Environmental Impact Of Products Research Articles

Energy Efficiency Improvement for Manufacturing Companies in Latvia

Concerns about climate change and environmental issues are becoming more and more popular nowadays and are causing concerns in everyone's life and beyond. One of significant causes of climate change is energy consumption, especially in the manufacturing sector. Even though, energy efficiency (EE) topic has been extensively discussed, not all EE aims are met. For the manufacturing sector the reason is that EE is often not a top priority for the companies. Currently the companies are also faced with another big challenge – in this digital era of rapidly developing technologies they have to adjust their practices to seize the opportunities provided by digitalization and automatization. Therefore, the aim of this research is to explore how digitization can be combined with EE to promote the resilience and increase performance of manufacturing companies, and how remote data analysis, also by using machine learning tools, can help improve EE. Literature review, content analysis, empirical data analysis and cases studies from real production companies in Latvia are used to achieve the research goals. The results section shows how digital tools and real-time monitoring help assessing the current state of the business and make decisions on changes to future operations, helping to reduce consumption and the environmental impact of production. Manufacturing companies have the potential to improve EE through digitalisation, but the manufacturing processes are complex and Latvian companies are only slowly moving towards digitalisation. Therefore, there is a strong need to examine empirical cases to gather more perspective and to find a way to implement digitalization and EE improvement across all sectors. Conclusions suggest that manufacturing companies should be encouraged to move towards a more unified energy data collection system, enabling more efficient data analysis and proposals for energy efficiency improvements.

Validation of Raman spectroscopic models to verify the origin of Australian beef grown under different production systems

Verification of beef production systems and authentication of origin is becoming increasingly important as consumers base purchase decisions on a greater number of perceived values including the healthiness and environmental impact of products. Previously Raman spectroscopy has been explored as a tool to classify carcases from grass and grain fed cattle. Thus, the aim of the current study was to validate Partial Least Squares Discriminant Analysis (PLS-DA) models created using independent samples from carcases sampled from northern and southern Australian production systems in 2019, 2020 and 2021. Validation of the robustness of discrimination models was undertaken using spectral measures of fat from 585 carcases which were measured in 2022 using a Raman handheld device with a sample excised for fatty acid analysis. PLS-DA models were constructed and then employed to classify samples as either grass or grain fed in a two-class model. Overall, predictions were high with accuracies of up to 95.7% however, variation in the predictive ability was noted with models created for southern cattle yielding an accuracy of 73.2%. While some variation in fatty acids and therefore models can be attributed to differences in genetics, management and diet, the impact of duration of feeding is currently unknown and thus further work is warranted.

Autochthonous Ingredients for Craft Beer Production

Innovation in the beer market focuses on research into the different ingredients that make up this popular and sought-after beverage. Some of these innovations have focused on the use of autochthonous ingredients, which bring added value to products, reduce production costs and environmental impact, and provide beers with special organoleptic characteristics. This study focuses on the use of autochthonous ingredients from the Community of Madrid and the design of four recipes that are suited to these ingredients and consumer demand. In terms of the ingredients used, the micromalting of barley grown in the CM was carried out, while hops (Cascade variety for bittering hops and wild hops Rayo verde Tajuña and Torreta Tajuña for aroma) and yeast strains (Saccharomyces cerevisiae G 520 and G 354) were selected from previous studies, which were also sourced from the CM. For the barley malt, parameters such as protein content were determined, which was at the maximum limit but did not affect the final quality of the beers. The content of α- and β-acids in the hops was also determined, being higher in the Cascade variety. Different physicochemical analyses (GC, aromatic compounds, bitterness, colour, SO2, polyphenols, and antioxidant capacity) were carried out to determine the quality of the beers obtained from the four recipes designed, as well as tastings by a panel of experts and consumers. Finally, two recipes were rated the best by a panel of experts and consumers, where the cereal, hop, and fruit flavours stood out for their aromatic profile.

Considering product life cycle characteristics and industry background in environmental impact analysis and application: a case study of a television.

