Plastic pollution is pervasive in our environment, with impacts seen across ecosystems and taxa. While plastic has become an integral part of our daily lives, not all of it is readily apparent, making it challenging to effectively reduce plastic pollution. A hidden source of plastic pollution is plastic-based printing, which is used on a wide range of items including single-use products like plastic food containers and multi-use plastic items like credit cards. This also includes items that we would not consider to be sources of plastic pollution such as glass bottles with surface printing. The widespread use of this printing, therefore, results in even non-plastic items contributing to plastic pollution, potentially contaminating recycling streams and exacerbating nano- and microplastic (NMP) dispersion. Given the challenges of remediating NMP plastic pollution once it has entered the environment, prevention becomes paramount. With significant efforts underway to reduce plastic production, it is important to take a holistic approach to redesigning objects and materials to avoid false solutions, which will continue to contribute to ecosystem degradation and planetary boundary transgressions. To make meaningful progress and avoid ineffective solutions, it is imperative to consider all sources of plastic pollution, including those concealed within apparently non-plastic objects.

The ability to provide adequate nutrition is considered a key factor in evaluating the sustainability of foods and diets. Nutrient indices are used as functional units (FU) in life cycle assessment of foods to include nutritional performance in the environmental assessment of a product. Several general and food-group-specific nutrient indices exist but many lack validation, particularly when used as FU. In addition, the nutrient selection strategies and reference units for nutrient intake can vary considerably among studies. To validate intake-based product-group-specific nutrient indices previously developed for protein (NR-FIprot) and carbohydrate (NR-FIcarb) foods and for fruits and vegetables (NR-FIveg), we applied principal component analysis to investigate correlations between nutrients in foods and dishes representing a typical Finnish diet. The reference amounts for meal components were based on a plate model that reflected Finnish dietary recommendations. The portion sizes for the different food groups were anchored at 100 g, 135 g and 350 g for proteins, carbohydrates and fruits/vegetables, respectively. Statistical modelling largely validated the NR-FI indices, highlighting protein foods as sources of niacin, vitamin B12 and Se, carbohydrate foods as sources of Mg, Fe and phosphorous, and fruits/vegetables as sources of potassium, vitamin K, vitamin C, fibre and thiamine. However, in contrast to the intake-based approach applied in NR-FIprot, the dietary recommendation-based validation process suggested that fruits and vegetables should be favoured as sources of riboflavin and vitamin B6.

Accumulation of plastic waste is a global issue, and plastic particles are detected in different environments. The recent COVID-19 pandemic has been attributed to significant piling up of plastic waste and debris (including micro- and nano-sized plastic particles), yet the manufacturing of plastic products is still expected to grow. With the continuation of the COVID-19 pandemic, the use and disposal of plastics has resulted in increasing plastic pollution. There has been a lack of research into the effects of climate change on microplastics and, likewise, the effects of microplastics on climate change. This article aims to examine the pros and cons of sustainable alternatives to plastics in addressing the climate change issue. Special attention is devoted to the correlation between climate change and microplastic pollution. This perspective also serves to spawn ideas for mitigating greenhouse gas emissions caused by plastics by identifying the life cycle stages of plastic production.

A variety of established tools are available for agricultural sustainability assessment at global, regional, and farm geographical scales. However, no assessment has been reported in research literature to indicate their ability to provide insights about the most sustainable cropping system at plot level or experimental unit. Despite the environmental and social importance of soil in agricultural systems, many of the sustainability assessments use few or no indicators related to soil properties or processes. Hence, we propose a sustainability assessment methodology oriented to soil-associated agricultural experiments (SMAES) by defining its parameters through simulations and testing the methodology with real data from a fertilization tomato experiment with five treatments: chemical control (CR); organic control (OR); and organic:chemical ratios (OR) of 25:75, 50:50, and 75:25. The distance from the maximum, principal component analysis, and product of weighted indicator techniques were chosen for normalization, weighting, and aggregation in a single index process, respectively. Applying the SMAES methodology, the sustainability level of the treatments followed this sequence: CR (0.95) > O25:C75 (0.73) > O50:C50 (0.60) > O75:C25 (0.55) > OR (0.45). The proposed SMAES methodology allows soil researchers to define the best treatment through the interaction of the environmental, social, and economic dimensions of agricultural systems.

Precise sustainability assessment becomes increasingly important in decision-making, marketing, and regulations. Therefore, reliable and comparable LCA becomes mandatory. Currently, primary data is rarely available due to vastly complex value chains. Secondary data from eco-databases provide a remedy to estimate the sustainability impacts of up- and downstream processes. While giving insights and estimations, this data is seldom fitting exactly to the own processes and lacks comparability. Therefore, this paper proposes a method to close the gap between unreliable secondary data and unavailable primary data. This gap is to be closed by the integration of simulated process data. CAM is a tool during the work preparation to assess the design's manufacturability, decrease set-up times and optimize the NC code. However, integrating DES into LCA is still subject to research and will be discussed in this paper. This paper answers the question of the necessary steps to integrate the simulated production process in an LCA to increase the quality and reliability of sustainability indicators. A method is presented, and the implementation of the steps with the help of a developed assistance system on an example is performed.

