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Complex dynamic models of carbon and nitrogen are often used to investigate the consequences of climate change on agricultural production and greenhouse gas emissions from agriculture. These models require high temporal resolution input data regarding the timing of field operations. This paper describes the Timelines model, which predicts the timelines of key field operations across Europe. The evaluation of the model suggests that it is broadly capable of simulating the timing of field operations for a range of arable crops at different locations. Systematic variations in the date of harvesting and in the timing of the first application of N fertiliser to winter crops need to be corrected and the prediction of soil workability and traffcability might enable the prediction of ploughing and applications of solid manure in preparation for spring crops. The data concerning the thermal time thresholds for sowing and harvesting underlying the model should be updated and extended to a wider range of crops. [ABSTRACT FROM AUTHOR]

The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m² m-2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0-54.2%), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0-20.1 and ~9.4-22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6-86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model. [ABSTRACT FROM AUTHOR]

Atmospheric inversions are used to derive constraints on the net sources and sinks of CO 2 and other stable atmospheric tracers from their observed concentrations. The resolution and accuracy that the fluxes can be estimated with depends, among other factors, on the quality and density of the observational coverage, on the precision and accuracy of the transport model used by the inversion to relate fluxes to observations, and on the adaptation of the statistical approach to the problem studied. In recent years, there has been an increasing demand from stakeholders for inversions at higher spatial resolution (country scale), in particular in the framework of the Paris agreement. This step up in resolution is in theory enabled by the growing availability of observations from surface in situ networks (such as ICOS in Europe) and from remote sensing products (OCO-2, GOSAT-2). The increase in the resolution of inversions is also a necessary step to provide efficient feedback to the bottom-up modeling community (vegetation models, fossil fuel emission inventories, etc.). However, it calls for new developments in the inverse models: diversification of the inversion approaches, shift from global to regional inversions, and improvement in the computational efficiency. In this context, we developed LUMIA, the Lund University Modular Inversion Algorithm. LUMIA is a Python library for inverse modeling built around the central idea of modularity: it aims to be a platform that enables users to construct and experiment with new inverse modeling setups while remaining easy to use and maintain. It is in particular designed to be transport-model-agnostic, which should facilitate isolating the transport model errors from those introduced by the inversion setup itself. We have constructed a first regional inversion setup using the LUMIA framework to conduct regional CO 2 inversions in Europe using in situ data from surface and tall-tower observation sites. The inversions rely on a new offline coupling between the regional high-resolution FLEXPART Lagrangian particle dispersion model and the global coarse-resolution TM5 transport model. This test setup is intended both as a demonstration and as a reference for comparison with future LUMIA developments. The aims of this paper are to present the LUMIA framework (motivations for building it, development principles and future prospects) and to describe and test this first implementation of regional CO 2 inversions in LUMIA. [ABSTRACT FROM AUTHOR]