Life cycle assessment (LCA) is widely used to evaluate product's life cycle environmental impact and identify the environmental weaknesses. However, it is difficult for existing LCA software to perform flexible LCA analysis based on the product life cycle characteristics and industry background. Meanwhile, under the existing LCA research model, product designers and manufacturers are usually not LCA evaluators, resulting in a certain time gap between the evaluation results and product improvement. Designers with less experience in green design often find it difficult to identify high environmental impact links in products at different life cycle stages and product levels, and updated products are challenging to meet various environmental restrictions. This paper establishes a multi-module product life cycle analysis model that combines product industry background that includes basic information, assessment information, structural information, and restriction information to achieve the multi-scenario of product LCA in different dimensions in a typical domain. The calculated mechanism of the dynamic power emission factor is built according to the service time and space dimensions. The proposed method forms an integrated environmental performance evaluation of household appliance (EPEHA) system. A software assessment and an optimization method are proposed to improve the EPEHA system. The results of this study show that these proposed methods can improve the timeliness and diversity of results analysis of product LCA in the field of household appliances in China. The universal data exchange format and simple operation interface of the EPEHA system enable people related to the product to quickly understand the environmental impact of the product in different scenarios, even if they lack green design knowledge and professional software training.

Sustainable Denim Design Using Giza Cotton

Designing denim fabrics that will have a longer wear life by combining Giza cotton, one of the best cottons in the world, with yarn technology, without using any reinforced synthetic fibers. Giza cotton will be used in the products to be developed specifically for the project. High strength yarns will be obtained with the fiber length of Giza cotton and the appropriate twist value to be applied. It is aimed that the fabrics produced from these threads will have a longer lifespan than normal cotton threads. One of the most important steps for the continuity of sustainable production will be that the produced product is recyclable and can be used for a longer time. In this way, a significant decrease in the carbon and water footprint resulting from production will be achieved. The environmental impact of production will be minimized.

Potential Applications of Yeast Biomass Derived from Small-Scale Breweries

Yeast biomass, a brewery by-product of the world’s substantial alcohol beverage industry, finds successful applications in the fodder industry and food additive production. This is attributed to its rich nutritional profile that comprises high protein and vitamin content. Nonetheless, in small-scale breweries, yeast slurries present a significant challenge, as the quantities obtained are insufficient to attract the attention of the food industry. The disposal of yeast contributes substantially to the organic load of wastewater (approximately 40%) and elevates water consumption (3–6 hL/hL of beer), consequently escalating production costs and environmental impact. In recent years, diverse potential applications of products derived from yeast biomass have emerged, encompassing the substitution of sera in cell culture media, the fortification of animal feed with vitamins and selenium, the utilization of beta-glucan in low-fat food products, and the development of functional foods incorporating yeast-derived peptides. These peptides exhibit the potential to safeguard the gastric mucosa, prevent hypertension, and address neurodegenerative disorders. The rising demand for value-added products derived from yeast underscores the potential profitability of processing yeast from small breweries. Due to the high equipment costs associated with yeast biomass fractionation, the establishment of specialized facilities in collaboration with multiple small breweries appears to be the most optimal solution.

Integrated Omics Approach: Revealing the Mechanism of Auxenochlorella pyrenoidosa Protein Extract Replacing Fetal Bovine Serum for Fish Muscle Cell Culture.

The process of producing cell-cultured meat involves utilizing a significant amount of culture medium, including fetal bovine serum (FBS), which represents a considerable portion of production expense while also raising environmental and safety concerns. This study demonstrated that supplementation with Auxenochlorella pyrenoidosa protein extract (APE) under low-serum conditions substantially increased Carassius auratus muscle (CAM) cell proliferation and heightened the expression of Myf5 compared to the absence of APE. An integrated intracellular metabolomics and proteomics analysis revealed a total of 13 and 67 differentially expressed metabolites and proteins, respectively, after supplementation with APE in the medium containing 5%FBS, modulating specific metabolism and signaling pathways, which explained the application of APE for passage cell culture under low-serum conditions. Further analysis revealed that the bioactive factors in the APE were protein components. Moreover, CAM cells cultured in reconstructed serum-free media containing APE, l-ascorbic acid, insulin, transferrin, selenium, and ethanolamine exhibited significantly accelerated growth in a scale-up culture. These findings suggest a promising alternative to FBS for fish muscle cell culture that can help reduce production costs and environmental impact in the production of cultured meat.

