The exchange of ozone between vegetation and atmosphere: micrometeorological measurement techniques and models
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Direct monitoring of CO2 exchange in forest ecosystems is necessary for evaluation of the annual net CO2 flux. We developed an automated foliage chamber system for long-term in situ measurement of the CO2 flux in foliage. The chamber closes automatically for 5 min in every 30. We found a high correlation between the photosynthesis rates measured by this system and by a portable H2O/CO2 analyzer (LCA-3, ADC). We used the new system to continuously monitor the CO2 flux in foliage of Quercus serrata. There was a positive correlation between CO2 flux and short-wave radiation. The daily photosynthesis rate varied widely depending on the environmental conditions. It increased from May to July and decreased temporarily in August. The seasonal pattern of photosynthesis was almost the same as that measured by the eddy covariance method. These results suggest that the new system is effective for tracking long-term seasonal change of the CO2 flux in foliage.
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Spatial heterogeneity in methane (CH 4 ) flux requires a reliable upscaling approach to reach accurate regional CH 4 budgets in the Arctic tundra. In this study, we combined the CLM-Microbe model with three footprint algorithms to scale up CH 4 flux from a plot level to eddy covariance (EC) tower domains (200 m × 200 m) in the Alaska North Slope, for three sites in Utqiaġvik (US-Beo, US-Bes, and US-Brw), one in Atqasuk (US-Atq) and one in Ivotuk (US-Ivo), for a period of 2013–2015. Three footprint algorithms were the homogenous footprint (HF) that assumes even contribution of all grid cells, the gradient footprint (GF) that assumes gradually declining contribution from center grid cells to edges, and the dynamic footprint (DF) that considers the impacts of wind and heterogeneity of land surface. Simulated annual CH 4 flux was highly consistent with the EC measurements at US-Beo and US-Bes. In contrast, flux was overestimated at US-Brw, US-Atq, and US-Ivo due to the higher simulated CH 4 flux in early growing seasons. The simulated monthly CH 4 flux was consistent with EC measurements but with different accuracies among footprint algorithms. At US-Bes in September 2013, RMSE and NNSE were 0.002 μmol m −2 s −1 and 0.782 using the DF algorithm, but 0.007 μmol m −2 s −1 and 0.758 using HF and 0.007 μmol m −2 s −1 and 0.765 using GF, respectively. DF algorithm performed better than the HF and GF algorithms in capturing the temporal variation in daily CH 4 flux each month, while the model accuracy was similar among the three algorithms due to flat landscapes. Temporal variations in CH 4 flux during 2013–2015 were predominately explained by air temperature (67–74%), followed by precipitation (22–36%). Spatial heterogeneities in vegetation fraction and elevation dominated the spatial variations in CH 4 flux for all five tower domains despite relatively weak differences in simulated CH 4 flux among three footprint algorithms. The CLM-Microbe model can simulate CH 4 flux at both plot and landscape scales at a high temporal resolution, which should be applied to other landscapes. Integrating land surface models with an appropriate algorithm provides a powerful tool for upscaling CH 4 flux in terrestrial ecosystems.
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Abstract. Our understanding of biosphere–atmosphere exchange has been considerably enhanced by eddy covariance measurements. However, there remain many trace gases, such as molecular hydrogen (H2), that lack suitable analytical methods to measure their fluxes by eddy covariance. In such cases, flux-gradient methods can be used to calculate ecosystem-scale fluxes from vertical concentration gradients. The budget of atmospheric H2 is poorly constrained by the limited available observations, and thus the ability to quantify and characterize the sources and sinks of H2 by flux-gradient methods in various ecosystems is important. We developed an approach to make nonintrusive, automated measurements of ecosystem-scale H2 fluxes both above and below the forest canopy at the Harvard Forest in Petersham, Massachusetts, for over a year. We used three flux-gradient methods to calculate the fluxes: two similarity methods that do not rely on a micrometeorological determination of the eddy diffusivity, K, based on (1) trace gases or (2) sensible heat, and one flux-gradient method that (3) parameterizes K. We quantitatively assessed the flux-gradient methods using CO2 and H2O by comparison to their simultaneous independent flux measurements via eddy covariance and soil chambers. All three flux-gradient methods performed well in certain locations, seasons, and times of day, and the best methods were trace gas similarity for above the canopy and K parameterization below it. Sensible heat similarity required several independent measurements, and the results were more variable, in part because those data were only available in the winter, when heat fluxes and temperature gradients were small and difficult to measure. Biases were often observed between flux-gradient methods and the independent flux measurements, and there was at least a 26% difference in nocturnal eddy-derived net ecosystem exchange (NEE) and chamber measurements. H2 fluxes calculated in a summer period agreed within their uncertainty and pointed to soil uptake as the main driver of H2 exchange at Harvard Forest, with H2 deposition velocities ranging from 0.04 to 0.10 cm s−1.
