Inventory Analysis Research Articles

Digital technologies for life cycle assessment: a review and integrated combination framework

Abstract Purpose Companies need to enhance their understanding of the environmental impacts of their products and services. Life cycle assessment (LCA) has become a prevalent method for evaluating these impacts. Despite significant advancements in LCA methodology and data availability, several challenges persist. Digital technologies may offer solutions to these challenges in LCA. Therefore, it is crucial to explore how digital technologies can be integrated into LCAs. Methods A systematic literature review was conducted to examine the application of digital technologies, specifically blockchain, the Internet of Things (IoT), big data, and artificial intelligence (AI), within LCAs. The review included 103 peer-reviewed journal articles and conference papers. Contributions of these technologies were categorized according to the four LCA phases outlined in ISO 14040/44 standards. The findings were synthesized into a framework that highlights the individual and combined potential of these technologies for enhancing LCAs. Results and discussion The review reveals that IoT is primarily used in the inventory analysis phase, while blockchain, AI, and big data are applied across the goal and scope definition, inventory analysis, impact assessment, and interpretation phases. Based on these findings, a comprehensive theoretical concept was developed to outline all possible combinations of these four technologies with LCA for synergistic application. Conclusions This study proposes a framework for integrating four key digital technologies—blockchain, IoT, big data, and AI—into LCAs to support environmental sustainability assessment from a company perspective. This framework offers a current overview and a foundation for future research. For LCA practitioners, it serves as a strategic tool for identifying potential technologies and making informed decisions about which digital technologies to apply in their assessments.

Inventory and Thematic Typological Analysis of 3.11 Picture Books

Inventory and Thematic Typological Analysis of 3.11 Picture Books

Text-based algorithms for automating life cycle inventory analysis in building sector life cycle assessment studies

Text-based algorithms for automating life cycle inventory analysis in building sector life cycle assessment studies

End of tubing placement optimization for multi-stage fractured horizontal wells by transient multiphase flow simulation

The exploitation of shale gas offers an effective pathway towards mitigating greenhouse gas emissions and promoting a clean and low-carbon energy system. Nonetheless, liquid loading has been commonly observed in the middle and late production stage, leading to sharp decline of shale gas production. How to improve unloading performance is challenging due to limited liquid-loading capacity. The strategic and timely installation of oil tubing serves as an effective means to mitigate wellbore fluid accumulation in the gas field. Thus, this work tries to improve gas recovery factor by optimizing the End of Tubing (EOT) location and the timing of tubing installation in shale gas wells through transient multiphase flow simulation. The transient simulation approach is adopted owing to its capability to accurately characterize the transient unloading process in gas wells and its closer approximation to field operation conditions compared to steady-state simulation methods. The casing production model and tubing production model have been developed to accurately simulate the flow behavior of fracturing fluid in the casing and tubing production, respectively. The annular flow and the coupling of fluid flow between reservoir and wellbore are the primary focuses of the two models aimed at analyzing fluid flow behavior and the total pressure drop (Δptotal). The casing production model is used to optimize the timing of tubing installation by simulating the liquid loading process of gas well including Δptotal and liquid inventory of wellbore. The optimal time of tubing placement is identified as the point when fluid starts to accumulate in the wellbore, as confirmed through the quantifiable analyses of Δptotal and liquid inventory. The tubing production model is further utilized to optimize the EOT location and tubing diameter considering variations in annular flow and the challenges associated with tubing installation. The placement of tubing in up-dip wells is recommended at Point A, which is determined by considering the influence of fluid gravity as a resistive force. Conversely, for down-dip wells, it is advisable to position the tubing between 1/3 of AB and 1/2 of AB as fluid gravity serves as a driving force in these scenarios. This work offers guidance for the optimum EOT location in shale gas reservoirs experiencing severe liquid loading. Consequently, it is essential to establish guidelines for determining the optimal EOT location across various horizontal well configurations and flow conditions.