Hybrid-electric propulsion is a promising alternative to sustainable aviation and is mainly considered for the commuter and regional aircraft class. However, the development of hybrid-electric propulsion variants is affected by the technology readiness level of electric components. The components’ technology will determine the electrification benefit, compared to a conventional aircraft, and will suggest which is the most beneficial variant and which has a closer entry into service date. Within this work, three different dates are explored, namely 2027, 2030 and 2040, to size three Parallel and three Series hybrid-electric architecture variants using an in-house aircraft sizing tool. All variants are compared to a conventional configuration sized using technological assumptions of 2014, with the main comparison metrics being the aircraft block fuel, energy consumption, direct operating cost and holistic environmental impact. On one hand, the Parallel configurations have reduced maximum take-off mass and mission energy consumption compared to the Series, however, the latter show a greater potential for block fuel reduction and require less onboard energy for the same mission. The annual operating cost evaluation indicates that the Parallel hybrid variant of 2030 has greater operational costs than the respective Series variant; however, it has reduced capital costs compared to the latter, making it more economical to operate considering both costs. Additionally, in the case of an energy recession, both hybrid variants of 2030 show a further cost reduction, with the Series having a total reduction of 10.4% excluding capital costs, compared to the reference aircraft. Moreover, the life cycle assessment shows that the Series variants have a lower environmental impact, both compared to the reference aircraft and the Parallel variants. The former could be up to 59.7% less detrimental to the environment than the reference aircraft, whereas the latter up to 23.9%, with the integration of renewable sources for electricity production. Finally, by the year 2040, the Series variant shows outstanding performance in all comparison metrics, compared to the Parallel and the reference aircraft.

With the topic of sustainability steadily gaining importance and public awareness, there is growing consensus about the need to incorporate environmental considerations in early stage product development (PD). This makes it imperative for PD practitioners to have access to methods and tools, including life cycle assessment (LCA), that support sustainability integration. This paper evaluates existing LCA tools on their ability to cater to the early-stage PD context, by having users apply the tools in practice and exploring their experiences. We find that the challenges to applying LCA in this context emanate primarily from the shortcomings of the tools themselves. Our evaluation metrics for tool critique are derived from a thematic analysis of user interviews we conducted, refined according to information and interaction design principles from human-computer interaction (HCI). This unique approach helps triangulate insights from users with literature, to produce design recommendations for the development of novel LCA tools tailored to the early PD context.

Metal additive manufacturing (AM) is revered for the design freedom it brings, but is it environmentally better or worse than conventional manufacturing? Since few direct comparisons are published, this study compared AM data from life-cycle assessment literature to conventional manufacturing data from the Granta EduPack database. The comparison included multiple printing technologies for steel, aluminum, and titanium. Results showed that metal AM had far higher CO2 footprints per kg of material processed than casting, extrusion, rolling, forging, and wire drawing, so it is usually a less sustainable choice than these. However, there were circumstances where it was a more sustainable choice, and there was significant overlap between these circumstances and aerospace industry use of metal AM. Notably, lightweight parts reducing embodied material impacts, and reducing use-phase impacts through fuel efficiency. Finally, one key finding was the irrelevance of comparing machining to AM per kg of material processed, since one is subtractive and the other is additive. Recommendations are given for future studies to use more relevant functional units to provide better comparisons.

To identify a proper strategy for future feed-efficient pig farming, it is required to evaluate the ongoing selection scenarios. Tools are lacking for the evaluation of pig selection scenarios in terms of environmental impacts to provide selection guidelines for a more sustainable pig production. Selection on residual feed intake (RFI) has been proposed to improve feed efficiency and potentially reduce the associated environmental impacts. The aim of this study was thus to develop a model to account for individual animal performance in life cycle assessment (LCA) methods to quantify the responses to selection. Experimental data were collected from the fifth generation of pig lines divergently selected for RFI (low line, more efficient pigs, LRFI; high line, less efficient pigs, HRFI). The average feed conversion ratio (FCR) and daily feed intake of LRFI pigs were 7% lower than the average of HRFI pigs (P < 0.0001). A parametric model was developed for LCA based on the dietary net energy fluxes in a pig system. A nutritional pig growth tool, InraPorc®, was included as a module in the model to embed flexibility for changes in feed composition, animal performance traits and housing conditions and to simulate individual pig performance. The comparative individual-based LCA showed that LRFI had an average of 7% lower environmental impacts per kilogram live pig at farm gate compared to HRFI (P < 0.0001) on climate change, acidification potential, freshwater eutrophication potential, land occupation and water depletion. High correlations between FCR and all environmental impact categories (>0.95) confirmed the importance of improvement in feed efficiency to reduce environmental impacts. Significant line differences in all impact categories and moderate correlations with impacts (>0.51) revealed that RFI is an effective measure to select for improved environmental impacts, despite lower correlations compared to FCR. Altogether more optimal criteria for efficient environment-friendly selection can then be expected through restructuring the selection indexes from an environmental point of view.

