42 research outputs found
UV-säteilyn aiheuttamat reaktiivisten typpiyhdisteiden emissiot männyn oksien kaasunvaihtoa mittaavissa kammioissa: niiden alkuperä ja merkitys
No full textVäitöskirjaselosteSeloste väitöskirjasta: Raivonen, M. 2008. UV-induced Noy emissions in gas-exchange chambers enclosing Scots pine shoots: an analysis on their origin and significance. Dissertationes Forestales 71
Kastelu, lämpösumma ja lannoitus nykyaikaisessa puutarhatuotannossa ja tietokoneen käyttö mallien hallinnassa
No full textvokSaatavana MTT puutarhatuotannost
Importance of vegetation classes in modeling CH4 emissions from boreal and subarctic wetlands in Finland
No full textBoreal/arctic wetlands are dominated by diverse plant species, which vary in their contribution to CH4 production, oxidation and transport processes. Earlier studies have often lumped the processes all together, which may induce large uncertainties into the results. We present a novel model, which includes three vegetation classes and can be used to simulate CH4 emissions from boreal and arctic treeless wetlands. The model is based on an earlier biogeophysical model, CH4MOD(wetland). We grouped the vegetation as graminoids, shrubs and Sphagnum and recalibrated the vegetation parameters according to their different CH4 production, oxidation and transport capacities. Then, we used eddy-covariance-based CH4 flux observations from a boreal (Siikaneva) and a subarctic fen (Lompolojaka) in Finland to validate the model. The results showed that the recalibrated model could generally simulate the seasonal patterns of the Finnish wetlands with different plant communities. The comparison between the simulated andmeasured daily CH4 fluxes resulted in a correlation coefficient (R-2) of 0.82 with a slope of 1.0 and an intercept of -0.1 mg m(-2) h(-1) for the Siikaneva site (n = 2249, p < 0.001) and an R-2 of 0.82 with a slope of 1.0 and an intercept of 0.0 mg m(-2) h(-1) for the Lompolojankka site (n = 1826, p < 0.001). Compared with the original model, the recalibrated model in this study significantly improved the model efficiency (EF), from - 5.5 to 0.8 at the Siikaneva site and from -0.4 to 0.8 at the Lompolojankka site. The simulated annual CH4 emissions ranged from 7 to 24 gm(-2) yr(-1), which was consistent with the observations (7-22 gm(-2) yr(-1)). However, there are some discrepancies between the simulated and observed daily CH4 fluxes for the Siikaneva site (RMSE = 50.0%) and the Lompolojankka site (RMSE = 47.9%). Model sensitivity analysis showed that increasing the proportion of the graminoids would significantly increase the CH4 emission levels. Our study demonstrated that the parameterization of the different vegetation processes was important in estimating long-term wetland CH4 emissions. (C) 2016 Elsevier B.V. All rights reserved
Technical note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models
No full textEmission via bubbling, i.e. ebullition, is one of the main methane (CH4)
emission pathways from wetlands to the atmosphere. Direct measurement of gas
bubble formation, growth and release in the peat–water matrix is challenging
and in consequence these processes are relatively unknown and are coarsely
represented in current wetland CH4 emission models. In this study we
aimed to evaluate three ebullition modelling approaches and their effect on
model performance. This was achieved by implementing the three approaches in
one process-based CH4 emission model. All the approaches were based on
some kind of threshold: either on CH4 pore water concentration (ECT),
pressure (EPT) or free-phase gas volume (EBG) threshold. The model was run
using 4 years of data from a boreal sedge fen and the results were
compared with eddy covariance measurements of CH4 fluxes.Modelled annual CH4 emissions were largely unaffected by the different
ebullition modelling approaches; however, temporal variability in CH4
emissions varied an order of magnitude between the approaches. Hence the
ebullition modelling approach drives the temporal variability in modelled
CH4 emissions and therefore significantly impacts, for instance,
high-frequency (daily scale) model comparison and calibration against
measurements. The modelling approach based on the most recent knowledge of
the ebullition process (volume threshold, EBG) agreed the best with the
measured fluxes (R2 = 0.63) and hence produced the most reasonable
results, although there was a scale mismatch between the measurements
(ecosystem scale with heterogeneous ebullition locations) and model results
(single horizontally homogeneous peat column). The approach should be
favoured over the two other more widely used ebullition modelling approaches
and researchers are encouraged to implement it into their CH4 emission
models
Role of needle surface waxes in dynamic exchange of mono- and sesquiterpenes
