Energy-socio-economic-environmental modelling for the EU energy and post-COVID-19 transitions.

Relevant energy questions have arisen because of the COVID-19 pandemic. The pandemic shock leads to emissions' reductions consistent with the rates of decrease required to achieve the Paris Agreement goals. Those unforeseen drastic reductions in emissions are temporary as long as they do not involve structural changes. However, the COVID-19 consequences and the subsequent policy response will affect the economy for decades. Focusing on the EU, this discussion article argues how recovery plans are an opportunity to deepen the way towards a low-carbon economy, improving at the same time employment, health, and equity and the role of modelling tools. Long-term alignment with the low-carbon path and the development of a resilient transition towards renewable sources should guide instruments and policies, conditioning aid to energy-intensive sectors such as transport, tourism, and the automotive industry. However, the potential dangers of short-termism and carbon leakage persist. The current energy-socio-economic-environmental modelling tools are precious to widen the scope and deal with these complex problems. The scientific community has to assess disparate, non-equilibrium, and non-ordinary scenarios, such as sectors and countries lockdowns, drastic changes in consumption patterns, significant investments in renewable energies, and disruptive technologies and incorporate uncertainty analysis. All these instruments will evaluate the cost-effectiveness of decarbonization options and potential consequences on employment, income distribution, and vulnerability.

Towards energy transition in Tunisia: Sustainability assessment of a hybrid concentrated solar power and biomass plant.

Electricity demand in the Middle East and North Africa (MENA) region increases at a rate of 6-8% per year. It is expected to double by 2020 and triple by 2030. Renewable electricity ensures climate protection and energy security. This work presents a sustainability assessment of CSP hybridization with biomass technology to be installed in Tunisia. Environmental impacts have been assessed by Life Cycle Analysis (LCA). For socioeconomic impacts, a Multiregional Input-Output (MRIO) analysis was used to estimate the production of goods and services, value added and employment creation. Regarding the results, the system reports 22 gCO2eq per kWh. The most important component in terms of emissions is the gasifier system, due to biomass transport. Socioeconomic results show important impacts for employment creation in Tunisia, coming essentially from the O&M phase. The multiplier effect of the direct investment for production of goods and services amounts to 2.4 (3.5 accounting induced effects). Domestic value added in investment is low, only 28.9% of the overall value added created. Thus, increasing the national content of the investment stage would bring additional local benefits. Using extended MRIO, CO2 emissions have also been calculated and differences in the CO2 emission with both methodologies are discussed.

Environmental footprint of a road pavement rehabilitation service in Spain.

Road surfaces are subject to wear and tear due to materials ageing, weathering and the action of road traffic. Periodic rehabilitation or reconstruction is needed in order to restore them. This manuscript presents an environmental assessment of a traditional road pavement rehabilitation technique (with hot mix asphalt) in Spain by means of a life cycle approach. The environmental footprint method was selected for presenting the results, which have a similar range as those obtained in earlier studies. Extraction of raw materials and the manufacturing of processed materials are the stages with the most environmental impacts. Therefore, the use of recycled asphalts in an adequate percentage is advisable for reducing the total environmental impact. This is the first complete study carried out in Spain. Its results could be used as a baseline for comparison with both newer restoration techniques and the use of advanced materials in the country.

CFD modelling of air quality in Pamplona City (Spain): Assessment, stations spatial representativeness and health impacts valuation.

A methodology based on CFD-RANS simulations (WA CFD-RANS, Weighted Averaged Computational Fluid Dynamic-Reynolds-Averaged Navier-Stokes simulations) which includes appropriate modifications, has been applied to compute the annual, seasonal, and hourly average concentration of NO2 and NOX throughout the city of Pamplona (Spain) at pedestrian level during 2016. The results have been evaluated using measurements provided both by the city's network of air quality monitoring stations and by a network of mobile microsensors carried around by cyclists during their daily commutes, obtaining a maximum relative error lower than 30% when computing NO2 annual average concentrations. The model has taken into account the actual city layout in three dimensions, as well as the traffic emissions. The resulting air pollution maps provided information critical for studying the traffic-related health effects of NO2 and their associated external costs in the city of Pamplona and the spatial representativeness of the current network of air quality monitoring stations (it has not been carried out for an entire city to date). The developed methodology can be applied to similar cities, providing useful information for the decision-makers.

Background qualitative analysis of the European Reference Life Cycle Database (ELCD) energy datasets - part I: fuel datasets.

INTRODUCTION: The aim of this study is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) fuel datasets. CASE DESCRIPTION: The revision is based on the data quality indicators described by the ILCD Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. DISCUSSION AND EVALUATION: Results show that ELCD fuel datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the fuel-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. CONCLUSIONS: Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD fuel datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall DQR of databases.

Method applied to the background analysis of energy data to be considered for the European Reference Life Cycle Database (ELCD).

Under the framework of the European Platform on Life Cycle Assessment, the European Reference Life-Cycle Database (ELCD - developed by the Joint Research Centre of the European Commission), provides core Life Cycle Inventory (LCI) data from front-running EU-level business associations and other sources. The ELCD contains energy-related data on power and fuels. This study describes the methods to be used for the quality analysis of energy data for European markets (available in third-party LC databases and from authoritative sources) that are, or could be, used in the context of the ELCD. The methodology was developed and tested on the energy datasets most relevant for the EU context, derived from GaBi (the reference database used to derive datasets for the ELCD), Ecoinvent, E3 and Gemis. The criteria for the database selection were based on the availability of EU-related data, the inclusion of comprehensive datasets on energy products and services, and the general approval of the LCA community. The proposed approach was based on the quality indicators developed within the International Reference Life Cycle Data System (ILCD) Handbook, further refined to facilitate their use in the analysis of energy systems. The overall Data Quality Rating (DQR) of the energy datasets can be calculated by summing up the quality rating (ranging from 1 to 5, where 1 represents very good, and 5 very poor quality) of each of the quality criteria indicators, divided by the total number of indicators considered. The quality of each dataset can be estimated for each indicator, and then compared with the different databases/sources. The results can be used to highlight the weaknesses of each dataset and can be used to guide further improvements to enhance the data quality with regard to the established criteria. This paper describes the application of the methodology to two exemplary datasets, in order to show the potential of the methodological approach. The analysis helps LCA practitioners to evaluate the usefulness of the ELCD datasets for their purposes, and dataset developers and reviewers to derive information that will help improve the overall DQR of databases.

Background qualitative analysis of the European reference life cycle database (ELCD) energy datasets - part II: electricity datasets.

The aim of this paper is to identify areas of potential improvement of the European Reference Life Cycle Database (ELCD) electricity datasets. The revision is based on the data quality indicators described by the International Life Cycle Data system (ILCD) Handbook, applied on sectorial basis. These indicators evaluate the technological, geographical and time-related representativeness of the dataset and the appropriateness in terms of completeness, precision and methodology. Results show that ELCD electricity datasets have a very good quality in general terms, nevertheless some findings and recommendations in order to improve the quality of Life-Cycle Inventories have been derived. Moreover, these results ensure the quality of the electricity-related datasets to any LCA practitioner, and provide insights related to the limitations and assumptions underlying in the datasets modelling. Giving this information, the LCA practitioner will be able to decide whether the use of the ELCD electricity datasets is appropriate based on the goal and scope of the analysis to be conducted. The methodological approach would be also useful for dataset developers and reviewers, in order to improve the overall Data Quality Requirements of databases.