• Energy Research

The ongoing energy transition is causing rapid changes in the electricity system and, in consequence, the environmental impacts associated with electricity generation. In parallel, the daily variability of generation increases with higher shares of renewable energies. This affects the potential environmental impacts or benefits of devices with variable load or power, such as electric vehicles, storage systems or photovoltaic home systems. However, recent environmental assessments of the actual benefit of such systems are scarce, with existing assessments majorly using average grid mixes that are frequently outdated and disregard the dynamic nature of renewable generation. This article provides detailed hourly average and marginal electricity mixes for each month of the year, determined for Spain as an illustrative country with a diversified (renewable) power generation portfolio that experienced a rapid change in the last years. These are combined with specific life-cycle emission factors for each generation technology. Main drivers for the impacts of the marginal mix turn out to be natural gas plants and imports, but also pumped hydropower due to its comparably low storage efficiency. Applied to a hypothetical photovoltaic rooftop installation, the differences between environmental assessments on hourly and on annual basis are found to be surprisingly low when assuming that the generated electricity replaces the average grid mix, but substantial when considering the marginal generation mix (i.e., the generation technologies that respond to a change in demand at a given time). This highlights the importance of considering the dynamics of the electricity system and the corresponding marginal electricity mixes when optimizing flexible load or generation technologies under environmental aspects.

Abstract Many countries are implementing energy policies that focus on the transformation of national power generation mixes into highly efficient and sustainable systems. In the case of the Spanish electricity sector, regulations applicable to existing coal thermal plants and the proximity to the end of the lifetime of nuclear power plants arise as critical concerns to be addressed. In this respect, a sensible energy strategy is required in order to fill the future gap of coal and nuclear power plants. Within this context, this work applies a novel methodological framework for the prioritisation of 15 energy scenarios formulated for power generation in Spain. In addition to a business-as-usual scenario, alternative ones are built based on potential restrictions on fossil-based technologies and lifetime extensions of coal and nuclear power plants. The novel multi-criteria decision analysis approach for enhanced, sustainability-oriented energy planning is based on the combined use of energy systems modelling, life cycle assessment, and data envelopment analysis. Besides conventional techno-economic results, the evolution of life-cycle indicators endogenously integrated into the energy system model of Spain is provided. The subsequent use of a dynamic data envelopment analysis model leads to identify and rank the most suitable energy scenarios according to sustainability criteria.

Dr. Martín-Gamboa would like to thank the Regional Government of Madrid for financial support (2019-T2/AMB-15713). Ana Cláudia Dias would like to thank FCT/MCTES for the contract CEECIND/02174/2017 and for the financial support to CESAM (UIDB/50017/2020+UIDP/50017/2020) through national funds. A key goal in sustainable supply chain management is the minimisation of risk across supply chains. However, this is jeopardised by underdeveloped aspects such as social risk management, especially in the case of energy systems as they involve complex supply chains. This article constitutes the first time that Social Life Cycle Assessment (S-LCA) is used to lay the foundation for a methodological framework to define, assess and prioritise strategies oriented towards the minimisation of social life-cycle impacts across the supply chain of energy products. This framework combines S-LCA, a novel approach to the definition of alternative supply chain strategies, and multi-criteria decision analysis (MCDA). It was demonstrated through a case study of bioelectricity in Portugal by defining and assessing fifteen strategies on the specific supply chains of oil and fertilisers to check their suitability to enhance the system's social life-cycle performance. The weighted sum method (WSM) and Data Envelopment Analysis (DEA) were used as MCDA tools to further support decision-making by prioritising strategies. According to the results for a set of six social indicators, the strategies proposed on the supply of oil and nitrogen-based fertilisers were deemed suitable trade-off solutions to mitigate the social life-cycle impact of the bioelectricity system.

Abstract Two energy production systems using short rotation coppice (SRC) willow chips were evaluated: bioethanol production via enzyme-catalyzed hydrolysis and electricity production following a biomass integrated gasification combined cycle scheme. The most relevant input and output flows of each renewable energy system were identified and quantified throughout the life cycle from the SRC willow plantation to the bioenergy plant gate. Both bioenergy systems were found to be feasible from an energy perspective. Moreover, they entailed environmental benefits when compared to conventional energy practices. However, improvements relating to not only willow biomass production but also bioenergy conversion-related activities should be considered. In this respect, the process steps that provided the highest environmental impacts have been highlighted. Furthermore, well-to-wheels environmental characterization results were estimated and compared for the bioethanol and bioelectricity scenarios. In this sense, the identification of the most appropriate processing route for willow chips was found to be highly dependent on the impact category under assessment. In particular, global warming and energy parameters led to opposite conclusions. While the bioethanol scenario arose as the potentially best choice from an energy perspective, the bioelectricity scenario seems to be a more suitable alternative when global warming is the decisive factor.

