Carbon emissions in China's steel industry from a life cycle perspective: Carbon footprint insights.

China is the most important steel producer in the world, and its steel industry is one of the most carbon-intensive industries in China. Consequently, research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development goals. We constructed a carbon dioxide (CO2) emission model for China's iron and steel industry from a life cycle perspective, conducted an empirical analysis based on data from 2019, and calculated the CO2 emissions of the industry throughout its life cycle. Key emission reduction factors were identified using sensitivity analysis. The results demonstrated that the CO2 emission intensity of the steel industry was 2.33 ton CO2/ton, and the production and manufacturing stages were the main sources of CO2 emissions, accounting for 89.84% of the total steel life-cycle emissions. Notably, fossil fuel combustion had the highest sensitivity to steel CO2 emissions, with a sensitivity coefficient of 0.68, reducing the amount of fossil fuel combustion by 20% and carbon emissions by 13.60%. The sensitivities of power structure optimization and scrap consumption were similar, while that of the transportation structure adjustment was the lowest, with a sensitivity coefficient of less than 0.1. Given the current strategic goals of peak carbon and carbon neutrality, it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies, increase the ratio of scrap steel to steelmaking, and build a new power system.

MalariaFlow: A comprehensive deep learning platform for multistage phenotypic antimalarial drug discovery.

Malaria remains a significant global health challenge due to the growing drug resistance of Plasmodium parasites and the failure to block transmission within human host. While machine learning (ML) and deep learning (DL) methods have shown promise in accelerating antimalarial drug discovery, the performance of deep learning models based on molecular graph and other co-representation approaches warrants further exploration. Current research has overlooked mutant strains of the malaria parasite with varying degrees of sensitivity or resistance, and has not covered the prediction of inhibitory activities across the three major life cycle stages (liver, asexual blood, and gametocyte) within the human host, which is crucial for both treatment and transmission blocking. In this study, we manually curated a benchmark antimalarial activity dataset comprising 407,404 unique compounds and 410,654 bioactivity data points across ten Plasmodium phenotypes and three stages. The performance was systematically compared among two fingerprint-based ML models (RF::Morgan and XGBoost:Morgan), four graph-based DL models (GCN, GAT, MPNN, and Attentive FP), and three co-representations DL models (FP-GNN, HiGNN, and FG-BERT), which reveal that: 1) The FP-GNN model achieved the best predictive performance, outperforming the other methods in distinguishing active and inactive compounds across balanced, more positive, and more negative datasets, with an overall AUROC of 0.900; 2) Fingerprint-based ML models outperformed graph-based DL models on large datasets (>1000 compounds), but the three co-representations DL models were able to incorporate domain-specific chemical knowledge to bridge this gap, achieving better predictive performance. These findings provide valuable guidance for selecting appropriate ML and DL methods for antimalarial activity prediction tasks. The interpretability analysis of the FP-GNN model revealed its ability to accurately capture the key structural features responsible for the liver- and blood-stage activities of the known antimalarial drug atovaquone. Finally, we developed a web server, MalariaFlow, incorporating these high-quality models for antimalarial activity prediction, virtual screening, and similarity search, successfully predicting novel triple-stage antimalarial hits validated through experimental testing, demonstrating its effectiveness and value in discovering potential multistage antimalarial drug candidates.

Life cycle assessment of biochar for sustainable agricultural application: A review.

Biochar application is an effective strategy to address Agro-climatic challenges. However, the agro-environmental impacts of different biochar technology models are lacking of systematic summaries and reviews. Therefore, this paper comprehensively reviews recent developments derived from published literature, delving into the economic implications and environmental benefits of three distinct process namely technologies-pyrolysis, gasification, and hydrothermal carbonization. This paper specifically focuses on the agricultural life cycle assessment (LCA) methodology, and the influence of biochar preparation technologies and products on energy consumption and agricultural carbon emissions. LCA analysis shows that process and feedstock pose a predominant role on the properties and production rate of biochar, while gasification technology exhibits excellent economic attributes compared to the other two technologies. Biochar applications in agricultural has the beneficial effect of sequestering carbon and reducing emissions, especially in the area of mitigating the carbon footprint of farmland. However, the complexity of the composition of the prepared feedstock and the mismatch between the biochar properties and the application scenarios are considered as potential sources of risks. Notably, mechanism of carbon sequestration and emission reduction by soil microorganisms and agro-environmental sequestration by biochar application remains unclear, calling for in-depth studies. We review novel aspects that have not been covered by previous reviews by comparing the technical, economic, and environmental benefits of pyrolysis, gasification, and hydrothermal carbonization systematically. Overall, this study will provide a valuable framework to environmental implications of biochar preparation, application, and life cycle assessments.

