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Sökning: WFRF:(Rinne Janne)

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1.
  • Junninen, Heikki, et al. (författare)
  • Terpene emissions from boreal wetlands can initiate stronger atmospheric new particle formation than boreal forests
  • 2022
  • Ingår i: Communications Earth and Environment. - : Springer Science and Business Media LLC. - 2662-4435. ; 3:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Aerosols and their interaction with clouds constitute the largest uncertainty in estimating the radiative forcing affecting the climate system. Secondary aerosol formation is responsible for a large fraction of the cloud condensation nuclei in the global atmosphere. Wetlands are important to the budgets of methane and carbon dioxide, but the potential role of wetlands in aerosol formation has not been investigated. Here we use direct atmospheric sampling at the Siikaneva wetland in Finland to investigate the emission of methane and volatile organic compounds, and subsequently formed atmospheric clusters and aerosols. We find that terpenes initiate stronger atmospheric new particle formation than is typically observed over boreal forests and that, in addition to large emissions of methane which cause a warming effect, wetlands also have a cooling effect through emissions of these terpenes. We suggest that new wetlands produced by melting permafrost need to be taken into consideration as sources of secondary aerosol particles when estimating the role of increasing wetland extent in future climate change.
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2.
  • Wachiye, Sheila, et al. (författare)
  • Effects of livestock and wildlife grazing intensity on soil carbon dioxide flux in the savanna grassland of Kenya
  • 2022
  • Ingår i: Agriculture, Ecosystems and Environment. - : Elsevier BV. - 0167-8809. ; 325
  • Tidskriftsartikel (refereegranskat)abstract
    • Although grazing is the primary land use in the savanna lowland of southern Kenya, the effects of grazing on soil carbon dioxide flux (RS) remain unclear. A 12-month study was conducted from January to December 2020 on the effects of six grazing intensities sites (overgrazed (OG), heavily grazed (HG), moderately grazed (MG), moderately to lightly grazed (M-LG), lightly grazed (LG) and no grazing (NG)) on RS on. A camera trap was used to monitor the total number of animals at each site, indicating the grazing intensity. Weekly measurements of RS were taken using static greenhouse gas chambers along with simultaneous measurements of soil temperature (TS) and volumetric soil water content (WS) (depth of 5 cm). Mean RS at HG, MG, M-LG and LG sites was approximately 15–25% higher than at NG and OG sites (p < 0.001). Mean WS increased with decrease in grazing especially in the dry season, while TS increased with increase in grazing. We observed bimodal temporal variation in RS and WS due to two wet seasons in the year. Thus, variation in RS across the study period followed the changes in WS rather than those in TS. Mean values of RS in the wet seasons were significantly higher (> 45%) than those in the dry seasons, and WS accounted for 71% of the temporal variability in RS (p < 0.05). In addition, the enhanced vegetation index (EVI, interpreted as a proxy for vegetation cover) explained 60% of the variance of RS, and WS and EVI together explained 75%. EVI showed a negative relationship (p < 0.05) with animal intensity, indicating that more grazing reduced vegetation cover and, consequently, soil organic carbon and biomass. Soil bulk density was lower at less grazed sites. While RS variability was unaffected by total nitrogen content, pH, and texture, correspondence analysis demonstrated that the main factors influencing RS dynamics across the year under different grazing intensities were WS and vegetation cover. Our results contribute to closing the existing knowledge gap regarding the effects of grazing intensity on RS in East Africa savannas. Therefore, this information is of great importance in understanding carbon cycling in savanna grassland, as well as the identification of the potential consequences of increasing land pressure caused by rising livestock numbers, and will assist in the development of climate-smart livestock management in East Africa.
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3.
  • Wachiye, Sheila, et al. (författare)
  • Soil greenhouse gas emissions from a sisal chronosequence in Kenya
  • 2021
  • Ingår i: Agricultural and Forest Meteorology. - : Elsevier BV. - 1873-2240 .- 0168-1923. ; 307
  • Tidskriftsartikel (refereegranskat)abstract
    • Sisal (Agave sisalana) is a climate-resilient crop grown on large-scale farms in semi-arid areas. However, no studies have investigated soil greenhouse gas (GHGs: CO2, N2O and CH4) fluxes from these plantations and how they relate to other land cover types. We examined GHG fluxes (Fs) in a sisal chronosequence at Teita Sisal Estatein southern Kenya. The effects of stand age on Fs were examined using static GHG chambers and gas chromatography for a period of one year in seven stands: young stands aged 1–3 years, mature stands aged 7–8 years, and old stands aged 13–14 years. Adjacent bushland served as a control site representing the surrounding land use type. Mean CO₂ fluxes were highest in the oldest stand (56 ± 3 mg C m-2 h-1) and lowest in the 8-year old stand (38 ± 3 mg C m-2 h-1), which we attribute to difference in root respiration between the stand. All stands had 13–28% higher CO₂ fluxes than bushland (32 ± 3 mg C m-2 h-1). CO2 fluxes in the wet season were about 70% higher than dry season across all sites. They were influenced by soil water content (WS) and vegetation phenology. Mean N2O fluxes were very low (<5 μg N m-2 h-1) in all sites due to low soil nitrogen (N) content. About 89% of CH4 fluxes were below the detection limit (LOD ± 0.02 mg C m-2 h-1). Our results imply that sisalplantations have higher soil CO2 emissions than the surrounding land use type, and the seasonal emissions were largely driven by WS and the vegetation status. Methane and nitrous oxide are of minor importance. Thus, soil GHG fluxes from sisal plantations are a minor contributor to agricultural GHG emissions in Kenya.
