Mercury vapor air–surface exchange measured by collocated micrometeorological and enclosure methods – Part II: Bias and uncertainty analysis

Abstract

Abstract. Dynamic flux chambers (DFCs) and micrometeorological (MM) methods are extensively deployed for gauging air-surface Hg 0 gas exchange. However, a systematic evaluation of the precision of the contemporary Hg 0 flux quantification methods is not available. In this study, the uncertainty in Hg 0 flux measured by the relaxed eddy accumulation (REA) method, the aerodynamic gradient method (AGM), the modified Bowen ratio (MBR) method, as well as DFC of traditional (TDFC) and novel (NDFC) designs, are assessed using a robust data set from two field intercomparison campaigns.The absolute precision in Hg 0 concentration difference ( C) measurements is estimated at 0.064 ng m −3 for the gradient-based MBR and AGM systems. For the REA system, the parameter is Hg 0 concentration (C) dependent at 0.069 + 0.022C. During the campaigns, 57 and 62 % of the individual vertical gradient measurements are found to be significantly different from 0, while for the REA technique, the percentage of significant observations is lower. For the chambers, non-significant fluxes are confined to a few nighttime periods with varying ambient Hg 0 concentrations. Relative bias for DFC-derived fluxes is estimated to be ∼ ±10, and ∼ 85 % of the flux bias is within ±2 ng m −2 h −1 in absolute terms. The DFC flux bias follows a diurnal cycle, which is largely affected by the forced temperature and irradiation bias in the chambers. Due to contrasting prevailing micrometeorological conditions, the relative uncertainty (median) in turbulent exchange parameters differs by nearly a factor of 2 between the campaigns, while that in C measurement is fairly consistent. The estimated flux uncertainties for the triad of MM techniques are 16-27, 12-23 and 19-31 % (interquartile range) for the AGM, MBR and REA methods, respectively. This study indicates that flux-gradient-based techniques (MBR and AGM) are preferable to REA in quantifying Hg 0 flux over ecosystems with low vegetation height. A limitation of all Hg 0 flux measurement systems investigated is their inability to obtain synchronous samples for the calculation of C. This reduces the precision of flux quantification, particularly in the MM systems under non-stationarity of ambient Hg 0 concentration. For future applications, it is recommended to accomplish C derivation from simultaneous collected samples.

Mercury fluxes over an Australian alpine grassland and observation of nocturnal atmospheric mercury depletion events

“…The bimodal pattern of GEM fluxes has been observed previously by others (e.g. Fritsche et al, 2008b;Bash and Miller, 2008;Zhu et al, 2015) and attributed to co-deposition of mercury with dew overnight, with subsequent re-volatilisation of GEM as the dew is evaporated from the surface. The linear correlation of GEM fluxes with latent heat fluxes in this study similarly provides evidence for this explanation of the bimodal GEM flux pattern.…”

“…The low linear correlation between GEM flux and soil temperature compared to scalar fluxes of heat may suggest that turbulent atmospheric processes (quasi-laminar and turbulent diffusion), rather than insoil processes, represent the larger influence on GEM fluxes. Zhu et al (2015) found stronger relationships between aerodynamic variables and GEM fluxes when measured by micrometeorological methods than when measured with flux chambers, suggesting the choice of measurement may influence these relationships. Edwards and Howard (2013) however similarly observed stronger relationships with atmospheric variables and GEM fluxes measured using dynamic flux chambers over bare background THg soil.…”

Global observations and modeling of atmosphere–surface exchange of elemental mercury: a critical review

“…There has not been a standardized protocol for any of the techniques (e.g., instrumentation set-up, operation parameters) (Gustin, 2011;Zhu et al, 2015b). Recent collocated measurements and uncertainties analysis emphasized the importance of method standardization and processing of field data acquired by the measurement systems (Fritsche et al, 2008b;Converse et al, 2010;Zhu et al, 2015a). Application of the appropriate flux measurement technique depends on the scalar detection accuracy, sensor response frequency and level of automation (Sutton et al, 2007).…”

“…2). Direct measurement of Hg 0 flux from the background surfaces is difficult due to small vertical Hg 0 concentration gradients (therefore low flux) (Zhu et al, 2015a). Since the first application of a stainless steel dynamic flux chamber for Hg 0 flux measurements over background lakes and soils in the 1980s (Schroeder et al, 1989;Xiao et al, 1991), significant advancements in the experimental approaches (e.g., dynamic flux chambers, micrometeorological methods, the Hg 0 / 222 Rn flux ratio, enriched isotope tracer methods, the open-path laser optical spectroscopic method and the Hg 0 / CO ratio) have been made (Sommar et al, 2013a).…”

“…In addition to the uncertainties caused by varying flushing flow rates, altered short and long wave radiation balances within DFCs resulting in a modified micro-environment were found to bias the observed fluxes (Zhu et al, 2015a). DFC flux is measured through intermittent sampling of ambient and chamber air for Hg 0 analysis using a single detector (Lindberg et al, 2002c), which assumes that ambient Hg 0 variability is negligible during air sampling.…”