Carbon sequestration in agricultural soils as potential climate change mitigation strategy for Germany

2021 ◽  
Author(s):  
Christian Dold ◽  
Herbst Michael ◽  
Weihermüller Lutz ◽  
Vereecken Harry
Keyword(s):  
Carbon Sequestration ◽  
Organic Carbon ◽  
Carbon Storage ◽  
Agricultural Soils ◽  
Mitigation Strategy ◽  
Surface Model ◽  
Climate Projections ◽  
Preliminary Results ◽  
Community Land Model ◽  
The Impact

<p>The limitation of global warming to +1.5°C compared to preindustrial levels requires net-zero CO<sub>2</sub> emissions globally by mid-century and substantial removal of CO<sub>2</sub> thereafter. Carbon sequestration in agricultural soils has been proposed as a potential mitigation strategy. Aim of this study is to quantify current carbon storage and emission reduction potential in agricultural soils, and assess the impact of mitigation measures in a prognostic modeling approach. The land surface model Community Land Model 5.0 (CLM) is used to assess soil carbon changes in agricultural soils in Germany. The simulation domain was set up with an 8 x 8 km grid across Germany using recent land use and soil texture maps, and parameters for major field crops. The model was spun up for ~1500 years with a 30-year climate dataset. Preliminary results show that spinup-derived organic carbon density (OCD, 0-188 cm) was significantly related to Soil Grid v2 OCD (R<sup>2</sup> = 0.82), but only weakly related to field-measured OCD (R<sup>2</sup> = 0.21). The simulated OCD values in the upper 32 cm soil layer were lower in Northwestern Germany compared to Soil Grids. This is probably due to the intensive use of organic amendment application in the region, and CLM5 lacks a subroutine for simulating organic carbon application. In a next step, carbon storage for different climate projections (regional EUR11 RCP2.6 and RCP8.5 scenarios) and management systems from 2020 - 2100 will be investigated. We will present preliminary results and discuss improvements of CLM5 to better represent agricultural soils.</p>

scholarly journals Large but decreasing effect of ozone on the European carbon sink

2018 ◽  
Vol 15 (13) ◽  
pp. 4245-4269 ◽  
Author(s):  
Rebecca J. Oliver ◽  
Lina M. Mercado ◽  
Stephen Sitch ◽  
David Simpson ◽  
Belinda E. Medlyn ◽  
...  
Keyword(s):  
Carbon Storage ◽  
Primary Productivity ◽  
Carbon Sink ◽  
Spatial Scales ◽  
Stomatal Closure ◽  
Regional Scale ◽  
Surface Model ◽  
Background Concentrations ◽  
Tropospheric O3 ◽  
The Impact

Abstract. The capacity of the terrestrial biosphere to sequester carbon and mitigate climate change is governed by the ability of vegetation to remove emissions of CO2 through photosynthesis. Tropospheric O3, a globally abundant and potent greenhouse gas, is, however, known to damage plants, causing reductions in primary productivity. Despite emission control policies across Europe, background concentrations of tropospheric O3 have risen significantly over the last decades due to hemispheric-scale increases in O3 and its precursors. Therefore, plants are exposed to increasing background concentrations, at levels currently causing chronic damage. Studying the impact of O3 on European vegetation at the regional scale is important for gaining greater understanding of the impact of O3 on the land carbon sink at large spatial scales. In this work we take a regional approach and update the JULES land surface model using new measurements specifically for European vegetation. Given the importance of stomatal conductance in determining the flux of O3 into plants, we implement an alternative stomatal closure parameterisation and account for diurnal variations in O3 concentration in our simulations. We conduct our analysis specifically for the European region to quantify the impact of the interactive effects of tropospheric O3 and CO2 on gross primary productivity (GPP) and land carbon storage across Europe. A factorial set of model experiments showed that tropospheric O3 can suppress terrestrial carbon uptake across Europe over the period 1901 to 2050. By 2050, simulated GPP was reduced by 4 to 9 % due to plant O3 damage and land carbon storage was reduced by 3 to 7 %. The combined physiological effects of elevated future CO2 (acting to reduce stomatal opening) and reductions in O3 concentrations resulted in reduced O3 damage in the future. This alleviation of O3 damage by CO2-induced stomatal closure was around 1 to 2 % for both land carbon and GPP, depending on plant sensitivity to O3. Reduced land carbon storage resulted from diminished soil carbon stocks consistent with the reduction in GPP. Regional variations are identified with larger impacts shown for temperate Europe (GPP reduced by 10 to 20 %) compared to boreal regions (GPP reduced by 2 to 8 %). These results highlight that O3 damage needs to be considered when predicting GPP and land carbon, and that the effects of O3 on plant physiology need to be considered in regional land carbon cycle assessments.

