Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or-more generally-for the production of organic ...matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings-FPE declining with age-are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate.
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•Landfill CH4 emissions are inversely correlated with the rate of change in pressure.•Short-term effect from pressure outweigh the effect of temperature and wind speed.•Large seasonal ...but not any diurnal variability was observed in CH4 emissions.•Results from two independent CH4 quantification techniques were strongly correlated.
This study investigates temporal variability on landfill methane (CH4) emissions from an old abandoned Danish landfill, caused by the rate of changes in barometric pressure. Two different emission quantification techniques, namely the dynamic tracer dispersion method (TDM) and the eddy covariance method (EC), were applied simultaneously and their results compared. The results showed a large spatial and temporal CH4 emission variation ranging from 0 to 100 kg h−1 and 0 to 12 μmol m−2 s−1, respectively. Landfill CH4 emissions dynamics were influenced by two environmental factors: the rate of change in barometric pressure (a strong negative correlation) and wind speed (a weak positive correlation). The relationship between CH4 emissions and the rate of change in barometric pressure was more complicated than a linear one, thereby making it difficult to estimate accurately annual CH4 emissions from a landfill based on discrete measurements. Furthermore, the results did not show any clear relationship between CH4 emissions and ambient temperature. Large seasonal variations were identified by the two methods, whereas no diurnal variability was observed throughout the investigated period. CH4 fluxes measured with the EC method were strongly correlated with emissions from the TDM method, even though no direct relationship could be established, due to the different sampling ranges of the two methods and the spatial heterogeneity of CH4 emissions.
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•Empirical models were developed to estimate annual landfill methane emissions.•Oxidation efficiency was assessed by comparing emissions before and after biocover.•Biocover system ...performance highly depended on barometric pressure variations.•The average oxidation efficiency of the system was estimated between 51% and 65%.•Eddy covariance results revealed seasonal variability in the investigated biowindow.
This study investigated the performance of a passive biocover system at a Danish landfill. The overall methane oxidation efficiency of the system was assessed by comparing annual whole-site methane emissions before and after biocover installation. Annual whole-site methane emission predictions were calculated based on empirical models developed by a discrete number of tracer gas dispersion measurements. Moreover, a series of field campaigns and continuous flux measurements was carried out to evaluate the functionality of an individual biowindow. The results indicated that biocover system performance highly depended on barometric pressure variations. Under decreasing barometric pressure, estimated efficiency declined to 20%, while under increasing barometric pressure, nearly 100% oxidation was achieved. In-situ measurements on a specific biowindow showed a similar oxidation efficiency pattern in respect to barometric pressure changes despite the difference in spatial representation. Eddy covariance results revealed pronounced seasonal variability in the investigated biowindow, measuring higher methane fluxes during the cold period compared to the warm period. Results from the in-situ campaigns confirmed this finding, reporting a threefold increase in the biowindow’s methane oxidation capacity from April to May. The annual average oxidation efficiency of the system was estimated to range between 51% and 65%, taking into consideration the impact of changes in barometric pressure and seasonal variability. This indicated an annual reduction in landfill’s methane emissions between 24 and 35 tonnes. This study revealed the challenge facing current approaches in documenting accurately the performance of a passive biocover system, due to the short-term variability of oxidation efficiency, which is influenced by barometric pressure changes.
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•An empirical model was developed to estimate annual landfill methane emissions.•A non-linear model was built based on discrete emission field measurements.•The model addressed ...temporal variability induced by the rate of change in pressure.•The model predicted similar short-term emission variability as the eddy covariance.•An optimised monitoring strategy suggests when field campaigns should be performed.
An empirical model was developed and employed to estimate annual methane (CH4) emissions from two Danish landfills (Skellingsted and AV Miljø). The overall aim was to provide accurate annual CH4 emission estimates based on discrete emission field measurements and to address temporal variability caused by the impact of barometric pressure. Four non-linear regression models were developed, corresponding to the two landfills as well as to the western and eastern waste sections of AV Miljø. A comparison of model predictions with on-site eddy covariance fluxes showed that the models can accurately predict short-term emission variability. Predicted annual CH4 emissions for the Skellingsted and AV Miljø landfills were 69 ± 4 and 80 ± 4 tonnes, respectively, whereas for the western and eastern sections of the AV Miljø landfill, emissions were estimated at 63 ± 3 and 19 ± 1 tonnes, respectively. The results demonstrate that even though maximum emissions from Skellingsted were approximately threefold compared to AV Miljø, annual predicted CH4 emissions for Skellingsted were lower. This was because during the most frequently occurring pressure change events, emission rates were higher at AV Miljø in comparison to Skellingsted. An optimised sampling strategy was proposed, targeting the determination of an empirical emission model though the effective use of discrete field measurements. Analysis of annual emission estimates, based on the number of the tracer dispersion method (TDM) measurements, showed that both the number as well as the distribution of performed TDM measurements across the range of expected dP/dt influence the uncertainty.
