Ranking Of Sites Research Articles

Gridlock in compromise, or is multi-objective optimisation possible in renewable energy planning? A stakeholder analysis using scenario-MCDA

ABSTRACT The energy and climate crises are driving renewable energy, but it is currently facing obstacles in leading countries. Balancing environmental, social and economic interests has become complex at the regional level due to spatial trade-offs in a contested space. To investigate stakeholder willingness to compromise on a joint ranking on wind and solar energy sites, multi-criteria decision analysis (MCDA) planning support was explored. Using a two-part stakeholder survey, four groups were identified: ‘advocates’ who were satisfied with the site ranking (66%), ‘realists’ who were willing to compromise despite previous disagreement (13%), ‘dissenters’ not accepting (35%), and ‘dogmatists’ not engaging. Planning decisions and stakeholder engagement are underpinned by distinct attitudes towards the role of (democratic) planning and sustainable development. The use of trade-off analysis can ensure transparency and trace back stakeholder interests in making planning decisions. However, decision quality factors also need to be considered to ensure a thorough planning reflection.

Hazardous materials facility siting optimization and ranking: A transportation risk mitigation framework

Hazardous material transportation problems have widely been studied in the past especially in the context of routing, scheduling, and network design problems. Yet, the combined hazardous material facility location-routing problem has not been studied adequately. We emphasize that locating a hazardous material facility is a rich process, and a good site can mitigate the potential transportation risk beforehand. A methodological framework is proposed which allows evaluation and ranking of potential sites based on hierarchical relationship utilities. The proposed method attempts to improve the risk functions and applies a stochastic analysis to measure the risk, which relaxes some assumptions in deterministic analysis, and is more realistic while avoiding overestimation of the risk. The study covers multi-objective optimization considering the decision-makers’ preferences on network segments and risk to the population and water bodies. Potential hazardous material facility sites’ rank is determined by the probability of optimality and one-to-one relationship utilities with the points of interests. Results show that the proposed stochastic analysis offers more flexibility to select and rank the potential sites.

Impacts of Proximity to Primary Source Areas on Concentrations of POPs at Global Sampling Stations Estimated from Land Cover Information.

Given the considerable financial and logistical resources supporting long-term monitoring for air pollutants, and the use of these data for performance evaluation of mitigation measures, it is important to account for contributions from primary versus secondary sources. We demonstrate a simple approach for using open source Global land cover raster data from the National Mapping Organization from the Geospatial Information Authority of Japan to assess local source inputs for air measurements of legacy persistent organic pollutants (POPs)-polychlorinated biphenyls (PCBs) and organochlorine pesticides-reported under the Global atmospheric passive sampling (GAPS) Network at 119 locations for the time period 2005-2014. The land cover composition within a 10 km radius around the GAPS sites was identified to create source impact indicator (SII) vectors to quantify and rank the remoteness of the sites from human infrastructure. Using principal component analysis, three SII vectors were established to rank sites by impact of (i) general infrastructure/remoteness, (ii) urban infrastructure, and (iii) agricultural infrastructure. General infrastructure describes the combined effects of settlements and agricultural infrastructure. We found significant correlations (p < 0.05) between POP concentrations in air and specific SIIs. PCB levels in air had a statistically significant correlation to the SII ranking urban impacts around the sampling sites, while Endosulfan I, Endosulfan II, and Endosulfan sulfate had a statistically significant correlation with SII ranking agricultural impacts. The complete GAPS data set from 2004-2014 (1040 samples at 119 locations) was standardized based on the SII rankings to assess the global temporal trends of legacy POPs. SIIs were incorporated in the multiple regression analysis to determine global halving times. This includes short-term monitoring data from 79 locations that were previously excluded. Furthermore, the SII approach allows the integration of global monitoring data from different studies for broader global temporal trend analysis. This ability to link the results of independent and small-scale studies can enhance temporal trend analysis in support of the larger scale initiatives, such as inter alia, the Global Monitoring Plan and Effectiveness Evaluation of the Stockholm Convention in the case of POPs. This simple approach using open source data has a broad potential for application for other classes of air pollutants.