ALTERNATIVE ROUTE OF TRANSMISSION AND HOST SPECIFICITY OF CYRTOSOMUM PENNERI IN FLORIDA'S INVASIVE LIZARDS.

The atractid nematode Cyrtosomum penneri is an autoinfective parasite of several lizard species. Intraspecific transmission between hosts appears to occur exclusively through sexual copulation, yet it is unclear how worms are transferred between different host species. Our research aims to test the possibility of oral transmission of C. penneri using experimental infections. The lizards Anolis sagrei, Leiocephalus carinatus, Hemidactylus mabouia, and Agama picticauda were experimentally exposed to C. penneri in 1 of these groups: (1) oral infection using a feces and saline slurry to approximate host coprophagy, (2) oral infection with a large meal to approximate host predation, and (3) venereal infection using a pipette to confirm sexual transmission. Experimental infections to test venereal transmission were successful in A. sagrei, A. picticauda, and H. mabouia, but were unable to establish infections in L. carinatus. In the predation exposures, A. picticauda, A. sagrei, and H. mabouia hosted infections, whereas L. carinatus were uninfected. Finally, coprophagy experimental infections did not result in infections for any species of host. Our study corroborates venereal transmission of C. penneri in multiple species of lizards and establishes predation as an alternative route of infection. Predation as an oral route of transmission may provide C. penneri an opportunity for interspecific transmission that would otherwise be unlikely during host copulation.

Unprecedented H5N1 Outbreak: A Rare Cross-Species Influenza Threat.

The recent detection of highly pathogenic avian influenza (HPAI) H5N1 in dairy cattle is a cross-species infection, underscoring the adaptability of the virus to infect mammals, particularly domestic ruminants across multiple farms. The outbreak has had a huge economic impact, including the depopulation of millions of hens. While current influenza surveillance indicates no unusual human influenza activity, the situation has raised public concerns due to the virus's zoonotic potential and its devastating impact on both avian and mammalian species. Most importantly, thorough surveillance and adherence to food safety measures to prevent potential human infections are top priorities.

A Review of Artificial Intelligence and Machine Learning in Product Life Cycle Management.

The pursuit of harnessing data for knowledge creation has been an enduring quest, with the advent of machine learning and artificial intelligence (AI) marking significant milestones in this journey. Machine Learning (ML), a subset of AI, emerged as the practice of employing mathematical models to enable computers to learn and improve autonomously based on their experiences. In the pharmaceutical and biopharmaceutical sectors, a significant portion of manufacturing data remains untapped or insufficient for practical use. Recognizing the potential advantages of leveraging available data for process design and optimization, manufacturers face the daunting challenge of data utilization. Diverse proprietary data formats and parallel data generation systems compound the complexity. The transition to Pharma 4.0 necessitates a paradigm shift in data capture for manufacturing and process operations. This paper highlights the pivotal role of artificial intelligence in converting process data into actionable knowledge to support critical functions throughout the whole process life cycle. Furthermore, it underscores the importance of maintaining compliance with data integrity guidelines, as mandated by regulatory bodies globally. Embracing AI-driven transformations is a crucial step toward shaping the future of the pharmaceutical industry, ensuring its competitiveness and resilience in an evolving landscape.

Fungal primary and opportunistic pathogens: an ecological perspective.