scholarly journals The role of clay content and mineral surface area for soil organic carbon storage in an arable toposequence

2021 ◽  
Author(s):  
Steffen A. Schweizer ◽  
Carsten W. Mueller ◽  
Carmen Höschen ◽  
Pavel Ivanov ◽  
Ingrid Kögel-Knabner
Keyword(s):  
Organic Carbon ◽  
Surface Area ◽  
Agricultural Soils ◽  
Mineral Soil ◽  
Clay Content ◽  
Clay Soils ◽  
Mineral Surface ◽  
Mineral Surface Area ◽  
The Impact

AbstractCorrelations between organic carbon (OC) and fine mineral particles corroborate the important role of the abundance of soil minerals with reactive surfaces to bind and increase the persistence of organic matter (OM). The storage of OM broadly consists of particulate and mineral-associated forms. Correlative studies on the impact of fine mineral soil particles on OM storage mostly combined data from differing sites potentially confounded by other environmental factors. Here, we analyzed OM storage in a soil clay content gradient of 5–37% with similar farm management and mineral composition. Throughout the clay gradient, soils contained 14 mg OC g−1 on average in the bulk soil without showing any systematic increase. Density fractionation revealed that a greater proportion of OC was stored as occluded particulate OM in the high clay soils (18–37% clay). In low clay soils (5–18% clay), the fine mineral-associated fractions had up to two times higher OC contents than high clay soils. Specific surface area measurements revealed that more mineral-associated OM was related to higher OC loading. This suggests that there is a potentially thicker accrual of more OM at the same mineral surface area within fine fractions of the low clay soils. With increasing clay content, OM storage forms contained more particulate OC and mineral-associated OC with a lower surface loading. This implies that fine mineral-associated OC storage in the studied agricultural soils was driven by thicker accrual of OM and decoupled from clay content limitations.

scholarly journals Estimation of the Value of Ecosystem Carbon Sequestration Services under Different Scenarios in the Central China (the Qinling-Daba Mountain Area)

2019 ◽  
Vol 12 (1) ◽  
pp. 337 ◽  
Author(s):  
Yuyang Yu ◽  
Jing Li ◽  
Zixiang Zhou ◽  
Li Zeng ◽  
Cheng Zhang
Keyword(s):  
Carbon Sequestration ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Carbon Storage ◽  
Discount Rate ◽  
Net Present Value ◽  
Carbon Price ◽  
Present Value ◽  
Mountain Area

The Qinling-Daba Mountain area is a transitional zone between north and south China and not much is known about its carbon storage, particularly its pool of soil organic carbon (SOC). Given this shortcoming, more reliable information regarding its SOC is needed. In light of this, we quantified above and below-ground carbon sinks using both the Carnegie-Ames-Stanford approach (CASA) model and an improved carbon cycle process model. We also assessed the net present value (NPV) for carbon budgets under different carbon price and discount rate scenarios using the NPV model. Our results indicated that the net primary productivity (NPP) was lower in places with low density forests that were situated at high elevation. The spatial distribution of carbon storage depended on NPP production and litter decompositon, which reflected specific vegetation as well as temperature and moisture gradients. The lowest amounts of carbon storage were in the center of the Qinling Mountains and also partly in the Daba area, which is a location associated with sparse grassland. Contrastingly, the broad-leaved forested area showed the highest amount of carbon storage. NPV was positively correlated with discount rate and carbon prices, thus resulting in the highest values in the forests and grassland. The net present value of total soil carbon sequestration in the six scenarios in 2015 was 3.555 b yuan, 3.621 b yuan, 5.421 b yuan, 5.579 b yuan, 7.530 b yuan, 7.929 b yuan; The net present value of total soil carbon sequestration in 6 scenarios in 2017 is 2.816 b yuan, 2.845 b yuan, 4.361 b yuan, 4.468 b yuan, 6.144 b yuan, 6.338 b yuan (billion = 109; b; RMB is the legal currency of the China, and its unit is yuan, 1 euro = 7.7949 yuan, and 1 pound = 9.2590 yuan). Levying a carbon tax would be a notable option for decision makers as they develop carbon emission reduction policies. Given this, incorporating discount rates and carbon pricing would allow for more realistic value estimations of soil organic carbon. This approach would also provide a theoretical basis and underscore the practical significance for the government to set a reasonable carbon price.