Our ability to predict future climate change relies on our understanding of current and future CO2 fluxes, particularly on a regional scale (100-1000 km). CO2 regional sources and sinks are still poorly understood. Inverse transport modeling, a method often used to quantify these fluxes, relies on atmospheric CO2 measurements. One of the main challenges for the transport models used in the inversions is to properly reproduce CO2 vertical gradients between the boundary layer and the free troposphere, as these gradients impact on the partitioning of the calculated fluxes between the different model regions. Vertical CO2 profiles are very well suited to assess the performances of the models. In this paper, we conduct a comparison between observed and modeled CO 2 profiles recorded during two CAATER campaigns that occurred in May 2001 and October 2002 over Western Europe, as described in a companion paper. We test different combinations between a global transport model (LMDZt), a mesoscale transport model (CHIMERE), and different sets of biospheric fluxes, all chosen with a diurnal cycle (CASA, SiB2 and ORCHIDEE). The vertical profile comparison shows that: 1) in most cases the influence of the biospheric flux is small but sometimes not negligible, ORCHIDEE giving the best results in the present study; 2) LMDZt is most of the time too diffuse, as it simulates a too high boundary layer height; 3) CHIMERE better reproduces the observed gradients between the boundary layer and the free troposphere, but is sometimes too variable and gives rise to incoherent structures. We conclude there is a need for more vertical profiles to conduct further studies to improve the parameterization of vertical transport in the models used for CO 2 flux inversions. Furthermore, we use a modeling method to quantify CO 2 fluxes at the regional scale from a chosen observing point, coupling influence functions from the transport model LMDZt (that works quite well at the synoptic scale) with information on the space-time distribution of fluxes. This modeling method is compared to a dual tracer method (the so-called Radon method) for a case study on 25 May 2001 during which simultaneous well-correlated in situ CO2 and Radon 222 measurements have been collected. Both methods give a similar result: a flux within the Radon 222 method uncertainty (35%), that is an atmospheric CO2 sink of -4.2 -2 -1 to -4.4 gCm-1 day-1 . We have estimated the uncertainty of the modeling method to be at least 33% on average, and even more for specific individual events. This method allows the determination of the area that contributed to the CO 2 observed concentration. In our case, the observation point located at 1700ma.s.l. in the north of France, is influenced by an area of 1500x700 km² that covers the Benelux region, part of Germany and western Poland. Furthermore, this method allows deconvolution between the different contributing fluxes. In this case study, the biospheric sink contributes 73% of the total flux, fossil fuel emissions for 27%, the oceanic flux being negligible. However, the uncertainties of the influence function method need to be better assessed. This could be possible by applying it to other cases where the calculated fluxes can be checked independently, for example at tall towers where simultaneous CO2 and Radon 222 measurements can be conducted. The use of optimized fluxes (from atmospheric inversions) and of mesoscale models for atmospheric transport may also significantly reduce the uncertainties. [ABSTRACT FROM AUTHOR]

Human-induced land use changes are nowadays the second largest contributor to atmospheric carbon dioxide after fossil fuel combustion. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modelling techniques, and the integration of land conversion types allow us to create accurate, high-resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km² (15.5 %) of land cover in Europe has changed over the period 1950-2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19 %). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicates that the main drivers of land change over the studied period were urbanization, the reforestation program resulting from the timber shortage after the Second World War, the fall of the Iron Curtain, the Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method considers the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristics allow the data to be used to support and improve ongoing GHG inventories and climate research. [ABSTRACT FROM AUTHOR]