SCALE inventory and reactivity analysis as part of the Hermes 2021 PSAR review

The readiness of SCALE for comprehensive studies of pebble-bed reactors has been demonstrated through detailed analysis of a fluoride salt–cooled, high-temperature pebble-bed reactor (PB-FHR). The methods developed for pebble-bed reactor modeling in SCALE, particularly for inventory generation, have proven effective in gaining insights into the reactor physics of this advanced reactor. Excellent agreement with another code package has been observed, further highlighting SCALE’s strong performance.The SCALE results supported the US Nuclear Regulatory Commission’s construction permit application review of the Hermes low-power PB-FHR demonstration reactor. A SCALE model of the Hermes reactor was developed at Oak Ridge National Laboratory using information from the Preliminary Safety Analysis Report (PSAR) and supplemented with publicly available data. SCALE reactivity coefficient simulations reproduced PSAR results within 1σ statistical uncertainties. Sensitivity studies emphasized the importance of graphite specifications for accurate keff predictions.

Inventory analysis and environmental life cycle impact assessment of hotel food waste management for bio-circular economy development in Zimbabwe

This study is an inventory analysis and environmental life cycle assessment of hotel food waste management that seeks to inform efforts towards the development of bio circular economy in Zimbabwe. An audit of food waste generation and an inventory analysis of the prevailing food waste management practices at three selected hotels was undertaken. The greenhouse gas emissions from the prevailing disposal of food waste at dumpsites and the proposed biological treatment of food waste were evaluated using the Tier 1 FOD method and Tier 1 method of biological treatment using the 2019 refined 2006 Intergovernmental Panel on Climate Change guidelines. Environmental life cycle assessment was also conducted for the open dumping, composting, and anaerobic digestion. The average food waste generation within the Zimbabwean hospitality industry was estimated at 1.63 kg/guest/day, with a minimum and maximum of 1.01 and 2.25 kg/guest/day, respectively. Source-separated food waste is currently being collected indiscriminately by municipal waste collection trucks for final disposal at the official landfills or dumpsites. This calls for the need for an offtake system of the source-separated food waste in the form of composting or anaerobic digestion. Study results showed that the disposal of food waste at solid waste disposal sites contributes to the highest greenhouse gas emissions, followed by composting with a 75% reduction in greenhouse emissions. Anaerobic digestion brings about a maximum reduction in greenhouse emissions of 97%. Environmental life cycle assessment results also show that anaerobic digestion is the best method leading to net negative environmental impacts.

Environmental Footprints of Yogurt Production: A Case Study of a Small-Scale Manufacturing Process in Sri Lanka

This study investigated the life cycle environmental impacts of yogurt production from cradle to gate at the Pulathisi milk factory in Polonnaruwa, Sri Lanka. The functional unit considered was one kilogram of yogurt produced in the factory using existing technology. The defined system boundary encompassed raw milk production and transportation, machinery fabrication, standardization of milk, and standard unit operations of yogurt production. Material and energy usage data were collected through a series of observations, literature and Ecoinvent 3.7.1 databases. The ReCiPe 2008 method was employed for impact analysis, considering eighteen impact categories with SimaPro software. The inventory analysis included material consumption for machinery fabrication, energy consumption, and emissions for each unit operation in yogurt production. Results were characterized using midpoint indicators, and normalized impacts were calculated. The characterized outcomes of the yogurt production process contributed 2.48 kgCO2eq to climate change, 0.0297 kgSO2eq to acidification, 0.0002 kgPeq to eutrophication, and 6.9199 kg 1,4-DBeq to human toxicity. The study identified hotspots, emphasizing the significant contributions of cow milk production and electricity usage to environmental impacts. Potential mitigations, such as improved waste management in dairy farming and switching to renewable energy sources, are proposed to address these impacts. The normalized impacts provided insights for decision-makers and stakeholders to compare environmental performances and guide sustainable practices in yogurt production. The total impact was recorded as 0.014-person equivalent per year per one kilogram of yogurt.