Fungal primary pathogenicity on vertebrates is here described as a deliberate strategy where the host plays a role in increasing the species fitness. Opportunism is defined as coincidental survival of an individual strain in host tissue using properties that are designed for life in an entirely different habitat. In that case the host's infection control is largely based on innate immunity, and the etiologic agent is not transmitted after infection, and thus fungal evolution is not possible. Primary pathogens encompass two types, depending on their mode of transmission. Environmental pathogens have a double life cycle, and tend to become enzootic, adapted to a preferred host in a particular habitat. In contrast, pathogens that have a host-to-host transmission pattern are prone to shift to a neighboring, immunologically naive host, potentially leading to epidemics. Beyond these prototypical life cycles, some environmental fungi are able to make large leaps between dissimilar hosts/habitats, probably due to similarity of key factors enabling survival in an entirely different niche, and thus allowing a change from opportunistic to primary pathogenicity. Mostly, such factors seem to be associated with extremotolerance.

Sustainable repurpose of end-of-life fiber reinforced polymer composites: A new circular pedestrian bridge concept.

In response to global challenges in resource supply, many industries are adopting the principles of the Circular Economy (CE) to improve their resource acquisition strategies. This paper introduces an innovative approach to address the environmental impact of waste Glass Fiber Reinforced-Polymer (GFRP) pipes and panels by repurposing them to manufacture structural components for new bicycle and pedestrian bridges. The study covers the entire process, including conceptualization, analysis, design, and testing of a deck system, with a focus on the manufacturing process for a 7-m-long prototype bridge. The study shows promising results in the concept of a sandwich structure utilizing discarded GFRP pipes and panels, which has the flexibility to account for variabilities in dimensions of incoming products while still meeting mechanical requirements. The LCA analysis shows that the transportation of materials is the governing contributing factor. It was concluded that further development of this concept should be accompanied by a business model that considers the importance of the contributions from the whole value chain.

Exploring the environmental impacts of plastic packaging: A comprehensive life cycle analysis for seafood distribution crates.

Annually, 8.3 million tonnes of mismanaged plastic waste enter oceans, prompting the food packaging industry, a major contributor, to minimize its environmental footprint. Within the seafood sector, a nascent number of studies are exploring the impacts of various packaging solutions for distribution, yet clear insights remain elusive. This study tries to fill the gap by comparing the impacts of two seafood packaging options: disposable expandable polystyrene (EPS) boxes and, for the first time, reusable plastic crates (RPC) crafted from high-density polyethylene. Using the life cycle assessment methodology with a 'cradle to grave' approach, the research evaluates the distribution of 1260,000 t of fish from port of Vigo (Spain) to various markets. Similar climate change values emerge in local (5.00·107 kg CO2 eq.) and regional trade (1.20·108 kg CO2 eq.) for both options, but RPCs exhibit around a 12 % increase (6.15·108 kg CO2 eq.) during national distribution, emphasizing package weight and load significance. The findings across all impact categories exhibited general consistent trends. The sensitivity analysis suggests relocating washing facilities to port could enhance RPCs´ environmental benefits for transport within a 160 km range. These findings underscore reusable packaging's potential as an eco-friendlier alternative in specific contexts, aligning with heightened environmental concerns and regulatory pressures surrounding plastic usage.

Enhanced astaxanthin production in Haematococcus lacustris by electrochemical stimulation of cyst germination.

This study investigated the technical feasibility of using electrogermination to activate dormant cysts as an inoculum for subsequent 14-d photosynthetic astaxanthin production in Haematococcus lacustris. Electrotreatment affected the cell viability, surface charge, and morphology of H. lacustris cysts. At an optimal voltage of 2 V for 60 min, the cyst germination rate peaked at 44.6 % after 1 d, representing a 2.2-fold increase compared with that of the untreated control. Notably, electrogermination significantly enhanced both the astaxanthin content (44.9 mg/g cell) and productivity (13.2 mg/L/d) after 14 d of photobioreactor cultivation, corresponding to 1.7- and 1.5-fold increases compared with those in control, respectively. However, excessive electrotreatment, particularly at voltages exceeding 2 V or for durations beyond 60 min, did not enhance the astaxanthin production capability of H. lacustris. Proper optimization of renewable electrogermination can enable sustainable algal biorefinery to produce multiple bioactive products without compromising cell viability and astaxanthin productivity.