Evaluating the performance of turbulence closure models for tidal stream resource characterization

Harvesting tidal stream energy from the ocean for electricity generation has been considered as an energy resource alternative to fossil fuels for mitigating the negative impact of climate change and enhancing energy security and coastal resilience. Numerical models have been used extensively to characterize and assess tidal resources at potential tidal energy development sites. Turbulence plays an important role in site selection and tidal turbine farm deployment. However, most of the numerical modeling studies for tidal energy resource characterization do not include turbulence characteristics because of the limitation of Reynolds averaged Navier–Stokes coastal ocean model in resolving the inertial sub-range turbulence scales. However, studies also demonstrated that turbulence properties, such as turbulence intensity and turbulence kinetic energy, simulated by the coastal ocean models based on turbulence closures can be useful in assisting tidal resource characterization at tidal energy sites. In this study, we evaluated four General Ocean Turbulence Model (GOTM) turbulence closure models implemented in a tidal hydrodynamic model –Finite Volume Community Ocean Model (FVCOM) to characterize the tidal energy resource in the Western Passage, Maine, USA – a top ranked tidal energy site. The four turbulence closure models used in this analysis are k–kl (Mellor–Yamada Level 2.5), k-ε, k–ω, and a generic model. Model sensitivities showed that the MY2.5 model performed the best in comparison with the field measurements. In particular, the simulated time series of turbulence intensity and kinetic energy matched the observed data very well in the Western Passage. Detailed analysis was conducted to characterize turbulence properties on the horizontal plane and at selective cross-sections. This study demonstrated that turbulence properties simulated by a coastal ocean model, along with tidal hydrodynamic properties, can be very informative for tidal energy resource characterization and project site selection, as recommended by the International Electrotechnical Commission (IEC) technical specifications (IEC TS 62600-201).

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Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the “FluidFlower”), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.

Selection Frameworks for Potential Rainwater Harvesting Sites in Arid and Semi-Arid Regions: A Systematic Literature Review

Water shortage is a concern in arid and semi-arid regions across the globe due to their lack of precipitation and unpredictable rainfall patterns. In the past few decades, many frameworks, each with their own criteria, have been used to identify and rank sites for rainwater harvesting (RWH), a process which is critical for the improvement and maintenance of water resources, particularly in arid and semi-arid regions. This study reviews the present state of the art in rainwater harvesting site selection for such regions and identifies areas for additional research. The results of a systematic review performed based on two major databases of engineering research, Scopus and Engineering Village, are presented. Sixty-eight relevant studies were found and critically analysed to identify patterns and unique features in the frameworks used. The results of this study show that 41% of the frameworks consider both biophysical and socioeconomic criteria, whereas the remaining 59% of the frameworks depend on biophysical criteria alone. The importance of each criterion is encapsulated through a suitability score, with 21% of the frameworks using a binary (0 or 1) indicator of whether the site matches a criterion or not and the other frameworks using graded scales of differing granularities, with 52% using a low-resolution scale of 1 to 3, 4, or 5, 7% using a medium-resolution scale of 1 to 10, and a further 7% using a high-resolution scale of 1 to 100. The remaining 13% of the frameworks did not specify the scale used. Importantly, this paper concludes that all existing frameworks for selecting RWH sites are solely based on biophysical and/or socioeconomic criteria; ecological impacts, the consideration of which is vital for building RWH systems sustainably, are currently ignored.

A design-support framework to assess urban green spaces for human wellbeing

Rapid and high-density urban development has led to limited Urban Green Space (UGS), which is crucial for human wellbeing and sustainable urban development. To avoid compromising human wellbeing while promoting environmental sustainability, we propose a novel research framework that quantifies the importance of each UGS on-site for human wellbeing, to support multi-objective UGS design. This paper presents a framework for spatial parameterised evaluation of human wellbeing based on accessibility and usability. The evaluation considers connectivity and walking distance for accessibility, and space enclosure and availability for usability. The proposed thresholds and weights can be adjusted to fit different study contexts and reflect various needs. The use case demonstrated that the framework allows for ranking of UGS sites facilitating integration of human needs and other sustainable environmental needs into a multi-objective UGS design workflow. This approach provides designers with evidence to accurately allocate UGS resources according to human needs on each UGS and space conditions of UGS. It also presents an opportunity to integrate with other quantified analyses for sustainable urban development. The framework provides a useful approach to promoting human wellbeing by identifying the most important UGS for safeguarding human needs.

