Field testing two flux footprint models

A field study was undertaken to investigate the accuracy of two micrometeorological flux footprint models for calculating the gas emission rate from a synthetic 10 × 10 m surface area source, based on the vertical flux of gas measured at fetches of 15 to 50 m downwind of the source. Calculations were made with an easy-to-use tool based on the Kormann–Meixner analytical model and with a more sophisticated Lagrangian stochastic dispersion model. A total of 59 testable 10 min observation periods were measured over 9 d. On average, both models underestimated the actual release rate by approximately 30 %, mostly due to large underestimates at the larger fetches. The accuracy of the model calculations had large period-to-period variability, and no statistical differences were observed between the two models in terms of overall accuracy.

Implementation of a Lagrangian Stochastic Particle Trajectory Model (LaStTraM) to Simulate Concentration and Flux Footprints Using the Microclimate Model ENVI-Met

The number of studies evaluating flux or concentration footprints has grown considerably in recent years. These footprints are vital to understand surface–atmosphere flux measurements, for example by eddy covariance. The newly developed backwards trajectory model LaStTraM (Lagrangian Stochastic Trajectory Model) is a post-processing tool, which uses simulation results of the holistic 3D microclimate model ENVI-met as input. The probability distribution of the particles is calculated using the Lagrangian Stochastic method. Combining LaStTraM with ENVI-met should allow us to simulate flux and concentration footprints in complex urban environments. Applications and evaluations were conducted through a comparison with the commonly used 2D models Kormann Meixner and Flux Footprint Predictions in two different meteorological cases (stable, unstable) and in three different detector heights. LaStTraM is capable of reproducing the results of the commonly used 2D models with high accuracy. In addition to the comparison with common footprint models, studies with a simple heterogeneous and a realistic, more complex model domain are presented. All examples show plausible results, thus demonstrating LaStTraM’s potential for the reliable calculation of footprints in homogeneous and heterogenous areas.

Field Testing Two Flux Footprint Models

A field study was undertaken to investigate the accuracy of two micrometeorological flux footprint models when calculating the gas emission rate from a 10 × 10 m synthetic surface area source, based on the vertical flux of gas measured 15 to 50 m downwind of the source. Calculations were made with an easy-to-use tool based on the Kormann-Meixner analytical model and with a more sophisticated Lagrangian stochastic dispersion model. A total of 323 10 minute observation periods were measured over 9 days. On average, each of the two models calculated the emission rate to within 10 % of the actual release rate. No clear differences were observed between the two models in terms of overall accuracy.

Field-scale CH₄ emission at a sub-arctic mire with heterogeneous permafrost thaw status

The Artic is exposed to faster temperature changes than most other areas on Earth. Constantly increasing temperature will lead to thawing permafrost and changes in the CH4 emissions from wetlands. One of the places exposed to those changes is the Abisko-Stordalen Mire in northern Sweden, where climate and vegetation studies have been conducted from the 1970s.In our study, we analyzed field-scale methane emissions measured by the eddy covariance method at Abisko-Stordalen Mire for three years (2014–2016). The site is a subarctic mire mosaic of palsas, thawing palsas, fully thawed fens, and open water bodies. A bimodal wind pattern prevalent at the site provides an ideal opportunity to measure mire patches with different permafrost statuses with one flux measurement system. The flux footprint for westerly winds is dominated by elevated palsa plateaus, while the footprint is almost equally distributed between palsas and thawing bog-like areas for easterly winds. As these patches are exposed to the same climatic conditions, we analyzed the differences in the responses of their methane emission for environmental parameters.The methane fluxes followed a similar annual cycle over the three study years, with a gentle rise during spring and a decrease during autumn and with no emission burst at either end of the ice-free season. The peak emission during the ice-free season differed significantly for the mire with two permafrost statuses: the palsa mire emitted 24 mg-CH4 m−2 d−1 and the thawing wet sector 56 mg-CH4 m−2 d−1. Factors controlling the methane emission were analyzed using generalized linear models. The main driver for methane fluxes was peat temperature for both wind sectors. Soil water content above the water table emerged as an explanatory variable for the three years for western sectors and the year 2016 in the eastern sector. Water table level showed a significant correlation with methane emission for the year 2016 as well. Gross primary production, however, did not show a significant correlation with methane emissions. Annual methane emissions were estimated based on four different gap-filing methods. The different methods generally resulted in very similar annual emissions. The mean annual emission based on all models was 4.2 ± 0.4 g-CH4 m−2 a−1 for western sector and 7.3 ± 0.7 g-CH4 m−2 a−1 for the eastern sector. The average annual emissions, derived from this data and a footprint climatology, were 3.6 ± 0.7 g-CH4 m−2 a−1 and 11 ± 2 g-CH4 m−2 a−1 for the palsa and thawing surfaces, respectively. Winter fluxes were relatively high, contributing 27–45 % to the annual emissions.