Assessing the environmental footprint of alternative green biorefinery protein extraction techniques from grasses and legumes.

The significant grasslands of Europe and its member states represents a significant feedstock opportunity for circular bioeconomy development. The development of green biorefineries (GBR), to supply protein for the feed industry from grass, could help many European member states to address significant deficits in protein availability and reduce imports. The current study assesses the environmental footprint of alternative GBR protein extraction techniques from grasses and legumes using life cycle assessment. The focus is on comparing feedstock and technology pathways that could displace soya bean imports. The study finds that leaf protein concentrate (LPC) produced from grass had an improved environmental performance when compared to soya bean meal (SBM), across the assessed feedstock (perennial ryegrass or grass-clover mixtures) and technology pathways (one-stage maceration versus multi-stage maceration). For example, in the case of Climate Change the emission intensity for LPC was 57-85 % lower per tonne of crude protein (CP) compared with SBM. Acidification burdens were 54-88 % lower, and Eutrophication: Freshwater burdens were 74-89 % lower. Some scenarios of GBR produced LPC with a larger Energy Resources: Non-Renewable burden than SBM, though this could be mitigated with higher renewable energy (biogas and wind energy) integration within the scenario. Grass-clover scenarios generally achieved a lower intensity of emissions compared to ryegrass scenarios, particularly in the category of Climate Change, where feedstock cultivation represented a significant contributor to impacts. Overall, GBR can produce high quality protein with a lower environmental burden than SBM, but choice of feedstock and system design are critical factors for overall environmental performance.

Integrating the water-energy-food nexus and LCA + DEA methodology for sustainable fisheries management: A case study of Cantabrian fishing fleets.

The fishing sector constitutes an important source of economic revenue in northern Spain. In this context, various research studies have focused on the application of the five-step Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methodology to quantify environmental impacts of fishing systems. However, some of them have used environmental indicators that focus on individual environmental issues, hindering the goal of achieving integrated resource management. Therefore, in this study, the Water-Energy-Food (WEF) Nexus is employed as an integrative perspective that considers the synergies and trade-offs between carbon footprint, energy requirements, and water demand. The main objective of this study is to evaluate the operational efficiency and environmental impacts of Cantabrian fishing fleets. To this end, the combined use of LCA and DEA, along with the WEF Nexus, was applied to the Cantabrian purse seine fleet. DEA matrices were generated using the LCA-derived WEF nexus values as inputs to calculate efficiency scores for each vessel. Subsequently, based on the efficiency projections provided by the DEA model, a new impact assessment was performed to understand the eco-efficiency and potential environmental benefits of operating at higher levels of efficiency within this fleet. The average efficiency of the fleet was above 60 %. Inefficient units demonstrated a greater potential to reduce their environmental impacts (up to 65 %) by operating according to efficiency projections. Furthermore, the results revealed a strong dependence of environmental impacts on one of the operational inputs, i.e., fuel consumption. These findings highlight the significance of embracing holistic approaches that combine technical, economic, and social factors to achieve a sustainable balance in fisheries systems. In this regard, the five-step LCA + DEA method applied in conjunction with the WEF Nexus emerged as a suitable tool for measuring operational and environmental objectives.

Comparison between the Baltic Sea and Irish Sea level of Cs-137 contamination on benthic, demersal and pelagic fish species.

The Irish Sea and the Baltic Sea are nowadays still the two most Cs-137 contaminated Seas worldwide. However, the origins of this contaminations are completely different. While the Baltic Sea was unintentionally contaminated due to global fallout after the accident in the Chernobyl nuclear powerplant in 1986, the Irish sea was intentionally used for low level liquid radioactive waste discharges from the Sellafield nuclear reprocessing facility (called Windscale until 1981) between the 1950s and 1990s. Nowadays, more than 30 years later, it is still possible to detect these contaminations in fish, water and sediments of both seas. Since fish are an important part of the human diet, monitoring Cs-137 levels in fish is essential for assessing the potential radiation exposure to humans. In 2019 and 2020 two surveys were dedicated to study the current levels of radioactive contamination in fish species from both Seas. During both surveys, fish samples were collected and analysed by gamma spectrometry later on. The results show that the average Cs-137 activity in benthic, demersal and pelagic fish species from the Baltic Sea are 2.7, 4.6 and 4.2, respectively, times higher than the corresponding values of the Irish Sea. Based on this and two other comparisons, it is concluded that the Baltic Sea is the most contaminated with Cs-137.

