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Multi-energy systems that combine different energy sources and carriers to improve the overall technical, economic, and environmental performance can boost the energy transition. In this paper we posit an innovative multi-energy system for green hydrogen production that achieves negative carbon emissions by combining bio-fuel membrane-integrated steam reforming and renewable electricity electrolysis. The system produces green hydrogen and carbon dioxide, both at high purity. We use thermo-chemical models to determine the system performance and optimal working parameters. Specifically, we focus on its ability to achieve negative carbon emissions. The results show that in optimal operating conditions the system can capture up to 14.1 g of CO 2 per MJ of stored hydrogen and achieves up to 70% storage efficiency. Therefore, we prove that a multi-energy system may reach the same efficiency of an average electrolyzer while implementing carbon capture. In the same optimal operating conditions the system converts 7.8 kg of biogas in 1 kg of hydrogen using 3.2 kg of oxygen coming from the production of 6.4 kg of hydrogen through the electrolyzer. With such ratios we estimate that the conversion of all the biogas produced in Europe with our system, could result in the installation of additional dedicated 800 GWp - 1280 GWp of photovoltaic power, or of 266 GWp - 532 GWp of wind power, without affecting the distribution grid and covering yearly the 45% of the worldwide hydrogen demand while removing from the atmosphere more than 2% of the European carbon dioxide emissions. • A Multi-energy system that produce hydrogen with negative CO 2 emissions. • More than 800 GWp of new photovoltaic power without grid burdens. • More than 800 GWp of new wind power without grid burdens. • Capture 56 Mton/year of CO 2 from the atmosphere. [ABSTRACT FROM AUTHOR]

Trees absorb CO 2 and reduce the impact of GHGs. This paper deals about the carbon uptake dynamics produced by the management of unused lands as tool to help the fulfilment of international commitments on atmospheric CO 2. The paper introduces a new perspective of using the unused lands around Municipalities to compensate the carbon emissions of urban contexts, according to the Sustainable Energy Action Plans as answer to climate change, already approved by the most part of Cities in Europe. The model of the carbon dynamics is based on a genetic algorithm which allows to find the sequence of operations on the unused land in space (portions of the land) and time (rotation of cuts and plantations) to ensure the reaching of a given outcome in terms of carbon captured. The algorithm, therefore, behaves as design support of land management, enriching the literature available for the sector. The paper identifies two possible original scenarios of storing carbon referred as " emergency " and " constant rate "; the first produces after fifty years a maximum carbon uptake of the order of 100 tC/ha while the second a maximum uptake rate of the order of 2 tC/(year ha), after an initial start-up period of 40–50 years. • Mathematical model to evaluate tree growth and carbon sink from reforestation. • Optimization model to manage the carbon uptake in different scenarios. • Forest represents an effective way to remove carbon from atmosphere. • Carbon stock per unit of unused areas around cities and urban area. • Climate mitigation tool suitable by municipality in the context of SECAPs. [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]

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]

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]