Competition and site weakly explain tree growth variability in undisturbed Central African moist forests

Abstract Identifying and quantifying factors that influence tree growth are crucial issues to ensure sustainable forest management, particularly in moist tropical forests. Tree growth depends on several factors comprising ontogenic stage, competition by neighbours and environmental conditions. Several studies have focused on one or two of them, but very few have considered all three, especially in Central Africa. We investigated the effects of diameter and competition on tree growth, in four Central African sites characterized by their soil physicochemical properties, at both tree community and population levels. We calibrated growth models using diameter data collected on 29,741 trees between 2015 and 2018, on twelve 4 or 9‐ha plots spread over the four sites. These models included diameter, wood density, competition indices and site effect as explainable variables at the community level and excluded wood density at the population level. At the community level, the best models explained 11% of growth variability with a decreasing effect of species wood density, diameter, site and competition. Our results show that even if low, site effect can result from different soil nutrients depending on both tree size and species wood density. We observed higher tree growth on sites with (i) high exchangeable K, organic C, total N and total P for low wood density species; (ii) high available P and C:N for small trees, high exchangeable Ca and Mg for medium to large trees, all belonging to medium and hard wood density species. At the population level, the best models explained between 0 to 43% of growth variability, with significant competition effect (resp. site effect) for 21 (resp. 9) of the 43 species studied. Site ranking varied greatly between the 9 species concerned, probably reflecting different sensitivities to the scarcity of particular soil nutrients. Synthesis. Our study provides original results on the factors influencing tree growth in Central Africa, showing that the potential effect of soil nutrients depends on tree size and species wood density. Remaining highly unpredictable at the population level, this effect makes it essential to increase the number of dynamics monitoring systems in logging concessions.

INCREASE WEBSITE VISIBILITY ON THE INTERNET BY GOOGLE SEARCH CONSOLE

The article "Increase Website Visibility On The Internet By Google Search Console" is devoted to the consideration of the importance and use of Google Search Console for website optimisation and improvement of its visibility in search engines. The article discusses the main aspects of search engine optimisation, as well as the role of Google Search Console as a powerful tool for analysing, monitoring and improving SEO strategy. The article describes methods of integrating Google Search Console with Google Analytics to obtain more detailed information about traffic, keywords, CTR and other important metrics. The article emphasises that using Google Search Console allows you to identify technical issues, analyse content, monitor website health, and perform competitive analysis to achieve better results in search results. Thanks to these insights, website owners and marketers can develop an effective strategy to increase the visibility of their site and attract a larger audience of users. Website indexing is an important part of the search engine optimisation process and is essential for increasing the visibility and accessibility of a website on the Internet. Indexing allows search engines such as Google, Bing, Yahoo, and others to find, analyse, and index the pages of a website. This allows search engines to include the site in their search results, which ensures its visibility to potential visitors. Indexing can help you drive more organic traffic to your website. When pages of a website are indexed, they can appear in search results when users make relevant requests. This opens up the possibility of attracting new visitors who are looking for relevant information or products and services. Indexing allows search engines to analyse website content, including keywords, meta tags, URLs, and other elements. This is important for SEO because this data affects the ranking of a website in search results. The better a website is indexed, the more chances it has to reach the top positions in search results and attract the target audience. During indexing, search engines can detect technical issues such as page errors, broken links, or duplicate content. This allows you to quickly identify and fix issues that could negatively affect your site's visibility and rankings. Using tools such as Google Search Console, you can track and analyse your site's indexing data. You can see which pages are being indexed, which get the most traffic, which keywords attract the attention of search engines, and much more. This information helps you understand how your site performs in search engines and how you can improve its visibility.

Was coal metamorphism an influence on the minor element chemistry of the Middle Pennsylvanian Springfield (No. 9) coal in Western Kentucky?