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers.

BACKGROUND: Efforts are underway to capitalize on the computational power of the data collected in electronic medical records (EMRs) to achieve a learning health system (LHS). Artificial intelligence (AI) in health care has promised to improve clinical outcomes, and many researchers are developing AI algorithms on retrospective data sets. Integrating these algorithms with real-time EMR data is rare. There is a poor understanding of the current enablers and barriers to empower this shift from data set-based use to real-time implementation of AI in health systems. Exploring these factors holds promise for uncovering actionable insights toward the successful integration of AI into clinical workflows. OBJECTIVE: The first objective was to conduct a systematic literature review to identify the evidence of enablers and barriers regarding the real-world implementation of AI in hospital settings. The second objective was to map the identified enablers and barriers to a 3-horizon framework to enable the successful digital health transformation of hospitals to achieve an LHS. METHODS: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were adhered to. PubMed, Scopus, Web of Science, and IEEE Xplore were searched for studies published between January 2010 and January 2022. Articles with case studies and guidelines on the implementation of AI analytics in hospital settings using EMR data were included. We excluded studies conducted in primary and community care settings. Quality assessment of the identified papers was conducted using the Mixed Methods Appraisal Tool and ADAPTE frameworks. We coded evidence from the included studies that related to enablers of and barriers to AI implementation. The findings were mapped to the 3-horizon framework to provide a road map for hospitals to integrate AI analytics. RESULTS: Of the 1247 studies screened, 26 (2.09%) met the inclusion criteria. In total, 65% (17/26) of the studies implemented AI analytics for enhancing the care of hospitalized patients, whereas the remaining 35% (9/26) provided implementation guidelines. Of the final 26 papers, the quality of 21 (81%) was assessed as poor. A total of 28 enablers was identified; 8 (29%) were new in this study. A total of 18 barriers was identified; 5 (28%) were newly found. Most of these newly identified factors were related to information and technology. Actionable recommendations for the implementation of AI toward achieving an LHS were provided by mapping the findings to a 3-horizon framework. CONCLUSIONS: Significant issues exist in implementing AI in health care. Shifting from validating data sets to working with live data is challenging. This review incorporated the identified enablers and barriers into a 3-horizon framework, offering actionable recommendations for implementing AI analytics to achieve an LHS. The findings of this study can assist hospitals in steering their strategic planning toward successful adoption of AI.

Light promotes asexual reproduction and mediates transcriptomic changes in Pediastrum duplex.

The green alga Pediastrum duplex forms colonies through asexual reproduction and has a unique life cycle. To elucidate the mechanisms that regulate the asexual reproductive cycle in P. duplex, we analyzed the effects of light on the processes and gene expression involved in each step of the asexual reproductive cycle, revealing light irradiation to be essential for increasing the number of colonies. Among the processes in the asexual reproductive cycle, the transition from cell hypertrophy to zoospore formation could proceed even in the dark if glucose was added to the medium. Transcriptome analysis revealed that the expression of different groups of genes was significantly promoted or suppressed before and after the number of colonies increased. Our findings indicate that the asexual reproductive cycle of P. duplex includes a process promoted by photosynthesis. This study enhances our understanding of the growth characteristics of P. duplex and other microalgae.

Life Cycle Assessment and Net Energy Analysis of an Integrated Hydrothermal Liquefaction-Anaerobic Digestion of Single and Mixed Beverage Waste and Sewage Sludge.