The role of cows on OVOC exchanges of a pasture

<p>The presence of cows on a pasture considerably modifies exchanges of biogenic volatile organic compounds (BVOCs). By regulating the biomass present, they can have an impact on the constitutive flux (exchanges from soil and grass that are not induced by leaf wounding or trampling by cows) but they can also cause direct emissions from exhalation and indirect emissions by leaf injury (grazing), trampling and wastes. In this study conducted on the ICOS pasture site of Dorinne (Belgium), we disentangled these different sources/sinks for three oxygenated BVOCs commonly exchanged on grasslands (methanol, acetaldehyde and acetone), using a combination of turbulent flux measurements, enclosure flux measurements, tools to detect the presence and activity of cows in the footprint of the turbulent flux measurements and a flux footprint model. Direct exhalation emissions were low, representing only 2.3% and 10% of the spring total flux of methanol and acetone respectively. Comparison of grazed and non-grazed enclosures pointed out that emissions following leaf wounding were significant for all studied BVOCs, decreased exponentially with time to become negligible after maximum five days. Cow indirect emissions at the pasture scale (turbulent flux measurements) where likely dominated by grazing and were shown to be a major component of the total diurnal flux for each of the three studied BVOCs. Comparison with a hay meadow also showed that the temporal dynamics of those BVOC emissions were very different according to the grass management type, calling for specific parametrization in up-scaling emission models.</p>

A tool for evaluation of target area homogeneity at ecosystem stations employing eddy covariance method

<p>Our understanding of the carbon and water cycle was greatly improved through application of eddy covariance measurements in recent decades. Though powerful, this micrometeorological approach relies on a number of assumptions that can be affected by a selection of station location. Most importantly, terrain of the target area should be flat, target area should be homogeneous and adequate air mixing should be achieved. Although possible shortcomings can be reduced by careful site inspection before tower installation (flat terrain) or can be corrected for during data post-processing (filtering of periods with low mixing), preliminary assessment of target area homogeneity is difficult as well as correction of its impacts afterwards. The influence of such inhomogeneities can lead to a bias in the flux annual sums but also a bias in their relationships with environmental variables. Certain solutions were already proposed, but target area homogeneity was so far assessed only at a few selected sites. Here we aim to provide a suit of software tools that build on the existing software packages (REddyProc, Flux Footprint Prediction, openair, openeddy) and allow easy diagnosis of the situation at the given ecosystem station. We plan to provide directional analyses of variables of interest. This will allow to identify the wind sectors that show large deviations from the mean value of the whole target area. In a further step, we plan to combine footprint modeling with CO<sub>2</sub> and energy flux measurements and thus provide attribution of mean (weighted) fluxes to their source area. Based on the differences with the directional analyses we will assess whether the higher computational expenses of footprint modeling are justified and bring additional information. Finally, we plan to separate the target area to a limited amount of wind sectors and attempt separate gap-filling and flux partitioning for areas identified by preceding homogeneity evaluation. The limitations and feasibility of this approach will be assessed.</p><p>This work was supported by the Ministry of Education, Youth and Sports of CR within Mobility CzechGlobe2 (CZ.02.2.69/0.0/0.0/18_053/0016924).</p>

Exploring the variation in ecosystem scale methane fluxes and its drivers within a boreal mire complex