Coal rank in the Middle Pennsylvanian Carbondale Formation Springfield coal in the Western Kentucky coalfield, part of the Illinois Basin, ranges from high volatile A bituminous in southern Union and Webster counties to high volatile C bituminous in the rest of the region. The chlorine content closely follows the coal rank, being highest in the high volatile A bituminous coals. High concentrations of V and Cr are evident in the top benches at all sites and is particularly strong in the higher rank sites. Zinc and other elements (Ni, Mo, among others) are enriched in some benches, but the trend is not as consistent as with V and Cr. Zirconium (+ Nb) and TiO2, both serving as proxies for a detrital influx, show differentiation among the quadrangles, with the high volatile C bituminous Spottsville quadrangle coals having the highest Zr + Nb content. The correlation between Y and Zr indicates that the highest Y occurs in the Spottsville samples. The Spottsville samples have highest REE. Principal components analysis using both a rank parameter (vitrinite maximum reflectance) and the set of geochemical parameters showed that the coal rank axis (Rmax) (with the highest rank being in the Providence quadrangle) is orthogonal to the overlapping LREE/HREE and GdN/GdN* axes and is opposite to the REE, Zr + Nb, and Zn axes. Hydrothermal metamorphism certainly influenced coal rank, the chlorine content of the coals, and, perhaps, some aspects of the minor element chemistry. Coal metamorphism, however, was not the sole influence and not even the dominant influence on the concentration of REE in the Springfield coal in western Kentucky since other factors, such as the greater concentrations of detrital minerals in the Spottsville quadrangle samples, seem to have had a greater influence on the REE chemistry.

Integrative biomarker response - Threshold (IBR-T): Refinement of IBRv2 to consider the reference and threshold values of biomarkers

The Integrated Biomarker Response (IBR) is one of the most used index in biomonitoring, especially the IBRv2 integrating a reference condition. However, some limitations remain for its routine and large-scale use. The IBRv2 is proportional to the total number of biomarkers, is dependent on the nature of biomarkers and considers all biomarkers modulations, even small and biologically non-significant. In addition, IBRv2 relies on reference values but the references are often different between each study, making it difficult to compare results between studies and/or campaigns. To overcome these limitations, the present work proposed a new index called IBR-T (“Integrated Biomarker Response – Threshold”) which considers the threshold values of biomarkers by limiting the calculation of the IBR value to biomarkers with significant modulations. The IBRv2 and the IBR-T were calculated and compared on four datasets from active biomonitoring campaigns using Dreissena polymorpha, a bivalve widely used in freshwater biomonitoring studies. The comparison between indices has demonstrated that the IBR-T presents a better correlation (0.907 < r2 < 0.998) with the percentage of biomarkers significantly modulated than the IBRv2 (0.002 < r2 < 0.759). The IBRv2 could not be equal to 0 (0.915 < intercept <1.694) because the value was dependent on the total number of biomarkers, whereas the IBR-T reached 0 when no biomarker was significantly modulated, which appears more biologically relevant. The final ranking of sites was different between the two index and the IBR-T ranking tends to be more ecologically relevant that the IBRv2 ranking. This IBR-T have shown an undeniable interest for biomonitoring and could be used by environmental managers to simplify the interpretation of large datasets, directly interpret the contamination status of the site, use it to decision-making, and finally to easily communicate the results of biomonitoring studies to the general public.

DETERMINING THE OPTIMAL SETTLEMENT LOCATING OF ANCIENT SITES USING TOPSIS MULTI-CRITERIA DECISION MODEL: A CASE STUDY: ESTABLISHMENTS IN MOUNTAINOUS AREAS OF NORTH KHORASAN, NORTHEAST IRAN

Human settlements emerged based on natural factors such as adequate water resources and suitable and fertile soil. Other factors such as altitude, slope, and slope direction, the distance to permanent water sources, and communication paths are natural substrates that affect the distribution of human settlements, some of which have a more influential role in the formation and survival of life. This study aims to investigate the status of the Iron Age settlement in the Atrak River Basin. To achieve the objectives of the research and hierarchical analysis of Iron Age sites, seven natural variables, including altitude, slope, slope direction, landing, soil type, distance to rivers, and communication routes that have been effective in establishing settlements, have been selected and by using the statistical methods in the GIS, the TOPSIS hierarchical analysis process, and Excel, and they finally been studied. In terms of statistical analysis, the distance from river, Landuse and the distance to communication routes have been assigned the most ideal values. The slope degree, above sea level and Slope Direction have the lowest ideal value, respectively. Based on this, the IAMA60 site ranked first, the IAMA49 site ranked second, and the IAMA18 site ranked third in terms of natural indicators. In the lowest rank, IAMA25, IAMA35, and IAMA56 sites are located. In addition to these, the rest of the sites are considered relatively privileged areas.