The conversion of biomass to bioenergy is one of the approaches to creating a sustainable society. In this study, the life cycle assessment and the net energy analysis of converting mixed sewage sludge and beverage waste into bioenergy via a combined hydrothermal liquefaction-anaerobic digestion (HTL-AD) system was carried out. Primary sludge (PS), winery rose lees (RL), brewery Trub (BT), the mixture of brewery trub and primary sludge (BTPS) and the mixture of winery rose lees and primary sludge (RLPS) were the feedstocks considered. Efficient energy utilization [in form of net energy ratio (NER)], and environmental emissions were evaluated. The NER of BT (2.07) and RL (1.76) increased when mixed with PS (3.18) to produce BTPS (3.20) and RLPS (2.85). Also, the HTL phase of the combined HTL-AD system produced a greater NER than the AD phase in BT, BTPS, and PS and vice-versa in RL and RLPS. Six environmental impact categories were studied namely global warming, terrestrial acidification, ionizing radiation, terrestrial ecotoxicity, human carcinogenic toxicity, and human non-carcinogenic toxicity. RL produced the greatest environmental impact while BTPS produced the least impact, thus indicating the advantage of feedstock combination. This study shows that the combination of feedstocks for bioenergy production in an HTL-AD system does not only increase the quality and quantity of products but also increases the overall NER as well as reducting the environmental impacts. The study also proved that an integrated HTL-AD system is an energy efficient system with greater resource utilization and less environmental footprint than the constituent systems.

Mind your tyres: The ecotoxicological impact of urban sediments on an aquatic organism.

The presence of tyre and road wear particles (TRWP) in the environment is an underestimated threat due to their potential impact on ecosystems and human health. However, their mode of action and potential impacts on aquatic ecosystems remain largely unknown. In the present study, we adopted a sediment exposure scenario to investigate the influence of sediment coming from an urban runoff sedimentation basin on the life cycle of Chironomus riparius. Targeted broad-spectrum chemical analysis helped to characterise the urban sediments and confirmed the significant contribution of contaminants from traffic (e.g. tyre wear contribution, Polycyclic Aromatic Hydrocarbons [PAHs], metals, tyre rubber additives). First-stage chironomid larvae were subjected to increasing concentrations of urban whole sediment. The results showed that exposure to this urban sediment influenced all measured endpoints. In vivo quantification of ROS showed that larvae exposed to the lowest concentration of contaminated sediment exhibited increased fluorescence. The contaminated sediment conditions increased mortality by almost 30 %, but this effect was surprisingly not concentration-dependent. Fertility decreased significantly and concentration-dependently. The results of the Mean Emergence Time (EmT50) and larval size showed an optimality curve. Furthermore, as a consequence of the effects on fitness, the Population Growth Rate (PGR) exhibited a significant decrease, which was concentration-dependent. Therefore, after a single generation, PGR calculation can be adopted as a sensitive tool to monitor pollution caused by complex matrices, i.e. composed of several contaminants. Our research highlights the importance of effective management of road runoff and underlines the need for further investigation to better understand the toxicity of TRWPs.

Nitrogen sources in donor human milk: True protein, nonprotein nitrogen, and amino acid profile.

BACKGROUND: Devices measuring the macronutrient content of human milk are commonly used to assist with clinical decision-making. It is unknown if these devices accurately measure protein content in donor human milk (DHM). Our objective is to quantify the nitrogen sources and protein content in commercial DHM. METHODS: The total nitrogen content (Dumas method) and nonprotein nitrogen content (Kjeldahl method) was measured in triplicate from six commercial DHM samples with protein content noted on the labels. In addition, the amino acid content was measured in 15 commercial DHM samples and protein content in each sample was calculated. The calculated protein content for each DHM sample was compared for consistency. RESULTS: The nonprotein nitrogen content in DHM was consistently higher (0.33 ± 0.05 g/g) than previous reports, leading to overreporting of protein content on DHM labels by a median value of 0.15 g/dl (range 0.02-0.23 g/dl). Similarly, calculation of the protein content from the total nitrogen content with an assumption of 20% (grams per gram) nonprotein nitrogen consistently overrepresented the protein content as determined from the amino acid profile for DHM. CONCLUSION: Common methods for assessing the macronutrient content of human milk may overestimate the protein content of DHM.

