| 1. |
- Raivonen, Maarit, et al.
(författare)
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HIMMELI v1.0 : HelsinkI Model of MEthane buiLd-up and emIssion for peatlands
- 2017
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Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 10:12, s. 4665-4691
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Tidskriftsartikel (refereegranskat)abstract
- Wetlands are one of the most significant natural sources of methane (CH4) to the atmosphere. They emit CH4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH4, in addition to carbon dioxide (CO2). Production of CH4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH4 emissions are thus needed for upscaling observations to estimate present CH4 emissions and for producing scenarios of future atmospheric CH4 concentrations. Aiming at a CH4 model that can be added to models describing peatland carbon cycling, we composed a model called HIMMELI that describes CH4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation, and water table depth (WTD), it simulates the concentrations and transport of CH4, CO2, and oxygen (O2) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure and results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and demonstrate that HIMMELI outputs realistic fluxes by comparing modeled and measured fluxes at two peatland sites. As HIMMELI describes only the CH4-related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that (1) the model is flexible and robust and thus suitable for different environments; (2) the simulated CH4 emissions largely depend on the prescribed rate of anoxic respiration; (3) the sensitivity of the total CH4 emission to other input variables is mainly mediated via the concentrations of dissolved gases, in particular, the O2 concentrations that affect the CH4 production and oxidation rates; (4) with given input respiration, the peat column description does not significantly affect the simulated CH4 emissions in this model version.
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| 2. |
- Berchet, Antoine, et al.
(författare)
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The Community Inversion Framework v1.0 : A unified system for atmospheric inversion studies
- 2021
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Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 14:8, s. 5331-5354
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Tidskriftsartikel (refereegranskat)abstract
- Atmospheric inversion approaches are expected to play a critical role in future observation-based monitoring systems for surface fluxes of greenhouse gases (GHGs), pollutants and other trace gases. In the past decade, the research community has developed various inversion software, mainly using variational or ensemble Bayesian optimization methods, with various assumptions on uncertainty structures and prior information and with various atmospheric chemistry-Transport models. Each of them can assimilate some or all of the available observation streams for its domain area of interest: flask samples, in situ measurements or satellite observations. Although referenced in peer-reviewed publications and usually accessible across the research community, most systems are not at the level of transparency, flexibility and accessibility needed to provide the scientific community and policy makers with a comprehensive and robust view of the uncertainties associated with the inverse estimation of GHG and reactive species fluxes. Furthermore, their development, usually carried out by individual research institutes, may in the future not keep pace with the increasing scientific needs and technical possibilities. We present here the Community Inversion Framework (CIF) to help rationalize development efforts and leverage the strengths of individual inversion systems into a comprehensive framework. The CIF is primarily a programming protocol to allow various inversion bricks to be exchanged among researchers. In practice, the ensemble of bricks makes a flexible, transparent and open-source Python-based tool to estimate the fluxes of various GHGs and reactive species both at the global and regional scales. It will allow for running different atmospheric transport models, different observation streams and different data assimilation approaches. This adaptability will allow for a comprehensive assessment of uncertainty in a fully consistent framework. We present here the main structure and functionalities of the system, and we demonstrate how it operates in a simple academic case.
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| 3. |
- Bergamaschi, Peter, et al.
(författare)
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Inverse modelling of European CH4 emissions during 2006–2012 using different inverse models and reassessed atmospheric observations
- 2018
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Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7324. ; 18:2, s. 901-920
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Tidskriftsartikel (refereegranskat)abstract
- We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006–2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions. The inverse models infer total CH4 emissions of 26.8 (20.2–29.7) Tg CH4 yr−1 (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006–2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 Tg CH4 yr−1 (2006) to 18.8 Tg CH4 yr−1 (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3–8.2) Tg CH4 yr−1 from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain. Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between −40 and 20 % at the aircraft profile sites in France, Hungary and Poland.
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| 4. |
- Chadburn, Sarah E., et al.
