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Models and observational strategies of carbon exchange need to take into account synoptic and mesoscale transport for correct interpretation of the relation between surface fluxes and atmospheric concentration gradients.A dequate quantification of the geographical distribution of sources and sinks of C02 is still a major task with considerable implications for both our understanding of the global climate and the possible opportunities to mitigate climate change. Atmospheric measurements of C02 mixing ratios at a number of locations around the globe have helped significantly to quantify the source-sink distribu-AFFILIATIONS: DOLMAN, TOLK, AND

Solar irradiation and wind speed vary with climatic, as well as seasonal and daily weather conditions. In order to represent these variable renewable energy (VRE) resources in specialized energy system models, high temporal and spatial resolution information on their availability is used. In contrast, Integrated Assessment Models (IAM), typically characterized by long term time scales and low temporal and spatial resolution, require aggregated information on VRE availability and balancing requirements at various levels of VRE penetration and mix. Parametric studies that provide such information typically regard solar energy synonymously with photovoltaic power generation. However, solar energy can also be harvested with Concentrating Solar Power (CSP) plants, which can be dispatchable if equipped with thermal storage. Accounting for this dispatchable use of the variable solar resource can change the balancing requirements at any solar energy penetration level. In this paper, we present an application of the high resolution energy system model REMix to a set of European supply scenarios with theoretical VRE shares ranging from 0-140%, three solar-to-wind ratios, with CSP included in the solar share. We evaluate balancing measures, curtailments and costs and compare the findings to previous results in which CSP is regarded a backup option among other dispatchable power plants. The results show that CSP potentials in Europe are widely exploited in most scenarios. System costs are found to be lowest for wind dominated systems or balanced mixes of wind and solar and for an overall VRE share between 40% for a low and 80% for a high scenario of the future CO 2 emission certificate price. The comparison with previous results shows that storage capacity is the only system variable that is significantly affected by allocating CSP to the VRE resources category. It is reduced by 24% on average across all VRE shares and proportions and by around 80% at most.

The prospect of irreversible environmental alterations and an increasingly volatile climate pressurises societies to reduce greenhouse gas emissions, thereby mitigating climate change impacts. As global electricity demand continues to grow, particularly if considering a future with increased electrification of heat and transport sectors, the imperative to decarbonise our electricity supply becomes more urgent. This letter implements outputs of a detailed power system optimisation model into a prospective life cycle analysis framework in order to present a life cycle analysis of 44 electricity scenarios for Europe in 2050, including analyses of systems based largely on low-carbon fossil energy options (natural gas, and coal with carbon capture and storage (CCS)) as well as systems with high shares of variable renewable energy (VRE) (wind and solar). VRE curtailments and impacts caused by extra energy storage and transmission capabilities necessary in systems based on VRE are taken into account. The results show that systems based largely on VRE perform much better regarding climate change and other impact categories than the investigated systems based on fossil fuels. The climate change impacts from Europe for the year 2050 in a scenario using primarily natural gas are 1400 Tg CO 2 -eq while in a scenario using mostly coal with CCS the impacts are 480 Tg CO 2 -eq. Systems based on renewables with an even mix of wind and solar capacity generate impacts of 120-140 Tg CO 2 -eq. Impacts arising as a result of wind and solar variability do not significantly compromise the climate benefits of utilising these energy resources. VRE systems require more infrastructure leading to much larger mineral resource depletion impacts than fossil fuel systems, and greater land occupation impacts than systems based on natural gas. Emissions and resource requirements from wind power are smaller than from solar power.

Mitigation-Process Integrated Assessment Models (MP-IAMs) are used to analyze long-term transformation pathways of the energy system required to achieve stringent climate change mitigation targets. Due to their substantial temporal and spatial aggregation, IAMs cannot explicitly represent all detailed challenges of integrating the variable renewable energies (VRE) wind and solar in power systems, but rather rely on parameterized modeling approaches. In the ADVANCE project, six international modeling teams have developed new approaches to improve the representation of power sector dynamics and VRE integration in IAMs. In this study, we qualitatively and quantitatively evaluate the last years' modeling progress and study the impact of VRE integration modeling on VRE deployment in IAM scenarios. For a comprehensive and transparent qualitative evaluation, we first develop a framework of 18 features of power sector dynamics and VRE integration. We then apply this framework to the newlydeveloped modeling approaches to derive a detailed map of strengths and limitations of the different approaches. For the quantitative evaluation, we compare the IAMs to the detailed hourlyresolution power sector model REMIX. We find that the new modeling approaches manage to represent a large number of features of the power sector, and the numerical results are in reasonable agreement with those derived from the detailed power sector model. Updating the power sector representation and the cost and resources of wind and solar substantially increased wind and solar shares across models: Under a carbon price of 30$/tCO2 in 2020 (increasing by 5% per year), the model-average cost-minimizing VRE share over the period 2050-2100 is 62% of electricity generation, 24%-points higher than with the old model version. Highlights: We develop a comprehensive framework to evaluate power sector modeling in IAMs  We evaluate 6 new modeling approaches to represent variability of wind and solar  Most IAMs now represent key power sector dynamics, as shown by hourly model REMIX  Previous integration modeling was in many of the analyzed IAMs too restrictive  IAMs with new approaches show on average 24%-points higher wind/solar shares than before Keywords:Integrated assessment models (IAM); variable renewable energy (VRE); wind and solar power; system integration; power sector model; flexibility options (storage, transmission grid, demand response); model evaluation; model validation.3