scholarly journals Assessing the impact of changes in climate and CO2on potential carbon sequestration in agricultural soils

2005 ◽  
Vol 32 (19) ◽  
pp. n/a-n/a ◽  
Author(s):  
Atul K. Jain ◽  
Tristram O. West ◽  
Xiaojuan Yang ◽  
Wilfred M. Post
Keyword(s):  
Carbon Sequestration ◽  
Agricultural Soils ◽  
The Impact ◽  
Potential Carbon

scholarly journals A Statistical–Dynamical Methodology to Downscale Regional Climate Projections to Urban Scale

2020 ◽  
Vol 59 (6) ◽  
pp. 1109-1123 ◽  
Author(s):  
François DuchÊne ◽  
Bert Van Schaeybroeck ◽  
Steven Caluwaerts ◽  
Rozemien De Troch ◽  
Rafiq Hamdi ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Heat Waves ◽  
Regional Climate ◽  
Wave Number ◽  
Surface Model ◽  
Climate Projections ◽  
Short Period ◽  
The Impact

AbstractThe demand of city planners for quantitative information on the impact of climate change on the urban environment is increasing. However, such information is usually extracted from decadelong climate projections generated with global or regional climate models (RCMs). Because of their coarse resolution and unsuitable physical parameterization, however, their model output is not adequate to be used at city scale. A full dynamical downscaling to city level, on the other hand, is computationally too expensive for climatological time scales. A statistical–dynamical computationally inexpensive method is therefore proposed that approximates well the behavior of the full dynamical downscaling approach. The approach downscales RCM simulations using the combination of an RCM at high resolution (H-RES) and a land surface model (LSM). The method involves the setup of a database of urban signatures by running an H-RES RCM with and without urban parameterization for a relatively short period. Using an analog approach, these signatures are first selectively added to the long-term RCM data, which are then used as forcing for an LSM using an urban parameterization in a stand-alone mode. A comparison with a full dynamical downscaling approach is presented for the city of Brussels, Belgium, for 30 summers with the combined ALADIN–AROME model (ALARO-0) coupled to the Surface Externalisée model (SURFEX) as H-RES RCM and SURFEX as LSM. The average bias of the nocturnal urban heat island during heat waves is vanishingly small, and the RMSE is strongly reduced. Not only is the statistical–dynamical approach able to correct the heat-wave number and intensities, it can also improve intervariable correlations and multivariate and temporally correlated indices, such as Humidex.

scholarly journals Long-Term Biosolids Application on Land: Beneficial Recycling of Nutrients or Eutrophication of Agroecosystems?

Soil Systems ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. 9
Author(s):  
Murray B. McBride
Keyword(s):  
Trace Metals ◽  
Organic Carbon ◽  
Nutrient Loading ◽  
Agricultural Soils ◽  
Soil Health ◽  
Water Soluble ◽  
Amended Soils ◽  
The Impact ◽  
Biosolids Application