Atmospheric air borne measurements of CO2 are very well suited for estimating the time-varying distribution of carbon sources and sinks at the regional scale due to the large geographical area covered over a short time. We present here an analysis of two cross-European airborne campaigns carried out on 23-26 May 2001 (CAATER-1) and 2-3 October 2002 (CAATER-2) over Western Europe. The area covered during CAATER-1 and CAATER-2 was 4° W to 14° E long; 44° N to 52° N 1° at and 1° E to 17° E long; 46° N to 52° N lat respectively. High precision in situ CO2, CO and Radon 222 measurements were recorded. Flask samples were collected during both campaigns to cross-validate the in situ data. During CAATER-1 and CAATER-2, the mean CO2concentration was 370.1±4.0 (1-δ standard deviation) ppm and 371.7±5.0 (1-δ) ppm respectively. A HYSPLIT back-trajectories analysis shows that during CAATER 1, northwesterly winds prevailed. In the planetary boundary layer (PBL) air masses became contaminated over Benelux and Western Germany by emissions from these highly urbanized areas, reaching about 380 ppm. Air masses passing over rural areas were depleted in CO2 because of the photosynthesis activity of the vegetation, with observations as low as 355 ppm. During CAATER-2, the back-trajectory analysis showed that air masses were distributed among the 4 sectors. Airmasses were enriched in CO2 and CO over anthropogenic emission spots in Germany but also in Poland, as these countries have part of the most CO2-emitting coal-based plants in Europe. Simultaneous measurements of in situ CO2 and CO combined with back-trajectories helped us to distinguish between fossil fuel emissions and other CO2 sources. The ΔCO/ΔCO2 ratios (R²=0.33 to 0.88, slopes=2.42 to 10.37), calculated for anthropogenic-influenced air masses over different countries/regions matched national inventories quite well, showing that airborne measurements can help to identify the origin of fossil fuel emissions in the PBL even when distanced by several days/hundreds of kms from their sources. We have compared airborne CO2 observations to nearby ground station measurements and thereby, confirmed that measurements taken in the lower few meters of the PBL (low-level ground stations) are representative of the local scale, while those located in the free troposphere (FT) (moutain stations) are representative of atmospheric CO2 regionally on a scale of a few hundred kilometers. Stations located several 100 km away from each other differ from a few ppm in their measurements indicating the existence of a gradient within the free troposphere. Observations at stations located on top of small mountains may match the airborne data if the sampled air comes from the FT rather than coming up from the valley. Finally, the analysis of the CO2 vertical variability conducted on the 14 profiles recorded in each campaign shows a variability at least 5 to 8 times higher in the PBL (the 1-δ standard deviation associated to the CO2mean of all profiles within the PBL is 4.0 ppm and 5.7 ppm for CAATER-1 and CAATER-2, respectively) than in the FT (within the FT, 1-δ is 0.5 ppm and 1.1 ppm for CAATER-1 and CAATER-2, respectively). The CO 2 jump between the PBL and the FT equals 3.7 ppm for the first campaign and -0.3 ppm for the second campaign. A very striking zonal CO2 gradient of about 11 ppm was observed in the mid-PBL during CAATER-2, with higher concentrations in the west than in the east. This gradient may originate from differences in atmospheric mixing, ground emission rates or Autumn's earlier start in the west. More airborne campaigns are currently under analysis in the framework of the CARBOEUROPE-IP project to better assess the likelihood of these different hypotheses. In a companion paper (Xueref-Remy et al., 2011, Part 2), a comparison of vertical profiles from observations and several modeling frameworks was conducted for both campaigns. [ABSTRACT FROM AUTHOR]