Hydrogen in Mexico: A technical and economic feasibility perspective for the transition to a hydrogen economy

Global warming, driven largely by CO2 emissions, poses a significant global challenge with health implications. Mexico's energy landscape heavily relies on fossil fuels, accounting for over 75% of consumption and substantial carbon emissions. Additionally, the national energy demand exceeds current production. This article evaluates the potential need to adopt a hydrogen economy in Mexico, its feasibility, and recommended implementation strategies. The research clarifies the concept of a hydrogen economy and explores its pros and cons in the context of Mexico's energy scenario and global comparisons, advocating for an energy shift. Feasibility is examined within economic, ecological, and social frameworks, weighing advantages and drawbacks. The article suggests green hydrogen production approaches, considering both cost-effectiveness and environmental impact. Implementation challenges are recognized, yet the benefits, as expounded herein, make the transition worthwhile.

High ionic conducting lithium fluoride rich solid electrolyte interphase induced by polysulfide for carbon-based dual ion batteries

Carbon-based dual ion batteries (DIBs) promise a high working voltage, ease of production, low cost and low environmental impact, yet they suffer from poor electrochemical performances ascribed predominantly to electrolyte decomposition, consequently impacting the stability of solid electrolyte interphase (SEI) formation in the negative electrode. Herein, we report a facile pre-formation of lithium fluoride (LiF)-rich SEI derived from lithium polysulfide (LiPS) added lithium bis(trifluoromethane)sulfonimide (LiTFSI)-based electrolyte. A pre-formed lithium sulfide (Li2S) as the inner passivation layer effectively facilitates the growth of LiF on carbon anode, which greatly enhances the ionic conductivity of SEI and prevents the formation of Li dendrites. The designed electrolyte consisting of 3.4 M LiTFSI in the mixture of ethyl methyl carbonate (EMC) and dimethyl carbonate (DMC) (1:1 by vol.) with the addition of 0.1 M LiPS achieves excellent compatibility with activated carbon, delivered an initial specific capacity of 408 mAh g−1 with coulombic efficiency ∼100% at 1 A g−1 over 150 cycles. With an in-depth analysis of compositions and the distribution of decomposition products at the interface, the critical impact of Li2S on SEI formation is revealed. DIB full cells assembled using the carbon anodes with a pre-formed SEI layer delivered an initial discharge capacity of 57.2 mAh g−1 and average voltage of 4.35 V. The above-mentioned findings shed new light on SEI pre-forming technique for high-performance DIB based on the rational design of electrolytes.

Open-Pit Granite Mining Area Extraction Using UAV Aerial Images and the Novel GIPNet

The ability to rapidly and accurately delineate open-pit granite mining areas is pivotal for effective production planning and environmental impact assessment. Over the years, advancements in remote sensing techniques, including the utilization of satellite imagery, LiDAR technology and unmanned aerial vehicles, have revolutionized the way mining areas are monitored and managed. Simultaneously, in the context of the open-pit mining area extraction task, deep learning-based automatic recognition is gradually replacing manual visual interpretation. Leveraging the potential of unmanned aerial vehicles (UAVs) for real-time, low-risk remote sensing, this study employs UAV-derived orthophotos for mining area extraction. Central to the proposed approach is the novel Gather–Injection–Perception (GIP) module, designed to overcome the information loss typically associated with conventional feature pyramid modules during feature fusion. The GIP module effectively enriches semantic features, addressing a crucial information limitation in existing methodologies. Furthermore, the network introduces the Boundary Perception (BP) module, uniquely tailored to tackle the challenges of blurred boundaries and imprecise localization in mining areas. This module capitalizes on attention mechanisms to accentuate critical high-frequency boundary details in the feature map and synergistically utilizes both high- and low-dimensional feature map data for deep supervised learning. The suggested method demonstrates its superiority in a series of comparative experiments on a specially assembled dataset of research area images. The results are compelling, with the proposed approach achieving 90.67% precision, 92.00% recall, 91.33% F1-score, and 84.04% IoU. These figures not only underscore the effectiveness of suggested model in enhancing the extraction of open-pit granite mining areas but also provides a new idea for the subsequent application of UAV data in the mining scene.

