| 1. |
- Petrescu, Ana Maria Roxana, et al.
(författare)
-
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990-2017
- 2021
-
Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 13:5, s. 2307-2362
-
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.
|
|
| 2. |
- Petrescu, Ana Maria Roxana, et al.
(författare)
-
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990-2019
- 2023
-
Ingår i: Earth System Science Data. - : COPERNICUS GESELLSCHAFT MBH. - 1866-3508 .- 1866-3516. ; 15:3, s. 1197-1268
-
Tidskriftsartikel (refereegranskat)abstract
- Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990-2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015-2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 TgCH(4) yr(-1) (EDGARv6.0, last year 2018) and 18.4 TgCH(4) yr(-1) (GAINS, last year 2015), close to the NGHGI estimates of 17 :5 +/- 2 :1 TgCH(4) yr(-1). TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 TgCH(4) yr(-1). Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 TgCH(4) yr(-1) inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH-HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 TgCH(4) yr(-1). For N2O emissions, over the 2015-2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 TgN(2)Oyr(-1), close to the NGHGI data (0 :8 +/- 55% TgN(2)Oyr(-1)). Over the same period, the mean of TD global and regional inversions was 1.4 TgN(2)Oyr(-1) (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 C UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs. The referenced dataset srelated to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023).
|
|
| 3. |
- Pulliainen, Jouni, et al.
(författare)
-
Early snowmelt significantly enhances boreal springtime carbon uptake
- 2017
-
Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424. ; 114:42, s. 11081-11086
-
Tidskriftsartikel (refereegranskat)abstract
- We determine the annual timing of spring recovery from spaceborne microwave radiometer observations across northern hemisphere boreal evergreen forests for 1979–2014. We find a trend of advanced spring recovery of carbon uptake for this period, with a total average shift of 8.1 d (2.3 d/decade). We use this trend to estimate the corresponding changes in gross primary production (GPP) by applying in situ carbon flux observations. Micrometeoro-logical CO2 measurements at four sites in northern Europe and North America indicate that such an advance in spring recovery would have increased the January–June GPP sum by 29 g·C·m−2 [8.4 g·C·m−2 (3.7%)/decade]. We find this sensitivity of the measured springtime GPP to the spring recovery to be in accordance with the corresponding sensitivity derived from simulations with a land ecosystem model coupled to a global circulation model. The model-predicted increase in springtime cumulative GPP was 0.035 Pg/decade [15.5 g·C·m−2 (6.8%)/decade] for Eurasian forests and 0.017 Pg/decade for forests in North America [9.8 g·C·m−2 (4.4%)/decade]. This change in the springtime sum of GPP related to the timing of spring snowmelt is quantified here for boreal evergreen forests.
|
|
| 4. |
- Raivonen, Maarit, et al.
(författare)
-
HIMMELI v1.0 : HelsinkI Model of MEthane buiLd-up and emIssion for peatlands
- 2017
-
Ingår i: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 10:12, s. 4665-4691
-
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.
|
|
| 5. |
- Zhang, Zhen, et al.
(författare)
-
Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH4 Sites Using Wavelet Analyses
- 2023
-
Ingår i: Journal of Geophysical Research: Biogeosciences. - 2169-8953. ; 128:11
-
Tidskriftsartikel (refereegranskat)abstract
- Process-based land surface models are important tools for estimating global wetland methane (CH4) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH4 fluxes (FCH4) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH4 production). Our evaluation suggests the need to accurately replicate FCH4 variability, especially at short time scales, in future wetland CH4 model developments.
|
|