Turbulence modeling to aid tidal energy resource characterization in the Western Passage, Maine, USA

Numerical models combined with field measurements are regularly used to characterize tidal energy resources at potential energetic sites. However, most existing works only focus on the tidal hydrodynamic characteristics, and turbulence parameters are often not reported because of the lack of high-quality turbulence measurements and the limitations of numerical models in resolving turbulent eddies. In this study, we used FVCOM – a hydrostatic primitive equation (HPE) model – to characterize the tidal energy resource in the Western Passage, Maine, USA, by taking care of the essential macro-scale turbulence properties. We observed an excellent model performance using the Mellor–Yamada Level 2.5 Turbulence Model; estimating the spatial and vertical distribution of the turbulent kinetic energy and intensity added a new perspective to the site ranking for tidal energy converter (TEC) deployments. In addition, we also examined the role of channel geometry and bathymetry, such as headlands and underwater sills, in enhancing turbulent eddies around potential TEC siting locations. Ultimately, the detailed analysis of the turbulent flow characteristics has changed the site-ranking results and demonstrated that the regional-scale HPE models could be used for the relative understanding of more or less turbulent sites for a refined resource assessment.

Accurate prediction of pan-cancer types using machine learning with minimal number of DNA methylation sites.

DNA methylation analysis has been applied to determine the primary site of cancer; however, robust and accurate prediction of cancer types with a minimum number of sites is still a significant scientific challenge. To build an accurate and robust cancer type prediction tool with a minimum number of DNA methylation sites, we internally benchmarked different DNA methylation site selection and ranking procedures, as well as different classification models. We used The Cancer Genome Atlas dataset (26 cancer types with 8296 samples) to train and test models and used an independent dataset (17 cancer types with 2738 samples) for model validation. A deep neural network model using a combined feature selection procedure (named MethyDeep) can predict 26 cancer types using 30 methylation sites with superior performance compared with the known methods for both primary and metastatic cancers in independent validation datasets. In conclusion, MethyDeep is an accurate and robust cancer type predictor with the minimum number of DNA methylation sites; it could help the cost-effective clarification of cancer of unknown primary patients and the liquid biopsy-based early screening of cancers.

The strength of Backlinks: How They Influence SEO and Improve Your internet site's Ranking

The strength of Backlinks: How They Influence SEO and Improve Your internet site's Ranking

Sanitary landfill site selection using GIS-based on a fuzzy multi-criteria evaluation technique: a case study of the City of Kraljevo, Serbia.

Adequate disposal of municipal solid waste (MSW) is one of Serbia's most complex environmental challenges. The problem is more serious in urban areas, since large amounts of waste are disposed of in locations that do not comply with environmental, technical, and socio-economic standards. Such is the case for the city of Kraljevo, where about 116,000 inhabitants do not have a sanitary landfill facility. This research includes a multi-criteria analysis, conducted with the help of geographic information systems, to find a suitable landfill site location. After data collection, the first step was to process 15 environmental and socio-economic factors utilizing the fuzzy analytic-hierarchy process method. The second step comprised the visual analysis and selection of the ten most suitable locations from the synthetic convenience map. The third step involved the final ranking of sites by means of the fuzzy multi-objective analysis by ratio, plus the full multiplicative form method, based on four additional beneficial and non-beneficial criteria. The results show that sanitary landfill candidate site A4 is the most suitable location for constructing a sanitary landfill site due to its large area (569ha) and relatively short distance from the urban zone (8km). This study is the first to integrate geographic information systems and the fuzzy analytic-hierarchy process, multi-objective analysis by ratio, and the full multiplicative form algorithm for sanitary landfill selection. The results of the research can be used as a reference for safe waste disposal in the city of Kraljevo.

Toxicity prediction: An application of alternative testing and computational toxicology in contaminated groundwater sites in Taiwan

Groundwater contamination remains a global threat due to its toxic effects to humans and the environment. The remediation of contaminated groundwater sites can be costly, thus, identifying the priority areas of concern is important to reduce money spent on resources. In this study, we aimed to identify and rank the priority groundwater sites in a contaminated petrochemical district by combining alternative, non-animal approaches – chemical analysis, cell-based high throughput screening (HTS), and Toxicological Priority Index (ToxPi) computational toxicology tool. Groundwater samples collected from ten different sites in a contaminated district showed pollutant levels below the detection limit, however, hepatotoxic bioactivity was demonstrated in human hepatoma HepaRG cells. Integrating the pollutants information (i.e., pollutant characteristics and concentration data) with the bioactivity data of the groundwater samples, an evidence-based ranking of the groundwater sites for future remediation was established using ToxPi analysis. The currently presented combinatorial approach of screening groundwater sites for remediation purposes can further be refined by including relevant parameters, which can boost the utility of this approach for groundwater screening and future remediation.