Multicriteria Analysis of Cement Mortar with Recycled Sand

Sustainable development requires a holistic perspective that integrates the different aspects of production and consumption and promotes the transition to a circular economy. This approach aims to balance the needs of the present and future generations, as well as the social, environmental, and economic dimensions of development. By producing products that are durable, recyclable, and reusable, and by minimizing the use of energy and materials, the environmental impact of production can be reduced while also generating economic benefits and enhancing social well-being. The article addresses the multicriteria sustainability of producing mortar modified with sand from recycled concrete rubble. The research explored the possibility of replacing natural sand with recycled sand in proportions from 10% to 100%. The consistency of mixtures, flexural and compressive strengths after 2, 28, and 90 days, as well as the carbon footprint and cost of the aggregate used were analyzed. The waste management index and sustainable use of natural resources were also considered. The research and analysis showed that recycled sand could be successfully used as an alternative for natural aggregate, as there are clear environmental and economic advantages, and the basic technical characteristics do not differ significantly statistically from the unmodified composite.

Factors affecting durability properties of GPC: A review

The imperative to find sustainable alternatives to conventional cement, given its energy-intensive production and significant environmental impact, has driven research into alternative binder materials for civil infrastructure. This paper explores Geopolymer concrete (GPC), a polymer-based binder technology, as a promising solution to reduce the environmental footprint associated with traditional cement production. The study meticulously examines various aspects of GPC, focusing on its impact on crucial durability properties for infrastructure applications. This includes an in-depth analysis of GPC properties, elucidating characteristics influencing performance. In addition to fundamental properties, the paper critically evaluates the resistance of geopolymer pastes and concrete to a spectrum of extreme conditions. The discussion spans testing methodologies for both heat- and ambient-cured geopolymers, providing insights into their performance and durability across diverse environmental challenges. This comprehensive review aims to enhance the understanding of GPC technology, offering valuable insights for researchers, engineers, and industry professionals committed to sustainable and resilient infrastructure solutions.

The politics of red meat consumption and climate change

Red meat production is one of the leading sources of carbon dioxide emission thus reducing meat production and consumption is crucial. Using a sample of American adults (n = 456), the link between right-wing sociopolitical ideologies and (i) attitudes towards red meat; (ii) willingness to reduce red meat consumption; (iii) willingness to pay more for red meat; (iv) belief about the impact of red meat consumption on the environment; and (v) and distrust (versus trust) of authorities was examined. Right-wing ideologies (i.e. right-wing-authoritarianism and social dominance orientation) were associated with more positive attitudes towards red meat, unwillingness to consume less red meat or pay more for red meat, disbelief that red meat negatively impacts the environment, and greater distrust of information from authorities that propose a link between red meat production and negative environmental impact. However, results varied by political ideology dimension. Findings suggest that attempts to alter peoples’ red meat consumption—as part of a strategy for tackling climate change—must incorporate a nuanced understanding of the impact of sociopolitical ideologies on attitudes towards red meat consumption and the need to raise awareness about its impact on the environment.

Using VIKOR and RSM-DA in the optimization of dry turning of 9XC steel

Dry turning is an effective method for reducing the production costs and environmental impact of machining processes. In this study, the effect of cutting speed (Vc), feed rate (fz), and depth of cut (ap) on the surface roughness (Ra) and material removal rate (MRR) of 9XC steel during dry turning was investigated. A Box-Behnken experimental design was employed to analyze the main effects and interaction effects of these cutting parameters. In this research, the combining Response Surface Methodology - Desirability Approach (RSM-DA) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method were both employed for solving multiple objective optimization problems, and their performance was compared. The results from both methods can be assessed based on their ability to identify the optimal set of parameters that simultaneously optimize surface quality and production rate, as well as their computational efficiency and ease of implementation. Both RSM-DA and VIKOR have been found effective for solving multi-objective optimization problems, such as optimizing cutting parameters in dry turning. While RSM-DA is a statistical tool that combines multiple objectives into a single function, VIKOR is a decision-making method that ranks alternatives based on multiple criteria. The choice of which method to use depends on the specific requirements of the problem and the availability of resources for implementation. The research results show that both VIKOR and RSM-DA are suitable for solving the multi-objective optimization problem of the turning process. According to the VIKOR method, the optimum cutting conditions were found to be a cutting speed Vc of 120 m/min, a depth of cut ap of 0.1 mm a feed rate fz of 0.06 mm/rev, and, which resulted in a surface roughness of 0.209 um and a material removal rate of 0.72 cm3/min. Meanwhile, RSM-DA predicts the optimal Ra and MRR values of 0.254 um and 3.36 cm3/min, respectively; corresponding to the Vc of 180m/min, fz of 0.06mm/rev and ap of 0.3mm; That means, the increasing the value of surface roughness by 21.5% will increase the MRR by 366.7%. The findings of this study can provide guidance for selecting the appropriate cutting parameters for dry turning of 9XC steel to achieve desired surface roughness Ra and material removal rate MRR in the specific case.