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5.
  • Cai, Zhanzhang, et al. (författare)
  • Modelling Daily Gross Primary Productivity with Sentinel-2 Data in the Nordic Region-Comparison with Data from MODIS
  • 2021
  • Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 13:3
  • Tidskriftsartikel (refereegranskat)abstract
    • The high-resolution Sentinel-2 data potentially enable the estimation of gross primary productivity (GPP) at finer spatial resolution by better capturing the spatial variation in a heterogeneous landscapes. This study investigates the potential of 10 m resolution reflectance from the Sentinel-2 Multispectral Instrument to improve the accuracy of GPP estimation across Nordic vegetation types, compared with the 250 m and 500 m resolution reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). We applied linear regression models with inputs of two-band enhanced vegetation index (EVI2) derived from Sentinel-2 and MODIS reflectance, respectively, together with various environmental drivers to estimate daily GPP at eight Nordic eddy covariance (EC) flux tower sites. Compared with the GPP from EC measurements, the accuracies of modelled GPP were generally high (R-2 = 0.84 for Sentinel-2; R-2 = 0.83 for MODIS), and the differences between Sentinel-2 and MODIS were minimal. This demonstrates the general consistency in GPP estimates based on the two satellite sensor systems at the Nordic regional scale. On the other hand, the model accuracy did not improve by using the higher spatial-resolution Sentinel-2 data. More analyses of different model formulations, more tests of remotely sensed indices and biophysical parameters, and analyses across a wider range of geographical locations and times will be required to achieve improved GPP estimations from Sentinel-2 satellite data.
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6.
  • Chang, Kuang Yu, et al. (författare)
  • Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions
  • 2021
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1, s. 2266-2266
  • Tidskriftsartikel (refereegranskat)abstract
    • Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.
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7.
  • Heiskanen, Jouni, et al. (författare)
  • The Integrated Carbon Observation System in Europe
  • 2022
  • Ingår i: Bulletin of the American Meteorological Society. - 0003-0007. ; 103:3, s. 855-872
  • Tidskriftsartikel (refereegranskat)abstract
    • Since 1750, land-use change and fossil fuel combustion has led to a 46% increase in the atmospheric carbon dioxide (CO2) concentrations, causing global warming with substantial societal consequences. The Paris Agreement aims to limit global temperature increases to well below 2C above preindustrial levels. Increasing levels of CO2 and other greenhouse gases (GHGs), such as methane (CH4) and nitrous oxide (N2O), in the atmosphere are the primary cause of climate change. Approximately half of the carbon emissions to the atmosphere are sequestered by ocean and land sinks, leading to ocean acidification but also slowing the rate of global warming. However, there are significant uncertainties in the future global warming scenarios due to uncertainties in the size, nature, and stability of these sinks. Quantifying and monitoring the size and timing of natural sinks and the impact of climate change on ecosystems are important information to guide policy-makers' decisions and strategies on reductions in emissions. Continuous, long-term observations are required to quantify GHG emissions, sinks, and their impacts on Earth systems. The Integrated Carbon Observation System (ICOS) was designed as the European in situ observation and information system to support science and society in their efforts to mitigate climate change. It provides standardized and open data currently from over 140 measurement stations across 12 European countries. The stations observe GHG concentrations in the atmosphere and carbon and GHG fluxes between the atmosphere, land surface, and the oceans. This article describes how ICOS fulfills its mission to harmonize these observations, ensure the related long-term financial commitments, provide easy access to well-documented and reproducible high-quality data and related protocols and tools for scientific studies, and deliver information and GHG-related products to stakeholders in society and policy.
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8.