Environmental impacts of oil extraction in blocks 16 and 67 of the Yasuní Reserve in the Amazonian Forest: Combined qualitative and Life-Cycle Assessment.

This research analyses 24 years of oil extraction in blocks 16 and 67 of the Yasuní National Park (YNP) in the Amazonian Forest of Ecuador, one of the most biodiverse spaces in the world and with the current presence of ancient indigenous communities. As a novel contribution, we have carried out a Life-Cycle Assessment (LCA) that quantifies the footprints associated with the extraction, transportation, refining, distribution and final uses of the oil in four different scenarios (oil for asphalt use, electricity, marine fuel and passenger car transport). This study also sheds light on the energy return at the point of use of different oil-derivatives, and complements this with a qualitative analysis of the social, cultural and environmental implications for the Waorani communities. We conclude that the environmental burdens of the extraction process in blocks 16 and 67 in 2015 were greater than those of countries such as the United States, Saudi Arabia and Indonesia, based on the analysis of 11 impact categories. The blocks' operation is the most unfavourable for the categories of Terrestrial Acidification Potential (TAP), Global Warming Potential (GWP), Terrestrial Ecotoxicity Potential (TEP) and Ecosystem Quality Loss Potential (EQL), with increments of 804.15 %, 105.36 %, 506.29 % and 210.73 %, respectively, in relation to the average of the rest of the extraction systems analysed. Specifically, the present case study shows 75.18 % higher impacts in the blocks addressed, when compared to the Ecuadorian average. During the period 1999-2022, the carbon emissions associated with the oil extraction in these blocks have increased by 139.01%. It has been detected a neo-colonial economic behaviour: while the Ecuadorian state received 21% of the sales, the Spanish government and the oil companies received, on average, 38% and 41% of the per-litre average fuel price, respectively. Thus, 79% of the income stayed in the Global North. We conclude that, on average, 19.64 % of the impacts associated with crude oil production and consumption occur in the Amazonian region of the YNP, depending on the fuel used and the consumption mechanism. For the Global Warming Potential (GWP) impact category, the extraction process carries, on average, 34.51 % of the weight in all of the life-cycle impacts, depending on the consumption scenario. It was also estimated that to be able to use 0.33 kWh of electricity from fuel combustion, 0.47 kWh of energy for goods transport and 0.20 kWh for passenger transport, an investment of 1 kWh is required, with an average extended EROI of 1:3.33. According to the qualitative analysis performed, it has been concluded that the main local impacts are related to the obstacles in environmental monitoring and information, the economic dependence of the communities on the oil extraction company, and cultural transformations; impacts that are not easily quantifiable or detectable using other methodologies. The combination of the qualitative analysis and LCA showed that the neo-colonial economic distribution did not compensate the social and environmental impacts of the oil extraction occurred in the YNP.

Assessing the Environmental Benefits of Extending the Service Lifetime of Solar Photovoltaic Modules.

Requiring no fuel for generation and negligible material/energy for operation and maintenance, photovoltaic (PV) systems have environmental impacts mostly due to the production of modules and the commissioning of power plants. Thus, extending the service lifetime of these systems from 30 to 40 years through an enhanced lamination process for module production potentially reduces environmental impacts per unit energy generated. Life cycle assessment is employed to evaluate the environmental impacts under scenarios for resource utilizations for the new lamination process, operation and maintenance requirements in the extended service lifetime, and degradation rates of the devised modules. Extending the service lifetime significantly reduces environmental impacts across categories, with a 21-27% reduction in global warming potential on the pessimistic and optimistic ends. At least 20% impact reduction is achieved in most impact categories, even under a pessimistic scenario. Considering uncertainty models in the life cycle inventories, samples are generated for scenarios via Monte Carlo simulation, and with significant improvements with large effects in most environmental impact categories, deterministic impact comparisons are supported by ANOVA and Tukey tests. Production strategies for more durable and reliable PV modules have a significant potential in contributing to global sustainability efforts.