Energy, exergy, sustainability evaluation of the usage of pyrolytic oil and conventional fuels in diesel engines

Solid wastes like used tires have high annual production and significant environmental impact potential. Tire wastes can be pyrolyzed to regenerate energy and create useful products. The purpose of this study is to demonstrate the use of pyrolytic oil produced by the pyrolysis of waste tires as fuel in diesel engines. The energy exergy and sustainability of pyrolytic oil and conventional marine diesel fuels were examined in this study. The energy was determined in the experimental processes used to transform used tires into carbon black, pyrolytic oil, and pyrolytic gas. The components of SOX, NOX, and CO2 produced when pyrolytic oil and conventional marine fuels were combusted in diesel engines were obtained. As a result of the study, the energy value of the pyrolytic oil produced during the pyrolysis process as fuel was determined to be 2.8 MW. The results indicated that the combustion of pyrolytic oil in diesel engines had a thermal efficiency of 38% and a second-law efficiency of 58%. The standard marine fuels were found to have a sustainability index of 2.7, while pyrolytic oil had a sustainability index of 1.42.

Mycoprotein as a meat substitute: production, functional properties, and current challenges‐a review

SummaryMeat has historically been an essential source of animal‐based protein. However, due to population growth, health problems linked to the consumption of red meat, and concerns over environmental challenges, there is an increased need for alternative protein sources. Various plant‐based meat alternatives have recently been explored, with ongoing advancements in industrial‐scale production. Mycoprotein has been proposed as a sustainable alternative to meat due to its distinctive functional food properties and fibrous structure. However, some challenges still prevail related to large‐scale production, texture, sustainability, and acceptability of mycoprotein products. This review paper provides a comprehensive overview of scientific research on mycoprotein, focusing on nutritional composition, functional properties, production technology, and health benefits. This study also examines the current challenges related to product safety, environmental impact, and prospects of this innovative food.

Building upcycling or building reconstruction? The ‘Global Benefit’ perspective to support investment decisions for sustainable cities

Investment decisions on demolition and reconstruction vs. refurbishment of the existing building stock can extend beyond financial and economic criteria. However, they must involve energy savings, environmental preservation, material consumption, and waste management for sustainable cities. The regulatory framework used in the past decades and the correlated research seem more unbalanced toward the containment of building energy consumption than toward embodied energy (EE) management in production processes and environmental impact management. Foreshadowing the perspective of a more restrictive regulatory framework on EE, such as prohibiting the displacement of materials with residual energy potential, such as waste in landfills, some challenging frontier issues are involved when facing the limits of the economic evaluation methodologies for transformation projects. Thus, this study aimed to propose a reasoning and an operative modality to support urban governance policies and investment decisions involving private and public subjects in the construction sector. Circular economy and life cycle thinking principles, through life cycle costing (LCC) and life cycle assessment (LCA), are assumed and harmonized with the discounted cash-flow analysis (DCFA): (1) monetizing and modeling into the DCFA the EE and the embodied carbon (EC); (2) internalizing the Global Cost and the new ‘Global Benefit’ into the net present value (NPV) calculation; and (3) focusing on the residual end-of-life value calculation from the early design and investment decision stages. The reasoning can be extended to single buildings, the urban scale, or even entire portions of existing buildings in urban areas concerning typological sub-segments. The operative modality is yet to be explored in a concrete application for orienting urban governance policies and sustainable public–private partnerships, including environmental and, thus, social externalities even in the private real estate investment decision process, in the scope of evolving regulations.