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Abstract The application of the eddy covariance flux method to measure fluxes of trace gas and energy between ecosystems and the atmosphere has exploded over the past 25 years. This opinion paper provides a perspective on the contributions and future opportunities of the eddy covariance method. First, the paper discusses the pros and cons of this method relative to other methods used to measure the exchange of trace gases between ecosystems and the atmosphere. Second, it discusses how the use of eddy covariance method has grown and evolved. Today, more than 400 flux measurement sites are operating world‐wide and the duration of the time series exceed a decade at dozens of sites. Networks of tower sites now enable scientists to ask scientific questions related to climatic and ecological gradients, disturbance, changes in land use, and management. The paper ends with discussions on where the field of flux measurement is heading. Topics discussed include role of open access data sharing and data mining, in this new era of big data, and opportunities new sensors that measure a variety of trace gases, like volatile organic carbon compounds, methane and nitrous oxide, and aerosols, may yield.
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Abstract. Carbonyl sulfide (COS) flux measurements with the eddy covariance (EC) technique are becoming popular for estimating gross primary productivity. To compare COS flux measurements across sites, we need standardized protocols for data processing. In this study, we analyze how various data processing steps affect the calculated COS flux and how they differ from carbon dioxide (CO2) flux processing steps, and we provide a method for gap-filling COS fluxes. Different methods for determining the time lag between COS mixing ratio and the vertical wind velocity (w) resulted in a maximum of 15.9 % difference in the median COS flux over the whole measurement period. Due to limited COS measurement precision, small COS fluxes (below approximately 3 pmol m−2 s−1) could not be detected when the time lag was determined from maximizing the covariance between COS and w. The difference between two high-frequency spectral corrections was 2.7 % in COS flux calculations, whereas omitting the high-frequency spectral correction resulted in a 14.2 % lower median flux, and different detrending methods caused a spread of 6.2 %. Relative total uncertainty was more than 5 times higher for low COS fluxes (lower than ±3 pmol m−2 s−1) than for low CO2 fluxes (lower than ±1.5 µmol m−2 s−1), indicating a low signal-to-noise ratio of COS fluxes. Due to similarities in ecosystem COS and CO2 exchange, we recommend applying storage change flux correction and friction velocity filtering as usual in EC flux processing, but due to the low signal-to-noise ratio of COS fluxes, we recommend using CO2 data for time lag and high-frequency corrections of COS fluxes due to the higher signal-to-noise ratio of CO2 measurements.
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Direct comparison of air–sea CO2 fluxes by open-path eddy covariance (OPEC) and closed-path eddy covariance (CPEC) techniques was carried out over the equatorial Pacific Ocean. Previous studies over oceans have shown that the CO2 flux by OPEC was larger than the bulk CO2 flux using the gas transfer velocity estimated by the mass balance technique, while the CO2 flux by CPEC agreed with the bulk CO2 flux. We investigated a traditional conflict between the CO2 flux by the eddy covariance technique and the bulk CO2 flux, and whether the CO2 fluctuation attenuated using the closed-path analyser can be measured with sufficient time responses to resolve small CO2 flux over oceans. Our results showed that the closed-path analyser using a short sampling tube and a high volume air pump can be used to measure the small CO2 fluctuation over the ocean. Further, the underestimated CO2 flux by CPEC due to the attenuated fluctuation can be corrected by the bandpass covariance method; its contribution was almost identical to that of H2O flux. The CO2 flux by CPEC agreed with the total CO2 flux by OPEC with density correction; however, both of them are one order of magnitude larger than the bulk CO2 flux.
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