Strategic carbon emission assessment in sludge treatment: A dynamic tool for low-carbon transformation

The carbon–neutral target presents a significant challenge for the sewage sludge treatment and disposal (SSTD) industry, necessitating strategic planning for a low-carbon transition. However, flexible and comprehensive carbon emission analysis tools to support this goal remain lacking. This study presents a carbon emission analysis tool to evaluate the carbon emission characteristics and future mitigation potentials of SSTD. The tool integrates life cycle inventory (LCI) modeling-based analysis, sensitivity analysis, regression analysis, and scenario analysis. Carbon emissions are dynamically calculated based on sludge properties, technological level, and industry external parameters, providing a foundation for adaptable evaluation tailored to local conditions. The framework considers the potential effects of multi-parameter and multi-aspect changes in scene design, both within and outside the industry, to achieve dynamic and comprehensive simulations. A case study conducted in Wuhan, China, demonstrated the usability and application processes of the framework. The results indicated that carbon emissions from SSTD are projected to more than double from 2021 to 2060 without interventions. Among the mitigation measures, energy and chemical savings would yield the largest reduction potential, followed by the technical layout adjustment and the promotion of energy efficiency. Operational optimization in the sludge industry and outside the industry would contribute the least. With all mitigation measures applied, emissions could decrease to –82.91 kt CO2-eq in 2060, equivalent to 13.03% compensation for emissions from the sewage treatment line. Among all the processes, incineration routes are recommended due to their current and future low carbon emissions. The cooperative resource route of anaerobic digestion and land use also shows promise as it progressively demonstrates superior performance with increasing organic matter and nutrient content of sludge. Critical factors, sub-processes, and emission types for different routes were identified and can be optimized accordingly. The developed method demonstrates sufficient flexibility to be applied to other cities and larger-scale regions, thereby offering technical and strategic support for SSTD towards carbon–neutral operation.

Life Cycle Assessment of Extraction of Cellulose from Date Palm Biomass Using Natural Deep Eutectic Solvent (NaDES) via Microwave-Assisted Process

This study investigates the extraction of cellulose from Saudi Arabia-based date palm biomass utilizing a natural deep eutectic solvent (NaDES) integrated with a microwave-assisted process. A comprehensive life cycle assessment (LCA) was conducted in accordance with the ISO 14040 standard, encompassing four key stages: goal and scope definition, life cycle inventory analysis (LCI), life cycle impact assessment (LCIA) and interpretation. The analysis was confined to a gate-to-gate boundary in which two impact assessment methods, namely, ReCiPe Midpoint (H) 2016 and ILCD 2011 Midpoint, were used to assess the environmental impacts. The OpenLCA software (version 2.1.1) with the European Life Cycle Database 3.2 (ELCD 3.2) was used in the study. The ReCiPe method identified impact categories such as fossil resource scarcity, terrestrial ecotoxicity, freshwater ecotoxicity, water consumption, human carcinogenic toxicity and marine ecotoxicity. Conversely, the ILCD method identified freshwater ecotoxicity, water resource depletion, mineral, fossil and resource depletion, human toxicity and cancer effects. The results indicate that freshwater ecotoxicity presents the most substantial environmental impact across both assessment methods, surpassing other categories. Fossil resource scarcity, even though originally appearing impactful, demonstrated a relatively lower normalized score compared to freshwater ecotoxicity. Terrestrial ecotoxicity and water consumption were found to be negligible in their impact. Our findings provide important insights into sustainable material science and waste management, affording potential applications for biomass utilization in the Gulf region.

Exploratory Factor Analysis and Convergent Validity of the Adult Executive Function Inventory (ADEXI).