No full textBiogenic volatile organic compounds (BVOCs) produced by plants have a major role in atmospheric chemistry. The different physicochemical properties of BVOCs affect their transport within and out of the plant as well as their reactions along the way. Some of these compounds may accumulate in or on the waxy surface layer of conifer needles and participate in chemical reactions on or near the foliage surface. The aim of this work was to determine whether terpenes, a key category of BVOCs produced by trees, can be found on the epicuticles of Scots pine (Pinus sylvestris L.) and, if so, how they compare with the terpenes found in shoot emissions of the same tree. We measured shoot-level emissions of pine seedlings at a remote outdoor location in central Finland and subsequently analysed the needle surface waxes for the same compounds. Both emissions and wax extracts were clearly dominated by monoterpenes, but the proportion of sesquiterpenes was higher in the wax extracts. There were also differences in the terpene spectra of the emissions and the wax extracts. The results, therefore, support the existence of BVOC associated to the epicuticular waxes. We briefly discuss the different pathways for terpenes to reach the needle surfaces and the implications for air chemistry.Peer reviewe
Towards an intergrated, optimisation approach tot assess NEE and its spatial variability in Amazonian landscapes.
No full textMeasuring shoot-level NOx flux in field conditions: the role of blank chambers
No full textWe monitored NOx fluxes in an empty chamber and in chambers containing Scots pine shoots. Our aims were to observe how the chamber blank behaves in non-controlled field conditions and at low ambient NOx concentrations, to find ways of reducing deleterious wall effects, and to evolve a method for a blank correction. We found that solar ultraviolet radiation induced NOx emission from the chamber walls. Comparisons between blanks of several chambers showed that the chambers were not identical. We therefore recommend that a separate blank chamber will be monitored together with the branch chambers in long-term field measurements. At regular time intervals, all of the chambers should be measured simultaneously while empty and the regression between the UV irradiance and NOx flux determined for each chamber. In case the chambers differ from each other, the blank could be corrected with the UV-regression coefficients obtained
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
No full textThe processes responsible for methane (CH4) emissions from boreal wetlands are complex; hence, their model representation is complicated by a large number of parameters and parameter uncertainties. The arctic-enabled dynamic global vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) is one such model that allows quantification and understanding of the natural wetland CH4 fluxes at various scales, ranging from local to regional and global, but with several uncertainties. The model contains detailed descriptions of the CH4 production, oxidation, and transport controlled by several process parameters. Complexities in the underlying environmental processes, warming-driven alternative paths of meteorological phenomena, and changes in hydrological and vegetation conditions highlight the need for a calibrated and optimised version of LPJ-GUESS. In this study, we formulated the parameter calibration as a Bayesian problem, using knowledge of reasonable parameters values as priors. We then used an adaptive Metropolis-Hastings (MH)-based Markov chain Monte Carlo (MCMC) algorithm to improve predictions of CH4 emission by LPJ-GUESS and to quantify uncertainties. Application of this method on uncertain parameters allows for a greater search of their posterior distribution, leading to a more complete characterisation of the posterior distribution with a reduced risk of the sample impoverishment that can occur when using other optimisation methods. For assimilation, the analysis used flux measurement data gathered during the period from 2005 to 2014 from the Siikaneva wetlands in Southern Finland with an estimation of measurement uncertainties. The data are used to constrain the processes behind the CH4 dynamics, and the posterior covariance structures are used to explain how the parameters and the processes are related. To further support the conclusions, the CH4 flux and the other component fluxes associated with the flux are examined. The results demonstrate the robustness of MCMC methods to quantitatively assess the interrelationship between objective function choices, parameter identifiability, and data support. The experiment using real observations from Siikaneva resulted in a reduction in the root-mean-square error (RMSE), from 0.044 to 0.023 gC m-2 d-1, and a 93.89 % reduction in the cost function value. As a part of this work, knowledge about how CH4 data can constrain the parameters and processes is derived. Although the optimisation is performed based on a single site's flux data from Siikaneva, the algorithm is useful for larger-scale multi-site studies for a more robust calibration of LPJ-GUESS and similar models, and the results can highlight where model improvements are needed.Peer reviewe