(författare)
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Modeled Microbial Dynamics Explain the Apparent Temperature Sensitivity of Wetland Methane Emissions
- 2020
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Ingår i: Global Biogeochemical Cycles. - 0886-6236 .- 1944-9224. ; 34:11
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Tidskriftsartikel (refereegranskat)abstract
- Methane emissions from natural wetlands tend to increase with temperature and therefore may lead to a positive feedback under future climate change. However, their temperature response includes confounding factors and appears to differ on different time scales. Observed methane emissions depend strongly on temperature on a seasonal basis, but if the annual mean emissions are compared between sites, there is only a small temperature effect. We hypothesize that microbial dynamics are a major driver of the seasonal cycle and that they can explain this apparent discrepancy. We introduce a relatively simple model of methanogenic growth and dormancy into a wetland methane scheme that is used in an Earth system model. We show that this addition is sufficient to reproduce the observed seasonal dynamics of methane emissions in fully saturated wetland sites, at the same time as reproducing the annual mean emissions. We find that a more complex scheme used in recent Earth system models does not add predictive power. The sites used span a range of climatic conditions, with the majority in high latitudes. The difference in apparent temperature sensitivity seasonally versus spatially cannot be recreated by the non-microbial schemes tested. We therefore conclude that microbial dynamics are a strong candidate to be driving the seasonal cycle of wetland methane emissions. We quantify longer-term temperature sensitivity using this scheme and show that it gives approximately a 12% increase in emissions per degree of warming globally. This is in addition to any hydrological changes, which could also impact future methane emissions.
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| 5. |
- Fisher, Rebecca E., et al.
(författare)
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Measurement of the C-13 isotopic signature of methane emissions from northern European wetlands
- 2017
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Ingår i: Global Biogeochemical Cycles. - 0886-6236 .- 1944-9224. ; 31:3, s. 605-623
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Tidskriftsartikel (refereegranskat)abstract
- Isotopic data provide powerful constraints on regional and global methane emissions and their source profiles. However, inverse modeling of spatially resolved methane flux is currently constrained by a lack of information on the variability of source isotopic signatures. In this study, isotopic signatures of emissions in the Fennoscandian Arctic have been determined in chambers over wetland, in the air 0.3 to 3m above the wetland surface and by aircraft sampling from 100m above wetlands up to the stratosphere. Overall, the methane flux to atmosphere has a coherent delta C-13 isotopic signature of -71 +/- 1%, measured in situ on the ground in wetlands. This is in close agreement with delta C-13 isotopic signatures of local and regional methane increments measured by aircraft campaigns flying through air masses containing elevated methane mole fractions. In contrast, results from wetlands in Canadian boreal forest farther south gave isotopic signatures of -67 +/- 1%. Wetland emissions dominate the local methane source measured over the European Arctic in summer. Chamber measurements demonstrate a highly variable methane flux and isotopic signature, but the results from air sampling within wetland areas show that emissions mix rapidly immediately above the wetland surface and methane emissions reaching the wider atmosphere do indeed have strongly coherent C isotope signatures. The study suggests that for boreal wetlands (>60 degrees N) global and regional modeling can use an isotopic signature of -71 parts per thousand to apportion sources more accurately, but there is much need for further measurements over other wetlands regions to verify this.
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| 6. |
- Halonen, Jaana I., et al.
(författare)
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Psychological distress and sickness absence : Within- versus between-individual analysis
- 2020
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Ingår i: Journal of Affective Disorders. - : Elsevier BV. - 0165-0327 .- 1573-2517. ; 264, s. 333-339
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Tidskriftsartikel (refereegranskat)abstract
- Background: Uncertainty remains whether associations for psychological distress and sickness absence (SA) observed between and within individuals differ, and whether age, gender and work-related factors moderate these associations.Methods: We analyzed SA records of 41,184 participants of the Finnish Public Sector study with repeated survey data between 2000 and 2016 (119,024 observations). Psychological distress was measured by the General Health Questionnaire (GHQ-12), while data on SA days were from the employers' registers. We used a hybrid regression estimation approach adjusting for time-variant confounders-age, marital status, occupational class, body mass index, job contract type, months worked in the follow-up year, job demand, job control, and workplace social capital-and time-invariant gender (for between-individual analysis).Results: Higher levels of psychological distress were consistently associated with SA, both within- and between-individuals. The within-individual association (incidence rate ratio (IRR) 1.68, 95% CI 1.61-1.75 for SA at high distress), however, was substantially smaller than the between-individual association (IRR 2.53, 95% CI 2.39-2.69). High levels of psychological distress had slightly stronger within-individual associations with SA among older (>45 years) than younger employees, lower than higher occupational class, and among men than women. None of the assessed work unit related factors (e.g. job demand, job control) were consistent moderators.Limitations: These findings may not be generalizable to other working sectors or cultures with different SA policies or study populations that are male dominated.Conclusions: Focus on within-individual variation over time provides more accurate estimates of the contribution of mental health to subsequent sickness absence.
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| 7. |
- Halonen, Jaana, et al.
