Application of a GC-ECD for measurements of biosphere–atmosphere exchange fluxes of peroxyacetyl nitrate using the relaxed eddy accumulation and gradient method

Peroxyacetyl nitrate (PAN) may constitute a significant fraction of reactive nitrogen in the atmosphere. Current knowledge about the biosphere–atmosphere exchange of PAN is limited, and only few studies have investigated the deposition of PAN to terrestrial ecosystems. We developed a flux measurement system for the determination of biosphere–atmosphere exchange fluxes of PAN using both the hyperbolic relaxed eddy accumulation (HREA) method and the modified Bowen ratio (MBR) method. The system consists of a modified, commercially available gas chromatograph with electron capture detection (GC-ECD, Meteorologie Consult GmbH, Germany). Sampling was performed by trapping PAN onto two pre-concentration columns; during HREA operation one was used for updraft and one for downdraft events, and during MBR operation the two columns allowed simultaneous sampling at two measurement heights. The performance of the PAN flux measurement system was tested at a natural grassland site, using fast-response ozone (O₃) measurements as a proxy for both methods. The measured PAN fluxes were comparatively small (daytime PAN deposition was on average −0.07 nmol m⁻² s⁻¹) and, thus, prone to significant uncertainties. A major challenge in the design of the system was the resolution of the small PAN mixing ratio differences. Consequently, the study focuses on the performance of the analytical unit and a detailed analysis of errors contributing to the overall uncertainty. The error of the PAN mixing ratio differences ranged from 4 to 15 ppt during the MBR and between 18 and 26 ppt during the HREA operation, while during daytime measured PAN mixing ratios were of similar magnitude. Choosing optimal settings for both the MBR and HREA method, the study shows that the HREA method did not have a significant advantage towards the MBR method under well-mixed conditions as was expected

Scalar turbulent behavior in the roughness sublayer of an Amazonian forest.

An important current problem in micrometeorology is the characterization of turbulence in the roughness sublayer (RSL), where most of the measurements above tall forests are made. There, scalar turbulent fluctuations display significant departures from the predictions of Monin?Obukhov similarity theory (MOST). In this work, we analyze turbulence data of virtual temperature, carbon dioxide, and water vapor in the RSL above an Amazonian forest (with a canopy height of 40&#8239;m), measured at 39.4 and 81.6&#8239;m above the ground under unstable conditions. We found that dimensionless statistics related to the rate of dissipation of turbulence kinetic energy (TKE) and the scalar variance display significant departures from MOST as expected, whereas the vertical velocity variance follows MOST much more closely. Much better agreement between the dimensionless statistics with the Obukhov similarity variable, however, was found for the subset of measurements made at a low zenith angle Z, in the range 0°&#8239;&#8201;<&#8201;&#8239;|Z|&#8239;&#8201;<&#8201;&#8239;20°. We conjecture that this improvement is due to the relationship between sunlight incidence and the ?activation?deactivation? of scalar sinks and sources vertically distributed in the forest. Finally, we evaluated the relaxation coefficient of relaxed eddy accumulation: it is also affected by zenith angle, with considerable improvement in the range 0°&#8239;&#8201;<&#8201;&#8239;|Z|&#8239;&#8201;<&#8201;&#8239;20°, and its values fall within the range reported in the literature for the unstable surface layer. In general, our results indicate the possibility of better stability-derived flux estimates for low zenith angle ranges

Using phase lags to evaluate model biases in simulating the diurnal cycle of evapotranspiration: a case study in Luxembourg

While modeling approaches of evapotranspiration (λE) perform reasonably well when evaluated at daily or monthly timescales, they can show systematic deviations at the sub-daily timescale, which results in potential biases in modeled λE to global climate change. Here we decompose the diurnal variation of heat fluxes and meteorological variables into their direct response to incoming solar radiation (Rsd) and a phase shift to Rsd. We analyze data from an eddy-covariance (EC) station at a temperate grassland site, which experienced a pronounced summer drought. We employ three structurally different modeling approaches of λE, which are used in remote sensing retrievals, and quantify how well these models represent the observed diurnal cycle under clear-sky conditions. We find that energy balance residual approaches, which use the surface-to-air temperature gradient as input, are able to reproduce the reduction of the phase lag from wet to dry conditions. However, approaches which use the vapor pressure deficit (Da) as the driving gradient (Penman–Monteith) show significant deviations from the observed phase lags, which is found to depend on the parameterization of surface conductance to water vapor. This is due to the typically strong phase lag of 2–3&thinsp;h of Da, while the observed phase lag of λE is only on the order of 15&thinsp;min. In contrast, the temperature gradient shows phase differences in agreement with the sensible heat flux and represents the wet–dry difference rather well. We conclude that phase lags contain important information on the different mechanisms of diurnal heat storage and exchange and, thus, allow a process-based insight to improve the representation of land–atmosphere (L–A) interactions in models.</p

Modelling chemistry in the nocturnal boundary layer above tropical rainforest and a generalised effective nocturnal ozone deposition velocity for sub-ppbv NOx conditions