We analyzed the magnitude, the trends and the uncertainties of fossil-fuel CO₂ emissions in the European Union 25 member states (hereafter EU-25), based on emission inventories from energy-use statistics. The stability of emissions during the past decade at EU-25 scale masks decreasing trends in some regions, offset by increasing trends elsewhere. In the recent 4 years, the new Eastern EU-25 member states have experienced an increase in emissions, reversing after a decade-long decreasing trend. Mediterranean and Nordic countries have also experienced a strong acceleration in emissions. In Germany, France and United Kingdom, the stability of emissions is due to the decrease in the industry sector, offset by an increase in the transportation sector. When four different inventories models are compared, we show that the between-models uncertainty is as large as 19% of the mean for EU-25, and even bigger for individual countries. Accurate accounting for fossil CO₂ emissions depends on a clear understanding of system boundaries, i.e. emitting activities included in the accounting. We found that the largest source of errors between inventories is the use of distinct systems boundaries (e.g. counting or not bunker fuels, cement manufacturing, nonenergy products). Once these inconsistencies are corrected, the between-models uncertainty can be reduced down to 7% at EU-25 scale. The uncertainty of emissions at smaller spatial scales than the country scale was analyzed by comparing two emission maps based upon distinct economic and demographic activities. A number of spatial and temporal biases have been found among the two maps, indicating a significant increase in uncertainties when increasing the resolution at scales finer than ≈200 km. At 100 km resolution, for example, the uncertainty of regional emissions is estimated to be 60 g C m−2 yr−1, up to 50% of the mean. The uncertainty on regional fossil-fuel CO₂ fluxes to the atmosphere could be reduced by making accurate ¹⁴C measurements in atmospheric CO₂, and by combining them with transport models

Abstract. In this study the sensitivity of the model performance of the chemistry transport model (CTM) LOTOS-EUROS to the description of the temporal variability of emissions was investigated. Currently the temporal release of anthropogenic emissions is described by European average diurnal, weekly and seasonal time profiles per sector. These default time profiles largely neglect the variation of emission strength with activity patterns, region, species, emission process and meteorology. The three sources dealt with in this study are combustion in energy and transformation industries (SNAP1), nonindustrial combustion (SNAP2) and road transport (SNAP7). First of all, the impact of neglecting the temporal emission profiles for these SNAP categories on simulated concentrations was explored. In a second step, we constructed more detailed emission time profiles for the three categories and quantified their impact on the model performance both separately as well as combined. The performance in comparison to observations for Germany was quantified for the pollutants NO 2 , SO 2 and PM 10 and compared to a simulation using the default LOTOS-EUROS emission time profiles. The LOTOS-EUROS simulations were performed for the year 2006 with a temporal resolution of 1 h and a horizontal resolution of approximately 25 × 25km 2 .In general the largest impact on the model performance was found when neglecting the default time profiles for the three categories. The daily average correlation coefficient for instance decreased by 0.04 (NO 2 ), 0.11 (SO 2 ) and 0.01 (PM 10 ) at German urban background stations compared to the default simulation. A systematic increase in the correlation coefficient is found when using the new time profiles. The size of the increase depends on the source category, component and station. Using national profiles for road transport showed important improvements in the explained variability over the weekdays as well as the diurnal cycle for NO 2 . The largest impact of the SNAP1 and 2 profiles were found for SO 2 . When using all new time profiles simultaneously in one simulation, the daily average correlation coefficient increased by 0.05 (NO 2 ), 0.07 (SO 2 ) and 0.03 (PM 10 ) at urban background stations in Germany. This exercise showed that to improve the performance of a CTM, a better representation of the distribution of anthropogenic emission in time is recommendable. This can be done by developing a dynamical emission model that takes into account regional specific factors and meteorology.

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