We analysed interannual and decadal changes in the atmospheric CO2 concentration gradient (ΔCO2) between Europe and the Atlantic Ocean over the period 1995–2007. Fourteen measurement stations are used, with Mace-Head being used to define background conditions. The variability of ΔCO2 reflects fossil fuel emissions and natural sinks activity over Europe, as well as atmospheric transport variability. The mean ΔCO2 increased by 1–2 ppm at Eastern European stations (∼30% growth), between 1990–1995 and 2000–2005. This built up of CO2 over the continent is predominantly a winter signal. If the observed increase of ΔCO2 is explained by changes in ecosystem fluxes, a loss of about 0.46 Pg C per year would be required during 2000–2005. Even if severe droughts have impacted Western Europe in 2003 and 2005, a sustained CO2 loss of that magnitude is unlikely to be true. We sought alternative explanations for the observed CO2 build-up into transport changes and into regional redistribution of fossil fuel CO2 emissions. Boundary layer heights becoming shallower can only explain 32% of the variance of the signal. Regional changes of emissions may explain up to 27% of the build-up. More insights are given in the Aulagnier et al. companion paper. [ABSTRACT FROM AUTHOR]

Lakes play a key role in the global carbon cycle, transporting, processing and storing organic carbon (OC) along the land‐ocean aquatic continuum. There are, however, surprisingly few complete lake OC budgets, particularly for certain lake types and geographical areas. An OC budget for Lough Feeagh (Ireland), an oligotrophic, peatland lake in a temperate oceanic location, was estimated for one year using both direct measurements and elements calculated from literature. It was constructed as a simple mass balance model that constrained the key OC processing rates. The total OC input to the lake during 2017 was estimated to be 2544 t C, of which it was estimated that 51% was imported as dissolved OC (DOC) in surface water, 4% in ground water, 1% in rainwater, and 3% was fixed in the lake as net ecosystem production. The remaining 41% was carried into the lake as particulate OC (POC) in surface water. The total C exported was estimated to be 2892 t C, of which 46% and 11% were exported as DOC and POC in the surface water outflow, respectively, 26% was deposited as sediment and 17% was mineralized and emitted as CO2 to the atmosphere. The results highlight the substantial volume of OC turned over in the lake during the study period. Moreover, it emphasizes how lakes in temperate, humic systems, common on the western edge of Europe, are important to the processing and fate of OC mobilized from their catchments. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim This paper identifies socio-economic driving forces of biodiversity change and analyses their political and economic dynamics by modelling socio-economic parts of three scenario storylines developed for the ALARM (assessing large-scale risks for biodiversity with tested methods) project. In the BAMBU (business-as-might-be-usual) scenario policy decisions already made in the European Union (EU) are implemented and enforced, but no additional measures are introduced. The GRAS (growth applied strategy) scenario describes a future world orientated towards economic growth and complete deregulation. And finally, SEDG (sustainable European development goal) is a normative scenario focusing on the achievement of sustainable development. Methods The GINFORS (global inter-industry forecasting system) model is applied to quantify the effects of different sets of policy measures representing the three scenarios. It allows investigation of the inter-relations between socio-economic driving forces and the state of the environment. Results The presented results for the 25 EU countries focus on the following variables: unemployment, material extraction, energy supply and CO2 emissions. The lowest amount of unemployment is in the SEDG scenario, where it steadily decreases from 2005 to 2020. In BAMBU it falls to a level that is also below that of 2005. In GRAS, the number of unemployed people in 2020 is clearly over the value of 2005. The development of total material extraction from 2005 to 2020 is nearly stable in BAMBU, while it clearly increases in GRAS. Only in SEDG is there a reduction in resource use. None of the scenarios achieves a substantial reduction in energy use. However, the development of CO2 emissions shows a decoupling from energy supply. For BAMBU there is a slight decline in CO2 emissions over time, for GRAS they increase but with a slightly smaller growth rate than energy supply. In SEDG the emissions are reduced. The decoupling trends can be explained by a shift to more renewable energy sources in all scenarios, with the highest share in SEDG. Main conclusions The results indicate that a growth-oriented policy design, such as presented in the GRAS scenario, is not compatible with the conservation of biodiversity. Only in the SEDG scenario do the policy measures support the idea of a sustainable development, but in some respects they are still not ambitious enough. [ABSTRACT FROM AUTHOR]

Climate change research is currently a topic of great interest for economic researchers. In particular, environmental input–output analysis increasingly plays an important role in measuring the economic and environmental effects of sustainable development policies in Europe. Other approaches also exist, such as econometric modelling, in which impacts are quantified on statistical grounds and with certain desirable properties (efficient estimates, confidence intervals, hypothesis testing, etc.) that are not found in the input–output approach. Consequently, this paper merges the two approaches to address the calculation of unbiased and consistent carbon dioxide emission multipliers for Denmark and their respective confidence intervals. The use of the supply and use system instead of the symmetric input–output table also presents the opportunity to avoid the common problems associated with the construction of technical coefficients (technology assumptions, negatives, etc.). Moreover, a new policy-relevant application of these multipliers is introduced: the quantification of the performance of the carbon dioxide emission reductions carried out by industries via external trading. [Copyright &y& Elsevier]

Phototrophic microbes, also known as micro‐algae, display a high abundance in many terrestrial surface soils. They contribute to atmospheric carbon dioxide fluxes through their photosynthesis, and thus regulate climate similar to plants. However, microbial photosynthesis remains overlooked in most terrestrial ecosystems. Here, we hypothesise that phototrophic microbes significantly contribute to peatland C uptake, unless environmental conditions limit their development and their photosynthetic activity.To test our hypothesis, we studied phototrophic microbial communities in five peatlands distributed along a latitudinal gradient in Europe. By means of metabarcoding, microscopy and cytometry analyses, as well as measures of photosynthesis, we investigated the diversity, absolute abundance and photosynthetic rates of the phototrophic microbial communities.We identified 351 photosynthetic prokaryotic and eukaryotic operational taxonomic units (OTUs) across the five peatlands. We found that water availability and plant composition were important determinants of the composition and the structure of phototrophic microbial communities. Despite environmental shifts in community structure and composition, we showed that microbial C fixation rates remained similar along the latitudinal gradient. Our results further revealed that phototrophic microbes accounted for approximately 10% of peatland C uptake.Synthesis. Our findings show that phototrophic microbes are extremely diverse and abundant in peatlands. While species turnover with environmental conditions, microbial photosynthesis similarly contributed to peatland C uptake at all latitudes. We estimate that phototrophic microbes take up around 75 MT CO2 per year in northern peatlands. This amount roughly equals the magnitude of projected peatland C loss due to climate warming and highlights the importance of phototrophic microbes for the peatland C cycle. [ABSTRACT FROM AUTHOR]

