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Abstract. Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27+UK). We integrate recent emission inventory data, ecosystem process-based model results, and inverse modelling estimates over the period 1990–2018. BU and TD products are compared with European National GHG Inventories (NGHGI) reported to the UN climate convention secretariat UNFCCC in 2019. For uncertainties, we used for NGHGI the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines recommendations. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model specific uncertainties when reported. In comparing NGHGI with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. TD total inversions estimates give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions and geological sources together account for the gap between NGHGI and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1 respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1 respectively, compared to 0.9 Tg N2O yr−1 from the BU data. The TU and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at EU+UK scale and at national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288969 (Petrescu et al., 2020).

Abstract. Regional land carbon budgets provide insights on the spatial distribution of the land uptake of atmospheric carbon dioxide, and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions, due to different definitions and component fluxes reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers, that connect CO2 uptake in one area with its release in another also requires better definition and protocols to reach harmonized regional budgets that can be summed up to the globe and compared with the atmospheric CO2 growth rate and inversion results. In this study, for the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims as an update of regional carbon budgets over the last two decades based on observations, for 10 regions covering the globe, with a better harmonization that the precursor project, we provide recommendations for using atmospheric inversions results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes and land use fluxes.

Abstract The combined production of electricity, heat and cold by a polygeneration system connected to a district heating and cooling network can provide high energy utilization efficiency. The inherent complexity of simultaneous production of different services and the high variability in the energy demand make combined cooling and heating systems performance highly dependent on the operational strategy. In this paper, an operational optimization method based on the moving average of real-time measurements of energy demands and ambient conditions is proposed. Real energy demand data from a district heating and cooling network close to Barcelona, Spain, are used to test the method. A complex polygeneration system is considered, consisting of an internal combustion engine, a double-effect absorption chiller, an electric chiller, a boiler and a cooling tower. A detailed modelling of the system is provided, considering partial load behavior of the components and ambient conditions effects. Results of the real-time optimal management are discussed and compared to traditional operational strategies and to the ideal optimal management achievable with perfectly accurate forecast of energy demands. Moreover, the optimal width of the window adopted for the moving average of real-time data is identified.

The increasing demand for energy and commodities has led to escalating greenhouse gas emissions, the chief of which is represented by carbon dioxide (CO2). Blue hydrogen (H2), a low-carbon hydrogen produced from natural gas with carbon capture technologies applied, has been suggested as a possible alternative to fossil fuels in processes with hard-to-abate emission sources, including refining, chemical, petrochemical and transport sectors. Due to the recent international directives aimed to combat climate change, even existing hydrogen plants should be retrofitted with carbon capture units. To optimize the process economics of such retrofit, it has been proposed to remove CO2 from the pressure swing adsorption (PSA) tail gas to exploit the relatively high CO2 concentration. This study aimed to design and numerically investigate a vacuum pressure swing adsorption (VPSA) process capable of capturing CO2 from the PSA tail gas of an industrial steam methane reforming (SMR)-based hydrogen plant using NaX zeolite adsorbent. The effect of operating conditions, such as purge-to-feed ratio and desorption pressure, were evaluated in relation to CO2 purity, CO2 recovery, bed productivity and specific energy consumption. We found that conventional cycle configurations, namely a 2-bed, 4-step Skarstrom cycle and a 2-bed, 6-step modified Skarstrom cycle with pressure equalization, were able to concentrate CO2 to a purity greater than 95% with a CO2 recovery of around 77% and 90%, respectively. Therefore, the latter configuration could serve as an efficient process to decarbonize existing hydrogen plants and produce blue H2.

China is confronted with an unprecedented water crisis regarding its quantity and quality. In this study, we quantified the dynamics of China?s embodied water use and chemical oxygen demand (COD) discharge from 2010 to 2015. The analysis was conducted with the latest available water use data across sectors in primary, secondary and tertiary industries and input?output models. The results showed that (1) China?s water crisis was alleviated under urbanisation. Urban consumption occupied the largest percentages (over 30%) of embodied water use and COD discharge, but embodied water intensities in urban consumption were far lower than those in rural consumption. (2) The ?new normal? phase witnessed the optimisation of China?s water use structures. Embodied water use in light-manufacturing and tertiary sectors increased while those in heavy-manufacturing sectors (except chemicals and transport equipment) dropped. (3) Transformation of China?s international market brought positive effects on its domestic water use. China?s water use (116?80 billion tonnes (Bts))(9) and COD discharge (3.95?2.22 million tonnes (Mts)) embodied in export tremendously decreased while its total export values (11?25 trillion CNY) soared. Furthermore, embodied water use and COD discharge in relatively low-end sectors, such as textile, started to transfer from international to domestic markets when a part of China?s production activities had been relocated to other developing countries.

Abstract The sustainable indicators are characterized by a low degree of aggregation and a high amount of information. An indicator must show a synthetic representation of a real environmental, by using a value or a parameter, so that they can be easily used by policy makers. It is necessary to connect, therefore, the various systems in an appropriately integrated sustainable system. The indicators need to be aggregated based on the structure of the data. Each indicator must to be defined through a weight with reference to another weighted indicator. In this paper is illustrated the calculation of the assigned weights that uses a procedure based on fuzzy logic and to define a model that allows us to estimate the sustainability of a city. The final result is, therefore, a combination of values assigned by expert opinion for the various criteria, processed using fuzzy logic to obtain a weight with significant objectivity and as it is possible to estimate the sustainability of the city through the weights.

Hybrid electric propulsion in the aviation field is becoming an effective alternative propulsion technology with potential advantages, including fuel savings, lower pollution, and reduced noise emission. On the one hand, the aeroengine manufacturers are working to improve fuel consumption and reduce pollutant emissions with new combustion systems; on the other hand, much attention is given to reducing the weight of the batteries increasing the energy density. Hybrid electric propulsion systems (HEPS) can take advantage of the synergy between two technologies by utilizing both internal combustion engines (ICEs) and electric motors (EMs) together, each operating at their respective optimum conditions. In the present work, some numerical investigations were carried out by using a zero-dimensional code able to simulate the flight mission of a turboprop aircraft, comparing fuel consumption and pollutant emissions of the original engine with other two smaller gas turbines working in hybrid configuration. An algorithm has been implemented to calculate the weight of the batteries for the different configurations examined, evaluating the feasibility of the hybrid propulsion system in terms of number of non-revenue passengers.