Adaptability responses to drought stress in the oak species Quercus petraea growing on dry sites

We studied sessile oak (Quercus petraea) growing on six dry sites to understand adaptability responses to drought stress. Pedunculate oak (Quercus robur) on a moderately dry site was tested in parallel. We analyzed accessions from mostly dry sites that were less sensitive to soil drought and found that the growth performance ranking was not the same before and after treatment. We used phenological plasticity approaches to study seed development and plant development before and after drought: the treatments included stem length, root length, and collar diameter, as well as dry above- and below-ground biomass performance. Additionally, after drought treatment, osmolytes and root surface were tested in Q. petraea. According to the analyses and results, the ranked sites did not maintain their ranking status, with Q. petraea exhibiting different rates of growth during each developmental stage from seed development until the end of the treatment of plant material. The smallest seeds came from the driest site, which may indicate more adaptability to drought stress. After drought treatment, large differences were found between the dry biomass performance, stem length, root length, and collar diameter of oaks grown on different sites. The osmolality of Q. petraea on most of the dry sites was higher under the reduced treatment than under the optimal treatment, but not significantly. After drought treatment, all accessions – and especially those from the driest site – showed large differences in growth performance between the treatments. The relationship between seed weight and seedling development before and after drought treatment differed according to the developmental stage.

Tabloidization in Philippine Online News Media: A Content Analysis

This study is a content analysis of the implication of tabloidization in the top online news sites of the Philippines: Philippine Daily Inquirer (PDI), Manila Bulletin (MB), and Philippine Star (PS). It sought to: determine the amount of tabloidization concepts observed in the three online news sites; and ascertain whether the amount of tabloidization has a significant association with the ranking of the online news sites. It made use of a correlational descriptive research design to acquire data regarding the current status of the phenomenon which is about the infiltration of tabloidization in news media. Also, it is anchored upon the Uses and Dependency theory and Media Dependency theory. Moreover, the study employed quantitative content analysis and purposive sampling method. The findings of the study show that the ranking of the amount of tabloidization concepts is true for all online news sites, with individualism as the highest, followed by drama, entertainment, and political concepts. Moreover, the PDI is found to be the most sensationalized among the three online news sites, followed by PS and MB. Finally, there is an association of the amount of tabloidization to the ranking of the online news sites. With these findings, it is concluded that the use of tabloidization in news media could be a strategy to gain a huge lead in readership and eventually attain the widest market possible.

Assessment of wind-to-hydrogen (Wind-H2) generation prospects in the Sultanate of Oman

Economic feasibility is one of the essential factors for choosing a project to launch. Hence, this study focused on assessing the economic viability of hydrogen generation using wind energy in the Sultanate of Oman. On this subject, wind energy potential for the selected sites was first investigated. Followed by Levelized Cost of Energy (LCOE), hydrogen production, the energy efficiency of hydrogen generation, and the Levelized Cost of Hydrogen (LCOH) production were examined. Two key factors, wind turbine power curve adjustment and turbine performance degradation during the project lifetime, were incorporated in the wind energy assessment, hydrogen production, and their costs for a site. This study has considered 18 locations throughout the country to evaluate hydrogen generation and the cost. The LCOE was found to be 0.0349–0.0701 USD/kWh without degradation and 0.0398–0.0801 USD/kWh with degradation. It also discovered the rank of the potential sites based on the merit order of hydrogen production. It showed that Masirah and Thumrait were the most suitable sites, whereas Sur was the least qualified. The LCOH for the most appropriate place, Masirah, is 3.37 USD/kg. The LCOH in Sur, a least suitable site, was found to be 6.15 USD/kg. Finally, a sensitivity analysis was done to identify the factors that significantly alter green hydrogen production costs in Omani conditions. The outcomes reveal that Wind-H2 production has significant potential with a cost-effective levelized cost in the Sultanate of Oman.