The Adult Executive Functioning Inventory (ADEXI)-a short, practical, self-report questionnaire accessible across diverse adult populations and languages-was used to assess executive functions (EFs), primarily inhibition and working memory. To examine the construct validity of the ADEXI Hebrew version through exploratory factor analysis (EFA) and convergent validity by correlating scores with similar measures of EF. Cross-sectional study using online anonymous surveys. Nonclinical sample of 239 adults, 74.1% women, ages 18 to 80 yr (Mage = 44.19 yr, SD = 12.89). The Hebrew version of the 14-item ADEXI, a demographic questionnaire, and the Dysexecutive Questionnaire (DEX). Descriptive statistics, Cronbach's α EFA using varimax rotation, and Pearson's correlations were used. Total internal consistency was good (α = .86). Unlike the two factors in the original English version, our construct validity through EFA revealed three factors-inhibition, working memory, and, uniquely, flexibility-that accounted for 55.71% of the variance. Convergent validity was supported by medium to large significant correlations (r =.29-.76) between the ADEXI and the DEX subscales and total scores. Our findings offer psychometric evidence to support using the Hebrew version of the ADEXI for EF assessments in adult Hebrew-speaking populations. Plain-Language Summary: The Adult Executive Functioning Inventory (ADEXI) assesses three key components: inhibition, working memory, and cognitive flexibility. In this study, we examined the construct validity of the Hebrew version of the ADEXI to assess executive functions. Our findings support using the ADEXI in Hebrew-speaking populations. The ADEXI offers occupational therapy practitioners serving Hebrew-speaking populations in their practice a validated tool for assessing executive functions.

Teaching data‐driven decision making for inventory analysis with Monte Carlo simulation

AbstractInventory management and the ability to make data‐driven decisions under uncertainty are two critical components of supply chain management. This brief describes how an Excel‐based Monte Carlo simulation of fuel and lottery purchases can be used to teach students to analyze a system with randomness. This exercise can serve as a group or individual assignment to demonstrate the ability of Monte Carlo simulation to estimate solutions involving uncertainty and to teach undergraduate business students how to implement a basic multiperiod fixed‐interval inventory policy with order‐up‐to‐levels. The important concepts of cycle service levels and confidence intervals are emphasized as are the proper implementation of one‐tailed and two‐tailed critical values. Students are encouraged to compare algebraic solutions to their simulation results.

Geosite Kahuripan Evaluation as Gili Genting Potential Asset for Archipelagic Geotourism Development

Abstract There is a growing global interest in natural tourism, which presents new opportunities for the development of small island regions. Several studies have shown that the development of tourism in the Indonesian Archipelago has led to several significant issues, so within the eastern islands of Sumenep— including Gili genting. The richness of natural features and the unique Maduranese Archipelago community, shown by Kahuripan area. However, the potential for developing a nature-based tourism sector (geosite) with the richness of geotourism, has not been adequately considered yet. Therefore, this study aimed to: 1) conducting inventory of the educational geotourism potential; 2) carrying out evaluations using GAM; 3) developing recommendations for future development of Gili Genting Potential Asset as Archipelagic Geotourism Development. According to inventory analysis, the Kahuripan Geosite consists of six Stop site with various information. The MV assessed 4.25 and AV counted of 4.75. The GAM diagram results indicate that the Kahuripan Geosite lies on Q22 tend to be moderate class of MV and AV. This quadrant suggests that the physical aspects of the geosites are quite interesting, while the tourism management that has begun to be developed needs to be further elaborated towards the geotourism-based education concept.

Perhitungan Spare Part HPSOV / PRSOV Pesawat Boeing 777 Dengan Metode Economic Order Quantity