The impact of repeated application of alkaline biosolids (sewage sludge) products over more than a decade on soil concentrations of nutrients and trace metals, and potential for uptake of these elements by crops was investigated by analyzing soils from farm fields near Oklahoma City. Total, extractable (by the Modified Morgan test), and water-soluble elements, including macronutrients and trace metals, were measured in biosolids-amended soils and, for comparison, in soils that had received little or no biosolids. Soil testing showed that the biosolids-amended soils had higher pH and contained greater concentrations of organic carbon, N, S, P, and Ca than the control soils. Soil extractable P concentrations in the biosolids-amended soils averaged at least 10 times the recommended upper limit for agricultural soils, with P in the amended soils more labile and soluble than the P in control soils. Several trace elements (most notably Zn, Cu, and Mo) had higher total and extractable concentrations in the amended soils compared to the controls. A radish plant assay revealed greater phytoavailability of Zn, P, Mo, and S (but not Cu) in the amended soils. The excess extractable and soluble P in these biosolids-amended soils has created a long-term source of slow-release P that may contribute to the eutrophication of adjacent surface waters and contamination of groundwater. While the beneficial effects of increased soil organic carbon on measures of “soil health” have been emphasized in past studies of long-term biosolids application, the present study reveals that these benefits may be offset by negative impacts on soils, crops, and the environment from excessive nutrient loading.

scholarly journals Identification of key parameters controlling demographicallystructured vegetation dynamics in a Land Surface Model [CLM4.5(ED)]

2019 ◽  
Author(s):  
Elias C. Massoud ◽  
Chonggang Xu ◽  
Rosie Fisher ◽  
Ryan Knox ◽  
Anthony Walker ◽  
...  
Keyword(s):  
Land Surface ◽  
Canopy Structure ◽  
Land Surface Model ◽  
Carbon Stocks ◽  
Surface Model ◽  
Model Parameters ◽  
Growth Strategies ◽  
Community Land Model ◽  
Vegetation Models ◽  
The Impact

Abstract. Vegetation plays a key role in regulating global carbon cycles and is a key component of the Earth System Models (ESMs) aimed to project Earth's future climates. In the last decade, the vegetation component within ESMs has witnessed great progresses from simple 'big-leaf' approaches to demographically-structured approaches, which has a better representation of plant size, canopy structure, and disturbances. The demographically-structured vegetation models are typically controlled by a large number of parameters, and sensitivity analysis is generally needed to quantify the impact of each parameter on the model outputs for a better understanding of model behaviors. In this study, we use the Fourier Amplitude Sensitivity Test (FAST) to diagnose the Community Land Model coupled to the Ecosystem Demography Model, or CLM4.5(ED). We investigate the first and second order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks. While the photosynthetic capacity parameter Vc,max25 is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which are shown here to determine vegetation demography and carbon stocks through their impacts on survival and growth strategies. The results of this study highlights the importance of understanding the dynamics of the next generation of demographically-enabled vegetation models within ESMs toward improved model parameterization and model structure for better model fidelity.

Increasing the depth of a Land Surface Model. Part II: Temperature sensitivity to improved subsurface thermodynamics and associated permafrost response

2021 ◽  
Author(s):  
N. J. Steinert ◽  
J. F. González-Rouco ◽  
P. de Vrese ◽  
E. García-Bustamante ◽  
S. Hagemann ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
Land Surface Model ◽  
Phase Changes ◽  
Surface Model ◽  
Climate Projections ◽  
Stable States ◽  
Soil Parameter ◽  
The Impact

AbstractThe impact of various modifications of the JSBACH Land Surface Model to represent soil temperature and cold-region hydro-thermodynamic processes in climate projections of the 21st century is examined. We explore the sensitivity of JSBACH to changes in the soil thermodynamics, energy balance and storage, and the effect of including freezing and thawing processes. The changes involve 1) the net effect of an improved soil physical representation and 2) the sensitivity of our results to changed soil parameter values and their contribution to the simulation of soil temperatures and soil moisture, both aspects being presented in the frame of an increased bottom boundary depth from 9.83 m to 1418.84 m. The implementation of water phase changes and supercooled water in the ground creates a coupling between the soil thermal and hydrological regimes through latent heat exchange. Momentous effects on subsurface temperature of up to ±3 K, together with soil drying in the high northern latitudes, can be found at regional scales when applying improved hydro-thermodynamic soil physics. The sensitivity of the model to different soil parameter datasets occurs to be low but shows important implications for the root zone soil moisture content. The evolution of permafrost under pre-industrial forcing conditions emerges in simulated trajectories of stable states that differ by 4 – 6 • 106 km2 and shows large differences in the spatial extent of 105 –106 km2 by 2100, depending on the model configuration.