The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) product (GPPMOD17A2) was evaluated against GPP from the eddy covariance flux measurements (GPPm) at a CO2 flux ...tower test site in a tropical rainforest in Sulawesi, Indonesia. The dynamics of 8-day GPPMOD17A2 averages generally showed similarities with observed values for the period 2004–2005 (r-value is 0.66, RMSE=1.31gCm−2d−1). However, the results revealed some underestimation of GPP by the MOD17A2 product during phases of low photosynthetic production while it overestimated GPP during phases with clear sky conditions. Obviously, these seasonal differences are caused by too large seasonal amplitudes in GPPMOD17A2. The observed inconsistencies of the GPPMOD17A2with GPPm were traced to the inputs of the MODIS GPP algorithm, including fraction of absorbed photosynthetically active radiation (fAPAR) and light use efficiency (εg). This showed that underestimation of low values is caused by several uncertainties in the MODIS fAPAR input, whereas overestimation at high irradiance is caused by the MODIS light use efficiency approach which does not account for saturation of canopy photosynthesis under clear sky conditions. The performance of the MODIS GPP algorithm has been improved through the use of a site-validated fAPAR data set and a novel approach for εg adjustment which allows for saturation of gross photosynthesis at high irradiance. Our study revealed a weakness of a commonly used light use efficiency approach to estimate global GPP at the example of a moist tropical rain forest in Indonesia and demonstrated a potential need for MOD17 enhancement.
► MODIS GPP product was evaluated at a flux tower site in a tropical rainforest. ► Uncertainties of MODIS GPP were traced to the inputs of the MODIS GPP algorithm. ► Potentials for MODIS GPP product enhancement were demonstrated. ► Alternative approach for light use efficiency adjustment was suggested. ► Consideration of canopy photosynthesis saturation improves MODIS GPP.
Gross primary productivity (GPP), the gross uptake of carbon dioxide (CO2) by plant photosynthesis, is the primary driver of the land carbon sink, which presently removes around one quarter of the ...anthropogenic CO2 emissions each year. GPP, however, cannot be measured directly and the resulting uncertainty undermines our ability to project the magnitude of the future land carbon sink. Carbonyl sulfide (COS) has been proposed as an independent proxy for GPP as it diffuses into leaves in a fashion very similar to CO2, but in contrast to the latter is generally not emitted. Here we use concurrent ecosystem‐scale flux measurements of CO2 and COS at four European biomes for a joint constraint on CO2 flux partitioning. The resulting GPP estimates generally agree with classical approaches relying exclusively on CO2 fluxes but indicate a systematic underestimation under low light conditions, demonstrating the importance of using multiple approaches for constraining present‐day GPP.
Plain Language Summary
Plants are Earth's biggest contributor for cleaning the atmosphere of carbon dioxide and remove around one quarter of the carbon dioxide emitted by humans each year. However, this contribution cannot be measured directly and has to be inferred or modelled on the basis of related parameters. This introduces large uncertainties, which in turn undermine our ability to accurately create future climate scenarios. Recent research revealed that the trace gas carbonyl sulfide is taken up by plants in a very similar way as carbon dioxide and offers us an additional way of quantifying the carbon dioxide uptake by photosynthesis. Here we use joint measurements of the carbon dioxide and carbonyl sulfide exchange to infer plant carbon dioxide uptake, demonstrating the advantage of using multiple approaches. We apply our method at four major European ecosystems and show that previous approaches, based solely on carbon dioxide, may have underestimated the plant carbon dioxide uptake.
Key Points
Traditionally gross primary productivity is inferred from ecosystem‐scale CO2 flux measurements
The proposed joint assimilation of CO2 and COS flux measurements avoids the need to specify the leaf relative uptake rate of COS a priori
The additional information content of ecosystem‐scale COS flux measurements increases inferred gross primary productivity estimates
Recent studies with closed-path eddy covariance (EC) systems have indicated that the attenuation of fluctuations of water vapor concentration is dependent upon ambient relative humidity, presumably ...due to sorption/desorption of water molecules at the interior surface of the tube. Previous studies of EC-related tube attenuation effects have either not considered this issue at all or have only examined it superficially. Nonetheless, the attenuation of water vapor fluctuations is clearly much greater than might be expected from a passive tracer in turbulent tube flow. This study reexamines the turbulent tube flow issue for both passive and sorbing tracers with the intent of developing a physically-based semi-empirical model that describes the attenuation associated with water vapor fluctuations. Toward this end, we develop a new model of tube flow dynamics (radial profiles of the turbulent diffusivity and tube airstream velocity). We compare our new passive-tracer formulation with previous formulations in a systematic and unified way in order to assess how sensitive the passive-tracer results depend on fundamental modeling assumptions. We extend the passive tracer model to the vapor sorption/desorption case by formulating the model's wall boundary condition in terms of a physically-based semi-empirical model of the sorption/desorption vapor fluxes. Finally we synthesize all modeling and observational results into a single analytical expression that captures the effects of the mean ambient humidity and tube flow (Reynolds number) on tube attenuation.