An Indonesian airline, PT. XYZ, performs maintenance on its Boeing 777 aircraft equipped with General Electric GE90 engines at PT. GMF AeroAsia. The aircraft’s Engine Air Supply System utilizes a High Pressure Shutoff Valve (HPSOV) and a Pressure Regulating Shutoff Valve (PRSOV). Between 2019 and 2022, PT. XYZ's Boeing 777 fleet experienced 10 delays and 52 instances of HPSOV/PRSOV replacements due to valve sticking or seizing. This study aims to analyze the reliability of the HPSOV/PRSOV by calculating the Mean Time Between Failures (MTBF) and to optimize spare parts inventory management using the Economic Order Quantity (EOQ) method. The MTBF calculation yielded a value of 8,134.08 Flight Hours (FH). Additionally, the spare parts inventory analysis indicated that the most economical order quantity for each repair is 2 units, with a remaining inventory of 2 units. The total cost of the spare parts inventory is $3,033.66 USD. The findings of this study are expected to provide recommendations for PT. XYZ to improve spare parts inventory management and minimize the risk of delays in aircraft maintenance.

Nitrogen accountancy in space agriculture.

Food production and pharmaceutical synthesis are posited as essential biotechnologies for facilitating human exploration beyond Earth. These technologies not only offer critical green space and food agency to astronauts but also promise to minimize mass and volume requirements through scalable, modular agriculture within closed-loop systems, offering an advantage over traditional bring-along strategies. Despite these benefits, the prevalent model for evaluating such systems exhibits significant limitations. It lacks comprehensive inventory and mass balance analyses for crop cultivation and life support, and fails to consider the complexities introduced by cultivating multiple crop varieties, which is crucial for enhancing food diversity and nutritional value. Here we expand space agriculture modeling to account for nitrogen dependence across an array of crops and demonstrate our model with experimental fitting of parameters. By adding nitrogen limitations, an extended model can account for potential interruptions in feedstock supply. Furthermore, sensitivity analysis was used to distill key consequential parameters that may be the focus of future experimental efforts.

Life cycle carbon emission calculation model of energy system in public buildings: A case study in Shanghai

Energy consumption and carbon emissions (CE) in the building sector have grown in importance in relation to global climate change for China's sustainable development. Relatively few research have addressed the embodied CE, despite the fact that many have examined the operational CE from energy system operational use. In order to determine the CE of the energy production, transportation, construction, operation, and recycling stages, we therefore put up an integrated model. An inventory analysis of the energy system's life cycle CE, a scenario forecast of various combinations of building energy system equipment, and a case study of the building energy system of a typical office building in Shanghai's service industry. According to the results, the embodied CE emits 38.01 % of its energy, and the operational CE emits 61.99 %. However, we should not underestimate the significance of the impact of the embodied CE. Among all projection scenarios, the suggested CE share is highest (18.40 %) when the system combination of air-source heat pump units, LED lights, and ground-source heat pump units is implemented. In the end, based on the structural analysis of the embodied CE, low-carbon growth strategies and policy recommendations for Shanghai's service sector will be made.

Standardizing fingerprint minutiae: A comprehensive inventory and statistical analysis based on Brazilian data

This study introduces a comprehensive inventory of 54 fingerprint minutiae and their variations aimed at standardizing characteristic point identification within forensic science. By analyzing a strategically sampled collection of fingerprints from the Brazilian Federal Police database, stratified by sex and geographic location, our research uncovers the complex interplay between various levels of fingerprint details (L1D, L2D, and L3D) and demographic factors such as sex and finger type. The sample encompassed the entire proposed list of minutiae, affirming the diversity and representativeness of the Brazilian populace, which had, for the first time, its minutiae frequency distributions studied. This investigation proposes a systematic approach for enhancing fingerprint identification accuracy by minimizing data categorization losses and lays the groundwork for more uniform comparative studies in the field. Our findings, derived from a review of contemporary studies and traditional identification manuals, suggest a step towards establishing a universally accepted standard for fingerprint minutiae classification.