Joining of hybrid busbars for E-Mobility: An economic and environmental study

This paper presents a model to evaluate and analyze the costs of joining hybrid (copper-aluminum) busbars when different production processes are deployed. The process-based cost model (PBCM) is built upon the subdivision of the production cycle in three different stages related with the fabrication or purchase of auxiliary joining elements, preparation of the individual copper and aluminum conductors, and final joining of the hybrid busbars. The total cost per hybrid busbar is obtained by converting the major physical, human, and financial resources associated with the production cycle into itemized costs that make use of the expenses in materials, labor working hours, number and usage time of machines and tools, among other production costs. Application of the PBCM is illustrated with three different joining processes and enriched with a life cycle assessment (LCA) focused on the environmental performance of hybrid busbars throughout its fabrication, service use and end of life. The combined economic and environmental sustainability analysis of joining hybrid busbars allows concluding that despite conventional fastening being the cheaper process it has the highest environmental impact due to the use of bolts, nuts and washers made from galvanized medium carbon steel. Injection lap riveting arises to be the most well-balanced process in terms of production cost and environmental impact.

Sustainable Valorization of Organic Materials as Substrates for Soilless Crops in Protected Environments in the Venezuelan Andes

Agricultural production activities generate a large amount of waste, most of which is of organic origin from plant remains. These residues could easily be transformed into a resource, specifically, into a substrate for use in soilless cultivation; however, in most cases, they are not used. Therefore, a characterization of local agricultural residues was carried out to determine their use as a substrate for crop cultivation without soil in a protected environment. The selected substrates were Sphagnum peat, coir fiber, and compost, which were managed alone or in mixtures of 50/50, 75/25, or 25/75% v/v ratios. We also included a mixture of virgin mountain soil and earthworm humus (known as INIA mixture) because it is used by local growers. The results showed that the substrates based on coir fiber, peat, and mixtures of both presented suitable characteristics for horticultural crops. On the contrary, compost-based substrates had high pH values and low organic matter contents that could be improved before use. The relationship found between the evaluated parameters of each substrate allowed us to establish that variables, such as the content of organic matter and water at different tensions and particle sizes, can be utilized to make a quick selection of the substrates produced locally, which would lead to the use of waste in a way that is more consistent with sustainable agricultural production and minimal environmental impact, by being used in the production of crops in containers without soil. In addition, these results can be used as an alternative reference in localities where these residues are easily available.

Thermodynamics modelling and optimisation of a biogas fueled decentralised poly-generation system using machine learning techniques

In the forthcoming era of smart energy systems, decentralised solutions are gaining increasing prominence due to their superior adaptability for interconnecting sectors, reduced inefficiencies, and environmentally friendly operation. This study introduces a new medium-scale biogas-based power plant that utilises a gas turbine to meet the energy needs of a specific locality, encompassing electricity, heating, cooling, and water supply, all whilst considering the system's environmental impact. To optimise the plant's performance, three different multi-objective optimisation scenarios employing machine learning methodologies and Greywolf algorithms with distinct objective functions are analysed. Under the base conditions, the proposed plant showcases impressive capabilities, delivering 1372 kW of electricity, 246.2 kW of heating, 293.3 kW of cooling, and 4.1 kg/s of distilled water. It operates with first and second law thermodynamics efficiencies of 72.3 % and 41.4 %, respectively, while maintaining a CO2 emission index of 0.778 kgCO2/kWh. Furthermore, the net present value and investment return period for the investment are estimated to be approximately 4.4 million USD and 4 years, respectively. Through optimisation (scenario 1) that prioritises maximising efficiency while minimising product costs and environmental impact, the following parameters are achieved: an exergy efficiency of 42.7 %, a cost of products at 28.8 $/GJ, and a reduced CO2 emission index of 0.762 kgCO2/kWh. The results reveal that the proposed system not only excels in efficiency but also proves to be economically viable and environmentally beneficial.