Forecasting atmospheric CO2 concentrations on synoptic timescales (∼ days) can benefit the planning of field campaigns by better predicting the location of important gradients. One aspect of this, accurately predicting the day-to-day variation in biospheric fluxes, poses a major challenge. This study aims to investigate the feasibility of using a diagnostic light-use-efficiency model, the Vegetation Photosynthesis Respiration Model (VPRM), to forecast biospheric CO2 fluxes on the timescale of a few days. As input, the VPRM model requires downward shortwave radiation, 2 m temperature, and enhanced vegetation index (EVI) and land surface water index (LSWI), both of which are calculated from MODIS reflectance measurements. Flux forecasts were performed by extrapolating the model input into the future, i.e., using downward shortwave radiation and temperature from a numerical weather prediction (NWP) model, as well as extrapolating the MODIS indices to calculate future biospheric CO2 fluxes with VPRM. A hindcast for biospheric CO2 fluxes in Europe in 2014 has been done and compared to eddy covariance flux measurements to assess the uncertainty from different aspects of the forecasting system. In total the range-normalized mean absolute error (normalized) of the 5 d flux forecast at daily timescales is 7.1 %, while the error for the model itself is 15.9 %. The largest forecast error source comes from the meteorological data, in which error from shortwave radiation contributes slightly more than the error from air temperature. The error contribution from all error sources is similar at each flux observation site and is not significantly dependent on vegetation type. [ABSTRACT FROM AUTHOR]

We present observing system simulation experiments (OSSEs) to evaluate the impact of a proposed network of ground-based miniaturized laser heterodyne radiometer (mini-LHR) instruments that measure atmospheric column-averaged carbon dioxide (XCO2) with a 1 ppm precision. A particular strength of this passive measurement approach is its insensitivity to clouds and aerosols due to its direct sun pointing and narrow field of view (0.2 ∘). Developed at the NASA Goddard Space Flight Center (GSFC), these portable, low-cost mini-LHR instruments were designed to operate in tandem with the sun photometers used by the AErosol RObotic NETwork (AERONET). This partnership allows us to leverage the existing framework of AERONET's global ground network of more than 500 sites as well as providing simultaneous measurements of aerosols that are known to be a major source of error in retrievals of XCO2 from passive nadir-viewing satellite observations. We show, using the global 3-D GEOS-Chem chemistry transport model, that a deployment of 50 mini-LHRs at strategic (but not optimized) AERONET sites significantly improves our knowledge of global and regional land-based CO2 fluxes. This improvement varies seasonally and ranges 58 %–81 % over southern lands, 47 %–76 % over tropical lands, 71 %–92 % over northern lands, and 64 %–91 % globally. We also show significant added value from combining mini-LHR instruments with the existing ground-based NOAA flask network. Collectively, these data result in improved a posteriori CO2 flux estimates on spatial scales of ∼10 km 2 , especially over North America and Europe, where the ground-based networks are densest. Our studies suggest that the mini-LHR network could also play a substantive role in reducing carbon flux uncertainty in Arctic and tropical systems by filling in geographical gaps in measurements left by ground-based networks and space-based observations. A realized network would also provide necessary data for the quinquennial global stocktakes that form part of the Paris Agreement. [ABSTRACT FROM AUTHOR]