Life-Cycle Analysis of Natural Treatment Systems for Wastewater (NTSW) Applied to Municipal Effluents

The objective of the described activity is to develop technologies or proposals that can be implemented within the cycle to enhance the relationship between climate change, water, energy, and food. The focus is on analyzing natural treatment systems for wastewater (NTSW) within the context of Macaronesia, considering factors such as life-cycle assessment (LCA), carbon footprint, impacts, and mitigation capacity. The analysis of real case data from the Canary Islands and Cape Verde will inform the development of appropriate technologies tailored to different areas and scales within Macaronesia. This work includes a comprehensive life-cycle analysis of the Santa Catarina (Cape Verde) NTSW. This analysis encompasses: (a) Inventory analysis of the construction phase: This involves the assessment of inputs and outputs associated with the construction of the NTSW, including materials, energy consumption, transportation, and waste generation. The maintenance and operation phases are then evaluated, with a focus on the ongoing maintenance and operation activities required for the NTSW, including energy consumption, water usage, chemical inputs (if any), labor, and equipment maintenance. (b) Finally, the impacts of the NTSW are evaluated. The environmental, social, and economic impacts generated by the NTSW are assessed. This includes an analysis of factors such as carbon emissions, water usage, land use, ecosystem impacts, human health effects, and economic costs. By conducting a comprehensive analysis of the Santa Catarina NTSW, the document aims to provide insights into the environmental performance and sustainability of the system. This information can then be used as a tool and experience of educational innovation for final-year undergraduate students to identify areas for improvement, develop mitigation strategies in the water sector, and inform decision-making processes regarding wastewater treatment technologies in Macaronesia. Furthermore, lessons learned from real case studies in the Canary Islands and Cape Verde can be applied to similar regions within the Macaronesia archipelago (IDIWATER project).

Inventory and geomorphological analysis of karstic collapse dolines in Sahel-Doukkala (Morocco)

Inventory and geomorphological analysis of karstic collapse dolines in Sahel-Doukkala (Morocco)

Zero-inflated multivariate tobit regression modeling

A frequent challenge encountered in real-world applications is data having a high proportion of zeros. Focusing on ecological abundance data, much attention has been given to zero-inflated count data. Models for non-negative continuous abundance data with an excess of zeros are rarely discussed. Work presented here considers the creation of a point mass at zero through a left-censoring approach or through a hurdle approach. We incorporate both mechanisms to capture the analog of zero-inflation for count data. Additionally, primary attention has been given to univariate zero-inflated modeling (e.g., single species), whereas data often arise jointly (e.g., a collection of species). With multivariate abundance data, a key issue is to capture dependence among the species at a site, both in terms of positive abundance as well as absence. Therefore, our contribution is a model for multivariate zero-inflated continuous data that are non-negative. Working in a Bayesian framework, we discuss the issue of separating the two sources of zeros and offer model comparison metrics for multivariate zero-inflated data. In an application, we model the total biomass for five tree species obtained from plots established in the Forest Inventory Analysis database in the Northeast region of the United States.

Analisis Persediaan Bahan Baku Susu pada Produksi Keju British Cheddar dengan Metode Economic Order Quantity ( EOQ ) di PT. Mazaraat Lokanatura Indonesia Pasuruan

To achieve profit, companies usually process raw materials into finished or semi-finished goods. Therefore, in this company, controlling and managing raw materials becomes an important factor influencing the smooth production process to achieve desired goals. Cow's milk is one of the popular agricultural products, and cheese is a dairy product consumed globally. PT Mazaraat Lokanatura Indonesia is a company that produces local Yogyakarta cheese and creamery products. The instability of organic milk quality from local farmers often negatively impacts the production process and the final quality of the company's British Cheddar Cheese products. This instability also affects raw material inventory planning, so the company must be more careful in maintaining the quality and quantity of organic milk stock to ensure optimal production. To address this issue, an analysis of raw milk inventory using the Economic Order Quantity (EOQ) method was conducted. This research began with observations and identification of problems related to raw material inventory management that could affect production efficiency and operational costs. Then, data collection was conducted regarding the demand amount, order time, ordering cost, and milk storage cost. The research results show that the application of EOQ is proven effective in optimizing inventory costs. Using EOQ allows the company to manage the optimal order quantity, significantly reducing total ordering costs by decreasing the order frequency.