(författare)
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Psychotropic medication before and after disability retirement by pre-retirement perceived work-related stress
- 2020
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Ingår i: European Journal of Public Health. - : Oxford University Press (OUP). - 1101-1262 .- 1464-360X. ; 30:1, s. 158-163
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Tidskriftsartikel (refereegranskat)abstract
- Background: Retirement has been associated with improved mental health, but it is unclear how much this is due to the removal of work-related stressors. We examined rates of psychotropic medication use before and after the transition to disability retirement due to mental, musculoskeletal and other causes by pre-retirement levels of perceived work stress (effort-reward imbalance, ERI). Methods: Register-based date and diagnosis of disability retirement of 2766 participants of the Finnish Public Sector study cohort were linked to survey data on ERI, socialand health-related covariates, and to national records on prescribed reimbursed psychotropic medication, measured as defined daily doses (DDDs). Follow-up for DDDs was 2–5 years before and after disability retirement. We assessed differences in the levels of DDDs before and after retirement among those with high vs. low level of pre-retirement ERI with repeated measures regression. Results: Those with high (vs. low) levels of ERI used slightly more psychotropic medication before disability retirement due to mental disorders [rate ratio (RR) 1.14, 95% confidence intervals (CI) 0.94–1.37], but after retirement this difference attenuated (RR 0.94, 95% CI 0.80–1.10, P for interaction 0.02). Such a change was not observed for the other causes of disability retirement. Conclusions: The level of psychotropic medication use over the transition to disability retirement due to mental, but not musculoskeletal or other, causes was modified by pre-retirement perceived work-related stress. This suggests that among people retiring due to mental disorders those who had stressful jobs benefit from retirement more than those with low levels of work-related stress.
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| 8. |
- Leinonen, Ville, et al.
(författare)
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Assessment of beta-amyloid in a frontal cortical brain biopsy specimen and by positron emission tomography with carbon 11-labeled Pittsburgh Compound B.
- 2008
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Ingår i: Archives of Neurology. - : American Medical Association (AMA). - 0003-9942 .- 1538-3687. ; 65:10, s. 1304-9
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To compare carbon 11-labeled Pittsburgh Compound B ([11C]PiB) positron emission tomography (PET) findings in patients with and without Alzheimer disease lesions in frontal cortical biopsy specimens.DESIGN: Cross-sectional study of [11C]PiB PET findings in patients with or without beta-amyloid (Abeta) aggregates in frontal cortical biopsy specimens.SETTING: Two university hospitals in Finland. Patients Ten patients who had undergone intraventricular pressure monitoring with a frontal cortical biopsy (evaluated for Abeta aggregates and hyperphosphorylated tau) for suspected normal-pressure hydrocephalus.INTERVENTIONS: [11C]PiB PET and evaluation for cognitive impairment using a battery of neuropsychological tests.MAIN OUTCOME MEASURES: Immunohistochemical evaluation for Abeta aggregates and hyperphosphorylated tau in the frontal cortical biopsy specimen and [11C]PiB PET.RESULTS: In patients with Abeta aggregates in the frontal cortical biopsy specimen, PET imaging revealed higher [11C]PiB uptake (P < .05) in the frontal, parietal, and lateral temporal cortices and in the striatum as compared with the patients without frontal Abeta deposits.CONCLUSIONS: Our study supports the use of noninvasive [11C]PiB PET in the assessment of Abeta deposition in the brain. Large prospective studies are required to verify whether [11C]PiB PET will be a diagnostic aid, particularly in early Alzheimer disease.
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| 9. |
- Peltola, Olli, et al.
(författare)
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Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations
- 2019
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Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 11:3, s. 1263-1289
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Tidskriftsartikel (refereegranskat)abstract
- Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process ("bottom-up") or inversion ("top-down") models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45° N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash-Sutcliffe model efficiency D 0:47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3-41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4-39.9) or 38 (25.9-49.5) Tg(CH4) yr-1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).
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| 10. |
- Petrescu, Ana Maria Roxana, et al.
(författare)
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The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990-2017
- 2021
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Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 13:5, s. 2307-2362
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Tidskriftsartikel (refereegranskat)abstract
- Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 C UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990-2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g., anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011-2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 TgCH(4) yr (-1) (EDGAR v5.0) and 19.0 TgCH(4) yr(-1) (GAINS), consistent with the NGHGI estimates of 18.9 +/- 1.7 TgCH(4) yr(-1). The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 TgCH(4) yr(-1). Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 TgCH(4) yr(-1)) and surface network (24.4 TgCH(4) yr (-1)). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 TgCH(4) yr(-1). For N2O emissions, over the 2011-2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 TgN(2)Oyr(-1), respectively, agreeing with the NGHGI data (0.9 0.6 TgN(2)Oyr(-1)). Over the same period, the average of the three total TD global and regional inversions was 1.3 +/- 0.4 and 1.3 +/- 0.1 TgN(2)Oyr(-1), respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU CUK scale and at the national scale.
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