<p>Northern peatlands cover a small fraction of the earth’s land surface, and yet they are one of the most important natural sources of atmospheric methane. With climate change causing rising temperatures, changes in water balance and increased growing season length, peatland contribution to atmospheric methane concentration is likely to increase, justifying the increased attention given to northern peatland methane dynamics. Northern peatlands often occur as heterogeneous complexes characterized by hydromorphologically distinct features from < 1 m² to tens of km², with differing physical, hydrological and chemical properties. The more commonly understood small-scale variation between hummocks, lawns and hollows has been well explored using chamber measurements. Single tower eddy covariance measurements, with a typical 95% flux footprint of < 0.5 km², have been used to assess the ecosystem scale methane exchange. However, how representative single tower flux measurements are of an entire mire complex is not well understood. To address this knowledge gap, the present study takes advantage of a network of four eddy covariance towers located less than 3 km apart at four mires within a typical boreal mire complex in northern Sweden. The variation of methane fluxes and its drivers between the four sites will be explored at different temporal scales, i.e. half-hourly, daily and at a growing-season scale.</p>

A data-driven approach to quantifying urban evapotranspiration using remote sensing, footprint modeling, and deep learning

<p>An increasing number of urban residents are affected by the urban heat island effect and water scarcity as urbanization and climate change progress. Evapotranspiration (ET) is a key component of urban greening measures aimed at addressing these issues, yet methods to estimate urban ET have thus far been limited. In this study, we present a novel approach to model urban ET at a half-hourly scale by fusing flux footprint modeling, remote sensing (RS) and geographic information system (GIS) data, and artificial intelligence (AI). We investigated this approach with a two-year dataset (2018-2020) from two eddy flux towers in Berlin, Germany. Two AI algorithms (1D convolutional neural networks and random forest) were compared. The land surface characteristics contributing to ET measurements were estimated by combining footprint modeling with RS and GIS data, which included Normalized Difference Vegetation Index (NDVI) derived from the Harmonized Landsat and Sentinel-2 (HLS) NASA product and indicators of 3D urban structure (e.g. building height). The contribution of remote sensing and meteorological data to model performance was examined by testing four predictor scenarios: (1) only reference evapotranspiration (ETo), (2) ETo and RS/ GIS data, (3) meteorological data, and (4) meteorological and RS/ GIS data. The inclusion of GIS and RS data extracted using flux footprints improved the predictive accuracy of models. The best-performing models were then used to model ET values for the year 2019 and compute monthly and annual sums of ET. A variable importance analysis highlighted the importance of the NDVI and impervious surface fraction in modeling urban ET. The 2019 ET sum was considerably higher at the site surrounded by more urban vegetation (366 mm) than at the inner-city site (223 mm). The proposed method is highly promising for modeling ET in a heterogeneous urban environment and can bolster sustainable urban planning efforts.</p>

High trace gas concentrations during lowered boundary layer heights at a Swiss tall tower site

<p>Measurements of trace gas concentrations and their fluxes are essential to investigate source regions of greenhouse gases (GHGs) and other pollutants. Most flux towers provide observations at heights of several meters to tens of meters and therefore provide information about possible flux sources on a local spatial scale. Here we present an analysis of trace gas concentration and flux measurements from one of the few European tall towers located close to Beromünster, Switzerland. The tower was initially set up as a CarboCount CH site — a dense GHG observation network run for four years (2012 - 2015) — and is continued since by the University of Bern. The presented measurements are taken at an altitude of 212m above ground. This relatively high observation height results in a flux footprint of the tower of many kilometers and therefore the tower observations are predestined for a source analysis on a much larger scale than typical for flux towers. We analyze subsets of the available time series selected by season, time of day, wind direction, and other criteria. In a first step, the field of view of the tower for these subsets is estimated with a flux footprint parameterization. This is followed by a correlation analysis between various observations. Results indicate particularly high trace gas concentrations during periods of lowered planetary boundary layer heights and wind coming from the Zurich metropolitan area. In a next step we intend to perform a field of view analysis with a Lagrangian atmospheric transport model (Flexpart).</p>