A comparison between electrochemical carbon dioxide conversion and reforestation is presented. By comparing thermodynamic and forestry data, recommendations for technology development can be made.

With the global average temperature steadily increasing due to anthropogenic emission of greenhouse gases into the atmosphere, there has been increasing interest worldwide in new technologies for carbon capture, utilization, and storage (CCUS). This coincides with the decrease in cost of deployment of intermittent renewable electricity sources, specifically solar energy, necessitating development of new methods for energy storage. Carbon dioxide conversion technologies driven by photovoltaics aim to address both these needs. To adequately contribute to greenhouse gas reduction, the carbon dioxide conversion technology deployed should have a substantially higher rate of carbon dioxide removal than planting an equivalent-sized forest. Using consistent methodologies, we analyze the effectiveness of model photovoltaic-driven carbon dioxide conversion technologies that produce liquid alcohols as compared to planting an equivalent forest. This analysis serves to establish an energy use boundary for carbon dioxide conversion technology, in order to be a viable alternative as a net carbon negative technology.

A case study of hard disk drives (HDDs) and rare-earth magnets is presented to show the use of decision support tools to identify and assess the barriers and opportunities for circular business models. Pilot demonstration projects, which showcased HDD circular recovery strategies, were useful as a low-risk opportunity for business model experimentation and to build trust among key supply chain actors.

A case study of hard disk drives and rare-earth magnets is presented to show the use of decision support tools (DSTs) to assess the complex interaction of variables that must be considered when demonstrating the viability of circular business models (CBMs). A mix of quantitative and qualitative DSTs such as life cycle assessment, techno-economic assessment, Ostrom's Framework for social-ecological systems, decision trees, and others were implemented by the iNEMI Value Recovery Project team to overcome many of the identified barriers to circular economy. The DSTs were used to guide stakeholder coordination, create and share environmental, logistical and financial data, and generate decision-making flowcharts which promote circular economic strategies. Demonstration projects were used as a low-risk opportunity for business model experimentation and to build trust among key supply chain actors. The tools highlighted by this case study could be useful for establishing or expanding CBMs for other electronic products or components, especially components containing critical materials.

Europe’s roadmap to a low-carbon economy aims to cut greenhouse gas (GHG) emissions 80% below 1990 levels by 2050. Beef production is an important source of GHG emissions and is expected to increase as the world population grows. LIFE BEEF CARBON is a voluntary European initiative that aims to reduce GHG emissions per unit of beef (carbon footprint) by 15% over a 10-year period on 2172 farms in four large beef-producing countries. Changes in farms beef carbon footprint are normally estimated via simulation modelling, but the methods current models apply differ. Thus, our initial goal was to develop a common modelling framework to estimate beef farms carbon footprint. The framework was developed for a diverse set of Western Europe farms located in Ireland, Spain, Italy and France. Whole farm and life cycle assessment (LCA) models were selected to quantify emissions for the different production contexts and harmonized. Carbon Audit was chosen for Ireland, Bovid-CO2 for Spain and CAP’2ER for France and Italy. All models were tested using 20 case study farms, that is, 5 per country and quantified GHG emissions associated with on-farm live weight gain. The comparison showed the ranking of beef systems gross carbon footprint was consistent across the three models. Suckler to weaning or store systems generally had the highest carbon footprint followed by suckler to beef systems and fattening beef systems. When applied to the same farm, Carbon Audit’s footprint estimates were slightly lower than CAP’2ER, but marginally higher than Bovid-CO2. These differences occurred because the models were adapted to a specific region’s production circumstances, which meant their emission factors for key sources; that is, methane from enteric fermentation and GHG emissions from concentrates were less accurate when used outside their target region. Thus, for the common modelling framework, region-specific LCA models were chosen to estimate beef carbon footprints instead of a single generic model. Additionally, the Carbon Audit and Bovid-CO2 models were updated to include carbon removal by soil and other environmental metrics included in CAP’2ER, for example, acidification. This allows all models to assess the effect carbon mitigation strategies have on other potential pollutants. Several options were identified to reduce beef farms carbon footprint, for example, improving genetic merit. These options were assessed for beef systems, and a mitigation plan was created by each nation. The cumulative mitigation effect of the LIFE BEEF CARBON plan was estimated to exceed the projects reduction target (−15%).