Simulation of greenhouse gases following land-use change to bioenergy crops using the ECOSSE model : a comparison between site measurements and model predictions

This work contributes to the ELUM (Ecosystem Land Use Modelling & Soil Carbon GHG Flux Trial) project, which was commissioned and funded by the Energy Technologies Institute (ETI). We acknowledge the E-OBS data set from the EU-FP6 project ENSEMBLES (http://ensembles-eu.metoffice.com) and the data providers in the ECA&D project (http://www.ecad.eu).Peer reviewedPublisher PD

CO2 fluxes and ecosystem dynamics at five European treeless peatlands – merging data and process oriented modeling

The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in land use intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out whether CO2 fluxes, measured at different sites, can be explained by common processes and parameters or to what extend a site specific configuration is needed. The model was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analyzed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. Seasonal variability in the major fluxes was well captured, when a site independent configuration was utilized for most of the parameters. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, rate coefficients for heterotrophic respiration were consistently the lowest on formerly drained sites and the highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Specific parameter values for the timing of plant shooting and senescence, the photosynthesis response to temperature, litter fall and plant respiration rates, leaf morphology and allocation fractions of new assimilates, were not needed, even though the gradient in site latitude ranged from 48° N (southern Germany) to 68° N (northern Finland) differed largely in their vegetation. This was also true for common parameters defining the moisture and temperature response for decomposition, leading to the conclusion that a site specific interpretation of these processes is not necessary. In contrast, the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon pool need to be estimated from available information on specific soil conditions, vegetation and management of the ecosystems, to be able to describe CO2 fluxes under different condition

Application of Bayesian statistics to estimate nitrous oxide emission factors of the nitrogen fertilisers in UK grasslands

Trapezoidal integration by linear interpolation of data points is by far the most commonly used method of cumulative flux calculations of nitrous oxide (N2O) in studies that use flux chambers; however, this method is incapable of providing accurate uncertainty estimates. A Bayesian approach was used to calculate N2O emission factors (EFs) and their associated uncertainties from flux chamber measurements made after the application of nitrogen fertilisers, in the form of ammonium nitrate (AN), urea (Ur) and urea treated with Agrotain® urease inhibitor (UI) at four grassland sites in the UK. The comparison between the cumulative fluxes estimated using the Bayesian and linear interpolation methods were broadly similar (R2=0.79); however, the Bayesian method was capable of providing realistic uncertainties when a limited number of data points is available. The study reports mean EF values (and 95% confidence intervals) of 0.60 ± 0.63, 0.29 ± 0.22 and 0.26 ± 0.17% of applied N emitted as N2O for the AN, Ur and UI treatments, respectively. There was no significant difference between N2O emissions from the Ur and UI treatments. In the case of the automatic chamber data collected at one site in this study, the data did not fit the log-normal model, implying that more complex models may be needed, particularly for measurement data with high temporal resolutioninfo:eu-repo/semantics/publishedVersio

Simulation of greenhouse gases following land-use change to bioenergy crops using the ECOSSE model. A comparison between site measurements and model predictions

This article evaluates the suitability of the ECOSSE model to estimate soil greenhouse gas (GHG) fluxes from short rotation coppice willow (SRC-Willow), short rotation forestry (SRF-Scots Pine) and Miscanthus after landuse change from conventional systems (grassland and arable). We simulate heterotrophic respiration (Rh), nitrous oxide (N2O) and methane (CH4) fluxes at four paired sites in the UK and compare them to estimates of Rh derived from the ecosystem respiration estimated from eddy covariance (EC) and Rh estimated from chamber (IRGA) measurements, as well as direct measurements of N2O and CH4 fluxes. Significant association between modelled and EC-derived Rh was found under Miscanthus, with correlation coefficient (r) ranging between 0.54 and 0.70. Association between IRGA-derived Rh and modelled outputs was statistically significant at the Aberystwyth site (r = 0.64), but not significant at the Lincolnshire site (r = 0.29). At all SRC-Willow sites, significant association was found between modelled and measurement-derived Rh (0.44 ≤ r ≤ 0.77); significant error was found only for the EC-derived Rh at the Lincolnshire site. Significant association and no significant error were also found for SRF-Scots Pine and perennial grass. For the arable fields, the modelled CO2 correlated well just with the IRGA-derived Rh at one site (r = 0.75). No bias in the model was found at any site, regardless of the measurement type used for the model evaluation. Across all land uses, fluxes of CH4 and N2O were shown to represent a small proportion of the total GHG balance; these fluxes have been modelled adequately on a monthly time-step. This study provides confidence in using ECOSSE for predicting the impacts of future land use on GHG balance, at site level as well as at national level

Methane emissions from soils: synthesis and analysis of a large UK data set

Nearly 5000 chamber measurements of CH4 flux were collated from 21 sites across the UK, covering a range of soil and vegetation types, to derive a parsimonious model that explains as much of the variability as possible, with the least input requirements. Mean fluxes ranged from -0.3 to 27.4 nmol CH4 m−2 s−1, with small emissions or low rates of net uptake in mineral soils (site means of -0.3 to 0.7 nmol m−2 s−1) and much larger emissions from organic soils (site means of -0.3 to 27.4 nmol m−2 s−1). Less than half of the observed variability in instantaneous fluxes could be explained by independent variables measured. The reasons for this include measurement error, stochastic processes and, probably most importantly, poor correspondence between the independent variables measured and the actual variables influencing the processes underlying methane production, transport and oxidation. When temporal variation was accounted for, and the fluxes averaged at larger spatial scales, simple models explained up to ~75% of the variance in CH4 fluxes. Soil carbon, peat depth, soil moisture and pH together provided the best sub-set of explanatory variables. However, where plant species composition data were available, this provided the highest explanatory power. Linear and non-linear models generally fitted the data equally well, with the exception that soil moisture required a power transformation. To estimate the impact of changes in peatland water table on CH4 emissions in the UK, an emission factor of +0.4 g CH4 m−2 y−1 per cm increase in water table height was derived from the data

