties for transfer velocity and
sensible heat flux in IC no. 1 have nearly doubled (on a median basis)
compared to those in IC no. 2 due to its lower turbulence quality. The
uncertainty estimates associated with EC sampling errors based on the
variance analysis of covariance time series (Finkelstein and Sims, 2001) used
in this study are expected to be somewhat larger than calculations based on
side-by-side comparisons or paired observations (Mauder et al., 2013).
However, the latter type of estimate concerning uncertainties in
concentration difference measurements is provided here as an upper limit.
Median

Box-whisker plots of the hourly fractional flux bias (

Linear regression of the Hg

For most of the IC no. 2 periods,

The estimated uncertainty in

The REA system utilizes zero-air injection and is equipped with actuators to
suppress pressure differentials occurring in the upstream zone of the
fast-response sampling valves that promotes constant flow rate
characteristics (Sommar et al., 2013b). This scheme (the effective sampling
time per conditional channel is on average

A disadvantage in coupling the flux measurement techniques with a
single-channel gas analyzer (e.g., Tekran 2537) is the temporally
asynchronous samples obtained for the calculation of

There are additional sources contributing to the uncertainty and bias in
Hg

In this paper, five contemporary Hg

The highest relative median flux uncertainty was observed for the REA
technique (24 %, IC no. 2), followed by 24 and 15 % for MBR, and 15 and
12 % for AGM during IC no. 1 and no. 2, respectively. Overall, a higher
imprecision in Hg

Notes: (*) the “atmosphere parameter” can
be specified as

This research was financially supported by the 973 Program (2013CB430002), the National Science Foundation of China (41030752), the Chinese Academy of Sciences through an instrument development program (YZ200910), and the State Key Laboratory of Environmental Geochemistry. We would like to express our gratitude to the staff from Yucheng Comprehensive Experimental Station, Chinese Academy of Sciences, for sampling and logistical assistance. Edited by: L. Zhang