  • Jaars, Kerneels, et al. (författare)
  • Measurements of biogenic volatile organic compounds at a grazed savannah grassland agricultural landscape in South Africa
  • 2016
  • Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 16:24, s. 15665-15688
  • Tidskriftsartikel (refereegranskat)abstract
    • Biogenic volatile organic compounds (BVOCs) play an important role in the chemistry of the troposphere, especially in the formation of tropospheric ozone (O3) and secondary organic aerosols (SOA). Ecosystems produce and emit a large number of BVOCs. It is estimated on a global scale that approximately 90% of annual BVOC emissions are from terrestrial sources. In this study, measurements of BVOCs were conducted at the Welgegund measurement station (South Africa), which is considered to be a regionally representative background site situated in savannah grasslands. Very few BVOC measurements exist for savannah grasslands and results presented in this study are the most extensive for this type of landscape. Samples were collected twice a week for 2h during the daytime and 2h during the night-time through two long-term sampling campaigns from February 2011 to February 2012 and from December 2013 to February 2015, respectively. Individual BVOCs were identified and quantified using a thermal desorption instrument, which was connected to a gas chromatograph and a mass selective detector. The annual median concentrations of isoprene, 2-methyl-3-butene-2-ol (MBO), monoterpene and sesquiterpene (SQT) during the first campaign were 14, 7, 120 and 8pptv, respectively, and 14, 4, 83 and 4pptv, respectively, during the second campaign. The sum of the concentrations of the monoterpenes were at least an order of magnitude higher than the concentrations of other BVOC species during both sampling campaigns, with α-pinene being the most abundant species. The highest BVOC concentrations were observed during the wet season and elevated soil moisture was associated with increased BVOC concentrations. However, comparisons with measurements conducted at other landscapes in southern Africa and the rest of the world that have more woody vegetation indicated that BVOC concentrations were, in general, significantly lower for savannah grasslands. Furthermore, BVOC concentrations were an order of magnitude lower compared to total aromatic concentrations measured at Welgegund. An analysis of concentrations by wind direction indicated that isoprene concentrations were higher from the western sector that is considered to be a relatively clean regional background region with no large anthropogenic point sources, while wind direction did not indicate any significant differences in the concentrations of the other BVOC species. Statistical analysis indicated that soil moisture had the most significant impact on atmospheric levels of MBO, monoterpene and SQT concentrations, whereas temperature had the greatest influence on isoprene levels. The combined O3 formation potentials of all the BVOCs measured calculated with maximum incremental reactivity (MIR) coefficients during the first and second campaign were 1162 and 1022pptv, respectively. α-Pinene and limonene had the highest reaction rates with O3, whereas isoprene exhibited relatively small contributions to O3 depletion. Limonene, α-pinene and terpinolene had the largest contributions to the OH reactivity of BVOCs measured at Welgegund for all of the months during both sampling campaigns.
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9.
  • Junttila, Sofia, et al. (författare)
  • Upscaling Northern Peatland CO2 Fluxes Using Satellite Remote Sensing Data
  • 2021
  • Ingår i: Remote Sensing. - : MDPI AG. - 2072-4292. ; 13:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Peatlands play an important role in the global carbon cycle as they contain a large soil carbon stock. However, current climate change could potentially shift peatlands from being carbon sinks to carbon sources. Remote sensing methods provide an opportunity to monitor carbon dioxide (CO2) exchange in peatland ecosystems at large scales under these changing conditions. In this study, we developed empirical models of the CO2 balance (net ecosystem exchange, NEE), gross primary production (GPP), and ecosystem respiration (ER) that could be used for upscaling CO2 fluxes with remotely sensed data. Two to three years of eddy covariance (EC) data from five peatlands in Sweden and Finland were compared to modelled NEE, GPP and ER based on vegetation indices from 10 m resolution Sentinel-2 MSI and land surface temperature from 1 km resolution MODIS data. To ensure a precise match between the EC data and the Sentinel-2 observations, a footprint model was applied to derive footprint-weighted daily means of the vegetation indices. Average model parameters for all sites were acquired with a leave-one-out-cross-validation procedure. Both the GPP and the ER models gave high agreement with the EC-derived fluxes (R-2 = 0.70 and 0.56, NRMSE = 14% and 15%, respectively). The performance of the NEE model was weaker (average R-2 = 0.36 and NRMSE = 13%). Our findings demonstrate that using optical and thermal satellite sensor data is a feasible method for upscaling the GPP and ER of northern boreal peatlands, although further studies are needed to investigate the sources of the unexplained spatial and temporal variation of the CO2 fluxes.
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10.
  • Kallingal, Jalisha T., et al. (författare)
  • Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
  • 2024
  • Ingår i: Geoscientific Model Development. - 1991-959X. ; 17:6, s. 2299-2324
  • Tidskriftsartikel (refereegranskat)abstract
    • The 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.
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