Commercially available fast-response analysers for methane (CH
) and nitrous oxide (N
O) have recently become more sensitive, more robust and easier to operate. This has made their application for ...long-term flux measurements with the eddy-covariance method more feasible. Unlike for carbon dioxide (CO
) and water vapour (H
O), there have so far been no guidelines on how to optimise and standardise the measurements. This paper reviews the state-of-the-art of the various steps of the measurements and discusses aspects such as instrument selection, setup and maintenance, data processing as well as the additional measurements needed to aid interpretation and gap-filling. It presents the methodological protocol for eddy covariance measurements of CH
and N
O fluxes as agreed for the ecosystem station network of the pan-European Research Infrastructure Integrated Carbon Observation System and provides a first international standard that is suggested to be adopted more widely. Fluxes can be episodic and the processes controlling the fluxes are complex, preventing simple mechanistic gap-filling strategies. Fluxes are often near or below the detection limit, requiring additional care during data processing. The protocol sets out the best practice for these conditions to avoid biasing the results and long-term budgets. It summarises the current approach to gap-filling.
•Full uncertainty analysis of carbon fluxes and stock changes in a forest.•Novel empirical analysis of site heterogeneity effects on turbulent CO2 flux.•New data published on soil respiration, litter ...production and tree growth.•Multi constraints approach to evaluate consistency of carbon budget data.•Synthesis on carbon cycling in a long-term CO2 flux forest site.
A synthesis of five years (2006–2010) of data on carbon cycling in a temperate deciduous forest, Sorø (Zealand, Denmark) was performed by combining all available data from eddy covariance, chamber, suction cups, and biometric measurements. The net ecosystem exchange of CO2 (NEE), soil respiration, tree growth, litter production and leaching of dissolved inorganic and organic carbon were independently estimated and used to calculate other unmeasured ecosystem carbon budget (ECB) components, based on mass balance equations. This provided a complete assessment of the carbon storage and allocation within the ecosystem. The results showed that this temperate deciduous forest was a moderate carbon sink (258±41gCm−2 yr−1) with both high rates of gross primary production (GPP, 1881±95gCm−2 yr−1) and ecosystem respiration (Re, 1624±197gCm−2 yr−1). Approximately 62% of the gross assimilated carbon was respired by the living plants, while 21% was contributed to the soil as litter production, the latter balancing the total heterotrophic respiration. The remaining 17% were either stored in the plants (mainly as aboveground biomass) or removed from the system as wood yield. The soil organic carbon stock was considered unchanged over the period of observation, given the high degree of uncertainty associated with the small loss detected (33±85gCm−2 yr−1). The ECB component data were generally consistent, except for one of the derived fluxes, the aboveground autotrophic respiration, which appeared to be higher than expected. The potential causes for this, i.e. underestimation of soil respiration and/or overestimation of Re are discussed. The plausibility analyses reported here, using multiple ECB data sets together with simple mass conservation equations and the evaluation of data consistency on the basis of the estimated residual terms is widely applicable to other experimental sites, even when some of the carbon fluxes and stock changes are not measured independently.
Abstract
Concentrations of atmospheric carbon dioxide (CO
2
) have continued to increase whereas atmospheric deposition of sulphur and nitrogen has declined in Europe and the USA during recent ...decades. Using time series of flux observations from 23 forests distributed throughout Europe and the USA, and generalised mixed models, we found that forest-level net ecosystem production and gross primary production have increased by 1% annually from 1995 to 2011. Statistical models indicated that increasing atmospheric CO
2
was the most important factor driving the increasing strength of carbon sinks in these forests. We also found that the reduction of sulphur deposition in Europe and the USA lead to higher recovery in ecosystem respiration than in gross primary production, thus limiting the increase of carbon sequestration. By contrast, trends in climate and nitrogen deposition did not significantly contribute to changing carbon fluxes during the studied period. Our findings support the hypothesis of a general CO
2
-fertilization effect on vegetation growth and suggest that, so far unknown, sulphur deposition plays a significant role in the carbon balance of forests in industrialized regions. Our results show the need to include the effects of changing atmospheric composition, beyond CO
2
, to assess future dynamics of carbon-climate feedbacks not currently considered in earth system/climate modelling.
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