Optimized biogenic carbon fluxes for Europe were estimated from high-resolution regional-scale inversions, utilizing atmospheric CO2 measurements at 16 stations for the year 2007. Additional sensitivity tests with different data-driven error structures were performed. As the atmospheric network is rather sparse and consequently contains large spatial gaps, we use a priori biospheric fluxes to further constrain the inversions. The biospheric fluxes were simulated by the Vegetation Photosynthesis and Respiration Model (VPRM) at a resolution of 0.1° and optimized against eddy covariance data. Overall we estimate an a priori uncertainty of 0.54 GtC yr-1 related to the poor spatial representation between the biospheric model and the ecosystem sites. The sink estimated from the atmospheric inversions for the area of Europe (as represented in the model domain) ranges between 0.23 and 0.38 GtC yr-1 (0.39 and 0.71 GtC yr-1 up-scaled to geographical Europe). This is within the range of posterior flux uncertainty estimates of previous studies using ground-based observations. [ABSTRACT FROM AUTHOR]

Soil respiration is one of the largest terrestrial fluxes of carbon dioxide (CO2/ to the atmosphere. Hence, small changes in soil respiration rates could have large effects on atmospheric CO2. In order to assess CO2 emissions from diverse European soils with different land-use types and climate (soil moisture and temperature), we conducted a laboratory incubation experiment. Emission measurements of CO2 under controlled conditions were conducted using soil monoliths of nine sites from a European flux network (ÉCLAIRE). The sites are located all over Europe - from the United Kingdom in the west to Ukraine in the east, and from Italy in the south to Finland in the north - and can be separated according to four land-use types (forests, grasslands, arable lands and one peatland). Intact soil cores were incubated in the laboratory in a two-way factorial design, with temperature (5, 10, 15, 20 and 25 C) and water-filled pore space (WFPS; 5, 20, 40, 60 and 80%) as the independent variables, while CO2 flux was the response variable. The latter was measured with an automated laboratory incubation measurement system. Land use generally had a substantial influence on carbon dioxide fluxes, with the order of CO2 emission rates of the different land-use types being grassland >peatland>forest/arable land (P <0.001). CO2 efflux responded strongly to varying temperature and moisture content with optimum moisture contents for CO2 emissions between 40 and 70% WFPS and a positive relationship between CO2 emissions and temperature. The relationship between temperature and CO2 emissions could be well described by a Gaussian model. Q10 values ranged between 0.86 and 10.85 and were negatively related to temperature for most of the moisture contents and sites investigated. At higher temperatures the effect of water and temperature on Q10 was very low. In addition, under cold temperatures Q10 varied with moisture contents, indicating a stronger prospective effect of rain events in cold areas on temperature sensitivity. At both coniferous forest sites we found a strong increase in the temperature sensitivity at a moisture range between 20 and 40% WFPS. We developed a new approach to calculate moisture sensitivity (MS) of CO2 efflux. MS was calculated as the slope of a polynomial function of second degree. Moisture sensitivities were highest under dry and wet conditions. In addition we found a positive relationship between MS of CO2 efflux and temperature for both arable lands. [ABSTRACT FROM AUTHOR]

Natural ecosystems respond to, and may affect climate change through uptake and storage of atmospheric CO2. Here we use the land-surface and carbon cycle model JULES to simulate the contemporary European carbon balance and its sensitivity to rising CO2 and changes in climate. We find that the impact of climate change is to decrease the ability of Europe to store carbon by 97 TgC yr-1. In contrast, the effect of rising atmospheric CO2 has been to stimulate increased uptake and storage. The CO2 effect is currently dominant leading to a net increase of 114 TgC yr-1. Our simulations do not at present include other important factors such as land use and management, the effects of forest age classes and nitrogen deposition. Understanding this balance and its implications for mitigation policies is becoming increasingly important. [ABSTRACT FROM AUTHOR]