PROcess-guided deep learning and DAta-driven modelling (PRODA) uncovers key mechanisms underlying global soil carbon storage

2021 ◽  
Author(s):  
Feng Tao ◽  
Yuanyuan Huang ◽  
Bruce A. Hungate ◽  
Xingjie Lu ◽  
Toby D. Hocking ◽  
...  
Keyword(s):  
Deep Learning ◽  
Organic Carbon ◽  
Spatial Variation ◽  
Soil Carbon ◽  
Carbon Storage ◽  
Data Driven ◽  
Soil Carbon Storage ◽  
Community Land Model ◽  
Global Soil ◽  
Primary Driver

<p>Soil carbon storage is a vital ecosystem service. Yet mechanisms that regulate global soil organic carbon (SOC) dynamics remain elusive. Here we explicitly retrieve the spatial patterns of key biogeochemical mechanisms and their regulation pathways on SOC storage using the novel PROcess-guided deep learning and Data-driven modelling (PRODA) approach. PRODA integrates data assimilation, deep learning, big data with 54,073 globally distributed vertical SOC profiles, and the Community Land Model version 5 (CLM5) to best represent and understand global soil carbon cycle. The PRODA-optimised CLM5 can represent 56±2% spatial variation of SOC across the world. Among all the mechanisms we explored in this study, microbial carbon use efficiency (CUE) emerges as the most critical regulator of global SOC storage. Increasing CUE, where more carbon flow is channelled into stabilisation, coincides with decreasing temperature and favours SOC accrual. Global sensitivity analysis further confirms the CUE, surpassing carbon input and decomposition, as the primary driver to SOC storage and its spatial variation. An increase of CUE by 1% from its standing value will lead to an additional 76±3 petagrams global SOC accumulation. We conclude that how efficiently soil microorganisms utilise organic carbon in metabolism is central to global SOC stabilisation. Understanding detailed processes underlying CUE and its environmental dependence will be critical in accurately describing soil carbon dynamics and its feedbacks to climate change.</p>

scholarly journals Effect of Land Use on Organic Carbon Storage Potential of Soils with Contrasting Native Organic Matter Content

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Sabina Yeasmin ◽  
Eshara Jahan ◽  
Md. Ashik Molla ◽  
A. K. M. Mominul Islam ◽  
Md. Parvez Anwar ◽  
...  
Keyword(s):  
Land Use ◽  
Organic Matter ◽  
Organic Carbon ◽  
Carbon Storage ◽  
Organic Matter Content ◽  
Fallow Land ◽  
Land Uses ◽  
Storage Potential ◽  
The Impact ◽  
Native Organic Matter

This study aimed to determine the impact of land use on organic carbon (OC) pools of soils with contrasting native organic matter (OM) content. Surface (0–15 cm) soils of four land uses (cropland, orchard, grassland, and fallow) were collected from four agroecological zones (AEZs) of Bangladesh with different OM content (AEZ-7: very low, −3: low, −9: medium, and −5: high). Bulk soils were physically fractionated into particulate and mineral associated OM (POM and MOM: >53 and <53 µm, respectively). Both bulk and fractionated soils were analyzed for OC and nitrogen (N). Among the land uses, undisturbed soils (grassland and fallow land) had significantly higher total OC (0.44–1.79%) than disturbed soils (orchard and cropland) (0.39–1.67%) in all AEZs. The distribution of OC and N in POM and MOM fractions was significantly different among land uses and also varied with native OM content. In all AEZs, cropland soils showed the lowest POM-C content (0.40–1.41%), whereas the orchard soils showed the highest values (0.71–1.91%). The MOM-C was highest (0.81–1.91%) in fallow land and lowest (0.53–1.51%) in orchard, and cropland had a moderate amount (0.70–1.61%). In croplands, distribution of a considerable amount of OC in the MOM pool was noticeable. These findings reveal that total OC in soils can be decreased with cultivation but does not inevitably indicate the loss of OC storage in the stable pool. Carbon storage potential of soils with both high- and low-native OM contents can be increased via proper land use and managements.

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