Measurements of atmospheric composition have been made over a remote rainforest landscape. A box model has previously been demonstrated to model the observed daytime chemistry well. However the box model is unable to explain the nocturnal measurements of relatively high [NO] and [O3], but relatively low observed [NO2]. It is shown that a one-dimensional (1-D) column model with simple O3 -NOx chemistry and a simple representation of vertical transport is able to explain the observed nocturnal concentrations and predict the likely vertical profiles of these species in the nocturnal boundary layer (NBL). Concentrations of tracers carried over from the end of the night can affect the atmospheric chemistry of the following day. To ascertain the anomaly introduced by using the box model to represent the NBL, vertically-averaged NBL concentrations at the end of the night are compared between the 1-D model and the box model. It is found that, under low to medium [NOx] conditions (NOx <1 ppbv), a simple parametrisation can be used to modify the box model deposition velocity of ozone, in order to achieve good agreement between the box and 1-D models for these end-of-night concentrations of NOx and O3. This parametrisation would could also be used in global climate-chemistry models with limited vertical resolution near the surface. Box-model results for the following day differ significantly if this effective nocturnal deposition velocity for ozone is implemented; for instance, there is a 9% increase in the following day’s peak ozone concentration. However under medium to high [NOx] conditions (NOx > 1 ppbv), the effect on the chemistry due to the vertical distribution of the species means no box model can adequately represent chemistry in the NBL without modifying reaction rate constants

The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models

&amp;lt;p&amp;gt;&amp;amp;#8216;Aerodynamic resistance&amp;amp;#8217; (hereafter r&amp;lt;sub&amp;gt;a&amp;lt;/sub&amp;gt;) is a preeminent variable in the modelling of evapotranspiration (ET), and its accurate quantification plays a critical role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links r&amp;lt;sub&amp;gt;a&amp;lt;/sub&amp;gt; with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The present study investigates the influence of r&amp;lt;sub&amp;gt;a&amp;lt;/sub&amp;gt; and its relation to LST uncertainties on the performance of three structurally different SEB models by combining nine OzFlux eddy covariance datasets from 2011 to 2019 from sites of different aridity in Australia with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the latent heat flux (LE, energy equivalent of ET in W/m&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt;) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST, LAI, and in-situ meteorological datasets were evaluated using observed flux data across water-limited (semi-arid and arid) and radiation-limited (mesic) ecosystems.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Our results revealed that the three models tend to overestimate instantaneous LE in the water-limited shrubland, woodland and grassland ecosystems by up to 60% on average, which was caused by an underestimation of the sensible heat flux (H). LE overestimation was associated with discrepancies in r&amp;lt;sub&amp;gt;a&amp;lt;/sub&amp;gt; retrievals under conditions of high atmospheric instability, during which errors in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive bias in LST coincides with low r&amp;lt;sub&amp;gt;a&amp;lt;/sub&amp;gt; and causes slight underestimation of LE at the water-limited sites. The impact of r&amp;lt;sub&amp;gt;a&amp;lt;/sub&amp;gt; on the LE residual error was found to be of the same magnitude as the influence of errors in LST in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for mesic forest ecosystems indicated minor dependency on r&amp;lt;sub&amp;gt;a&amp;lt;/sub&amp;gt; for modelling LE (VIP&amp;lt;0.4), which was due to a higher roughness length and lower LST resulting in dominance of mechanically generated turbulence, thereby diminishing the importance of atmospheric stability in the determination of r&amp;lt;sub&amp;gt;a&amp;lt;/sub&amp;gt;.&amp;lt;/p&amp;gt;</jats:p

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin.

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (&#955;ET) and evaporation (&#955;EE) flux components of the terrestrial latent heat flux (&#955;E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on &#955;ET and &#955;EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, &#955;ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on &#955;ET during the wet (rainy) seasons where &#955;ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80&#8239;% of the variances of &#955;ET. However, biophysical control on &#955;ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65&#8239;% of the variances of &#955;ET, and indicates &#955;ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between &#955;ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales

Canopy-scale biophysical controls on transpiration and evaporation in the Amazon Basin

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales

Efficient control of atmospheric sulfate production based on three formation regimes

The formation of sulfate (SO₄²⁻) in the atmosphere is linked chemically to its direct precursor, sulfur dioxide (SO₂), through several key oxidation paths for which nitrogen oxides or NO_x (NO and NO₂) play essential roles. Here we present a coherent description of the dependence of SO₄²⁻ formation on SO₂ and NO_x under haze-fog conditions, in which fog events are accompanied by high aerosol loadings and fog-water pH in the range of 4.7–6.9. Three SO₄²⁻ formation regimes emerge as defined by the role played by NO_x. In the low-NO_x regime, NO_x act as catalyst for HO_x, which is a major oxidant for SO₂, whereas in the high-NO_x regime, NO₂ is a sink for HO_x. Moreover, at highly elevated NO_x levels, a so-called NO₂-oxidant regime exists in which aqueous NO₂ serves as the dominant oxidant of SO₂. This regime also exists under clean fog conditions but is less prominent. Sensitivity calculations using an emission-driven box model show that the reduction of SO₄²⁻ is comparably sensitive to the reduction of SO₂ and NO_x emissions in the NO₂-oxidant regime, suggesting a co-reduction strategy. Formation of SO₄²⁻ is relatively insensitive to NO_x reduction in the low-NO_x regime, whereas reduction of NO_x actually leads to increased SO₄²⁻ production in the intermediate high-NO_x regime

A comparison of HONO budgets for two measurement heights at a field station within the boreal forest in Finland

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