The CO2 source and sink distribution across Europe can be estimated in principle through inverse methods by combining CO2 observations and atmospheric transport models. Uncertainties of such estimates are mainly due to insufficient spatiotemporal coverage of CO2 observations and biases of the models. In order to assess the biases related to the use of different models the CO2 concentration field over Europe has been simulated with five different Eulerian atmospheric transport models as part of the EU-funded AEROCARB project, which has the main goal to estimate the carbon balance of Europe. In contrast to previous comparisons, here both global coarse-resolution and regional higher-resolution models are included. Continuous CO2 observations from continental, coastal and mountain sites as well as flasks sampled on aircrafts are used to evaluate the models' ability to capture the spatiotemporal variability and distribution of lower troposphere CO2 across Europe. 14CO2 is used in addition to evaluate separately fossil fuel signal predictions. The simulated concentrations show a large range of variation, with up to ~10 ppm higher surface concentrations over Western and Central Europe in the regional models with highest (mesoscale) spatial resolution. The simulation - data comparison reveals that generally high-resolution models are more successful than coarse models in capturing the amplitude and phasing of the observed short-term variability. At high-altitude stations the magnitude of the differences between observations and models and in between models is less pronounced, but the timing of the diurnal cycle is not well captured by the models. The data comparisons show also that the timing of the observed variability on hourly to daily time scales at low-altitude stations is generally well captured by all models. However, the amplitude of the variability tends to be underestimated. While daytime values are quite well predicted, nighttime values are generally underpredicted. This is a reflection of the different mixing regimes during day and night combined with different vertical resolution between models. In line with this finding, the agreement among models is increased when sampling in the afternoon hours only and when sampling the mixed portion of the PBL, which amounts to sampling at a few hundred meters above ground. The main recommendations resulting from the study for constraining land carbon sources and sinks using high-resolution concentration data and state-of-the art transport models through inverse methods are given in the following: 1) Low altitude stations are presently preferable in inverse studies. If high altitude stations are used then the model level that represents the specific sites should be applied, 2) at low altitude sites only the afternoon values of concentrations can be represented sufficiently well by current models and therefore afternoon values are more appropriate for constraining large-scale sources and sinks in combination with transport models, 3) even when using only afternoon values it is clear that data sampled several hundred meters above ground can be represented substantially more robustly in models than surface station records, which emphasize the use of tower data in inverse studies and finally 4) traditional large scale transport models seem not sufficient to resolve fine-scale features associated with fossil fuel emissions, as well as larger-scale features like the concentration distribution above the south-western Europe. It is therefore recommended to use higher resolution models for interpretation of continental data in future studies. [ABSTRACT FROM AUTHOR]

Globally, the year 2003 is associated with one of the largest atmospheric CO2 rises on record. In the same year, Europe experienced an anomalously strong flux of CO2 from the land to the atmosphere associated with an exceptionally dry and hot summer in Western and Central Europe. In this study we analyze the magnitude of this carbon flux anomaly and key driving ecosystem processes using simulations of seven terrestrial ecosystem models of different complexity and types (process-oriented and diagnostic). We address the following questions: (1) how large were deviations in the net European carbon flux in 2003 relative to a short-term baseline (1998-2002) and to longer-term variations in annual fluxes (1980 to 2005), (2) which regions exhibited the largest shift 10 in carbon fluxes during the growing season 2003, and (3) which processes controlled the carbon balance anomaly . In Western and Central Europe, the anomaly in net ecosystem productivity (NEP) over growing season 2003 was outside the 1σ bound of the carbon flux anomalies for 1980-2005. The estimated growing season anomaly ranged between -29 and -196 TgC for Western Europe and between 13 and -94 TgC for Central Europe depending on the model used. All models responded to a dipole pattern of the climate anomaly in 2003. In Western and Central Europe NEP was reduced due to heat and drought. Over Western Russia NEP was decreased in response to lower than normal temperatures and high precipitation. While models agree on changes in simulated NEP and gross primary productivity anomalies in 2003 over Western and Central Europe, models diverge in the estimates of anomalies in ecosystem respiration. Except for two process models which simulate respiration increase, most models simulated a decrease in ecosystem respiration in 2003. The diagnostic models showed a weaker decrease in ecosystem respiration than the process-oriented models. Based on the multi-model simulations we estimated the total carbon flux anomaly over the 2003 growing season in Europe to range between -0.02 and -0.27 PgC relative to the net flux in 1998-2002. [ABSTRACT FROM AUTHOR]

Examines the effects of elevated carbon dioxide concentration on stomal conductance of forest trees in Europe. Application of meta-analysis; Decrease in stomal conductance in response to growth in elevated carbon dioxide; Comparison of carbon dioxide reponse between younger and older trees.