Abstract Environmental criteria have to be taken into account when it comes to selecting a specific building component among a set of candidates with the same function. This article presents a methodological approach – based on both Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) – for the selection of building components according to their environmental impact efficiency. A three-step LCA + DEA approach is proposed and tested through a case study for 175 external walls. The three steps of this approach involve data collection, life cycle impact assessment, and DEA of the sample of building components using environmental impacts as DEA inputs. Overall, from the availability of multiple data on the material and energy flows of each building component, the method provides decision makers with eco-efficiency scores and environmental benchmarks. A cautious definition of the set of candidates is critical, as relative efficiency scores are calculated. Data availability and functional homogeneity regarding the building components evaluated are the key requirements for the general use of the method. The three-step LCA + DEA approach proposed is proven to be a useful method to enhance decision making and environmental benchmarking in the building sector.

The energy sector is still dominated by the use of fossil resources. In particular, natural gas represents the third most consumed resource, being a significant source of electricity in many countries. Since electricity production in natural gas combined cycle (NGCC) plants provides some benefits with respect to other non-renewable technologies, it is often seen as a transitional solution towards a future low‑carbon power generation system. However, given the environmental profile and operational variability of NGCC power plants, their eco-efficiency assessment is required. In this respect, this article uses a novel combined Life Cycle Assessment (LCA) and dynamic Data Envelopment Analysis (DEA) approach in order to estimate -over the period 2010-2015- the environmental impact efficiencies of 20 NGCC power plants located in Spain. A three-step LCA+DEA method is applied, which involves data acquisition, calculation of environmental impacts through LCA, and the novel estimation of environmental impact efficiency (overall- and term-efficiency scores) through dynamic DEA. Although only 1 out of 20 NGCC power plants is found to be environmentally efficient, all plants show a relatively good environmental performance with overall eco-efficiency scores above 60%. Regarding individual periods, 2011 was -on average- the year with the highest environmental impact efficiency (95%), accounting for 5 efficient NGCC plants. In this respect, a link between high number of operating hours and high environmental impact efficiency is observed. Finally, preliminary environmental benchmarks are presented as an additional outcome in order to further support decision-makers in the path towards eco-efficiency in NGCC power plants.

This study evaluates the environmental and thermodynamic performance of six coal-fired power plants with CO2 capture and storage. The technologies examined are post-combustion capture using monoethanolamine, membrane separation, cryogenic fractionation and pressure swing adsorption, pre-combustion capture through coal gasification, and capture performing conventional oxy-fuel combustion. The incorporation of CO2 capture is evaluated both on its own and in combination with CO2 transport and geological storage, with and without beneficial use. Overall, we find that pre-combustion CO2 capture and post-combustion through membrane separation present relatively low life-cycle environmental impacts and high exergetic efficiencies. When accounting for transport and storage, the environmental impacts increase and the efficiencies decrease. However, a better environmental performance can be achieved for CO2 capture, transport and storage when incorporating beneficial use through enhanced oil recovery. The performance with enhanced coal-bed methane recovery, on the other hand, depends on the impact categories evaluated. The incorporation of methane recovery results in a better thermodynamic performance, when compared to the incorporation of oil recovery. The cumulative energy demand shows that the integration of enhanced resource recovery strategies is necessary to attain favourable life-cycle energy balances.

Life Cycle Assessment (LCA) is often used for the environmental evaluation of agri-food systems due to its holistic perspective. In particular, the assessment of milk production at farm level requires the evaluation of multiple dairy farms to guarantee the representativeness of the study when a regional perspective is adopted. This article shows the joint implementation of LCA and Data Envelopment Analysis (DEA) in order to avoid the formulation of an average farm, therefore preventing standard deviations associated with the use of average inventory data while attaining the characterization and benchmarking of the operational and environmental performance of dairy farms. Within this framework, 72 farms located in Galicia (NW Spain) were subject to an LCA+DEA study which led to identify those farms with an efficient operation. Furthermore, target input consumption levels were benchmarked for each inefficient farm, and the corresponding target environmental impacts were calculated so that eco-efficiency criteria were verified. Thus, average reductions of up to 38% were found for input consumption levels, leading to impact reductions above 20% for every environmental impact category. Finally, the economic savings arising from efficient farming practices were also estimated. Economic savings of up to 0.13€ per liter of raw milk were calculated, which means extra profits of up to 40% of the final raw milk price.