Carbon-nitrogen interactions in European forests and semi-natural vegetation - Part 1: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling

The impact of atmospheric reactive nitrogen (N$_{r}$) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC/dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of N$_{r}$ deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet N$_{r}$ deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and N$_{r}$ inputs and losses, these data were also combined with in situ flux measurements of NO, N$_{2}$O and CH$_{4}$ fluxes; soil NO$_{3}$̅ leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from -70 to 826 gCm$^{-2}$ yr$^{-1}$ at total wet+dry inorganic N$_{r}$ deposition rates (N$_{dep}$) of 0.3 to 4.3 gNm$^{-2}$ yr$^{-1}$ and from -4 to 361 g Cm$^{-2}$ yr$^{-1}$ at N$_{dep}$ rates of 0.1 to 3.1 gNm$^{-2}$ yr$^{-1}$ in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO$_{2}$ exchange, while CH$_{4}$ and N$_{2}$O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated N$_{dep}$ where N$_{r}$ leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N$_{2}$ losses by denitrification. Nitrogen losses in the form of NO, N$_{2}$O and especially NO$_{3}$̅ were on average 27%(range 6 %–54 %) of N$_{dep}$ at sites with N$_{dep}$ 3 gNm$^{-2}$ yr$^{-1}$. Such large levels of N$_{r}$ loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with N$_{r}$ deposition up to 2–2.5 gNm$^{-2}$ yr$^{-1}$, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP = GPP ratio). At elevated N$_{dep}$ levels (> 2.5 gNm$^{-2}$ yr$^{-1}$), where inorganic N$_{r}$ losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate N$_{dep}$ levels was partly the result of geographical cross-correlations between N$_{dep}$ and climate, indicating that the actual mean dC/dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. N$_{dep}$

Qualitative impact assessment of land management interventions on ecosystem services ("QEIA"). Report-1: executive summary QEIA evidence review & integrated assessment

The focus of this project was to provide a rapid qualitative assessment of land management interventions on Ecosystem Services (ES) proposed for inclusion in Environmental Land Management (ELM) schemes. This involved a review of the current evidence base by ten expert teams drawn from the independent research community in a consistent series of ten Evidence Reviews. These reviews were undertaken rapidly at Defra’s request and together captured more than 2000 individual sources of evidence. These reviews were then used to inform an Integrated Assessment (IA) to provide a more accessible summary of these evidence reviews with a focus on capturing the actions with the greatest potential magnitude of change for the intended ES and their potential co-benefits and trade-offs across the Ecosystem Services and Ecosystem Services Indicators. The final IA table captured scores for 741 actions across 8 Themes, 33 ES and 53 ES-indicators. This produced a total possible matrix of 39,273 scores. It should be noted that this piece of work is just one element of the wider underpinning work Defra has commissioned to support the development of the ELM schemes. The project was carried out in two phases with the environmental and provisioning services commissioned in Phase 1 and cultural and regulatory services in a follow-on Phase 2. Due to the urgency of the need for these evidence reviews, there was insufficient time for systematic reviews and therefore the reviews relied on the knowledge of the team of the peer reviewed and grey literature with some rapid additional checking of recent reports and papers. This limitation of the review process was clearly explained and understood

Qualitative impact assessment of land management interventions on ecosystem services (‘QEIA’). Report-2: integrated assessment

This project assessed the impacts of 741 potential land management actions, suitable for agricultural land in England, on the Farming & Countryside Programme’s Environmental Objectives (and therefore Environment Act targets and climate commitments) through 53 relevant environmental and cultural service indicators. The project used a combination of expert opinion and rapid evidence reviews, which included 1000+ pages of evidence in 10 separate reports with reference to over 2400 published studies, and an Integrated Assessment comprising expert-derived qualitative impact scores. The project has ensured that ELM schemes are evidence-based, offer good value for money, and contribute to SoS priorities for farming

Dry matter losses and methane emissions during wood chip storage: the impact on full life cycle greenhouse gas savings of short rotation coppice willow for heat

A life cycle assessment (LCA) approach was used to examine the greenhouse gas (GHG) emissions and energy balance of short rotation coppice (SRC) willow for heat production. The modelled supply chain includes cutting multiplication, site establishment, maintenance, harvesting, storage, transport and combustion. The relative impacts of dry matter losses and methane emissions from chip storage were examined from a LCA perspective, comparing the GHG emissions from the SRC supply chain with those of natural gas for heat generation. The results show that SRC generally provides very high GHG emission savings of over 90 %. The LCA model estimates that a 1, 10 and 20 % loss of dry matter during storage causes a 1, 6 and 11 % increase in GHG emissions per MWh. The GHG emission results are extremely sensitive to emissions of methane from the wood chip stack: If 1 % of the carbon within the stack undergoes anaerobic decomposition to methane, then the GHG emissions per MWh are tripled. There are some uncertainties in the LCA results, regarding the true formation of methane in wood chip stacks, non-CO2 emissions from combustion, N2O emissions from leaf fall and the extent of carbon sequestered under the crop, and these all contribute a large proportion of the life cycle GHG emissions from cultivation of the cro